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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Bacillus subtilis Lipid Extract, A Branched-Chain Fatty Acid Model Membrane

Lipid extracts are an excellent choice of model biomembrane; however at present, there are no commercially available lipid extracts or computational models that mimic microbial membranes containing the branched-chain fatty acids found in many pathogenic and industrially relevant bacteria. Here, we advance the extract of Bacillus subtilis as a standard model for these diverse systems, providing a detailed experimental description and equilibrated atomistic bilayer model included as Supporting Information to this Letter and at (http://cmb.ornl.gov/members/cheng). The development and validation of this model represents an advance that enables more realistic simulations and experiments on bacterial membranes and reconstituted bacterial membrane proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Three-dimensional magnetohydrodynamic modeling of auto-magnetizing liner implosions on the Z accelerator

Auto-magnetizing (AutoMag) liners are cylindrical tubes that employ helical current flow to produce strong internal axial magnetic fields prior to radial implosion on ~100 ns timescales. AutoMag liners have demonstrated strong uncompressed axial magnetic field production (>100 T) and remarkable implosion uniformity during experiments on the 20 MA Z accelerator. However, both axial field production and implosion morphology require further optimization to support the use of AutoMag targets in magnetized liner inertial fusion (MagLIF) experiments. Data from experiments studying the initiation and evolution of dielectric flashover in AutoMag targets on the Mykonos accelerator have enabled the advancement of magnetohydrodynamic (MHD) modeling protocols used to simulate AutoMag liner implosions. Implementing these protocols using ALEGRA has improved the comparison of simulations to radiographic data. Specifically, both the liner in-flight aspect ratio and the observed width of the encapsulant-filled helical gaps during implosion in ALEGRA simulations agree more closely with radiography data compared to previous GORGON simulations. Although simulations fail to precisely reproduce the measured internal axial magnetic field production, improved agreement with radiography data inspired the evaluation of potential design improvements with newly developed modeling protocols. Three-dimensional MHD simulation studies focused on improving AutoMag target designs, specifically seeking to optimize the axial magnetic field production and enhance the cylindrical implosion uniformity for MagLIF. Importantly, by eliminating the driver current prepulse and reducing the initial inter-helix gap widths in AutoMag liners, simulations indicate that the optimal 30–50 T range of precompressed axial magnetic field for MagLIF on Z can be accomplished concurrently with improved cylindrical implosion uniformity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Quantification of Arctic Soil and Permafrost Properties Using Ground-Penetrating Radar and Electrical Resistivity Tomography Datasets

Improving understanding of Arctic ecosystem climate feedback and parameterization of models that simulate freeze-Thaw dynamics require advances in quantifying soil and snow properties. Due to the significant spatiotemporal variability of soil properties and the limited information provided by point-scale measurements (e.g., cores), geophysical methods hold potential for improving soil and permafrost characterization. In this study, we evaluate the use of a ground-penetrating radar (GPR) to estimate thaw layer thickness, snow depth, and ice-wedge characteristics in an ice-wedge-dominated tundra region near Barrow, AK, USA. To this end, we analyze GPR and point-scale measurements collected along several parallel transects at the end of the growing season and the end of frozen season. In addition, we compare the structural information extracted from the GPR data with electrical resistivity tomography (ERT) information about ice-wedge characteristics. Our study generally highlights the value of GPR data collected in the frozen season, when conditions lead to the improved GPR signal-To-noise ratio, facilitate data acquisition, and reduce acquisition-related ecosystem disturbance relative to growing season. We document for the first time that GPR data collected during the frozen season can provide reliable estimates of active layer thickness and geometry of ice wedges. We find that the ice-wedge geometry extracted from GPR data collected during the frozen season is consistent with ERT data, and that GPR data can be used to constrain the ERT inversion. Consistent with recent studies, we also find that GPR data collected during the frozen season can provide good estimates of snow thickness, and that GPR data collected during the growing season can provide reliable estimate thaw depth. As a result, our quantification of the value of the GPR and ERT data collected during growing and frozen seasons paves the way for coupled inversion of the datasets to improve understanding of permafrost variability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Assessing Advanced Technology in CENATE

PNNL's Center for Advanced Technology Evaluation (CENATE) is a new U.S. Department of Energy center whose mission is to assess and facilitate access to emerging computing technology. CENATE is assessing a range of advanced technologies, from evolutionary to disruptive. Technologies of interest include the processor socket (homogeneous and accelerated systems), memories (dynamic, static, memory cubes), motherboards, networks (network interface cards and switches), and input/output and storage devices. CENATE is developing a multi-perspective evaluation process based on integrating advanced system instrumentation, performance measurements, and modeling and simulation. We show evaluations of two emerging network technologies: silicon photonics interconnects and the Data Vortex network. CENATE's evaluation also addresses the question of which machine is best for a given workload under certain constraints. We show a performance-power tradeoff analysis of a well-known machine learning application on two systems.

Tallent, Nathan R.↗
DOE OSTI2020

SAM Code Validation on Frictional Pressure Drop through Pebble Beds

The System Analysis Module (SAM) is currently under development at Argonne National Laboratory as a modern system-level modeling and simulation tool for safety analyses of advanced non-light water reactors. This report presents a recent effort to validate the capability of SAM to predict the frictional pressure drop through pebble beds. Selected experimental data were used for code validation, including data from test facilities at Texas A&M University, Missouri University of Science and Technology, and North-West University of South Africa. SAM implements three empirical correlations to predict frictional pressure drop: the classical Ergun correlation; the KTA correlation, which is widely used in high-temperature gas-cooled reactor applications; and the Eisfeld and Schnitzlein correlation, which explicitly considers wall effect. Code validation was performed using all three correlations. For all selected experimental data, the KTA correlation shows the best performance and agrees very well with experimental measurement; the Eisfeld and Schnitzlein correlation, explicitly considering wall effects, shows acceptable accuracy, while there is no evidence that it is better than the KTA correlation; the Ergun correlation, however, over-predicts frictional pressure drop for most selected data points.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1987

Building intelligent systems - Artificial intelligence research at NASA Ames Research Center

The basic components that make up the goal of building autonomous intelligent systems are discussed, and ongoing work at the NASA Ames Research Center is described. It is noted that a clear progression of systems can be seen through research settings (both within and external to NASA) to Space Station testbeds to systems which actually fly on the Space Station. The starting point for the discussion is a 'truly' autonomous Space Station intelligent system, responsible for a major portion of Space Station control. Attention is given to research in fiscal 1987, including reasoning under uncertainty, machine learning, causal modeling and simulation, knowledge from design through operations, advanced planning work, validation methodologies, and hierarchical control of and distributed cooperation among multiple knowledge-based systems.

Friedland, Peter↗
NASA NTRS1987

Building intelligent systems: Artificial intelligence research at NASA Ames Research Center

The basic components that make up the goal of building autonomous intelligent systems are discussed, and ongoing work at the NASA Ames Research Center is described. It is noted that a clear progression of systems can be seen through research settings (both within and external to NASA) to Space Station testbeds to systems which actually fly on the Space Station. The starting point for the discussion is a truly autonomous Space Station intelligent system, responsible for a major portion of Space Station control. Attention is given to research in fiscal 1987, including reasoning under uncertainty, machine learning, causal modeling and simulation, knowledge from design through operations, advanced planning work, validation methodologies, and hierarchical control of and distributed cooperation among multiple knowledge-based systems.

Friedland, P.↗
NASA NTRS1990

Integrated analysis and applications

An overview is presented of current research activities which, in a broad context, are focused on the development and verification of integrated structural analysis and optimal design capabilities for advanced aerospace propulsion and power systems. The overview encompasses a variety of subject areas including: (1) composite materials; (2) advanced structural analysis; (3) constitutive modeling; (4) computational simulation; (5) probabilistic analysis; and (6) multidisciplinary optimization. Typical results are presented which illustrate the benefit and utility of the emerging technologies as applied to propulsion and power system structures.

Hopkins, Dale A.↗
NASA NTRS1991

Space - A unique environment for process modeling R&D

Process modeling, the application of advanced computational techniques to simulate real processes as they occur in regular use, e.g., welding, casting and semiconductor crystal growth, is discussed. Using the low-gravity environment of space will accelerate the technical validation of the procedures and enable extremely accurate determinations of the many necessary thermophysical properties. Attention is given to NASA's centers for the commercial development of space; joint ventures of universities, industries, and goverment agencies to study the unique attributes of space that offer potential for applied R&D and eventual commercial exploitation.

Overfelt, Tony↗
NASA NTRS2002

Fractional-order Viscoelasticity (FOV): Constitutive Development Using the Fractional Calculus: First Annual Report

This is the first annual report to the U.S. Army Medical Research and Material Command for the three year project "Advanced Soft Tissue Modeling for Telemedicine and Surgical Simulation" supported by grant No. DAMD17-01-1-0673 to The Cleveland Clinic Foundation, to which the NASA Glenn Research Center is a subcontractor through Space Act Agreement SAA 3-445. The objective of this report is to extend popular one-dimensional (1D) fractional-order viscoelastic (FOV) materials models into their three-dimensional (3D) equivalents for finitely deforming continua, and to provide numerical algorithms for their solution.

Freed, Alan↗
NASA NTRS2006

Impact of the Columbia Supercomputer on NASA Space and Exploration Mission

NASA's 10,240-processor Columbia supercomputer gained worldwide recognition in 2004 for increasing the space agency's computing capability ten-fold, and enabling U.S. scientists and engineers to perform significant, breakthrough simulations. Columbia has amply demonstrated its capability to accelerate NASA's key missions, including space operations, exploration systems, science, and aeronautics. Columbia is part of an integrated high-end computing (HEC) environment comprised of massive storage and archive systems, high-speed networking, high-fidelity modeling and simulation tools, application performance optimization, and advanced data analysis and visualization. In this paper, we illustrate the impact Columbia is having on NASA's numerous space and exploration applications, such as the development of the Crew Exploration and Launch Vehicles (CEV/CLV), effects of long-duration human presence in space, and damage assessment and repair recommendations for remaining shuttle flights. We conclude by discussing HEC challenges that must be overcome to solve space-related science problems in the future.

Biswas, Rupak↗
NASA NTRS2010

Mercury's Dynamic Magnetic Tail

The Mariner 10 and MESSENGER flybys of Mercury have revealed a magnetosphere that is likely the most responsive to upstream interplanetary conditions of any in the solar system. The source of the great dynamic variability observed during these brief passages is due to Mercury's proximity to the Sun and the inverse proportionality between reconnection rate and solar wind Alfven Mach number. However, this planet's lack of an ionosphere and its small physical dimensions also contribute to Mercury's very brief Dungey cycle, approx. 2 min, which governs the time scale for internal plasma circulation. Current observations and understanding of the structure and dynamics of Mercury's magnetotail are summarized and discussed. Special emphasis will be placed upon such questions as: 1) How much access does the solar wind have to this small magnetosphere as a function of upstream conditions? 2) What roles do heavy planetary ions play? 3) Do Earth-like substorms take place at Mercury? 4) How does Mercury's tail respond to extreme solar wind events such coronal mass ejections? Prospects for progress due to advances in the global magnetohydrodynamic and hybrid simulation modeling and the measurements to be taken by MESSENGER after it enters Mercury orbit on March 18, 2011 will be discussed.

Slavin, James A.↗
NASA NTRS2013

Autonomous Aerobraking Development Software: Phase 2 Summary

NASA has used aerobraking at Mars and Venus to reduce the fuel required to deliver a spacecraft into a desired orbit compared to an all-propulsive solution. Although aerobraking reduces the propellant, it does so at the expense of mission duration, large staff, and DSN coverage. These factors make aerobraking a significant cost element in the mission design. By moving on-board the current ground-based tasks of ephemeris determination, atmospheric density estimation, and maneuver sizing and execution, a flight project would realize significant cost savings. The NASA Engineering and Safety Center (NESC) sponsored Phase 1 and 2 of the Autonomous Aerobraking Development Software (AADS) study, which demonstrated the initial feasibility of moving these current ground-based functions to the spacecraft. This paper highlights key state-of-the-art advancements made in the Phase 2 effort to verify that the AADS algorithms are accurate, robust and ready to be considered for application on future missions that utilize aerobraking. The advancements discussed herein include both model updates and simulation and benchmark testing. Rigorous testing using observed flight atmospheres, operational environments and statistical analysis characterized the AADS operability in a perturbed environment.

Cianciolo, Alicia D.↗
DOE OSTI2024

NEA HTTR LOFC Project Test#3 Benchmark Results

In the second half of FY23, the High Temperature Engineering Test Reactor (HTTR) Loss Of Forced Cooling (LOFC)#3 data for the 9 MW test case with Vessel Cooling System (VCS) off were made available through the Nuclear Energy Agency (NEA) LOFC project framework; the neutronic model developed for the initial test (LOFC#1) achieved a satisfactory level of maturity, demonstrating its accuracy in predicting power evolution and core re-criticality, but LOFC#3 should be used primarily to investigate thermal hydraulic phenomena, as the reactor was shut down prematurely due to overheating in the upper reactor components, which prevented re-criticality; this report focuses on advancing the HTTR thermal hydraulic model to accurately simulate the LOFC#3 scenario, including simulating the LOFC#3 benchmark and generating the corresponding benchmark specifications, aiming to ensure consistency across participant models and provide essential data for future participants, including private industry stakeholders seeking to validate their computational tools.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Neutron Capture Energies for Flux Normalization and Approximate Model for Gamma-Smeared Power

The Consortium for Advanced Simulation of Light Water Reactors (CASL) Virtual Environment for Reactor Applications (VERA) neutronics simulator MPACT has used a single recoverable fission energy for each fissionable nuclide assuming that all recoverable energies come only from fission reaction, for which capture energy is merged with fission energy. This approach includes approximations and requires improvement by separating capture energy from the merged effective recoverable energy. This report documents the procedure to generate recoverable neutron capture energies and the development of a program called CapKappa to generate capture energies. Recoverable neutron capture energies have been generated by using CapKappa with the evaluated nuclear data file (ENDF)/B-7.0 and 7.1 cross section and decay libraries. The new capture kappas were compared to the current SCALE-6.2 and the CASMO-5 capture kappas. These new capture kappas have been incorporated into the Simplified AMPX 51- and 252-group libraries, and they can be used for the AMPX multigroup (MG) libraries and the SCALE code package. The CASL VERA neutronics simulator MPACT does not include a gamma transport capability, which limits it to explicitly estimating local energy deposition from fission, neutron, and gamma slowing down and capture. Since the mean free path of gamma rays is typically much longer than that for the neutron, and the total gamma energy is about 10% to the total energy, the gamma-smeared power distribution is different from the fission power distribution. Explicit local energy deposition through neutron and gamma transport calculation is significantly important in multi-physics whole core simulation with thermal-hydraulic feedback. Therefore, the gamma transport capability should be incorporated into the CASL neutronics simulator MPACT. However, this task will be timeconsuming in developing the neutron induced gamma production and gamma cross section libraries. This study is to investigate an approximate model to estimate gammasmeared power distribution without performing any gamma transport calculation. A simple approximate gamma smearing model has been investigated based on the facts that pinwise gamma energy depositions are almost flat over a fuel assembly, and assembly-wise gamma energy deposition is proportional to kappa-fission energy deposition. The approximate gamma smearing model works well for single assembly cases, and can partly improve the gamma smeared power distribution for the whole core model. Although the power distributions can be improved by the approximate gamma smearing model, still there is an issue to explicitly obtain local energy deposition. A new simple approach or gamma transport/diffusion capability may need to be incorporated into MPACT to estimate local energy deposition for more robust multi-physics simulation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Simulating Hurricane Katrina in the Simple Cloud‐Resolving E3SM Atmosphere Model v1

Climate models are important tools for advancing understanding and prediction of tropical cyclones (TCs). Traditional global climate models, however, do not have the ability to properly simulate TC intensity due to their coarse horizontal resolution. Regional models can be run at convection‐permitting resolutions, but these models are often strongly influenced by the data used in the lateral boundary forcing, and domain choice can have a large impact on the simulation. Cloud‐resolving global climate models have demonstrated great potential for realism in TC simulations, and in this study we focus specifically on the Simple Cloud‐Resolving Energy Exascale Earth System Model (E3SM) Atmosphere Model (SCREAM) v1 configuration. We evaluate SCREAMv1 against the observational record and the Weather Research and Forecasting (WRF) model run at a convection‐permitting resolution with Hurricane Katrina as our case study. We found that both models produced realistic simulations of Hurricane Katrina. SCREAMv1 demonstrated skill in simulating TC track, size, and intensity, while the model produced an excessive amount of precipitation. In comparison, WRF more accurately simulated TC precipitation and intensity, although the TC wind extent was smaller than the observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Investigation of dynamics of ELM crashes and their mitigation techniques

The accurate prediction of H-mode pedestal dynamics is critical for planning experiments in existing tokamaks and in the design of future tokamaks such as ITER and DEMO. The main objective of the proposed research is to advance the understanding of the physics of H-mode pedestal. Through advances in coupled kinetic-MHD simulations, a new model for H-mode pedestal and ELM crashes as well as an improved model for the bootstrap current will be developed. ELMmitigation techniques will also be investigated. The proposed research will help design efficient confinement scenarios and reduce transient heat loads on the divertor and plasma facing components. During the last two years, the principal investigator (PI) of this proposal actively participated in physics studies related to the DOE Joint Research Targets. These studies include the modeling of divertor heat load in the DIII-D, Alcator C-Mod, and NSTX tokamaks in 2010, and the modeling of H-mode pedestal structure in the DIII-D tokamak in 2011. It is proposed that this close collaboration with experimentalists from major US tokamaks continue during the next funding period. Verification and validation will be a strong component of the proposed research. During the course of the project, advances will be made in the following areas; Dynamics of the H-mode pedestal buildup and recovery after ELM crashes – The effects of neutral fueling, particle and thermal pinches will be explored; Dynamics of ELM crashes in realistic tokamak geometries – Heat loads associated with ELM crashes will be validated against experimental measurements. An improved model for ELM crashes will be developed; ELM mitigation – The effect of resonant magnetic perturbations on ELMs stability and their evolution will be investigated; Development of a new bootstrap current model – A reduced model for will be developed through careful verification of existing models for bootstrap current against first-principle kinetic neoclassical simulations. The primary focus here will be on plasma regimes where the existing reduced models deviate from each other, such as high-beta and low aspect ratio plasmas; and Results will be verified against analytical models and simulation results from other codes. Simulation results will be compared with diagnostic experimental data such as Thomson measurements (HRTC) or flux measurements if available. We have arrangements with experimentalists from DIII-D and JET to use diagnostic edge data for this validation. In summary, we propose to study the H-mode pedestal buildup, the stability and evolution of ELMs using a model that will account for dynamically evolving neoclassical sources.

42 ENGINEERING↗
DOE OSTI2022

Enhanced physics-constrained deep neural networks for modeling vanadium redox flow battery

Numerical simulation has become indispensable in advancing cost-effective process optimization and control of flow batteries. We propose an enhanced version of the physics-constrained deep neural network (PCDNN) approach to provide high-accuracy voltage predictions in the vanadium redox flow batteries (VRFBs). The purpose of the PCDNN approach is to enforce the physics-based zero-dimensional (0D) VRFB model in a neural network to assure model generalization for various battery operation conditions. However, limited by the simplifications of the 0D model, the PCDNN cannot capture sharp voltage changes in the extreme SOC regions. To improve the accuracy of voltage prediction at extreme ranges, we introduce a second (enhanced) DNN to mitigate the prediction errors carried from the 0D model itself and call the resulting approach enhanced PCDNN (ePCDNN). By comparing with experimental data, we demonstrate that the ePCDNN approach can accurately capture the voltage response throughout the charge–discharge cycle, including the tail region of the voltage discharge curve. The loss function for training the ePCDNN is designed to be flexible by adjusting the weights of the physics-constrained DNN and the enhanced DNN. In conclusion, this allows the ePCDNN framework to be transferable to battery systems with variable physical model fidelity.

25 ENERGY STORAGE↗