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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Microcalorimeter Absorber Optimization for 0.2 to 12 keV X-Rays

The Advanced Telescope for High ENergy Astrophysics (ATHENA) mission requires high quantum efficiency (QE) x-ray absorption, >90.6% at 7 keV and low specific heat capacity, 0.731 pJ/K. The designed ATHENA x-ray absorbers are cantilevered square tiles (pitch of 317 microns) of 1.05 μm thick Au and 5.51 μm thick Bi electroplated films supported by stems that connect the absorber to the detector below. We discuss some of the methods used to produce x-ray absorbers meeting these specifications for ATHENA. To tune the thermal conductance of the device and the effect on the normal-to superconducting transition shape, the stems need to be small diameter and can have a weak bottle-neck connection to the substrate. A funnel shape of the stem using a proximity exposed photoresist mold has been developed to improve the strength of the connections. Further requirements on the absorbers include low levels of fine particulate remaining on the substrate after production and zero shorts between absorbers due to incomplete ion milling or trapped fine particular between absorbers. To optimize for post patterning substrate cleanliness and absorber yield, we have examined several methods of absorber fabrication. Three such methods are 1) an ion mill/wet etch combination, 2) a photoresist mold for electroplating followed by wet or dry etch to remove the seed layer, and 3) an electroplating process with leveling to smooth the surface followed by ion mill to separate the absorbers. The different combinations of wet and dry etches lead to different yields and surface appearance of the absorber sidewalls. We present results on the achieved pixel yields and the energy resolution of pixels made with the various fabrication methods. We discuss the impact of absorber patterning method on performance, uniformity, and yield.

Edward J Wassell↗
NASA NTRSDate not supplied

Design of A Transition-Edge-Sensor-Based Thermal Stabilization Stage

Electrothermal feedback in a transition edge sensor suppresses thermal fluctuations in the TES and regions in close thermal contact. We designed a heavily-metallized, leg-isolated membrane with a TES which serves as a thermal stabilization stage that can be lithographically integrated with other devices. Through modeling, fabrication and test of prototype devices, we examine whether the noise reduction in this stage can reduce thermal fluctuations (e.g. 1/f noise) in the other components by providing a more stable base temperature. In one implementation, a leg-isolated TES bolometer of higher superconducting transition temperature (Tc) is encircled by a second membrane region which is metallized and thermally stabilized by a second, lower-Tc TES. We present fabrication results on the dual-Tc design and testing of the simultaneous biasing of a two-stage, two-TES device. We explore varied heat capacity of the thermally stabilized stage in the single pixel design. We also present other designs to evaluate the use of an outer thermal stabilization stage for multiple pixel arrangements.

Rachel Borrelli↗
NASA NTRS2017

Physical Properties of the Stone Meteorites: Implications for the Properties of Their Parent Bodies

The physical properties of the stone meteorites provide important clues to understanding the formation and physical evolution of material in the Solar protoplanetary disk as well providing indications of the properties of their asteroidal parent bodies. Knowledge of these properties is essential for modeling a number of Solar System processes, such as bolides in planetary atmospheres, the thermal inertia of atmosphereless solid body surfaces, and the internal physical and thermal evolution of asteroids and rock-rich icy bodies. In addition, insight into the physical properties of the asteroids is important for the design of robotic and crewed reconnaissance, lander, and sample return spacecraft missions to the asteroids. One key property is meteorite porosity, which ranges from 0% to more than 40%, similar to the range of porosities seen in asteroids. Porosity affects many of the other physical properties including thermal conductivity, speed of sound, deformation under stress, strength, and response to impact. As a result of the porosity, the properties of most stone meteorites differ significantly from those of compact terrestrial rocks, whose physical properties have been used in many models of asteroid behavior. A few physical properties, such as grain density, magnetic susceptibility, and heat capacity are not functions of porosity. Taken together, the grain density and the magnetic susceptibility can be used to classify unweathered or minimally weathered ordinary chondrites. This provides a rapid screening technique to identify heterogeneous samples, classify new samples, and identify misclassified meteorites or interlopers in strewn fields.

Chondritic meteorites↗
NASA NTRS2023

Toward Accurate Thermal Modeling of Phase Change Material Based Photonic Devices

Reconfigurable or programmable photonic devices are rapidly growing and have become an integral part of many optical systems. The ability to selectively modulate electromagnetic waves through electrical stimuli is crucial in the advancement of a variety of applications from data communication and computing devices to environmental science and space explorations. Chalcogenide-based phase change materials (PCMs) are one of the most promising material candidates for reconfigurable photonics due to their large optical contrast between their different solid-state structural phases. Although significant efforts have been devoted to accurate simulation of PCM-based devices, in this paper, we highlight three important aspects which have often evaded prior models yet having significant impacts on the thermal and phase transition behavior of these devices: the enthalpy of fusion, the heat capacity change upon glass transition, as well as the thermal conductivity of liquid-phase PCMs. We further investigated the important topic of switching energy scaling in PCM devices, which also helps explain why the three above-mentioned effects have long been overlooked in electronic PCM memories but only become important in photonics. Our findings offer insight to facilitate accurate modeling of PCM-based photonic devices and can inform the development of more efficient reconfigurable optics.

Phase change materials↗
NASA NTRS2023

PMT F7 Silver Standard Material Properties Characterization

PMT F7 epoxy resin was characterized to capture the material's thermochemical and thermo-mechanical properties. DSC testing was performed and the data was used to develop a cure kinetics model which predicts the material cure response and specific heat capacity. TMA and DMA testing were performed and the data was used to develop thermo-mechanical models which predict the material CTE, cure shrinkage, and modulus evolution with cure. Convergent Manufacturing Technologies US determined test parameters, analyzed data, and performed model fitting. NASA completed tests and provided data to Convergent Manufacturing Technologies US.

Epoxy↗
NASA NTRS2023

Asymmetry in the Seasonal Cycle of Zonal-Mean Surface Air Temperature

At most latitudes, the seasonal cycle of zonal-mean surface air temperature is notably asymmetric: the length of the warming season is not equal to the length of the cooling season. The asymmetry varies spatially, with the cooling season being ∼40 days shorter than the warming season in the subtropics and the warming season being ∼100 days shorter than the cooling season at the poles. Furthermore, the asymmetry differs between the Northern Hemisphere and the Southern Hemisphere. Here, we show that these observed features are broadly captured in a simple model for the evolution of temperature forced by realistic insolation. The model suggests that Earth's orbital eccentricity largely determines the hemispheric contrast, and obliquity broadly dictates the meridional structure. Clouds, atmospheric heat flux convergence, and time-invariant effective surface heat capacity have minimal impacts on seasonal asymmetry. This simple, first-order picture has been absent from previous discussions of the surface temperature seasonal cycle.

seasonal cycle↗
NASA NTRSDate not supplied

Machine Learning Approaches for Rare-Earth Silicate Environmental Barrier Coating Thermochemical and Thermomechanical Property Predictions

Environmental barrier coatings (EBCs) are a necessary enabling technology for the transition from superalloys to silicon carbide (SiC) ceramic matrix composites (CMCs) in gas turbine engines for increased efficiency and decreased fuel costs. SiC-based CMCs are prone to oxidation-based degradation in the engine hot section, and rare-earth (RE) silicates are promising candidates for EBCs due to their close thermal expansion match to the composite substrate and oxidation resistance. However, the design of EBCs is hindered by the large chemical space of candidate materials and the difficulty in obtaining material properties for engineering optimization. This is especially difficult as research continues into mixed-cation or “high-entropy” RE silicates. First-principles computational methods such as density functional theory (DFT) are highly effective at calculating material properties to guide coating design but are limited by their computational cost. Atomistic simulations have the potential to both accelerate property calculations and expand the properties able to be calculated due to their lower computational compared to DFT. However, they require interatomic potentials (IAPs) specific to the material system of interest, and, to our knowledge, there are no suitable IAPs for RE silicates. Machine learning (ML) is a promising technique to accelerate material property predictions indirectly by generating IAPs for atomistic simulations or via direct prediction. In this work, we present two ML approaches to accelerate the calculation of RE silicate properties relevant to EBC design: 1) a ML-derived interatomic potential (IAP) for atomistic simulations of yttrium disilicate (Y2Si2O7) from DFT training data, and 2) a neural network (NN) model to directly predict thermochemical properties of RE silicates and oxides directly from easily obtainable unit cell parameters. Classical MD simulations using the IAP yield lattice properties and bond lengths in good agreement with both DFT and experimental results from x-ray diffraction. Thermodynamic properties calculated using the finite-displacement phonon method and quasi-harmonic approximation were orders of magnitude faster than DFT with good agreement to the DFT results. The IAP was also used to calculate properties such as coefficient of thermal expansion (CTE) that require large simulation supercells and are therefore difficult with DFT. The IAP correctly predicted the anisotropic nature of the CTE in three different phases of Y2Si2O7. The NN model predicts constant pressure heat capacity, Cp, orders of magnitude faster than DFT calculations, which can enable its use as a surrogate model for multiscale simulations. The two methods presented in this work demonstrate the utility of ML for accelerating the prediction of RE silicate properties, which can in turn accelerate EBC design and optimization.

machine learning↗
NASA NTRSDate not supplied

Enabling Mission Flexibility to Battery Driven Deep Space Endeavors With Generalized Battery-Health-Monitoring Using Physics-Based and Data-Driven Reduced-Order Models

The needs and requirements for an electrochemical energy storage for deep space exploration is well explored. It is often understood that different mission sites and environmental conditions require different battery chemistries or technologies. Additionally, various engineering solutions are deployed to overcome specific chemical challenges. One often overlooked need is the “health” monitoring of an electrochemical storage system. The term generalized health monitoring, as envisioned in this work, refers to the monitoring of various aspects such as electrode health, electrolyte health, reaction pathway health, cooling system health, sensor health, and BMS health [1]. Generalized health monitoring allows mission leads, engineers, and scientists to incorporate flexibility in mission designs, make on-the-fly mission changes, and extend the duration of science missions. Moreover, it enables automation and data-driven decision-making without compromising safety and performance. Recently, our group developed a hierarchy of thermal reduced-order models (TROM) by combining a physics-based modeling approach and data-driven model reduction techniques applied to flight data [2]. The resulting TROMs were found to be not only accurate but also identifiable from the flight data. Consequently, the coefficient of variance of the model parameters is small over the course of hundreds of flights, allowing for monitoring the parameter evolution trajectories as the battery ages and degrades. These parameters constitute the metrics of the generalized health of a battery. Monitoring their evolution allows such models to be used for anomaly detection and prognostics, improving early detection of abnormal behavior and thus enabling timely maintenance, longer battery life, and enhanced battery safety. For this presentation, the practicality of the thermal model will be validated on a pack of 14cells under various topology configurations such as 1S14P, 2P7S, 7S2P, and 1P14S. It is well known that manufacturing and non-uniform aging lead to variability in the performance of a cell, which is exacerbated by cell balancing during active load. Additionally, in extreme scenarios, the paramount objective is to complete the mission, regardless of the stresses on the battery. Topology-induced balancing issues further stress the battery. The goal of this study is to determine if the noise (identifiability) in the reduced-order thermal model parameters is sensitive to topology, cell spacing, cooling strategy, and manufacturing or age variability. The variability in cells is considered by assuming a multimodal distribution for microscopic parameters of a cell (such as porosity, tortuosity, reaction kinetics, volumetric thermal conductivity, and volumetric heat capacity). The compounded effect of manufacturing variability, topological selection, cooling strategies, and cell balancing ages each cell in a battery differently. The study aims to clarify whether the challenge in extracting maximum information depends on the minimum number of sensors or models used for data extraction.

Automation↗
NASA NTRS2026

Optimization of X-ray Absorbers for High-Resolution TES Detectors in NewATHENA X-IFU

NewATHENA’s X-ray Integral Field Unit (X-IFU) uses a large-format array of Transition Edge Sensor (TES) microcalorimeters coupled with absorbers made of gold and bismuth providing 4 eV FWHM resolution up to 7 keV in the 0.2- 12 keV band. X-ray absorbers must be thick enough for photon absorption, maintain low heat capacity for energy resolution, and have good thermalization properties. The X-IFU requires total Quantum Efficiency (QE) of 96%, 87%, and 63% at 1, 7, and 9.5 keV, respectively. Optimal thicknesses are 1.05 µm gold and 5.5 µm bismuth to achieve 0.731 pJ/K at 90 mK and 87% QE at 7 keV. While typical TES absorbers are 3-4 µm thick, producing the required 5.5 µm Bi absorbers via standard electroplating creates enlarged grains and surface roughness. The increased roughness and grain size variability produced with our standard recipe have resulted in instances of 1) low energy spectral tails 2) spectral broadening of the energy resolution and 3) thermal shorts between pixels when a large grain bridges the gap between absorbers. In this study, we have introduced a new fabrication process and altered the morphology of the thick Bi through changes in the electroplating process. The process changes are intended to address all three issues as well as reduce particulate contamination observed on the finished detector arrays.

Absorber↗
DOE OSTI2020

Dynamic Modelling and Performance Evaluation of a Chemisorption Heat Pump for Cold Climate

Space heating is a significant contributor to the energy consumption in residential buildings, especially in cold climates where electric-driven heat pumps lose the advantage of high efficiency and conventional gas-combustion furnaces have limited efficiency. Chemical adsorption (chemisorption) heat pumps (CSHP) have the potential for producing heating with high energy efficiency under cold operating conditions. A CSHP operates intermittently between desorption and adsorption modes, and their performance is affected by system design and transient system control. This study developed a dynamic model and used it to evaluate the daily system performance under different designs and controls, particularly the buffer tank size and the controlled minimum heating power. The simulation results revealed the effects of these parameters on the system performance and helped identify the optimal design and control for the highest coefficient of performance and heating capacity.

Yang, Zhiyao↗
DOE OSTI2021

Sorption heat pump and control method

A method operates an absorption heat pump system, specifically the flow of hydronic cooling fluid through the condenser during system start-ups, or when the cooling fluid temperature is low. To minimize the time for an absorption heat pump to reach full cooling or heating capacity, it is desirable for the high side pressure to increase as fast as possible, and the low side pressure to decrease as fast as possible. Since the high side pressure is a function of the temperature of the refrigerant exiting the condenser, if the condenser cooling fluid temperature is low, the corresponding high side pressure will be low, which may not permit adequate working fluid flow rates from the high pressure side of the system to the low pressure side.

Garrabrant, Michael A.↗
DOE OSTI2021

RELAP5-3D Simulation of PG-27 Test at the HTTF Facility

The High Temperature Test Facility (HTTF) at Oregon State University (OSU) is a quarter scaled integral-effect test facility designed to examine the transient phenomena occurring in a Modular Hight Temperature Gas-cooled Reactor (MHTGR). It is specifically designed to handle the pressurized and depressurized conduction cooldown (PCC and DCC) events. The PCC event is an accident scenario in which there is a loss of forced convection of the coolant through the system. However, the pressure boundary remains intact. This study focuses on the Reactor Excursions and Leak Analysis Program (RELAP)5-3D simulation of the PG-27 test (PCC phenomena) and the sensitivity of those simulations from the material properties and primary helium mass flow rate standpoint. The aim is to capture a reasonable one-dimensional picture of a three dimensional phenomena. The simulation will help in the code assessment and in understanding the various unknown parameters involved. The presented results will demonstrate the code is able to capture the detailed one-dimensional physics accurately. However, input parameters to the code (i.e., the primary mass flow rate, refractory material thermal conductivity, and heat capacity at elevated temperatures) impact the fuel temperature the most. This work will discuss the sensitivity of simulations to the identified input parameters.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

DFT Calculation of Thermal Expansion within Debye-Grüneisen Framework Made Simple and Accurate

The density functional theory (DFT) based Debye-Grüneisen approach is a computational method used to calculate the thermodynamic properties of materials by relating the volume dependence of the Debye frequency to the Grüneisen parameter. In this study, we propose a new model to describe the volume dependence of the Grüneisen parameter. This model offers a simple yet accurate approach to predict the thermal expansion of materials within the framework of the Debye-Grüneisen theory. Specifically, for pure elements or species used as a reference system, we calibrated the parameters to reproduce the experimental coefficient of thermal expansion, heat capacity, and entropy. For compounds with arbitrary compositions, the parameters are determined by taking the arithmetic or geometric average of those obtained from the pure elements or species based on their composition. We then compared the model prediction with experiments. This allowed for a comprehensive characterization of the thermal expansion behavior of various materials.

Wang, Yi↗
DOE OSTI2024

Evaluation of Thermal Scattering Law for U 3 Si 2 Using Temperature-Dependent Phonon Density of States

The thermal scattering law for uranium silicide, a candidate material for high-density nuclear fuel, was evaluated from the temperature-dependent phonon density of states obtained using the quasi-harmonic approximation. For uranium silicide model systems of various volumes near the equilibrium volume, Hellmann-Feynman forces were calculated by performing ab initio lattice dynamics simulations based on density functional theory. Subsequently, the quasi-harmonic approximation was applied by interpolating the results of the harmonic approximation for each volume system. As a sensitivity test, the phonon density of states was calculated for the structures with temperature-dependent volumes at 298 K and 1000 K, obtained by the quasi-harmonic approximation, and the corresponding thermal neutron scattering cross section was evaluated. The temperature-dependent volume and heat capacity of uranium silicide obtained by the quasi-harmonic approximation showed reasonable agreement with experimental data while lattice thermal expansion showed deviation from experimental observations. Thermal scattering cross sections evaluated from 0 K and temperature-dependent phonon density of states exhibited differences of up to 4.1% at 1000 K. This study examines the impact of temperature on the thermal scattering law, employing ab initio lattice dynamics simulations through the quasi-harmonic approximation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Morphological-informed Thermal Property Prediction in the Engineering Domain

Using first-principle, atomic scale methods to predict thermal carrier (electron and phonon) behavior at nanoscale yields highly resolved thermal properties. Density functional theory simulations can model myriad effects on the transport of phonons and electrons (e.g., phonon and electron coupling, electron correlation, defect presence, carrier scattering), and yield thermal properties for small geometric domains such as thermal and electrical conductivity, or heat capacity. While these thermal properties are accurate in atomistic and nanoscopic systems, they must be scaled up to the microstructural domain to be a useful predictor for experimental basis, as the microscale is where myriad changes and physical phenomenon occur within a material (e.g., grain boundaries, precipitate aggregations, interfaces, defect clusters). My talk will discuss the necessity of thermal property predictions for nuclear fuels applications and more. Additionally I will discuss the necessity in developing multi-physics, multi-scale methods for future applications in predictions for not only nuclear fuels, but other materials applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

INL Poster - Juan Barrera Salazar

Generation IV nuclear reactors introduce several advantages and benefits in terms of safety and efficiency when compared with their predecessors from previous generation. This is due, among many things, to the use of innovative forms of fuel and coolant, different from the conventional ones used in the last decades. Given that these upcoming designs utilize emerging technologies, the related instrumentation is also in the process of being developed; therefore, it is necessary to establish the sensitivity requirements and the effects of uncertainty on different properties of the components and elements of the reactor designs. This report presents the results of simulations that quantify the impacts of the uncertainties of four thermophysical properties of the refrigerant salt (LiF-BeF2) for the Kairos Power benchmark model (g-FHR) for steady state making use of the Sobol’ method through polynomial chaos surrogate modeling. The properties of the salt to which uncertainty was evaluated were density, dynamic viscosity, thermal conductivity and heat capacity. This study was carried out using the Griffin/Pronghorn multiphysics model under the computational resources of the Idaho National Laboratory (INL) High Performance Computing (HPC). The results indicate a weak dependence of the uncertainty of thermal conductivity on the quantities of core pressure drop and core outlet temperature.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
NASA NTRS2001

Safer Aviation Materials Tested

A series of thermally stable polymer samples were tested. These materials are called low heat release materials and are designed for aircraft interior decorative materials. The materials are designed to give off a minimum amount of noxious gases when heated, which increases the possibility that people can escape from a burning aircraft. New cabin materials have suitably low heat release so that fire does not spread, toxic chemicals are not given off, and the fire-emergency escape time for crew and passengers is lengthened. These low heat-release materials have a variety of advantages and applications: interiors for ground-based facilities, interiors of space vehicles, and many commercial fire-protection environments. A microscale combustion calorimeter at the Federal Aviation Administration's (FAA) Technical Center tested NASA Langley Research Center materials samples. The calorimeter is shown. A sharp, quantitative, and reproducible heat-release-rate peak is obtained in the microscale heat-release-rate test. The newly tested NASA materials significantly reduced the heat release capacity and total heat release. The thermal stability and flammability behavior of the samples was very good. The new materials demonstrated a factor of 4 reduction in total heat release over ULTEM (a currently used material). This information is provided in the following barchart. In other tests, the materials showed greater than a factor 9 reduction in heat-release capacity over ULTEM. The newly tested materials were developed for low dielectric constant, low color, and good solubility. A scale up of the material samples is needed to determine the repeatability of the performance in larger samples. Larger panels composed of the best candidate materials will be tested in a larger scale FAA Technical Center fire facility. The NASA Glenn Research Center, Langley (Jeff Hinkley), and the FAA Technical Center (Richard Lyon) cooperatively tested these materials for the Accident Mitigation aspects of Fire Prevention under NASA's Aviation Safety Program.

Palaszewski, Bryan A.↗
NASA NTRS1985

High-Performance Heat Pipe

Single vapor channel and single liquid channel joined by axial slot. New design, permits high heat-transport capacity without excessively reducing heat-transfer efficiency. Contains two large axial channels, one for vapor and one for liquid, permitting axial transport and radial heat-transfer requirements met independently. Heat pipe has capacity of approximately 10 to sixth power watt-inches (2.5 X 10 to sixth power watt-cm) orders of magnitude greater than heat capacity of existing heat pipes. Design has high radial-heat-transfer efficiency, structurally simple, and has large liquid and vapor areas.

Alario, J. P.↗