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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 1,261 records · Page 70

Materials Processing in Space: Model Experiments aboard the International Space Station

Direct observation of fluid flow, bubble movement and solidification during controlled melting and solidification of succinonitrile were conducted in the glovebox facility of the International Space Station (ISS). The samples were processed in the Pore Formation and Mobility Investigation (PFMI) apparatus in the glovebox facility (GBX) on board the ISS. Experimental processing parameters of temperature gradient and translation speed, as well as camera settings, were remotely monitored and manipulated from the ground Telescience Center (TSC) at the Marshall Space Flight Center. Real time visualization of the controlled directional melt back and resolidification reveals a number of microgravity dependent phenomena otherwise masked by Earth s gravity. These and some initial analysis of the observed events is presented.

Grugel, Richard↗

Modeling Ablation of Fibrous Materials from Bulk to Knudsen Regime

Material-environment interactions are analyzed at microscopic scale to explain the lower than expected density observed by post-flight analysis of the char layer on the Stardust shield. Mass transfer, ablation (oxidation), and surface recession of fibrous material is simulated in 3D using a Monte-Carlo simulation tool. Ablation is found to occur either at the surface or in volume depending on Knudsen and Thiele number values. This study supports the idea of volume ablation followed by possible carbon fiber spallation that may explain post-flight analyses.

Lachaud, Jean↗

Decoupled Method for Reconstruction of Surface Conditions From Internal Temperatures On Ablative Materials With Uncertain Recession Model

Obtaining measurements of flight environments on ablative heat shields is both critical for spacecraft development and extremely challenging due to the harsh heating environment and surface recession. Thermocouples installed several millimeters below the surface are commonly used to measure the heat shield temperature response, but an ill-posed inverse heat conduction problem must be solved to reconstruct the surface heating environment from these measurements. Ablation can contribute substantially to the measurement response making solutions to the inverse problem strongly dependent on the recession model, which is often poorly characterized. To enable efficient surface reconstruction for recession model sensitivity analysis, a method for decoupling the surface recession evaluation from the inverse heat conduction problem is presented. The decoupled method is shown to provide reconstructions of equivalent accuracy to the traditional coupled method but with substantially reduced computational effort. These methods are applied to reconstruct the environments on the Mars Science Laboratory heat shield using diffusion limit and kinetically limited recession models.

Oliver, A. Brandon↗

Development of a Three-Dimensional, Unstructured Material Response Design Tool

A preliminary verification and validation of a new material response model is presented. This model, Icarus, is intended to serve as a design tool for the thermal protection systems of re-entry vehicles. Currently, the capability of the model is limited to simulating the pyrolysis of a material as a result of the radiative and convective surface heating imposed on the material from the surrounding high enthalpy gas. Since the major focus behind the development of Icarus has been model extensibility, the hope is that additional physics can be quickly added. This extensibility is critical since thermal protection systems are becoming increasing complex, e.g. woven carbon polymers. Additionally, as a three-dimensional, unstructured, finite-volume model, Icarus is capable of modeling complex geometries. In this paper, the mathematical and numerical formulation is presented followed by a discussion of the software architecture and some preliminary verification and validation studies.

Thermal Protection System↗

Regularized machine learning on molecular graph model explains systematic error in DFT enthalpies

Abstract A major goal of materials research is the discovery of novel and efficient heterogeneous catalysts for various chemical processes. In such studies, the candidate catalyst material is modeled using tens to thousands of chemical species and elementary reactions. Density Functional Theory (DFT) is widely used to calculate the thermochemistry of these species which might be surface species or gas-phase molecules. The use of an approximate exchange correlation functional in the DFT framework introduces an important source of error in such models. This is especially true in the calculation of gas phase molecules whose thermochemistry is calculated using the same planewave basis set as the rest of the surface mechanism. Unfortunately, the nature and magnitude of these errors is unknown for most practical molecules. Here, we investigate the error in the enthalpy of formation for 1676 gaseous species using two different DFT levels of theory and the ‘ground truth values’ obtained from the NIST database. We featurize molecules using graph theory. We use a regularized algorithm to discover a sparse model of the error and identify important molecular fragments that drive this error. The model is robust to rigorous statistical tests and is used to correct DFT thermochemistry, achieving more than an order of magnitude improvement.

36 MATERIALS SCIENCE↗

Preliminary study: Moisture-polymer interaction. Stuby objectives

The problems associated with mathematically modeling water-module interaction phenomena, including sorption and desorption, diffusion, and permeation are discussed. With reliable analytical models, an extensive materials data base, and solar radiation surface meteorological observations (SOLMET) weather data, predicting module lifetimes in realistic environments can become a practical reality. The status of the present techniques of simulating the various transport mechanisms was reported. The Dent model (a modified Brunauer-Emmet-Teller) approach represented polyvinyl butyral (PVB) sorption data. A 100-layer material model and Fick's diffusion model gave diffusivity values exhibiting adequate agreement with those measured for PVB. Diffusivity of PVB is concentration dependent, decreasing as the water content in PVB increases. The temperature dependence of diffusion in PVB is well modeled by the Arrhenius rate equation. Equilibrium conductivity and leakage current data are well represented by Hearle's model for bulk ionic conductivity. A nodal network analysis using the Systems Improved Numerical Differencing Analyzer (SINDA) Thermal Analyzer gave reasonable correlation with measurable data. It is concluded that realistic lifetime predictions seem to be feasible.

Wen, L. C.↗

Finite element modeling of truss structures with frequency-dependent material damping

A physically motivated modelling technique for structural dynamic analysis that accommodates frequency dependent material damping was developed. Key features of the technique are the introduction of augmenting thermodynamic fields (AFT) to interact with the usual mechanical displacement field, and the treatment of the resulting coupled governing equations using finite element analysis methods. The AFT method is fully compatible with current structural finite element analysis techniques. The method is demonstrated in the dynamic analysis of a 10-bay planar truss structure, a structure representative of those contemplated for use in future space systems.

Lesieutre, George A.↗

Dynamic in-context learning with conversational models for data extraction and materials property prediction

The advent of natural language processing and large language models (LLMs) has revolutionized the extraction of data from unstructured scholarly papers. However, ensuring data trustworthiness remains a significant challenge. In this paper, we introduce PropertyExtractor, an open-source tool that leverages advanced conversational LLMs such as Google gemini-pro and OpenAI gpt-4, blends zero-shot with few-shot in-context learning, and employs engineered prompts for the dynamic refinement of structured information hierarchies—enabling autonomous, efficient, scalable, and accurate identification, extraction, and verification of material property data. Our tests on material data demonstrate precision and recall that exceed 95% with an error rate of ∼9%, highlighting the effectiveness and versatility of the toolkit. Finally, databases for 2D material thicknesses, a critical parameter for device integration, and energy bandgap values are developed using PropertyExtractor. In particular, for the thickness database, the rapid evolution of the field has outpaced both experimental measurements and computational methods, creating a significant data gap. Our work addresses this gap and showcases the potential of PropertyExtractor as a reliable and efficient tool for the autonomous generation of various material property databases, advancing the field.

Ekuma, Chinedu E. (ORCID:0000000258527556)↗

Modeling support for the development of material surveillance specimens and procedures

This report describes modeling and simulation activities performed at Argonne National Laboratory supporting the development of passively actuated mechanical test articles for material surveillance in Molten Salt Reactors (MSRs). These test articles are a critical technology in formulating material surveillance programs for future MSRs to monitor the degradation in the structural properties of the materials in critical plant components. The main activity described in this report is the development of a method for inferring the amount of mechanical damage a test article has experienced during some duration of exposure to plant thermal and environmental conditions, using only mechanical test data collected from the test articles before and after exposure. The basic approach is to develop a model of the test article, including a description of mechanical degradation through continuum damage mechanics, and then use this model to cast the problem of inferring mechanical degradation in the test article materials into a shooting problem for a set of ordinary differential equations. We can then solve the shooting problem to determine the amount of damage accumulated in the sample. The report also details a few miscellaneous simulation studies completed at Argonne to support the development of the test articles themselves at Idaho National Laboratory.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Material Control & Accounting Statistical Test Modeling Supporting the Low Enriched Fuel Fabrication Facility Using F3M and MAPIT

This report covers the application of the TRi-structural ISOtropic (TRISO) fuel fabrication facility material control & accounting (MC&A) modeling capability developed by Sandia National Laboratories (SNL) under the U.S. Department of Energy (DOE) Materials Protection, Accounting, and Control Technologies (MPACT) program to support the development of MC&A approaches for the Low Enriched Fuel Fabrication Facility (LEFFF) at Los Alamos National Laboratory (LANL).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗