Publications

In this report with discuss load-balancing research and results in the context of the DARMA/VT project.

The goal of this exploratory express LDRD is to demonstrate a reproducible laser activated doping diagnostic for eventual use on the Z machine by producing consistent spectral line emission with radiances above 10⁵ W sr^-1 nm^-1 111^-2 from a variety of dopant materials. Here we show that while such radiances are achieved, the line emission is from regions with high electron densities, and close to the laser ablation surface. Therefore, it would be more ideal to improve current optical spectroscopy capabilities on Z to view radiances around 10⁴ W sr^-l nm^-l m^-2 . We also discuss the viability of a modular beam path that can be remotely aligned and used on the Z machine. This technique can be used to make spatially resolved measurements of electric and magnetic field strengths and electron densities within the Z power flow and load regions. The measurements can also be used to inform theory and simulation efforts needed to design the next generation of pulsed power capabilities. This was funded as an exploratory LDRD project, number: 214278

As the size and complexity of high performance computing (HPC) systems grow in line with advancements in hardware and software technology, HPC systems increasingly suffer from performance variations due to shared resource contention as well as software-and hardware-related problems. Such performance variations can lead to failures and inefficiencies, which impact the cost and resilience of HPC systems. To minimize the impact of performance variations, one must quickly and accurately detect and diagnose the anomalies that cause the variations and take mitigating actions. However, it is difficult to identify anomalies based on the voluminous, high-dimensional, and noisy data collected by system monitoring infrastructures. This paper presents a novel machine learning based framework to automatically diagnose performance anomalies at runtime. Our framework leverages historical resource usage data to extract signatures of previously-observed anomalies. We first convert collected time series data into easy-to-compute statistical features. We then identify the features that are required to detect anomalies, and extract the signatures of these anomalies. At runtime, we use these signatures to diagnose anomalies with negligible overhead. We evaluate our framework using experiments on a real-world HPC supercomputer and demonstrate that our approach successfully identifies 98 percent of injected anomalies and consistently outperforms existing anomaly diagnosis techniques.

The Department of Energy maintains an up-to-date documentation of the number of available full drawdowns of each of the caverns owned by the Strategic Petroleum Reserve (SPR). This information is important for assessing the SPR's ability to deliver oil to domestic oil companies expeditiously if national or world events dictate a rapid sale and deployment of the oil reserves. What factors go into assessing available drawdowns? Determining the number of drawdowns requires the consideration of several factors regarding cavern and wellbore integrity and stability, including stress states caused by cavern geometry and operations, salt damage caused by dilatant and tensile stresses, the effect of enhanced creep on wellbore integrity, and the sympathetic stress effect of operations on neighboring caverns. A consensus has now been built regarding the assessment of drawdown capabilities and risks for the SPR caverns. The process involves an initial assessment of the pillar-to-diameter (P/D) ratio for each cavern with respect to neighboring caverns. Ideally, it is desired to keep this value greater than 1.0, which is in line with most industry design standards and should ensure cavern integrity and prevent loss of fluids to the surrounding rock mass. However, many of the SPR caverns currently have a P/D less than 1.0, or will likely have a low P/D after one or two full drawdowns. For these caverns, it is important to examine the structural integrity with more detail using geomechanical models. Finite-element geomechanical models have been used to determine the stress states in the pillars following successive drawdowns. By computing the tensile and dilatant stresses in the salt, areas of potential structural instability can be identified that may represent "red flags" for additional drawdowns. These analyses have found that many caverns will maintain structural integrity even when grown via drawdowns to dimensions resulting in a P/D of less than 1.0. The analyses have also confirmed that certain caverns should only be completely drawn down one time. As the SPR caverns are utilized and partial drawdowns are performed to remove oil from the caverns (e.g., for occasional oil sales authorized by the Congress or the President), the changes to the cavern volumes casused by these procedures must be tracked and accounted for so that an ongoing assessment of the cavern's drawdown capacity may be continued. A proposed methodology for assessing and tracking the available drawdowns for each cavern is presented in this report.

Abstract not provided.

External electric field and plasma assisted combustion show great potential for combustion enhancement, e.g., emission and ignition control. To understand soot suppression by external electric fields and flame ignition in spark ignition engines, flame ion chemistry needs to be investigated and developed. In this work, comprehensive and systematic investigations of neutral and ion chemistry are conducted in premixed rich methane flames. Cations are measured by quadrupole molecular beam mass spectrometry (MBMS), and neutrals are measured by synchrotron vacuum ultra violet photoionization time of flight MBMS (SVUV-PI-TOF-MBMS). The molecular formula and dominant isomers of various measured cations are identified based on literature survey and quantum chemistry calculations. Experimentally, we found that H3O+ is the dominant cation in slightly rich flame (ϕ=1.5), but C3H3+ is the most significant in very rich flames (ϕ=1.8 and 2.0). An updated ion chemistry model is proposed and used to explain the effects of changing equivalence ratio. To further verify key ion-neutral reaction pathways, measured neutral profiles are compared with cation profiles experimentally. Detailed cation and neutral measurements and numerical simulations by this work help to understand and develop ion chemistry models. Deficiencies in our current understanding of ion chemistry are also highlighted to motivate further research.

The purpose of this report is to review technical issues and previous studies relevant to the performance evaluation of dry storage systems during vacuum drying and long-term storage operations and to describe vital experimental components under development that are required for conducting advanced studies. There is a need to validate the extent of water removal in a multi-assembly system using an industrial vacuum-drying procedure, as operational conditions leading to incomplete drying may have potential impacts on the fuel, cladding, and other components in the system. Waterproof, electrically-heated spent fuel rod simulators are under development to enable experimental simulation of the entire de-watering and drying process. Specially-designed, unheated mock fuel rods are used to monitor internal rod pressures and study water removal from simulated failed fuel rods. Furthermore, single assembly studies conducted previously cannot incorporate important inter-assembly heat-transfer physics, so plans for harvesting up to five full-length 5 x 5 truncated assemblies from a single 17 x 17 PWR skeleton are described.

The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources. The primary physics codes in the ExaWind project are Nalu-Wind, which is an unstructured-grid solver for the acoustically incompressible Navier-Stokes equations, and OpenFAST, which is a whole-turbine simulation code. The Nalu-Wind model consists of the mass-continuity Poisson-type equation for pressure and a momentum equation for the velocity. For such modeling approaches, simulation times are dominated by linear-system setup and solution for the continuity and momentum systems. For the ExaWind challenge problem, the moving meshes greatly affect overall solver costs as reinitialization of matrices and recomputation of preconditioners is required at every time step. This milestone represents the culmination of several parallel development activities towards the goal of establishing a full-physics simulation capability for modeling wind turbines operating in turbulent atmospheric inflow conditions. The demonstration simulation performed in this milestone is the first step towards the "ground truth" simulation and includes the following components: neutral atmospheric boundary layer inflow conditions generated using a precursor simulation, a hybrid RANS/LES simulation of the wall-resolved turbine geometry, hybridization of the turbulence equations using a blending function approach to transition from the atmospheric scales to the blade boundary layer scales near the turbine, fluid-structure interaction (FSI) that accounts for the complete set of blade deformations (bending, twisting and pitch motion, yaw and tower displacements) by coupling to a comprehensive turbine dynamics code (OpenFAST). The use of overset mesh methodology for the simulations in this milestone presents a significant deviation from the previous efforts where a sliding mesh approach was employed to model the rotation of the turbine blades. The choice of overset meshes was motivated by the need to handle arbitrarily large deformations of the blade and to allow for blade pitching in the presence of a controller and the ease of mesh generation compared to the sliding mesh approach. FSI and the new timestep algorithm used in the simulations were developed in partnership with the A2e High-Fidelity Modeling project. The individual physics components were verified and validated (V%V) through extensive code-to-code comparisons and with experiments where possible. The detailed V&V efforts provide confidence in the final simulation where these physics models were combined together even though no detailed experimental data is available to perform validation of the final configuration. Taken together, this milestone successfully demonstrated the most advanced simulation to date that has been performed with Nalu-Wind.

Performance to Plan highlights are provided.

This study was initiated to quantify and characterize the uncertainty associated with the degradation mechanisms impacting normal dry storage operations for used nuclear fuel (UNF) and normal conditions of transport in support of the Spent Fuel and Waste Science & Technology Campaign (SFWST) and its effectiveness to rank the data needs and parameters of interest. This report describes the technical basis and guidance resulting from the development of software to perform uncertainty quantification (UQ) by developing and describing a holistic model that integrates the various processes controlling Atmospheric Stress Corrosion Cracking (ASCC) in the specific context of Interim Spent Fuel Storage Installations (ISFSIs). These processes include the daily and annual cycles of temperature and humidity associated with the environment, the deposition of chloride-containing aerosol particles, pit formation, pit-to-crack transition, and crack propagation.

Prior research in falls risk classification using inertial sensors has relied on the use of engineered features, which has concluded in a feature space containing hundreds of features that are likely redundant and possibly irrelevant. In this paper, we propose using fully convolutional neural networks (FCNNs) to classify older adults at low or high risk of falling using inertial sensor data collected from a smartphone. Due to the limited nature of older adult inertial gait data sets, we first pre-train the FCNN models using a publicly available data set for pedestrian activity recognition. Then via transfer learning, we train the network for falls risk classification. We reveal that via transfer learning, our falls risk classifier obtains an area under the receiver operating characteristic curve of 93.3%, which is 10.6% higher than the equivalent model trained without the use of transfer learning. Moreover, we show that our method outperforms other standard machine learning classifiers trained on features developed in prior research.

We present that self-assembly of anisotropic plasmonic nanomaterials into ordered superstructures has become popular in nanoscience because of their unique anisotropic optical and electronic properties. Gold nanorods (GNRs) are a well-defined functional building block for fabrication of these superstructures. They possess important anisotropic plasmonic characteristics that are resulted from strong local electric field and responsive to visible and near infrared light, which attracts extensive attention in various fields, such as biomedical technologies, plasmon-enhanced spectroscopies, and optoelectronic devices. There are recent examples of assembling the GNRs into ordered arrays or superstructures through processes such as solvent evaporation, interfacial assembly. In this review, we describe recent progresses in the development of the self-assembled GNR arrays with focus on the formation of oriented GNR arrays on substrates. We discuss key driving forces such as van der Waals (vdW), electrostatic interactions, steric force, and depletion force. We survey different strategies and self-assembly processes of forming oriented GNR arrays. Lastly, we also overview the applications of the oriented GNR arrays in optoelectronic devices especially surface enhanced Raman scattering (SERS). At the end of this review, we briefly summarize the review and discuss future challenges and perspectives.

With the successes deep neural networks have achieved across a range of applications, researchers have been exploring computational architectures to more efficiently execute their operation. In addition to the prevalent role of graphics processing units (GPUs), many accelerator architectures have emerged. Neuromorphic is one such particular approach which takes inspiration from the brain to guide the computational principles of the architecture including varying levels of biological realism. In this paper we present results on using the SpiNNaker neuromorphic platform (48-chip model) for deep learning neural network inference. We use the Sandia National Laboratories developed Whetstone spiking deep learning library to train deep multi-layer perceptrons and convolutional neural networks suitable for the spiking substrate on the neural hardware architecture. By using the massively parallel nature of SpiNNaker, we are able to achieve, under certain network topologies, substantial network tiling and consequentially impressive inference throughput. Such high-throughput systems may have eventual application in remote sensing applications where large images need to be chipped, scanned, and processed quickly. Additionally, we explore complex topologies that push the limits of the SpiNNaker routing hardware and investigate how that impacts mapping software-implemented networks to on-hardware instantiations.

The ability of an intelligent agent to process complex signals such as those found in audio or video depends heavily on the nature of the internal representation of the relevant information. This work explores the mechanisms underlying this process by investigating theories inspired by the function of the neocortex. In particular, we focus on the phenomenon of polychronization, which describes the self-organization in a spiking neural network resulting from the interplay between network structure, driven spiking activity, and synaptic plasticity. What emerges are groups of neurons that exhibit reproducible, time-locked patterns of spiking activity. We propose that this representation is well suited to spatio-temporal signal processing, as it naturally resembles patterns found in real-world signals. We explore the computational properties of this approach and demonstrate the ability of a simple polychronizing network to learn different spatio-temporal signals.

Abstract not provided.

Celliers et al. (Reports, 17 August 2018, p. 677), in an attempt to reconcile differences in inferred metallization pressures, provide an alternative temperature analysis of the Knudson et al. experiments (Reports, 26 June 2015, p. 1455). We show here that this reanalysis implies an anomalously low specific heat for the metallic fluid that is clearly inconsistent with first-principles calculations.

Reactions of the methylidyne (CH) radical with ammonia (NH 3 ), methylamine (CH 3 NH 2 ), dimethylamine ((CH 3 ) 2 NH), and trimethylamine ((CH 3 ) 3 N) have been investigated under multiple collision conditions at 373 K and 4 Torr. The reaction products are detected by using soft photoionization coupled to orthogonal acceleration time-of-flight mass spectrometry at the Advanced Light Source (ALS) synchrotron. Kinetic traces are employed to discriminate between CH reaction products and products from secondary or slower reactions. Branching ratios for isomers produced at a given mass and formed by a single reaction are obtained by fitting the observed photoionization spectra to linear combinations of pure compound spectra. The reaction of the CH radical with ammonia is found to form mainly imine, HN?CH 2 , in line with an addition-elimination mechanism. The singly methyl-substituted imine is detected for the CH reactions with methylamine, dimethylamine, and trimethylamine. Dimethylimine isomers are formed by the reaction of CH with dimethylamine, while trimethylimine is formed by the CH reaction with trimethylamine. Overall, the temporal profiles of the products are not consistent with the formation of aminocarbene products in the reaction flow tube. In the case of the reactions with methylamine and dimethylamine, product formation is assigned to an addition-elimination mechanism similar to that proposed for the CH reaction with ammonia. However, this mechanism cannot explain the products detected by the reaction with trimethylamine. A C - H insertion pathway may become more probable as the number of methyl groups increases.

Accurate and efficient constitutive modeling remains a cornerstone issue for solid mechanics analysis. Over the years, the LAME advanced material model library has grown to address this challenge by implementing models capable of describing material systems spanning soft polymers to stiff ceramics including both isotropic and anisotropic responses. Inelastic behaviors including (visco)plasticity, damage, and fracture have all incorporated for use in various analyses. This multitude of options and flexibility, however, comes at the cost of many capabilities, features, and responses and the ensuing complexity in the resulting implementation. Therefore, to enhance confidence and enable the utilization of the LAME library in application, this effort seeks to document and verify the various models in the LAME library. Specifically, the broader strategy, organization, and interface of the library itself is first presented. The physical theory, numerical implementation, and user guide for a large set of models is then discussed. Importantly, a number of verification tests are performed with each model to not only have confidence in the model itself but also highlight some important response characteristics and features that may be of interest to end-users. Finally, in looking ahead to the future, approaches to add material models to this library and further expand the capabilities are presented.

A variety of recent work has expanded capabilities in LAMÉ with respect to anisotropic and modular plasticity model. In this context, modular refers to a flexible framework and consistent implementation such that different hardening functional forms may all be incorporated into the same material model implementation rather than needing a new model for each description. However, such work has been focused on three-dimensional formulations and limited attention has been paid to structural formulations; i.e. for use with beam or shell elements. As a first step to bringing some of these recent advances towards structural elements, modular isotropic hardening capabilities will be added to the J2 von Mises plane-stress plasticity formulation of Simo and Taylor. To accomplish this effort, in Section 2 and 3 the theory and numerical formulation of the model are given. Specific functional forms of the hardening and example syntax to use them are then presented in Section 4 while verification exercises are documented in Section 5. Finally, some concluding thoughts about future work are given in Section 6.

Abstract not provided.

This Storm Water Pollution Prevention Plan (SWPPP) has been prepared for the C902 Data Center Replacement Facility in Livermore, California. C902 Data Center Replacement Facility is a proposed development consisting of the construction of an approximately 8,900 square foot new single-story building and an approximately 4,200 square foot equipment yard. The project also includes paved parking lot, hardscape and landscape consisting of 2-6" stone at retention ponds and wood mulch elsewhere. The property is owned by the U.S. Department of Energy, and managed and operated by National Technology & Engineering Solutions of Sandia, LLC.

We introduce a 1D planar static model to elucidate the underlying mechanism of large ion current losses in the vacuum convolute and the inner magnetically insulated transmission line (MITL) of the Z machine. We consider E×B electron flow, parallel to the electrodes, and ion motion across the vacuum gap, for given voltage V, gap distance d, anode magnetic field Ba, and vacuum electron current ΔI. This model has been introduced and solved before by Desjarlais [Phys. Rev. Lett. 59, 2295 (1987)PRLTAO0031-900710.1103/PhysRevLett.59.2295] for the applied magnetic field ion diode. Here we apply it to convolute and inner MITL ion losses of Z, relaxing the fix magnetic flux condition of that reference. In the absence of ions we show that the electron vacuum flow must be close to the anode if its current exceeds the value given by the local flow impedance, implying high electric fields there. We then introduce space charge limited ion emission from the anode, neglecting the magnetic force on ions. We obtain the solution of the steady state equations for two special cases: (a) when both the electric potential and the electric field are zero inside the gap, and there is a layer of electrons not carrying current that neutralizes the ion charge between the virtual and the electrode cathode, making that region electric field free, and (b) when the electric field is zero inside the gap, but the potential is not, and zero electron charge between that point and the physical cathode. For case (a) we obtain an ion current density which we conjecture is the maximum attainable for any electron charge distribution in the electron current carrying layer, given V,d,Ba,ΔI an ion species. We obtain the enhancement factor for both cases with respect to the ion-only Child-Langmuir ion current density, and show that it can be significantly larger than that of the electron saturated flow case. Furthermore, imposing electron current conservation as the flow enters the inner MITL from the four outer MITLs, we recover the well-known dependence jion∼V3/2/d2, where voltage and gap are taken near the joining point of those outer MITLs. The implications and limitations of the proposed model are discussed.

This work details the development of an algorithm to determine 3D position and in plane size and shape of particles by exploiting the perspective shift capabilities of a plenoptic camera combined with stereo-matching methods. This algorithm is validated using an experimental data set previously examined in a refocusing based particle location study in which a static particle field is translated to provide known depth displacements at varied magnification and object distances. Examination of these results indicates increased accuracy and precision is achieved compared to a previous refocusing based method at significantly reduced computational costs. The perspective shift method is further applied to fragment localization and sizing in a lab scale fragmenting explosive.

Enhancement-mode Al0.7Ga0.3N-channel high electron mobility transistors (HEMTs) were achieved through a combination of recessed etching and fluorine ion deposition to shift the threshold voltage (VTH) relative to depletion-mode devices by +5.6 V to VTH = +0.5 V. Accounting for the threshold voltage shift (ΔVTH), current densities of approximately 30 to 35 mA/mm and transconductance values of 13 mS/mm were achieved for both the control and enhancement mode devices at gate biases of 1 V and 6.6 V, respectively. Little hysteresis was observed for all devices, with voltage offsets of 20 mV at drain currents of 1.0 × 10-3mA/mm. Enhancement-mode devices exhibited slightly higher turn-on voltages (+0.38 V) for forward bias gate currents. Piecewise evaluation of a threshold voltage model indicated a ΔVTH of +3.3 V due to a gate recess etching of 12 nm and an additional +2.3 V shift due to fluorine ions near the AlGaN surface.

Compositing of ground penetrating radar (GPR) scans of differing frequencies have been found to produce cleaner images at depth using the Gaussian mixture model (GMM) feature of the expectation-maximization (EM) algorithm. GPR scans at various heights (“Stand Off”), as well as ground-based scans, have been studied. In this paper, we compare the GPR response from a chirp excitation function-based radar with the response from the EM GMM algorithm compositing process, using the same mix of frequencies. A chirp excitation pulse was found to be effective in delineating the defined buried object, but the resulting image is less sharp than the GMM EM method.

The use of untrusted design tools, components, and designers, coupled with untrusted device fabrication, introduces the possibility of malicious modifications being made to integrated circuits (ICs) during their design and fabrication. These modifications are known as hardware trojans. The widespread use of commercially purchased 3rd party intellectual property (3PIP) and commercial design tools extends even into trusted design flows. Unfortunately, due to the theoretical result that there is no program that can decide whether any other program will eventually halt, we know that the properties of a program, or circuit, cannot be known in advance of running it. While we can design a circuit to meet some functional specification and generate a simulation or test suite to obtain at least probabilistic confidence that the circuit implements the intended functionality, we cannot test a circuit for unintended functionality due to the combinatorially large state space. To address these concerns, we have developed a design-time method for automatically and systematically modifying portions of a design that exhibit characteristics of hardware trojans. After each modification, the functionality of the design is verified against a comprehensive simulation suite to ensure that the intended circuit functionality has not been changed. This approach can be applied to any digital circuit and does not rely on secret keys or obfuscation.

Applications in environmental monitoring, surveillance and patrolling typically require a network of mobile agents to collectively gain information regarding the state of a static or dynamical process evolving over a region. However, these networks of mobile agents also introduce various challenges, including intermittent observations of the dynamical process, loss of communication links due to mobility and packet drops, and the potential for malicious or faulty behavior by some of the agents. The main contribution of this paper is the development of resilient, fully-distributed, and provably correct state estimation algorithms that simultaneously account for each of the above considerations, and in turn, offer a general framework for reasoning about state estimation problems in dynamic, failure-prone and adversarial environments. Specifically, we develop a simple switched linear observer for dealing with the issue of time-varying measurement models, and resilient filtering techniques for dealing with worst-case adversarial behavior subject to time-varying communication patterns among the agents. Our approach considers both communication patterns that recur in a deterministic manner, and patterns that are induced by random packet drops. For each scenario, we identify conditions on the dynamical system, the patrols, the nominal communication network topology, and the failure models that guarantee applicability of our proposed techniques. Finally, we complement our theoretical results with detailed simulations that illustrate the efficacy of our algorithms in the presence of the technical challenges described above.

This report documents proposed improvements to an apparatus for measuring flow rates and aerosol retention in stress corrosion cracks (SCCs). The potential for SCCs in canister walls is a concern for dry cask storage systems for spent nuclear fuel. Some of the canisters in these systems are backfilled to significant pressures to promote heat rejection via internal convection. Pressure differentials covering the upper limit of commercially available dry cask storage systems are the focus of the current test assembly. Initial studies will be conducted using engineered microchannels with characteristic dimensions expected in SCCs that hypothetically could form in dry storage canister walls. In a previous study, an apparatus and procedures were developed and implemented to investigate aerosol retention in a simple microchannel with an SCC-like opening of 28.9 gm (0.00110 in.). The width was 12.7 mm (0.500 in.), and the length was 8.86 mm (0.349 in.). These initial results indicated 44% of the aerosols available for transmission were retained upstream of microchannel However, limitations in the aerosol instruments available at the time of the preliminary study introduced known biases into the measurements. While these biases were identified and quantified, their presence introduced unwanted degrees of freedom into the measurements and reduced accuracy. Because these aerosol particle sizers (APS) were limited to sampling at atmospheric pressure, a mass flow controller was used to supply the sample upstream of the crack to the APS. The average line loss across all particle sizes for this mass flow controller was 50%. The sample downstream of the crack was delivered via a mass flow meter and caused a line loss of 20%. Another source of bias was using separate (but identical) instruments to measure the aerosols upstream and downstream of the microchannel, which could register up to 40% different when measuring the same sample stream. The experience of conducting the preliminary study highlighted the need for improvements in the experimental approach that would eliminate these biases and benefit future studies. An aerosol analyzer has been identified and ordered that is ideally suited for this study and should substantially mitigate these biases. Moving forward in the near term, the same simple microchannel will be further investigated using the improved aerosol instrumentation. Additionally, an offset microchannel with a step in the flow path will be designed and fabricated for similar testing. Looking out further, the capability to produce and test laboratory generated SCCs will be developed.

The primary objective of this report is to determine a viable pipe preheating system for a chloride-salt blend that can preheat the pipe to 450°C and withstand a maximum exposure temperature of 750°C. Preheating involves heating the pipe to a specific desired temperature, called preheat temperature, of the pipe. The temperature is maintained by heated molten salt flowing through the piping system. This report reviews 5-types of pipe preheating systems, of which three pipe preheating systems- MI cable, heat tape, and ceramic fiber heaters, were found to be viable for the Gen 3 Liquid Pathway application. The report reviews the pipe preheating efficiency of conduction verses radiant heat transfer. For each of the 5 types of pipe preheating systems, the report describes the system and addresses installation requirements, temperature control, reliability survey, and pre-construction verification testing for the most applicable preheating system. Under Appendix A, images from design drawings demonstrate pipe routing with the preheating system and insulation attached to the pipe along with pipe guides and pipe supports, as designed using Caesar II finite element analysis within the SNL NSTTF Solar Power Tower.

Lab based x-ray phase contrast imaging (XPCI) systems have historically focused on medical applications, but there is growing interest in material science applications for non-destructive analysis of low density materials. Extending this imaging technique to higher density materials or larger samples requires higher aspect ratio gratings, to allow the use of a higher energy x-ray source. In this work, we demonstrate the use of anisotropic silicon (Si) etching in potassium hydroxide (KOH), to achieve extremely high aspect ratio gratings. This method has been shown to be effective in fabricating deep, uniform gratings by taking advantage of the etch selectivity of differing crystalline planes of silicon. Our work has demonstrated a method for determining Si crystalline plane directions, specific to (110) Si wafers, enabling high alignment accuracy of the etch mask to these crystalline planes.

State of the art grating fabrication currently limits the maximum source energy that can be used in lab based x-ray phase contrast imaging (XPCI) systems. In order to move to higher source energies, and image high density materials or image through encapsulating barriers, new grating fabrication methods are needed. In this work we have analyzed a new modality for grating fabrication that involves precision alignment of etched gratings on both sides of a substrate, effectively doubling the thickness of the grating. We have achieved a front-to-backside feature alignment accuracy of 0.5 µm demonstrating a methodology that can be applied to any grating fabrication approach extending the attainable aspect ratios allowing higher energy lab based XPCI systems.

Silicone foam is used as a shock mitigation material in a variety of systems to protect internal components from being damaged during external shock or impact loading. Characterizing the shock mitigation response of silicone foam under a variety of scenarios is a critical step in designing and/or evaluating new shock mitigation systems. In this study, a Kolsky bar with pre-compression capability was used with a passive radial confinement tube to subject the sample to various levels of pre-strain followed by impact loading. The effects of both pre-strain and impact velocity on impact energy dissipation behavior were investigated for silicone foam. The energy dissipation response of silicone foam is compared to a silicone rubber manufactured using the same processing methods to understand the energy dissipation characteristics of silicone foams transitioning to a silicone rubber. The final density of the foam or rubber plays a key role in both the total energy dissipation ratio in the time domain and the energy dissipation ratio as a function of frequency in the frequency domain.

New manufacturing technologies such as additive manufacturing require research and development to minimize the uncertainties in the produced parts. The research involves experimental measurements and large simulations, which result in huge quantities of data to store and analyze. We address this challenge by alleviating the data storage requirements using lossy data compression. We select wavelet bases as the mathematical tool for compression. Unlike images, additive manufacturing data is often represented on irregular geometries and unstructured meshes. Thus, we use Alpert tree-wavelets as bases for our data compression method. We first analyze different basis functions for the wavelets and find the one that results in maximal compression and miminal error in the reconstructed data. We then devise a new adaptive thresholding method that is data-agnostic and allows a priori estimation of the reconstruction error. Finally, we propose metrics to quantify the global and local errors in the reconstructed data. One of the error metrics addresses the preservation of physical constraints in reconstructed data fields, such as divergence-free stress field in structural simulations. While our compression and decompression method is general, we apply it to both experimental and computational data obtained from measurements and thermal/structural modeling of the sintering of a hollow cylinder from metal powders using a Laser Engineered Net Shape process. The results show that monomials achieve optimal compression performance when used as wavelet bases. The new thresholding method results in compression ratios that are two to seven times larger than the ones obtained with commonly used thresholds. Overall, adaptive Alpert tree-wavelets can achieve compression ratios between one and three orders of magnitude depending on the features in the data that are required to preserve. These results show that Alpert tree-wavelet compression is a viable and promising technique to reduce the size of large data structures found in both experiments and simulations.

Computational fluid dynamics (CFD)-based wear predictions are computationally expensive to evaluate, even with a high-performance computing infrastructure. Thus, it is difficult to provide accurate local wear predictions in a timely manner. Data-driven approaches provide a more computationally efficient way to approximate the CFD wear predictions without running the actual CFD wear models. In this paper, a machine learning (ML) approach, termed WearGP, is presented to approximate the 3D local wear predictions, using numerical wear predictions from steady-state CFD simulations as training and testing datasets. The proposed framework is built on Gaussian process (GP) and utilized to predict wear in a much shorter time. The WearGP framework can be segmented into three stages. At the first stage, the training dataset is built by using a number of CFD simulations in the order of O(102). At the second stage, the data cleansing and data mining processes are performed, where the nodal wear solutions are extracted from the solution database to build a training dataset. At the third stage, the wear predictions are made, using trained GP models. Two CFD case studies including 3D slurry pump impeller and casing are used to demonstrate the WearGP framework, in which 144 training and 40 testing data points are used to train and test the proposed method, respectively. The numerical accuracy, computational efficiency and effectiveness between the WearGP framework and CFD wear model for both slurry pump impellers and casings are compared. It is shown that the WearGP framework can achieve highly accurate results that are comparable with the CFD results, with a relatively small size training dataset, with a computational time reduction on the order of 105 to 106.

In a previous study, we described a new abstract circuit model for reversible computation called Asynchronous Ballistic Reversible Computing (ABRC), in which localized information bearing pulses propagate ballistically along signal paths between stateful abstract devices, and elastically scatter off those devices serially, while updating the device state in a logically-reversible and deterministic fashion. The ABRC model has been shown to be capable of universal computation. In the research reported here, we begin exploring how the ABRC model might be realized in practice using single flux quantum (SFQ) solitons (fluxons) in superconducting Josephson junction (JJ) circuits. One natural family of realizations could utilize fluxon polarity to represent binary data in individual pulses propagating near-ballistically along discrete or continuous long Josephson junctions (LJJs) or microstrip passive transmission lines (PTLs), and utilize the flux charge (-1, 0, +1) of a JJ-containing superconducting loop with Φ₀ < I_cL < 2Φ₀ to encode a ternary state variable internal to a device. A natural question then arises as to which of the definable abstract ABRC device functionalities using this data representation might be implementable using a JJ circuit that dissipates only a small fraction of the input fluxon energy. We discuss conservation rules and symmetries considered as constraints to be obeyed in these circuits, and begin the process of classifying the possible ABRC devices in this family having up to 3 bidirectional I/O terminals, and up to 3 internal states.

Even as today's most prominent spin-based qubit technologies are maturing in terms of capability and sophistication, there is growing interest in exploring alternate material platforms that may provide advantages, such as enhanced qubit control, longer coherence times, and improved extensibility. Recent advances in heterostructure material growth have opened new possibilities for employing hole spins in semiconductors for qubit applications. Undoped, strained Ge/SiGe quantum wells are promising candidate hosts for hole spin-based qubits due to their low disorder, large intrinsic spin-orbit coupling strength, and absence of valley states. Here, we use a simple one-layer gated device structure to demonstrate both a single quantum dot as well as coupling between two adjacent quantum dots. The hole effective mass in these undoped structures, m∗ ∼ 0.08 m 0, is significantly lower than for electrons in Si/SiGe, pointing to the possibility of enhanced tunnel couplings in quantum dots and favorable qubit-qubit interactions in an industry-compatible semiconductor platform.

Sierra is an engineering mechanics simulation code suite supporting the Nation's Nuclear Weapons mission as well as other customers. It has explicit ties to Sandia National Labs' workflow, including geometry and meshing, design and optimization, and visualization. Distinguishing strengths include "application aware" development, scalability, SQA and V&V, multiple scales, and multi-physics coupling. This document is intended to help new and existing users of Sierra as a user manual and troubleshooting guide.

Presented in this document is a small portion of the tests that exist in the Sierra/SolidMechanics (Sierra/SM) verification test suite. Most of these tests are run nightly with the Sierra/SM code suite, and the results of the test are checked versus the correct analytical result. For each of the tests presented in this document, the test setup, a description of the analytic solution, and comparison of the Sierra/SM code results to the analytic solution is provided. Mesh convergence is also checked on a nightly basis for several of these tests. This document can be used to confirm that a given code capability is verified or referenced as a compilation of example problems. Additional example problems are provided in the Sierra/SM Example Problems Manual. Note, many other verification tests exist in the Sierra/SM test suite, but have not yet been included in this manual.

This user's guide documents capabilities in Sierra/SolidMechanics which remain "in-development" and thus are not tested and hardened to the standards of capabilities listed in Sierra/SM 4.52 User's Guide. Capabilities documented herein are available in Sierra/SM for experimental use only until their official release. These capabilities include, but are not limited to, novel discretization approaches such as peridynamics and the reproducing kernel particle method (RKPM), numerical fracture and failure modeling aids such as the extended finite element method (XFEM) and J-integral, explicit time step control techniques, dynamic mesh rebalancing, as well as a variety of new material models and finite element formulations.

This is an addendum to the Sierra/SolidMechanics 4.52 User's Guide that documents additional capabilities available only in alternate versions of the Sierra/SolidMechanics (Sierra/SM) code. These alternate versions are enhanced to provide capabilities that are regulated under the U.S. Department of State's International Traffic in Arms Regulations (ITAR) export control rules. The ITAR regulated codes are only distributed to entities that comply with the ITAR export control requirements. The ITAR enhancements to Sierra/SM include material models with an energy-dependent pressure response (appropriate for very large deformations and strain rates) and capabilities for blast modeling. This document is an addendum only; the standard Sierra/SolidMechanics 4.52 User's Guide should be referenced for most general descriptions of code capability and use.

Sierra/SolidMechanics (Sierra/SM) is a Lagrangian, three-dimensional finite element analysis code for solids and structures subjected to extensive contact and large deformations, encompassing explicit and implicit dynamic as well as quasistatic loading regimes. This document supplements the primary Sierra/SM 4.52 User's Guide, describing capabilities specific to Goodyear analysis use cases, including additional implicit solver options, material models, finite element formulations, and contact settings.

Magnetostrictive Co77Fe23 films are fully suspended to produce free-standing, clamped-clamped, microbeam resonators. A negative or positive shift in the resonant frequency is observed for magnetic fields applied parallel or perpendicular to the length of the beam, respectively, confirming the magnetoelastic nature of the shift. Notably, the resonance shifts linearly with higher-bias fields oriented perpendicular to the beam's length. Domain imaging elucidates the distinction in the reversal processes along the easy and hard axes. Together, these results suggest that through modification of the magnetic anisotropy, the frequency shift and angular dependence can be tuned, producing highly magnetic-field-sensitive resonators.

We report there has been widespread recent interest in self-assembly and synthesis of porphyrin and its derivatives-based ordered arrays aiming to emulate natural light-harvesting processes and energy storage. However, technologies that leverage the structural advantages of individual porphyrins have not been fully realized and have been limited by available synthesis methods. This article provides general perspectives on porphyrin and derivative chemistry, and discussions on surfactant-assisted cooperative self-assembly using amphiphilic surfactants and functional porphyrins and derivatives. The cooperative self-assembly amplifies the intrinsic advantages of individual porphyrins by engineering them into well-defined one-dimensional–three-dimensional (1D–3D) nanostructures. Surfactant-assisted self-assembly of amphiphilic surfactants and porphyrins has been utilized to form well-defined “micelle-like” nanostructures. Lastly, driven by intermolecular interactions, subsequent nucleation and growth confined within these nanostructures lead to the formation of 1D–3D ordered optically and electrically active nanomaterials with structure and function on multiple length scales.

Presented in this document are tests that exist in the Sierra/SolidMechanics example problem suite, which is a subset of the Sierra/SM regression and performance test suite. These examples showcase common and advanced code capabilities. A wide variety of other regression and verification tests exist in the Sierra/SM test suite that are not included in this manual.

Presented in this document are the theoretical aspects of capabilities contained in the Sierra/SM code. This manuscript serves as an ideal starting point for understanding the theoretical foundations of the code. For a comprehensive study of these capabilities, the reader is encouraged to explore the many references to scientific articles and textbooks contained in this manual. It is important to point out that some capabilities are still in development and may not be presented in this document. Further updates to this manuscript will be made as these capabilities come closer to production level.

Sierra/SolidMechanics (Sierra/SM) is a Lagrangian, three-dimensional code for finite element analysis of solids and structures. It provides capabilities for explicit dynamic, implicit quasistatic and dynamic analyses. The explicit dynamics capabilities allow for the efficient and robust solution of models with extensive contact subjected to large, suddenly applied loads. For implicit problems, Sierra/SM uses a multi-level iterative solver, which enables it to effectively solve problems with large deformations, nonlinear material behavior, and contact. Sierra/SM has a versatile library of continuum and structural elements, and a large library of material models. The code is written for parallel computing environments enabling scalable solutions of extremely large problems for both implicit and explicit analyses. It is built on the SIERRA Framework, which facilitates coupling with other SIERRA mechanics codes. This document describes the functionality and input syntax for Sierra/SM.

Due to remarkable electronic property, optical transparency, and mechanical flexibility, monolayer molybdenum disulfide (MoS₂) has been demonstrated to be promising for electronic and optoelectronic devices. To date, the growth of high-quality and large-scale monolayer MoS₂ has been one of the main challenges for practical applications. In this paper, we present a MoS₂–OH bilayer-mediated method that can fabricate inch-sized monolayer MoS₂ on arbitrary substrates. This approach relies on a layer of hydroxide groups (-OH) that are preferentially attached to the (001) surface of MoS₂ to form a MoS₂–OH bilayer structure for growth of large-area monolayer MoS₂ during the growth process. Specifically, the hydroxide layer impedes vertical growth of MoS₂ layers along the [001] zone axis, promoting the monolayer growth of MoS₂, constrains growth of the MoS₂ monolayer only in the lateral direction into larger area, and effectively reduces sulfur vacancies and defects according to density functional theory calculations. Finally, the hydroxide groups advantageously prevent the MoS₂ from interface oxidation in air, rendering high-quality MoS₂ monolayers with carrier mobility up to ~30 cm² V^–1 s^–1. Using this approach, inch-sized uniform monolayer MoS₂ has been fabricated on the sapphire and mica and high-quality monolayer MoS₂ of single-crystalline domains exceeding 200 μm has been grown on various substrates including amorphous SiO₂ and quartz and crystalline Si, SiC, Si₃N₄, and graphene Finally, this method provides a new opportunity for the monolayer growth of other two-dimensional transition metal dichalcogenides such as WS₂ and MoSe₂.

Goals/Action Plan - Current FY: Iterate on existing design to improve precision and increase throughput; Acquire Hg porosimetry and relative gas permeability data. Future FY: Correlate pore distributions and water saturation to effective gas permeability and diffusivity.

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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 S^2–/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.

Ferroelectricity in doped and alloyed hafnia thin films has been demonstrated using several different electrodes, with TiN and TaN being most prominent. In this work, we demonstrate ferroelectric Hf0.58Zr0.42O2 thin films with superconducting NbN electrodes at cryogenic temperatures. Demonstration of polarization - electric field [P(E)] response at liquid helium cryogenic temperatures, 4 K, suggests that the polarization is switchable over a wide temperature range after an initial 600 °C anneal. Further, room temperature P(E) and capacitance measurements demonstrate an expected polarization response with wake-up required to reach the steady state. Wake-up cycling at 4 K is observed to have no effect upon the ferroelectric phase suggesting an oxygen vacancy mobility freeze out whereas wake-up cycling at 294 K demonstrates close to a 3× increase in remanent polarization. This integration of a ferroelectric Hf0.58Zr0.42O2 thin film with NbN demonstrates the suitability of a highly scalable ferroelectric in applications for cryogenic technologies.

In this study, tokamak-like sawtooth oscillations are observed in the Compact Toroidal Hybrid (CTH), a current-carrying stellarator. CTH has the unique ability to change the amount of the applied vacuum rotational transform from external stellarator coils relative to the rotational transform generated by the internal plasma current to investigate the effects of strong three-dimensional magnetic shaping on sawtooth behavior. The observed sawteeth in CTH, for plasmas with monotonically decreasing rotational transform profiles dominated by the plasma current, have characteristics of those observed on tokamaks including (1) a central emissivity rise and then a sudden crash with a well-defined inversion radius, (2) the presence of an m = 1 emissivity fluctuation, and (3) the normalized inversion surface radius scales with the total edge rotational transform. We explore the properties of an ensemble of discharges in CTH in which the fractional rotational transform, defined as the vacuum rotational transform divided by the total rotational transform, is systematically varied from 0.04 to 0.42 to observe changes in sawtooth oscillation dynamics. Over this range of the fractional rotational transform, the measured sawtooth period decreased by a factor of two. At a high fractional rotational transform, the sawtooth amplitude is observed to consist of only low-amplitude oscillations while the measured crash time of the sawtooth oscillation does not appear to have a strong dependence on the amount of the fractional transform applied. Lastly, experimental results indicate that the low-amplitude sawteeth are accompanied by a decrease in the sawtooth period and predominantly correlated with the mean elongation (due to the increasing fractional rotational transform) of the non-axisymmetric plasmas within CTH rather than other global equilibrium parameters.

Telemetry and H-Gear Engineering, Org. 8430, is frequently required to design, manufacture, test, and deliver products directly to flight tests and important ground tests. Due to schedule or budget constraints, these deliveries often cannot follow the full product acceptance process laid out in Sandia's Realize Product Processes. Telemetry and H-Gear Engineering therefore created tailored quality expectations and outputs for products that fall into this category. This document describes these quality requirements and the reasons they have been put in place.

Stepped-lip diesel pistons can enhance in-cylinder vortex formation and thereby improve the thermal efficiency and emissions behavior of a diesel engine. Further improvements to diesel combustion systems may be realized through improved understanding of the mechanisms by which fuel sprays interact with pistons to form vortices. Analysis of computational fluid dynamics simulations provides insight about vorticity formation in one particular region of a particular stepped-lip combustion chamber. Interactions at the boundary between the sprays and the piston surface are a source of new vorticity that is transported upward and outward. This process is believed to be the origin of an energetic vortex that has been experimentally observed in the outermost region of the combustion chamber during the mixing-controlled combustion process, and is associated with improved turbulent mixing.

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In recent years, increasing interest in distributed sensing networks has led to a demand for robust multi-sensor multi-object tracking (MOT) methods that can take advantage of large quantities of gathered data. However, distributed sensing has unique challenges stemming from limited computational resources, limited bandwidth, and complex network topology that must be considered within a given tracking method. Several recently developed methods that are based upon the random finite set (RFS) have shown promise as statistically rigorous approaches to the distributed MOT problem. Among the most desirable qualities of RFS-based approaches is that they are derived from a common mathematical framework, finite set statistics, which provides a basis for principled fusion of full multi-object probability distributions. Yet, distributed labeled RFS tracking is a still-maturing field of research, and many practical considerations must be addressed before large-scale, real-time systems can be implemented. For example, methods that use label-based fusion require perfect label consistency of objects across sensors, which is impossible to guarantee in scalable distributed systems. This paper provides a survey of the challenges inherent in distributed tracking using labeled RFS methods. An overview of labeled RFS filtering is presented, the distributed MOT problem is characterized, and recent approaches to distributed labeled RFS filtering are examined. The problems that currently prevent implementation of distributed labeled RFS trackers in scalable real-time systems are identified and demonstrated within the scope of several exemplar scenarios.

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A hybrid analogue–digital computing system based on memristive devices is capable of solving classic control problems with potentially a lower energy consumption and higher speed than fully digital systems.

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We demonstrate the first electrically injected nonpolar m-plane GaN-based vertical-cavity surface-emitting lasers (VCSELs) with lattice-matched nanoporous bottom DBRs. Lasing under pulsed operation at room temperature was observed near 409 nm with a linewidth of ∼0.6 nm and a maximum output power of ∼1.5 mW. The VCSELs were linearly polarized and polarization-locked in the a-direction, with a polarization ratio of 0.94. The high polarization ratio and polarization pinning reveal that the optical scattering from the nanoporous DBRs is negligible. A high characteristic temperature of 357 K resulted from the slightly negative offset between the peak gain and cavity mode wavelengths.

Basis adaptation in Homogeneous Chaos spaces rely on a suitable rotation of the underlying Gaussian germ. Several rotations have been proposed in the literature resulting in adaptations with different convergence properties. In this paper we present a new adaptation mechanism that builds on compressive sensing algorithms, resulting in a reduced polynomial chaos approximation with optimal sparsity. The developed adaptation algorithm consists of a two-step optimization procedure that computes the optimal coefficients and the input projection matrix of a low dimensional chaos expansion with respect to an optimally rotated basis. We demonstrate the attractive features of our algorithm through several numerical examples including the application on Large-Eddy Simulation (LES) calculations of turbulent combustion in a HIFiRE scramjet engine.

This work exhibits the ability to shift the threshold voltage of an Al0.45Ga0.55N/Al0.3Ga0.7N high electron mobility transistor through the implementation of a 100 nm thick p-Al0.3Ga0.7N gate. A maximum threshold voltage of +0.3 V was achieved with a 3 μm gate length. In addition to achieving enhancement-mode operation, this work also shows the capability to obtain high saturated drain current (>50 mA/mm), no gate hysteresis, high ION,MAX/IOFF,MIN ratio of >109, and exceptionally low gate leakage current of 10-6 mA/mm even under high forward bias of Vgs = 8 V.

We propose a novel global solution algorithm for the network-constrained unit commitment problem that incorporates a nonlinear alternating current (ac) model of the transmission network, which is a nonconvex mixed-integer nonlinear programming problem. Our algorithm is based on the multi-tree global optimization methodology, which iterates between a mixed-integer lower-bounding problem and a nonlinear upper-bounding problem. We exploit the mathematical structure of the unit commitment problem with ac power flow constraints and leverage second-order cone relaxations, piecewise outer approximations, and optimization-based bounds tightening to provide a globally optimal solution at convergence. Numerical results on four benchmark problems illustrate the effectiveness of our algorithm, both in terms of convergence rate and solution quality.

The development and revision of safety codes and standards for hydrogen infrastructure requires a solid scientific basis, including studies of unignited releases from high pressure systems for various scenarios. Most hydrogen releases are modeled as axisymmetric jets, but real leaks are more likely to be non-axisymmetric jets issuing from high aspect ratio cracks or slots. In the present study, underexpanded hydrogen jets from square and rectangular nozzles with aspect ratios of 1–16 were numerically modeled for stagnation pressures up to 20 MPa. The near and far flow fields were modeled separately using two sequential computational domains to accurately and efficiently capture the flow characteristics. The numerical models were first validated with experimental data from a previous experimental study and literature data. The mass fraction and velocity distributions show that the centerline decay rates increase as the nozzle aspect ratio increases, but this increase is dependent on the pressure. This means that the canonical decay law of round turbulent jets and plumes no longer applies to the slot nozzle jets for high pressures. The radial profiles collapse onto a Gaussian curve in the major axis plane, but neither collapse, nor are they Gaussian in the minor axis plane with peaks away from the jet centerline. Different shock patterns were identified along the major and minor axes and the axis switching phenomenon seen in the literature was also reproduced. The axis switching resulted in significantly wider flattened concentration distributions compared with the axisymmetric jet which may require consideration during safety analyses for non-circular nozzles. A scaling factor taking both the nozzle shape and pressure effects into account was then developed to better scale the centerline decay rates for jets from both the square and rectangular nozzles. The present study demonstrates that the nozzle shape effects on the jet spreading should not be overlooked and proper scaling factors are required to collapse the data and calculate decay rates.

Many physical systems are modeled using partial differential equations (PDEs) with uncertain or random inputs. For such systems, naively propagating a fixed number of samples of the input probability law (or an approximation thereof) through the PDE is often inadequate to accurately quantify the “risk” associated with critical system responses. In this paper, we develop a goal-oriented, adaptive sampling and local reduced basis approximation for PDEs with random inputs. Our method determines a set of samples and an associated (implicit) Voronoi partition of the parameter domain on which we build local reduced basis approximations of the PDE solution. The samples are selected in an adaptive manner using an a posteriori error indicator. A notable advantage of the proposed approach is that the computational cost of the approximation during the adaptive process remains constant. We provide theoretical error bounds for our approximation and numerically demonstrate the performance of our method when compared to widely used adaptive sparse grid techniques. In addition, we tailor our approach to accurately quantify the risk of quantities of interest that depend on the PDE solution. We demonstrate our method on an advection–diffusion example and a Helmholtz example.

Literature describes various methods for determining a series resistance for a photovoltaic device from measured IV curves. We investigate use of these techniques to estimate the series resistance parameter for a single diode equivalent circuit model. With simulated IV curves we demonstrate that the series resistance values obtained by these techniques differ systematically from the known series resistance parameter values used to generate the curves, indicating that these methods are not suitable for determining the series resistance parameter for the single diode model equation. We present an alternative method to determine the series resistance parameter jointly with the other parameters for the single diode model equation, and demonstrate the accuracy and reliability of this technique in the presence of measurement errors.

Power measurement capabilities are becoming commonplace on large scale HPC system deployments. There exist several different approaches to providing power measurements that are used today, primarily in-band and out-of-band measurements. Both of these fundamental techniques can be augmented with application-level profiling and the combination of different techniques is also possible. However, it can be difficult to assess the type and detail of measurement needed to obtain insights and knowledge of the power profile of an application. In addition, the heterogeneity of modern hybrid supercomputing platforms requires that different CPU architectures must be examined as well. This paper presents a taxonomy for classifying power profiling techniques on modern HPC platforms. Three relevant HPC mini-applications are analyzed across systems of multicore and manycore nodes to examine the level of detail, scope, and complexity of these power profiles. We demonstrate that a combination of out-of-band measurement with in-band application region profiling can provide an accurate, detailed view of power usage without introducing overhead. Furthermore, we confirm the energy and power profile of these mini applications at an extreme scale with the Trinity supercomputer. This finding validates the extrapolation of the power profiling techniques from testbed scale of just several dozen nodes to extreme scale Petaflops supercomputing systems, along with providing a set of recommendations on how to best profile future HPC workloads.

The integrity of engineering structures is often compromised by embedded surfaces that result from incomplete bonding during the manufacturing process, or initiation of damage from fatigue or impact processes. Examples include delaminations in composite materials, incomplete weld bonds when joining two components, and internal crack planes that may form when a structure is damaged. In many cases the areas of the structure in question may not be easily accessible, thus precluding the direct assessment of structural integrity. In this paper, we present a gradient-based, partial differential equation (PDE)-constrained optimization approach for solving the inverse problem of interface detection in the context of steady-state dynamics. An objective function is defined that represents the difference between the model predictions of structural response at a set of spatial locations, and the experimentally measured responses. One of the contributions of our work is a novel representation of the design variables using a density field that takes values in the range [0,1]andraised and raised to an integer exponent that promotes solutions to be near the extrema of the range. The density field is combined with the penalty method for enforcing a zero gap condition and realizing partially bonded surfaces. The use of the penalty method with a density field representation leads to objective functions that are continuously differentiable with respect to the unknown parameters, enabling the use of efficient gradient-based optimization algorithms. Numerical examples of delaminated plates are presented to demonstrate the feasibility of the approach.

We develop a general risk quadrangle that gives rise to a large class of spectral risk measures. The statistic of this new risk quadrangle is the average value-at-risk at a specific confidence level. As such, this risk quadrangle generates a continuum of error measures that can be used for superquantile regression. For risk-averse optimization, we introduce an optimal approximation of spectral risk measures using quadrature. We prove the consistency of this approximation and demonstrate our results through numerical examples.

We report high-voltage regrown nonpolar {m}-plane p-n diodes on freestanding GaN substrates. A high blocking voltage of 540 V at 1 mA/cm ^{\textsf {2}} (corresponding to an electric field of E 3.35 MV/cm), turn-ON voltages between 2.9 and 3.1 V, specific on-resistance of 1.7 \text{m}\Omega \cdot \textsf {cm}^{\textsf {2}} at 300 A/cm ^{\textsf {2}} and a minimum ideality factor of 1.7 were obtained for the regrown diodes. Our results suggest that Si, O, and C interfacial impurity levels up to \textsf {2}\times \textsf {10}^{\textsf {17}} cm ^{-\textsf {3}} \textsf {8}\times \textsf {10}^{\textsf {17}} cm ^{-\textsf {3}} and\textsf {1}\times \textsf {10}^{\textsf {19}} cm ^{-\textsf {3}} respectively, at the metallurgical junction of {m}-plane, p-n diodes do not result in very early breakdown in the reverse bias although the off-state leakage current in the forward bias is affected. The impact of the growth interruption/regrowth on diode performance is also investigated.

A multi-frame shadowgraphy diagnostic has been developed and applied to laser preheat experiments relevant to the Magnetized Liner Inertial Fusion (MagLIF) concept. The diagnostic views the plasma created by laser preheat in MagLIF-relevant gas cells immediately after the laser deposits energy as well as the resulting blast wave evolution later in time. The expansion of the blast wave is modeled with 1D radiation-hydrodynamic simulations that relate the boundary of the blast wave at a given time to the energy deposited into the fuel. This technique is applied to four different preheat protocols that have been used in integrated MagLIF experiments to infer the amount of energy deposited by the laser into the fuel. The results of the integrated MagLIF experiments are compared with those of two-dimensional LASNEX simulations. The best performing shots returned neutron yields ∼40-55% of the simulated predictions for three different preheat protocols.

Commercial InGaN/GaN light emitting diodes continue to suffer from efficiency droop at high current densities, and urgently require enhanced structural-optical toolsets for active region characterization. In our work, we measure delayed (tens of seconds) cathodoluminescence which is influenced by carrier transport and deep level defects. Further, we observe that drops in efficiency are not correlated with quantum well (QW) width fluctuations. To explain the rise dynamics, we propose a model involving filling of deep level defects and simultaneous reduction of built-in field within the multi-QW active region. These measurements yield insights into carrier transport, efficiency-reducing defects, and QW band structure.

Performance portability on heterogeneous high-performance computing (HPC) systems is a major challenge faced today by code developers: parallel code needs to be executed correctly as well as with high performance on machines with different architectures, operating systems, and software libraries. The finite element method (FEM) is a popular and flexible method for discretizing partial differential equations arising in a wide variety of scientific, engineering, and industrial applications that require HPC. This article presents some preliminary results pertaining to our development of a performance portable implementation of the FEM-based Albany code. Performance portability is achieved using the Kokkos library. We present performance results for the Aeras global atmosphere dynamical core module in Albany. Numerical experiments show that our single code implementation gives reasonable performance across three multicore/many-core architectures: NVIDIA General Processing Units (GPU’s), Intel Xeon Phis, and multicore CPUs.

This work describes the first documented case of an effect defined herein as “octane hyperboosting” by an oxygenated fuel compound, 3-methyl-2-buten-1-ol (prenol). Octane hyperboosting is characterized by the Research Octane Number (RON) of a mixture (e.g. an oxygenate biofuel blended into gasoline) exceeding the RON of the individual components in that mixture. This finding counters the widely held assumption that interpolation between the RON values of a pure compound and the base fuel provides the bounds for the RON performance of the blend. This is clearly distinct from the more commonly observed synergistic blending of oxygenates with gasoline, where the RON never exceeds the performance of the highest performing component. Octane hyperboosting was observed for blends of prenol and six different gasoline fuels with varying composition. Testing of compounds chemically similar to prenol yielded no qualitatively similar instances of octane hyperboosting, which suggests that the effect may not be widespread among fuel candidates. The phenomenon suggests an unexplored aspect of autoignition kinetics research for fuel blends, and may provide a new mechanism for significantly increasing fuel octane number, which is necessary for increasing combustion efficiency in spark ignition engines. This phenomenon also increases the potential candidate list of biofuels, as compounds hitherto discounted due to their lower pure component RON may exhibit hyperboosting behavior, and thereby enhanced performance, in blends.

The effect of ion irradiation on the microstructure of oxide dispersion strengthened (ODS) MA956 steel, before and after friction stir welding (FSW), was studied. Both the base material (BM) and welded stir zone (SZ) were irradiated with 5 MeV Fe ++ ions at 450 °C up to 25 displacements per atom (dpa). Characterization was performed using scanning transmission electron microscopy (STEM) and atom probe tomography (APT), with particular emphasis on the Y–Al–O dispersoid characteristics and dislocation microstructures. After irradiation, the dispersoids in the BM increased in diameter and decreased in number density, which was explained by an Ostwald ripening mechanism. FSW caused significant coarsening and agglomeration of the dispersoids. After irradiation, both the diameter and number density of the SZ dispersoids increased, which was explained by an irradiation-enhanced diffusion mechanism. Dislocation loop and network behavior was also characterized and large dislocation loops of ≈20 nm diameter formed by 1 dpa in both the BM and SZ samples, whereas the network density remained nearly constant with irradiation.

Software is the key crosscutting technology that enables advances in mathematics, computer science, and domain-specific science and engineering to achieve robust simulations and analysis for science, engineering, and other research fields. However, software itself has not traditionally received focused attention from research communities; rather, software has evolved organically and inconsistently, with its development largely as by-products of other initiatives. Moreover, challenges in scientific software are expanding due to disruptive changes in computer hardware, increasing scale and complexity of data, and demands for more complex simulations involving multiphysics, multiscale modeling and outer-loop analysis. In recent years, community members have established a range of grass-roots organizations and projects to address these growing technical and social challenges in software productivity, quality, reproducibility, and sustainability. This article provides an overview of such groups and discusses opportunities to leverage their synergistic activities while nurturing work toward emerging software ecosystems.

The proliferation of distributed generation on distribution feeders triggers a large number of integration and planning studies. Further, the complexity of distribution feeder models, short simulation time steps, and long simulation horizons rapidly render studies computational burdensome. To mend this issue, we propose a methodology for reducing the number of nodes, loads, generators, line, and transformers of p-phase distribution feeders with unbalanced loads and generation, non-symmetric wire impedance, mutual coupling, shunt capacitance, and changes in voltage and phase. The methodology is derived on a constant power load assumption and employs a Gaussian elimination inversion technique to design the reduced feeder. Compared to previous work by the authors, the inversion reduction takes half the time and voltage errors after reduction are reduced by an order of magnitude. Using a snapshot simulation the reduction is tested on six additional publicly available feeders with a maximum voltage error 0.0075 p.u. regardless of feeder size or complexity, and typical errors on the order of 1 × 10 -4 p.u. For a day long quasi-static time series simulation on the UCSD A feeder, errors are shown to increase with changes in loading when a large number of buses removed, but shows less variation for less than 85% of buses removed.

The Corrective Action Management Unit (CAMU) at Sandia National Laboratories, New Mexico (SNL/NM) consists of a containment cell and ancillary systems that underwent regulatory closure in 2003 in accordance with the Closure Plan in Appendix D of the Class 3 Permit Modification (SNL/NM September 1997). The containment cell was closed with wastes in place. On January 26, 2015, the New Mexico Environment Department (NMED) issued the Hazardous Waste Facility Operating Permit (Permit) for Sandia National Laboratories (NMED January 2015). The Permit became effective February 26, 2015. The CAMU is undergoing post-closure care in accordance with the Permit, as revised and updated. This CAMU Report of Post-Closure Care Activities documents all activities and results for calendar year (CY) 2018 as required by the Permit.

In order to generate a public data set that can be used to validate Wave Energy Converter (WEC) numerical codes, such as WEC-Sim, Sandia National Laboratories led an experimental testing campaign of a 1:33 scale Floating Oscillating Surge Wave Energy Converter (FOSWEC) in the Directional Wave Basin at Oregon State University's Hinsdale Wave Research Laboratory. Testing was performed in two phases; Phase 1 testing was completed in November - December 2015, and Phase 2 testing was completed in May - June 2016. This experimental testing report details the selection and design of a FOSWEC, experimental setup and tests, and overview of the resulting dataset from Phase 1 and Phase 2 testing.

Once Synthetic Aperture Radar (SAR) images are formed, they typically need to be stored in some file format which might restrict the dynamic range of what can be represented. Thereafter, for exploitation by human observers, the images might need to be displayed in a manner to reveal the subtle scene reflectivity characteristics the observer seeks, which generally requires further manipulation of dynamic range. Proper image scaling, for both storage and for display, to maximize the perceived dynamic range of interest to an observer depends on many factors, and an understanding of underlying data characteristics. While SAR images are typically rendered with gray-scale, or at least monochromatic intensity variations, color might also be usefully employed in some cases. We analyze these and other issues pertaining to SAR image scaling, dynamic range, radiometric calibration, and display.

The globalization of modern supply chains has resulted in many new risks to Sandia's NW programs and mission. The potential impact of counterfeit products, tampering, theft, malicious software, poor manufacturing and/or development practices, and the influence of foreign governments has become more obvious as new threats and compromises continuously emerge. The Supply Chain Risk Management (SCRM) team was formed specifically to understand and address these risks. We were able to coalesce around these principles to develop and optimize an effective risk assessment process for critical suppliers, called Subcontractor Risk Assessments (SRAs). These elevated screening techniques are planned and delivered in a cost-effective way for Sandia's programs (no increase to purchasing burden rates) and also demonstrate due diligence to DOE/NNSA as a component of Sandia's overall SCRM strategy. SRAs are communicated in a concise 1-page format complete with recommendations as well as links to reference materials for those who require additional details about the SRA process and results.

The most straightforward concept for disposal of large, heavy packages containing commercial spent nuclear fuel (CSNF) in a repository in bedded salt, would be to emplace them directly on the floor in emplacement tunnels. In-tunnel axially aligned horizontal emplacement would minimize excavated volume and avoid drilling of large-diameter emplacement boreholes. A similar concept was proposed in Germany for direct disposal of POLLUX^® canisters. The repository would be constructed at a depth of 500 to 1,000 m for isolation from the surface, and for sufficient overburden stress to ensure creep reconsolidation of repository openings. It could entail modular panels of emplacement tunnels arranged on headings oriented in cardinal directions from a central core, to accommodate the estimated 140,000 MTU total U.S. CSNF inventory. To do so, the overall area of the repository layout would be approximately 20 km². Many layouts are possible, but the approach should be modular, excavation should be deferred for as long as possible to avoid maintenance, and the emplacement areas should share support facilities and shafts. Vertical shafts would be used in accordance with mining practice in sedimentary basins. Large diameter shafts would be needed for ventilation exhaust and waste transport, with smaller shafts for waste salt removal, men & materials, and ventilation intake. The spacing between disposal tunnels as estimated from thermal modeling, seeks to limit the maximum average areal thermal load in the panels to 11 W/m² to control long-term heat buildup in the host rock. Peak salt temperature would occur within a few years and would be dominated by each waste package locally, simplifying thermal management. There would be some flexibility to decrease the package spacing or increase the emplacement thermal power limit Backfilling emplaced waste packages immediately with mine-run crushed salt would provide shielding and expedite reconsolidation. This arrangement would isolate adjacent waste packages from one another by the intervening backfill, especially after it reconsolidates and its properties approach those of intact salt. After the repository is fully loaded and the performance confirmation program is complete, activities to permanently close the repository would be initiated. During closure operations all openings in the host salt would be backfilled, then shafts would be sealed, and boreholes plugged. Plans for the Waste Isolation Pilot Plant (WIPP) show how sealing and plugging could be done. A monitoring program could continue for 50 years or longer after repository closure. With an emplacement thermal power limit of 10 kW per waste package, nearly all the CSNF that is projected to be produced by the current fleet of reactors in the U.S. could be emplaced over a period of approximately 50 years starting in calendar 2048. No barriers to implementation in a reasonable timeframe have been identified from this generic analysis. Engineering challenges include: 1) shaft construction; 2) a very-large capacity shaft hoist; 3) overpack design; 4) a transport-emplacement-vehicle (TEV) for transporting waste packages once they are underground and emplacing them remotely; and 5) remotely operated equipment for emplacing backfill. The method of shaft construction would depend on site-specific conditions, and could involve freezing the subsurface. A shaft hoist with payload capacity of 175 MT seems technically and economically feasible based on development work in Germany, and it would be the largest hoist of its kind. The function of disposal overpacks would be to provide reliable containment during repository operations, which could be accomplished using a corrosion allowance material such as a low-carbon steel. Development effort would be needed to determine overpack thickness (e.g., 7 to 20 cm) that can resist corrosion and loading from salt creep, to rovide containment throughout the repository operational period. The transport-emplacement vehicle (TEV) would be similar to previous concepts, particularly one option proposed for a Yucca Mountain repository. It would move over a rough salt floor on independently driven and steered wheels, and carry heavy shielding in addition to a waste package. By analogy to the safety case for the WIPP in New Mexico, human intrusion is likely to be the dominant mode of radionuclide release from the repository. Treatment of human intrusion for a CSNF repository in salt could depend on promulgation of site-specific changes in the regulations. Radionuclide release and migration would be quite limited for undisturbed conditions. There may be opportunities for improved understanding of salt performance with waste heating, based on future in situ testing in an underground salt research laboratory. This report also discusses a developing area of salt rock mechanics that involves low-stress, low strain-rate creep that might cause large, heavy waste packages to slowly sink. Site-specific sampling, testing, and modeling would be used to determine if the mechanism is important enough to merit consideration in design, or inclusion in performance assessment. Part of engineering design and postclosure safety assessment for a CSNF repository in salt would be to implement a methodology to show that the probability of a criticality event in the repository, when waste packages eventually breach and are flooded, is less than the probability screening threshold for performance assessment. In the methodology, a criticality analysis would be performed for waste packages in the repository, incorporating measures that could be introduced as needed to limit reactivity, for example using fuel selection and loading rules, and crediting the absorption of thermal neutrons by natural chlorine in the environment. A similar analysis has been underway for CSNF stored in dual-purpose canisters. Ideally the strategy would be developed prior to actually loading SNF assemblies into canisters used in waste packages for disposal.

This document summarizes existing Marine and Hydrokinetic (MHK) performance metrics known to the United States Department of Energy and national laboratories. This document was updated based on feedback from the MHK Energy community, however, this summary still may not be exhaustive. There are a wide variety of needs and uses for metrics. All stakeholders, such as developers, funding agencies, investors, and researchers, have a need for metrics and their many uses. It is evident that the sector will benefit from clear techno economic performance metrics to guide development towards success. There are international efforts underway to bring the community together to (1) understand what metrics/approaches are being used currently and (2) reach a global framework on the approach to the measurement of success. This document serves to list existing metrics known to the U.S. at the present, and is not meant to represent international efforts or consensus.

More than 300 counter-unmanned aircraft system (CUAS) products were identified in our market survey by reviewing and comparing existing market surveys and reports, academic and commercial compilations, CUAS demonstration event reports, and other documents. Of these, Sandia collected technical data on more than 200 of these products through a combination of manual research and a request for information posted to www.fbo.gov. Technical product information has been compiled into a database that can be filtered by key technical characteristics to find products that match high-level requirements. The CUAS market is shifting from an emerging to a growth industry. Many companies are partnering or collaborating with peers to combine benefits from their core strengths and technologies into more complete solutions. These companies want to know the governments CUAS requirements, so they can design and deliver a product tailored to the application space or requirements.