Publications

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With low-cost and simple processing, organic electrochromic polymers have attracted considerable attention as a promising material platform for flexible and low-energy-consuming optoelectronic devices. However, typical electrochromic polymers can only be switched from natural-colored to oxidized-transparent states. As a result, the complexity of combining several distinct polymers to achieve a full-color gamut has significantly limited the niche applications of electrochromic polymers. Here in this paper we report an electrochromic polymer based on 4,7-di((3,3-dimethyl-3,4-dihydro-2H-thieno[3,4-b][1,4]dioxepine-3-yl)-3,4-ethylenedioxythiophene) (PEP), which exhibits fast full-color reversible tuning capability and good stability. Furthermore, a red-green-blue flexible electrochromic device just based on poly(PEP) was fabricated, which offers an effective approach to dynamically manipulate color and enables a variety of optoelectronic applications.

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This acceptable knowledge(AK)Summary Report has been prepared for the Central Characterization Program (CCP) for remote-handled (RH) transuranic (TRU) waste generated and managed by Sandia National Laboratories/New Mexico (SNL/NM) in Albuquerque, New Mexico. The waste described in this report was predominately generated in the SNL/NM Hot Cell Facility (HCF) during the removal and packaging of experimental material and decontamination operations in Building 6580 at Technical Area (TA)-V.

Metallic particles formed in oxide fuels (e.g., UO2) during neutron irradiation have an adverse impact on fuel performance. A fundamental investigation of particle precipitation is needed to predict the fuel performance and potentially improve fuel designs and operations. This study reports on the precipitation of Mo-dominant β-phase particles in polycrystalline CeO2 (surrogate for UO2) films doped with Mo, Pd, Rh, Ru, and Re (surrogate for Tc). In situ heating scanning transmission electron microscopy indicates that particle precipitation starts at ∼1073 K with a limited particle growth to ∼10 nm. While particle concentration increases with increasing temperature, particle size remains largely unchanged up to 1273 K. There is a dramatic change in the microstructure following vacuum annealing at 1373 K, probably due to phase transition of reduced cerium oxide. At the high temperature, particles grow up to 75 nm or larger with distinctive facets. The particles are predominantly composed of Mo with a body-centered cubic structure (β phase). An oxide layer was observed after storage at ambient conditions. In situ heating X-ray photoelectron spectroscopy reveals an increasing reduction of Ce charge state from 4+ to 3+ in the doped CeO2 film at temperatures from 673 to 1273 K. In situ ion irradiation transmission electron microscopy with 2 MeV Al2+ ions up to a dose of ∼20 displacements per atom at nominally room temperature does not lead to precipitation of visible particles. However, irradiation with 1.7 MeV Au3+ ions to ∼10 dpa at 973 K produces ∼2 nm sized pure Pd particles; Au3+ irradiation at 1173 K appears to result in precipitates of ∼6 nm in size. Some of the defects produced by ion irradiation could be nucleation sites for precipitation, leading to generation of smaller particles with a higher concentration. ©

Crude oil stored at the U.S. Strategic Petroleum Reserve (SPR) requires mitigation procedures to maintain oil vapor pressure within program delivery standards. Crude oil degasification is one effective method for lowering crude oil vapor pressure, and was implemented at the West Hackberry SPR site from 2014-2018. Performance monitoring during and after degasification revealed a range of outcomes for caverns that had similar inventory and geometry.

Recently developed Distributed Energy Resource (DER) interoperability standards include communication and cyber security requirements. In 2018, the US national interconnection standard, IEEE 1547, was revised to require DER to include a Sun Spec Modbus, IEEE 2030.5 (Smart Energy Profile, SEP 2.0), or IEEE 1815 (DNP3) communication interface but does not include any normative overarching cybersecurity requirements. IEEE 2030.5 and associated implementation requirements for California, known as the California Smart Inverter Profile (CSIP), prescribe the greatest security features - including encryption, authentication, and key management requirements. Sun Spec Modbus and IEEE 1815 security requirements are not as comprehensive, leading to implementation questions throughout the industry. Further, while the security features in IEEE 2030.5 are commonly used in computing platforms, there are still questions of how well the technologies will scale in highly-distributed, computationally-limited inverter environments. In this paper, (a) the elements of IEEE 2030.5 encryption, authentication, and key management guidelines are analyzed, (b) potential scalability gaps are identified, and (c) alternative technologies are explored for possible inclusion in DER interoperability or cyber security standards.

An increasing number of public utility commissions are adopting Distributed Energy Resource (DER) interconnection standards which require photovoltaic (PV) inverters, energy storage systems, and other DER to include interoperable grid-support functionality. The recently updated national standard, IEEE 1547-2018, requires all DER to include a Sun Spec Modbus, IEEE 2030.5, or IEEE 1815 communication interface in order to provide local and bulk power system services. Those communication protocols and associated information models will ensure system interoperability for PV and storage systems, but these new utility-to-DER communication networks must be deployed with sufficient cybersecurity to protect the U.S. power system and other critical infrastructure reliant on dependable power. Unlike bulk generators, DER are commonly connected to grid operators via public internet channels. These DER networks are exposed to a large attack surface that may leverage sophisticated techniques and infrastructure developed on IT systems, including remote exploits and distributed attacks. Although DER make up a growing portion of the national generation mix, they have limited processing capabilities and do not typically support modern security features such as encryption or authentication. In this work, Sandia National Laboratories constructed simulated DER communication net- works with a range of security features in order to study the security posture of different communication approaches. The experimental test environment was created in a Sandia-developed co-simulation platform, called SCEPTRE, which emulated Sun Spec-compliant DER equipment, the utility DER management system, communication network, and distribution power system. Adversary-based assessments were conducted and a quantitative scoring criteria was applied to evaluate the resilience of various architectures against cyber attacks and to measure the systemic impact during such attacks. The team found that network segmentation, encryption, and moving target defense improved the security of these networks and would be recommended for utility, aggregator, and local DER networks.

This is a review of existing microgrid design tool capabilities, such as the Microgrid Design Tool (MDT), LANL PNNL NRECA Optimal Resilience Model (LPNORM), Distributed Energy Resource-Customer Adoption Model (DER-CAM), Renewable Energy Optimization (REopt), and the Hybrid Optimization Model for Multiple Energy Resources (HOMER). Additionally, other simulation and analysis tools which may provide fundamental support will be examined. These will include GridLAB-DTM, OpenDSS, and the hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS). Their applicability to networked microgrid operations will be evaluated, and strengths and gaps of existing tools will be identified. This review will help to determine which elements of the proposed optimal design and operations (OD&D) tool should be formulated from first principles, and which elements should be integrated from past DOE investments.

In November 2016, the High-Energy Radiation Megavolt Electron Source (HERIVIES)-III gamma simulator was used in a series of physics experiments. As part of the environmental characterization, six Spherical Compton Diodes (SCDs) were fielded in order to measure the dose rate at various locations. This report documents the locations, calibration, compensation, and analysis of these sensors. Several short studies are conducted of the SCD signals examining their change with respect to distance, comparison to other sensors and historical data, evaluation of the log-derivative, and signal behavior with a partially obscured converter. Recommendations for future work includes study and extension of SCD bandwidth, characterization of the HERMES-III output spectrum variability, and study of sensor signals with the courtyard shielded from the top of the Magnetically Insulated Transmission Line (MITL).

Neutron dosimetry monitors should be used during all irradiations in the Annular Core Research Reactor. This report provides the recommended conversion factors that should be used to translate the monitor dosimeter read-outs into the damage metrics that are typically used by experimenters to assess the results of their experiment. These conversion factors are based upon the use of the latest least-squares adjusted neutron spectrum determination to describe the Sandia National Laboratories reference neutron fields and the latest International Atomic Energy Agency recommended dosimetry cross sections to capture the response of the dosimeter. The resulting conversion factors are built into the dosimetry results routinely provided by the Radiation Metrology Laboratory.

Molecular dynamics simulations were employed to simulate the mechanical response and grain evolution in a Ni nanowire for both static and cyclic loading conditions at both 300 and 500 K for periods of 40 ns. The loading conditions included thermal annealing with no deformation, constant 1% extension (creep loading) and cyclic loading with strain amplitudes of 0.5% and 1% for 200 cycles. Under cyclic loading, the stress-strain response showed permanent deformation and cyclic hardening behavior. At 300 K, modest grain evolution was observed at all conditions within the 40 ns simulations. At 500 K, substantial grain growth is observed in all cases, but is most pronounced under cyclic loading. This may result mechanistically from a net motion of the boundaries associated with boundary ratcheting. There is a striking qualitative consistency between the present simulation results and the experimental observation of abnormal grain growth in nanocrystalline metals as a precursor to fatigue crack initiation.

In January 2019, the U.S. Department of Energy, Office of Science program in Advanced Scientific Computing Research, convened a workshop to identify priority research directions for in situ data management (ISDM). The workshop defined ISDM as the practices, capabilities, and procedures to control the organization of data and enable the coordination and communication among heterogeneous tasks, executing simultaneously in a high-performance computing system, cooperating toward a common objective. The workshop revealed two primary, interdependent motivations for processing and managing data in situ. The first motivation is that the in situ methodology enables scientific discovery from a broad range of data sources over a wide scale of computing platforms: leadership-class systems, clusters, clouds, workstations, and embedded devices at the edge. The successful development of ISDM capabilities will benefit real-time decision-making, design optimization, and data-driven scientific discovery. The second motivation is the need to decrease data volumes. ISDM can make critical contributions to managing large data volumes from computations and experiments to minimize data movement, save storage space, and boost resource efficiency, often while simultaneously increasing scientific precision.

Nanoparticles; Supramolecular Chemistry; Materials Science Nanoparticles (NPs)of controlled size, shape, and composition are important building blocks for the next generation of devices. There are numerous recent examples of organizing uniformly sized NPs into ordered arrays or superstructures in processes such as solvent evaporation, heterogeneous solution assembly, Langmuir-Blodgett receptor-ligand interactions, and layer-by-layer assembly. This review summarizes recent progress in the development of surfactant-assisted cooperative self-assembly method using amphiphilic surfactants and NPs to synthesize new classes of highly ordered active nanostructures. Driven by cooperative interparticle interactions, surfactant-assisted NP nucleation and growth results in optically and electrically active nanomaterials with hierarchical structure and function. How the approach works with nanoscale materials of different dimensions into active nanostructures is discussed in details. Some applications of these self-assembled nanostructures in the areas of nanoelectronics, photocatalysis, and biomedicine are highlighted. Finally, we conclude with the current research progress and perspectives on the challenges and some future directions.

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Scour beneath seafloor pipelines, cables, and other offshore infrastructure is a well-known problem. Recent interest in seafloor mounted wave energy converters brings another dynamic element into the traditional seafloor scour problem. In this paper, we consider the M3 Wave APEX device, which utilizes airflow between two flexible chambers to generate electricity from waves. In an initial at-sea deployment of a demonstration/experimental APEX in September 2014 off the coast of Oregon, scour beneath the device was observed. As sediment from the beneath the device was removed by scour, the device's pitch orientation was shifted. This change in pitch orientation caused a degradation in power performance. Characterizing the scour associated with seafloor mounted wave energy conversion devices such as the M3 device is the objective of the present work.

Snippet is a collaborative source code auditing tool developed by Sandia National Laboratories, in conjunction with researchers from other government agencies and partners. As a tool for use by groups of auditors, Snippet showed the value of providing in-line annotations that captured the thoughts of auditors in such a way that teams of auditors could share their insights. Snippet users found that the annotation mechanisms improved the auditing process but were frustrated at having to learn another environment. To address this issue, collaborators made extensions to existing Integrated Development Environments (IDEs) to incorporate functionality that mimics Snippet's behaviors. This document is one of a pair of documents. The other document, "Snippet Open-Source Specification", goes into details about the history and reasoning behind the requirements made in this document. That document provides for a broader understanding of the motivations backing this document. This document provides the complete specification for collaborative annotation, and a characterization of each specification as required or recommended. Tools that implement these specifications will be considered Snippet compliant. The intent is that complete implementation of these specifications will enable seamless sharing of annotation information between disjoint tools.

Snippet is a collaborative software code auditing tool developed at Sandia National Laboratories (Sandia) in conjunction with several sponsoring government agencies to enable software analysts, individually or in groups, to non-destructively audit large codebases, share files and comments from those audits, and develop Snippet plugins for use with other text editing software applications. This specification defines the requirements and the reasoning behind the requirements for tools developed to be compatible with the technology and purpose of Snippet. A condensation of the requirements is given in the companion document, "Snippet Open-Source Specification Synopsis" also generated by Sandia National Laboratories. Snippet's approach to browsing through codebases is similar to a web browser navigating the internet.

We describe and evaluate version 2.1 of the Community Ice Sheet Model (CISM). CISM is a parallel, 3-D thermomechanical model, written mainly in Fortran, that solves equations for the momentum balance and the thickness and temperature evolution of ice sheets. CISM's velocity solver incorporates a hierarchy of Stokes flow approximations, including shallow-shelf, depth-integrated higher order, and 3-D higher order. CISM also includes a suite of test cases, links to third-party solver libraries, and parameterizations of physical processes such as basal sliding, iceberg calving, and sub-ice-shelf melting. The model has been verified for standard test problems, including the Ice Sheet Model Intercomparison Project for Higher-Order Models (ISMIP-HOM) experiments, and has participated in the initMIP-Greenland initialization experiment. In multimillennial simulations with modern climate forcing on a 4 km grid, CISM reaches a steady state that is broadly consistent with observed flow patterns of the Greenland ice sheet. CISM has been integrated into version 2.0 of the Community Earth System Model, where it is being used for Greenland simulations under past, present, and future climates. The code is open-source with extensive documentation and remains under active development.

Voltage-controlled room temperature isothermal reversible spin crossover switching of [Fe{H 2 B(pz) 2 } 2 (bipy)] thin films is demonstrated. This isothermal switching is evident in thin film bilayer structures where the molecular spin crossover film is adjacent to a molecular ferroelectric. The adjacent molecular ferroelectric, either polyvinylidene fluoride hexafluoropropylene or croconic acid (C 5 H 2 O 5 ), appears to lock the spin crossover [Fe{H 2 B(pz) 2 } 2 (bipy)] molecular complex largely in the low or high spin state depending on the direction of ferroelectric polarization. In both a planar two terminal diode structure and a transistor structure, the voltage controlled isothermal reversible spin crossover switching of [Fe{H 2 B(pz) 2 } 2 (bipy)] is accompanied by a resistance change and is seen to be nonvolatile, i.e., retained in the absence of an applied electric field. The result appears general, as the voltage controlled nonvolatile switching can be made to work with two different molecular ferroelectrics: croconic acid and polyvinylidene fluoride hexafluoropropylene.

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The synthesis of materials that can mimic the mechanical, and ultimately functional, properties of biological cells can broadly impact the development of biomimetic materials, as well as engineered tissues and therapeutics. Yet, it is challenging to synthesize, for example, microparticles that share both the anisotropic shapes and the elastic properties of living cells. Here in paper, a cell-directed route to replicate cellular structures into synthetic hydrogels such as polyethylene glycol (PEG) is described. First, the internal and external surfaces of chemically fixed cells are replicated in a conformal layer of silica using a sol–gel process. The template is subsequently removed to render shape-preserved, mesoporous silica replicas. Infiltration and cross-linking of PEG precursors and dissolution of the silica result in a soft hydrogel replica of the cellular template as demonstrated using erythrocytes, HeLa, and neuronal cultured cells. The elastic modulus can be tuned over an order of magnitude (≈10–100 kPa) though with a high degree of variability. Furthermore, synthesis without removing the biotemplate results in stimuli-responsive particles that swell/deswell in response to environmental cues. Overall, this work provides a foundation to develop soft particles with nearly limitless architectural complexity derived from dynamic biological templates.

Existing approaches to evaluating cyber risk are summarized and explored for their applicability to critical infrastructure. The approaches cluster in three different spaces: network security, cyber-physical, and mission assurance. In all approaches, some form of modeling is utilized at varying levels of detail, while the ability to understand consequence varies, as do interpretations of risk. A hybrid approach can account for cyber risk in critical infrastructure and allow for allocation of limited resources across the entirety of the risk spectrum.

When the core is breached during a severe nuclear accident, a molten mixture of nuclear fuel, cladding, and structural supports is discharged from the reactor vessel. This molten mixture of ceramic and metal is often referred to as “corium”. Predicting the flow and solidification of corium poses challenges for numerical models due to the presence of large Peclet numbers when convective transport dominates the physics. Here, we utilize a control volume finite-element method (CVEM) discretization to stabilize the advection dominated flow and heat transport. This CVFEM approach is coupled with the conformal decomposition finite-element method (CDFEM), which tracks the corium/air interface on an existing background mesh. CDFEM is a sharp-interface method, allowing the direct discretization of the corium front. This CVFEM-CDFEM approach is used to model the spreading of molten corium in both two- and three-dimensions. The CVFEM approach is briefly motivated in a comparison with a streamwise upwind/Petrov-Galerkin (SUPG) stabilized finite-element method, which was not able to suppress spurious temperature oscillations in the simulations. Our model is compared directly with the FARO L26 corium spreading experiments and with previous numerical simulations, showing both quantitative and qualitative agreement with those studies.

The effect of mixing and sintering processes to prepare tin fluorophosphate glass (Pglass) matrix composites incorporating trisilanol phenyl polyhedral oligomeric silsesquioxane (TSP-POSS) was investigated by comparing manual and suspension mixing, one-step and stepwise sintering processes to explore the structure dynamics and physical properties in the composites as a function of the different process conditions used. Energy Dispersive X-ray analysis confirmed optimal homogeneous dispersion of the TSP-POSS molecules in the composites prepared by the suspension method. The observed increase of glass transition temperature and the reduction of non-bridging bonds in the composites are believed to be the reason for the effective dispersion of TSP-POSS molecules in the composites. The chemical reaction between the TSP-POSS and Pglass was strongly influenced by the mixing/dispersion and sintering processes investigated. 13C cross polarized magic angle spinning (CP MAS) solid state nuclear magnetic resonance (NMR) spectroscopy confirmed the chemical stability of the TSP-POSS during the sintering process at elevated temperatures. In addition, a chemical reaction between the TSP-POSS and Pglass was evidenced by 29Si CP MAS NMR analysis. This study will provide a better fundamental understanding of the effective dispersion mechanism of the TSP-POSS molecules in the Pglass matrix that will facilitate tailoring the physicochemical properties of the composites with addition of various small concentrations of TSP-POSS for a number of applications where the pure Pglass is not applicable due to the intrinsic properties of the Pglass.

An increasing number of jurisdictions are adopting Distributed Energy Resource (DER) interconnection standards which require photovoltaic (PV) inverters, energy storage systems, and other DER to include interoperable grid-support functionality. These functions provide grid operators the nobs to support local and bulk power system operations with DER equipment, but the associated grid operator-to-DER communications networks must be deployed with appropriate cybersecurity features. In some situations, additional security features may prevent control system scalability or increase communication latencies and dropouts. These unintentional consequences of the security features would therefore hinder the ability of the grid operator to implement specific control algorithms. This project evaluated the tradeoffs between power system performance and cybersecurity metrics for several grid services.

We provide a Helmholtz decomposition in the nonlocal setting.

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Each instrument recorded the x-ray emission from the Z-pinch dynamic hohlraum (ZPDH): LOS 330 TREX 6A & B: recorded time resolved and time integrated absorption spectra from a radiatively heated Ne gas; and, LOS 170 are LM monochromatic and high-pass imagers, imaging the Z-pinch before and near stagnation.

This report contains a response from Sandia National Laboratories for the 2019 update to the 2016 Federal Cybersecurity Research and Development Strategic Plan.

Extensive deployment of interoperable distributed energy resources (DER) on power systems is increasing the power system cyber security attack surface. National and jurisdictional interconnection standards require DER to include a range of autonomous and commanded grid support functions which can drastically influence power quality, voltage, and bulk system frequency. This project was split into two phases. The first provided a survey and roadmap of the cybersecurity for the solar industry. The second investigated multiple PV cybersecurity research and development (R&D) concepts identified in the first phase. In the first year, the team created a roadmap for improving cybersecurity for distributed solar energy resources. This roadmap was intended to provide direction for the nation over the next five years and focused on the intersection of industry and government and recommends activities in four related areas: stakeholder engagement, cyber security research and development, standards development, and industry best practices. At the same time, the team produced a primer for DER vendors, aggregators, and grid operators to establish a common taxonomy and describe basic principles of cyber security, encryption, communication protocols, DER cyber security recommendations and requirements, and device-, aggregator-, and utility-level security best practices to ensure data confidentiality, integrity, and availability. This material was motivated by the need to assist the broader PV industry with cybersecurity resilience and describe the state-of-the-art for securing DER communications. Lastly, an adversary-based assessment of multiple PV devices was completed at the Distributed Energy Technologies Laboratory at Sandia National Laboratories to determine the status of industry cybersecurity practices. The team found multiple deficiencies in the security features of the assessed devices. In the second year, a set of recommendations was created for DER communication protocols— especially with respect to the state-of-the-art requirements in IEEE 2030.5. Additionally, several cybersecurity R&D technologies related to communications-enabled photovoltaic systems were studied to harden DER communication networks. Specifically, the team investigated (a) using software defined networking to create a moving target defense system for DER communications, and (b) engineering controls that prevent misprogramming or adversary action on DER devices/networks by disallowing setpoints that will generate unstable power system operations.

Magnesium oxide (MgO)-engineered barriers used in subsurface applications will be exposed to high concentration brine environments and may form stable intermediate phases that can alter the effectiveness of the barrier. To explore the formation of these secondary intermediate phases, MgO was aged in water and three different brine solutions and characterized with X-ray diffraction (XRD) and 1H magic angle spinning (MAS) nuclear magnetic resonance (NMR) spectroscopy. After aging, there is ∼4% molar equivalent of a hydrogen-containing species formed. The 1H MAS NMR spectra resolved multiple minor phases not visible in XRD, indicating that diverse disordered proton-containing environments are present in addition to crystalline Mg(OH)2 brucite. Density functional theory (DFT) simulations for the proposed Mg-O-H-, Mg-Cl-O-H-, and Na-O-H-containing phases were performed to index resonances observed in the experimental 1H MAS NMR spectra. Although the intermediate crystal structures exhibited overlapping 1H NMR resonances in the spectra, Mg-O-H intermediates were attributed to the growth of resonances in the δ +1.0 to 0.0 ppm region, and Mg-Cl-O-H structures produced the increasing contributions of the δ = +2.5 to 5.0 ppm resonances in the chloride-containing brines. Overall, 1H NMR analysis of aged MgO indicates the formation of a wide range of possible intermediate structures that cannot be observed or resolved in the XRD analysis.

An increasing number of jurisdictions are adopting Distributed Energy Resource (DER) interconnection standards which require photovoltaic (PV) inverters, energy storage systems, and other DER to include interoperable grid-support functionality. These functions provide grid operators the nobs to support local and bulk power system operations with DER equipment, but the associated grid operator-to-DER communications networks must be deployed with appropriate cybersecurity features. In some situations, additional security features may prevent control system scalability or increase communication latencies and dropouts. These unintentional consequences of the security features would therefore hinder the ability of the grid operator to implement specific control algorithms. This project evaluated the tradeoffs between power system performance and cybersecurity metrics for several grid services. This was conducted in two parts.

We present VideoSwarm, a system for visualizing video ensembles generated by numerical simulations. VideoSwarm is a web application, where linked views of the ensemble each represent the data using a different level of abstraction. VideoSwarm uses multidimensional scaling to reveal relationships between a set of simulations relative to a single moment in time, and to show the evolution of video similarities over a span of time. VideoSwarm is a plug-in for Slycat, a web-based visualization framework which provides a web-server, database, and Python infrastructure. The Slycat framework provides support for managing multiple users, maintains access control, and requires only a Slycat supported commodity browser (such as Firefox, Chrome, or Safari).

This quarter, we have focused on characterizing the electrochemical response, both through cyclic voltammetry and through constant current charge/discharge characterization of the silicon samples coated with silicates containing varying amounts of Li in the SiOx layer. These studies were performed using a standard Gen-2 electrolyte without FEC. We also performed electrochemical impedance spectroscopy on samples exposed to the Gen-2 electrolyte continually, and collected EIS spectra as a function of time and temperature.

Strong ground motion induces acoustic waves in the atmosphere that can be detected at great distances. These waves provide a record of acceleration at the epicenter of the subterranean event. While this information is valuable for nuclear monitoring purposes, a systematic study of the variation in acoustic parameters with explosive yield and depth has not yet been conducted. Here, we provide a survey of low frequency sound waves generated during the Source Physics Phase 1 experiment, in which six chemical explosions were detonated in granite. We found that pressure amplitudes increase with explosion size but decrease with depth as expected. Pressure amplitude variability increased with signal magnitude. Surprisingly, peak frequency appears to increase with depth. A possible directional signal was identified for one of the events as well. The results presented here may aid the nuclear monitoring community in developing means of determining event depth and yield using acoustic methods. This will complement existing algorithms based on seismic radiation.

This work demonstrates void-free Cu filling of millimeter size Through Silicon Vias (mm-TSV) in an acid copper sulfate electrolyte using a combination of a polyoxamine suppressor and chloride, analogous to previous work filling TSV that were an order of magnitude smaller in size. For high chloride concentration (i.e., 1 mmol/L) bottom-up deposition is demonstrated with the growth front being convex in shape. Instabilities in filling profile arise as the growth front approaches the freesurface due to non-uniform coupling with electrolyte hydrodynamics Filling is negatively impacted by large lithography-induced reentrant notches that increase the via cross section at the bottom. In contrast, deposition from low chloride electrolytes, proceeds with a passive-active transition on the via sidewalls. For a given applied potential the location of the transition is fixed in time and the growth front is concave in nature reflecting the gradient in chloride surface coverage. Application of a suitable potential wave form enables the location of the sidewall transition to be advanced thereby giving rise to void-free filling of the TSV.

A comprehensive comparison of the dominant sources of radiation-induced blur for radiographic imaging system performance is made. End-point energies of 6, 10, 15, and 20 MeV bremsstrahlung photon radiation produced at the Los Alamos National Laboratory Microtron facility were used to examine the performance of large-panel cerium-doped lutetium yttrium silicon oxide (LYSO:Ce) scintillators 3, 5 and 10 mm thick. The system resolution was measured and compared between the various end-point energies and scintillator thicknesses. Contrary to expectations, it is found that there was only a minor dependence of system resolution on scintillator thickness or beam end-point energy. This indicates that increased scintillator thickness does not have a dramatic effect on system performance. The data are then compared to Geant4 simulations to assess contributions to the system performance through the examination of modulation transfer functions. It was determined that the low-frequency response of the system is dominated by the radiation-induced signal, while the higher-frequency response of the system is dominated by the optical imaging of the scintillation emission.

Solid-state metal hydrides are prime candidates to replace compressed hydrogen for fuel cell vehicles due to their high volumetric capacities. Sodium aluminum hydride has long been studied as an archetype for higher-capacity metal hydrides, with improved reversibility demonstrated through the addition of titanium catalysts; however, atomistic mechanisms for surface processes, including hydrogen desorption, are still uncertain. Here in this paper, operando and ex situ measurements from a suite of diagnostic tools probing multiple length scales are combined with ab initio simulations to provide a detailed and unbiased view of the evolution of the surface chemistry during hydrogen release. In contrast to some previously proposed mechanisms, the titanium dopant does not directly facilitate desorption at the surface. Instead, oxidized surface species, even on well-protected NaAlH₄ samples, evolve during dehydrogenation to form surface hydroxides with differing levels of hydrogen saturation. Additionally, the presence of these oxidized species leads to considerably lower computed barriers for H₂ formation compared to pristine hydride surfaces, suggesting that oxygen may actively participate in hydrogen release, rather than merely inhibiting diffusion as is commonly presumed. These results demonstrate how close experiment–theory feedback can elucidate mechanistic understanding of complex metal hydride chemistry and potentially impactful roles of unavoidable surface impurities.

In order to support the codesign needs of ECP applications in current and future hardware in the area of machine learning, the ExaLearn team at Sandia studied the different machine learning use cases in three different ECP applications. This report is a summary of the needs of the three applications. The Sandia ExaLearn team will develop a proxy application representative of ECP application needs, specifically the ExaSky and EXAALT ECP projects. The proxy application will allow us to demonstrate performance portable kernels within machine learning codes. Furthermore, current training scalability of machine learning networks in these applications is negatively affected by large batch sizes. Training throughput of the network will increase as batch size increases, but network accuracy and generalization worsens. The proxy application will contain hybrid model- and data-parallelism to improve training efficiency while maintaining network accuracy. The proxy application will also target optimizing 3D convolutional layers, specific to scientific machine learning, which have not been as thoroughly explored by industry.

In the past decade, basic physics, chemistry, and materials science research on topological quantum materials - and their potential use to implement reliable quantum computers - has rapidly expanded to become a major endeavor. A pivotal goal of this research has been to realize materials hosting Majorana quasiparticles, thereby making topological quantum computing a technological reality. While this goal remains elusive, recent data-mining studies, performed using topological quantum chemistry methodologies, have identified thousands of potential topological materials - some, and perhaps many, with potential for hosting Majoranas. We write this Review for advanced materials researchers who are interested in joining this expanding search, but who are not currently specialists in topology. The first half of the Review addresses, in readily understood terms, three main areas associated with topological sciences: (1) a description of topological quantum materials and how they enable quantum computing; (2) an explanation of Majorana quasiparticles, the important topologically endowed properties, and how it arises quantum mechanically; and (3) a description of the basic classes of topological materials where Majoranas might be found. The second half of the Review details selected materials systems where intense research efforts are underway to demonstrate nontrivial topological phenomena in the search for Majoranas. Specific materials reviewed include the groups II-V semiconductors (Cd3As2), the layered chalcogenides (MX2, ZrTe5), and the rare-earth pyrochlore iridates (A2Ir2O7, A = Eu, Pr). In each case, we describe crystallographic structures, bulk phase diagrams, materials synthesis methods (bulk, thin film, and/or nanowire forms), methods used to characterize topological phenomena, and potential evidence for the existence of Majorana quasiparticles.

We report on the first accurate validation of low-Z ion-stopping formalisms in the regime ranging from low-velocity ion stopping - through the Bragg peak - to high-velocity ion stopping in well-characterized high-energy-density plasmas. These measurements were executed at electron temperatures and number densities in the range of 1.4-2.8 keV and 4×1023-8×1023 cm-3, respectively. For these conditions, it is experimentally demonstrated that the Brown-Preston-Singleton formalism provides a better description of the ion stopping than other formalisms around the Bragg peak, except for the ion stopping at vi∼0.3vth, where the Brown-Preston-Singleton formalism significantly underpredicts the observation. It is postulated that the inclusion of nuclear-elastic scattering, and possibly coupled modes of the plasma ions, in the modeling of the ion-ion interaction may explain the discrepancy of ∼20% at this velocity, which would have an impact on our understanding of the alpha energy deposition and heating of the fuel ions, and thus reduce the ignition threshold in an ignition experiment.

The repetitive rapid solidification that occurs in metal additive manufacturing (AM) processes creates microstructures distinctly different from wrought materials. Local variability in AM microstructures (either by design or unintentional) raises questions as to how AM structures should be modeled at the part-scale to minimize modeling error. The key goal of this work is to demonstrate a posteriori error estimation applied to an AM part. It is assumed that the actual microstructure is unknown and an approximate, spatially uniform material model is used. Error bounds are calculated for many reference models based on AM microstructures with elongated grain morphology and localized or global fiber textures during a post-processing step. The current findings promote confidence that a posteriori model form error estimation could be used effectively in mechanical performance simulations of AM parts to quickly obtain quantitative error metrics between an approximate model result and many microstructure-based reference models. The a posteriori error estimation introduces significant time savings compared to computing the full reference model solutions. Tight bounds on model form error are obtained when texture variations in the reference models occur on large length scales. For materials with property variation at small length scales, multi-scale error estimation techniques are needed to properly account for the many interfaces present between areas with different properties.

Here, the formation of zonal flows from inhomogeneous drift-wave (DW) turbulence is often described using statistical theories derived within the quasilinear approximation. However, this approximation neglects wave–wave collisions. Hence, some important effects such as the Batchelor–Kraichnan inverse-energy cascade are not captured within this approach. Here we derive a wave kinetic equation that includes a DW collision operator in the presence of zonal flows. Our derivation makes use of the Weyl calculus, the quasinormal statistical closure and the geometrical-optics approximation. The obtained model conserves both the total enstrophy and energy of the system. The derived DW collision operator breaks down at the Rayleigh–Kuo threshold. This threshold is missed by homogeneous-turbulence theory but expected from a full-wave quasilinear analysis. In the future, this theory might help better understand the interactions between drift waves and zonal flows, including the validity domain of the quasilinear approximation that is commonly used in the literature.

The Nalu Exascale Wind application assembles linear systems using data structures provided by the Tpetra package in Trilinos. This note describes the initialization and assembly process. The purpose of this note is to help Nalu developers and maintainers to understand the code surrounding linear system assembly, in order to facilitate debugging, optimizations, and maintenance.

The National Rotor Testbed (NRT) design verification experiment is the first test of the new NRT blades retrofitted to the existing Vestas V27 hub and nacelle operated at the Sandia Scaled Wind Farm Technology (SWiFT) facility. This document lays out a plan for pre-assembly, ground assembly, installation, commissioning, and flight testing the NRT rotor. Its performance will be quantified. Adjustments to torque constant and collective blade pitch will be made to ensure that the tip-speed-ratio and span-wise loading are as close to the NRT design as possible. This will ensure that the NRT creates a scaled wake of the GE 1.5sle turbine. Upon completion of this test, the NRT will be in an operational state, ready for future experiments.

This application note describes some known differences in syntax, parsing, and supported features between the HSPICE and Xyce circuit simulators that might be relevant to both internal Sandia Xyce users and other performers on the DARPA Posh Open Source Hardware (POSH) program. It also presents strategies for converting HSPICE netlists and libraries to Xyce netlists and libraries.

This report explores the reliance on communication systems for bulk grid operations and considers selected options as a supplement to cyber security. The extreme scenario of a complete loss of communications for power grid operation is assessed, presenting a bounded, worst-case perspective. The paper explores grid communications failures and how a system modifications can, at an increased cost, retain a moderate level of preparedness for a loss of communications and control when used in partnership with cyber security protocols. Doing so allows the increased economic and secure operation that communication based controls affords, but also ensures a level of resilient operation if they are lost. The motivation of this paper is due to the proliferation of photovoltaic (PV) resources, and more generally, smart-grid resources within the US grid, which are requiring more and more active and wide-area controls. Though the loss of communication and control can affect nearly any grid control system, the risk of losing load at large scales requires a broad view of system interconnectivity, so it has been evaluated from a transmission perspective in this report.

Sandia National Laboratories (SNL) continued evaluation of total system performance assessment (TSPA) computing systems for the previously considered Yucca Mountain Project (YMP). This was done to maintain the operational readiness of the computing infrastructure (computer hardware and software) and knowledge capability for total system performance assessment (TSPA) type analysis, as directed by the National Nuclear Security Administration (NNSA), DOE 2010. This work is a continuation of the ongoing readiness evaluation reported in Lee and Hadgu (2014), Hadgu et al. (2015) and Hadgu and Appel (2016), and Hadgu et al. (2017). The TSPA computing hardware (2014 server cluster -CL2014) and storage system described in Hadgu et al. (2015) were used for the current analysis. One floating license of Gold Sim with Versions 9.60.300, 10.5, 11.1 and 12.0 was installed on the cluster head node, and its distributed processing capability was mapped on the cluster processors. Other supporting software were tested and installed to support the TSPA-type analysis on the server cluster. The FY18 task included developing an inventory of software used for the Yucca Mountain Project process models and preliminary assessment of status of the software; enhancing security of the cluster and setting a backup system. The 2014 server cluster and supporting software systems are fully operational to support TSPA-LA type analysis.

The STDA05-17 milestone comprises the following 3 deliverables. VTK-m Release 2 We will provide a release of VTK-m software and associated documentation. The source code repository will be tagged at a stable state, and, at a minimum, tarball captures of the source code will be made available from the web site. A version of the VTK-m User's Guide documenting this release will also be made available. Productionize zfp compression The "ZFP: Compressed Floating-Point Arrays" project (WBS 1.3.4.13) is creating an implementation of ZFP compression in VTK-m. Their implementation will be focused on operating in CUDA. The VTK-m project will assist by generalizing the implementation to other devices (such as multi-core CPUs). We will also assist in productionizing the code such that it can be used by external projects and products. Clip Clip operations intersect meshes with implicit functions. It is the foundation of spatial subsetting algorithms, such as "box," and the foundation of data-based subsetting, such as "isovolume." The algorithm requires considering thousands of possible cases, and is thus quite difficult to implement. This milestone will implement clipping to be sufficient for Visit's and ParaView's needs.

The STDA05-16 milestone comprises the following 3 distinct deliverables. OpenMP VTK-m currently supports three types of devices: serial CPU, TBB, and CUDA. To run algorithms on multicore CPU-type devices (such as Xeon and Xeon Phi), TBB is required. However, there are known issues with integrating a software product using TBB with another one using OpenMP. Therefore, we will add an OpenMP device to the VTK-m software. When engaged, this device will run parallel algorithms using OpenMP directives. This will mesh more nicely with other code also using OpenMP. Rendering Topological Entities VTK-m currently supports surface rendering by tessellation of data structures,and rendering the resulting triangles. We will extend current functionality to include face, edge, and point rendering. Better Dynamic Types Impl For the best efficiency across all platforms, VTK-m algorithms use static typing with C++ templates. However, many libraries like VTK, ParaView, and Visit use dynamic types with virtual functions because data types often cannot be determined at compile time. We have an interface in VTK-m to merge these two typing mechanisms by generating all possible combinations of static types when faced with a dynamic type. Although this mechanism works, it generates very large executables and takes a very long time to compile. As we move forward, it is clear that these problems will get worse and become infeasible at exascale. We will rectify the problem by introducing some level of virtual methods, which require only a single code path, within VTK-m algorithms. This first milestone produces a design document to propose an approach to the new system.

We have completed a series of small-scale cook-off experiments of ammonium nitrate (AN) prills in our Sandia Instrumented Thermal Ignition test at nominal packing densities of about 0.8 g/cm3. We increased the boundary temperature of our aluminum confinement cylinder from room temperature to a prescribed set-point temperature in 10 min. Our set-point temperature ranged from 508 to 538 K. The external temperature of the confining cylinder was held at the set-point temperature until ignition. We used type K thermocouples to measure temperatures associated with several polymorphic phase changes as well as melting and boiling. As the AN boiled, our thermocouples were destroyed by corrosion, which may have been caused by reaction of hot nitric acid (HNO3) with nickel to form nickel nitrate, Ni(NO3)2. Videos of the corroding thermocouples showed a green solution that was similar to the color of Ni(NO3)2. We found that ignition was imminent as the AN boiling point was exceeded. Ignition of the AN prills was modeled by solving the energy equation with an energy source due to desorption of moisture and decomposition of AN to form equilibrium products. A Boussinesq approximation was used in conjunction with the momentum equation to model flow of the liquid AN. We found that the prediction of ignition was not sensitive to small perturbations in the latent enthalpies.

Due to the complex multiscale interaction between intense turbulence and relatively weak flames, turbulent premixed flames in the thin and broken reaction zones regimes exhibit strong finite-rate chemistry and strain effects and are hence challenging to model. In this work, a laboratory premixed jet flame in the broken reaction zone, which has recently been studied using direct numerical simulation (DNS), is modeled using a large eddy simulation (LES)/dynamic thickened flame (DTF) approach with detailed chemistry. The presence of substantial flame thickening due to strong turbulence-chemistry interactions, which can be characterized by a high Karlovitz number (Ka), requires the DTF model to thicken the flame in an adaptive way based on the local resolution of flame scales. Here, an appropriate flame sensor and strain-sensitive flame thickness are used to automatically determine the thickening location and thickening factor, respectively. To account for finite-rate chemistry and strain effects, the chemistry is described in two different ways: (1) detailed chemistry denoted as full transport and chemistry (FTC), and (2) tabulated chemistry based on a strained premixed flamelet (SPF) model. The performance of the augmented LES/DTF approach for modeling the high Ka premixed flame is assessed through detailed a posteriori comparisons with DNS of the same flame. It is found that the LES/DTF/FTC model is capable of reproducing most features of the high Ka turbulent premixed flame including accurate CO and NO prediction. The LES/DTF/SPF model has the potential to capture the impact of strong turbulence on the flame structure and provides reasonable prediction of pollutant emissions at a reasonable computational cost. In order to identify the impact of aerodynamic strain, the turbulent flame structure is analyzed and compared with unstrained and strained premixed flamelet solutions. The results indicate that detailed strain effects should be considered when using tabulated methods to model high Ka premixed flames.

The link between the distribution of fluid residence time and the distribution of reactive scalars is analysed using Direct Numerical Simulation data. Information about the reactive scalar distribution is needed in order to model the reaction terms that appear in Large Eddy and Reynolds-Averaged simulations of turbulent reacting flows. The lifted flame is simulated taking account of multi-step chemistry for dimethyl-ether fuel. Due to autoignition and flame propagation, the reaction progress increases with residence time. The variation of fluid residence time is evaluated by solving an Eulerian transport equation for the fluid age. The fluid age is a passive scalar with a spatially-uniform source term, meaning that its moments and dissipation rates in turbulent flows can be modelled using closures already established for conserved scalars such as mixture fraction. In combination with the mixture fraction, the fluid age serves as a useful mapping variable to distinguish younger less-reacted fluid near the inlet from older more-reacted fluid downstream. The local fluctuations of mixture fraction and fluid age have strong negative correlation and, building upon established presumed-pdf models for mixture fraction, this feature can be used to construct an accurate presumed-pdf model for the joint mixture fraction/fluid age pdf. It is demonstrated that the double-conditional first-order moment closure combined with the proposed presumed model for the joint pdf of mixture fraction and fluid age gives accurate predictions for unconditional reaction rates - both for pre-ignition radical species produced by low-temperature processes upstream of the flame base, and for major species that are produced at the flame front.

A three-dimensional direct numerical simulation (DNS) is performed for a turbulent hydrogen-air flame, represented with detailed chemistry, stabilized in a model gas-turbine combustor. The combustor geometry consists of a mixing duct followed by a sudden expansion and a combustion chamber, which represents a geometrically simplified version of Ansaldo Energia's GT26/GT36 sequential combustor design. In this configuration, a very lean blend of hydrogen and vitiated air is prepared in the mixing duct and convected into the combustion chamber, where the residence time from the inlet of the mixing duct to the combustion chamber is designed to coincide with the ignition delay time of the mixture. The results show that when the flame is stabilized at its design position, combustion occurs due to both autoignition and flame propagation (deflagration) modes at different locations within the combustion chamber. A chemical explosive mode analysis (CEMA) reveals that most of the fuel is consumed due to autoignition in the bulk-flow along the centerline of the combustor, and lower amounts of fuel are consumed by flame propagation near the corners of the sudden expansion, where the unburnt temperature is reduced by the thermal wall boundary layers. An unstable operating condition is also identified, wherein periodic auto-ignition events occur within the mixing duct. These events appear upstream of the intended stabilization position, due to positive temperature fluctuations induced by pressure waves originating from within the combustion chamber. The present DNS investigation represents the initial step of a comprehensive research effort aimed at gaining detailed physical insight into the rate-limiting processes that govern the sequential combustor behavior and avoid the insurgence of the off-design auto-ignition events.

The ignition process in diesel engines is highly complex and incompletely understood. In the present study, two-dimensional direct numerical simulations are performed to investigate the ignition dynamics and their sensitivity to thermochemical and mixing parameters. The thermochemical and mixing conditions are matched to the benchmark Spray A experiment from the Engine Combustion Network. The results reveal a complex ignition process with overlapping stages of: low-temperature ignition (cool flames), rich premixed ignition, and nonpremixed ignition, which are qualitatively consistent with prior experimental and numerical investigations, however, this is the first time that fully-resolved simulations have been reported at the actual Spray A thermochemical condition. Parametric variations are then performed for the Damkohler number Da, oxidiser temperature, oxygen concentration, and peak mixture fraction (a measure of premixedness), to study their effect on the ignition dynamics. It is observed that with both increasing oxidiser temperature and decreasing oxygen concentration, that the cool flame moves to richer mixtures, the overlap in the ignition stages decreases, and the (nondimensional) time taken to reach a fully burning state increases. With increasing Da, the cool-flame speed is decreased due to lower mean mixing rates, which causes a delayed onset of high-temperature ignition. With increasing peak mixture fraction, the onset of each stage of ignition is not affected, but the overall duration of the ignition increases leading to a longer burn duration. Overall, the results suggest that turbulence-chemistry interactions play a significant role in determining the timing and location in composition space of the entire ignition process.

In turbulent premixed flame propagation, the formation of isolated pockets of reactants or products is associated with flame pinch-off events which cause rapid changes in the flame surface area. Previous topological analysis of these phenomena has been carried out based on Morse theory and Direct Numerical Simulation (DNS) in two spatial dimensions. The present work extends the topological analysis to three dimensions with emphasis on the formation and subsequent burnout of reactant pockets. Singular behaviour observed previously for terms of the Surface Density Function (SDF) transport equation in the two-dimensional case is shown to occur also in three dimensions. Further singular behaviour is observed in the displacement speed close to reactant pocket burnout. The theory is compared against DNS data from hydrogen-air flames and good agreement is obtained.

We investigate the influence of inflow velocity (Vin) and scalar dissipation rate (χ) on the flame structure and stabilisation mechanism of steady, laminar partially premixed n-dodecane edge flames stabilised on a convective mixing layer. Numerical simulations were performed for three different χ profiles and several Vin (Vin = 0.2 to 2.5m/s). The ambient thermochemical conditions were the same as the Engine Combustion Network's (ECN) Spray A flame, which in turn represents conditions in a typical heavy duty diesel engine. The results of a combustion mode analysis of the simulations indicate that the flame structure and stabilisation mechanism depend on Vin and χ. For low Vin the flame is attached. Increasing Vin causes the high-temperature chemistry (HTC) flame to lift-off, while the low-temperature chemistry (LTC) flame is still attached. A unique speed SR associated with this transition is defined as the velocity at which the lifted height has the maximum sensitivity to changes in Vin. This transition velocity is negatively correlated with χ. Near Vin=SR a tetrabrachial flame structure is observed consisting of a triple flame, stabilised by flame propagation into the products of an upstream LTC branch. Further increasing the inlet velocity changes the flame structure to a pentabrachial one, where an additional HTC ignition branch is observed upstream of the triple flame and ignition begins to contribute to the flame stabilisation. At large Vin, the LTC is eventually lifted, and the speed at which this transition occurs is insensitive to χ. Further increasing Vin increases the contribution of ignition to flame stabilisation until the flame is completely ignition stabilised. Flow divergence caused by the LTC branch reduces the χ at the HTC branches making the HTC more resilient to χ. The results are discussed in the context of identification of possible stabilisation modes in turbulent flames.

The Hurty/Craig-Bampton method in structural dynamics represents the interior dynamics of each subcomponent in a substructured system with a truncated set of normal modes and retains all of the physical degrees of freedom at the substructure interfaces. This makes the assembly of substructures into a reduced-order system model relatively simple, but means that the reduced-order assembly will have as many interface degrees of freedom as the full model. When the full-model mesh is highly refined, and/or when the system is divided into many subcomponents, this can lead to an unacceptably large system of equations of motion. To overcome this, interface reduction methods aim to reduce the size of the Hurty/Craig-Bampton model by reducing the number of interface degrees of freedom. This research presents a survey of interface reduction methods for Hurty/Craig-Bampton models, and proposes improvements and generalizations to some of the methods. Some of these interface reductions operate on the assembled system-level matrices while others perform reduction locally by considering the uncoupled substructures. The advantages and disadvantages of these methods are highlighted and assessed through comparisons of results obtained from a variety of representative linear FE models.

Existing machines for lazy evaluation use a flat representation of environments, storing the terms associated with free variables in an array. Combined with a heap, this structure supports the shared intermediate results required by lazy evaluation. We propose and describe an alternative approach that uses a shared environment to minimize the overhead of delayed computations. We show how a shared environment can act as both an environment and a mechanism for sharing results. To formalize this approach, we introduce a calculus that makes the shared environment explicit, as well as a machine to implement the calculus, the Cactus Environment Machine. A simple compiler implements the machine and is used to run experiments for assessing performance. The results show reasonable performance and suggest that incorporating this approach into real-world compilers could yield performance benefits in some scenarios.

The computational burden of a large-eddy simulation for reactive flows is exacerbated in the presence of uncertainty in flow conditions or kinetic variables. A comprehensive statistical analysis, with a sufficiently large number of samples, remains elusive. Statistical learning is an approach that allows for extracting more information using fewer samples. Such procedures, if successful, will greatly enhance the predictability of models in the sense of improving exploration and characterization of uncertainty due to model error and input dependencies, all while being constrained by the size of the associated statistical samples. In this paper, it is shown how a recently developed procedure for probabilistic learning on manifolds can serve to improve the predictability in a probabilistic framework of a scramjet simulation. The estimates of the probability density functions of the quantities of interest are improved together with estimates of the statistics of their maxima. It is also demonstrated how the improved statistical model adds critical insight to the performance of the model.

We present a meshfree quadrature rule for compactly supported nonlocal integro-differential equations (IDEs) with radial kernels. We apply this rule to develop a meshfree discretization of a peridynamic solid mechanics model that requires no background mesh. Existing discretizations of peridynamic models have been shown to exhibit a lack of asymptotic compatibility to the corresponding linearly elastic local solution. By posing the quadrature rule as an equality constrained least squares problem, we obtain asymptotically compatible convergence by introducing polynomial reproduction constraints. Our approach naturally handles traction-free conditions, surface effects, and damage modeling for both static and dynamic problems. We demonstrate high-order convergence to the local theory by comparing to manufactured solutions and to cases with crack singularities for which an analytic solution is available. Finally, we verify the applicability of the approach to realistic problems by reproducing high-velocity impact results from the Kalthoff–Winkler experiments.

Finite element models are regularly used in many disciplines to predict dynamic behavior of a structure under certain loads and subject to various boundary conditions, in particular when analytical models cannot be used due to geometric complexity. One such example is a structure with an entrained fluid cavity. To assist an experimental study of the acoustoelastic effect, numerical studies of an enclosed cylinder were performed to design the test hardware. With a system that demonstrates acoustoelastic coupling, it was then desired to make changes to decouple the structure from the fluid by making changes to either the fluid or the structure. In this paper, simulation is used to apply various changes and observe the effects on the structural response to choose an effective decoupling approach for the experimental study.

This paper analyzes the effect of wind turbine integration (WT) on the inter-area oscillation mode of a test two-area power system. The paper uses a root-locus based design method to propose a pair of controllers to provide damping to the inter-area mode of the system. The controllers are selected from the best combination of feedback signal and WT control action. One of the controllers uses the active power control part of the WT while the other uses the reactive power part. The paper analyzes the impact that increases on the transmission line connecting the WT to the system have on the controllers' performance. Time domain simulations are provided to evaluate the effectiveness of the controllers under different conditions.

Several recent studies (Mayes, R.L., Pacini, B.R., Roettgen, D.R.: A modal model to simulate typical structural dynamics nonlinearity. In: Proceedings of the 34th International Modal Analysis Conference. Orlando, FL, (2016); Pacini, B.R., Mayes, R.L., Owens, B.C., Schultz, R.: Nonlinear finite element model updating, part I: experimental techniques and nonlinear modal model parameter extraction. In: Proceedings of the 35th international modal analysis conference, Garden Grove, CA, (2017)) have investigated predicting nonlinear structural vibration responses using modified modal models. In such models, a nonlinear element is added in parallel to the traditional linear spring and damping elements. This assumes that the mode shapes do not change with amplitude and there are no interactions between modal degrees of freedom. Previous studies have predominantly applied this method to idealistic structures. In this work, the nonlinear modal modeling technique is applied to a more realistic industrial aerospace structure which exhibits complex bilinear behavior. Linear natural frequencies, damping values, and mode shapes are first extracted from low level shaker testing. Subsequently, the structure is excited using high level tailored shaker inputs. The resulting response data are modally filtered and used to empirically derive the nonlinear elements which, together with their linear counterparts, comprise the nonlinear modal model. This model is then used in both modal and physical domain simulations. Comparisons to measured data are made and the performance of the nonlinear modal model to predict this complex bilinear behavior is discussed.

We consider a standard elliptic partial differential equation and propose a geometric multigrid algorithm based on Dirichlet-to-Neumann (DtN) maps for hybridized high-order finite element methods. The proposed unified approach is applicable to any locally conservative hybridized finite element method including multinumerics with different hybridized methods in different parts of the domain. For these methods, the linear system involves only the unknowns residing on the mesh skeleton, and constructing intergrid transfer operators is therefore not trivial. The key to our geometric multigrid algorithm is the physics-based energy-preserving intergrid transfer operators which depend only on the fine scale DtN maps. Thanks to these operators, we completely avoid upscaling of parameters and no information regarding subgrid physics is explicitly required on coarse meshes. Moreover, our algorithm is agglomeration-based and can straightforwardly handle unstructured meshes. We perform extensive numerical studies with hybridized mixed methods, hybridized discontinuous Galerkin methods, weak Galerkin methods, and hybridized versions of interior penalty discontinuous Galerkin methods on a range of elliptic problems including subsurface flow through highly heterogeneous porous media. We compare the performance of different smoothers and analyze the effect of stabilization parameters on the scalability of the multigrid algorithm.

Data science includes a variety of scientific methods and processes to extract data from various sources. The integration of interdisciplinary fields such as mathematics, statistics, information science, and computer science affords techniques to analyze large volumes of data to arrive at unique insights and make data-driven decisions (Sinelnikov et al., 2015) in real time. The technique lends itself to other applications across many domains including hazard assessments, analysis of near-miss data, identification of leading and lagging indicators from past accidents, and others. Benefits of this technique include efficiency due to improved data acquisition. Near-miss data represents an important source to identify conditions that lead to accidents to develop strategies to prevent them. Analysis of near-miss data sets can involve various techniques. This paper will explore the use of data science to mine accident reports, with a special emphasis on near misses to uncover occurrences that were not initially identified in the documentation. Data-science techniques such as text analyses facilitate searching large volumes of data to uncover patterns for more informed decisions. Regarding near-miss data, data science techniques can be used to test the ability to uncover new hazards/ hazardous preconditions and the accuracy of those findings. With the benefits of crunching large data sets and uncovering new hazards, considerations and implications are also made regarding how that might influence safety culture.

Malicious cyber-attacks are becoming increasingly prominent due to the advance of technology and attack methods over the last decade. These attacks have the potential to bring down critical infrastructures, such as nuclear power plants (NPP’s), which are so vital to the country that their incapacitation would have debilitating effects on national security, public health, or safety. Despite the devastating effects a cyber-attack could have on NPP’s, it is unclear how control room operations would be affected in such a situation. In this project, the authors are collaborating with NPP operators to discern the impact of cyber-attacks on control room operations and lay out a framework to better understand the control room operators’ tasks and decision points. A cyber emulation of a digital control system was developed and coupled with a generic pressurized water reactor (GPWR) training simulator at Idaho National Laboratories. Licensed operators were asked to complete a series of scenarios on the simulator in which some of the scenarios were purposely obfuscated; that is, in which indicators were purposely displaying inaccurate information. Of interest is how this obfuscation impacts the ability to keep the plant safe and how it affects operators’ perceptions of workload and performance. Results, conclusions and lessons learned from this pilot experiment will be discussed. This research sheds light onto about how cyber events impact plant operations.

Aerospace systems and components are designed and qualified against several operational environments. Some of these environments are climatic, mechanical, and electrical in nature. Traditionally, mechanical test specifications are derived with the goal of qualifying a system or component to a suite of independent mechanical environments in series. True operational environments, however, are composed of complex, combined events. This work examines the effect of combined mechanical shock and vibration environments on response of a dynamic system. Responses under combined environments are compared to those under single environments, and the adequacy/limitations of conventional, single environment test approaches (shock only or vibration only) will be assessed. Test integration strategies for combined shock and vibration environments are also discussed.

Background: Prior research in falls risk prediction often relies on qualitative and/or clinical methods. There are two challenges with these methods. First, qualitative methods typically use falls history to determine falls risk. Second, clinical methods do not quantify the uncertainty in the classification decision. In this paper, we propose using Bayesian classification to predict falls risk using vectors of gait variables shown to contribute to falls risk. Research Questions: (1) Using a vector of risk ratios for specific gait variables shown to contribute to falls risk, how can older adults be classified as low or high falls risk? and (2) how can the uncertainty in the classifier decision be quantified when using a vector of gait variables? Methods: Using a pressure sensitive walkway, biomechanical measurements of gait were collected from 854 adults over the age of 65. In our method, we first determine low and high falls risk labels for vectors of risk ratios using the k-means algorithm. Next, the posterior probability of low or high falls risk class membership is obtained from a two component Gaussian mixture model (GMM) of gait vectors, which enables risk assessment directly from the underlying biomechanics. We classify the gait vectors using a threshold based on Youden's J statistic. Results: Through a Monte Carlo simulation and an analysis of the receiver operating characteristic (ROC), we demonstrate that our Bayesian classifier, when compared to the k-means falls risk labels, achieves an accuracy greater than 96% at predicting low or high falls risk. Significance: Our analysis indicates that our approach based on a Bayesian framework and an individual's underlying biomechanics can predict falls risk while quantifying uncertainty in the classification decision.

Recently, an approach for determining the value of a visualization was proposed, one moving beyond simple measurements of task accuracy and speed. The value equation contains components for the time savings a visualization provides, the insights and insightful questions it spurs, the overall essence of the data it conveys, and the confidence about the data and its domain it inspires. This articulation of value is purely descriptive, however, providing no actionable method of assessing a visualization's value. In this work, we create a heuristic-based evaluation methodology to accompany the value equation for assessing interactive visualizations. We refer to the methodology colloquially as ICE-T, based on an anagram of the four value components. Our approach breaks the four components down into guidelines, each of which is made up of a small set of low-level heuristics. Evaluators who have knowledge of visualization design principles then assess the visualization with respect to the heuristics. We conducted an initial trial of the methodology on three interactive visualizations of the same data set, each evaluated by 15 visualization experts. We found that the methodology showed promise, obtaining consistent ratings across the three visualizations and mirroring judgments of the utility of the visualizations by instructors of the course in which they were developed.

Statechart modelling notations, with so-called ‘run to completion’ semantics and simulation tools for validation, are popular with engineers for designing systems. However, they do not support formal refinement and they lack formal static verification methods and tools. For example, properties concerning the synchronisation between different parts of a system may be difficult to verify for all scenarios, and impossible to verify at an abstract level before the full details of substates have been added. Event-B, on the other hand, is based on refinement from an initial abstraction and is designed to make formal verification by automatic theorem provers feasible, restricting instantiation and testing to a validation role. In this paper, we introduce a notion of refinement, similar to that of Event-B, into a ‘run to completion’ Statechart modelling notation, and leverage Event-B’s tool support for proof. We describe the pitfalls in translating ‘run to completion’ models into Event-B refinements and suggest a solution. We illustrate the approach using our prototype translation tools and show by example, how a synchronisation property between parallel Statecharts can be automatically proven at an intermediate refinement level.

We describe for the first time hydrogen bonded acid (HBA) polymer, poly[methyl[3-(2-hydroxyl, 4,6-bistrifluoromethyl)- phenyl]propylsiloxane], (DKAP), as stationary phase for gas chromatography (μGC) of organophosphate (OP), chemical warfare agent (CWA) surrogates, dimethylmethylphosphonate (DMMP), diisopropylmethylphosphonate (DIMP), diethylmethylphosphonate (DEMP), and trimethylphosphate (TMP), with high selectivity. Absorption of OPs to DKAP was one-to-several orders of magnitude higher relative to commercial polar, mid-polar, and nonpolar stationary phases. We also present for the first-time thermodynamic studies on the absorption of OP vapors and quantitative binding energy data for interactions with various stationary phases. These data help to identify the best pair of hetero-polar columns for a two-dimensional GC system, employing a nonpolar stationary phase as GC1 and DKAP as the GC2 stationary phase, for selective and rapid field detection of CWAs.

Numerically modeling chatter behavior of small electrical components embedded within larger components is challenging. Reduced order models (ROMs) have been developed to assess these components’ chatter behavior in vibration and shock environments. These ROMs require experimental validation to instill confidence that these components meet their performance requirements. While achieving conservative results, experimental validation is required, especially considering that the ROMs neglect the viscous damping effects of the fluid that surrounds these particular components within their system. Dynamic ring-down data of the electrical receptacles in air will be explored and will be assessed as to whether that data provides a validation data set for this ROM. Additional data will be examined in which dynamic ring-down data was taken on the receptacle while submerged in an oil, resulting in a unique experimental setup that should prove as a proof of concept for this type of testing on small components in unique environments.

Historically, control systems have primarily depended upon their isolation from the Internet and from traditional information technology (IT) networks as a means of maintaining secure operation in the face of potential remote attacks over computer networks. However, these networks are incrementally being upgraded and are becoming more interconnected with external networks so they can be effectively managed and configured remotely. Examples of control systems include the electrical power grid, smart grid networks, microgrid networks, oil and natural gas refineries, water pipelines, and nuclear power plants. Given that these systems are becoming increasingly connected, computer security is an essential requirement as compromises can result in consequences that translate into physical actions and significant economic impacts that threaten public health and safety. Moreover, because the potential consequences are so great and these systems are remotely accessible due to increased interconnectivity, they become attractive targets for adversaries to exploit via computer networks. Several examples of attacks on such systems that have received a significant amount of attention include the Stuxnet attack, the US-Canadian blackout of 2003, the Ukraine blackout in 2015, and attacks that target control system data itself. Improving the cybersecurity of electrical power grids is the focus of our research.

Experimental modal analysis via shaker testing introduces errors in the measured structural response that can be attributed to the force transducer assembly fixed on the vibrating structure. Previous studies developed transducer mass-cancellation techniques for systems with translational degrees of freedom; however, studies addressing this problem when rotations cannot be neglected are sparse. In situations where rotations cannot be neglected, the apparent mass of the transducer is dependent on its geometry and is not the same in all directions. This paper investigates a method for correcting the measured system response that is contaminated with the effects of the attached force transducer mass and inertia. Experimental modal substructuring facilitated estimations of the translational and rotational mode shapes at the transducer connection point, thus enabling removal of an analytical transducer model from the measured test structure resulting in the corrected response. A numerical analysis showed the feasibility of the proposed approach in estimating the correct modal frequencies and forced response. To provide further validation, an experimental analysis showed the proposed approach applied to results obtained from a shaker test more accurately reflected results obtained from a hammer test.

Joining technologies such as welds, adhesives, and bolts are nearly ubiquitous and often lead to concentrated stresses, making them key in analyzing failure of a structure. While high-fidelity models for fasteners have been developed, they are impractical for use in a full system or component analyses, which may involve hundreds of fasteners undergoing mixed loading. Other failure models for fasteners which use specialized boundary conditions, e.g., spot welds, do well in replicating the load-displacement response of a fastener in a mesh independent manner, but are limited in their ability to transmit a bending moment and require constitutive assumptions when there is a lack of experimental data. A reduced-order finite element model using cohesive surface elements to model fastener failure is developed. A cohesive zone allows for more explicitly representing the fracture of the fastener, rather than simply specifying a load-displacement relationship between two surfaces as in the spot weld. This fastener model is assessed and calibrated against tensile and shear loading data and compared to a traditional spot weld approach. The cohesive zone model can reproduce the experimental data, demonstrating its viability as a reduced-order model of fastener behavior.

Qualification of complex systems often involves shock and vibration testing at the component level to ensure each component is robust enough to survive the specified environments. In order for the component testing to adequately satisfy the system requirements, the component must exhibit a similar dynamic response between the laboratory component test and system test. There are several aspects of conventional testing techniques that may impair this objective. Modal substructuring provides a framework to accurately assess the level of impairment introduced in the laboratory setup. If the component response is described in terms of fixed-base modes in both the laboratory and system configurations, we can gain insight into whether the laboratory test is exercising the appropriate damage potential. Further, the fixed-base component response in the system can be used to determine the correct rigid body laboratory fixture input to overcome the errors seen in the standard component test. In this paper, we investigate the effectiveness of reproducing a system shock environment on a simple beam model with an essentially rigid fixture.

This work introduces a new method to efficiently solve optimization problems constrained by partial differential equations (PDEs) with uncertain coefficients. The method leverages two sources of inexactness that trade accuracy for speed: (1) stochastic collocation based on dimension-Adaptive sparse grids (SGs), which approximates the stochastic objective function with a limited number of quadrature nodes, and (2) projection-based reduced-order models (ROMs), which generate efficient approximations to PDE solutions. These two sources of inexactness lead to inexact objective function and gradient evaluations, which are managed by a trust-region method that guarantees global convergence by adaptively refining the SG and ROM until a proposed error indicator drops below a tolerance specified by trust-region convergence theory. A key feature of the proposed method is that the error indicator|which accounts for errors incurred by both the SG and ROM|must be only an asymptotic error bound, i.e., a bound that holds up to an arbitrary constant that need not be computed. This enables the method to be applicable to a wide range of problems, including those where sharp, computable error bounds are not available; this distinguishes the proposed method from previous works. Numerical experiments performed on a model problem from optimal ow control under uncertainty verify global convergence of the method and demonstrate the method's ability to outperform previously proposed alternatives.

A new apparatus – “Dropkinson Bar” – has been successfully developed for material property characterization at intermediate strain rates. This Dropkinson bar combines a drop table and a Hopkinson bar. The drop table was used to generate a relatively long and stable low-speed impact to the specimen, whereas the Hopkinson bar principle was applied to measure the load history with accounting for inertia effect in the system. Pulse shaping technique was also applied to the Dropkinson bar to facilitate uniform stress and strain as well as constant strain rate in the specimen. The Dropkinson bar was then used to characterize 304L stainless steel and 6061-T6 aluminum at a strain rate of ∼600 s−1. The experimental data obtained from the Dropkinson bar tests were compared with the data obtained from conventional Kolsky tensile bar tests of the same material at similar strain rates. Both sets of experimental results were consistent, showing the newly developed Dropkinson bar apparatus is reliable and repeatable.

There are several methodologies for modeling fasteners in finite element analyses. This work examines the effect of four predominant fastener modeling methods regarding the fatigue of mock hardware that requires fasteners. Typical fastener modeling methods explored in this work consist of a spring method with no preload, a beam method with no preload, a beam method with a preload, and a solid model representation of the fastener with preload. It is found that the different fastener modeling methods produce slightly different fatigue damage predictions, and that this uncertainty in modeling is insignificant as compared to uncertainty in input. Consequently, any of these methods are considered appropriate. In order to make this assertion, multiaxial fatigue methods are investigated and a proportional method is used because of a biaxiality metric.

We examine the problem of crawling the community structure of a multiplex network containing multiple layers of edge relationships. While there has been a great deal of work examining community structure in general, and some work on the problem of sampling a network to preserve its community structure, to the best of our knowledge, this is the first work to consider this problem on multiplex networks. We consider the specific case in which the layers of a multiplex network have different query (collection) costs and reliabilities; and a data collector is interested in identifying the community structure of the most expensive layer. We propose MultiComSample (MCS), a novel algorithm for crawling a multiplex network. MCS uses multiple levels of multi-armed bandits to determine the best layers, communities and node roles for selecting nodes to query. We test MCS against six baseline algorithms on real-world multiplex networks, and achieved large gains in performance. For example, after consuming a budget equivalent to sampling 20% of the nodes in the expensive layer, we observe that MCS outperforms the best baseline by up to 49%.

U. S. Nuclear Power Plants are seeking to implement wireless communications for cost-effective operations. New technology introduced into power plants must not introduce security concerns into critical plant functions. This paper describes the potential for new security concerns with proposed nuclear power plant wireless system implementations and methods of evaluation. While two aspects of concern are introduced, only one (cyber attack vulnerability) is expanded with a description of test setup and methods. A novel method of cyber vulnerability discovery is also described. The goal of this research is to establish wireless technology as a part of a secure operations architecture that brings increased efficiency without introducing new security concerns.

We use Bayesian data analysis to predict dengue fever outbreaks and quantify the link between outbreaks and meteorological precursors tied to the breeding conditions of vector mosquitos. We use Hamiltonian Monte Carlo sampling to estimate a seasonal Gaussian process modeling infection rate, and aperiodic basis coefficients for the rate of an “outbreak level” of infection beyond seasonal trends across two separate regions. We use this outbreak level to estimate an autoregressive moving average (ARMA) model from which we extrapolate a forecast. We show that the resulting model has useful forecasting power in the 6–8 week range. The forecasts are not significantly more accurate with the inclusion of meteorological covariates than with infection trends alone.

Some of the primary barriers to widespread adoption of metal additive manufacturing (AM) are persistent defect formation in built components, high material costs, and lack of consistency in powder feedstock. To generate more reliable, complex-shaped metal parts, it is crucial to understand how feedstock properties change with reuse and how that affects build mechanical performance. Powder particles interacting with the energy source, yet not consolidated into an AM part can undergo a range of dynamic thermal interactions, resulting in variable particle behavior if reused. In this work, we present a systematic study of 316L powder properties from the virgin state through thirty powder reuses in the laser powder bed fusion process. Thirteen powder characteristics and the resulting AM build mechanical properties were investigated for both powder states. Results show greater variability in part ductility for the virgin state. The feedstock exhibited minor changes to size distribution, bulk composition, and hardness with reuse, but significant changes to particle morphology, microstructure, magnetic properties, surface composition, and oxide thickness. Additionally, sieved powder, along with resulting fume/condensate and recoil ejecta (spatter) properties were characterized. Formation mechanisms are proposed. It was discovered that spatter leads to formation of single crystal ferrite through large degrees of supercooling and massive solidification. Ferrite content and consequently magnetic susceptibility of the powder also increases with reuse, suggesting potential for magnetic separation as a refining technique for altered feedstock.

Many test articles exhibit slight nonlinearities which result in natural frequencies shifting between data from different references. This shifting can confound mode fitting algorithms because a single mode can appear as multiple modes when the data from multiple references are combined in a single data set. For this reason, modal test engineers at Sandia National Laboratories often fit data from each reference separately. However, this creates complexity when selecting a final set of modes, because a given mode may be fit from a number of reference data sets. The color-coded complex mode indicator function was developed as a tool that could be used to reduce a complex data set into a manageable figure that displays the number of modes in a given frequency range and also the reference that best excites the mode. The tool is wrapped in a graphical user interface that allows the test engineer to easily iterate on the selected set of modes, visualize the MAC matrix, quickly resynthesize data to check fits, and export the modes to a report-ready table. This tool has proven valuable, and has been used on very complex modal tests with hundreds of response channels and a handful of reference locations.

Small components are becoming increasingly prevalent in today’s society. Springs are a commonly found piece-part in many mechanisms, and as these components become smaller, so do the springs inside of them. Because of their size, small manufacturing defects or other damage to the spring may become significant: a tiny gouge might end up being a significant portion of the cross-sectional area of the wire. However, their small size also makes it difficult to detect such flaws and defects in an efficient manner. This work aims to investigate the effectiveness of using dynamic measurements to detect damage to a miniature spring. Due to their small size, traditional instrumentation cannot be used to take measurements on the spring. Instead, the non-contact Laser Doppler Vibrometry technique is investigated. Natural frequencies and operating shapes are measured for a number of springs. These results are compared against springs that have been intentionally flawed to determine if the change in dynamic properties is a reasonable metric for damage detection.

Many methods have been proposed for updating finite element matrices using experimentally derived modal parameters. By using these methods, a finite element model can be made to exactly match the experiment. These techniques have not achieved widespread use in finite element modeling because they introduce non-physical matrices. Recently, Scanning Laser Doppler Vibrometery (SLDV) has enabled finer measurement point resolution and more accurate measurement point placement with no mass loading compared to traditional accelerometer or roving hammer tests. Therefore, it is worth reinvestigating these updating procedures with high-resolution data inputs to determine if they are able to produce finite element models that are suitable for substructuring. A rough finite element model of an Ampair Wind Turbine Blade was created, and a SLDV measurement was performed that measured three-dimensional data at every node on one surface of the blade. This data was used to update the finite element model so that it exactly matched test data. A simple substructuring example of fixing the base of the blade was performed and compared to previously measured fixed-base data.

Experiments are a critical part of the model validation process, and the credibility of the resulting simulations are themselves dependent on the credibility of the experiments. The impact of experimental credibility on model validation occurs at several points through the model validation and uncertainty quantification (MVUQ) process. Many aspects of experiments involved in the development and verification and validation (V&V) of computational simulations will impact the overall simulation credibility. In this document, we define experimental credibility in the context of model validation and decision making. We summarize possible elements for evaluating experimental credibility, sometimes drawing from existing and preliminary frameworks developed for evaluation of computational simulation credibility. The proposed framework is an expert elicitation tool for planning, assessing, and communicating the completeness and correctness of an experiment (“test”) in the context of its intended use—validation. The goals of the assessment are (1) to encourage early communication and planning between the experimentalist, computational analyst, and customer, and (2) the communication of experimental credibility. This assessment tool could also be used to decide between potential existing data sets to be used for validation. The evidence and story of experimental credibility will support the communication of overall simulation credibility.

Differences in impedance are usually observed when components are tested in fixtures at lower levels of assembly from those in which they are fielded. In this work, the Kansas City National Security Campus (KCNSC) test bed hardware geometry is used to explore the sensitivity of the form of the objective function on the adequate reproduction of relevant response characteristics at the next level of assembly. Inverse methods within Sandia National Laboratories’ Sierra/SD code suite along with the Rapid Optimization Library (ROL) are used for identifying an unknown material (variable shear and bulk modulus) distributed across a predefined fixture volume. Comparisons of the results between time-domain based objective functions are presented. The development of the objective functions, solution sensitivity, and solution convergence will be discussed in the context of the practical considerations required for creating a realizable set of test hardware based on the variable-modulus optimized solutions.

In the past decade, multi-axis vibration testing has progressed from its early research stages towards becoming a viable technology which can be used to simulate more realistic environmental conditions. The benefits of multi-axis vibration simulation over traditional uniaxial testing methods have been demonstrated by numerous authors. However, many challenges still exist to best utilize this new technology. Specifically, methods to obtain accurate and reliable multi-axis vibration specifications based on data acquired from field tests is of great interest. Traditional single axis derivation approaches may be inadequate for multi-axis vibration as they may not constrain profiles to adhere to proper cross-axis relationships—they may introduce behavior that is neither controllable nor representative of the field environment. A variety of numerical procedures have been developed and studied by previous authors. The intent of this research is to benchmark the performance of these different methods in a well-controlled lab setting to provide guidance for their usage in a general context. Through a combination of experimental and analytical work, the primary questions investigated are as follows: (1) In the absence of part-to-part variability and changes to the boundary condition, which specification derivation method performs the best? (2) Is it possible to optimize the sensor selection from field data to maximize the quality/accuracy of derived multi-axis vibration specifications? (3) Does the presence of response energy in field data which did not originate due to rigid body motion degrade the accuracy of multi-axis vibration specifications obtained via these derivation methods?

Random vibration tests have been conducted for over 5 decades using vibration machines which excite a test item in uniaxial motion. With the advent of multi shaker test systems, excitation in multiple axes and/or at multiple locations is feasible. For random vibration testing, both the auto spectrum of the individual controls and the cross spectrum, which defines the relationship between the controls, define the test environment. This is a striking contrast to uniaxial testing where only the control auto spectrum is defined. In a vibration test the energy flow proceeds from drive excitation voltages to control acceleration auto and cross spectral densities and finally, to response auto and cross spectral densities. This paper examines these relationships, which are encoded in the frequency response function. Following the presentation of a complete system diagram, examination of the relationships between the excitation and control spectral density matrices is clarified. It is generally assumed that the control auto spectra are known from field measurements, but the control cross spectra may be unknown or uncertain. Given these constraints, control algorithms often prioritize replication of the field auto spectrum. The system dynamics determine the cross spectrum. The Nearly Independent Drive Algorithm, described herein, is one approach. A further issue in Multi Input Multi Response testing is the link between cross spectrum at one set of locations and auto spectra at a second set of locations. The effect of excitation cross spectra on control auto spectra is one important case, encountered in every test. The effect of control cross spectra on response auto spectra is important since we may desire to adjust control cross spectra to achieve some desired response auto spectra. The relationships between cross spectra at one set of locations and auto spectra at another set of locations is examined with the goal of elucidating the advantages and limitations of using control cross spectra to define response auto spectra.

Spatially resolved, line-of-sight measurements of aluminum monoxide emission spectra in laser ablation plasma are used with Abel inversion techniques to extract radial plasma temperatures. Contour mapping of the radially deconvolved signal intensity shows a ring of AlO formation near the plasma boundary with the ambient atmosphere. Simulations of the molecular spectra were coupled with the line profile fitting routines. Temperature results are presented with simultaneous inferences from lateral, asymmetric radial, and symmetric radial AlO spectral intensity profiles. This analysis indicates that shockwave phenomena in the radial profiles, including a temperature drop behind the blast wave created during plasma initiation were measured.

Trajectories of unique particles were tracked using spatially and temporally interlaced single-shot images from multiple views. Synthetic data were investigated to verify the ability of the technique to track particles in three-dimensions and time. The synthetic data was composed of four images from unique perspectives at four instances in time. The analysis presented verifies that under certain circumstances particle trajectories can be mapped in three dimensions from a minimal amount of information, i.e. one image per viewing angle. These results can enable four-dimensional measurements where they may otherwise prove unfeasible.

A collaborative testing and analysis effort investigating the effects of threaded fastener size on load-displacement behavior and failure was conducted to inform the modeling of threaded connections. A series of quasistatic tension tests were performed on #00, #02, #04, #06 and #4 (1/4”) A286 stainless steel fasteners (NAS1351N00-4, NAS1352N02-6, NAS1352N04-8, NAS1352N06-10, and NAS1352N4-24, respectively) to provide calibration and validation data for the analysis portion of the study. The data obtained from the testing series reveals that the size of the fastener may influence the characteristic stress-strain response, as the failure strains and ultimate loads varied between the smaller (#00 and #02) and larger (#04, #06, and #4) fasteners. These results motivated the construction of high-fidelity finite element models to investigate the underlying mechanics of these responses. Two threaded fastener models, one with axisymmetric threads and the other with full 3D helical threads, were calibrated to subsets of the data to compare modeling approaches, analyze fastener material properties, and assess how well these calibrated properties extend to fasteners of varying sizes and if trends exist that can inform future best modeling practices. The modeling results are complemented with a microstructural analysis to further investigate the root cause of size effects observed in the experimentally obtained load-displacement curves. These analyses are intended to inform and guide reduced-order modeling approaches that can be incorporated in system level analyses of abnormal environments where modeling fidelity is limited and each component is not always testable, but models must still capture fastener behavior up to and including failure. This complimentary testing and analysis study identifies differences in the characteristic stress-strain response of varying sized fasteners, provides microstructural evidence to support these variations, evaluates our ability to extrapolate calibrated properties to different sized fasteners, and ultimately further educates the analysis community on the robustness of fastener modeling.

Digital in-line holography techniques for coherent imaging are important for object sizing and tracking applications in multiphase flows and combustion systems. In explosive, supersonic, or hypersonic environments, however, gas-phase shocks impart phase distortions that obscure objects. In this work, we implement phase-conjugate digital in-line holography (PCDIH) with both a picosecond laser and a nanosecond pulse-burst laser for reducing the phase distortions caused by shock-waves. The technique operates by first passing a forward beam of coherent light through the shock-wave phase-distortion. The light then enters a phase-conjugate mirror, created via a degenerate four-wave-mixing process, to produce a return beam with the opposite phase-delay as the forward beam. By passing the return beam back through the phase-distortion, phase delays are canceled producing phase-distortion-free images. This technique enables the measurement of the three-dimensional position and velocity of objects through shock-wave distortions at rates up to 500 kHz. This method is demonstrated in a variety of experiments including imaging supersonic shock-waves, sizing objects through laser-spark plasma-generated shock-waves, and tracking explosively-generated hypersonic fragments.

The simulation of various structural systems often requires accounting for the fasteners holding the distinct parts together. When fasteners are not expected to yield, simple reduced representations like linear springs can be used. However, in analyses of abnormal environments where fastener failure must be accounted for, fasteners are often represented with more detail. One common approach is to mesh the head and the shank of the fastener as smooth cylinders, neglecting the threads (referred to as a plug model). The plug can elicit a nonlinear mechanical response by using an elastic-plastic material model, which can be calibrated to experimental load-displacement curves, typically in pure tension. Fasteners rarely fail exclusively in pure tension, so the study presented here considers current plug modeling practice at multiaxial loadings. Comparisons of this plug model are made to experimental data as well as a higher fidelity model that includes the threads of the fastener. For both models, a multilinear elastic-plastic constitutive model is used, and two different failure models are explored to capture the ultimate failure of the fastener. The load-displacement curves of all three sets of data (the plug model, threaded model, and the experiments) are compared. The comparisons between simulations and experiments contribute to understanding the role of multiaxial loading on fastener response, and motivate future work on improving fastener models that can accurately capture multiaxial failure.

The generation of optimal trajectories for test flights of hypersonic vehicles with highly nonlinear dynamics and complicated physical and path constraints is often time consuming and sometimes intractable for high-fidelity, software-in-the-loop vehicle models. Practical use of hypersonic vehicles requires the ability to rapidly generate a feasible and robust optimal trajectory. We propose a solution that involves interaction between an optimizer using a low fidelity 3-DOF vehicle model and feedback from vehicle simulations of varying fidelities, with the goal of rapidly converging to a solution trajectory for a hypersonic vehicle mission. Further computational efficiency is sought using aerodynamic surrogate models in place of aerodynamic coefficient look-up tables. We address the need for rapidly converging optimization by analyzing how model fidelity choice impacts the quality and speed of the resulting guidance solution.

In computational structural dynamics problems, the ability to calibrate numerical models to physical test data often depends on determining the correct constraints within a structure with mechanical interfaces. These interfaces are defined as the locations within a built-up assembly where two or more disjointed structures are connected. In reality, the normal and tangential forces arising from friction and contact, respectively, are the only means of transferring loads between structures. In linear structural dynamics, a typical modeling approach is to linearize the interface using springs and dampers to connect the disjoint structures, then tune the coefficients to obtain sufficient accuracy between numerically predicted and experimentally measured results. This work explores the use of a numerical inverse method to predict the area of the contact patch located within a bolted interface by defining multi-point constraints. The presented model updating procedure assigns contact definitions (fully stuck, slipping, or no contact) in a finite element model of a jointed structure as a function of contact pressure computed from a nonlinear static analysis. The contact definitions are adjusted until the computed modes agree with experimental test data. The methodology is demonstrated on a C-shape beam system with two bolted interfaces, and the calibrated model predicts modal frequencies with <3% total error summed across the first six elastic modes.

The emerging Al-rich AlGaN-channel Al x Ga1-xN/Al y Ga1-yN high-electron-mobility transistors (HEMTs) with 0.7 ≤ y < x ≤ 1.0 have the potential to greatly exceed the power handling capabilities of today's GaN HEMTs, possibly by five times. This projection is based on the expected 4× enhancement of the critical electric field, the 2× enhancement of sheet carrier density, and the parity of the electron saturation velocity for Al-rich AlGaN-channel HEMTs relative to GaN-channel HEMTs. In this paper, the expected increased RF power density in Al-rich AlGaN-channel HEMTs is calculated by theoretical analysis and computer simulations, based on existing data on long-channel AlGaN devices. It is shown that a saturated power density of 18 W mm-1, a power-added efficiency of 55% and an output third-order intercept point over 40 dB can be achieved for this technology. The method for large-signal RF performance estimation presented in this paper is generic and can be applied to other novel high-power device technologies at the early stages of development.

This paper details a joint numerical and experimental investigation of transition-delaying roughness. A numerical simulation was undertaken to design a surface roughness configuration that would suppress Mack’s 2nd mode instability in order to maintain laminar flow over a Mach 8 hypersonic blunt cone. Following the design process the roughness configuration was implemented on a hypersonic cone test article. Multiple experimental runs at the Mach 8 condition with different Reynolds numbers were run, as well as an off-design Mach 5 condition. The roughness did appear to delay transition in the Mach 8 case as intended, but did not appear to delay transition in the Mach 5 case. Concurrently, simulations of the roughness configuration were also computed for both Mach cases utilizing the experimental conditions. Linear stability theory was applied to the simulations in order to determine their boundary layer stability characteristics. This investigation of multiple cases helps to validate the numerical code with real experimental results as well as provide physical evidence for the transition-delaying roughness phenomenon.

Al-rich AlGaN-channel high electron mobility transistors with 80-nm long gates and 85% (70%) Al in the barrier (channel) were evaluated for RF performance. The dc characteristics include a maximum current of 160 mA/mm with a transconductance of 24 mS/mm, limited by source and drain contacts, and an on/off current ratio of 109. fT of 28.4 GHz and fMAX of 18.5 GHz were determined from small-signal S-parameter measurements. Output power density of 0.38 W/mm was realized at 3 GHz in a power sweep using on-wafer load pull techniques.

A controlled between-groups experiment was conducted to demonstrate the value of human factors for process design. Twenty-four Sandia National Laboratories employees completed a simple visual inspection task simulating receipt inspection. The experimental group process was designed to conform to human factors and visual inspection principles, whereas the control group process was designed without consideration of such principles. Results indicated the experimental group exhibited superior performance accuracy, lower workload, and more favorable usability ratings as compared to the control group. The study provides evidence to help human factors experts revitalize the critical message regarding the benefits of human factors involvement for a new generation of systems engineers.

The excitation of Mg3F2GeO4:Mn thermographic phosphors using a UV LED centered at 365 nm is explored. Two different LED drivers, one available commercially and one built at Sandia National Laboratories (SNL), were used and assessed for their viability for phosphor thermometry utilizing LED excitation and intensified, high-speed, CMOS camera data collection. The SNL-driven LED was then utilized as an excitation source for Mg3F2GeO4:Mn-phosphor calibration and demonstration experiments measuring the temperature of a silicon carbide heating rod using the time-decay method. The results presented here serve as a step toward determining the application space, wherein SNL driven LED excitation would be preferable over the use of laser systems for thermographic phosphor measurements.

With the growth of light field imaging as an emerging diagnostic tool for the measurement of 3D particle fields, various algorithms for 3D particle measurements have been developed. These methods have exploited both the computational refocusing and perspective-shift capabilities of plenoptic imaging. This work continues the development of a 3D particle location method based on perspective-shifted plenoptic images. Specific focus is placed on adaptations that provide increased robustness for variations in and measurement of size and shape characteristics, thus allowing measurements of fragment fields. An experimental data set of non-spherical fragment simulants is studied to examine the dependency of the uncertainty of this perspective-shift based processing method on particle shape and the uncertainty of size measurements of fragments. Synthetic data sets are examined to provide metrics of the relationship between measurement uncertainty that can be achieved using this method, particle density, and processing time requirements.

Poisson's ratio is a material constant representing compressibility of material volume. However, when soft, hyperelastic materials such as silicone foam are subjected to large deformation into densification, the Poisson's ratio may rather significantly change, which warrants careful consideration in modeling and simulation of impact/shock mitigation scenarios where foams are used as isolators. The evolution of Poisson's ratio of silicone foam materials has not yet been characterized, particularly under dynamic loading. In this study, radial and axial measurements of specimen strain are conducted simultaneously during quasi-static and dynamic compression tests to determine the Poisson's ratio of silicone foam. The Poisson's ratio of silicone foam exhibited a transition from compressible to nearly incompressible at a threshold strain that coincided with the onset of densification in the material. Poisson's ratio as a function of engineering strain was different at quasi-static and dynamic rates. The Poisson's ratio behavior is presented and can be used to improve constitutive modeling of silicone foams subjected to a broad range of mechanical loading.

Understanding the dynamic behavior of geomaterials is critical for refining modeling and simulation of applications that involve impacts or explosions. Obtaining material properties of geomaterials is challenging, particularly in tension, due to the brittle and low-strength nature of such materials. Dynamic split tension technique (also called dynamic Brazilian test) has been employed in recent decades to determine the dynamic tensile strength of geomaterials. This is primarily because the split tension method is relatively straightforward to implement in a Kolsky compression bar. Typically, investigators use the peak load reached by the specimen to calculate the tensile strength of the specimen material, which is valid when the specimen is compressed at quasi-static strain rate. However, the same assumption cannot be safely made at dynamic strain rates due to wave propagation effects. In this study, the dynamic split tension (or Brazilian) test technique is revisited. High-speed cameras and digital image correlation (DIC) were used to image the failure of the Brazilian-disk specimen to discover when the first crack occurred relative to the measured peak load during the experiment. Differences of first crack location and time on either side of the sample were compared. The strain rate when the first crack is initiated was also compared to the traditional estimation method of strain rate using the specimen stress history.

To better understand the factors contributing to electromagentic (EM) observables in developed field sites, we examine in detail through finite element analysis the specific effects of casing completion design. The presense of steel casing has long been exploited for improved subsurface interrogation and there is growing interest in remote methods for assessing casing integrity accross a range of geophysical scenarios related to resource development and sequestration/storage activities. Accurate modeling of the casing response to EM stimulation is recognized as relevant, and a difficult computational challenge because of the casing's high conductivity contrast with geomaterials and its relatively small volume fraction over the field scale. We find that casing completion design can have a significant effect on the observed EM fields, especially at zero frequency. This effect appears to originate in the capacitive coupling between inner production casing and the outer surface casing. Furthermore we show that an equivalent “effective conductivity” for the combined surface/production casing system is inadequate for replicating this effect, regardless of whether the casings are grounded to one another or not. Lastly, we show that in situations where this coupling can be ignored and knowledge of casing currents is not required, simplifying the casing as a perfectly conducting line can be an effective strategy for reducing the computational burden in modeling field-scale response.

We seek to develop a fundamental understanding of dynamic strain aging through discovery experiments to inform the development of a dislocation based micromechanical constitutive model that can tie to existing continuum level plasticity and failure analysis tools. Dynamic strain aging (DSA) occurs when dislocation motion is hindered by the repetitive interaction of solute atoms, most frequently interstitials, with dislocation cores. At temperatures where the interstitials are mobile enough, the atmospheres can repeatedly reform, lock, and release dislocations producing a characteristic serrated flow curve. This phenomenon can produce reversals in the expected mechanical behavior of materials with varying strain rate or temperature. Loss of ductility can also occur. Experiments were conducted on various forms of 304L stainless steel over a range of temperatures and strain rates, along with temporally extreme measurements to capture information from the data signals during serrated flow. The experimental approach and observations for some of the test conditions are described herein.

Polymeric foams have been extensively used in shock isolation applications because of their superior shock or impact energy absorption capability. In order to meet the shock isolation requirements, the polymeric foams need to be experimentally characterized and numerically modeled in terms of material response under shock/impact loading and then evaluated with experimental, analytical, and/or numerical efforts. Measurement of the dynamic compressive stress-strain response of polymeric foams has become fundamental to the shock isolation performance. However, radial inertia has become a severe issue when characterizing soft materials. It is even much more complicated and difficult to address the radial inertia effect in soft polymeric foams. In this study, we developed an analytical method to calculate the additional stress induced by radial inertia in a polymeric foam specimen. The effect of changing profile of Poisson’s ratio during deformation on radial inertia was investigated. The analytical results were also compared with experimental results obtained from Kolsky compression bar tests on a silicone foam.

Delaminations are of great concern to any fiber reinforced polymer composite (FRPC) structure. In order to develop the most efficient structure, designers may incorporate hybrid composites to either mitigate the weaknesses in one material or take advantage #of the strengths of another. When these hybrid structures are used at service temperatures outside of the cure temperature, residual stresses can develop at the dissimilar interfaces. These residual stresses impact the initial stress state at the crack tip of any flaw in the structure and govern whether microcracks, or other defects, grow into large scale delaminations. Recent experiments have shown that for certain hybrid layups which are used to determine the strain energy release rate, G, there may be significant temperature dependence on the apparent toughness. While Nairn and Yokozeki believe that this effect may solely be attributed to the release of stored strain energy in the specimen as the crack grows, others point to a change in the inherent mode mixity of the test, like in the classic interface crack between two elastic layers solution given by Suo and Hutchinson. When a crack is formed at the interface of two dissimilar materials, while the external loading, in the case of a double cantilever beam (DCB), is pure mode I, the stress field at the crack tip produces a mixed-mode failure. Perhaps a change in apparent toughness with temperature can be the result of an increase in mode mixity. This study serves to investigate whether the residual stress formed at the bimaterial interface produces a noticeable shift in the strain energy release rate-mode mixing curve.

The concept of progressive failure modeling is an ongoing concern within the composite community. A common approach is to employ a building block approach where constitutive material properties lead to lamina level predictions which then lead to laminate predictions and then up to structural predictions. There are advantages to such an approach, developments can be made within each step and the whole workflow can be updated. However, advancements made at higher length scales can be hampered by insufficient modeling at lower length scales. This can make industry wide evaluations of methodologies more complicated. For instance, significant advances have been made in recent years to strain rate independent failure theories on the lamina level. However, since the Northwestern Theory is stress dependent, for adequate use in a progressive damage model, a similarly robust constitutive model must also be employed to calculate these lamina level stresses. An improper constitutive model could easily cause a valid failure model to produce incorrect results. Also, any global strain rate applied to a multi-directional laminate will produce a spectrum of local lamina level strain rates so it is important for the constitutive law to account for strain rate dependent deformation.

As the complexity of composite laminates rises, the use of hybrid structures and multi-directional laminates, large operating temperature ranges, the process induced residual stresses become a significant factor in the design. In order to properly model the initial stress state of a structure, a solid understanding of the stress free temperature, the temperature at which the initial crosslinks are formed, as well as the contribution of cure shrinkage, must be measured. Many in industry have moved towards using complex cure kinetics models with the assistance of commercial software packages such as COMPRO. However, in this study a simplified residual stress model using the coefficient of thermal expansion (CTE) mismatch and change in temperature from the stress free temperature are used. The limits of this simplified model can only be adequately tested using an accurate measure of the stress free temperature. Only once that is determined can the validity of the simplified model be determined. Various methods were used in this study to test for the stress free temperature and their results are used to validate each method. Two approaches were taken, both involving either cobonded carbon fiber reinforced polymer (CFRP) or glass fiber reinforced polymer (GFRP) to aluminum. The first method used a composite-aluminum plate which was allowed to warp due to the residual stress. The other involved producing a geometrical stable hybrid composite-aluminum cylinder which was then cut open to allow it to spring in. Both methods placed the specimens within an environmental chamber and tracked the residual stress induced deformation as the temperature was ramped beyond the stress free temperature. Both methods revealed a similar stress free temperature that could then be used in future cure modeling simulations.

Poisson’s ratio of soft, hyperelastic foam materials such as silicone foam is typically assumed to be both a constant and a small number near zero. However, when the silicone foam is subjected to large deformation into densification, the Poisson’s ratio may significantly change, which warrants careful and appropriate consideration in modeling and simulation of impact/shock mitigation scenarios. The evolution of the Poisson’s ratio of foam materials has not yet been characterized. In this study, radial and axial measurements of specimen strain are made simultaneously during quasi-static and dynamic compression test on a silicone foam. The Poisson’s ratio was found to exhibit a transition from compressible to nearly incompressible based on strain level and reached different values at quasi-static and dynamic rates.

Understanding the dynamic behavior of geomaterials is critical for refining modeling and simulation of applications that involve impacts or explosions. Obtaining material properties of geomaterials is challenging, particularly in tension, due to the brittle and low-strength nature of such materials. Dynamic split tension technique (also called dynamic Brazilian test) has been employed in recent decades to determine the dynamic tensile strength of geomaterials. This is primarily because the split tension method is relatively straightforward to implement in a Kolsky compression bar. Typically, investigators use the peak load reached by the specimen to calculate the tensile strength of the specimen material, which is valid when the specimen is compressed at quasi-static strain rate. However, the same assumption cannot be safely made at dynamic strain rates due to wave propagation effects. In this study, the dynamic split tension (or Brazilian) test technique is revisited. High-speed cameras and digital image correlation (DIC) were used to image the failure of the Brazilian-disk specimen to discover when the first crack occurred relative to the measured peak load during the experiment. Differences of first crack location and time on either side of the sample were compared. The strain rate when the first crack is initiated was also compared to the traditional estimation method of strain rate using the specimen stress history.

The Sandia Fracture Challenges provide the mechanics community a forum for assessing its ability to predict ductile fracture through a blind, round-robin format where computationalists are asked to predict the deformation and failure of an arbitrary geometry given experimental calibration data. This presentation will cover the three Sandia Fracture Challenges, with emphasis on the third. The third Challenge, issued in 2017, consisted of an additively manufactured 316L stainless steel tensile bar with through holes and internal cavities that could not have been conventionally machined. The volunteer prediction teams were provided extensive materials data from tensile tests of specimens printed on the same build tray to electron backscatter diffraction microstructural maps and micro-computed tomography scans of the Challenge geometry. The teams were asked a variety of questions, including predictions of variability in the resulting fracture response, as the basis for assessment of their predictive capabilities. This presentation will describe the Challenges and compare the experimental results to the predictions, identifying gaps in capabilities, both experimentally and computationally, to inform future investments. The Sandia Fracture Challenge has evolved into the Structural Reliability Partnership, where researchers will create several blind challenges covering a wider variety of topics in structural reliability. This presentation will also describe this new venture.

The Tularosa study was designed to understand how defensive deception-including both cyber and psychological-affects cyber attackers. Over 130 red teamers participated in a network penetration task over two days in which we controlled both the presence of and explicit mention of deceptive defensive techniques. To our knowledge, this represents the largest study of its kind ever conducted on a professional red team population. The design was conducted with a battery of questionnaires (e.g., experience, personality, etc.) and cognitive tasks (e.g., fluid intelligence, working memory, etc.), allowing for the characterization of a “typical” red teamer, as well as physiological measures (e.g., galvanic skin response, heart rate, etc.) to be correlated with the cyber events. This paper focuses on the design, implementation, data, population characteristics, and begins to examine preliminary results.

This report examines the role of interfaces in electronic packaging applications with the focus placed on soldering technology. Materials and processes are described with respect to their roles on the performance and reliability of associated interfaces. The discussion will also include interface microstructures created by coatings and finishes that are frequently used in packaging applications. Numerous examples are cited to illustrate the importance of interfaces in physical and mechanical metallurgy as well as the engineering function of interconnections. Regardless of the specific application, interfaces are non-equilibrium structures, which has important ramifications for the long-term reliability of electronic packaging.

A procedure for determining the joint uncertainty of Arrhenius parameters across multiple combustion reactions of interest is demonstrated. This approach is capable of constructing the joint distribution of the Arrhenius parameters arising from the uncertain measurements performed in specific target experiments without having direct access to the underlying experimental data. The method involves constructing an ensemble of hypothetical data sets with summary statistics consistent with the available information reported by the experimentalists, followed by a fitting procedure that learns the structure of the joint parameter density across reactions using this consistent hypothetical data as evidence. The procedure is formalized in a Bayesian statistical framework, employing maximum-entropy and approximate Bayesian computation methods and utilizing efficient Markov chain Monte Carlo techniques to explore data and parameter spaces in a nested algorithm. We demonstrate the application of the method in the context of experiments designed to measure the rates of selected chain reactions in the H2-O2 system and highlight the utility of this approach for revealing the critical correlations between the parameters within a single reaction and across reactions, as well as for maximizing consistency when utilizing rate parameter information in predictive combustion modeling of systems of interest.

A general formulation of silicon damage metrics and associated energy-dependent response functions relevant to the radiation effects community is provided. Using this formulation, a rigorous quantitative treatment of the energy-dependent uncertainty contributors is performed. This resulted in the generation of a covariance matrix for the displacement kerma, the Norgett-Robinson-Torrens-based damage energy, and the 1-MeV(Si)-equivalent damage function. When a careful methodology is used to apply a reference 1-MeV damage value, the systematic uncertainty in the fast fission region is seen to be removed, and the uncertainty for integral metrics in broad-based fission-based neutron fields is demonstrated to be significantly reduced.

Silicon-on-insulator latch designs and layouts that are robust to multiple-node charge collection are introduced. A general Monte Carlo radiative energy deposition (MRED) approach is used to identify potential single-event susceptibilities associated with different layouts prior to fabrication. MRED is also applied to bound single-event testing responses of standard and dual interlocked cell latch designs. Heavy ion single-event testing results validate new latch designs and demonstrate bounds for standard latch layouts.

Silicon-on-insulator latch designs and layouts that are robust to multiple-node charge collection are introduced. A general Monte Carlo radiative energy deposition (MRED) approach is used to identify potential single-event susceptibilities associated with different layouts prior to fabrication. MRED is also applied to bound single-event testing responses of standard and dual interlocked cell latch designs. Heavy ion single-event testing results validate new latch designs and demonstrate bounds for standard latch layouts.

With the growing interest to explore Jupiter's moons, technologies with +10 Mrad(Si) tolerance are now needed, to survive the Jovian environment. Conductive-bridging random access memory (CBRAM) is a nonvolatile memory that has shown a high tolerance to total ionizing dose (TID). However, it is not well understood how CBRAM behaves in an energetic ion environment where displacement damage (DD) effects may also be an issue. In this paper, the response of CBRAM to 100-keV Li, 1-MeV Ta, and 200-keV Si ion irradiations is examined. Ion bombardment was performed with increasing fluence steps until the CBRAM devices failed to hold their programed state. The TID and DD dose (DDD) at the fluence of failure were calculated and compared against tested ion species. Results indicate that failures are more highly correlated with TID than DDD. DC cycling tests were performed during 100-keV Li irradiations and evidence was found that the mobile Ag ion supply diminished with increasing fluence. The cycling results, in addition to prior 14-MeV neutron work, suggest that DD may play a role in the eventual failure of a CBRAM device in a combined radiation environment.

Sampling of drinking water distribution systems is performed to ensure good water quality and protect public health. Sampling also satisfies regulatory requirements and is done to respond to customer complaints or emergency situations. Water distribution system modeling techniques can be used to plan and inform sampling strategies. However, a high degree of accuracy and confidence in the hydraulic and water quality models is required to support real-time response. One source of error in these models is related to uncertainty in model input parameters. Effective characterization of these uncertainties and their effect on contaminant transport during a contamination incident is critical for providing confidence estimates in model-based design and evaluation of different sampling strategies. In this paper, the effects of uncertainty in customer demand, isolation valve status, bulk reaction rate coefficient, contaminant injection location, start time, duration, and rate on the size and location of the contaminant plume are quantified for two example water distribution systems. Results show that the most important parameter was the injection location. The size of the plume was also affected by the reaction rate coefficient, injection rate, and injection duration, whereas the exact location of the plume was additionally affected by the isolation valve status. Uncertainty quantification provides a more complete picture of how contaminants move within a water distribution system and more information when using modeling results to select sampling locations.

We present an approach to the development and evaluation of environmental stress screening (ESS) for a dormant-storage, multi-shot component. The ESS is developed to precipitate and detect latent manufacturing defects without significantly degrading the component's probability of successful function under normal operating environments. The evaluation of the ESS is achieved by using an additional strength of screen (SOS) operation to test for escapes from the screen. The resulting data are pass/fail data only, because the characteristics of this type of component do not allow a standard 'time to failure' analysis. The calculated SOS efficiency f is then used to estimate initial field 'reliability.' We illustrate the use of the methodology with a case study involving an electrical component manufactured within the Nuclear Security Enterprise (NSE). In development and qualification, twelve failures were detected by the ESS, and the SOS operations detected one escape. The resulting analysis showed the SOS efficiency to be approximately 92%, adequate for the component reliability goal. The resulting initial field reliability was estimated to be 99.3%, acceptable for this electrical component. Failure investigations were conducted to determine the root cause of each of these failures. Information from these investigations resulted in changes to the manufacturing process to eliminate or minimize the reoccurrence of these failures. The number of ESS failures have been reduced, and no additional failures have been observed at the SOS operation.

We present an approach to the development and evaluation of environmental stress screening (ESS) for a dormant-storage, multi-shot component. The ESS is developed to precipitate and detect latent manufacturing defects without significantly degrading the component's probability of successful function under normal operating environments. The evaluation of the ESS is achieved by using an additional strength of screen (SOS) operation to test for escapes from the screen. The resulting data are pass/fail data only, because the characteristics of this type of component do not allow a standard 'time to failure' analysis. The calculated SOS efficiency f is then used to estimate initial field 'reliability.' We illustrate the use of the methodology with a case study involving an electrical component manufactured within the Nuclear Security Enterprise (NSE). In development and qualification, twelve failures were detected by the ESS, and the SOS operations detected one escape. The resulting analysis showed the SOS efficiency to be approximately 92%, adequate for the component reliability goal. The resulting initial field reliability was estimated to be 99.3%, acceptable for this electrical component. Failure investigations were conducted to determine the root cause of each of these failures. Information from these investigations resulted in changes to the manufacturing process to eliminate or minimize the reoccurrence of these failures. The number of ESS failures have been reduced, and no additional failures have been observed at the SOS operation.

Abstract not provided.

Apparent char kinetic rates are commonly used to predict pulverized coal char burning rates. These kinetic rates quantify the char burning rate based on the temperature of the particle and the oxygen concentration at the external particle surface, inherently neglecting the impact of variations in the internal diffusion rate and penetration of oxygen. To investigate the impact of bulk gas diffusivity on these phenomena during Zone II burning conditions, experimental measurements were performed of char particle combustion temperature and burnout for a subbituminous coal burning in an optical entrained flow reactor with helium and nitrogen diluents. The combination of much higher thermal conductivity and mass diffusivity in the helium environments resulted in cooler char combustion temperatures than in equivalent N2 environments. Measured char burnout was similar in the two environments for a given bulk oxygen concentration but was approximately 60% higher in helium environments for a given char combustion temperature. To augment the experimental measurements, detailed particle simulations of the experimental conditions were conducted with the SKIPPY code. These simulations also showed a 60% higher burning rate in the helium environments for a given char particle combustion temperature. To differentiate the effect of enhanced diffusion through the external boundary layer from the effect of enhanced diffusion through the particle, additional SKIPPY simulations were conducted under selected conditions in N2 and He environments for which the temperature and concentrations of reactants (oxygen and steam) were identical on the external char surface. Under these conditions, which yield matching apparent char burning rates, the computed char burning rate for He was 50% larger, demonstrating the potential for significant errors with the apparent kinetics approach. However, for specific application to oxy-fuel combustion in CO2 environments, these results suggest the error to be as low as 3% when applying apparent char burning rates from nitrogen environments.

In the context of the DARPA funded project SEQUOIA we are interested in the design under uncertainty of a jet engine nozzle subject to the performance requirements of a reconnaissance mission for a small unmanned military aircraft. This design task involves complex and expensive aero-thermo-structural computational analyses where it is of a paramount importance to also include the effect of the uncertain variables to obtain reliable predictions of the device’s performance. In this work we focus on the forward propagation analysis which is a key part of the design under uncertainty workflow. This task cannot be tackled directly by means of single fidelity approaches due to the prohibitive computational cost associated to each realization. We report here a summary of our latest advancement regarding several multilevel and multifidelity strategies designed to alleviate these challenges. The overall goal of these techniques is to reduce the computational cost of analyzing a high-fidelity model by resorting to less accurate, but less computationally demanding, lower fidelity models. The features of these multifidelity UQ approaches are initially illustrated and demonstrated on several model problems and afterward for the aero-thermo-structural analysis of the jet engine nozzle.

The generation of optimal trajectories for test flights of hypersonic vehicles with highly nonlinear dynamics and complicated physical and path constraints is often time consuming and sometimes intractable for high-fidelity, software-in-the-loop vehicle models. Practical use of hypersonic vehicles requires the ability to rapidly generate a feasible and robust optimal trajectory. We propose a solution that involves interaction between an optimizer using a low fidelity 3-DOF vehicle model and feedback from vehicle simulations of varying fidelities, with the goal of rapidly converging to a solution trajectory for a hypersonic vehicle mission. Further computational efficiency is sought using aerodynamic surrogate models in place of aerodynamic coefficient look-up tables. We address the need for rapidly converging optimization by analyzing how model fidelity choice impacts the quality and speed of the resulting guidance solution.

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Ammonia and amines are emitted into the troposphere by various natural and anthropogenic sources, where they have a significant role in aerosol formation. Here, we explore the significance of their removal by reaction with Criegee intermediates, which are produced in the troposphere by ozonolysis of alkenes. Rate coefficients for the reactions of two representative Criegee intermediates, formaldehyde oxide (CH2OO) and acetone oxide ((CH3)2COO) with NH3 and CH3NH2 were measured using cavity ring-down spectroscopy. Temperature-dependent rate coefficients, k(CH2OO + NH3) = (3.1 ± 0.5) × 10-20T2exp(1011 ± 48/T) cm3 s-1 and k(CH2OO + CH3NH2) = (5 ± 2) × 10-19T2exp(1384 ± 96/T) cm3 s-1 were obtained in the 240 to 320 K range. Both the reactions of CH2OO were found to be independent of pressure in the 10 to 100 Torr (N2) range, and average rate coefficients k(CH2OO + NH3) = (8.4 ± 1.2) × 10-14 cm3 s-1 and k(CH2OO + CH3NH2) = (5.6 ± 0.4) × 10-12 cm3 s-1 were deduced at 293 K. An upper limit of ≤2.7 × 10-15 cm3 s-1 was estimated for the rate coefficient of the (CH3)2COO + NH3 reaction. Complementary measurements were performed with mass spectrometry using synchrotron radiation photoionization giving k(CH2OO + CH3NH2) = (4.3 ± 0.5) × 10-12 cm3 s-1 at 298 K and 4 Torr (He). Photoionization mass spectra indicated production of NH2CH2OOH and CH3N(H)CH2OOH functionalized organic hydroperoxide adducts from CH2OO + NH3 and CH2OO + CH3NH2 reactions, respectively. Ab initio calculations performed at the CCSD(T)(F12∗)/cc-pVQZ-F12//CCSD(T)(F12∗)/cc-pVDZ-F12 level of theory predicted pre-reactive complex formation, consistent with previous studies. Master equation simulations of the experimental data using the ab initio computed structures identified submerged barrier heights of -2.1 ± 0.1 kJ mol-1 and -22.4 ± 0.2 kJ mol-1 for the CH2OO + NH3 and CH2OO + CH3NH2 reactions, respectively. The reactions of NH3 and CH3NH2 with CH2OO are not expected to compete with its removal by reaction with (H2O)2 in the troposphere. Similarly, losses of NH3 and CH3NH2 by reaction with Criegee intermediates will be insignificant compared with reactions with OH radicals.

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The excitation of Mg3F2GeO4:Mn thermographic phosphors using a UV LED centered at 365 nm is explored. Two different LED drivers, one available commercially and one built at Sandia National Laboratories (SNL), were used and assessed for their viability for phosphor thermometry utilizing LED excitation and intensified, high-speed, CMOS camera data collection. The SNL-driven LED was then utilized as an excitation source for Mg3F2GeO4:Mn-phosphor calibration and demonstration experiments measuring the temperature of a silicon carbide heating rod using the time-decay method. The results presented here serve as a step toward determining the application space, wherein SNL driven LED excitation would be preferable over the use of laser systems for thermographic phosphor measurements.

Abstract not provided.

Montmorillonite with an empirical formula of Na0.2Ca0.1Al2Si4O10(OH)2(H2O)10 is a di-octahedral smectite. Montmorillonite-rich bentonite is a primary buffer candidate for high level nuclear waste (HLW) and used nuclear fuel to be disposed in mild environments. In such environments, temperatures are expected to be ≤ 90oC, the solutions are of low ionic strengths, and pH is close to neutral. Under the conditions outside the above parameters, the performance of montmorillonite-rich bentonite is deteriorated because of collapse of swelling particles as a result of illitization, and dissolution of the swelling clay minerals followed by precipitation of non-swelling minerals. It has been well known that tri-octahedral smectites such as saponite, with an ideal formula of Mg3(Si, Al)4O10(OH)2•4H2O for an Mg-end member (saponite-15A), are less susceptible to alteration under harsh conditions. Recently, Mg-bearing saponite has been favorably considered as a preferable engineered buffer material for the Swedish very deep holes (VDH) disposal concept in crystalline rock formations. In the VDH, HLW is disposed in deep holes at depth between 2,000 m and 4,000 m. At such deployment depths, the temperatures are expected to be between 100oC and 150oC, and the groundwater is of high ionic strength. The harsh chemical conditions of high pH are also introduced by the repository designs in which concretes and cements are used as plugs and buffers. In addition, harsh chemical conditions introduced by high ionic strength solutions are also present in repository designs in salt formations and sedimentary basins. For instance, the two brines associated with the salt formations for the Waste Isolation Pilot Plant (WIPP) in USA have ionic strengths of 5.82 mol•kg-1 (ERDA-6) and 8.26 mol•kg-1 (GWB). In the Asse site proposed for a geological repository in salt formations in Germany, the Q-brine has an ionic strength of ~13 mol•kg-1. In this work, we present our investigations regarding the stability of saponite under hydrothermal conditions in harsh environments.

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Geogenic noble gases are contained in crustal rocks at inter- and intracrystalline sites. In this study, bedded rock salt from southern New Mexico was deformed in a variety of triaxial compression states while measuring the release of naturally contained helium and argon utilizing mass spectrometry. Noble gas release is empirically correlated to volumetric strain and acoustic emissions. At low confining pressures, rock salt deforms primarily by microfracturing, rupturing crystal grains, and releasing helium and argon with a large amount of acoustic emissions, both measured real-time. At higher confining pressure, microfracturing is reduced and the rock salt is presumed to deform more by intracrystalline flow, releasing less amounts of noble gases with fewer acoustic emissions. Our work implies that geogenic gas release during deformation may provide an additional signal which contains information on the type and amount of deformation occurring in a variety of earth systems.

Abstract not provided.

Falling particle receivers (FPRs) are an important component of future falling particle concentrating solar power plants to enable next-generation energy generation. High thermal efficiencies in a FPR are required to high thermodynamic efficiencies of the system. External winds can significantly impact the thermal performance of cavity-type FPRs primarily through changing the air flow in and out of the aperture. A numerical parametric study is performed in this paper to quantify the effect of wind on the thermal performance of a FPR. Wind direction was found to be a significant parameter that can affect the receiver thermal efficiency. The particle mass flow rate did not significantly change the overall effect of wind on the receiver. The receiver efficiency was strong function of the particle diameter, but this was primarily a result of varying curtain opacity with different diameters and not from varying effects with wind. Finally, the model was used to demonstrate that receiver efficiencies of 90% were achievable under the assumption that the effect of wind/advective losses were mitigated.

In order to improve the accuracy of subsurface target classification with ground penetrating radar (GPR) systems, it is desired to transmit and receive ultra-wide band pulses with varying combinations of polarization (a technique referred to as polarimetry). The sinuous antenna exhibits such desirable properties as ultra-wide bandwidth, polarization diversity, and low-profile form factor, making it an excellent candidate for the radiating element of such systems. However, sinuous antennas are dispersive since the active region moves with frequency along the structure, resulting in the distortion of radiated pulses. This distortion may be compensated in signal processing with accurately simulated or measured antenna phase information. However, in a practical GPR, the antenna performance may deviate from that simulated, accurate measurements may be impractical, and/or the dielectric loading of the environment may cause deviations. In such cases, it may be desirable to employ a simple dispersion model based on antenna design parameters which may be optimized in situ. This paper explores the dispersive properties of the sinuous antenna and presents a simple, adjustable, model that may be used to correct dispersed pulses. The dispersion model is successfully applied to both simulated and measured scenarios, thereby enabling the use of sinuous antennas in polarimetric GPR applications.

The wave energy resource for U.S. coastal regions has been estimated at approximately 1,200 TWh/ yr (EPRI 2011). The magnitude is comparable to the natural gas and coal energy generation. Although the wave energy industry is relatively new from a commercial perspective, wave energy conversion (WEC) technology is developing at an increasing pace. Ramping up to commercial scale deployment of WEC arrays requires demonstration of performance that is economically competitive with other energy generation methods. The International Electrotechnical Commission has provided technical specifications for developing wave energy resource assessments and characterizations, but it is ultimately up to developers to create pathways for making a specific site competitive. The present study uses example sites to evaluate the annual energy production using different wave energy conversion strategies and examines pathways available to make WEC deployments competitive. The wave energy resource is evaluated for sites along the U.S. coast and combinations of wave modeling and basic resource assessments determine factors affecting the cost of energy at these sites. The results of this study advance the understanding of wave resource and WEC device assessment required to evaluate commercial-scale deployments.

Falling particle receivers are an emerging technology for use in concentrating solar power systems. In this work, quartz tubes cut in half to form tube shells (referred to as quartz half-shells) are investigated for use as a full or partial aperture cover to reduce radiative and advective losses from the receiver. A receiver subdomain and surrounding air volume are modeled using ANSYS® Fluent®. The model is used to simulate fluid dynamics and heat transfer for the following cases: (1) open aperture, (2) aperture fully covered by quartz half-shells, and (3) aperture partially covered by quartz half-shells. We compare the percentage of total incident solar power lost due to conduction through the receiver walls, advective losses through the aperture, and radiation exiting out of the aperture. Contrary to expected outcomes, simulation results using the simplified receiver subdomain show that quartz aperture covers can increase radiative losses and, in the partially covered case, also increase advective losses. These increased heat losses are driven by elevated quartz half-shell temperatures and have the potential to be mitigated by active cooling and/or material selection.

Advances in machine intelligence have sparked interest in hardware accelerators to implement these algorithms, yet embedded electronics have stringent power, area budgets, and speed requirements that may limit non- volatile memory (NVM) integration. In this context, the development of fast nanomagnetic neural networks using minimal training data is attractive. Here, we extend an inference-only proposal using the intrinsic physics of domain-wall MTJ (DW-MTJ) neurons for online learning to implement fully unsupervised pattern recognition operation, using winner-take-all networks that contain either random or plastic synapses (weights). Meanwhile, a read-out layer trains in a supervised fashion. We find our proposed design can approach state-of-the-art success on the task relative to competing memristive neural network proposals, while eliminating much of the area and energy overhead that would typically be required to build the neuronal layers with CMOS devices.

Sandia National Laboratories has developed a model characterizing the nonlinear encoding operator of the world's first hyperspectral x-ray computed tomography (H-CT) system as a sequence of discrete-to-discrete, linear image system matrices across unique and narrow energy windows. In fields such as national security, industry, and medicine, H-CT has various applications in the non-destructive analysis of objects such as material identification, anomaly detection, and quality assurance. However, many approaches to computed tomography (CT) make gross assumptions about the image formation process to apply post-processing and reconstruction techniques that lead to inferior data, resulting in faulty measurements, assessments, and quantifications. To abate this challenge, Sandia National Laboratories has modeled the H-CT system through a set of point response functions, which can be used for calibration and anaylsis of the real-world system. This work presents the numerical method used to produce the model through the collection of data needed to describe the system; the parameterization used to compress the model; and the decompression of the model for computation. By using this linear model, large amounts of accurate synthetic H-CT data can be efficiently produced, greatly reducing the costs associated with physical H-CT scans. Furthermore, successfully approximating the encoding operator for the H-CT system enables quick assessment of H-CT behavior for various applications in high-performance reconstruction, sensitivity analysis, and machine learning.

Abstract not provided.

Ionic liquids are a unique class of materials with several potential applications in electrochemical energy storage. When used in electrolytes, these highly coordinating solvents can influence device performance through their high viscosities and strong solvation behaviors. In this work, we explore the effects of pyrrolidinium cation structure and Li+ concentration on transport processes in ionic liquid electrolytes. We present correlated experimental measurements and molecular simulations of Li+ mobility and O2 diffusivity, and connect these results to dynamic molecular structural information and device performance. In the context of Li-O2/Li-air battery chemistries, we find that Li+ mobility is largely influenced by Li+-anion coordination, but that both Li+ and O2 diffusion may be affected by variations of the pyrrolidinium cation and Li+ concentration.

Batteries for grid storage applications must be inexpensive, safe, reliable, as well as have a high energy density. Here, we utilize the high capacity of sulfur (S) (1675 mAh g-1, based on the idealized redox couple of S2./S) in order to demonstrate for the first time, a reversible high capacity solid-state S-based cathode for alkaline batteries. To maintain S in the solid-state, it is bound to copper (Cu), initially in its fully reduced state as the sulfide. Upon charging, the sulfide is oxidized to a polysulfide species which is captured and maintained in the solid-state by the Cu ions. This solid-state sulfide/polysulfide cathode was analyzed versus a zinc (Zn) anode which gives a nominal >1.2 V cell voltage based on the sulfide/polysulfide redox cathode chemistry. It was found that in order for the S cathode to have the best cycle life in the solid-state it must not only be bound to Cu ions but bound to Cu ions in the +1 valence state, forming Cu2S as a discharge product. Zn/Cu2S batteries cycled between 1.45 V and 0.4 V vs. Zn displayed capacities of 1500 mAh g-1 (based on mass of S) or i300 mAh g-1 (based on mass of Cu2S) and high areal (>23 mAh cm.2) and energy densities (>135 Wh L-1), but suffered from moderate cycle lifes (<250 cycles). The failure mechanism of this electrode was found to be disproportionation of the charged S species into irreversible sulfite releasing the bound Cu ions. The Cu ions become free to perform Cu specific redox reactions which slowly changes the battery redox chemistry from that of S to that of Cu with a S additive. Batteries utilizing the Cu2S cathode and a 50% depth of charge (DOC) cathode cycling protocol, with 5 wt% Na2S added to the electrolyte, retained a cathode capacity of 838 mAh g-1 (based on the mass of S) or 169 mA h g-1 (based on mass of Cu2S) after 450 cycles with >99.7% coulombic efficiency. These Zn/Cu2S batteries provided a grid storage relevant energy density of >42Wh L-1 (at 65 wt% Cu2S loading), despite only using a 3% depth of discharge (DOD) for the Zn anode. This work opens the way to a new class of energy dense grid storage batteries based on high capacity solid-state S-based cathodes.

Historically, “skill-of-the-craft” was the single measure of job qualification. In those days, no one gave workers a procedure to follow. Today, large complex industries rely on procedures as a way of ensuring the job will be performed reliably and safely. Typically, these procedures provide a layer of protection to mitigate the severity of an accident or prevent it from happening. While paper-based procedures have long been the standard way of doing business, there is increasing interest in replacing this format with Computer-Based Procedures. Though, the transition from paper to paperless can be more problematic than it seems. Some issues that have led to these problems are discussed here. It is hoped that, by knowing what these issues are, the same mistakes will not be repeated in the future. Mistake avoidance begins with a well-defined set of user requirements for the proposed system. Plus, it is important to realize that Computer-Based Procedures are likely going to be placed in a facility that has never used this type of technology before. As for any new technology, a new way of thinking must come with it. Otherwise, if attempts are made to intermingle old ideas with new ways of doing business, problems are destined to occur.

Neuromorphic computers could overcome efficiency bottlenecks inherent to conventional computing through parallel programming and readout of artificial neural network weights in a crossbar memory array. However, selective and linear weight updates and <10-nanoampere read currents are required for learning that surpasses conventional computing efficiency. We introduce an ionic floating-gate memory array based on a polymer redox transistor connected to a conductive-bridge memory (CBM). Selective and linear programming of a redox transistor array is executed in parallel by overcoming the bridging threshold voltage of the CBMs. Synaptic weight readout with currents <10 nanoamperes is achieved by diluting the conductive polymer with an insulator to decrease the conductance. The redox transistors endure >1 billion write-read operations and support >1-megahertz write-read frequencies.

When attempting to integrate single-molecule fluorescence microscopy with microfabricated devices such as microfluidic channels, fabrication constraints may prevent using traditional coverslips. Instead, the fabricated devices may require imaging through material with a different thickness or index of refraction. Altering either can easily reduce the quality of the image formation (measured by the Strehl ratio) by a factor of 2 or more, reducing the signal-to-noise ratio accordingly. In such cases, successful detection of single-molecule fluorescence may prove difficult or impossible. Here we provide software to calculate the effect of non-design materials upon the Strehl ratio or ensquared energy and explore the impact of common materials used in microfabrication.

International nuclear safeguards inspectors visit nuclear facilities to assess their compliance with international nonproliferation agreements. Inspectors note whether anything unusual is happening in the facility that might indicate the diversion or misuse of nuclear materials, or anything that changed since the last inspection. They must complete inspections under restrictions imposed by their hosts, regarding both their use of technology or equipment and time allotted. Moreover, because inspections are sometimes completed by different teams months apart, it is crucial that their notes accurately facilitate change detection across a delay. The current study addressed these issues by investigating how note-taking methods (e.g., digital camera, hand-written notes, or their combination) impacted memory in a delayed recall test of a complex visual array. Participants studied four arrays of abstract shapes and industrial objects using a different note-taking method for each, then returned 48–72Â h later to complete a memory test using their notes to identify objects changed (e.g., location, material, orientation). Accuracy was highest for both conditions using a camera, followed by hand-written notes alone, and all were better than having no aid. Although the camera-only condition benefitted study times, this benefit was not observed at test, suggesting drawbacks to using just a camera to aid recall. Change type interacted with note-taking method; although certain changes were overall more difficult, the note-taking method used helped mitigate these deficits in performance. Finally, elaborative hand-written notes produced better performance than simple ones, suggesting strategies for individual note-takers to maximize their efficacy in the absence of a digital aid.

This work proposes a space-time least-squares Petrov-Galerkin (ST-LSPG) projection method for model reduction of nonlinear dynamical systems. In contrast to typical nonlinear model-reduction methods that first apply (Petrov-)Galerkin projection in the spatial dimension and subsequently apply time integration to numerically resolve the resulting low-dimensional dynamical system, the proposed method applies projection in space and time simultaneously. To accomplish this, the method first introduces a low-dimensional space-time trial subspace, which can be obtained by computing tensor decompositions of state-snapshot data. The method then computes discreteoptimal approximations in this space-time trial subspace by minimizing the residual arising after time discretization over all space and time in a weighted ℓ2-norm. This norm can be defined to enable complexity reduction (i.e., hyper-reduction) in time, which leads to space-time collocation and space-time Gauss-Newton with Approximated Tensors (GNAT) variants of the ST-LSPG method. Advantages of the approach relative to typical spatial-projection-based nonlinear model reduction methods such as Galerkin projection and least-squares Petrov-Galerkin projection include a reduction of both the spatial and temporal dimensions of the dynamical system, and a priori error bounds that bound the solution error by the best space-time approximation error and whose stability constants exhibit slower growth in time. Numerical examples performed on model problems in fluid dynamics demonstrate the ability of the method to generate orders-of-magnitude computational savings relative to spatial-projection-based reduced-order models without sacrificing accuracy for a fixed spatio-temporal discretization.

Mining rock salt results in subsurface damage, which may affect the strength because of applied stress, anisotropy, and deformation rate. In this study, we used a Kolsky compression bar to measure the high strain rate response of bedded and domal salt at strain rates up to approximately 50 s−1 in parallel and perpendicular directions to bedding or foliation direction depending on rock salt type. Both types of salt exhibited a negative strain rate effect wherein a decrease in strength was observed with increasing strain rate compared to strength measured in the quasi-static regime. Both materials exhibited strength anisotropy. Fracturing and microfracturing were the dominant deformation mechanisms. High pore pressures and frictional heating due to the high loading rate may have contributed to reduction in strength.

Photoelectrochemical (PEC) water splitting has the potential to significantly reduce the costs associated with electrochemical hydrogen production through the direct utilization of solar energy. Many PEC cells utilize liquid electrolytes that are detrimental to the durability of the photovoltaic (PV) or photoactive materials at the heart of the device. The membrane-electrode-assembly (MEA) style, PEC cell presented herein is a deviation from that paradigm as a solid electrolyte is used, which allows the use of a water vapor feed. The result of this is a correspondent reduction in the amount of liquid and electrolyte contact with the PV, thereby opening the possibility of longer PEC device lifetimes. In this study, we demonstrate the operation of a liquid and vapor-fed PEC device utilizing a commercial III-V photovoltaic that achieves a solar-to-hydrogen (STH) efficiency of 7.5% (12% as a PV-electrolyzer). While device longevity using liquid water was limited to less than 24 hours, replacement of reactant with water vapor permitted 100 hours of continuous operation under steady-state conditions and diurnal cycling. Key findings include the observations that the exposure of bulk water or water vapor to the PV must be minimized, and that operating in mass-transport limited regime gave preferable performance.

Advancements in micro-scale additive manufacturing techniques have made it possible to fabricate intricate architectures including 3D interpenetrating electrode microstructures. A mesoscale electrochemical lithium-ion battery model is presented and implemented in the PETSc software framework using a finite volume scheme. The model is used to investigate interpenetrating 3D electrode architectures that offer potential energy density and power density improvements over traditional particle bed battery geometries. Using the computational model, a variety of battery electrode geometries are simulated and compared across various battery discharge rates and length scales to quantify performance trends and investigate geometrical factors that improve battery performance. The energy density vs. power density relationship of the electrode microstructures are compared in several ways, including a uniform surface area to volume ratio comparison as well as a comparison requiring a minimum manufacturable feature size. Significant performance improvements over traditional particle-bed electrode designs are predicted, and electrode microarchitectures derived from minimal surfaces are shown to be superior under a minimum feature size constraint, especially when subjected to high discharge currents. An average Thiele modulus formulation is presented as a back-of-the-envelope calculation to predict the performance trends of microbattery electrode geometries.

Progress in modern biology is being driven, in part, by the large amounts of freely available data in public resources such as the International Nucleotide Sequence Database Collaboration (INSDC), the world's primary database of biological sequence (and related) information. INSDC and similar databases have dramatically increased the pace of fundamental biological discovery and enabled a host of innovative therapeutic, diagnostic, and forensic applications. However, as high-value, openly shared resources with a high degree of assumed trust, these repositories share compelling similarities to the early days of the Internet. Consequently, as public biological databases continue to increase in size and importance, we expect that they will face the same threats as undefended cyberspace. There is a unique opportunity, before a significant breach and loss of trust occurs, to ensure they evolve with quality and security as a design philosophy rather than costly "retrofitted" mitigations. This Perspective surveys some potential quality assurance and security weaknesses in existing open genomic and proteomic repositories, describes methods to mitigate the likelihood of both intentional and unintentional errors, and offers recommendations for risk mitigation based on lessons learned from cybersecurity.

DNA structural transitions facilitate genomic processes, mediate drug-DNA interactions, and inform the development of emerging DNA-based biotechnology such as programmable materials and DNA origami. While some features of DNA conformational changes are well characterized, fundamental information such as the orientations of the DNA base pairs is unknown. Here, we use concurrent fluorescence polarization imaging and DNA manipulation experiments to probe the structure of S-DNA, an elusive, elongated conformation that can be accessed by mechanical overstretching. To this end, we directly quantify the orientations and rotational dynamics of fluorescent DNA-intercalated dyes. At extensions beyond the DNA overstretching transition, intercalators adopt a tilted (q ~ 54°) orientation relative to the DNA axis, distinct from the nearly perpendicular orientation (q ~ 90°) normally assumed at lower extensions. These results provide the first experimental evidence that S-DNA has substantially inclined base pairs relative to those of the standard (Watson-Crick) B-DNA conformation.

Gold deposition on rotating disk electrodes, Bi3+ adsorption on planar Au films and superconformal Au filling of trenches up to 45 μm deep are examined in Bi3+-containing Na3Au(SO3)2 electrolytes with pH between 9.5 and 11.5. Higher pH is found to increase the potential-dependent rate of Bi3+ adsorption on planar Au surfaces, shortening the incubation period that precedes active Au deposition on planar surfaces and bottom-up filling in patterned features. Decreased contact angles between the Au seeded sidewalls and bottom-up growth front also suggest improved wetting. The bottom-up filling dynamic in trenches is, however, lost at pH 11.5. The impact of Au concentration, 80 mmol/L versus 160 mmol/L Na3Au(SO3)2, on bottom-up filling is examined in trenches up to ≈ 210 μm deep with aspect ratio of depth/width ≈ 30. The microstructures of void-free, bottom-up filled trench arrays used as X-ray diffraction gratings are characterized by scanning electron microscopy (SEM) and Electron Backscatter Diffraction (EBSD), revealing marked spatial variation of the grain size and orientation within the filled features.

We provide an overview of the experimental techniques, measurement modalities, and diverse applications of the quantum diamond microscope (QDM). The QDM employs a dense layer of fluorescent nitrogen-vacancy (NV) color centers near the surface of a transparent diamond chip on which a sample of interest is placed. NV electronic spins are coherently probed with microwaves and optically initialized and read out to provide spatially resolved maps of local magnetic fields. NV fluorescence is measured simultaneously across the diamond surface, resulting in a wide-field, two-dimensional magnetic field image with adjustable spatial pixel size set by the parameters of the imaging system. NV measurement protocols are tailored for imaging of broadband and narrowband fields, from DC to GHz frequencies. Here we summarize the physical principles common to diverse implementations of the QDM and review example applications of the technology in geoscience, biology, and materials science.

Tin-germanium alloys are increasingly of interest as optoelectronic and thermoelectric materials as well as materials for Li/Na ion battery electrodes. However, the lattice incompatibility of bulk Sn and Ge makes creating such alloys challenging. By exploiting the unique strain tolerance of nanosized crystals, we have developed a facile synthetic method for homogeneous SnxGe1-x alloy nanocrystals with composition varying from essentially pure Ge to 95% Sn while still maintaining the cubic structure.

An electrodeposition process for void-free bottom-up filling of sub-millimeter scale through silicon vias (TSVs) with Cu is detailed. The 600 μm deep and nominally 125 μm diameter metallized vias were filled with Cu in less than 7 hours under potentiostatic control. The electrolyte is comprised of 1.25 mol/L CuSO4 - 0.25 mol/L CH3SO3H with polyether and halide additions that selectively suppress metal deposition on the free surface and side walls. A brief qualitative discussion of the procedures used to identify and optimize the bottom-up void-free feature filling is presented.

Understanding the impact of distributed photovoltaic (PV) resources on various elements of the distribution feeder is imperative for their cost effective integration. A year-long quasi-static time series (QSTS) simulation at 1-second granularity is often necessary to fully study these impacts. However, the significant computational burden associated with running QSTS simulations is a major challenge to their adoption. In this paper, we propose a fast scalable QSTS simulation algorithm that is based on a linear sensitivity model for estimating voltage-related PV impact metrics of a three-phase unbalanced, nonradial distribution system with various discrete step control elements including tap changing transformers and capacitor banks. The algorithm relies on computing voltage sensitivities while taking into account all the effects of discrete controllable elements in the circuit. Consequently, the proposed sensitivity model can accurately estimate the state of controllers at each time step and the number of control actions throughout the year. For the test case of a real distribution feeder with 2969 buses (5469 nodes), 6 load/PV time series power profiles, and 9 voltage regulating elements including controller delays, the proposed algorithm demonstrates a dramatic time reduction, more than 180 times faster than traditional QSTS techniques.

The curing of diglycidyl ether of bisphenol A (DGEBA) epoxy with diethanolamine (DEA) is studied. DEA has three reactive groups, a secondary amine hydrogen and two hydroxyls. The secondary amine reacts rapidly, forming an adduct containing tertiary amines, epoxides and hydroxyls. The epoxides and hydroxyls then react in the presence of the amines to crosslink and vitrify the epoxy in the “gelation” reaction. The gelation reaction, the subject of this study, is not simple. The reaction exhibits unusual dependencies on both temperature and degree of cure. Previously, the general mechanisms of this curing process were explored by a number of us. In the present paper, both differential scanning calorimetry (DSC) and isothermal microcalorimetry (IMC) are used to determine a number of characteristic times associated with the reaction. The characteristic times show that the reaction rate has different functional forms at different temperatures and extents of reaction. This results from the reaction rate not depending solely upon the temperature and over-all extent-of-reaction. The concentration of a number of auxiliary reactive species that are generated in the course of the reaction (as well as their mobility and steric hindrance) appear to be key factors in defining the reaction kinetics. The dependence of the final network structure on cure schedule for this type of tertiary amine activated reaction is then discussed in the context of the literature. Finally, in the Supplementary Material, Kamal-like functions are fit to the isothermal reaction kinetics, with the reader cautioned in applying the functions to non-isothermal cures.

Widespread permafrost thaw in response to changing climate conditions has the potential to dramatically impact ecosystems, infrastructure, and the global carbon budget. Ambient seismic noise techniques allow passive subsurface monitoring that could provide new insights into permafrost vulnerability and active-layer processes. Using nearly 2 years of continuous seismic data recorded near Fairbanks, Alaska, we measured relative velocity variations that showed a clear seasonal cycle reflecting active-layer freeze and thaw. Relative to January 2014, velocities increased up to 3% through late spring, decreased to −8% by late August, and then gradually returned to the initial values by the following winter. Velocities responded rapidly (over ~2 to 7 days) to discrete hydrologic events and temperature forcing and indicated that spring snowmelt and infiltration events from summer rainfall were particularly influential in propagating thaw across the site. Velocity increases during the fall zero-curtain captured the refreezing process and incremental ice formation. Looking across multiple frequency bands (3–30 Hz), negative relative velocities began at higher frequencies earlier in the summer and then shifted lower when active-layer thaw deepened, suggesting a potential relationship between frequency and thaw depth; however, this response was dependent on interstation distance. Bayesian tomography returned 2-D time-lapse images identifying zones of greatest velocity reduction concentrated in the western side of the array, providing insight into the spatial variability of thaw progression, soil moisture, and drainage. This study demonstrates the potential of passive seismic monitoring as a new tool for studying site-scale active-layer and permafrost thaw processes at high temporal and spatial resolution.

Model error estimation remains one of the key challenges in uncertainty quantification and predictive science. For computational models of complex physical systems, model error, also known as structural error or model inadequacy, is often the largest contributor to the overall predictive uncertainty. This work builds on a recently developed frame- work of embedded, internal model correction, in order to represent and quantify structural errors, together with model parameters, within a Bayesian inference context.We focus specifically on a polynomial chaos representation with addi- tive modification of existing model parameters, enabling a nonintrusive procedure for efficient approximate likelihood construction, model error estimation, and disambiguation of model and data errors’ contributions to predictive uncer- tainty. The framework is demonstrated on several synthetic examples, as well as on a chemical ignition problem.

Emerging memory devices, such as resistive crossbars, have the capacity to store large amounts of data in a single array. Acquiring the data stored in large-capacity crossbars in a sequential fashion can become a bottleneck. We present practical methods, based on sparse sampling, to quickly acquire sparse data stored on emerging memory devices that support the basic summation kernel, reducing the acquisition time from linear to sub-linear. The experimental results show that at least an order of magnitude improvement in acquisition time can be achieved when the data are sparse. In addition, we show that the energy cost associated with our approach is competitive to that of the sequential method.

This work documents the first version of the U.S. Department of Energy (DOE) new Energy Exascale Earth System Model (E3SMv1). We focus on the standard resolution of the fully coupled physical model designed to address DOE mission-relevant water cycle questions. Its components include atmosphere and land (110-km grid spacing), ocean and sea ice (60 km in the midlatitudes and 30 km at the equator and poles), and river transport (55 km) models. This base configuration will also serve as a foundation for additional configurations exploring higher horizontal resolution as well as augmented capabilities in the form of biogeochemistry and cryosphere configurations. The performance of E3SMv1 is evaluated by means of a standard set of Coupled Model Intercomparison Project Phase 6 (CMIP6) Diagnosis, Evaluation, and Characterization of Klima simulations consisting of a long preindustrial control, historical simulations (ensembles of fully coupled and prescribed SSTs) as well as idealized CO2 forcing simulations. The model performs well overall with biases typical of other CMIP-class models, although the simulated Atlantic Meridional Overturning Circulation is weaker than many CMIP-class models. While the E3SMv1 historical ensemble captures the bulk of the observed warming between preindustrial (1850) and present day, the trajectory of the warming diverges from observations in the second half of the twentieth century with a period of delayed warming followed by an excessive warming trend. Using a two-layer energy balance model, we attribute this divergence to the model's strong aerosol-related effective radiative forcing (ERFari+aci = −1.65 W/m2) and high equilibrium climate sensitivity (ECS = 5.3 K).

In magneto-inertial-fusion experiments, energy losses such as a radiation need to be well controlled in order to maximize the compressional work done on the fuel and achieve thermonuclear conditions. One possible cause for high radiation losses is high-Z material mixing from the target components into the fuel. In this work, we analyze the effects of mix on target performance in Magnetized Liner Inertial Fusion (MagLIF) experiments at Sandia National Laboratories. Our results show that mix is likely produced from a variety of sources, approximately half of which originates during the laser heating phase and the remainder near stagnation, likely from the liner deceleration. By changing the "cushion" component of MagLIF targets from Al to Be, we achieved a 10× increase in neutron yield, a 60% increase in ion temperature, and an ∼50% increase in fuel energy at stagnation.

Flame-sampling experiments, especially in conjunction with laminar low-pressure premixed flames, are routinely used in combustion chemistry studies to unravel the identities and quantities of key intermediates and their pathways. In many instances, however, an unambiguous interpretation of the experimental and modeling results is hampered by the uncertainties about the probe-induced, perturbed temperature profile. To overcome this limitation, two-dimensional perturbations of the temperature field caused by sampling probes with different geometries have been investigated using synchrotron-based X-ray fluorescence spectroscopy. In these experiments, which were performed at the 7-BM beamline of the Advanced Photon Source (APS) at the Argonne National Laboratory, a continuous beam of hard X-rays at 15keV was used to excite krypton atoms that were added in a concentration of 5vol.-% to the unburnt gas mixture and the resulting krypton fluorescence at 12.65keV was subsequently collected. The highly spatially resolved signal was converted into the local flame temperature to obtain temperature fields at various burner-probe separations as functions of the distance to the burner surface and the radial distance from the centerline. Multiple measurements were performed with different probe geometries and because of the observed impact on the temperature profiles the results clearly revealed the need to specify the sampling probe design to enable quantitative and meaningful comparisons of modeling results with flame-sampled mole fraction data.

The term photonic wire laser is now widely used for lasers with transverse dimensions much smaller than the wavelength. As a result, a large fraction of the mode propagates outside the solid core. Here, we propose and demonstrate a scheme to form a coupled cavity by taking advantage of this unique feature of photonic wire lasers. In this scheme, we used quantum cascade lasers with antenna-coupled third-order distributed feedback grating as the platform. Inspired by the chemistry of hybridization, our scheme phase-locks multiple such lasers by π coupling. With the coupled-cavity laser, we demonstrated several performance metrics that are important for various applications in sensing and imaging: a continuous electrical tuning of ~10 GHz at ~3.8 THz (fractional tuning of ~0.26%), a good level of output power (~50–90 mW of continuous-wave power) and tight beam patterns (~100 of beam divergence).