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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Sensitivity Study of Impact Risk Model Results to Thermal Radiation Damage Model for Large Objects

NASA’s Probabilistic Asteroid Impact Risk (PAIR) assessment model assesses the likelihood of potential damage for asteroid impact scenarios. Fast-running models are used to capture the effects of different hazards. This paper looks specifically at local ground damage hazards, including blast overpressure and thermal radiation damage, for large object impact scenarios. A sensitivity study is conducted to determine which parameters, and over what ranges, cause impact risks to become sensitive to thermal damage. Two additional thermal models with different approaches are used for comparison. The study determined the current thermal model is most sensitive to the luminous efficiency parameter that reflects the model’s uncertainty in the amount of energy contributing to the thermal radiation damage. This sensitivity was most apparent for the highest severity damage levels. Comparisons of the three models showed that in addition to sensitivities within the models, the impact risks are also sensitive to the choice of thermal model. The study results were applied to the 2023 Planetary Defense Conference hypothetical asteroid impact scenario and parameter ranges of interest determined. At the serious damage level, luminous efficiencies above 0.006 showed a small chance of thermal playing an important role, while luminous efficiencies above 0.0008 led to thermal playing a significant role at the unsurvivable damage severity level. Study results are used to identify key areas where additional model refinement and better knowledge of asteroid properties may be important for improving damage estimates.

SMD↗
DOE OSTI2021

Battery Performance, Thermal, and Life Modeling for Southern California Edison (Cooperative Research and Development Final Report)

The objective of this project is to develop battery performance models, thermal models and life models for SCE to use in simulation and analysis of grid services involving energy storage. NREL will fit the models to three separate chemistries using test data provided by SCE. The dataset for each chemistry will include electrical, thermal and aging response to different temperatures and cycling conditions, measured under a variety of cell-level and module-level experiments described in SCE test protocol documents. Once tuned to a test dataset, the battery system model software will provide predictions of battery energy and power loss, and thus cycle and calendar life, for any energy storage grid service power profile of interest to SCE. The automated battery life modeling and simulation tool can also be applied to any other grid battery systems as long as necessary input data is available to accelerate battery model development and battery lifetime analysis.

25 ENERGY STORAGE↗
NASA NTRS1982

Comparison of Orbiter STS-2 development flight instrumentation data with thermal math model predictions

Thermal performance verification of Reusable Surface Insulation (RSI) has been accomplished by comparisons of STS-2 Orbiter Flight Test (OFT) data with Thermal Math Model (TMM) predictions. The OFT data was obtained from Development Flight Instrumentation RSI plug and gap thermocouples. Quartertile RSI TMMs were developed using measured flight data for surface temperature and pressure environments. Reference surface heating rates, derived from surface temperature data, were multiplied by gap heating ratios to obtain tile sidewall heating rates. This TMM analysis resulted in good agreement of predicted temperatures with flight data for thermocouples located in the RSI, Strain Isolation Pad, filler bar and structure.

Norman, I.↗
NASA NTRSDate not supplied

Coupling a Computational Fluid Dynamics Model to a Spacecraft Thermal System Model for the DraMS Instrument Thermal Analysis

The Dragonfly Mass Spectrometer (DraMS) is an instrument on the Dragonfly mission, which will spend 7 years in deep space cruise before landing and operating on the surface of Titan. Vacuum thermal analyses are required for deep space cruise, and convection analyses are required for the Titan surface operations. Model exchanges across multiple thermal teams are needed for all phases of the mission. For DraMS, Thermal Desktop® (TD) has been the main thermal analytical tool of choice due to its capability in modeling complex thermal systems with relatively low computational power and for its availability across thermal teams. However, TD does not have computational fluid dynamics (CFD) capability and struggles to accurately capture complex convective behavior. DraMS has fans operating in tandem and gas flow behaviors are not easily predicted due to its complex flow paths. CFD software, such as Fluent, can model and predict such complex flow behaviors, but CFD models are computationally expensive, and its workflow processes are not tailored towards simulating large and complex systems. Therefore, a coupled modeling approach was chosen for DraMS: A TD model was used for simulating all the conductive, radiative, and source terms, while a Fluent CFD model was added on, as needed, to the TD model to provide the convective boundary conditions using the System Coupling software. The coupling software allows the TD and Fluent models to communicate data and arrive at a co-solved and co-converged solution. Furthermore, Thermal Iso-value Exchange (TIE) method was developed to facilitate and improve the TD-Fluent data exchange process. This paper will discuss the analytical studies that were done to verify the accuracy and usability of the coupled approach and the challenges associated, which lead to the development of the TIE approach. DraMS thermal design and co-solved analysis results will also be discussed.

Heat transfer↗
NASA NTRSDate not supplied

Coupling a Computational Fluid Dynamics (CFD) Model to a Spacecraft Thermal System Model for the DraMS Instrument Thermal Analysis

The Dragonfly Mass Spectrometer (DraMS) is an instrument on the Dragonfly mission, which will spend 7 years in deep space cruise before landing and operating on the surface of Titan. Vacuum thermal analyses are required for deep space cruise, and convection analyses are required for the Titan surface operations. Model exchanges across multiple thermal teams are needed for all phases of the mission. For DraMS, Thermal Desktop (TD) has been the main thermal analytical tool of choice due to its capability in modeling complex thermal systems with relatively low computational power and for its availability across thermal teams. However, TD does not have computational fluid dynamics (CFD) capability and struggles to accurately capture complex convective behavior. DraMS has fans operating in tandem and gas flow behaviors are not easily predicted due to its complex flow paths. CFD software, such as Fluent, can model and predict such complex flow behaviors, but CFD models are computationally expensive, and its workflow processes are not tailored towards simulating large and complex systems. Therefore, a coupled modeling approach was chosen for DraMS: A TD model was used for simulating all the conductive, radiative, and source terms, while a Fluent CFD model was added on, as needed, to the TD model to provide the convective boundary conditions using the System Coupling software. The coupling software allows the TD and Fluent models to communicate data and arrive at a co-solved and co-converged solution. Furthermore, Thermal Iso-value Exchange (TIE) method was developed to facilitate and improve the TD-Fluent data exchange process. This paper will discuss the analytical studies that were done to verify the accuracy and usability of the coupled approach and the challenges associated, which lead to the development of the TIE approach. DraMS thermal design and co-solved analysis results will also be discussed.

heat transfer↗
NASA NTRS2026

Model Correlation and Thermal Analysis of xEMU Boot at Lunar South Pole Temperatures

The National Aeronautics and Space Administration (NASA) Artemis program plans to send astronauts to the lunar south pole, a region of the moon that is colder than previous lunar missions and low earth orbit operations. The spacesuit boots that will be used on these missions will be directly impacted by these extremely cold temperatures (down to ~50 K). To assess the performance of the Exploration Extravehicular Mobility Unit (xEMU) lunar boot in these extreme temperatures, the boot was tested at the Jet Propulsion Lab (JPL) in the Cryogenic Ice Transfer, Acquisition Development, and Excavation Laboratory (CITADEL) thermal vacuum (TVAC) chamber. This data was used to correlate thermal models to predict operational performance of the boots on the lunar south pole. This paper documents the data analysis, thermal boot model correlation, and operational predictions conducted using data from the xEMU TVAC test. Data from the test series was used to determine expected thermal conductances within the boot and between the boot and environment. These conductances were used to correlate a Thermal Desktop model of the xEMU boot across 10 different test points which varied external temperature, internal boot ventilation flowrate, and contact pressure. The correlated model was then used to predict operational performance in the lunar south pole. While the predictions indicate promising evidence for performance of the boots at the 100K test point, there is still substantial uncertainty in performance, particularly at the 48K test point. The results of this test series and model correlation stress the importance of improved testing for characterizing the expected thermal resistance between the outside of the boot and the lunar surface.

xEMU↗
NASA NTRSDate not supplied

Model Correlation and Thermal Analysis of xEMU Boot at Lunar South Pole Temperatures

The National Aeronautics and Space Administration (NASA) Artemis program plans to send astronauts to the lunar south pole, a region of the moon that is colder than previous lunar missions and low earth orbit operations. The spacesuit boots that will be used on these missions will be directly impacted by these extremely cold temperatures (down to ~50 K). To assess the performance of the Exploration Extravehicular Mobility Unit (xEMU) lunar boot in these extreme temperatures, the boot was tested at the Jet Propulsion Lab (JPL) in the Cryogenic Ice Transfer, Acquisition Development, and Excavation Laboratory (CITADEL) thermal vacuum (TVAC) chamber. This data was used to correlate thermal models to predict operational performance of the boots on the lunar south pole. This paper documents the data analysis, thermal boot model correlation, and operational predictions conducted using data from the xEMU TVAC test. Data from the test series was used to determine expected thermal conductances within the boot and between the boot and environment. These conductances were used to correlate a Thermal Desktop model of the xEMU boot across 10 different test points which varied external temperature, internal boot ventilation flowrate, and contact pressure. The correlated model was then used to predict operational performance in the lunar south pole. While the predictions indicate promising evidence for performance of the boots at the 100K test point, there is still substantial uncertainty in performance, particularly at the 48K test point. The results of this test series and model correlation stress the importance of improved testing for characterizing the expected thermal resistance between the outside of the boot and the lunar surface.

thermal analysis↗
NASA NTRS1980

Thermal Pollution Math Model. Volume 1. Thermal Pollution Model Package Verification and Transfer

Two three dimensional, time dependent models, one free surface, the other rigid lid, were verified at Anclote Anchorage and Lake Keowee respectively. The first site is a coastal site in northern Florida; the other is a man-made lake in South Carolina. These models describe the dispersion of heated discharges from power plants under the action of ambient conditions. A one dimensional, horizontally-averaged model was also developed and verified at Lake Keowee. The data base consisted of archival in situ measurements and data collected during field missions. The field missions were conducted during winter and summer conditions at each site. Each mission consisted of four infrared scanner flights with supporting ground truth and in situ measurements. At Anclote, special care was taken to characterize the complete tidal cycle. The three dimensional model results compared with IR data for thermal plumes on an average within 1 C root mean square difference. The one dimensional model performed satisfactorily in simulating the 1971-1979 period.

Lee, S. S.↗
DOE OSTI2024

Rapid subsurface analysis of frequency-domain thermoreflectance images with K-means clustering

K-means clustering analysis is applied to frequency-domain thermoreflectance (FDTR) hyperspectral image data to rapidly screen the spatial distribution of thermophysical properties at material interfaces. Performing FDTR while raster scanning a sample consisting of 8.6 μm of doped-silicon (Si) bonded to a doped-Si substrate identifies spatial variation in the subsurface bond quality. Routine thermal analysis at select pixels quantifies this variation in bond quality and allows assignment of bonded, partially bonded, and unbonded regions. Performing this same routine thermal analysis across the entire map, however, becomes too computationally demanding for rapid screening of bond quality. To address this, K-means clustering was used to reduce the dimensionality of the dataset from more than 20 000 pixel spectra to just K = 3 component spectra. The three component spectra were then used to express every pixel in the image through a least-squares minimized linear combination providing continuous interpolation between the components across spatially varying features, e.g., bonded to unbonded transition regions. Fitting the component spectra to the thermal model, thermal properties for each K cluster are extracted and then distributed according to the weighting established by the regressed linear combination. Thermophysical property maps are then constructed and capture significant variation in bond quality over 25 μm length scales. The use of K-means clustering to achieve these thermal property maps results in a 74-fold speed improvement over explicit fitting of every pixel.

36 MATERIALS SCIENCE↗
DOE OSTI2023

pvlib python: 2023 project update

pvlib python is a community-developed, open-source software toolbox for simulating the performance of solar photovoltaic (PV) energy components and systems. It provides reference implementations of over 100 empirical and physics-based models from the peer-reviewed scientific literature, including solar position algorithms, irradiance models, thermal models, and PV electrical models. In addition to individual low-level model implementations, pvlib python provides high-level workflows that chain these models together like building blocks to form complete “weather-to-power” photovoltaic system models. It also provides functions to fetch and import a wide variety of weather datasets useful for PV modeling. pvlib python has been developed since 2013 and follows modern best practices for open-source python software, with comprehensive automated testing, standards-based packaging, and semantic versioning. Its source code is developed openly on GitHub and releases are distributed via the Python Package Index (PyPI) and the conda-forge repository. pvlib python’s source code is made freely available under the permissive BSD-3 license. Here we (the project’s core developers) present an update on pvlib python, describing capability and community development since our 2018 publication (Holmgren, Hansen, & Mikofski, 2018).

14 SOLAR ENERGY↗
NASA NTRS1987

Geophysical constraints on lunar bulk composition and structure - A reassessment

Theoretical lunar mantle seismic velocity and density profiles were calculated for a series of specific bulk composition models, thermal models, and evolutionary models. It was found that most of the calculated seismic profiles are in qualitative agreement with the Nakamura (1983) observational mantle seismic velocity model. With respect to the density modeling results, the most interesting finding is that none of the considered models yield mantle density increases that are sufficient to match the adapted upper bound on the lunar moment-of-inertia factor (0.3928). The results suggest that the moon possesses a dense metallic core with a mass in the range of 1 to 4 percent of the lunar mass and that the alumina-rich models of Morgan et al. (1978) and Taylor (1982) are best able to match the middle mantle velocity increase that characterizes the Nakamura model.

Hood, L. L.↗
NASA NTRS2001

Validating GOES Instrument Thermal Deformations

Comparison of the Geostationary Operational Environmental Satellite (GOES) instrument thermal model predictions with on-orbit data shows that the models capture the observed temperature and misalignment trends. Lack of precise knowledge as to spacecraft pointing precludes such comparison with instrument pointing predictions. Based on the models, thermally induced instrument attitude variation will dominate GOES N-Q Image Motion Compensation (IMC). Errors due to day-to-day changes in the attitude profiles are predicted to be under 10 microradians except for rapid scans where disturbances may reach 30 microradians.

Harter, Peter↗
NASA NTRS2014

Selection of Thermal Worst-Case Orbits via Modified Efficient Global Optimization

Efficient Global Optimization (EGO) was used to select orbits with worst-case hot and cold thermal environments for the Stratospheric Aerosol and Gas Experiment (SAGE) III. The SAGE III system thermal model changed substantially since the previous selection of worst-case orbits (which did not use the EGO method), so the selections were revised to ensure the worst cases are being captured. The EGO method consists of first conducting an initial set of parametric runs, generated with a space-filling Design of Experiments (DoE) method, then fitting a surrogate model to the data and searching for points of maximum Expected Improvement (EI) to conduct additional runs. The general EGO method was modified by using a multi-start optimizer to identify multiple new test points at each iteration. This modification facilitates parallel computing and decreases the burden of user interaction when the optimizer code is not integrated with the model. Thermal worst-case orbits for SAGE III were successfully identified and shown by direct comparison to be more severe than those identified in the previous selection. The EGO method is a useful tool for this application and can result in computational savings if the initial Design of Experiments (DoE) is selected appropriately.

Moeller, Timothy M.↗
NASA NTRS2017

Mars Propellant Liquefaction and Storage Performance Modeling using Thermal Desktop with an Integrated Cryocooler Model

NASAs current Mars architectures are assuming the production and storage of 23 tons of liquid oxygen on the surface of Mars over a duration of 500+ days. In order to do this in a mass efficient manner, an energy efficient refrigeration system will be required. Based on previous analysis NASA has decided to do all liquefaction in the propulsion vehicle storage tanks. In order to allow for transient Martian environmental effects, a propellant liquefaction and storage system for a Mars Ascent Vehicle (MAV) was modeled using Thermal Desktop. The model consisted of a propellant tank containing a broad area cooling loop heat exchanger integrated with a reverse turbo Brayton cryocooler. Cryocooler sizing and performance modeling was conducted using MAV diurnal heat loads and radiator rejection temperatures predicted from a previous thermal model of the MAV. A system was also sized and modeled using an alternative heat rejection system that relies on a forced convection heat exchanger. Cryocooler mass, input power, and heat rejection for both systems were estimated and compared against sizing based on non-transient sizing estimates.

fluid modeling↗
DOE OSTI2021

Thermal-Hydrological-Mechanical Modelling of Stockton University Reservoir Cooling System, Fine Scale Stress Test Modelling

Mesh, properties, initial conditions, injection/withdrawal rates for modelling thermal, hydrological, and mechanical effects of fluid injection to and withdrawal from ground for Stockton University reservoir cooling system (aquifer storage cooling system), Galloway, New Jersey, for unscheduled two hour injection at 133 % designed capacity, on fine scale grid, with some results. Second simulation of J.T. Smith, E. Sonnenthal, P. Dobson, P. Nico, and M. Worthington, 2021. Thermal-hydrological-mechanical modeling of Stockton University reservoir cooling system, Proceedings of the 46th Workshop on Geothermal Reservoir Engineering, Stanford University, SGP-TR-218, from which Figures 6-9, pertain.

15 GEOTHERMAL ENERGY↗
NASA NTRS2023

Thermal Desktop Modeling of the 2016 CRYOTE-2 Tank Chill and Fill Tests

The storing and transfer of cryogenic propellants is an enabling technology for NASA as it moves to expand future missions into low Earth orbit (LEO) and beyond. The transfer of cryogenic propellants is of particular interest because it has never been successfully demonstrated in microgravity. Several ground tests have been conducted in past decades examining various tank chilldown and fill methods. Creating accurate models using these historical datasets is a vital step toward developing appropriate modeling tools to form pre-test predictions for eventual flight and ground tests of various novel injector concepts. The goal of this work was to create a working model in Thermal Desktop using data from the CRYOTE-2 experiments whose purpose was to demonstrate the chill and fill process in a spherical receiver tank parametrically examining the effect of injection method, receiver tank initial wall temperature and initial state, supply pressure, and mass flow rate on the NVF process. These tests were conducting using liquid nitrogen with different injectors with different injection patterns. The focus of the current work is on one particular spray nozzle. The pressure rise inside the tank, the fill level, and the change in the outside wall temperature were all tracked and compared with test data. The Thermal Desktop model was able to accurately predict each of these metrics for this nozzle within 11.0%, 22.0%, and 7.0%, respectively.

Cryogenic Tank Chilldown↗
DOE OSTI2021

Thermal-Hydrological-Mechanical Modelling of Stockton University Reservoir Cooling System, Large Scale Grid

Mesh, properties, initial conditions, injection/withdrawal rates for modeling thermal, hydrological, and mechanical effects of fluid injection to and withdrawal from ground for Stockton University reservoir cooling system (aquifer storage cooling system), Galloway, New Jersey, on large scale grid, with some results. First simulation of J.T. Smith, E. Sonnenthal, P. Dobson, P. Nico, and M. Worthington, 2021. Thermal-hydrological-mechanical modeling of Stockton University reservoir cooling system, Proceedings of the 46th Workshop on Geothermal Reservoir Engineering, Stanford University, SGP-TR-218, from which Figures 1-5 pertain.

15 GEOTHERMAL ENERGY↗
NASA NTRS1977

Thermal radiation model for solid rocket booster plumes

The Monte Carlo method is used to model the thermal radiation field of the plumes for the dual solid rocket boosters astride the Space Shuttle launch configuration. The model accounts for axial and radial variations in radiative properties of the plumes. The plumes are considered to be composed of a dispersion of aluminum oxide (Al2O3) particles immersed in the gaseous products of combustion. The principal emitting gases are taken to be CO, CO2, H2O, and HCl. The thermal model is based on local thermodynamic equilibrium. Scattering of radiant energy by Al2O3 particles may be treated as isotropic or anisotropic. Sample radiant heating rates to the base region of the Space Shuttle are shown. Space Shuttle geometries are simulated as combinations of quadric surfaces.

Watson, G. H.↗