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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 613 records · Page 34

RT_BUILD: An expert programmer for implementing and simulating Ada real-time control software

The RT BUILD is an expert control system programmer that creates real-time Ada code from block-diagram descriptions of control systems. Since RT BUILD embodies substantial knowledge about the implementation of real-time control systems, it can perform many, if not most of the functions normally performed by human real-time programmers. Though much basic research was done in automatic programming, RT BUILD appears to be the first application of this research to an important problem in flight control system development. In particular, RT BUILD was designed to directly increase productivity and reliability for control implementations of large complex systems.

Lehman, Larry L.↗

Energy-Efficient and Resilient Infrastructure: Simulation, Validation, and Installation

Advanced, high-performance computing at the National Renewable Energy Laboratory (NREL) has enabled access to vast data resources with cutting-edge software techniques to understand, design, plan for, and maintain energy-efficient and resilient infrastructure. We have focused on cities and airports, but the technology we have developed will easily translate to seaports, inland ports, military installations, or other complex and large-scale energy-intensive systems. We can digitally simulate and explore current and future scenarios to make datadriven decisions for optimizing advanced energy systems, transportation and building operations, infrastructure planning and expansion, and battery storage to guide short- and long-term investments, electrification strategies, and integration of new technologies.

Athena↗

Scale-up of microwave-assisted, continuous flow, liquid phase reactors: Application to 5-Hydroxymethylfurfural production

Microwave (MW) technology can be powerful for the electrification and intensification of chemical manufacturing. However, very few examples of scaled MW processes exist. In this work, we build a scaled, MW-assisted, continuous flow reactor for the processing of liquid phase chemistries with specific application to 5-hydroxymethylfurfural (HMF) production. Here, we demonstrate a corresponding computational fluid dynamics model to simulate the reactor’s temperature profile and performance, both of which are in good agreement with experiments. We construct a surrogate model to relate operating parameters to performance for guiding experiments, without demanding simulations, via active learning. Heat recirculation is demonstrated in this scaled reactor, further extending its scale and reducing the energy demand. An HMF yield of ~55 % and a productivity of 0.1 kg/hr, 8x higher than any other reactor, at a flowrate >20x than prior work, are demonstrated while maintaining energy efficiency of >98 %. A basic economic analysis estimates a $1.85/kg cost of HMF from fructose and >60 % reduction in CO 2 emissions than a conventional system without considering the impact of green electricity. We demonstrate that MW technology is well-applied to systems larger than the laboratory scale, and strategies to further reduction in cost and CO 2 are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A unified non-equilibrium phase change model for injection flow modeling

The homogenous relaxation model (HRM) is one of the most widely used models to describe the liquid- gas phase transition. However, in its original formulation, it is unable to handle multispecies vapor-liquid equilibrium (VLE), which limits its applicability to single-component fluids. In this work, a unified non-equilibrium phase change model that considers the VLE of multicomponent mixtures is proposed building upon the HRM's structure. A time factor is introduced to mimic the effect of different phase change timescales due to different mechanisms, e.g., cavitation, flash-boiling, and evaporation. Here to assess the model's performance, computational fluid dynamics simulations of the internal and near-nozzle injection flow of the Engine Combustion Network's Spray G injector were performed using the nine-component PACE-20 fuel with both the unified model and the original HRM. The predicted fuel density in the near-nozzle region matched well with X-ray tomography measurements. The simulation results indicated that, whereas the HRM failed to capture the vaporization due to convective mixing between the fuel and ambient gas, the unified model performed well in predicting the mixing-driven vaporization and the corresponding evaporative cooling. Further comparisons using the nine-component fuel formula and a single-component fuel surrogate demonstrated the unified model's ability to predict preferential vaporization, which affects the predictions of local mixture composition and rate of vaporization. Finally, it is shown that the unified model is capable of representing multiple phase change mechanisms, and the relaxation time factor plays an important role in determining the degree of phase change due to the different mechanisms.

33 ADVANCED PROPULSION SYSTEMS↗

Role of reinforcement learning for risk-based robust control of cyber-physical energy systems

Critical infrastructures such as cyber-physical energy systems (CPS-E) integrate information flow and physical operations that are vulnerable to natural and targeted failures. Safe, secure, and reliable operation and control of CPS-E is critical to ensure societal well-being and economic prosperity. Automated control is key for real-time operations and may be mathematically cast as a sequential decision-making problem under uncertainty. Emergence of data-driven techniques for decision making under uncertainty, such as reinforcement learning (RL), have led to promising advances for addressing sequential decision-making problems for risk-based robust CPS-E control. However, existing research challenges include understanding the applicability of RL methods across diverse CPS-E applications, addressing the effect of risk preferences across multiple RL methods, and development of open-source domain-aware simulation environments for RL experimentation within a CPS-E context. This article systematically analyzes the applicability of four types of RL methods (model-free, model-based, hybrid model-free and model-based, and hierarchical) for risk-based robust CPS-E control. Problem features and solution stability for the RL methods are also discussed. We demonstrate and compare the performance of multiple RL methods under different risk specifications (risk-averse, risk-neutral, and risk-seeking) through the development and application of an open-source simulation environment. Motivating numerical simulation examples include representative single-zone and multizone building control use cases. Finally, six key insights for future research and broader adoption of RL methods are identified, with specific emphasis on problem features, algorithmic explainability, and solution stability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Efficient Evaluation and Optimization of Structural Reliability

Use of approximations for calculating the structural failure probability under uncertainties is a necessary aspect. But efficient use of suitable approximations at different stages of reliability prediction and design makes this valuable tool practical for many large scale structures. This research addresses the modern approximation concepts and their utility in structural reliability estimation. Emphasis is placed on building higher order approximations using intervening variables to closely represent the nonlinear limit state functions. Several test problems with highly nonlinear performance functions are used to demonstrate the accuracy of the proposed method. Many of the structural problems are modeled and simulated using the finite element methods (FEM) for obtaining a detailed structural response. FEM is a computationally intensive numerical procedure with a large number of degrees of freedom. With an increase in the complexity of the structural model and the multidisciplinary nature of analyses, the number of limit states and their computation increases very significantly. The requirement of frequent repetitive analysis of the structure hinders the utility of any tool and discourages that approach from being used. One particular tool which faces this difficulty is the computation of the structural reliability under parametric uncertainties.

Grandhi, Ramana V.↗

The Clock Is Ticking

Recently, I worked on creating a one-of-a-kind device for a Space Station group studying exercise physiology at another NASA Center. They approached my department at Ames Research Center to design and build an exercise bed that allowed users to perform the motions that they needed for ground-based research. The real challenge was that they needed the device designed, built, and delivered in just one month. The bed was intended to simulate doing squats while in a horizontal position as if on a moving sled. They wanted to incorporate a resistant device called an Interim Resistive Exercise Device (IRED), an adjustable cable tied into a reel to provide a measured amount of resistance. This device was used on the Station for exercising in space; we were taking the same resistant reel and incorporating it in this bed. In the early stages of a design project, I communicate with a customer as much as I can and as often as they will tolerate. There s a lot of learning that needs to go on, and I prefer to spend a little bit of extra time here because that can save a lot of time later. In the beginning, you need to volley the information back-and-forth, so that you understand the customer s requirements and they know what you re capable of doing.

Gundo, Dan↗

Delay and Disruption Tolerant Networking MACHETE Model

To verify satisfaction of communication requirements imposed by unique missions, as early as 2000, the Communications Networking Group at the Jet Propulsion Laboratory (JPL) saw the need for an environment to support interplanetary communication protocol design, validation, and characterization. JPL's Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE), described in Simulator of Space Communication Networks (NPO-41373) NASA Tech Briefs, Vol. 29, No. 8 (August 2005), p. 44, combines various commercial, non-commercial, and in-house custom tools for simulation and performance analysis of space networks. The MACHETE environment supports orbital analysis, link budget analysis, communications network simulations, and hardware-in-the-loop testing. As NASA is expanding its Space Communications and Navigation (SCaN) capabilities to support planned and future missions, building infrastructure to maintain services and developing enabling technologies, an important and broader role is seen for MACHETE in design-phase evaluation of future SCaN architectures. To support evaluation of the developing Delay Tolerant Networking (DTN) field and its applicability for space networks, JPL developed MACHETE models for DTN Bundle Protocol (BP) and Licklider/Long-haul Transmission Protocol (LTP). DTN is an Internet Research Task Force (IRTF) architecture providing communication in and/or through highly stressed networking environments such as space exploration and battlefield networks. Stressed networking environments include those with intermittent (predictable and unknown) connectivity, large and/or variable delays, and high bit error rates. To provide its services over existing domain specific protocols, the DTN protocols reside at the application layer of the TCP/IP stack, forming a store-and-forward overlay network. The key capabilities of the Bundle Protocol include custody-based reliability, the ability to cope with intermittent connectivity, the ability to take advantage of scheduled and opportunistic connectivity, and late binding of names to addresses.

Segui, John S.↗

Investigation of Hardware and Instrumentation to Measure Hand Grasp Activity with the Spacesuit Gloves

Introduction: During the 2022 suited injury summit, it was hypothesized that there will be concerns for hand and glove injuries for future exploration space missions, especially given the fact that the “total number of Extravehicular activity (EVA) hours and frequency” for lunar surface missions is expected to vastly increase [1]. It has been reported that the hands experienced the greatest “absolute numbers” of reported injuries and far exceeds other injuries during EVA [1, 2]. It was reported that the most fatiguing part of the surface EVA was the repetitive gripping tasks [3]. It was recommended that a “glove sub-team” be created to look at possible injury mechanism and mitigation strategies. Some of the recommendations that were suggested [1] are as follows: examine hand fatigue, utilize motion capture, examine the duration and frequency of hand movements, and identify frequent hand motions. We started assessing hardware and instrumentation to measure hand grasp activity in the pressurized glove environment. The purpose of this test was to perform a hardware evaluation for motion capture (MoCap) gloves obtained from StretchSense (Auckland, New Zealand). The specific gloves used were the Pro Fidelity and SuperSplay to determine the repeatability, reliability, feasibility, and useability inside of a pressurized gloved environment. Methods: The MoCap gloves were customized (e.g., battery/Bluetooth pack relocated to upper arm) to better suit the pressurized testing environment and protect the subject from unintentional injury (Fig. 1). Fourteen total subjects from different demographics (i.e., gender and pressurized glove experience level) participated in this test series. Testing included one session each of a baseline data collection (NASA Johnson Space Center (JSC) building 21) and a spacesuit glove box (Fig. 2 at JSC building 7 room 2027) data collection (under vacuum down to 4.3 psid), where each session lasted 3-5 hours. Controlled and reproducible tasks to systematically evaluate the repeatability and reliability of the hardware were performed during baseline data collection. Additionally, subjects performed simulated EVA-like tasks in a pressurized gloved environment. For all sessions, MoCap gloves were placed on each of the subjects’ hands and the signal from it, or the raw capacitance (Fig. 3), was analysed. The raw capacitance was used to estimate the open and closed hand states between the testing conditions and allow us to provide an offset caused by the pressurized environment. Results & Discussion: Initial observation with the bare hands (baseline) condition showed that the MoCap gloves appeared to track grasping and releasing of the fingers (opening and closing fist) with both high- and low-speed conditions, while adduction and abduction of the fingers were not relatively tracked. A hardware evaluation was done outside of the glove box to assess the reliability and repeatability of the MoCap glove. In one task, a point force was applied to various locations on the back of the hand. When the point force was applied to the space between the 1st digit and the pointer finger, there was a noticeable distortion to the MoCap data. Another task examining an increasing force from a 10 lb. sandbag applied to the back of the hand while lying flat on a table, showed a constant flat line with only a distortion when the weight was increased or added to the back of the hand. Fig. 3 shows an object relocation task where you can see when each individual finger “opened” and “closed” (changed position) when picking up and setting down the dumbbell. When the fingers were stationary, the signal remained relatively flat compared to the peaks and valleys that can be observed in Fig. 3. This study showed promising results and imperative input into an attempt to discriminate between hand states across various functional tasks and should be evaluated with context to the repeatability and reliability outcomes. Depending on the task done inside of the pressurized glove box environment and outside, the results appear to be affected by many different factors (i.e., drift, pressure, hand size, etc.). Significance: If this hardware proves to be reliable and repeatable in determining the open and closed hand states then this may provide critical insight into assisting in the characterization of the pressurized gloved environment and the effect on crew member exertion level. Ultimately, this tool will provide useful data for quantifying the repetitive nature of EVA training and tasks. Acknowledgments: The authors would like to acknowledge the NASA Mars Campaign Office for providing funding for this research. Lastly, thanks to all the engineers and technicians at NASA JSC who helped with this data collection. References: [1] Reiber, et al. (2022), NASA/TM-20220007605; [2] Scheuring, et al. (2009), Av., Sp., and Envir. Med. 80(2). [3] Scheuring, et al. (2007), NASA/TM–2007–214755.

Rachel L Thompson↗

Towards Flange-to-Flange Turbopump Simulations for Liquid Rocket Engines

The primary objective of this research is to support the design of liquid rocket systems for the Advanced Space Transportation System. Since the space launch systems in the near future are likely to rely on liquid rocket engines, increasing the efficiency and reliability of the engine components is an important task. One of the major problems in the liquid rocket engine is to understand fluid dynamics of fuel and oxidizer flows from the fuel tank to plume. Understanding the flow through the entire turbopump geometry through numerical simulation will be of significant value toward design. This will help to improve safety of future space missions. One of the milestones of this effort is to develop, apply and demonstrate the capability and accuracy of 3D CFD methods as efficient design analysis tools on high performance computer platforms. The development of the MPI and MLP versions of the INS3D code is currently underway. The serial version of INS3D code is a multidimensional incompressible Navier-Stokes solver based on overset grid technology. INS3D-MPI is based on the explicit massage-passing interface across processors and is primarily suited for distributed memory systems. INS3D-MLP is based on multi-level parallel method and is suitable for distributed-shared memory systems. For the entire turbopump simulations, moving boundary capability and an efficient time-accurate integration methods are build in the flow solver. To handle the geometric complexity and moving boundary problems, overset grid scheme is incorporated with the solver that new connectivity data will be obtained at each time step. The Chimera overlapped grid scheme allows subdomains move relative to each other, and provides a great flexibility when the boundary movement creates large displacements. The performance of the two time integration schemes for time-accurate computations is investigated. For an unsteady flow which requires small physical time step, the pressure projection method was found to be computationally efficient since it does not require any subiterations procedure. It was observed that the artificial compressibility method requires a fast convergence scheme at each physical time step in order to satisfy incompressibility condition. This was obtained by using a GMRES-ILU(0) solver in our computations. When a line-relaxation scheme was used, the time accuracy was degraded and time-accurate computations became very expensive. The current geometry for the LOX boost turbopump has various rotating and stationary components, such as inducer, stators, kicker, hydrolic turbine, where the flow is extremely unsteady. Figure 1 shows the geometry and computed surface pressure of the inducer. The inducer and the hydrolic turbine rotate in different rotational speed.

Kiris, Cetin↗

Coupling Microstructural Evolution Simulations to Material Property Degradation Predictions for Plasma-Facing Materials

Reliable material performance is required for plasma-facing material (PFM) candidates. Previous research has shown that plasma and neutron radiation exposure induces microstructural changes in PFMs; changes in thermal and electrical conductivities and in material hardening and embrittlement were also observed after neutron irradiation. These material property changes will negatively impact the performance of the PFMs in a fusion reactor. Despite the well-known connection between material microstructure, properties, and performance, there is a need for validated modeling capabilities connecting PFM property degradation with microstructural evolution under fusion-relevant conditions. We are developing a simulation capability to couple plasma-induced microstructural evolution to material property degradation. Our approach relies on deliberate mapping between individual simulation models and experimental characterization for validation. The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) software was used for this simulation capability development. A MOOSE phase-field model was coupled with the cluster dynamics code, Xolotl, to predict microstructural evolution. Microstructure characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and laser scanning confocal microscopy (LSCM) are used to validate these microstructural evolution simulations. Calculation of thermal and electrical conductivities with first principles simulations was performed for bulk material and for grain boundaries; these results are used within MOOSE models to calculate effective thermal and electrical conductivities as a function of grain characteristics. Thermoreflectance and four-probe techniques were employed to measure the thermal and electrical conductivities, respectively. A MOOSE crystal plasticity model was adapted to predict microstructure-sensitive deformation behavior, and X-ray diffraction (XRD) was used to collect bulk dislocation density data for validation. After individual simulation validation, these models are coupled to predict material property changes resulting from plasma exposure. We focused here on an experimental design to emphasize the separate effects of moderate thermal loads and plasma exposure using tungsten. Annealing of tungsten was performed under a protective environment for temperatures ranging from 500 C to 1500 C. The plasma exposure was completed in the Tritium Plasma Experiment at Idaho National Laboratory under a deuterium flux of 1e22 D/m^2-s. This incremental approach is employed to build confidence in the modeling capability: separate-effects tests ensure that the models capture key mechanisms from single environmental conditions before predicting PFM property degradation under combined loads. We will show our early results from coupling these simulation models to predict PFM property changes from microstructural evolution. Comparisons of the simulation results with preliminary validation data will be discussed.

36 - MATERIALS SCIENCE↗

Feasibility of using the Massively Parallel Processor for large eddy simulations and other Computational Fluid Dynamics applications

The results of an investigation into the feasibility of using the MPP for direct and large eddy simulations of the Navier-Stokes equations is presented. A major part of this study was devoted to the implementation of two of the standard numerical algorithms for CFD. These implementations were not run on the Massively Parallel Processor (MPP) since the machine delivered to NASA Goddard does not have sufficient capacity. Instead, a detailed implementation plan was designed and from these were derived estimates of the time and space requirements of the algorithms on a suitably configured MPP. In addition, other issues related to the practical implementation of these algorithms on an MPP-like architecture were considered; namely, adaptive grid generation, zonal boundary conditions, the table lookup problem, and the software interface. Performance estimates show that the architectural components of the MPP, the Staging Memory and the Array Unit, appear to be well suited to the numerical algorithms of CFD. This combined with the prospect of building a faster and larger MMP-like machine holds the promise of achieving sustained gigaflop rates that are required for the numerical simulations in CFD.

Bruno, John↗

Carbon emission responsive building control: A case study with an all-electric residential community in a cold climate

In the United States, buildings account for 35% of total energy-related carbon dioxide emissions, making them important contributors to decarbonization. Carbon intensities in the power grid are time-varying and can fluctuate significantly within hours, so shifting building loads in response to the carbon intensities can reduce a building’s operational carbon emissions. This paper presents a rule-based carbon responsive control framework that controls the setpoints of thermostatically controlled loads responding to the grid’s carbon emission signals in real time. Based on this framework, four controllers are proposed with different combinations of carbon accounting methods and control rules. To evaluate their performance, we performed simulation studies using models of a 27-home, all-electric, net zero energy residential community located in Basalt, Colorado, United States. The carbon intensity data of four future years from the Cambium data set are adopted to account for the evolving resource mix in the power grid. Various performance metrics, including energy consumption, carbon emission, energy cost, and thermal discomfort, were used to evaluate the performance of the controllers. Sensitivity analysis was also conducted to determine how the control thresholds and intervals affect the controllers’ performance. Simulation results indicate that the carbon responsive controllers can reduce the homes’ annual carbon emissions by 6.0% to 20.5%. However, the energy consumption increased by 0.9% to 6.7%, except in one scenario where it decreased by 2.2%. Compared to the baseline, the change in energy cost was between –2.9% and 3.4%, and thermal discomfort was also maintained within an acceptable range. The little impact on energy cost and thermal discomfort indicates there are no potential roadblocks for customer acceptance when rolling out the controllers in utility programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

AlphaBuilding - Synthetic Buildings Operation Dataset

This is a synthetic building operation dataset which includes HVAC, lighting, miscellaneous electric loads (MELs) system operating conditions, occupant counts, environmental parameters, end-use and whole-building energy consumptions at 10-minute intervals. The data is created with 1395 annual simulations using the U.S. DOE detailed medium-sized reference office building, and 30 years' historical weather data in three typical climates including Miami, San Francisco, and Chicago. Three energy efficiency levels of the building and systems are considered. Assumptions regarding occupant movements, occupants' diverse temperature preferences, lighting, and MELs are adopted to reflect realistic building operations. A semantic building metadata schema - BRICK, is used to store the building metadata. The dataset is saved in a 1.2 TB of compressed HDF5 file. This dataset can be used in various applications, including building energy and load shape benchmarking, energy model calibration, evaluation of occupant and weather variability and their influences on building performance, algorithm development and testing for thermal and energy load prediction, model predictive control, policy development for reinforcement learning based building controls.

AlphaBuilding↗

Using the ATLAS experiment software on heterogeneous resources

With the large dataset expected from 2030 onwards by the HL-LHC at CERN, the ATLAS experiment is reaching the limits of the current data processing model in terms of traditional CPU resources based on x86_64 architectures and an extensive program for software upgrades towards the HL-LHC has been set up. The ARM CPU architecture is becoming a competitive and energy efficient alternative. Accelerators like GPUs are available in any recent HPC. In the past years ATLAS has successfully ported its full data processing and simulation software framework Athena to ARM and has invested significant effort in porting parts of the reconstruction and simulation algorithms to GPUs. We report on the successful usage of the ATLAS experiment offline and online software framework Athena on ARM and GPUs through the PanDA workflow management system at various WLCG sites. Furthermore we report on performance optimizations of the builds for ARM CPUs and the GPU integration efforts. We will discuss performance comparisons of different ARM and x86_64 architectures on WLCG resources and Cloud compute providers like GCP and AWS using ATLAS productions workflows as used in the Hep-Score23 benchmark suite.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Hybrid Data-Driven Physics-Based Model Framework Implementation: Towards a Secure Cyber-Physical Operation of the Smart Grid

False data injection cyber-attack detection models on smart grid operation have been much explored recently, considering analytical physics-based and data-driven solutions. Recently, a hybrid data-driven physics-based model framework for monitoring the smart grid is developed. However, the framework has not been implemented in real-time environment yet. In this paper, the framework of the hybrid model is developed within a real-time simulation environment. OPAL-RT real-time simulator is used to enable Hardware-in-the-Loop testing of the framework. IEEE 9-bus system is considered as a testing grid for gaining insight. The process of building the framework and the challenges faced during development are presented. The performance of the framework is investigated under various false data injection attacks.

false data injection attack, machine learning, sta↗

A Stochastic Multi-Criteria Decision-Making Algorithm for Dynamic Load Prioritization in Grid-Interactive Efficient Buildings

Increasing deployment of advanced sensing, controls, and communication infrastructure enables buildings to provide services to the power grid, leading to the concept of grid-interactive efficient buildings. Since occupant activities and preferences primarily drive the availability and operational flexibility of building devices, there is a critical need to develop occupant-centric approaches that prioritize devices for providing grid services, while maintaining the desired end-use quality of service. In this paper, we present a decision-making framework that facilitates a building owner/operator to effectively prioritize loads for curtailment service under uncertainties, while minimizing any adverse impact on the occupants. The proposed framework uses a stochastic (Markov) model to represent the probabilistic behavior of device usage from power consumption data, and a load prioritization algorithm that dynamically ranks building loads using a stochastic multi-criteria decision-making algorithm. The proposed load prioritization framework is illustrated via numerical simulations in a residential building use-case, including plug-loads, air-conditioners, and plug-in electric vehicle chargers, in the context of load curtailment as a grid service. Suitable metrics are proposed to evaluate the closed-loop performance of the proposed prioritization algorithm under various scenarios and design choices. Scalability of the proposed algorithm is established via computational analysis, while time-series plots are used for intuitive explanation of the ranking choices.

24 POWER TRANSMISSION AND DISTRIBUTION↗

pypolymix

SAND2026-16700O Pypolymix builds stochastic surrogate models using a lightweight Python library. Researchers working with large-scale scientific models can use it to enhance optimization and uncertainty quantification studies. Pypolymix enables the efficient construction of surrogate models and improves analysis and performance of complex simulations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗