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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Exascale Deep Learning to Accelerate Cancer Research

Deep learning, through the use of neural networks, has demonstrated remarkable ability to automate many routine tasks when presented with sufficient data for training. The neural network architecture (e.g. number of layers, types of layers, connections between layers, etc.) plays a critical role in determining what, if anything, the neural network is able to learn from the training data. The trend for neural network architectures, especially those trained on ImageNet, has been to grow ever deeper and more complex. The result has been ever increasing accuracy on benchmark datasets with the cost of increased computational demands. In this paper we demonstrate that neural network architectures can be automatically generated, tailored for a specific application, with dual objectives: accuracy of prediction and speed of prediction. Using MENNDL- an HPC-enabled software stack for neural architecture search-we generate a neural network with comparable accuracy to state-of-the-art networks on a cancer pathology dataset that is also 16× faster at inference. The speedup in inference is necessary because of the volume and velocity of cancer pathology data; specifically, the previous state-of-the-art networks are too slow for individual researchers without access to HPC systems to keep pace with the rate of data generation. Our new model enables researchers with modest computational resources to analyze newly generated data faster than it is collected.

Patton, Robert↗
DOE OSTI2012

Mapping Dense LU Factorization on Multicore Supercomputer Nodes

Dense LU factorization is a prominent benchmark used to rank the performance of supercomputers. Many implementations use block-cyclic distributions of matrix blocks onto a two-dimensional process grid. The process grid dimensions drive a trade-off between communication and computation and are architecture- and implementation-sensitive. The critical panel factorization steps can be made less communication-bound by overlapping asynchronous collectives for pivoting with the computation of rank-k updates. By shifting the computation-communication trade-off, a modified block-cyclic distribution can beneficially exploit more available parallelism on the critical path, and reduce panel factorization's memory hierarchy contention on now-ubiquitous multicore architectures. During active panel factorization, rank-1 updates stream through memory with minimal reuse. In a column-major process grid, the performance of this access pattern degrades as too many streaming processors contend for access to memory. A block-cyclic mapping in the row-major order does not encounter this problem, but consequently sacrifices node and network locality in the critical pivoting steps. We introduce 'striding' to vary between the two extremes of row- and column-major process grids. The maximum available parallelism in the critical path work (active panel factorization, triangular solves, and subsequent broadcasts) is bounded by the length or width of the process grid. Increasing one dimension of the process grid decreases the number of distinct processes and nodes in the other dimension. To increase the harnessed parallelism in both dimensions, we start with a tall process grid. We then apply periodic 'rotation' to this grid to restore exploited parallelism along the row to previous levels. As a test-bed for further mapping experiments, we describe a dense LU implementation that allows a block distribution to be defined as a general function of block to processor. Other mappings can be tested wit...

Computer Science↗
DOE OSTI2025

Neutrino-Argon Cross-Section Measurements from the MicroBooNE Experiment

MicroBooNE is a liquid argon time projection chamber (LArTPC) neutrino detector located along the Fermilab Booster Neutrino Beam and 8 degrees off-axis to the Neutrinos at the Main Injector beam. MicroBooNE collected data from both beams accumulating a large neutrino-argon scattering dataset with a mean neutrino energy of approximately 0.8 GeV. Understanding neutrino-argon interactions is crucial for the next generation of neutrino oscillation experiments including DUNE. MicroBooNE has developed pioneering methodologies and novel reconstruction tools in order to benchmark models at very high sensitivity across the interaction phase space, including for ultra-rare channels. This talk will give an overview of the most recent MicroBooNE neutrino interaction results. These measurements provide invaluable datasets for constraining backgrounds and improving the modelling of neutrino scattering critical for the broader LArTPC neutrino physics program.

Liu, Liang [Fermilab]↗
NASA NTRS2002

Structural Analyses of Stirling Power Convertor Heater Head for Long-Term Reliability, Durability, and Performance

Deep-space missions require onboard electric power systems with reliable design lifetimes of up to 10 yr and beyond. A high-efficiency Stirling radioisotope power system is a likely candidate for future deep-space missions and Mars rover applications. To ensure ample durability, the structurally critical heater head of the Stirling power convertor has undergone extensive computational analyses of operating temperatures (up to 650 C), stresses, and creep resistance of the thin-walled Inconel 718 bill of material. Durability predictions are presented in terms of the probability of survival. A benchmark structural testing program has commenced to support the analyses. This report presents the current status of durability assessments.

Halford, Gary R.↗
NASA NTRS2004

NASA Data for Water Resources Applications

Water Management Applications is one of twelve elements in the Earth Science Enterprise National Applications Program. NASA Goddard Space Flight Center is supporting the Applications Program through partnering with other organizations to use NASA project results, such as from satellite instruments and Earth system models to enhance the organizations critical needs. The focus thus far has been: 1) estimating water storage including snowpack and soil moisture, 2) modeling and predicting water fluxes such as evapotranspiration (ET), precipitation and river runoff, and 3) remote sensing of water quality, including both point source (e.g., turbidity and productivity) and non-point source (e.g., land cover conversion such as forest to agriculture yielding higher nutrient runoff). The objectives of the partnering cover three steps of: 1) Evaluation, 2) Verification and Validation, and 3) Benchmark Report. We are working with the U.S. federal agencies including the Environmental Protection Agency (EPA), the Bureau of Reclamation (USBR) and the Department of Agriculture (USDA). We are using several of their Decision Support Systems (DSS) tools. This includes the DSS support tools BASINS used by EPA, Riverware and AWARDS ET ToolBox by USBR and SWAT by USDA and EPA. Regional application sites using NASA data across the US. are currently being eliminated for the DSS tools. The current NASA data emphasized thus far are from the Land Data Assimilation Systems WAS) and MODIS satellite products. We are currently in the first two steps of evaluation and verification validation. Water Management Applications is one of twelve elements in the Earth Science Enterprise s National Applications Program. NASA Goddard Space Flight Center is supporting the Applications Program through partnering with other organizations to use NASA project results, such as from satellite instruments and Earth system models to enhance the organizations critical needs. The focus thus far has been: 1) estimating water storage including snowpack and soil moisture, 2) modeling and predicting water fluxes such as evapotranspiration (ET), precipitation and river runoff, and 3) remote sensing of water quality, including both point source (e.g., turbidity and productivity) and non-point source (e.g., land cover conversion such as forest to agriculture yielding higher nutrient runoff). The objectives of the partnering cover three steps of 1) Evaluation, 2) Verification and Validation, and 3) Benchmark Report. We are working with the U.S. federal agencies the Environmental Protection Agency (EPA), the Bureau of Reclamation (USBR) and the Department of Agriculture (USDA). We are using several of their Decision Support Systems (DSS) tools. T us includes the DSS support tools BASINS used by EPA, Riverware and AWARDS ET ToolBox by USBR and SWAT by USDA and EPA. Regional application sites using NASA data across the US. are currently being evaluated for the DSS tools. The current NASA data emphasized thus far are from the Land Data Assimilation Systems (LDAS) and MODIS satellite products. We are currently in the first two steps of evaluation and verification and validation.

Toll, David↗
DOE OSTI2022

Estimating β eff from static, late-time Feynman neutron noise measurements

The effective delayed neutron fraction, β eff , is a kinematic parameter describing the contribution of delayed neutrons to the effective multiplication factor, $\kappa$ eff , and is of great interest to the nuclear criticality safety community and beyond. In fact, $\kappa$ eff presently must be inferred (as opposed to directly measured) since variables like β eff must be obtained from simulation, reference tables, or a dynamic or pulsed measurement where the assembly of fissile material is perturbed and not in steady state. Several recent works have proposed neutron noise techniques to estimate β eff from static measurements (such as benchmark experiments). This work experimentally investigates an approach based on looking at late-time (up to thousands of seconds) correlated neutrons in Feynman histograms. This work utilizes measurements of weapons grade plutonium and highly enriched uranium to construct late-time Feynman histograms and investigate a proposed methodology of estimating β eff from a fit of the distribution. Data is shown from both He-3 detectors and an organic scintillator array. This work is preliminary in nature, demonstrating some experimental feasibility and proposing improvements for future investigations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Status of h-BN quasi-bulk crystals and high efficiency neutron detectors

III-nitrides have fomented a revolution in the lighting industry and are poised to make a huge impact in the field of power electronics. In the III-nitride family, the crystal growth and use of hexagonal BN (h-BN) as an ultrawide bandgap (UWBG) semiconductor are much less developed. Bulk crystals of h-BN produced by the high-temperature/high-pressure and the metal flux solution methods possess very high crystalline and optical qualities but are impractical to serve as substrates or for device implementation as their sizes are typically in millimeters. The development of crystal growth technologies for producing thick epitaxial films (or quasi-bulk or semi-bulk crystals) in large wafer sizes with high crystalline quality is a prerequisite for utilizing h-BN as an UWBG electronic material. Compared to traditional III-nitrides, BN has another unique application as solid-state neutron detectors, which however, also require the development of quasi-bulk crystals to provide high detection efficiencies because the theoretical efficiency (ηi) relates to the detector thickness (d) by ηi=1−e−dλ, where λ denotes the thermal neutron absorption length which is 47 μm (237 μm) for 10B-enriched (natural) h-BN. We provide an overview and recent progress toward the development of h-BN quasi-bulk crystals via hydride vapor phase epitaxy (HVPE) growth and the attainment of thermal neutron detectors based on 100 μm thick 10B-enriched h-BN with a record efficiency of 60%. The thermal neutron detection efficiency was shown to enhance at elevated temperatures. Benchmarking the crystalline and optical qualities of h-BN quasi-bulk crystals with the state-of-the-art mm-sized bulk crystal flakes and 0.5 μm thick epitaxial films identified that reducing the density of native defects such as vacancies remains the most critical task for h-BN quasi-bulk crystal growth by HVPE.

Physics↗
NASA NTRSDate not supplied

Reference Intercalibration for the Climate Observing System

Reference Intercalibration is critical in supporting the construction of climate data records, which, given their necessary longevity, must consist of measurements from multiple instruments. Reference intercalibration enables placing multiple instruments on the same radiometric scale, reducing calibration-based biases in climate data records. Measurements that have characteristics of a climate benchmark make excellent in-orbit intercalibration references. Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) consists of a reflected solar (RS) spectrometer (350-2300 nm) that will take hyperspectral Earth reflectance measurements with unprecedented SI-traceable accuracy (0.3%, 1-sigma) from the International Space Station (ISS). CPF measurements will have several characteristics of climate benchmark measurements and will demonstrate its capability as a rigorous in-orbit intercalibration reference with Clouds and Earth’s Radiant Energy System (CERES) and Visible Infrared Imaging Radiometer Suite (VIIRS). The methodologies that have been developed to support CPF-CERES and CPF-VIIRS intercalibration can readily be extended to other Low Earth Orbit and Geostationary instrument targets. With its highly accurate hyperspectral observations, CPF measurements can also be used to improve the characterization of targets widely used for satellite instrument vicarious calibration including Earth land surface pseudo-invariant calibration sites, deep convective clouds, and the Moon. We will discuss the importance of climate benchmark measurement attributes for intercalibration and considerations for the associated intercalibration data analysis to support building and maintaining climate data records.

Yolanda Shea↗
DOE OSTI2025

Empirically-calibrated H100 node power models for accurate AI training energy estimation

Accurately quantifying the energy use of artificial intelligence (AI) training is critical for infrastructure planning, carbon accounting, and sustainable data center operation, but few studies have directly measured the power consumption of production workloads on contemporary hardware. By combining empirical measurements from Brookhaven National Laboratory during AI training on 8-graphics-processing-unit H100 systems with open-source benchmarking data, we develop statistical models relating computational intensity to node-level power consumption. We measure the gap between manufacturer-rated thermal design power (TDP) and actual power demand during AI training. Our analysis reveals that even computationally intensive workloads operate at only 76% of the 10.2 kW TDP rating. Our architecture-specific model, calibrated to floating-point operations, predicts energy consumption with 11.4% mean absolute percentage error, significantly outperforming TDP-based approaches (27%–37% error). We identified distinct power signatures between transformer and convolutional neural network architectures, with transformers showing characteristic fluctuations that may impact grid stability. These results provide a measurement-grounded basis for improving AI training energy estimates, enabling more reliable infrastructure sizing, cost projections, and environmental impact assessments.

Newkirk, Alex C↗
DOE OSTI2019

Study of Physics Performances at Muon Collider

Muon Collider is a promising option for the next generation high-energy collider, possessing very low radiation losses due to synchrotron radiation.Treatment of the beam-induced background is one of the most critical issues in such a machine.Since the muon beams must be very intense to reach high luminosity, the muons decay products and subsequent particles from secondary interactions with the environment can reach the interaction point, limiting the physical performance of the detector.This talk presents a reconstruction strategy for a benchmark process, H->bb-bar, in the presence of the beam-induced background.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2013

Characterizing Wheel-Soil Interaction Loads Using Meshfree Finite Element Methods: A Sensitivity Analysis for Design Trade Studies

A wheel experiencing sinkage and slippage events poses a high risk to planetary rover missions as evidenced by the mobility challenges endured by the Mars Exploration Rover (MER) project. Current wheel design practice utilizes loads derived from a series of events in the life cycle of the rover which do not include (1) failure metrics related to wheel sinkage and slippage and (2) performance trade-offs based on grouser placement/orientation. Wheel designs are rigorously tested experimentally through a variety of drive scenarios and simulated soil environments; however, a robust simulation capability is still in development due to myriad of complex interaction phenomena that contribute to wheel sinkage and slippage conditions such as soil composition, large deformation soil behavior, wheel geometry, nonlinear contact forces, terrain irregularity, etc. For the purposes of modeling wheel sinkage and slippage at an engineering scale, meshfree nite element approaches enable simulations that capture su cient detail of wheel-soil interaction while remaining computationally feasible. This study implements the JPL wheel-soil benchmark problem in the commercial code environment utilizing the large deformation modeling capability of Smooth Particle Hydrodynamics (SPH) meshfree methods. The nominal, benchmark wheel-soil interaction model that produces numerically stable and physically realistic results is presented and simulations are shown for both wheel traverse and wheel sinkage cases. A sensitivity analysis developing the capability and framework for future ight applications is conducted to illustrate the importance of perturbations to critical material properties and parameters. Implementation of the proposed soil-wheel interaction simulation capability and associated sensitivity framework has the potential to reduce experimentation cost and improve the early stage wheel design proce

terramechanics↗
DOE OSTI2020

INDEN Fissile Actinide Issues [Slides]

This presentation addresses the outlook for the International Nuclear Data Evaluation Network (INDEN), specifically regarding general issues that have been solved, including Thermal Neutron Constants (TNC) and Prompt Fission Neutron Spectra (PFNS). Other topics discussed include outstanding issues in fissile evaluations, comments on the RPI quasi-differential experiment, and reaction rate testing of trial evaluations in fast assemblies. The presentation concludes by discussing how INDEN interactions strongly helped to find deficiencies in existing evaluations and highlighted potential solutions to existing challenges, that updated trial evaluations for U-235, U-233, Pu-239 are available for testing, that further work is expected on U-235, Pu-239, and U-233, and that performance was tested on the ICSBEP and/or SINBAD benchmarks, during which significant improvement was demonstrated. The INDEN scheme of international collaboration on nuclear data evaluation is working well.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Convection Effects During Bulk Transparent Alloy Solidification in DECLIC-DSI and Phase-Field Simulations in Diffusive Conditions

In order to study the dynamical formation and evolution of cellular and dendritic arrays under diffusive growth conditions, three-dimensional (3D) directional solidification experiments were conducted in microgravity on a model transparent alloy onboard the International Space Station using the Directional Solidification Insert in the DEvice for the study of Critical LIquids and Crystallization. Selected experiments were repeated on Earth under gravity-driven fluid flow to evidence convection effects. Both radial and axial macrosegregation resulting from convection are observed in ground experiments, and primary spacings measured on Earth and microgravity experiments are noticeably different. The microgravity experiments provide unique benchmark data for numerical simulations of spatially extended pattern formation under diffusive growth conditions. The results of 3D phase-field simulations highlight the importance of accurately modeling thermal conditions that strongly influence the front recoil of the interface and the selection of the primary spacing. The modeling predictions are in good quantitative agreements with the microgravity experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Simulating Long–Term Dynamics of Radiation Belt Electrons Using DREAM3D Model

Here, we compared the performance of DREAM3D simulations in reproducing the long-term radiation belt dynamics observed by Van Allen Probes over the entire year of 2017 with various boundary conditions (BCs) and model inputs. Specifically, we investigated the effects of three different outer boundary conditions, two different low-energy boundary conditions for seed electrons, four different radial diffusion (RD) coefficients (DLL), four hiss wave models, and two chorus wave models from the literature. Using the outer boundary condition driven by GOES data, our benchmark simulation generally well reproduces the observed radiation belt dynamics inside L* = 6, with a better model performance at lower μ than higher μ, where μ is the first adiabatic invariant. By varying the boundary conditions and inputs, we find that: (a) The data-driven outer boundary condition is critical to the model performance, while adding in the data-driven seed population doesn't further improve the performance. (b) The model shows comparable performance with DLL from Brautigam and Albert (2000, https://doi.org/10.1029/1999ja900344), Ozeke et al. (2014, https://doi.org/10.1002/2013ja019204), and Liu et al. (2016, https://doi.org/10.1002/2015gl067398), while with DLL from Ali et al. (2016, https://doi.org/10.1002/2016ja023002) the model shows less RD compared to data. (c) The model performance is similar with data-based hiss models, but the results show faster loss is still needed inside the plasmasphere. (d) The model performs similarly with the two different chorus models, but better capturing the electron enhancement at higher μ using the Wang et al. (2019, https://doi.org/10.1029/2018ja026183) model due to its stronger wave power, since local heating for higher energy electrons is under-reproduced in the current model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Valorisation of technical lignin in rigid polyurethane foam: A critical evaluation on trends, guidelines and future perspectives

Lignin is one of the most abundant aromatic natural polymers. Produced as a by-product from the biomass refinery industries, lignin remains largely underutilised in high-value industrial applications. The incorporation of lignin in rigid polyurethane foam (RPUF) has been the focus of much research, due to its potential to replace fossil fuel-based components of RPUF. However, the overall sustainability of RPUF depends on numerous factors including processability, cost-effectiveness, and retention of performance throughout the service life. To date, the incorporation of lignin has been explored either as filler particles (through direct incorporation) or as a blendable liquid polyol introduced after chemical modifications (such as oxyalkylation, functionalisation, or depolymerisation). However, the production of lignin incorporated foam with high performance through cost-effective processing is still an ongoing challenge. Herein, this review critically appraises the progress on the effective incorporation of lignin in RPUF. Firstly, this review briefly covers the essential raw materials, formulation, important properties, and sustainability aspects of RPUF for industrial applications. Secondly, it provides insights on the key parameters of lignin of relevance to incorporation into RPUF. Thirdly, it benchmarks the reported studies on incorporation of lignin in RPUF systems by evaluating their important properties and proposes potential strategies for addressing the key challenges in the incorporation of lignin in RPUF. By bridging the gaps that exist in the literature on the utilisation of lignin in RPUF this account will serve as a resource for both beginners and professionals in the polyurethane and biorefinery industries towards the successful development of lignin incorporated RPUF for industrial applications

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Resilient Control of Networked Microgrids Using Vertical Federated Reinforcement Learning: Designs and Real-Time Test-Bed Validations

Improving system-level resiliency of networked microgrids against adversarial cyber-attacks is an important aspect in the current regime of increased inverter-based resources (IBRs). To achieve that, this paper contributes in designing a hierarchical control layer, in conjunction with the existing control layers, resilient to adversarial attack signals. Considering model complexities, unknown dynamical behaviors of IBRs, and privacy issues regarding data sharing in multi-party-owned microgrids, designing such a control layer is non-trivial. Here, to tackle these issues, a novel federated reinforcement learning (Fed-RL) method is proposed. To grasp the interconnected dynamics of networked microgrids, the paper develops Federated Soft Actor-Critic (FedSAC) algorithm following the vertical structure of implementing Fed-RL. Next, utilizing the OpenAI Gym interface, we built a custom set-up in GridLAB-D/HELICS co-simulation platform, named Resilient RL Co-simulation (ResRLCoSIM), to train the RL agents with IEEE 123-bus benchmark comprising 3 interconnected microgrids. Finally, the learned policies in the simulation are transferred to the real-time hardware-in-the-loop (HIL) test-bed developed using the high-fidelity Hypersim platform. Finally, experiments show that the simulator-trained RL controllers achieve desirable performance with the test-bed platform, validating the minimization of the sim-to-real gap.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

HTR-PROTEUS Pebble Bed Experimental Program Core 4: Random Packing With a 1:1 Moderator-to-Fuel Pebble Ratio

In its deployment as a pebble bed reactor (PBR) critical facility from 1992 to 1996, the PROTEUS facility was designated as HTR-PROTEUS. This experimental program was performed as part of an International Atomic Energy Agency (IAEA) Coordinated Research Project (CRP) on the Validation of Safety Related Physics Calculations for Low Enriched HTGRs. Within this project, critical experiments were conducted for graphite moderated LEU systems to determine core reactivity, flux and power profiles, reaction-rate ratios, the worth of control rods, both in-core and reflector based, the worth of burnable poisons, kinetic parameters, and the effects of moisture ingress on these parameters. One benchmark experiment was evaluated in this report: Core 4. Core 4 represents the only configuration with random pebble packing in the HTR-PROTEUS series of experiments, and has a moderator-to-fuel pebble ratio of 1:1. Three random configurations were performed. The initial configuration, Core 4.1, was rejected because the method for pebble loading, separate delivery tubes for the moderator and fuel pebbles, may not have been completely random; this core loading was rejected by the experimenters. Cores 4.2 and 4.3 were loaded using a single delivery tube, eliminating the possibility for systematic ordering effects. The second and third cores differed slightly in the quantity of pebbles loaded (40 each of moderator and fuel pebbles), stacked height of the pebbles in the core cavity (0.02 m), withdrawn distance of the stainless steel control rods (20 mm), and withdrawn distance of the autorod (30 mm). The 34 coolant channels in the upper axial reflector and the 33 coolant channels in the lower axial reflector were open. Additionally, the axial graphite fillers used in all other HTR-PROTEUS configurations to create a 12-sided core cavity were not used in the randomly packed cores. Instead, graphite fillers were placed on the cavity floor, creating a funnel-like base, to discourage ordering effects during pebble loading. Core 4 was determined to be acceptable benchmark experiment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗