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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 73 records · Page 4

Transfer learning as a method to reproduce high-fidelity non-local thermodynamic equilibrium opacities in simulations

Simulations of high-energy density physics often need non-local thermodynamic equilibrium opacity data. These data, however, are expensive to produce at relatively low fidelity. It is even more so at high fidelity such that the opacity calculations can contribute 95 % of the total computation time. This proportion can even reach large proportions. Neural networks can be used to replace the standard calculations of low-fidelity data, and the neural networks can be trained to reproduce artificial, high-fidelity opacity spectra. In this work, it is demonstrated that a novel neural network architecture trained to reproduce high-fidelity krypton spectra through transfer learning can be used in simulations. Further, it is demonstrated that this can be done while achieving a relative per cent error of the peak radiative temperature of the hohlraum of approximately 1 % to 4 % while achieving a 19.4 $\times$ speed up.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

IM3/HyperFACETS Thermodynamic Global Warming (TGW) Simulation Datasets

Publication For a thorough description of the methods, see the peer-reviewed paper: Jones, A.D., Rastogi, D., Vahmani, P. et al. Continental United States climate projections based on thermodynamic modification of historical weather. Sci Data 10, 664 (2023). https://doi.org/10.1038/s41597-023-02485-5 Overview The IM3 / HyperFACETS climate simulations provide 40-year historical (1980-2019) as well as four 80-year future simulations (2020-2099) over the U.S. The future simulations are split into near (2020-2059) and far future (2060-2099) segments. The future scenarios span a range of plausible changes in future climate (both Global Circulation Model (GCM) and Representative Concentration Pathways/Shared Socioeconomic Pathway (RCP/SSP) dimensions). The simulations provide climate variables with high spatiotemporal resolution (25 hourly variables and 207 3-hourly variables at 12 km2). The datasets are generated using dynamical downscaling with the WRF (Weather Research and Forecasting) model (version 4.2.1) and therefore preserve physical consistency across variables. WRF is a state-of-the-art, fully compressible, non-hydrostatic, mesoscale numerical weather prediction model. WRF is coupled with an urban canopy model (UCM), which resolves urban surfaces. The future scenarios were developed using a thermodynamic global warming approach where past events are replayed under a range of future warming conditions. These scenarios therefore provide a perspective on potential increases in extreme event intensity, geographic scope, and duration, with previously non-extreme conditions potentially crossing new thresholds to be considered extreme by today's standards. This approach is not intended to estimate future changes in extreme event frequency that might result from changes in large-scale atmospheric dynamics. This dataset has NOT been bias corrected. A bias corrected version of selected variables is under development and will be released here when available. Scenarios Files Data for each scenario is provided in weekly NetCDF files. 25 variables are available at hourly resolution, and 207 variables are available at three-hourly resolution. Spatial resolution is 12km and spans the conterminous United States (CONUS), including some areas of Canada and Mexico, resulting in a grid of 424 by 299 cells. The spatial projection is a Lambert Conformal Conic with the following proj-string: "+proj=lcc +lat_0=40.0000076293945 +lon_0=-97 +lat_1=30 +lat_2=45 +x_0=0 +y_0=0 +R=6370000 +units=m +no_defs". The available scenarios and simulation periods are listed below: historical | 1980 - 2019 rcp45cooler | 2020 - 2059 rcp45cooler | 2060 - 2099 rcp45hotter | 2020 - 2059 rcp45hotter | 2060 - 2099 rcp85cooler | 2020 - 2059 rcp85cooler | 2060 - 2099 rcp85hotter | 2020 - 2059 rcp85hotter | 2060 - 2099 * The first year (1979, 2019, and 2059) of data within each scenario represents a model warmup period and should not be used. These are located in the `spinup_files` directory. Historical year 2020 is considered an extra year of data beyond the simulation period and can be found in the `additional_files` directory. For information on specific variables and a more in-depth discussion of methodology, please refer to the data landing page at https://tgw-data.msdlive.org. Delta Warming Files The global and CONUS warming deltas for each scenario are provided in degrees Celsius annually and monthly. Restart Files Yearly restart files are provided for each scenario which can be used to restart the WRF model at a particular point in time. Spinup Files The first year of data within each simulation period represents a model warmup period and should not be used. The files are provided here for the sake of reproducibility. Additional Files Additional years of data are provided as an extension of the historic simulation.

Jones, Andrew D.↗

Calculating adsorption isotherms using the two-phase thermodynamic method and molecular dynamics simulations

We describe the calculation of adsorption isotherms from molecular dynamics simulations based on the two-phase thermodynamic (2PT) model. The 2PT model developed for bulk fluid phases treats the gas-like components as hard spheres (HSs), which correctly recovers the limiting behaviors of unconfined fluids. We showed that this treatment, however, does not always lead to the correct zero-loading behavior in strongly confining systems. For methane adsorption into zeolite MFI, the HS reference state underestimates entropy by up to 20% at low loadings and leads to an order-of-magnitude increase in the adsorption onset pressure. To fix these issues, we propose the use of ideal adsorbed gas (IAG) as the gas reference model, the properties of which can be computed using the Widom insertion method on an empty adsorbent. We further describe three routes to compute adsorption isotherms from the Helmholtz free energy at different loadings. Comparing against established Monte Carlo (MC) methods, we found that the adsorption isotherms obtained using the IAG reference state agrees to within 40%, which corresponds to deviations of <5% in adsorption free energy. The isotherms calculated using the HS reference state underestimate the adsorption uptake at low to medium loadings in strongly confining systems, but its accuracy improves at higher loadings and as the pore size increases relative to the sorbate diameter. The methods described here provide an alternative approach for computing adsorption isotherms when MC simulations in an open ensemble are undesirable and enable a direct comparison of computed adsorption thermodynamics with experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Propulsion System Simulation Using the Toolbox for the Modeling and Analysis of Thermodynamic System T-MATS

A simulation toolbox has been developed for the creation of both steady-state and dynamic thermodynamic software models. This paper describes the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS), which combines generic thermodynamic and controls modeling libraries with a numerical iterative solver to create a framework for the development of thermodynamic system simulations, such as gas turbine engines. The objective of this paper is to present an overview of T-MATS, the theory used in the creation of the module sets, and a possible propulsion simulation architecture. A model comparison was conducted by matching steady-state performance results from a T-MATS developed gas turbine simulation to a well-documented steady-state simulation. Transient modeling capabilities are then demonstrated when the steady-state T-MATS model is updated to run dynamically.

gas path dynamics↗

Propulsion System Simulation Using the Toolbox for the Modeling and Analysis of Thermodynamic System (T-MATS)

A simulation toolbox has been developed for the creation of both steady-state and dynamic thermodynamic software models. This presentation describes the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS), which combines generic thermodynamic and controls modeling libraries with a numerical iterative solver to create a framework for the development of thermodynamic system simulations, such as gas turbine engines. The objective of this presentation is to present an overview of T-MATS, the theory used in the creation of the module sets, and a possible propulsion simulation architecture.

aerothermodynamics↗

Propulsion System Simulation Using the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS)

A simulation toolbox has been developed for the creation of both steady-state and dynamic thermodynamic software models. This paper describes the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS), which combines generic thermodynamic and controls modeling libraries with a numerical iterative solver to create a framework for the development of thermodynamic system simulations, such as gas turbine engines. The objective of this paper is to present an overview of T-MATS, the theory used in the creation of the module sets, and a possible propulsion simulation architecture. A model comparison was conducted by matching steady-state performance results from a T-MATS developed gas turbine simulation to a well-documented steady-state simulation. Transient modeling capabilities are then demonstrated when the steady-state T-MATS model is updated to run dynamically.

aerothermodynamics↗

Thermo4PFM: Facilitating Phase-field simulations of alloys with thermodynamic driving forces

Phase-field modeling is a popular front-tracking approach used to model solidification. Its time-evolution equations are often coupled to alloy composition and/or thermal diffusion in high-resolution multiphysics approaches. Materials thermodynamic properties tabulated in CALPHAD databases can be used for phase-field modeling to parameterize bulk energies of alloys. In addition, they can be naturally integrated into models such as the Kim-Kim-Suzuki (KKS) model where driving forces depend on the differences between chemical potentials of co-existing phases. In that case, a small system of coupled nonlinear equations needs to be solved at every point in space where the phase-field order parameter is to be updated and evolved in time. Here we present Thermo4PFM, a solver for the KKS equations for binary and ternary alloys, with two or three phases, and parameterized with CALPHAD models. Thermo4PFM is open source, written in C++, and can take advantage of Graphics Processing Units (GPU) accelerators. Using OpenMP offload capabilities for C++ classes, an excellent performance is demonstrated on GPU using the LLVM compiler. CALPHAD data is read from simple JSON files using an open source parser from the boost library.

36 MATERIALS SCIENCE↗

Toward an improved nonlocal thermodynamic equilibrium model for more predictive simulations of ignition scale hohlraums

Recently, nonlocal thermodynamic equilibrium (NLTE) modeling has been identified as the primary reason for discrepant predictions of the peak neutron production time in indirectly driven inertial confinement fusion (ICF) platforms. It has also been observed that predictions of collisional excitation rates differ by as much as 50% from measurements. Theoretical uncertainties in dielectronic recombination rates have also been posited as possibly contributing to errors in NLTE predictions. This work examines the impact of multipliers on collisional excitation and dielectronic recombination rates on simulations of a directly driven gold sphere and an indirect drive ICF implosion. It is found that multipliers on the collisional excitation rates have a strong impact on radiant intensity and electron temperature and a weaker impact on ionization state, whereas multipliers on dielectronic recombinations rates strongly impact ionization state with a smaller impact on radiant intensity and electron temperature. A self-consistent NLTE model which places multipliers on differing transitions, as motivated by experimental measurements and more detailed atomic physics predictions, improves agreement but does not completely eliminate discrepancies with measurements of the radiant intensity within the 2–4 keV spectral range.

Farmer, W. A. [Lawrence Livermore National Laborat↗

How Frequent Will the Rarest Daily Rainfall Records of Hurricane Ida’s Remnants Be in the Future?

Abstract Gaining continued insights into the impact of global warming on the occurrence of hurricane-associated intense record downpours is essential for building climate resilient communities. This study investigates projected future changes in extreme rainfall over the Northeast United States, as represented by extreme daily amounts during Hurricane Ida in 2021. We used historical control simulations of Weather Research and Forecasting (WRF) Model generated from 40 years of weather events (1980–2014, 12 km) forced by the fifth generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis. These simulations are thermodynamically modified (2060–2100) via an imposed warming for the high-emission scenario of shared socioeconomic pathway (SSP585) from a range of general circulation models. Ground observations from the Global Historical Climatology Network (1950–2014) and WRF simulations (historical, 1980–2014, and future, 2060–2100) are integrated into a nonstationary generalized extreme value (GEV) framework to assess the frequency of Ida’s heaviest daily rain rates under the SSP585 scenario. Results show that Ida’s daily maximum rainfall recorded at different observation locations was higher than the single highest September daily maximum observed (1950–2014) for 5 out of 17 stations (∼30% of the stations). Ida-like extreme daily rain rates are projected to be, on average, more than 2 times more likely to occur at the end of the century in the simulations (with some regions as high as 5 times). This work demonstrates that integrating a high-resolution atmospheric model’s present-day and thermodynamically modified future simulations along with ground observations, within a nonstationary statistical framework, is crucial for understanding changing characteristics of extreme weather events. Significance Statement Daily scale extreme precipitation is expected to become more frequent and severe, as evidenced by observations and model simulations. While it is important to investigate how these intensifying heavy rainfall events affect current engineering standards, fewer studies have contextualized how warming impacts the most extreme rainfall from a single storm event relative to historical heavy downpours. In this study, we focused on the daily extreme rainfall associated with the extratropical transition of Hurricane Ida (2021), particularly over the northeastern United States—some of which exceeded the commonly used hydrologic design criteria for a 100-yr storm. Using a high-resolution atmospheric model simulation, we investigated how continued warming may influence the frequency of such daily rain rates. Under a high-emission scenario, these events are projected to become up to 5 times more likely at the end of the twenty-first century.

Dollan, Ishrat J↗

Molecular simulation of the structural and thermodynamic properties of n-alkane/brine interfacial systems with nonionic surfactants

All-atom molecular dynamics (MD) simulations are used to study the structural and thermodynamic properties of water + n-heptane interfacial systems in the presence of salinity (NaCl, NaI, KCl, and KI) and two different nonionic surfactants. Excellent qualitative and quantitative agreement with interfacial tension experimental data is obtained, but this requires applying a charge scaling factor to the ionic species, suggesting the likely role of polarizability effects. Tensoactive behavior is observed for the NaI and KI systems, coinciding with layering of the iodide species near the interface. Further, there are significant interaction differences between the surfactants and the different ionic species, but the structural and thermodynamic behavior of the surfactant molecules is relatively unaffected by the specific salt species. Our analysis suggest that the surfactant-surfactant interactions play a critical role in determining the interfacial behavior, with a much smaller impact associated with the composition of the brine phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Thermodynamic modeling of the Ti-Nb-Sn system and its preliminary applications in aging precipitation and solidification simulations

Abstract Gasping the thermodynamic and phase diagram of the materials being studied is essential for further guiding the development process, like composition design, heat treatment optimization and so on. Nb and Sn are common alloying elements in Ti-based biomedical alloys. In this work, the Ti-Nb-Sn system has been thermodynamically assessed based on experimental phase equilibria. A self-consistent thermodynamic description for the Ti-Nb-Sn system including two ternary compounds Ti 3 Nb 3 Sn 2 and Ti 3 NbSn has been obtained. Based on the comparison between the calculated and experimental phase equilibria, the reliability of the presently obtained thermodynamic description has been verified. The influence of Nb and Sn contents on the precipitation temperature and amount of hcp α -Ti phase in bcc β -(Ti, Nb) has been investigated based on thermodynamic calculations. Results show that the increase of Nb or Sn content in Ti-based alloys would significantly reduce the precipitation amount and transformation temperature of hcp α -Ti phase in bcc β -(Ti, Nb) and the influence of Nb content is more effective than that of Sn. The solidified phases in several as-cast alloys have been thermodynamically predicted based on Scheil solidification simulations. The presently developed thermodynamic description of the Ti-Nb-Sn system can serve as a sub-ternary one in the thermodynamic database for multicomponent Ti-based biomedical alloys.

Peng, Yingbiao↗

Radiative Forcing of Nitrate Aerosols From 1975 to 2010 as Simulated by MOSAIC Module in CESM2-MAM4

In this work, we incorporate the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) module in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model Version 6 with interactive chemistry (CAM6-chem), and couple it with the four mode version of the Modal Aerosol Module (MAM4). The MOSAIC module is used to simulate the thermodynamics of the gas-aerosol mass exchange, with a special focus on simulating nitrate aerosol. By comparing against ground and satellite observations, we found that the MOSAIC/MAM4 scheme performs reasonably well in simulating spatiotemporal distributions of aerosols, including nitrate aerosol. We conducted a series of model experiments with and without nitrate aerosols, and examined the radiative effect (RE) associated with nitrate aerosols in 1975, 2000, and 2010, and accessed the radiative forcing (RF) of nitrate aerosols between the present day and pre-industrial periods. Comparing with the nitrate aerosol RE, we predicted relatively small RF of anthropogenic nitrate aerosol from aerosol-radiation interactions (RF ari : -0.014 W m -2 ) and large RF from aerosol-cloud interactions (RF aci : -0.219 W m -2 ). Regional signatures of nitrate RE/RF are noticeable and important: for instance, very small changes in RE ari in Europe and USA, but 2.8–3 times increases in RE ari in India and China from 1975 to 2010, while RE aci /RF aci in China is a warming effect due to the competing effect between sulfate and nitrate aerosols as cloud condensation nuclei.

54 ENVIRONMENTAL SCIENCES↗

Parallel Grand Canonical Monte Carlo (ParaGrandMC) Simulation Code

This report provides an overview of the Parallel Grand Canonical Monte Carlo (ParaGrandMC) simulation code. This is a highly scalable parallel FORTRAN code for simulating the thermodynamic evolution of metal alloy systems at the atomic level, and predicting the thermodynamic state, phase diagram, chemical composition and mechanical properties. The code is designed to simulate multi-component alloy systems, predict solid-state phase transformations such as austenite-martensite transformations, precipitate formation, recrystallization, capillary effects at interfaces, surface absorption, etc., which can aid the design of novel metallic alloys. While the software is mainly tailored for modeling metal alloys, it can also be used for other types of solid-state systems, and to some degree for liquid or gaseous systems, including multiphase systems forming solid-liquid-gas interfaces.

Vesselin I Yamakov↗

Parallel Grand-Canonical Monte Carlo (ParaGrandMC) User’s Manual Version 2.0

This manual describes the commands and command line options for the Parallel Grand Canonical Monte Carlo version 2.0 (ParaGrandMC.2.0) simulation code. This is a highly scalable parallel FORTRAN 2003 code for simulating the thermodynamic evolution of materials at the atomic level, and predicting their thermodynamic state, phase diagram, chemical composition and mechanical properties. The code is specifically designed to simulate multi-component alloy systems, predict solid-state phase transformations such as austenite-martensite transformations, precipitate formation, recrystallization, capillary effects at interfaces, surface absorption, etc., which can aid the design of novel metallic alloys. While the software is mainly tailored for modeling metal alloys, it can also be used for other types of solid-state systems, and to some degree for liquid or gaseous systems, including multiphase systems forming solid-liquid-gas interfaces. In addition to performing Monte Carlo (MC) simulations, the code can also perform Molecular Dynamics (MD) and Langevin Dynamics (LD) simulations, which can be combined and interchanged with MC for faster and more efficient system evolution. A detailed description of the MC part of the code is provided in the NASA ParaGrandMC report: NASA/CR–2016-219202; http://www.sti.nasa.gov.

High performance computing↗

Approach to Integrate Global-Sun Models of Magnetic Flux Emergence and Transport for Space Weather Studies

The Sun lies at the center of space weather and is the source of its variability. The primary input to coronal and solar wind models is the activity of the magnetic field in the solar photosphere. Recent advancements in solar observations and numerical simulations provide a basis for developing physics-based models for the dynamics of the magnetic field from the deep convection zone of the Sun to the corona with the goal of providing robust near real-time boundary conditions at the base of space weather forecast models. The goal is to develop new strategic capabilities that enable characterization and prediction of the magnetic field structure and flow dynamics of the Sun by assimilating data from helioseismology and magnetic field observations into physics-based realistic magnetohydrodynamics (MHD) simulations. The integration of first-principle modeling of solar magnetism and flow dynamics with real-time observational data via advanced data assimilation methods is a new, transformative step in space weather research and prediction. This approach will substantially enhance an existing model of magnetic flux distribution and transport developed by the Air Force Research Lab. The development plan is to use the Space Weather Modeling Framework (SWMF) to develop Coupled Models for Emerging flux Simulations (CMES) that couples three existing models: (1) an MHD formulation with the anelastic approximation to simulate the deep convection zone (FSAM code), (2) an MHD formulation with full compressible Navier-Stokes equations and a detailed description of radiative transfer and thermodynamics to simulate near-surface convection and the photosphere (Stagger code), and (3) an MHD formulation with full, compressible Navier-Stokes equations and an approximate description of radiative transfer and heating to simulate the corona (Module in BATS-R-US). CMES will enable simulations of the emergence of magnetic structures from the deep convection zone to the corona. Finally, a plan will be summarized on the development of a Flux Emergence Prediction Tool (FEPT) in which helioseismology-derived data and vector magnetic maps are assimilated into CMES that couples the dynamics of magnetic flux from the deep interior to the corona.

Mansour, Nagi N.↗

The Impact of Detailed Snow Physics on the Simulation of Snow Cover and Subsurface Thermodynamics at Continental Scales

The three-layer snow model is coupled to the global catchment-based Land Surface Model (LSM) of the NASA Seasonal to Interannual Prediction Project (NSIPP) project, and the combined models are used to simulate the growth and ablation of snow cover over the North American continent for the period 1987-1988. The various snow processes included in the three-layer model, such as snow melting and re-freezing, dynamic changes in snow density, and snow insulating properties, are shown (through a comparison with the corresponding simulation using a much simpler snow model) to lead to an improved simulation of ground thermodynamics on the continental scale.

Stieglitz, Marc↗

KONFIG and REKONFIG: Two interactive preprocessing to the Navy/NASA Engine Program (NNEP)

The NNEP is a computer program that is currently being used to simulate the thermodynamic cycle performance of almost all types of turbine engines by many government, industry, and university personnel. The NNEP uses arrays of input data to set up the engine simulation and component matching method as well as to describe the characteristics of the components. A preprocessing program (KONFIG) is described in which the user at a terminal on a time shared computer can interactively prepare the arrays of data required. It is intended to make it easier for the occasional or new user to operate NNEP. Another preprocessing program (REKONFIG) in which the user can modify the component specifications of a previously configured NNEP dataset is also described. It is intended to aid in preparing data for parametric studies and/or studies of similar engines such a mixed flow turbofans, turboshafts, etc.

Fishbach, L. H.↗

Development of a Twin-Spool Turbofan Engine Simulation Using the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS)

The Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) is a tool that has been developed to allow a user to build custom models of systems governed by thermodynamic principles using a template to model each basic process. Validation of this tool in an engine model application was performed through reconstruction of the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) (v2) using the building blocks from the T-MATS (v1) library. In order to match the two engine models, it was necessary to address differences in several assumptions made in the two modeling approaches. After these modifications were made, validation of the engine model continued by integrating both a steady-state and dynamic iterative solver with the engine plant and comparing results from steady-state and transient simulation of the T-MATS and C-MAPSS models. The results show that the T-MATS engine model was accurate within 3% of the C-MAPSS model, with inaccuracy attributed to the increased dimension of the iterative solver solution space required by the engine model constructed using the T-MATS library. This demonstrates that, given an understanding of the modeling assumptions made in T-MATS and a baseline model, the T-MATS tool provides a viable option for constructing a computational model of a twin-spool turbofan engine that may be used in simulation studies.

numerical simulation↗