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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Precision Thermal Control (PTC) Technology to Enable Thermally Stable Telescopes

The Precision Thermal Control (PTC) project was a multiyear effort initiated in Fiscal Year 2017 to mature the Technology Readiness Level (TRL) of technologies required to enable ultra-thermally stable ultraviolet/ optical/infrared (UVOIR) space telescope primary-mirror (PM) assemblies for ultra-high-contrast observations of exoplanets. PTC had three objectives: (1) validate thermal optical performance models, (2) derive thermal system stability specifications, and (3) demonstrate multi-zonal active thermal control. PTC successfully achieved its objectives and matured active thermal control technology to at least TRL 5. PTC’s key accomplishments are a demonstration of better than 2-mK root-mean-square (rms) stable thermal control of the 1.5-m ultra-low-expansion (ULE®) Advanced Mirror Technology Development-2 (AMTD-2) mirror when exposed to thermal disturbances in a relevant thermal/vacuum environment, and the ability to shape the 1.5-m AMTD-2 mirror to picometer precision.

thermal control↗
NASA NTRS2024

Exploration Extravehicular Mobility Unit (xEMU) Chamber B Thermal Vacuum “Suit 2” Pressure Garment System Test Article Results

NASA’s Exploration Extravehicular Mobility Unit (xEMU) is the government reference next-generation spacesuit design and is engineered to protect astronauts from extreme lunar environmental temperatures. To evaluate the xEMU hardware thermal requirements, the xEMU Testing Team invented, designed, and executed a dual-suit, uncrewed thermal vacuum (TVAC) test at Johnson Space Center’s (JSC) Chamber B. This paper details the test results from the “Suit 2” Pressure Garment System (PGS) test article. The primary objective of the “Suit 2” PGS test article was to evaluate system-level suit heat leak and Environmental Protection Garment (EPG) thermal performance. Eleven unique thermal profiles were tested including both cold and hot environmental cases over the course of five continuous days of testing. The radiative thermal environment was controlled through exposure to liquid-nitrogen shrouds on the chamber walls and a heater cage surrounding the test article. This paper will principally focus on system-level thermal results from the “Suit 2” PGS test article. This paper will examine data collected from one-hundred and seventy thermocouples located in critical locations inside and outside of the suit, as well as seven resistance thermometers (RTDs) for calorimetry to determine total heat flux in and out of the suit. The test data will be compared against the system-level PGS thermal models for model validation. To conclude, this paper will address knowledge gaps presented by unmanned xPGS thermal vacuum testing and the current state of lunar xPGS thermal modeling and testing.

xEMU↗
DOE OSTI2020

Machine Learning in Nuclear Thermal Hydraulics, Part 2: Opportunities and Perspectives

This paper summarizes the issues in nuclear thermal hydraulics (NTH), mainly from the three named aspects, and illustrates potential opportunities of machine learning (ML) applications in dealing with these issues. These issues are problems in simultaneously realizing computational efficiency and accuracy of system thermal hydraulic (STH) modeling and simulation, uncertainty in the scaling analysis for the best-estimate calculations of transient and accident analysis, and difficulties in optimal data production and usage for the development and assessment of evaluation models. Due to ML uncertainty, data insufficiency, and lack of cognition about how to efficiently incorporate knowledge and data, challenges of adapting ML techniques still exist. Accordingly, several perspectives are proposed to provide insights for ML applications in solving these issues.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2014

Ballistic Performance Model of Crater Formation in Monolithic, Porous Thermal Protection Systems

Porous monolithic ablative systems insulate atmospheric reentry vehicles from reentry plasmas generated by atmospheric braking from orbital and exo-orbital velocities. Due to the necessity that these materials create a temperature gradient up to several thousand Kelvin over their thickness, it is important that these materials are near their pristine state prior to reentry. These materials may also be on exposed surfaces to space environment threats like orbital debris and meteoroids leaving a probability that these exposed surfaces will be below their prescribed values. Owing to the typical small size of impact craters in these materials, the local flow fields over these craters and the ablative process afford some margin in thermal protection designs for these locally reduced performance values. In this work, tests to develop ballistic performance models for thermal protection materials typical of those being used on Orion are discussed. A density profile as a function of depth of a typical monolithic ablator and substructure system is shown in Figure 1a.

Miller, J. E.↗
NASA NTRS1974

Transient thermoregulatory model with graphics output

A user's guide is presented for the transient version of the thermoregulatory model. The model is designed to simulate the transient response of the human thermoregulatory system to thermal inputs. The model consists of 41 compartments over which the terms of the heat balance are computed. The control mechanisms which are identified are sweating, vaso-constriction and vasodilation.

Grounds, D. J.↗
DOE OSTI2023

Thermal Modeling of Advanced Test Reactor Fuel in a Generalized Dry Storage System Under Hypothetical Accident Conditions

Work was performed to investigate the thermal behavior of a sealed aluminum-clad spent nuclear fuel (ASNF) dry storage configuration under hypothetical accident conditions during long-term storage. The considered system consists of a concrete dry storage overpack; a welded over canister, backfilled with argon; and nine Department of Energy (DOE) standardized canisters (DOESCs) loaded with ASNF, backfilled with helium gas. One technical concern associated with the long-term storage of ASNF includes radiolytic hydrogen generation. The yield of large quantities of hydrogen could lead to DOESC over pressurization or a flammable internal atmosphere. While flammability concerns can be resolved by preventing the ingress of oxygen, the canister pressure is partially controlled by the atmosphere temperature. This memorandum summarizes the results of modeling and simulation (M&S) work completed with Star CCM+ (a computational fluid dynamics [CFD] software) considering the thermal effects of a fully engulfing flame and another scenario with the vent ports of the concrete dry storage overpack completely blocked. The goal was to determine the bounding maximum temperature of the DOESC internal atmosphere to evaluate a worst-case pressure scenario, as well as the critical vent port blockage durations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRSDate not supplied

Overview of Ablative TPS Modeling at NASA Ames

Over the past decade, NASA has invested in efforts to build predictive thermal protection system (TPS) material models from the micro-scale to the macro-scale. To complement the mission design cycle process and reduce the need for extensive testing, NASA is developing modeling and simulation tools that enable characterizing material properties and response to hot plasma experienced during atmospheric entry. Traditional material response and ablation modeling tools, such as the heritage code FIAT, and its multidimensional siblings, TITAN and 3dFIAT, are being complemented with newly developed software such as Icarus and PATO. Both of these programs are three-dimensional, finite-volume solvers that use unstructured meshes and 21st century programming paradigms to allow for efficient parallel simulations. FIAT and Icarus are also used for TPS sizing purposes. Today, these traditional tools are being supplemented with computational materials models at the atomistic level. The scales of interest range from computational chemistry (Density Functional Theory [DFT]), to atomistic simulations (Molecular Dynamics [MD]), to the microscale with the Porous Microstructure Analysis (PuMA) software that was recently awarded the 2022 NASA Software of the Year award. Finally, thermo-structural modeling is also of interest to the TPS Materials branch and done using commercial tools such as MSC MARC, MENTAT, NASTRAN and PATRAN. The present talk will also link the use of these computational tools to current NASA missions and projects associated with challenging and complex vehicles entries/reentries.

materials modeling↗
DOE OSTI2024

Research Highlight - Dispatch Optimization, System Design and Cost Benefit Analysis of a Nuclear Reactor with Molten Salt Thermal Storage

We highlight our work from our previous publication titled "Dispatch Optimization, System Design, and Cost Benefit Analysis of a Nuclear Reactor with Molten Salt Thermal Storage" published in MDPI Energies 2022 (doi.org/10.3390/en15103599). Variable renewable energy availability has increased the volatility in energy prices in most markets. Nuclear power plants, with a large ratio of capital to variable costs, have historically operated as base load energy suppliers but the need for more flexible operation is increasing. We simulate the techno-economic performance of a 950 MWt nuclear power plant, based on the Westinghouse lead-cooled fast reactor, coupled with molten salt thermal storage as a method for flexible energy dispatch. We use the System Advisor Model to model the nuclear reactor thermal power input and power cycle operating modes. We combine this robust engineering model with a mixed-integer linear program model for optimized dispatch scheduling. We then simulate the coupled nuclear and thermal storage system under different market scenarios with varying price volatility. We find that the coupled plant outperforms the base plant under markets where energy price peaks fluctuate by a factor of two or more about the mean price. We show that a calculated power purchase agreement price for the plant improves by up to 10% when operating under California energy market conditions. Sensitivity analysis on the thermal storage cost shows that the optimal design remains unchanged even when doubling costs.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2016

Multiscale Modeling of Carbon/Phenolic Composite Thermal Protection Materials: Atomistic to Effective Properties

Next generation ablative thermal protection systems are expected to consist of 3D woven composite architectures. It is well known that composites can be tailored to achieve desired mechanical and thermal properties in various directions and thus can be made fit-for-purpose if the proper combination of constituent materials and microstructures can be realized. In the present work, the first, multiscale, atomistically-informed, computational analysis of mechanical and thermal properties of a present day - Carbon/Phenolic composite Thermal Protection System (TPS) material is conducted. Model results are compared to measured in-plane and out-of-plane mechanical and thermal properties to validate the computational approach. Results indicate that given sufficient microstructural fidelity, along with lowerscale, constituent properties derived from molecular dynamics simulations, accurate composite level (effective) thermo-elastic properties can be obtained. This suggests that next generation TPS properties can be accurately estimated via atomistically informed multiscale analysis.

Materials Science↗
DOE OSTI2026

Dynamic modeling of heat pipe integrated thermal battery latent heat storage system experiment validation

A heat pipe integrated thermal battery system has been constructed to investigate a high-temperature latent heat thermal energy storage technology that takes advantage of near isothermal operation of latent heat storage and heat pipes to potentially enable high-energy isothermal heat storage. A dynamic model constructed in Modelica has been validated, showing errors between 2.5 °C–39.7 °C across 10-h to 47-h simulations against experiment results, showing good prediction capability of experiment output, especially against phase change time. Model calibrations showing vessel heat-up capability of 3 kW and heat pipes combining to provide 600 W each during experiment operation validate experiment circumstances including reduced material loading and reduced power capability. The experiment configuration uses an Al-Mg-Zn eutectic metal as the storage material, heated via heat tape wrapped around the vessel and guide tubes to bring the system to operation range (>400 °C) and to simulate charging heat exchange, respectively, with heat rejection occurring through the surfaces of the material and facilitated via guide tubes with less insulation wrapping. The model is available in the open-source repository HYBRID on Github.

25 - ENERGY STORAGE↗
NASA NTRS1992

Composite flexible insulation for thermal protection of space vehicles

A composite flexible blanket insulation (CFBI) system considered for use as a thermal protection system for space vehicles is described. This flexible composite insulation system consists of an outer layer of silicon carbide fabric, followed by alumina mat insulation, and alternating layers of aluminized polyimide film and aluminoborosilicate scrim fabric. A potential application of this composite insulation would be as a thermal protection system for the aerobrake of the Aeroassist Space Transfer Vehicle (ASTV). It would also apply to other space vehicles subject to high convective and radiative heating during atmospheric entry. The thermal performance of this composite insulation as exposed to a simulated atmospheric entry environment in a plasma arc test facility is described. Other thermophysical properties which affect the thermal response of this system are also described. Analytical modeling describing the thermal performance of this composite insulation is included. It shows that this composite insulation is effective as a thermal protection system at total heating rates up to 30.6 W/sq cm.

Kourtides, Demetrius A.↗
DOE OSTI2021

Forecasting Solar-Thermal Systems Performance under Transient Operation Using a Data-Driven Machine Learning Approach Based on the Deep Operator Network Architecture

Modeling and prediction of the dynamic behavior of thermal systems operating under intermittent energy input and variable load requirements represent one of the greatest challenges in the development of efficient and reliable renewable-based power generation technologies. In this work, a data-driven machine learning modeling framework was developed based on a modified version of the Deep Operator Network architecture where the time coordinate in the trunk net is replaced with historical data of the predicting quantity. The modeling framework can be used to accurately predict the performance of renewable-based energy conversion technologies including wind- and solar-based power plants. This novel framework was applied on a solar-thermal system that consists of a solar collection loop using a flat plate collector, a power generation loop comprising an Organic Rankine Cycle, and a thermal energy storage tank connecting both loops. Variable solar irradiance, air temperature, and power load profiles were used by the Deep Operator Network to predict the State-of-Charge and the efficiency of the thermal system for several days. The results were compared with the State-of-Charge and efficiency functions calculated using a physics-based model. For a simple operation scenario, characterized by a clear sky solar irradiance profile and constant load, the standard deviation in the State-of-Charge prediction by Deep Operator Network is below 0.9% during a seven-day prediction time horizon. For the most realistic operation scenario that considers real solar irradiance and a rough load profile, the maximum standard deviation in the predictions for the State-of-Charge and efficiency are below 6.8% and 2.5%, respectively. A comparison between Deep Operator Network and Long Short Term Memory network was also performed. In general, both networks predict very well the State-of-Charge for different data density conditions; however, a higher accuracy, with a standard deviation below 2.0%, is obtained by the Deep Operator Network during three and half days using sparser training data of 20-minute points. The same accuracy for the State-of-Charge prediction with the Long Short Term Memory network is achieved only for 14 h. Average standard deviations for the State-of-Charge prediction of 1.1% with the Deep Operator Network and 1.5% with the Long Short Term Memory network are obtained for a four-day prediction time using a denser training data of 5-minute points.

DeepONet↗
NASA NTRS2010

General Pressurization Model in Simscape

System integration is an essential part of the engineering design process. The Ares I Upper Stage (US) is a complex system which is made up of thousands of components assembled into subsystems including a J2-X engine, liquid hydrogen (LH2) and liquid oxygen (LO2) tanks, avionics, thrust vector control, motors, etc. System integration is the task of connecting together all of the subsystems into one large system. To ensure that all the components will "fit together" as well as safety and, quality, integration analysis is required. Integration analysis verifies that, as an integrated system, the system will behave as designed. Models that represent the actual subsystems are built for more comprehensive analysis. Matlab has been an instrument widely use by engineers to construct mathematical models of systems. Simulink, one of the tools offered by Matlab, provides multi-domain graphical environment to simulate and design time-varying systems. Simulink is a powerful tool to analyze the dynamic behavior of systems over time. Furthermore, Simscape, a tool provided by Simulink, allows users to model physical (such as mechanical, thermal and hydraulic) systems using physical networks. Using Simscape, a model representing an inflow of gas to a pressurized tank was created where the temperature and pressure of the tank are measured over time to show the behavior of the gas. By further incorporation of Simscape into model building, the full potential of this software can be discovered and it hopefully can become a more utilized tool.

Servin, Mario↗
NASA NTRS1977

Aluminum-26 as a planetoid heat source in the early solar system

The results of thermal model calculations which assume Al-26 as a heat source are presented. The relation between Al-26 content, the maximum central temperature obtained, and the time interval after formation until central cooling commences is elucidated. Because of the heating times required, these results constrain maximum permissible planetoid dimensions more severely than do previous calculations which assume a high initial temperature.

Herndon, J. M.↗
NASA NTRS1998

Radiation Heat Transfer Modeling Improved for Phase-Change, Thermal Energy Storage Systems

Spacecraft solar dynamic power systems typically use high-temperature phase-change materials to efficiently store thermal energy for heat engine operation in orbital eclipse periods. Lithium fluoride salts are particularly well suited for this application because of their high heat of fusion, long-term stability, and appropriate melting point. Considerable attention has been focused on the development of thermal energy storage (TES) canisters that employ either pure lithium fluoride (LiF), with a melting point of 1121 K, or eutectic composition lithium-fluoride/calcium-difluoride (LiF-20CaF2), with a 1040 K melting point, as the phase-change material. Primary goals of TES canister development include maximizing the phase-change material melt fraction, minimizing the canister mass per unit of energy storage, and maximizing the phase-change material thermal charge/discharge rates within the limits posed by the container structure.

Kerslake, Thomas W.↗
DOE OSTI2023

Performance Evaluation and Optimal Design Analysis of Continuous-Operation Solar-Driven Cooling Absorption Systems With Thermal Energy Storage

A solar absorption cooling system consisting of a flat plate collector, thermal energy storage tank, and absorption chiller is analyzed in this work. A dimensionless model is developed from the energy balance on each component and the chiller's characteristic performance curves. The model is used to determine the interaction and influence of different parameters such as tank size, solar collector area, chiller size, cooling load, cooling temperature, heat loss, and mass flow rates on the performance. From the analysis, smaller solar collector areas are required for lower cooling loads and smaller tank volumes. A specific cooling load of 1 x 10^-5 will require a specific solar collector area between two and six times larger, depending on the initial tank temperature, than the area required for a baseline system that considers typical commercial design and operation parameters. A similar behavior was observed for the specific tank volume. For the baseline system, the minimum specific area of the collector of 9.57 is achieved for an initial tank temperature of 1.19. For a cooling load of 1 x 10^-5, the optimum initial tank temperature will be 1.11 that results in a minimum specific solar collector area of 25.26. A specific tank volume of 4 x 10^-4 will also have an optimum initial tank temperature of 1.11 that minimizes the specific solar collector area to a value of 28.18. The approach and analysis in this work can be used to determine design parameters for solar absorption cooling systems based on a proper relation among system's dimensions to achieve optimum operation.

cooling load↗
NASA NTRS1986

A spacecraft cooling system for a charged coupled device

This paper describes the thermal analysis, design, and testing of a dedicated cooling system for a Spartan spacecraft payload. A simple reliable design that requires minimum power consumption and minimum weight was developed. The payload has a CCD detector that must be maintained at a temperature of approximately -40 C or colder. The cooling system consists of a fin radiator, dual redundant heat pipes, and a thermal electric device (TED). The system was analytically modeled through the use of the Simplified Shuttle Payload Thermal Analyzer (SSPTA) computer program. A thermal test of the system simulating flight conditions was conducted to correlate the computer model and verify performance specifications.

Walker, Mary S.↗