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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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Combined convective and diffusive simulations: VERB-4D comparison with 17 March 2013 Van Allen Probes observations: VERB-4D

Our study focused on understanding the coupling between different electron populations in the inner magnetosphere and the various physical processes that determine evolution of electron fluxes at different energies. Observations during the 17 March 2013 storm and simulations with a newly developed Versatile Electron Radiation Belt-4D (VERB-4D) are presented. This analysis of the drift trajectories of the energetic and relativistic electrons shows that electron trajectories at transitional energies with a first invariant on the scale of ~100 MeV/G may resemble ring current or relativistic electron trajectories depending on the level of geomagnetic activity. Simulations with the VERB-4D code including convection, radial diffusion, and energy diffusion are presented. Sensitivity simulations including various physical processes show how different acceleration mechanisms contribute to the energization of energetic electrons at transitional energies. In particular, the range of energies where inward transport is strongly influenced by both convection and radial diffusion are studied. Our results of the 4-D simulations are compared to Van Allen Probes observations at a range of energies including source, seed, and core populations of the energetic and relativistic electrons in the inner magnetosphere.

58 GEOSCIENCES↗
DOE OSTI2016

Group Structure Optimization Using the PyGroup Code

Group constants are used as coefficients in the energy domain discretized Linear Boltzmann Equation (LBE), in which the Continuous-Energy (CE) fluxes are also integrated over energy bins and transformed into group fluxes. This procedure, based on the Multi-Group (MG) theory, is widely applied in radiation transport and diffusion simulations Careful preparation of MG cross section data, or group constants, is thus a prerequisite for success in acquiring high-fidelity LBE solutions. Generation of MG cross section data itself is a complicated multi-step task, since group constants are indispensably coupled with the solution of the LBE, i.e. the flux spectrum in the problem to be solved. Theoretically, a MG cross section library is only valid for the problem that it is built upon. Nevertheless, in practice MG cross section libraries are prepared for similar type of problems, such as thermal reactors, fast reactors, etc., to facilitate the neutronic simulations. Generally, CE point-wise cross section data set, generated by both theoretical models and experimental data, is first converted to Fine-Group (FG) libraries using a pre-defined or precalculated flux spectra, then, Broad-Group (BG) libraries are collapsed from the fine-group libraries using problem-dependent flux spectra. Proper treatments of energy and spatial self-shielding and resonance cross section are required in the CE-to-MG converting process Previously, we have developed a computer code, YGROUP, for fine-to-broad group cross section collapsing. To maintain high accuracy of the resulting BG libraries, YGROUP provides users several options on collapsing strategies and weighting schemes for group binning and evaluation of BG cross section data in users' specific problems.. An approach based on Particle Swarm Optimization was applied to automatically determine the optimal group structure. We also developed a hybrid weighting scheme to further improve BG library performance for Special Nuclear Materials (SNM) detection applications. In this work, a new computer code, PyGroup, has been developed to implement the PSO approach with an improved simulation-driven fitness function design that includes both response and forward/adjoint flux errors. Together with YGROUP, and deterministic transport code TITAN/PENMSHXP, the PyGroup code package is tested on a Dual Range Coincident Counter (DRCC) model. In this paper, we demonstrated the capability of the PyGroup code for group structure optimization using the DRCC detector model. In the future, an iteration scheme can be implemented to determine the number of broad groups based on a user-defined tolerance. we will also apply PyGroup to more complicated reactor models, and investigate physics-based fitness function designs to further reduce computational cost. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Porting a fast-running wildfire plume model for use in national security and climate applications

In this project, the code for the fast-running Freitas wildfire plume model was successfully ported into the NARAC system, creating an operations-ready capability for predicting the transport of hazardous smoke from large wildfires. “Porting” refers to copying a section of code from one software package to another while accounting for unique dependencies in each software package. In this case, the code was ported from the Weather Research and Forecasting (WRF) Model, which is used extensively by the project team. To verify correct implementation, model results from the updated NARAC system were compared to those from WRF and the High-Resolution Rapid Refresh (HRRR) forecast model, which also employs the Freitas scheme. The NARAC User Interface (UI) and code documentation were also updated to include the new wildfire plume option, and a wildfire case was added to the NARAC test suite. The code was used in a real-time, semi-operational setup to predict smoke transport during the Cerro Pelado fire near Los Alamos National Laboratory in May 2022. The Freitas plume model was also tested for LLNL climate applications. Although the code was not ported into the Energy Exascale Earth System Model (E3SM), it was tested offline using E3SM atmospheric inputs, and results were compared to existing high-resolution plume predictions from large-eddy simulations in WRF. The code implementation and testing completed during this project will enable future work predicting smoke transport from large wildfires in LLNL national security and climate mission spaces.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1995

Fluid Film Bearing Code Development

The next generation of rocket engine turbopumps is being developed by industry through Government-directed contracts. These turbopumps will use fluid film bearings because they eliminate the life and shaft-speed limitations of rolling-element bearings, increase turbopump design flexibility, and reduce the need for turbopump overhauls and maintenance. The design of the fluid film bearings for these turbopumps, however, requires sophisticated analysis tools to model the complex physical behavior characteristic of fluid film bearings operating at high speeds with low viscosity fluids. State-of-the-art analysis and design tools are being developed at the Texas A&M University under a grant guided by the NASA Lewis Research Center. The latest version of the code, HYDROFLEXT, is a thermohydrodynamic bulk flow analysis with fluid compressibility, full inertia, and fully developed turbulence models. It can predict the static and dynamic force response of rigid and flexible pad hydrodynamic bearings and of rigid and tilting pad hydrostatic bearings. The Texas A&M code is a comprehensive analysis tool, incorporating key fluid phenomenon pertinent to bearings that operate at high speeds with low-viscosity fluids typical of those used in rocket engine turbopumps. Specifically, the energy equation was implemented into the code to enable fluid properties to vary with temperature and pressure. This is particularly important for cryogenic fluids because their properties are sensitive to temperature as well as pressure. As shown in the figure, predicted bearing mass flow rates vary significantly depending on the fluid model used. Because cryogens are semicompressible fluids and the bearing dynamic characteristics are highly sensitive to fluid compressibility, fluid compressibility effects are also modeled. The code contains fluid properties for liquid hydrogen, liquid oxygen, and liquid nitrogen as well as for water and air. Other fluids can be handled by the code provided that the user inputs information that relates the fluid transport properties to the temperature.

Source record↗
DOE OSTI2023

Coupling SCALE with DAKOTA for Axial Burnup Profiles Assessment in Burnup Credit

This paper presents a computational study that demonstrates the application of the SCALE code system in conjunction with the Design Analysis Kit for Optimization and Terascale Applications (DAKOTA) for the analysis of key factors influencing the evaluation of burnup credit (BUC) in pressurized water reactors (PWRs). The primary objective of this analysis is to characterize the model by utilizing parameterization, uncertainty quantification, and optimization studies. Using this approach, we can comprehensively assess the system and conduct informed predictive studies. This study highlights the effectiveness of the SCALE code system integrated within the DAKOTA framework in terms of efficiency and capability. With the coupling of the burnup code ORIGAMI with the CSAS or TSUNAMI-3D sequence embedded in a DAKOTA analysis, we can characterize the factors that influence the k eff of PWR 17x17 spent nuclear fuel (SNF) in the GBC-32 computational benchmark cask for the assessment of BUC in criticality safety analysis. The coupling methodology used in this study is not exclusive to BUC analysis. However, the choice to apply this methodology to the BUC problem is particularly significant because of the diverse range of aspects it encompasses in nuclear criticality safety analyses. This problem presents a unique opportunity to explore and address multiple facets of such analyses related to BUC and illustrates the capability of the SCALE code system with DAKOTA. This analysis makes use of historical reference data for the axial burnup profile, where the entire space within the bounds is considered. Both SCALE and DAKOTA are currently integrated in the Nuclear Energy Advanced Modeling Simulation (NEAMS) Workbench code system, which has a user-friendly graphical interface that simplifies the setup of simulations and configuration of input parameters as well as the visualization of simulation results.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1990

Ion cyclotron absorption at the second harmonic of the oxygen gyrofrequency

A hot ray tracing code (HOTRAY) is used to establish the ultimate demise of the wave energy generated inside the plasmasphere during storm conditions. The code uses the WKB approximation of geometric optics to calculate the paths of electromagnetic and electrostatic waves in a hot, multiion plasma. Ray tracing calculations with HOTRAY are detailed and path integrated absorption is discussed. Unducted waves which are preferentially generated in the field aligned direction are rapidly refracted to large wave normal angles. The waves are observed to reflect at frequencies between oxygen and helium gyrofrequencies once their frequency falls below the bi-ion frequency and the waves bounce back accross the equator. Either Landau resonance with plasmaspheric electrons or second harmonic cyclotron resonance with thermal oxygen ultimately absorb the wave energy. It is suggested that both processes may provide a significant heating mechanism for either population during a storm.

Horne, R. B.↗
DOE OSTI2014

Optimization and Parallelization of the Thermal-Hydraulic Sub-channel Code CTF for High-Fidelity Multi-physics Applications

This paper describes major improvements to the computational infrastructure of the CTF sub-channel code so that full-core sub-channel-resolved simulations can now be performed in much shorter run-times, either in stand-alone mode or as part of coupled-code multi-physics calculations. These improvements support the goals of the Department Of Energy (DOE) Consortium for Advanced Simulations of Light Water (CASL) Energy Innovation Hub to develop high fidelity multi-physics simulation tools for nuclear energy design and analysis. A set of serial code optimizations--including fixing computational inefficiencies, optimizing the numerical approach, and making smarter data storage choices--are first described and shown to reduce both execution time and memory usage by about a factor of ten. Next, a Single Program Multiple Data (SPMD) parallelization strategy targeting distributed memory Multiple Instruction Multiple Data (MIMD) platforms and utilizing domain-decomposition is presented. In this approach, data communication between processors is accomplished by inserting standard MPI calls at strategic points in the code. The domain decomposition approach implemented assigns one MPI process to each fuel assembly, with each domain being represented by its own CTF input file. The creation of CTF input files, both for serial and parallel runs, is also fully automated through use of a pre-processor utility that takes a greatly reduced set of user input over the traditional CTF input file. To run CTF in parallel, two additional libraries are currently needed; MPI, for inter-processor message passing, and the Parallel Extensible Toolkit for Scientific Computation (PETSc), which is leveraged to solve the global pressure matrix in parallel. Results presented include a set of testing and verification calculations and performance tests assessing parallel scaling characteristics up to a full core, sub-channel-resolved model of Watts Bar Unit 1 under hot full-power conditions (193 17x17 assemblies, ~56,000 pins, ~59,000 sub-channels, ~2.8 million thermal-hydraulic (TH) control volumes). Results demonstrate that CTF can now perform full core analysis (not previously possible due to excessively long runtimes and memory requirements) on the order of 20 minutes. This new capability is not only useful to standalone CTF users, but is also being leveraged in support of coupled code multi-physics calculations being done in the CASL program.

COBRA-TF↗
DOE OSTI2013

Industrial Geospatial Analysis Tool for Energy Evaluation (IGATE-E)

IGATE-E is an energy analysis tool for industrial energy evaluation. The tool applies statistical modeling to multiple publicly available datasets and provides information at the geospatial resolution of zip code using bottom up approaches. Within each zip code, the current version of the tool estimates electrical energy consumption of manufacturing industries based on each type of industries using DOE s Industrial Assessment Center database (IAC-DB) and DOE s Energy Information Administration Manufacturing Energy Consumption Survey database (EIA-MECS DB), in addition to other commercially available databases such as the Manufacturing News database (MNI, Inc.). Ongoing and future work include adding modules for the predictions of fuel energy consumption streams, manufacturing process steps energy consumption, major energy intensive processes (EIPs) within each industry type among other metrics of interest. The tool provides validation against DOE s EIA-MECS state level energy estimations and permits several statistical examinations. IGATE-E is intended to be a decision support and planning tool to a wide spectrum of energy analysts, researchers, government organizations, private consultants, industry partners, and alike.

Energy Analysis Tool↗
NASA NTRS2010

Overview of the Graphical User Interface for the GERM Code (GCR Event-Based Risk Model

The descriptions of biophysical events from heavy ions are of interest in radiobiology, cancer therapy, and space exploration. The biophysical description of the passage of heavy ions in tissue and shielding materials is best described by a stochastic approach that includes both ion track structure and nuclear interactions. A new computer model called the GCR Event-based Risk Model (GERM) code was developed for the description of biophysical events from heavy ion beams at the NASA Space Radiation Laboratory (NSRL). The GERM code calculates basic physical and biophysical quantities of high-energy protons and heavy ions that have been studied at NSRL for the purpose of simulating space radiobiological effects. For mono-energetic beams, the code evaluates the linear-energy transfer (LET), range (R), and absorption in tissue equivalent material for a given Charge (Z), Mass Number (A) and kinetic energy (E) of an ion. In addition, a set of biophysical properties are evaluated such as the Poisson distribution of ion or delta-ray hits for a specified cellular area, cell survival curves, and mutation and tumor probabilities. The GERM code also calculates the radiation transport of the beam line for either a fixed number of user-specified depths or at multiple positions along the Bragg curve of the particle. The contributions from primary ion and nuclear secondaries are evaluated. The GERM code accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections, and has been used by the GERM code for application to thick target experiments. The GERM code provides scientists participating in NSRL experiments with the data needed for the interpretation of their experiments, including the ability to model the beam line, the shielding of samples and sample holders, and the estimates of basic physical and biological outputs of the designed experiments. We present an overview of the GERM code GUI, as well as providing training applications.

Kim, Myung-Hee↗
DOE OSTI2012

Knudsen Layer Reduction of Fusion Reactivity

Over-prediction of fusion energy yield has been a persistent enigma in inertial fusion systems for over 50 years. This paper presents a new piece of physics to help to resolve this puzzle. Our best (clean) theory and code predictions have systematically calculated higher energy yield from fusion than observed in experiments by factors of two and more. This yield over-prediction has traditionally been attributed to the “mix” of impurities into the fuel. Many models of such mix have been developed, refined and applied over the years. Nonetheless, current mix models fall short of being fully satisfactory. This work is motivated by the belief that it is missing physics beyond “mix” that is needed to account for yield over-prediction (although we certainly expect mix to play a role and have combined it with the new physics in simulating experiment ). The Knudsen layer effect we describe briefly here (and published in Physical Review Letters) is such a piece of physics that fundamentally reduces the fusion reactivity by depleting the high energy tail population of fuel ions that are primarily responsible for the yield.

Plasma Physics & Fusion Technology(70)↗
DOE OSTI2024

TEAMER: Twin Ocean Power Wave Energy Converter Comprehensive Overview

These files collectively provide a comprehensive overview of the testing process, data analysis, and validation for the Twin Ocean Power device tested at the O.H. Hinsdale Wave Research Laboratory, supported by TEAMER funding. This resource includes an overview of power results for a series of 7 trials. The files included in this comprehensive overview include a comprehensive log sheet for each trial, a summary of all trials, and processing scripts for the raw data. It includes all raw data in .tsv and MATLAB compatible formats, an average power chart, angular velocity charts for each trial, trial metrics, and power output files. This resource includes images of the Twin Ocean Power Wave Energy Converter device components and movement during testing and video recordings of each trial.

16 TIDAL AND WAVE POWER↗
DOE OSTI2017

HELIOS vs. DRAGON – Code-to-Code Comparison for High Temperature Gas Reactors

Full core neutronics modeling for depletion and transient analysis in commercial and test reactors requires a lattice physics code to obtain material homogenized and energy group condensed cross- sections at an assembly level. These cross-sections are then used in a full-core model for depletion and transient analysis. HELIOS and DRAGON are two popular lattice physics codes that are capable of modeling the HTGR, which is not straight forward due to the large neutron mean free path in graphite, the presence of burnable poisons, proximity to reflectors, and the double heterogeneous nature of prismatic TRISO fuel. To understand on how HELIOS and DRAGON perform, a simple hexagonal fuel pin cell based on the MHTGR design was analyzed. In total, there are three benchmark cases, with each case increasing in complexity. These cases were selected to help distinguish and identify limitations and benefits of each reactor physics code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Photonic Crystal-Based High-Power Backward Wave Oscillator

An electron beam traversing a slow wave structure can be used to either generate or amplify electromagnetic radiation through the interaction of the slow space charge wave on the beam with the slow wave structure modes. Here, a cylindrical waveguide with a periodic array of conducting loops is used for the slow wave structure. This paper considers operation as a backward wave oscillator. The dispersion properties of the structure are determined using a frequency-domain eigenmode solver. The interaction of the electron beam with the structure modes is investigated using a 2-D particle-in-cell (PIC) code. In conclusion, the operating frequency and growth rate dependence on beam energy and beam current are investigated using the PIC code and compared with analytic and scaling estimates where possible.

42 ENGINEERING↗
DOE OSTI2017

How the Geothermal Community Upped the Game for Computer Codes

The Geothermal Technologies Office Code Comparison Study brought 11 research institutions together to collaborate on coupled thermal, hydrologic, geomechanical, and geochemical numerical simulators. These codes have the potential to help facilitate widespread geothermal energy development.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Distributed Wind Aeroelastic Modeling (dWAM)

Aeroelastic modeling is the primary method for the structural and performance assessment of any wind turbine. Despite the advantages afforded by aeroelastic modeling tools, their use in the distributed wind energy industry is limited. dWAM started from the NREL Aeroelastic Modeling for Distributed Wind Turbines project with Damiani & Davis (2022) researching current needs, including input from an industry workshop. NREL's efforts will focus on OpenFAST code improvements, validation using research turbines at NREL's Flatirons Campus, code-to-code verification activities, and development of guidance documents and improved user manuals. Partner lab, Sandia National Laboratories, will focus their efforts on vertical axis wind turbine (VAWT) modeling including modeling code development, validation, and user-experience improvements.

aeroelastic↗
DOE OSTI2024

Towards exascale for wind energy simulations

We examine large-eddy-simulation modeling approaches and computational performance of two open-source computational fluid dynamics codes for the simulation of atmospheric boundary layer flows that are of direct relevance to wind energy production. The first code, NekRS, is a high-order, unstructured-grid, spectral element code. The second code, AMR-Wind, is a second-order, block-structured, finite-volume code with adaptive mesh refinement capabilities. The objective of this study is to co-develop these codes in order to improve model fidelity and performance for each. These features will be critical for running ABL-based applications such as wind farm analysis on advanced computing architectures. To this end, we investigate the performance of NekRS and AMR-Wind on the Oak Ridge Leadership Facility supercomputers Summit, using 4 to 800 nodes (24 to 4,800 NVIDIA V100 GPUs), and Crusher, the testbed for the Frontier exascale system, using 18 to 384 Graphics Compute Dies on AMD MI250X GPUs. We compare strong- and weak-scaling capabilities, linear solver performance, and time to solution. We also identify leading inhibitors to parallel scaling.

17 WIND ENERGY↗
DOE OSTI2014

Preliminary Verification and Validation of WEC-Sim, an Open-Source Wave Energy Converter Design Tool: Preprint

To promote and support the wave energy industry, a wave energy converter (WEC) design tool, WEC-Sim, is being developed by Sandia National Laboratories and the National Renewable Energy Laboratory. In this paper, the WEC-Sim code is used to model a point absorber WEC designed by the U.S. Department of Energy's reference model project. Preliminary verification was performed by comparing results of the WEC-Sim simulation through a code-to-code comparison, utilizing the commercial codes ANSYS-AQWA, WaveDyn, and OrcaFlex. A preliminary validation of the code was also performed by comparing WEC-Sim simulation results to experimental wave tank tests.

16 TIDAL AND WAVE POWER↗