Arithmetic Coding (AC) using Prediction by Partial Matching (PPM) is a compression algorithm that can be used as a machine learning algorithm. This paper describes a new algorithm, NGram PPM. NGram PPM has all the predictive power of AC/PPM, but at a fraction of the computational cost. Unlike compression-based analytics, it is also amenable to a vector space interpretation, which creates the ability for integration with other traditional machine learning algorithms. AC/PPM is reviewed, including its application to machine learning. Then NGram PPM is described and test results are presented, comparing them to AC/PPM.
This report summarizes the activities performed as part of the Science and Engineering of Cybersecurity by Uncertainty quantification and Rigorous Experimentation (SECURE) Grand Challenge LDRD project. We provide an overview of the research done in this project, including work on cyber emulation, uncertainty quantification, and optimization. We present examples of integrated analyses performed on two case studies: a network scanning/detection study and a malware command and control study. We highlight the importance of experimental workflows and list references of papers and presentations developed under this project. We outline lessons learned and suggestions for future work.
Ship tracks are quasi-linear cloud patterns produced from the interaction of ship emissions with low boundary layer clouds. They are visible throughout the diurnal cycle in satellite images from space-borne assets like the Advanced Baseline Imagers (ABI) aboard the National Oceanic and Atmospheric Administration Geostationary Operational Environmental Satellites (GOES-R). However, complex atmospheric dynamics often make it difficult to identify and characterize the formation and evolution of tracks. Ship tracks have the potential to increase a cloud's albedo and reduce the impact of global warming. Thus, it is important to study these patterns to better understand the complex atmospheric interactions between aerosols and clouds to improve our climate models, and examine the efficacy of climate interventions, such as marine cloud brightening. Over the course of this 3-year project, we have developed novel data-driven techniques that advance our ability to assess the effects of ship emissions on marine environments and the risks of future marine cloud brightening efforts. The three main innovative technical contributions we will document here are a method to track aerosol injections using optical flow, a stochastic simulation model for track formations and an automated detection algorithm for efficient identification of ship tracks in large datasets.
This report presents the results of the “Foundations of Rigorous Cyber Experimentation” (FORCE) Laboratory Directed Research and Development (LDRD) project. This project is a companion project to the “Science and Engineering of Cyber security through Uncertainty quantification and Rigorous Experimentation” (SECURE) Grand Challenge LDRD project. This project leverages the offline, controlled nature of cyber experimentation technologies in general, and emulation testbeds in particular, to assess how uncertainties in network conditions affect uncertainties in key metrics. We conduct extensive experimentation using a Firewheel emulation-based cyber testbed model of Invisible Internet Project (I2P) networks to understand a de-anonymization attack formerly presented in the literature. Our goals in this analysis are to see if we can leverage emulation testbeds to produce reliably repeatable experimental networks at scale, identify significant parameters influencing experimental results, replicate the previous results, quantify uncertainty associated with the predictions, and apply multi-fidelity techniques to forecast results to real-world network scales. The I2P networks we study are up to three orders of magnitude larger than the networks studied in SECURE and presented additional challenges to identify significant parameters. The key contributions of this project are the application of SECURE techniques such as UQ to a scenario of interest and scaling the SECURE techniques to larger network sizes. This report describes the experimental methods and results of these studies in more detail. In addition, the process of constructing these large-scale experiments tested the limits of the Firewheel emulation-based technologies. Therefore, another contribution of this work is that it informed the Firewheel developers of scaling limitations, which were subsequently corrected.
As the seismic monitoring community advances toward detecting, identifying, and locating ever-smaller natural and anthropogenic events, the need is constantly increasing for higher resolution, higher fidelity data, models, and methods for accurately characterizing events. Local-distance seismic data provide robust constraints on event locations, but also introduce complexity due to the significant geologic heterogeneity of the Earth’s crust and upper mantle, and the relative sparsity of data that often occurs with small events recorded on regional seismic networks. Identifying the critical characteristics for improving local-scale event locations and the factors that impact location accuracy and reliability is an ongoing challenge for the seismic community. Using Utah as a test case, we examine three data sets of varying duration, finesse, and magnitude to investigate the effects of local earth structure and modeling parameters on local-distance event location precision and accuracy. We observe that the most critical elements controlling relocation precision are azimuthal coverage and local-scale velocity structure, with tradeoffs based on event depth, type, location, and range.
To date, disinformation research has focused largely on the production of false information ignoring the suppression of select information. We term this alternative form of disinformation information suppression. Information suppression occurs when facts are withheld with the intent to mislead. In order to detect information suppression, we focus on understanding the actors who withhold information. In this research, we use knowledge of human behavior to find signatures of different gatekeeping behaviors found in text. Specifically, we build a model to classify the different types of edits on Wikipedia using the added text alone and compare a human-informed feature engineering approach to a featureless algorithm. Being able to computationally distinguish gatekeeping behaviors is a first step towards identifying when information suppression is occurring.
A new copper equation of state is developed utilizing the available experimental data in addition to recent theoretical calculations. Semi-empirical models are fit to the data and the results are tabulated in the SNL SESAME format. Comparison to other copper EOS tables are given, along with recommendations of which tables provide the best accuracy.
Wellbore integrity is a significant problem in the U.S. and worldwide, which has serious adverse environmental and energy security consequences. Wells are constructed with a cement barrier designed to last about 50 years. Indirect measurements and models are commonly used to identify wellbore damage and leakage, often producing subjective and even erroneous results. The research presented herein focuses on new technologies to improve monitoring and detection of wellbore failures (leaks) by developing a multi-step machine learning approach to localize two types of thermal defects within a wellbore model, a prototype mechatronic system for automatically drilling small diameter holes of arbitrary depth to monitor the integrity of oil and gas wells in situ, and benchtop testing and analyses to support the development of an autonomous real-time diagnostic tool to enable sensor emplacement for monitoring wellbore integrity. Each technology was supported by experimental results. This research has provided tools to aid in the detection of wellbore leaks and significantly enhanced our understanding of the interaction between small-hole drilling and wellbore materials.
Battery cells with metal casings are commonly considered incompatible with nuclear magnetic resonance (NMR) spectroscopy because the oscillating radio-frequency magnetic fields ("rf fields") responsible for excitation and detection of NMR active nuclei do not penetrate metals. Here, we show that rf fields can still efficiently penetrate nonmetallic layers of coin cells with metal casings provided "B1 damming"configurations are avoided. With this understanding, we demonstrate noninvasive high-field in situ 7Li and 19F NMR of coin cells with metal casings using a traditional external NMR coil. This includes the first NMR measurements of an unmodified commercial off-the-shelf rechargeable battery in operando, from which we detect, resolve, and separate 7Li NMR signals from elemental Li, anodic β-LiAl, and cathodic LixMnO2 compounds. Real-time changes of β-LiAl lithium diffusion rates and variable β-LiAl 7Li NMR Knight shifts are observed and tied to electrochemically driven changes of the β-LiAl defect structure.
While it is likely practically a bad idea to shrink a transistor to the size of an atom, there is no arguing that it would be fantastic to have atomic-scale control over every aspect of a transistor – a kind of crystal ball to understand and evaluate new ideas. This project showed that it was possible to take a niche technique used to place dopants in silicon with atomic precision and apply it broadly to study opportunities and limitations in microelectronics. In addition, it laid the foundation to attaining atomic-scale control in semiconductor manufacturing more broadly.
This report summarizes the 2021 fiscal year (FY21) status of ongoing borehole heater tests in salt funded by the disposal research and development (R&D) program of the Office of Spent Fuel & Waste Science and Technology (SFWST) of the US Department of Energy’s Office of Nuclear Energy’s (DOE-NE) Office of Spent Fuel and Waste Disposition (SFWD). This report satisfies SFWST milestone M2SF- 21SN010303052 by summarizing test activities and data collected during FY21. The Brine Availability Test in Salt (BATS) is fielded in a pair of similar arrays of horizontal boreholes in an experimental area at the Waste Isolation Pilot Plant (WIPP). One array is heated, the other unheated. Each array consists of 14 boreholes, including a central borehole with gas circulation to measure water production, a cement seal exposure test, thermocouples to measure temperature, electrodes to infer resistivity, a packer-isolated borehole to add tracers, fiber optics to measure temperature and strain, and piezoelectric transducers to measure acoustic emissions. The key new data collected during FY21 include a series of gas tracer tests (BATS phase 1b), a pair of liquid tracer tests (BATS phase 1c), and data collected under ambient conditions (including a period with limited access due to the ongoing pandemic) since BATS phase 1a in 2020. A comparison of heated and unheated gas tracer test results clearly shows a decrease in permeability of the salt upon heating (i.e., thermal expansion closes fractures, which reduces permeability).
University partnerships play an essential role in sustaining Sandia’s vitality as a national laboratory. The SAA is an element of Sandia’s broader University Partnerships program, which facilitates recruiting and research collaborations with dozens of universities annually. The SAA program has two three-year goals. SAA aims to realize a step increase in hiring results, by growing the total annual inexperienced hires from each out-of-state SAA university. SAA also strives to establish and sustain strategic research partnerships by establishing several federally sponsored collaborations and multi-institutional consortiums in science & technology (S&T) priorities such as autonomy, advanced computing, hypersonics, quantum information science, and data science. The SAA program facilitates access to talent, ideas, and Research & Development facilities through strong university partnerships. Earlier this year, the SAA program and campus executives hosted John Myers, Sandia’s former Senior Director of Human Resources (HR) and Communications, and senior-level staff at Georgia Tech, U of Illinois, Purdue, UNM, and UT Austin. These campus visits provided an opportunity to share the history of the partnerships from the university leadership, tours of research facilities, and discussions of ongoing technical work and potential recruiting opportunities. These visits also provided valuable feedback to HR management that will help Sandia realize a step increase in hiring from SAA schools. The 2020-2021 Collaboration Report is a compilation of accomplishments in 2020 and 2021 from SAA and Sandia’s valued SAA university partners.
Develop, verify, and document model capabilities sufficient for comparing field wake measurements from SWiFT with synthetic lidar wake measurements from Nalu-Wind (hereafter referred to as `Nalu').
Gannon, Renae N.; Hamann, Danielle M.; Ditto, Jeffrey; Mitchson, Gavin; Bauers, Sage R.; Merrill, Devin R.; Medlin, Douglas L.; Johnson, David C.
Layered van der Waals heterostructures provide extraordinary opportunities for applications such as thermoelectrics and allow for tunability of optical and electronic properties. The performance of devices made from these heterostructures will depend on their properties, which are sensitive to the nanoarchitecture (constituent layer thicknesses, layer sequence, etc.). However, performance will also be impacted by defects, which will vary in concentration and identity with the nanoarchitecture and preparation conditions. Here, we identify several types of defects and propose mechanisms for their formation, focusing on compounds in the ([SnSe]1+δ)m(TiSe2)n system prepared using the modulated elemental reactants method. The defects were observed by atomic resolution high-angle annular dark-field scanning transmission electron microscopy and can be broadly categorized into those that form domain boundaries as a result of rotational disorder from the self-assembly process and those that are layer-thickness-related and result from local or global deviations in the amount of material deposited. Defect type and density were found to depend on the nanoarchitecture of the heterostructure. Categorizing the defects provides insights into defect formation in these van der Waals layered heterostructures and suggests strategies for controlling their concentrations. Strategies for controlling defect type and concentration are proposed, which would have implications for transport properties for applications in thermoelectrics.
This report summarizes the FY21 Activities for EBS International Collaborations Work Package. The international collaborations work packages aim to leverage knowledge, expertise, and tools from the international nuclear waste community, as deemed relevant according to SFWST “roadmap” priorities. This report describes research and development (R&D) activities conducted during fiscal year 2021(FY21) specifically related to the Engineered Barrier System (EBS) R&D Work Package in the Spent Fuel and Waste Science and Technology (SFWST) Campaign supported by the United States (U.S.) Department of Energy (DOE). It fulfills the SFWST Campaign deliverable M4SF- 21SN010308062. The R&D activities described in this report focus on understanding EBS component evolution and interactions within the EBS, as well as interactions between the host media and the EBS. A primary goal is to advance the development of process models that can be implemented directly within the Generic Disposal System Analysis (GDSA) platform or that can contribute to the safety case in some manner such as building confidence, providing further insight into the processes being modeled, establishing better constraints on barrier performance, etc. Sandia National Laboratories is participating in THM modeling in the international projects EBS Task Force and DECOVALEX 2023. EBS Task Force, Task 11 is on modeling of laboratory-scale High Temperature Column Test conducted at Lawrence Berkeley National Laboratory. DECOVALEX 2023, Task C is on THM modeling of the full-scale emplacement experiment (FE experiment) at the Mont Terri Underground Rock Laboratory, Switzerland. This report summarizes Sandia’s progress in the modeling studies of DECOVALEX 2023, Task C. Modeling studies related to the High Temperature Column Test will be documented in future reports.
Steam cracking of ethane, a non-catalytic thermochemical process, remains the dominant means of ethylene production. The severe reaction conditions and energy expenditure involved in this process incentivize the search for alternative reaction pathways and reactor designs which maximize ethylene yield while minimizing cost and energy input. Herein, we report a comparison of catalytic and non-catalytic non-oxidative dehydrogenation of ethane. We achieve ethylene yields as high as 67 % with an open tube quartz reactor without the use of a catalyst at residence times ∼4 s. The open tube reactor design promotes simplicity, low cost, and negligible coke formation. Pristine quartz tubes were most effective, since coke formation was detected when defects were introduced by scratching the surface of the quartz. Surprisingly, the addition of solids to the quartz tube, such as quartz sand, alumina powder, or even Pt-based intermetallic catalysts, led to lower ethylene yield. Pt alloy catalysts are effective at lower temperatures, such as at 575 °C, but conversion is limited due to thermodynamic constraints. When operated at industrially relevant temperatures, such as 700 °C and above, these catalysts were not stable in our tests, causing ethylene yield to drop below that of the open tube. These results suggest that future research on non-oxidative dehydrogenation should be directed at optimizing reactor designs to improve the conversion of ethane to ethylene, since this approach shows promise for decentralized production of ethylene from natural gas deposits.
The final review for the FY21 Advanced Simulation and Computing (ASC) Computational Systems and Software Environments (CSSE) L2 Milestone #7840 was conducted on August 25th, 2021 at Sandia National Laboratories in Albuquerque, New Mexico. The review committee/panel unanimously agreed that the milestone has been successfully completed, exceeding expectations on several of the key deliverables.
Choffel, Marisa A.; Gannon, Renae N.; Gohler, Fabian; Miller, Aaron M.; Medlin, Douglas L.; Seyller, Thomas; Johnson, David C.
The synthesis and electrical properties of a new misfit compound containing BiSe, Bi2Se3, and MoSe2 constituent layers are reported. The reaction pathway involves competition between the formation of (BiSe)1+x(Bi2Se3)1+y(BiSe)1+x(MoSe2) and [(Bi2Se3)1+y]2(MoSe2). Excess Bi and Se are required in the precursor to synthesize (BiSe)1+x(Bi2Se3)1+y(BiSe)1+x(MoSe2). High-angle annular dark field-scanning transmission electron microscopy (HAADF-STEM) confirm the stacking sequence of the heterostructure. Small grains of both 2H-and 1T-MoSe2 are observed in the MoSe2 layers. X-ray photoelectron spectroscopy (XPS) indicates that there is a significantly higher percentage of 1T-MoSe2 in (BiSe)1+x(Bi2Se3)1+y(BiSe)1+x(MoSe2) than in (BiSe)0.97(MoSe2), suggesting that more charge transfer to MoSe2 occurs due to the additional BiSe layer. The additional charge transfer results in (BiSe)1+x(Bi2Se3)1+y(BiSe)1+x(MoSe2) having a low resistivity (14-19 μω m) with metallic temperature dependence. The heterogeneous mix of MoSe2 polytypes observed in the XPS complicates the interpretation of the Hall data as two bands contribute to the electrical continuity.
Atomic precision advanced manufacturing (APAM) leverages the highly reactive nature of Si dangling bonds relative to H- or Cl-passivated Si to selectively adsorb precursor molecules into lithographically defined areas with sub-nanometer resolution. Due to the high reactivity of dangling bonds, this process is confined to ultra-high vacuum (UHV) environments, which currently limits its commercialization and broad-based appeal. In this work, we explore the use of halogen adatoms to preserve APAM-derived lithographic patterns outside of UHV to enable facile transfer into real-world commercial processes. Specifically, we examine the stability of H-, Cl-, Br-, and I-passivated Si(100) in inert N2 and ambient environments. Characterization with scanning tunneling microscopy and x-ray photoelectron spectroscopy (XPS) confirmed that each of the fully passivated surfaces were resistant to oxidation in 1 atm of N2 for up to 44 h. Varying levels of surface degradation and contamination were observed upon exposure to the laboratory ambient environment. Characterization by ex situ XPS after ambient exposures ranging from 15 min to 8 h indicated the Br– and I–passivated Si surfaces were highly resistant to degradation, while Cl–passivated Si showed signs of oxidation within minutes of ambient exposure. As a proof-of-principle demonstration of pattern preservation, a H–passivated Si sample patterned and passivated with independent Cl, Br, I, and bare Si regions was shown to maintain its integrity in all but the bare Si region post-exposure to an N2 environment. The successful demonstration of the preservation of APAM patterns outside of UHV environments opens new possibilities for transporting atomically-precise devices outside of UHV for integrating with non-UHV processes, such as other chemistries and commercial semiconductor device processes.
Lithium metal is considered the "holy grail"material to replace typical Li-ion anodes due to the absence of a host structure coupled with a high theoretical capacity. The absence of a host structure results in large volumetric changes when lithium is electrodeposited/dissolved, making the lithium prone to stranding and parasitic reactions with the electrolyte. Lithium research is focused on enabling highly reversible lithium electrodeposition/dissolution, which is important to achieving long cycle life. Understanding the various mechanisms of self-discharge is also critical for realizing practical lithium metal batteries but is often overlooked. In contrast to previous work, it is shown here that self-discharge via galvanic corrosion is negligible, particularly when lithium is cycled to relevant capacities. Rather, the continued electrochemical cycling of lithium metal results in self-discharge when periodic rest is applied during cycling. The extent of self-discharge can be controlled by increasing the capacity of plated lithium, tuning electrolyte chemistry, incorporating regular rest, or introducing lithiophilic materials. The Coulombic losses that occur during periodic rest are largely reversible, suggesting that the dominant self-discharge mechanism in this work is not an irreversible chemical process but rather a morphological process.
Abdelfattah, Ahmad; Anzt, Hartwig; Ayala, Alan; Boman, Erik G.; Carson, Erin C.; Cayrols, Sebastien; Cojean, Terry; Dongarra, Jack J.; Falgout, Rob; Gates, Mark; G, R\{U}Tzmacher; Higham, Nicholas J.; Kruger, Scott E.; Li, Sherry; Lindquist, Neil; Liu, Yang; Loe, Jennifer A.; Nayak, Pratik; Osei-Kuffuor, Daniel; Pranesh, Sri; Rajamanickam, Sivasankaran R.; Ribizel, Tobias; Smith, Bryce B.; Swirydowicz, Kasia; Thomas, Stephen J.; Tomov, Stanimire; Tsai, Yaohung M.; Yamazaki, Ichitaro Y.; Yang, Urike M.
Over the last year, the ECP xSDK-multiprecision effort has made tremendous progress in developing and deploying new mixed precision technology and customizing the algorithms for the hardware deployed in the ECP flagship supercomputers. The effort also has succeeded in creating a cross-laboratory community of scientists interested in mixed precision technology and now working together in deploying this technology for ECP applications. In this report, we highlight some of the most promising and impactful achievements of the last year. Among the highlights we present are: Mixed precision IR using a dense LU factorization and achieving a 1.8× speedup on Spock; results and strategies for mixed precision IR using a sparse LU factorization; a mixed precision eigenvalue solver; Mixed Precision GMRES-IR being deployed in Trilinos, and achieving a speedup of 1.4× over standard GMRES; compressed Basis (CB) GMRES being deployed in Ginkgo and achieving an average 1.4× speedup over standard GMRES; preparing hypre for mixed precision execution; mixed precision sparse approximate inverse preconditioners achieving an average speedup of 1.2×; and detailed description of the memory accessor separating the arithmetic precision from the memory precision, and enabling memory-bound low precision BLAS 1/2 operations to increase the accuracy by using high precision in the computations without degrading the performance. We emphasize that many of the highlights presented here have also been submitted to peer-reviewed journals or established conferences, and are under peer-review or have already been published.
Porous nanoscale carbonaceous materials are widely employed for catalysis, separations, and electrochemical devices where device performance often relies upon specific and well-defined regular feature sizes. The use of block polymers as templates has enabled affordable and scalable production of diverse porous carbons. However, popular carbon preparations use equilibrating micelles which can change dimensions in response to the processing environment. Thus, polymer methods have not yet demonstrated carbon nanomaterials with constant average template diameter and tailored wall thickness. In contrast, persistent micelle templates (PMTs) use kinetic control to preserve constant micelle template diameters, and thus PMT has enabled constant pore diameter metrics. With PMT, the wall thickness is independently adjustable via the amount of material precursor added to the micelle templates. Previous PMT demonstrations relied upon thermodynamic barriers to inhibit chain exchange while in solution, followed by rapid evaporation and cross-linking of material precursors to mitigate micelle reorganization once the solvent evaporated. It is shown here that this approach, however, fails to deliver kinetic micelle control when used with slowly cross-linking material precursors such as those for porous carbons. A new modality for kinetic control over micelle templates, glassy-PMTs, is shown using an immobilized glassy micelle core composed of polystyrene (PS). Although PS based polymers have been used to template carbon materials before, all prior reports included plasticizers that prevented kinetic micelle control. Here the key synthetic conditions for carbon materials with glassy-PMT control are enumerated, including dependencies upon polymer block selection, block molecular mass, solvent selection, and micelle processing timeline. The use of glassy-PMTs also enables the direct observation of micelle cores by TEM which are shown to be commensurate with template dimensions. Glassy-PMTs are thus robust and insensitive to material processing kinetics, broadly enabling tailored nanomaterials with diverse chemistries.
The DOE R&D program under the Spent Fuel Waste Science Technology (SFWST) campaign has made key progress in modeling and experimental approaches towards the characterization of chemical and physical phenomena that could impact the long-term safety assessment of heatgenerating nuclear waste disposition in deep-seated clay/shale/argillaceous rock. International collaboration activities such as heater tests, continuous field data monitoring, and postmortem analysis of samples recovered from these have elucidated key information regarding changes in the engineered barrier system (EBS) material exposed to years of thermal loads. Chemical and structural analyses of sampled bentonite material from such tests as well as experiments conducted on these are key to the characterization of thermal effects affecting bentonite clay barrier performance and the extent of sacrificial zones in the EBS during the thermal period. Thermal, hydrologic, and chemical data collected from heater tests and laboratory experiments has been used in the development, validation, and calibration of THMC simulators to model near-field coupled processes. This information leads to the development of simulation approaches (e.g., continuum and discrete) to tackle issues related to flow and transport at various scales of the host-rock, its interactions with barrier materials, and EBS design concept.
In this study, model derivations are carried out of a dynamical system under base excitations with a piezoelectric energy harvesting absorber as the tuned-mass-damper. Additionally, amplitude stoppers are included to the absorber in order to create a broadband resonant response, increasing the window of operational use for energy harvesting and system's control. This study is unique in the fact that the energy harvester is coupled to the source of its excitation. A nonlinear reduced-order model is developed using Euler–Lagrange principle and the Galerkin method to accurately estimate the energy harvesting absorber's displacement, harvested power, and the oscillating response of the primary structure. The nonlinear interaction of the energy harvesting absorber and the amplitude stoppers are the focus of this study, where an in-depth investigation of bifurcation points of the primary structure and energy harvesting absorber responses is performed. Due to a transfer of energy between the primary structure and the absorber, it is shown that a soft stopper with stiffness $5 \times {10^3}\,{\text{N}}\;{{\text{m}}^{ - 1}}\,$ has great control of the primary structure with 60% of the uncontrolled amplitude being reduced, as well as an increase of the harvested energy. Medium stoppers with small initial gaps size and hard stoppers do not control the primary structure and show a decrease in the energy harvesting capabilities due to the activation of the nonlinear contact-impact interactions. Finally, these stoppers also generate aperiodic regions due to the possible presence of grazing bifurcations.
As a general-purpose force field for molecular simulations of layered materials and their fluid interfaces, Clayff continues to see broad usage in atomistic computational modeling for numerous geoscience and materials science applications due to its (1) success in predicting properties of bulk nanoporous materials and their interfaces, (2) transferability to a range of layered and nanoporous materials, and (3) simple functional form which facilitates incorporation into a variety of simulation codes. Here, we review applications of Clayff to model bulk phases and interfaces not included in the original parameter set and recent modifications for modeling surface terminations such as hydroxylated nanoparticle edges. We conclude with a discussion of expectations for future developments.
The following trade study was done to answer the following task from the Sandia JPL Collaboration for Europa Lander Statement of Work: Survey facility infrastructure SNL may have for performing aseptic assembly and integration of S/C and assess its suitability for PP applications.
Currently, traditional methods such as short-term average/long-term average (STA/LTA) are used to detect arrivals in three-component seismic waveform data. Accurately establishing the identity and arrival of these waves is helpful in detecting and locating seismic events. Convolutional Neural Networks (CNNs) have been shown to significantly improve performance at local distances. This work will expand the use of CNNs to more remote distances and lower magnitudes. Sandia National Labs (SNL) will explore the advantages and limits of a particular approach and investigate requirements for expanding this technique to different types, distances, and magnitudes of events in the future. The team will describe detailed performance results of this method tuned on a curated dataset from Utah with its expert-defined arrival picks.
This report summarizes initial results from a series of gun experiments which were conducted at the DICE facility. The target of these experiments was a modified metal slug composed of a tantalum/tungsten alloy (Ta-10W). The general geometry of the slug was a right circular cylinder with a through-hole cut normal to the cylinder's axis. In all experiments, hardened steel impactors were used, the desired impact velocity was 200 m/s, the slug was preheated to a target temperature of 175° C, photon doppler velocimetry (PDV) was used to measure the projectile velocity before and after impact, and the impact event was recorded with high-speed video. In two of the impacts the slug was oriented perpendicular to the projectile, while in the remaining two it was tilted 8° from normal. Initial high-speed speed video results showed slug failure in the tilted impact case, while the slug survived normal impacts. Recovery fixtures were used to preserve impacted slugs for future postmortem analysis. Discussions are included regarding improvements to potential future experiments involving these slugs.
This report is a functional review of the radionuclide containment strategies of fluoride-salt-cooled high temperature reactor (FHR), molten salt reactor (MSR) and high temperature gas reactor (HTGR) systems. This analysis serves as a starting point for further, more in-depth analyses geared towards identifying phenomenological gaps that still exist, hindering the creation of a mechanistic source term for these reactor types. As background information to this review, an overview of how a mechanistic source term is created and used for consequence assessment necessary for licensing is provided. How a mechanistic source term is used within the Licensing Modernization Project (LMP) is also provided. Lastly, the characteristics of non-LWR mechanistic source terms are examined. This report does not assess the viability of any software system for use with advanced reactor designs, but instead covers system function requirements. Future work within the Nuclear Energy Advanced Modeling and Simulations (NEAMS) program will address such gaps. This document is an update of SAND 2020-6730. An additional chapter is included as well as edits to original content.
Sandia will provide technical assistance to New Mexico Department of Health to provide analysis of SafeGraph mobility data (for which Sandia already has the data and a Data Use Agreement in place with the data provider). Sandia will produce analysis to determine the contribution of travel to SARS-CoV-2 spread within New Mexico.
The goal of this work is to develop a Bayesian framework to characterize the uncertainty of material response when using a nonlocal, homogenized model to describe wave propagation through heterogeneous, disordered materials. Our approach is based on an operator regression technique combined with Bayesian optimization, through which the nonlocal kernel for a specific disordered microstructure is investigated.
We present an approach for constructing a surrogate from ensembles of information sources of varying cost and accuracy. The multifidelity surrogate encodes connections between information sources as a directed acyclic graph, and is trained via gradient-based minimization of a nonlinear least squares objective. While the vast majority of state-of-the-art assumes hierarchical connections between information sources, our approach works with flexibly structured information sources that may not admit a strict hierarchy. The formulation has two advantages: (1) increased data efficiency due to parsimonious multifidelity networks that can be tailored to the application; and (2) no constraints on the training data—we can combine noisy, non-nested evaluations of the information sources. Finally, numerical examples ranging from synthetic to physics-based computational mechanics simulations indicate the error in our approach can be orders-of-magnitude smaller, particularly in the low-data regime, than single-fidelity and hierarchical multifidelity approaches.
This Storm Water Pollution Prevention Plan (SWPPP) has been prepared for the Sandia National Laboratories Water Line Project – Northern Portion, in Livermore, CA. The project, located at 7011 East Avenue, and will entail the portion of the site north of the Arroyo Section. The project is comprised of 19,584 linear feet of water line improvements totaling approximately 9.0 acres. The property is owned by the U.S. Department of Energy, and managed and operated by National Technology & Engineering Solutions of Sandia, LLC with this project being developed by NTESS for Sandia National Laboratories.
The advanced materials team investigated the use of additively manufactured metallic lattice structures for mitigating impact response in a Davis gun earth penetrator impact experiment. High-fidelity finite element models were developed and validated with quasistatic experiments. These models were then used to simulate the response of such lattices when subjected to the acceleration loads expected in the Davis gun experiment. Results reveal how the impact mitigation performance of lattices can change drastically at a certain relative density. Based on these observations, an experiment deck was designed to probe the response of lattices with different relative densities during the Davis gun phase 2 shots. The expected performance of these lattices is predicted before testing based on simulation results. The results of the Davis gun phase 2 shots are expected to provide data which will be used to assess the predictive capability of the finite element simulations in such a complex impact environment.
Historically, nuclear component manufacturing vendors, from small businesses through large conglomerates, have felt compelled to obtain an American Society for Mechanical Engineers (ASME) Nuclear Certification, known colloquially as an "N-stamp", to assure supply chain quality standards that will be acceptable to regulators and safety concerns. Since the N-stamp quality standard is a U.S.-origin code, combined with the apparent decline in the U.S. nuclear industry alongside the growth of the Asian nuclear industry, there is the question of whether the rest of the world, including new entrants to the nuclear industry, also regard N-stamp as a needed certification. This study addresses this question through analysis of the entire N-stamp database of holders, and former holders, of N-stamp certificates of all types and for all regions worldwide from 1989-2020 (the dates available in the database). From this 30 years of data, we find that actually U.S.-based vendors still consistently obtain the largest number of N-stamps worldwide over all time periods, but also find that the countries participating in the N-stamp certification process has broadly expanded beyond just North America, Japan, S. Korea and Western Europe (the primary N-stamp recipients before the mid-2000's). We produced global heats maps and bar charts to illustrate our findings, as well as further investigation into why the data shows changes over time and region. We note that nuclear entities involved with Soviet-type reactors do not participate in the N-stamp process, but instead pursue the Russian version PNAE, which is substantially similar to the ASME code. We conclude that at least from the N-stamp database, the United States nuclear component manufacturing industry is alive and well, although there have been some consolidations, and that the ASME N-stamp appears to still be a valued certificate worldwide, including in China which now ranks second only to the United States in obtaining N-stamp certificates in recent years. We further note that the vendors of new reactor types, in particular High Temperature Gas-Cooled Reactors (HTGRs) and Small Modular Reactors (SMRs), are actively engaged with ASME (and other U.S.-based nuclear standards bodies such as the American Nuclear Society and Nuclear Energy Institute) to coordinate updates to the ASME N-Stamp criteria to ensure applicability of the code for these new designs. Implications of these findings include the following: The global use of the U.S.-origin N-stamp certification supports the view that, despite the decline of the U.S. nuclear industry, the United States remains an esteemed global leader in the area of nuclear safety. As the U.S. Government works to revitalize the U.S. nuclear industry, especially in the area of exports, it may be beneficial to leverage the global standing of the N-stamp certification. The findings indicate that the N-stamp database would be a useful tool for the U.S. Government to use to track the growth of the civil nuclear industry in foreign countries, under certain circumstances. The Excel-format N-stamp database produced as part of this study may be a useful tool for this purpose. N-stamp data may be a useful tool for foreign governments to use to identify nuclear manufacturers within their own country, especially to identify "targets" for outreach on nuclear export control compliance. The U.S. Government could carry this message to foreign partners during bilateral engagements or as part of Nuclear Suppliers Group (NSG) discussions on industry outreach.
MELCOR is a fully integrated, engineering-level computer code for modeling the progression of severe accidents in light water reactors (LWR) at nuclear power plants and nuclear fuel cycle facilities. Originally developed to assess severe accidents following Three Mile Island, MELCOR’s flexible modeling framework has enabled it to be applied to safety assessments of a much broader range of nuclear power reactor designs and other types of nuclear facilities processing radioactive material. Further, MELCOR can model a broad spectrum of severe accident phenomena such as thermal-hydraulic response in a reactor coolant system; core heat-up, degradation, and relocation; and transport behavior in both boiling water and pressurized water reactors.
Sandia will provide technical assistance to Helpful Engineering to develop and test the Universal Citizen Protection Device (UCPD) which is a UV-based filter-less PPE concept that aims to keep the Sars-CoV-2 virus out of eyes, nose and mouth with a 99%+ reliability. The heart of the device would be a concealed UV Chamber that decontaminates all air going in and out of the PPE. Helpful Engineering’s goal is to build this device to be reusable and cost less than $100 to construct and can be worn for 8 hours. The UCPD is an open source project, and once developed, prototyped, tested and approved, it will be shared with interested manufacturers globally.
Information from 2015 annual report highlighting several tasks, including: Task 7: Research of microspectrophotometry for inspection and validation of laser color markings. Task 8: Investigate new laser fabrication techniques that produce color markings with improved corrosion resistance. Task 9: Research new methods for laser marking curved surfaces (and large areas). Task 10: Complete model simulations of laser-induced ripple formation-involves an ElectroMagnetic field solver.
As the demand for higher-performance batteries has increased, so has the body of research on theoretical high-capacity anode materials. However, the research has been hindered because the high-capacity anode material properties and interactions are not well understood, largely due to the difficulty of observing cycling in situ. Using electrochemical scanning transmission electron microscopy (ec-STEM), we report the real-time observation and electrochemical analysis of pristine tin (Sn) and titanium dioxide-coated Sn (TiO2@Sn) electrodes during lithiation/delithiation. As expected, we observed a volume expansion of the pristine Sn electrodes during lithiation, but we further observed that the expansion was followed by Sn detachment from the current collector. Remarkably, although the TiO2@Sn electrodes also exhibited similar volume expansion during lithiation, they showed no evidence of Sn detachment. We found that the TiO2 surface layer acted as an electrochemically activated artificial solid-electrolyte interphase that serves to conduct Li ions. As a physical coating, it mechanically prevented Sn detachment following volume changes during cycling, providing significant degradation resistance and 80% Coulombic efficiency for a complete lithiation/delithiation cycle. Interestingly, upon delithiation, TiO2@Sn electrode displayed a self-healing mechanism of small pore formation in the Sn particle followed by agglomeration into several larger pores as delithiation continued.
Kreitz, Bjarne; Sargsyan, Khachik S.; Mazeau, Emily J.; Blondal, Katrin; West, Richard H.; Wehinger, Gregor D.; Turek, Thomas; Goldsmith, C.F.
Automatic mechanism generation is used to determine mechanisms for the CO2 hydrogenation on Ni(111) in a two-stage process while considering the correlated uncertainty in DFT-based energetic parameters systematically. In a coarse stage, all the possible chemistry is explored with gas-phase products down to the ppb level, while a refined stage discovers the core methanation submechanism. Five thousand unique mechanisms were generated, which contain minor perturbations in all parameters. Global uncertainty assessment, global sensitivity analysis, and degree of rate control analysis are performed to study the effect of this parametric uncertainty on the microkinetic model predictions. Comparison of the model predictions with experimental data on a Ni/SiO2 catalyst find a feasible set of microkinetic mechanisms within the correlated uncertainty space that are in quantitative agreement with the measured data, without relying on explicit parameter optimization. Global uncertainty and sensitivity analyses provide tools to determine the pathways and key factors that control the methanation activity within the parameter space. Together, these methods reveal that the degree of rate control approach can be misleading if parametric uncertainty is not considered. The procedure of considering uncertainties in the automated mechanism generation is not unique to CO2 methanation and can be easily extended to other challenging heterogeneously catalyzed reactions.
Nanostructures with a high density of interfaces, such as in nanoporous materials and nanowires, resist radiation damage by promoting the annihilation and migration of defects. This study details the size effect and origins of the radiation damage mechanisms in nanowires and nanoporous structures in model face-centered (gold) and body-centered (niobium) cubic nanostructures using accelerated multi-cascade atomistic simulations and in-situ ion irradiation experiments. Our results reveal three different size-dependent mechanisms of damage accumulation in irradiated nanowires and nanoporous structures: sputtering for very small nanowires and ligaments, the formation and accumulation of point defects and dislocation loops in larger nanowires, and a face-centered-cubic to hexagonal-close-packed phase transformation for a narrow range of wire diameters in the case of gold nanowires. Smaller nanowires and ligaments have a net effect of lowering the radiation damage as compared to larger wires that can be traced back to the fact that smaller nanowires transition from a rapid accumulation of defects to a saturation and annihilation mechanism at a lower dose than larger nanowires. These irradiation damage mechanisms are accompanied with radiation-induced surface roughening resulting from defect-surface interactions. Comparisons between nanowires and nanoporous structures show that the various mechanisms seen in nanowires provide adequate bounds for the defect accumulation mechanisms in nanoporous structures with the difference attributed to the role of nodes connecting ligaments in nanoporous structures. Taken together, our results shed light on the compounded, size-dependent mechanisms leading to the radiation resistance of nanowires and nanoporous structures.
We describe a method to automatically generate an ion implantation recipe, a set of energies and fluences, to produce a desired defect density profile in a solid using the fewest required energies. We simulate defect density profiles for a range of ion energies, fit them with an appropriate function, and interpolate to yield defect density profiles at arbitrary ion energies. Given N energies, we then optimize a set of N energy-fluence pairs to match a given target defect density profile. Finally, we find the minimum N such that the error between the target defect density profile and the defect density profile generated by the N energy-fluence pairs is less than a given threshold. Inspired by quantum sensing applications with nitrogen-vacancy centers in diamond, we apply our technique to calculate optimal ion implantation recipes to create uniform-density 1 μm surface layers of 15N or vacancies (using 4He).
Schneemann, Andreas; Ying, Juan; Evans, Jack D.; Toyao, Takashi; Hijikata, Yuh; Kamiya, Yuichi; Shimizu, Ken I.; Burtch, Nicholas C.
The trapping of paraffins is beneficial compared to selective olefin adsorption for adsorptive olefin purification from a process engineering point of view. Here we demonstrate the use of a series of Zn2(X-bdc)2(dabco) (where X-bdc2−is bdc2−= 1,4-benzenedicarboxylate with substituting groups X, DM-bdc2−= 2,5-dimethyl-1,4-benzenedicarboxylate or TM-bdc2−= 2,3,5,6-tetramethyl-1,4-benzenedicarboxylate and dabco = diazabicyclo[2.2.2.]octane) metal-organic frameworks (MOFs) for the adsorptive removal of ethane from ethylene streams. The best performing material from this series is Zn2(TM-bdc)2(dabco) (DMOF-TM), which shows a high ethane uptake of 5.31 mmol g−1at 110 kPa, with a good IAST selectivity of 1.88 towards ethane over ethylene. Through breakthrough measurements a high productivity of 13.1 L kg−1per breakthrough is revealed with good reproducibility over five consecutive cycles. Molecular simulations show that the methyl groups of DMOF-TM are forming a van der Waals trap with the methylene groups from dabco, snuggly fitting the ethane. Further, rarely used high pressure coadsorption measurements, in pressure regimes that most scientific studies on hydrocarbon separation on MOFs ignore, reveal an increase in ethane capacity and selectivity for binary mixtures with increased pressures. The coadsorption measurements reveal good selectivity of 1.96 at 1000 kPa, which is verified also through IAST calculations up to 3000 kPa. This study overall showcases the opportunities that pore engineering by alkyl group incorporation and pressure increase offer to improve hydrocarbon separation in reticular materials.
The Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Fuel Cycle Technology (FCT) is conducting research and development (R&D) on geologic disposal of spent nuclear fuel (SNF) and high-level nuclear waste (HLW). Two high priorities for SFWST disposal R&D are design concept development and disposal system modeling. These priorities are directly addressed in the SFWST Geologic Disposal Safety Assessment (GDSA) control account, which is charged with developing a geologic repository system modeling and analysis capability, and the associated software, GDSA Framework, for evaluating disposal system performance for nuclear waste in geologic media. GDSA Framework is supported by SFWST Campaign and its predecessor the Used Fuel Disposition (UFD) campaign. This report fulfills the GDSA Uncertainty and Sensitivity Analysis Methods work package (SF-21SN01030404) level 3 milestone, Uncertainty and Sensitivity Analysis Methods and Applications in GDSA Framework (FY2021) (M3SF-21SN010304042). It presents high level objectives and strategy for development of uncertainty and sensitivity analysis tools, demonstrates uncertainty quantification (UQ) and sensitivity analysis (SA) tools in GDSA Framework in FY21, and describes additional UQ/SA tools whose future implementation would enhance the UQ/SA capability of GDSA Framework. This work was closely coordinated with the other Sandia National Laboratory GDSA work packages: the GDSA Framework Development work package (SF-21SN01030405), the GDSA Repository Systems Analysis work package (SF-21SN01030406), and the GDSA PFLOTRAN Development work package (SF-21SN01030407). This report builds on developments reported in previous GDSA Framework milestones, particularly M3SF 20SN010304032.
Organic materials are an attractive choice for structural components due to their light weight and versatility. However, because they decompose at low temperatures relative to tradiational materials they pose a safety risk due to fire and loss of structural integrity. To quantify this risk, analysts use chemical kinetics models to describe the material pyrolysis and oxidation using thermogravimetric analysis. This process requires the calibration of many model parameters to closely match experimental data. Previous efforts in this field have largely been limited to finding a single best-fit set of parameters even though the experimental data may be very noisy. Furthermore the chemical kinetics models are often simplified representations of the true de- composition process. The simplification induces model-form errors that the fitting process cannot capture. In this work we propose a methodology for calibrating decomposition models to thermogravimetric analysis data that accounts for uncertainty in the model-form and experimental data simultaneously. The methodology is applied to the decomposition of a carbon fiber epoxy composite with a three-stage reaction network and Arrhenius kinetics. The results show a good overlap between the model predictions and thermogravimetric analysis data. Uncertainty bounds capture devia- tions of the model from the data. The calibrated parameter distributions are also presented. In conclusion, the distributions may be used in forward propagation of uncertainty in models that leverage this material.
The representation of material heterogeneity (also referred to as "spatial variation") plays a key role in the material failure simulation method used in ALEGRA. ALEGRA is an arbitrary Lagrangian-Eulerian shock and multiphysics code developed at Sandia National Laboratories and contains several methods for incorporating spatial variation into simulations. A desirable property of a spatial variation method is that it should produce consistent stochastic behavior regardless of the mesh used (a property referred to as "mesh independence"). However, mesh dependence has been reported using the Weibull distribution with ALEGRA's spatial variation method. This report describes efforts towards providing additional insight into both the theory and numerical experiments investigating such mesh dependence. In particular, we have implemented a discrete minimum order statistic model with properties that are theoretically mesh independent.
Continued creation of harmful emissions such as NOx and soot from compression-ignition engines utilizing mixing-controlled combustion systems (i.e., diesel engines) remains a problem and is the subject of on-going research. The inherently high efficiency, relatively low cost, and numerous other desirable attributes of such engines, coupled with a widely supported infrastructure, motivates their continued advancement. Recently, a scientifically distinct and mechanically simple technology called ducted fuel injection (DFI) has shown a robust ability to allow such engines to operate with simultaneously low engine-out soot and NOx emissions when it is employed with simulated exhaust-gas recirculation. To better understand the property ranges of sustainable, oxygenated-fuel blending stocks that will most improve engine performance, two oxygenated blendstocks were separately blended with a commercial diesel base fuel and tested within a heavy-duty diesel optical engine equipped with a four-duct DFI configuration. Conventional and crank-angle-resolved optical diagnostics were used to elucidate the effects of fuel ignition quality, oxygenate molecular structure, and overall oxygen content on engine performance.
Designing polymers with controlled nanoscale morphologies and scalable synthesis is of great interest in the development of fluorine-free materials for proton-exchange membranes in fuel cells. This study focuses on a precision polyethylene with phenylsulfonic acid branches at every fifth carbon, p5PhSA, with a high ion-exchange capacity (4.2 mmol/g). The polymers self-assemble into hydrophilic and hydrophobic co-continuous nanoscale domains. In the hydrated state, the hydrophilic domain, composed of polar sulfonic acid moieties and water, serves as a pathway for efficient mesoscopic proton conductivity. The morphology and proton transport of p5PhSA are evaluated under hydrated conditions using in situ X-ray scattering and electrochemical impedance spectroscopy techniques. At 40 °C and 95% relative humidity, the proton conductivity of p5PhSA is 0.28 S/cm, which is four times greater than Nafion 117 under the same conditions. Atomistic molecular dynamics (MD) simulations are also used to elucidate the interplay between the structure and the water dynamics. The MD simulations show strong nanophase separation between the percolated hydrophilic and hydrophobic domains over a wide range of water contents. The percolated hydrophilic nanoscale domain facilitates the rapid proton transport in p5PhSA and demonstrates the potential of precise hydrocarbon-based polymers as processible and effective proton-exchange membranes.
Klein, Brianna A.; Song, Yiwen; Ranga, Praneeth; Zhang, Yingying; Feng, Zixuan; Huang, Hsien-Lien; Santia, Marco D.; Badescu, Stefan C.; Gonzalez-Valle, C.U.; Perez, Carlos; Ferri, Kevin; Lavelle, Robert M.; Snyder, David W.; Deitz, Julia D.; Baca, Albert G.; Maria, Jon-Paul; Ramos-Alvarado, Bladimir; Hwang, Jinwoo; Zhao, Hongping; Wang, Xiaojia; Krishnamoorthy, Sriram; Foley, Brian M.; Choi, Sukwon
Heteroepitaxy of β-phase gallium oxide (β-Ga2O3) thin films on foreign substrates shows promise for the development of next-generation deep ultraviolet solar blind photodetectors and power electronic devices. In this work, the influences of the film thickness and crystallinity on the thermal conductivity of ($\bar{2}01$)-oriented β-Ga2O3 heteroepitaxial thin films were investigated. Unintentionally doped β-Ga2O3 thin films were grown on c-plane sapphire substrates with off-axis angles of 0° and 6° toward $\langle$$11\bar{2}0$$\rangle$ via metal–organic vapor phase epitaxy (MOVPE) and low-pressure chemical vapor deposition. The surface morphology and crystal quality of the β-Ga2O3 thin films were characterized using scanning electron microscopy, X-ray diffraction, and Raman spectroscopy. The thermal conductivities of the β-Ga2O3 films were measured via time-domain thermoreflectance. The interface quality was studied using scanning transmission electron microscopy. The measured thermal conductivities of the submicron-thick β-Ga2O3 thin films were relatively low as compared to the intrinsic bulk value. The measured thin film thermal conductivities were compared with the Debye–Callaway model incorporating phononic parameters derived from first-principles calculations. The comparison suggests that the reduction in the thin film thermal conductivity can be partially attributed to the enhanced phonon-boundary scattering when the film thickness decreases. They were found to be a strong function of not only the layer thickness but also the film quality, resulting from growth on substrates with different offcut angles. Growth of β-Ga2O3 films on 6° offcut sapphire substrates was found to result in higher crystallinity and thermal conductivity than films grown on on-axis c-plane sapphire. However, the β-Ga2O3 films grown on 6° offcut sapphire exhibit a lower thermal boundary conductance at the β-Ga2O3/sapphire heterointerface. In addition, the thermal conductivity of MOVPE-grown ($\bar{2}01$)-oriented β-(AlxGa1–x)2O3 thin films with Al compositions ranging from 2% to 43% was characterized. Because of phonon-alloy disorder scattering, the β-(AlxGa1–x)2O3 films exhibit lower thermal conductivities (2.8–4.7 W/m∙K) than the β-Ga2O3 thin films. The dominance of the alloy disorder scattering in β-(AlxGa1–x)2O3 is further evidenced by the weak temperature dependence of the thermal conductivity. This work provides fundamental insight into the physical interactions that govern phonon transport within heteroepitaxially grown β-phase Ga2O3 and (AlxGa1–x)2O3 thin films and lays the groundwork for the thermal modeling and design of β-Ga2O3 electronic and optoelectronic devices.
Metallic enclosures are commonly used to protect electronic circuits against unwanted electromagnetic (EM) interactions. However, these enclosures may be sealed with imperfect mechanical seams or joints. These joints form narrow slots that allow external EM energy to couple into the cavity and then to the internal circuits. This coupled EM energy can severely affect circuit operations, particularly at the cavity resonance frequencies when the cavity has a high Q factor. To model these slots and the corresponding EM coupling, a thin-slot sub-cell model [1] , developed for slots in infinite ground plane and extended to numerical modeling of cavity-backed apertures, was successfully implemented in Sandia's electromagnetic code EIGER [2] and its next-generation counterpart Gemma [3]. However, this thin-slot model only considers resonances along the length of the slot. At sufficiently high frequencies, the resonances due to the slot depth must also be considered. Currently, slots must be explicitly meshed to capture these depth resonances, which can lead to low-frequency instability (due to electrically small mesh elements). Therefore, a slot sub-cell model that considers resonances in both length and depth is needed to efficiently and accurately capture the slot coupling.
Cyber testbeds provide an important mechanism for experimentally evaluating cyber security performance. However, as an experimental discipline, reproducible cyber experimentation is essential to assure valid, unbiased results. Even minor differences in setup, configuration, and testbed components can have an impact on the experiments, and thus, reproducibility of results. This paper documents a case study in reproducing an earlier emulation study, with the reproduced emulation experiment conducted by a different research group on a different testbed. We describe lessons learned as a result of this process, both in terms of the reproducibility of the original study and in terms of the different testbed technologies used by both groups. This paper also addresses the question of how to compare results between two groups' experiments, identifying candidate metrics for comparison and quantifying the results in this reproduction study.
This paper describe our team's experience using minimega, a network emulation system using node and network virtualization, to support evaluation of a set of networked and distributed systems for topology discovery, traffic classification and engineering in the DARPA Searchlight program [18]. We present the methodology we developed to encode network and traffic definitions into an experiment description model, and how our tools compile this model onto the underlying minimega API. We then present three cases studies which demonstrate the ability of our EDM to support experiments with diverse network topologies, diverse traffic mixes, and networks with specialized layer-2 connectivity requirements. We conclude with the overall takeaways from using minimega to support our evaluation process.
Polymerization induced phase separation (PIPS) in a three component thermoset is studied using molecular dynamics simulations of a new coarse-grained thermoset model. The system includes two crosslinker molecules, which differ in their glass transition temperatures (Tg) and chain length and thus have the potential for phase separation. One crosslinker has a high Tg corresponding to a rubbery behavior, and simulations were performed for a short length (4 beads) and a long length (33 beads). The resin and other crosslinker have low Tg. A coarse-grained model is developed with these features and with interaction parameters determined so that for either rubbery crosslinker length, the system is in the liquid state at the cure temperature. For sufficiently slow reaction rates, the long rubbery molecule exhibits PIPS into a bicontinuous array of nanoscale domains, but the short one does not, reproducing recent experimental results. The simulations demonstrate that the reaction rates must be slow enough to allow diffusion to yield phase separation. Particularly, the reaction rate corresponding to the secondary amine must be very slow, else the structure of crosslinked clusters and the substantially increased diffusion time will prevent PIPS.
We study the deformation of tantalum under extreme loading conditions. Experimental velocity data are drawn from both ramp loading experiments on Sandia's Z-machine and gas gun compression experiments. The drive conditions enable the study of materials under pressures greater than 100 GPa. We provide a detailed forward model of the experiments including a model of the magnetic drive for the Z-machine. Utilizing these experiments, we simultaneously infer several different types of physically motivated parameters describing equation of state, plasticity, and anelasticity via the computational device of Bayesian model calibration. Characteristics of the resulting calculated posterior distributions illustrate relationships among the parameters of interest via the degree of cross correlation. The calibrated velocity traces display good agreement with the experiments up to experimental uncertainty as well as improvement over previous calibrations. Examining the Z-shots and gun-shots together and separately reveals a trade-off between accuracy and transferability across different experimental conditions. Implications for model calibration, limitations from model form, and suggestions for improvements are discussed.
Electric vehicles (EVs) represent an important socio-economic development opportunity for islands and remote locations because they can lead to reduced fuel imports, electricity storage, grid services, and environmental and health benefits. This paper presents an overview of opportunities, challenges, and examples of EVs in islands and remote power systems, and is meant to provide background to researchers, utilities, energy offices, and other stakeholders interested in the impacts of electrification of transportation. The impact of uncontrolled EV charging on the electric grid operation is discussed, as well as several mitigation strategies. Of particular importance in many islands and remote systems is taking advantage of local resources by combining renewable energy and EV charging. Policy and economic issues are presented, with emphasis on the need for an overarching energy policy to guide the strategies for EVs growth. The key conclusion of this paper is that an orderly transition to EVs, one that maximizes benefits while addressing the challenges, requires careful analysis and comprehensive planning.
Ionogels are hybrid materials formed by impregnating the pore space of a solid matrix with a conducting ionic liquid. By combining the properties of both component materials, ionogels can act as self-supporting electrolytes in Li batteries. In this study, molecular dynamics simulations are used to investigate the dependence of mechanical properties of silica ionogels on solid fraction, temperature, and pore width. Comparisons are made with corresponding aerogels. We find that the solid matrix fraction increases the moduli and strength of the ionogel. This varies nonlinearly with temperature and strain rate, according to the contribution of the viscous ionic liquid to resisting deformation. Owing to the temperature and strain sensitivity of the ionic liquid viscosity, the mechanical properties approach a linear mixing law at high temperature and low strain rates. The median pore width of the solid matrix plays a complex role, with its influence varying qualitatively with deformation mode. Narrower pores increase the relevant elastic modulus under shear and uniaxial compression but reduce the modulus obtained under uniaxial tension. Conversely, shear and tensile strength are increased by narrowing the pore width. All of these pore size effects become more pronounced as the silica fraction increases. Pore size effects, similar to the effects of temperature and strain rate, are linked to the ease of fluid redistribution within the pore space during deformation-induced changes in the geometry of the pores.
Superionic phases of bulk anhydrous salts based on large cluster-like polyhedral (carba)borate anions are generally stable only well above room temperature, rendering them unsuitable as solid-state electrolytes in energy-storage devices that typically operate at close to room temperature. To unlock their technological potential, strategies are needed to stabilize these superionic properties down to subambient temperatures. One such strategy involves altering the bulk properties by confinement within nanoporous insulators. In the current study, the unique structural and ion dynamical properties of an exemplary salt, NaCB11H12, nanodispersed within porous, high-surface-area silica via salt-solution infiltration were studied by differential scanning calorimetry, X-ray powder diffraction, neutron vibrational spectroscopy, nuclear magnetic resonance, quasielastic neutron scattering, and impedance spectroscopy. Combined results hint at the formation of a nanoconfined phase that is reminiscent of the high-temperature superionic phase of bulk NaCB11H12, with dynamically disordered CB11H12- anions exhibiting liquid-like reorientational mobilities. However, in contrast to this high-temperature bulk phase, the nanoconfined NaCB11H12 phase with rotationally fluid anions persists down to cryogenic temperatures. Moreover, the high anion mobilities promoted fast-cation diffusion, yielding Na+ superionic conductivities of ∼0.3 mS/cm at room temperature, with higher values likely attainable via future optimization. It is expected that this successful strategy for conductivity enhancement could be applied as well to other related polyhedral (carba)borate-based salts. Thus, these results present a new route to effectively utilize these types of superionic salts as solid-state electrolytes in future battery applications.
Poly(carbon monofluoride), or (CF)n, is a layered fluorinated graphite material consisting of nanosized platelets. Here, we present experimental multidimensional solid-state NMR spectra of (CF)n, supported by density functional theory (DFT) calculations of NMR parameters, which overhauls our understanding of structure and bonding in the material by elucidating many ways in which disorder manifests. We observe strong 19F NMR signals conventionally assigned to elongated or "semi-ionic"C-F bonds and find that these signals are in fact due to domains where the framework locally adopts boat-like cyclohexane conformations. We calculate that C-F bonds are weakened but are not elongated by this conformational disorder. Exchange NMR suggests that conformational disorder avoids platelet edges. We also use a new J-resolved NMR method for disordered solids, which provides molecular-level resolution of highly fluorinated edge states. The strings of consecutive difluoromethylene groups at edges are relatively mobile. Topologically distinct edge features, including zigzag edges, crenellated edges, and coves, are resolved in our samples by solid-state NMR. Disorder should be controllable in a manner dependent on synthesis, affording new opportunities for tuning the properties of graphite fluorides.
Finding dense regions of graphs is fundamental in graph mining. We focus on the computation of dense hierarchies and regions with graph nuclei - -a generalization of k-cores and trusses. Static computation of nuclei, namely through variants of 'peeling', are easy to understand and implement. However, many practically important graphs undergo continuous change. Dynamic algorithms, maintaining nucleus computations on dynamic graph streams, are nuanced and require significant effort to port between nuclei, e.g., from k-cores to trusses. We propose a unifying framework to maintain nuclei in dynamic graph streams. First, we show no dynamic algorithm can asymptotically beat re-computation, highlighting the need to experimentally understand variability. Next, we prove equivalence between k-cores on a special hypergraph and nuclei. Our algorithm splits the problem into maintaining the special hypergraph and maintaining k-cores on it. We implement our algorithm and experimentally demonstrate improvements up to 108 x over re-computation. We show algorithmic improvements on k-cores apply to trusses and outperform truss-specific implementations.
In this paper, the effects and mitigation strategies of pulsed loads on medium voltage DC (MVDC) electric ships are explored. Particularly, the effect of high-powered pulsed loads on generator frequency stability are examined. As a method to stabilize a generator which has been made unstable by high-powered pulsed loads, it is proposed to temporarily extract energy from the propulsion system using regenerative propeller braking. The damping effects on generator speed oscillation of this method of control are examined. The impacts on propeller and ship speed are also presented.
Finding dense regions of graphs is fundamental in graph mining. We focus on the computation of dense hierarchies and regions with graph nuclei - -a generalization of k-cores and trusses. Static computation of nuclei, namely through variants of 'peeling', are easy to understand and implement. However, many practically important graphs undergo continuous change. Dynamic algorithms, maintaining nucleus computations on dynamic graph streams, are nuanced and require significant effort to port between nuclei, e.g., from k-cores to trusses. We propose a unifying framework to maintain nuclei in dynamic graph streams. First, we show no dynamic algorithm can asymptotically beat re-computation, highlighting the need to experimentally understand variability. Next, we prove equivalence between k-cores on a special hypergraph and nuclei. Our algorithm splits the problem into maintaining the special hypergraph and maintaining k-cores on it. We implement our algorithm and experimentally demonstrate improvements up to 108 x over re-computation. We show algorithmic improvements on k-cores apply to trusses and outperform truss-specific implementations.
Recently, lithium nitride (Li3N) has been proposed as a chemical warfare agent (CWA) neutralization reagent for its ability to produce nucleophilic ammonia molecules and hydroxide ions in aqueous solution. Quantum chemical calculations can provide insight into the Li3N neutralization process that has been studied experimentally. Here, we calculate reaction-free energies associated with the Li3N-based neutralization of the CWA VX using quantum chemical density functional theory and ab initio methods. We find that alkaline hydrolysis is more favorable to either ammonolysis or neutral hydrolysis for initial P-S and P-O bond cleavages. Reaction-free energies of subsequent reactions are calculated to determine the full reaction pathway. Notably, products predicted from favorable reactions have been identified in previous experiments.
Costs to permit Marine Energy projects are poorly understood. In this paper we examine environmental compliance and permitting costs for 19 projects in the U.S., covering the last 2 decades. Guided discussions were conducted with developers over a 3-year period to obtain historical and ongoing project cost data relative to environmental studies (e.g., baseline or pre-project site characterization as well as post-installation effects monitoring), stakeholder outreach, and mitigation, as well as qualitative experience of the permitting process. Data are organized in categories of technology type, permitted capacity, pre-and post-installation, geographic location, and funding types. We also compare our findings with earlier logic models created for the Department of Energy (i.e., Reference Models). Environmental studies most commonly performed were for Fish and Fisheries, Noise, Marine Habitat/Benthic Studies and Marine Mammals. Studies for tidal projects were more expensive than those performed for wave projects and the range of reported project costs tended to be wider than ranges predicted by logic models. For eight projects reporting full project costs, from project start to FERC or USACE permit, the average amount for environmental permitting compliance was 14.6%.
Automated vehicles (AV) hold great promise for improving safety, as well as reducing congestion and emissions. In order to make automated vehicles commercially viable, a reliable and highperformance vehicle-based computing platform that meets ever-increasing computational demands will be key. Given the state of existing digital computing technology, designers will face significant challenges in meeting the needs of highly automated vehicles without exceeding thermal constraints or consuming a large portion of the energy available on vehicles, thus reducing range between charges or refills. The accompanying increases in energy for AV use will place increased demand on energy production and distribution infrastructure, which also motivates increasing computational energy efficiency.
Based on the latest DOE (Department of Energy) milestones, Sandia needs to convert to IPv6 (Internet Protocol version 6)-only networks over the next 5 years. Our original IPv6 migration plan did not include migrating to IPv6-only networks at any point within the next 10 years, so it must necessarily change. To be successful in this endeavor, we need to evaluate technologies that will enable us to deploy IPv6-only networks early without creating system stability or security issues. We have set up a test environment using technology representative of our production network where we configured and evaluated industry standard translation technologies and techniques. Based on our results, bidirectional translation between IPv4 (Internet Protocol version 4) and IPv6 is achievable with our current equipment, but due to the complexity of the configuration, may not scale well to our production environment.
Underground explosions nonlinearly deform the surrounding earth material and can interact with the free surface to produce spall. However, at typical seismological observation distances the seismic wavefield can be accurately modeled using linear approximations. Although nonlinear algorithms can accurately simulate very near field ground motions, they are computationally expensive and potentially unnecessary for far field wave simulations. Conversely, linearized seismic wave propagation codes are orders of magnitude faster computationally and can accurately simulate the wavefield out to typical observational distances. Thus, devising a means of approximating a nonlinear source in terms of a linear equivalent source would be advantageous both for scenario modeling and for interpretation of seismic source models that are based on linear, far-field approximations. This allows fast linear seismic modeling that still incorporates many features of the nonlinear source mechanics built into the simulation results so that one can have many of the advantages of both types of simulations without the computational cost of the nonlinear computation. In this report we first show the computational advantage of using linear equivalent models, and then discuss how the near-source (within the nonlinear wavefield regime) environment affects linear source equivalents and how well we can fit seismic wavefields derived from nonlinear sources.
The generalized singular value decomposition (GSVD) is a valuable tool that has many applications in computational science. However, computing the GSVD for large-scale problems is challenging. Motivated by applications in hyper-differential sensitivity analysis (HDSA), we propose new randomized algorithms for computing the GSVD which use randomized subspace iteration and weighted QR factorization. Detailed error analysis is given which provides insight into the accuracy of the algorithms and the choice of the algorithmic parameters. We demonstrate the performance of our algorithms on test matrices and a large-scale model problem where HDSA is used to study subsurface flow.
PCalc is a software tool that computes travel-time predictions, ray path geometry and model queries. This software has a rich set of features, including the ability to use custom 3D velocity models to compute predictions using a variety of geometries. The PCalc software is especially useful for research related to seismic monitoring applications.
The continuum-scale electrokinetic porous-media flow and excess charge redistribution equations are uncoupled using eigenvalue decomposition. The uncoupling results in a pair of independent diffusion equations for “intermediate” potentials subject to modified material properties and boundary conditions. The fluid pressure and electrostatic potential are then found by recombining the solutions to the two intermediate uncoupled problems in a matrix-vector multiplication. Expressions for the material properties or source terms in the intermediate uncoupled problem may require extended precision or careful rewriting to avoid numerical cancellation, but the solutions themselves can typically be computed in double precision. The approach works with analytical or gridded numerical solutions and is illustrated through two examples. The solution for flow to a pumping well is manipulated to predict streaming potential and electroosmosis, and a periodic one-dimensional analytical solution is derived and used to predict electroosmosis and streaming potential in a laboratory flow cell subjected to low frequency alternating current and pressure excitation. The examples illustrate the utility of the eigenvalue decoupling approach, repurposing existing analytical solutions or numerical models and leveraging solutions that are simpler to derive for coupled physics.
LocOO3D is a software tool that computes geographical locations for seismic events at regional to global scales. This software has a rich set of features, including the ability to use custom 3D velocity models, correlated observations and master event locations. The LocOO3D software is especially useful for research related to seismic monitoring applications, since it allows users to easily explore a variety of location methods and scenarios and is compatible with the CSS3.0 data format used in monitoring applications. The LocOO3D software, User's Manual, and Examples are available on the web at: https://github.com/sandialabs/LocOO3D For additional information on GeoTess, SALSA3D, RSTT, and other related software, please see: https://github.com/sandialabs/GeoTessJava, www.sandia.gov/geotess, www.sandia.gov/salsa3d, and www.sandia.gov/rstt