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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Using the FLUKA Monte Carlo Code to Simulate the Interactions of Ionizing Radiation with Matter to Assist and Aid Our Understanding of Ground Based Accelerator Testing, Space Hardware Design, and Secondary Space Radiation Environments

Designing hardware to operate in the space radiation environment is a very difficult and costly activity. Ground based particle accelerators can be used to test for exposure to the radiation environment, one species at a time, however, the actual space environment cannot be duplicated because of the range of energies and isotropic nature of space radiation. The FLUKA Monte Carlo code is an integrated physics package based at CERN that has been under development for the last 40+ years and includes the most up-to-date fundamental physics theory and particle physics data. This work presents an overview of FLUKA and how it has been used in conjunction with ground based radiation testing for NASA and improve our understanding of secondary particle environments resulting from the interaction of space radiation with matter.

Reddell, Brandon↗
NASA NTRS2004

The Energy Spectra of Heavy Nuclei Measured by the ATIC Experiment

ATIC (Advanced Thin Ionization Calorimeter) is a balloon-borne experiment to measure the spectra and composition of primary cosmic rays in the region of total energy from 100 GeV to near 100 TeV for Z from 1 to 26. ATIC consists of a pixelated silicon matrix detector to measure charge plus a fully active BGO calorimeter, to measure energy, located below a carbon target interleaved with three layers of scintillator hodoscope. The ATIC instrument had a second (scientific) flight from McMurdo, Antarctica from 12/29/02 to 1/18/03, yielding 20 days of good data. The GEANT 3.21 Monte Carlo code with the QGSM event generator and the FLUKA code with the DPMJET-II event generator were used to convert energy deposition measurements to primary energy. We present the preliminary energy spectra for the abundant elements C, O, Ne, Mg, Si and Fe and compare them with the results of the first (test) flight of ATIC in 2000-01 and with results from the HEAO-3 and CRN experiments.

Panov, A. D.↗
DOE OSTI2026

Viscous Gubser flow with conserved charges to benchmark fluid simulations

We present semi-analytical solutions for the evolution of both the temperature and chemical potentials for viscous Gubser flow with conserved charges. Such a solution can be especially useful in testing numerical codes intended to simulate relativistic fluids with large chemical potentials. The freeze-out hypersurface profiles for constant energy density are calculated, along with the corresponding normal vectors, and presented as a new unit test for numerical codes. We also compare the influence of the equation of state on the semi-analytical solutions. We benchmark the newly developed smoothed particle hydrodynamics code ccake that includes both shear viscosity and three conserved charges. Here, the numerical solutions are in excellent agreement with the semi-analytical solution and are also able to accurately reproduce the hypersurface at freeze-out.

Hydrodynamic models↗
NASA NTRS1994

Target compressions by working fluids driven with solid liner implosions

Compression by a spherical solid liner of a gold target surrounded by a hydrogen plasma is simulated. Two-dimensional simulations that treat only a subset of the physics included in the one-dimensional code were performed in an attempt to assess multidimensional effects. A one-dimensional numerical code has been developed to study the effects of thermal radiation and conduction. Results of pressure, density, and energy deposited for different initial plasma conditions are presented and discussed. Results from both one- and two-dimensional codes show that the average target density at peak compression is 39-43 g/cu cm, using the SHIVA Star facility at 90 kV discharge.

Chiang, P.-R.↗
NASA NTRS1987

High temperature transport properties of air

A general computer code was developed to allow calculation of atom-atom and ion-atom transport collision integrals from accurate potential energy curves described by a set of discrete data points for a broad range of scattering conditions. This code is based upon semiclassical approximations that properly account for quantum mechanical behavior such as tunneling effects near a barrier maximum, resonance charge exchange, and nuclear symmetry effects. Transport collision integrals were determined for N-N, O-O, N(+)-N, and O(+)-O interactions from complete sets of accurate potential functions derived from combined experimental and ab initio structure calculations. For the O-O case, this includes results for excited states. The calculated values of the N(+)-N and O(+)-O resonance charge exchange cross section Q(ex) agree well with measurements from beam experiment that are available at high energies where the diffusion cross section Q(d) satisfies Q(d) approximately equal to 2Q(ex).

Levin, E.↗
NASA NTRS1985

Studies on effects of boundary conditions in confined turbulent flow predictions

The differences in k epsilon model predictions of plane and axisymmetric expansion flows is investigated. The prediction of the coaxial jet for different velocity ratios of the annular to central jet is presented. The effects of inlet kinetic energy and the energy dissipation rate profiles are investigated for swirling and nonswirling flows. The effects of expansion ration and Reynolds number on the reattachment length are also presented. The results show that the inlet k and epsilon profiles have the most significant effect on the reattachment length and flow redevelopment for the case of coaxial jet of high velocity ratio. A comparison of k epsilon model predictions for the pipe expansion flow by the PHOENICS and TEACH codes reveals some discrepancies in the predicted results. TEACH prediction seems to produce unrealistic kinetic energy profiles in some regions of the flow. PHOENICS code produces a long tail in the recirculation region under certain conditions.

Nallasamy, M.↗
DOE OSTI2024

Optimization using pathwise algorithmic derivatives of electromagnetic shower simulations

Among the well-known methods to approximate derivatives of expectancies computed by Monte-Carlo simulations, averages of pathwise derivatives are often the easiest one to apply. Computing them via algorithmic differentiation typically does not require major manual analysis and rewriting of the code, even for very complex programs like simulations of particle-detector interactions in high-energy physics. However, the pathwise derivative estimator can be biased if there are discontinuities in the program, which may diminish its value for applications. This work integrates algorithmic differentiation into the electromagnetic shower simulation code HepEmShow based on G4HepEm, allowing us to study how well pathwise derivatives approximate derivatives of energy depositions in a sampling calorimeter with respect to parameters of the beam and geometry. We found that when multiple scattering is disabled in the simulation, means of pathwise derivatives converge quickly to their expected values, and these are close to the actual derivatives of the energy deposition. Additionally, we demonstrate the applicability of this novel gradient estimator for stochastic gradient-based optimization in a model example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Paths Forward: Approaches to Achieve Plug and Process Load Efficiency and Control in Commercial Buildings: Preprint

To accomplish net-zero carbon in the built environment by 2050, we must equitably decarbonize commercial buildings, which includes reducing plug and process loads (PPLs). PPLs are plug-in or hardwired electric and gas loads that are not directly associated with major building end uses like lighting and heating, ventilating, and air conditioning. PPLs account for a growing portion of U.S. commercial building energy consumption. Although commercial building PPL strategies and technologies are available today, they have not been adopted at a level sufficient to achieve significant savings and load flexibility across the building stock. In our "Pathways to Plug and Process Load Efficiency and Control" study, we investigated why these technologies and strategies have not seen widespread adoption and identified five behavior and technology pathways to increase PPL reduction in commercial buildings. In this paper, we expand beyond identifying the pathways and discuss approaches for achieving them. We discuss the importance of collecting and sharing data and case studies on PPL energy consumption and savings from control technology implementation, including code-required measures, for increasing adoption. Centralizing case studies and data, engaging industry organizations, and promoting awareness of PPL efficiency benefits to relevant groups are also key approaches. Additionally, funding, incentives, and rebate programs play important roles in driving PPL efficiency and control adoption. Finally, we discuss integrating PPL efficiency into broader company goals, such as environmental, social and governance (ESG) strategies and green building certifications, to further drive adoption.

adoption pathways↗
DOE OSTI2024

Isotopic Analysis using FRAM [Slides]

FRAM is an isotopic analysis code nominally designed for plutonium and uranium. It stands for Fixed-energy Response-function Analysis with Multiple efficiencies. It has self-calibration using several gamma-ray peaks and can analyze gamma ray data from 30keV to >1MeV of HPGe, CdTe, or LaBr3 detector. The key difference between the MGA family of codes (from LLNL) and FRAM is the use of user-editable analysis parameters in the latter.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2003

Heats of Segregation of BCC Binaries from Ab Initio and Quantum Approximate Calculations

We compare dilute-limit segregation energies for selected BCC transition metal binaries computed using ab initio and quantum approximate energy methods. Ab initio calculations are carried out using the CASTEP plane-wave pseudopotential computer code, while quantum approximate results are computed using the Bozzolo-Ferrante-Smith (BFS) method with the most recent parameters. Quantum approximate segregation energies are computed with and without atomistic relaxation. Results are discussed within the context of segregation models driven by strain and bond-breaking effects. We compare our results with full-potential quantum calculations and with available experimental results.

Good, Brian S.↗
NASA NTRS2003

Surface Segregation Energies of BCC Binaries from Ab Initio and Quantum Approximate Calculations

We compare dilute-limit segregation energies for selected BCC transition metal binaries computed using ab initio and quantum approximate energy method. Ab initio calculations are carried out using the CASTEP plane-wave pseudopotential computer code, while quantum approximate results are computed using the Bozzolo-Ferrante-Smith (BFS) method with the most recent parameterization. Quantum approximate segregation energies are computed with and without atomistic relaxation. The ab initio calculations are performed without relaxation for the most part, but predicted relaxations from quantum approximate calculations are used in selected cases to compute approximate relaxed ab initio segregation energies. Results are discussed within the context of segregation models driven by strain and bond-breaking effects. We compare our results with other quantum approximate and ab initio theoretical work, and available experimental results.

Good, Brian S.↗
DOE OSTI2025

Hourly Electricity Demand Profiles for Each County in the Contiguous United States

This dataset provides estimated hourly electricity demand for each county in the contiguous United States from 2016-2023. The demand profiles represent the sum of two components: (1) Weighted averages of reported hourly demand profiles for North American Electric Reliability Corporation balancing authority (BA) regions and subregions, scaled to match annual estimates of county-level retail sales and direct use of electricity and weighted by the estimated percentage of county load served by each BA region or subregion. (2) Weighted averages of modeled hourly, county- and sector-level distributed photovoltaic (DPV) capacity factor profiles, scaled to match annual estimates of on-site consumption of DPV-generated electricity for each county and weighted by the percentage of consumption attributable to each sector Annual county-level retail sales are estimated by aggregating utility-reported sales to the state level and allocating the results to counties according to each county's share of state population. Annual county-level direct use is calculated by aggregating power plant-reported direct use values. Annual county-level on-site consumption of DPV-generated electricity is estimated by aggregating utility-reported net metering data to determine the amount of DPV-generated electricity sold back to the grid for each state, subtracting those values from modeled state-level DPV generation estimates, and allocating the results to counties according to each county's share of statewide modeled DPV generation. The open-source Python code used to develop this dataset is available at "Historical Load Data Repository" link below.

14 SOLAR ENERGY↗
DOE OSTI2024

SEAS Communication Engine: An Extensible, Flexible Wrapper for Co-Simulation Agents

When modeling and analyzing the power grid and other large scale systems, researchers often express scenarios as optimization problems and feed them into advanced software solvers. In order to allow multiple solvers to communicate with each other and share data from different domains, the National Renewable Energy Laboratory (NREL) and associated Department of Energy (DOE) labs have developed a software framework called the Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS). HELICS allows cosimulation via a collection of client libraries for different languages that can be called from the appropriate optimization software. However, these client libraries do not provide a higher level of abstraction beyond reading and writing data off of the shared HELICS bus. In this paper, we describe a new software library called the SEAS Communication Engine that exposes a higher-level API for running cosimulation problems. The SEAS Engine provides a class-based abstraction on top of the Python HELICS client, in order to allow users to implement their domain-specific cosimulations without needing to interact with core HELICS primitives. This will make adoption of HELICS and cosimulation in general easier, by exposing a simpler API. In the second part of the paper, we validate our library on a collection of different simulation examples, including the canonical IEEE 13 Bus Feeder. Lastly, we demonstrate using the SEAS Engine to directly call domain-specific code written in the Julia programming language. Our hope is that this will serve as a template for easily calling software in different programming languages via the SEAS Engine, thereby avoiding code duplication and complexity.

co-simulation↗
NASA NTRS1987

Calibration and comparison of the NASA Lewis free-piston Stirling engine model predictions with RE-1000 test data

A free-piston Stirling engine performance code is being upgraded and validated at the NASA Lewis Research Center under an interagency agreement between the Department of Energy's Oak Ridge National Laboratory and NASA Lewis. Many modifications were made to the free-piston code in an attempt to decrease the calibration effort. A procedure was developed that made the code calibration process more systematic. Engine-specific calibration parameters are often used to bring predictions and experimental data into better agreement. The code was calibrated to a matrix of six experimental data points. Predictions of the calibrated free-piston code are compared with RE-1000 free-piston Stirling engine sensitivity test data taken at NASA Lewis. Resonable agreement was obtained between the code predictions and the experimental data over a wide range of engine operating conditions.

Geng, Steven M.↗
NASA NTRS1987

Calibration and comparison of the NASA Lewis free-piston Stirling engine model predictions with RE-1000 test data

A free-piston Stirling engine performance code is being upgraded and validated at the NASA Lewis Research Center under an interagency agreement between the Department of Energy's Oak Ridge National Laboratory and NASA Lewis. Many modifications were made to the free-piston code in an attempt to decrease the calibration effort. A procedure was developed that made the code calibration process more systematic. Engine-specific calibration parameters are often used to bring predictions and experimental data into better agreement. The code was calibrated to a matrix of six experimental data points. Predictions of the calibrated free-piston code are compared with RE-1000 free-piston Stirling engine sensitivity test data taken at NASA Lewis. Reasonable agreement was obtained between the code prediction and the experimental data over a wide range of engine operating conditions.

Geng, Steven M.↗
DOE OSTI2024

Adapting CLUTCH methodology to multigroup TSUNAMI-3D for eigenvalue sensitivity calculations

The sensitivity of the eigenvalue to uncertainties in nuclear data and its evaluation are important for nuclear criticality safety. TSUNAMI-3D sequences within the SCALE code system offer several options to the user community for calculating eigenvalue sensitivity coefficients with multigroup (MG) and continuous energy (CE) 3D transport capabilities. TSUNAMI-3D sequences implement the adjoint-based perturbation theory with MG KENO code, the Contributon Linked eigenvalue sensitivity/Uncertainty estimation via Track length importance CHaracterization (CLUTCH) method with CE KENO code, and the Iterated Fission Probability (IFP) method with CE KENO and Shift codes. Each method has benefits and limitations depending on the problem that is run. The work presented here aims to adapt the CLUTCH method, which enables the Contributon method's mesh-free, memory-efficient approach for calculating adjoint-weighted tallies for sensitivity calculations, to the MG TSUNAMI-3D sequence. This application would eliminate the explicit adjoint KENO calculation, as well as the memory-consuming mesh flux moment tallies required by the conventional MG TSUNAMI-3D. Smaller memory footprints in the CLUTCH methodology and relatively shorter runtimes in MG KENO transport can make MG TSUNAMI-3D a viable method for some complex problems. Moreover, this adaptation allows MG sensitivity calculations with Shift, ORNL's next-generation high-performance Monte Carlo transport code, which currently does not offer any sensitivity capabilities with MG particle transport simulations. Initial implementation of the new MG TSUNAMI-3D sequence and its preliminary results with a selected critical benchmark experiment in the Verified, Archived Library of Inputs and Data (VALID) are presented in this study.

KENO↗
DOE OSTI2025

Machine Learning-Driven Optimization of Building Enclosures for Moisture Durability and Thermal Performance

The design of moisture-durable building enclosures with low embodied carbon often involves an iterative process of selecting the materials for the specific exposure conditions to meet the performance requirements. While hygrothermal simulations are commonly used to evaluate moisture durability, they often require advanced expertise for proper implementation. Machine learning (ML) provides a promising alternative by streamlining the design process and minimizing the reliance on complex simulations. This study presents a machine learning-based approach for predicting moisture durability in residential wall assemblies. The ML model was trained to estimate the mold index and maximum moisture content of various layers under typical exposure conditions. The model achieved a high predictive accuracy, with a coefficient of determination (R²) exceeding 0.90 when compared to traditional hygrothermal simulations on materials that were not part of training the ML model. Building on these results, the ML model was developed into a practical tool for optimizing wall assembly designs. This tool allows users to automatically optimize material selections based on energy, moisture, and carbon performance criteria. By incorporating multi-objective optimization, the tool identifies configurations that minimize embodied carbon while maintaining moisture safety and code-compliant thermal performance. Additionally, it provides insights into how material choices influence assembly durability, energy efficiency, and carbon reduction. The tool will be implemented in the Building Science Advisor (BSA) to enhance its performance and provide more granularity on the results. This research highlights the potential for ML-driven tools to simplify the design of high-performance building enclosures, offering architects and engineers a faster, more efficient way to balance critical performance factors.

Salonvaara, Mikael [ORNL] (ORCID:0000000318991554)↗
NASA NTRSDate not supplied

Understanding Solar Energetic Particles With STEREO HET

The project evaluates solar energetic particles (SEPs) in the Heliosphere utilizing in situ data from the STEREO mission. More specifically, raw data from the High Energy Telescope (HET) corresponding to the abundances and energy spectra of electrons, protons, He, and heavier nuclei was extracted. C codes were modified and written to analyze Pulse heights and fluxes in a readable format. Plots of the data were formulated in Python. Low fluxes of heavier elements prompted a revaluation of the onboard binning process. New selection criteria will be generated to orient the particle energy loss in the detectors with the expected locations of the energy tracks corresponding to each element.

Energetic Particles↗