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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Development of processing techniques for advanced thermal protection materials

The effort, which was focused on the research and development of advanced materials for use in Thermal Protection Systems (TPS), has involved chemical and physical testing of refractory ceramic tiles, fabrics, threads and fibers. This testing has included determination of the optical properties, thermal shock resistance, high temperature dimensional stability, and tolerance to environmental stresses. Materials have also been tested in the Arc Jet 2 x 9 Turbulent Duct Facility (TDF), the 1 atmosphere Radiant Heat Cycler, and the Mini-Wind Tunnel Facility (MWTF). A significant part of the effort hitherto has gone towards modifying and upgrading the test facilities so that meaningful tests can be carried out. Another important effort during this period has been the creation of a materials database. Computer systems administration and support have also been provided. These are described in greater detail below.

Selvaduray, Guna S.↗
NASA NTRS1997

Validation of Framework Code Approach to a Life Prediction System for Fiber Reinforced Composites

The grant was conducted by the MMC Life Prediction Cooperative, an industry/government collaborative team, Ohio Aerospace Institute (OAI) acted as the prime contractor on behalf of the Cooperative for this grant effort. See Figure I for the organization and responsibilities of team members. The technical effort was conducted during the period August 7, 1995 to June 30, 1996 in cooperation with Erwin Zaretsky, the LERC Program Monitor. Phil Gravett of Pratt & Whitney was the principal technical investigator. Table I documents all meeting-related coordination memos during this period. The effort under this grant was closely coordinated with an existing USAF sponsored program focused on putting into practice a life prediction system for turbine engine components made of metal matrix composites (MMC). The overall architecture of the NMC life prediction system was defined in the USAF sponsored program (prior to this grant). The efforts of this grant were focussed on implementing and tailoring of the life prediction system, the framework code within it and the damage modules within it to meet the specific requirements of the Cooperative. T'he tailoring of the life prediction system provides the basis for pervasive and continued use of this capability by the industry/government cooperative. The outputs of this grant are: 1. Definition of the framework code to analysis modules interfaces, 2. Definition of the interface between the materials database and the finite element model, and 3. Definition of the integration of the framework code into an FEM design tool.

Gravett, Phillip↗
NASA NTRS2000

Long-Term Durability Analysis of a 100,000+ Hr Stirling Power Convertor Heater Head

DOE and NASA have identified Stirling Radioisotope Power Systems (SRPS) as the power supply for deep space exploration missions the Europa Orbiter and Solar Probe. As a part of this effort, NASA has initiated a long-term durability project for critical hot section components of the Stirling power convertor to qualify flight hardware. This project will develop a life prediction methodology that utilizes short-term (t < 20,000 hr) test data to verify long-term (t > 100,000 hr) design life. The project consists of generating a materials database for the specific heat of alloy, evaluation of critical hermetic sealed joints, life model characterization, and model verification. This paper will describe the qualification methodology being developed and provide a status for this effort.

Bartolotta, Paul A.↗
NASA NTRS2002

A "Tread" Ahead of the Competition

Through a consortium formed by NASA's Glenn Research Center and the Great Lakes Industrial Technology Center, Goodyear acquired a software use agreement for NASA's Micromechanics Analysis Code (MAC), in an effort to design stronger and safer tires. Based on the Generalized Method of Cells micromechanics methodology, the MAC technology has allowed Goodyear scientists and engineers to perform structural analysis of composite laminates for tires all in one step, rather than the several steps previously required. Currently, the MAC code can be used to assess and optimize composite laminates; set cord-spacing guidelines (the diameter and distance between cords may impact the overall durability of a tire); explain structural impact of geometrical configurations; and compare the behavior of the different wire constructions that make up a tire. Furthermore, the MAC software contains a built-in material database and several representative volume elements for a wider choice of composites to better represent the plies and belts in a tire. The end result of the process ultimately reduces the time spent on building, testing, and adjusting tires.

Source record↗
NASA NTRS2003

Membrane-Based Gas Traps for Ammonia, Freon-21, and Water Systems to Simplify Ground Processing

Gas traps are critical for the smooth operation of coolant loops because gas bubbles can cause loss of centrifugal pump prime, interference with sensor readings, inhibition of heat transfer, and blockage of passages to remote systems. Coolant loops are ubiquitous in space flight hardware, and thus there is a great need for this technology. Conventional gas traps will not function in micro-gravity due to the absence of buoyancy forces. Therefore, clever designs that make use of adhesion and momentum are required for adequate separation, preferable in a single pass. The gas traps currently used in water coolant loops on the International Space Station are composed of membrane tube sets in a shell. Each tube set is composed of a hydrophilic membrane (used for water transport and capture of bubbles) and a hydrophobic membrane (used for venting of air bubbles). For the hydrophilic membrane, there are two critical pressures, the pressure drop and the bubble pressure. The pressure drop is the decrease in system pressure across the gas trap. The bubble pressure is the pressure required for air bubbles to pass across the water filled membrane. A significant difference between these pressures is needed to ensure complete capture of air bubbles in a single pass. Bubbles trapped by the device adsorb on the hydrophobic membrane in the interior of the hydrophilic membrane tube. After adsorption, the air is vented due to a pressure drop of approximately 1 atmosphere across the membrane. For water systems, the air is vented to the ambient (cabin). Because water vapor can also transport across the hydrophobic membrane, it is critical that a minimum surface area is used to avoid excessive water loss (would like to have a closed loop for the coolant). The currently used gas traps only provide a difference in pressure drop and bubble pressure of 3-4 psid. This makes the gas traps susceptible to failure at high bubble loading and if gas venting is impaired. One mechanism for the latter is when particles adhere to the hydrophobic membrane, promoting formation of a water layer about it that can blind the membrane for gas transport (Figure 1). This mechanism is the most probable cause for observed failures with the existing design. The objective of this project was to devise a strategy for choosing new membrane materials (database development and procedure), redesign of the gas trap to mitigate blinding effects, and to develop a design that can be used in ammonia and Freon-21 coolant loops.

Ritchie, Stephen M. C.↗
NASA NTRS2005

Polymers in Space: Applications in the NASA Life Support and Habitation Program

Outline of Content to be Presented: Session 1: Background on Human Space Flight, NASA Human Space Flight Programs: Apollo, Shuttle, ISS, U.S. Vision for Space Exploration, Goals of Human Spaceflight. Session. 2: Use of Polymers in NASA Technology Development, Life Support & Habitation Program, Spacecraft and Space Suit Requirements and Constraints Applications - Past, Current, Future Technologies in Development. Session 3: NASA Materials Database, Classes of Useful Polymers and Composites, Unique Requirements on Polymers in Space Applications of Synthetic and Biological Polymers. Session 4: Design of Polymer Parts for a Lunar Space Suit, Sample Activities for Teachers to Use in High School Classrooms.

Campbell, Paul D.↗
NASA NTRS2022

Virtual Assistant for First Responders Using Natural Language Understanding and Optical Character Recognition

Commercial deep learning capabilities are available for many applications such as computer vision processing and intelligent chat bots. The Google Cloud Platform product Google Dialogflow provides lifelike conversational artificial intelligence (AI) using machine learning (ML) to generate natural conversations between computers and humans. This ML utilizes natural language understanding (NLU) to recognize a user’s intent and extracts key information into a form of entities. We have developed a user-friendly application through understanding the hazardous material database, first aid safety guidelines and observing the process of first responders who access this information in the field. We created the Trusted and Explainable Artificial Intelligence for Saving Lives (TruePAL) virtual assistant using Dialogflow1 and TensorFlow2 paired with EasyOCR.3 The chatbot supports first responders by providing voice interaction which helps limit additional steps such as browsing through multiple categories when searching for information. Using feedback from our field interviews, the voice interface has been developed to enable the first responder to focus on the immediate emergency. With less distractions, the first responder is able to engage the incident more effectively. The partial hands-free TruePAL chatbot assistant improves the accessibility to the correct guidance by an average of 1.9 seconds compared to the widely used application, NIH WISER, which requires full attention to operate. We combined this intelligent chatbot with a separate visual processing capability to produce hazardous signage analysis and generate the proper guidance for first responders. With the evolving functionality of AI tools, the use of virtual assistants in first responder technology will be an advancement, benefiting the safety of both first responders and civilians.

Chow, Edward↗
DOE OSTI2021

OPTIMADE, an API for exchanging materials data

Abstract The Open Databases Integration for Materials Design (OPTIMADE) consortium has designed a universal application programming interface (API) to make materials databases accessible and interoperable. We outline the first stable release of the specification, v1.0, which is already supported by many leading databases and several software packages. We illustrate the advantages of the OPTIMADE API through worked examples on each of the public materials databases that support the full API specification.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS1994

A manufacturing database of advanced materials used in spacecraft structures

Cost savings opportunities over the life cycle of a product are highest in the early exploratory phase when different design alternatives are evaluated not only for their performance characteristics but also their methods of fabrication which really control the ultimate manufacturing costs of the product. In the past, Design-To-Cost methodologies for spacecraft design concentrated on the sizing and weight issues more than anything else at the early so-called 'Vehicle Level' (Ref: DOD/NASA Advanced Composites Design Guide). Given the impact of manufacturing cost, the objective of this study is to identify the principal cost drivers for each materials technology and propose a quantitative approach to incorporating these cost drivers into the family of optimization tools used by the Vehicle Analysis Branch of NASA LaRC to assess various conceptual vehicle designs. The advanced materials being considered include aluminum-lithium alloys, thermoplastic graphite-polyether etherketone composites, graphite-bismaleimide composites, graphite- polyimide composites, and carbon-carbon composites. Two conventional materials are added to the study to serve as baseline materials against which the other materials are compared. These two conventional materials are aircraft aluminum alloys series 2000 and series 7000, and graphite-epoxy composites T-300/934. The following information is available in the database. For each material type, the mechanical, physical, thermal, and environmental properties are first listed. Next the principal manufacturing processes are described. Whenever possible, guidelines for optimum processing conditions for specific applications are provided. Finally, six categories of cost drivers are discussed. They include, design features affecting processing, tooling, materials, fabrication, joining/assembly, and quality assurance issues. It should be emphasized that this database is not an exhaustive database. Its primary use is to make the vehicle designer aware of some of the most important aspects of manufacturing associated with his/her choice of the structural materials. The other objective of this study is to propose a quantitative method to determine a Manufacturing Complexity Factor (MCF) for each material being contemplated. This MCF is derived on the basis of the six cost drivers mentioned above plus a Technology Readiness Factor which is very closely related to the Technology Readiness Level (TRL) as defined in the Access To Space final report. Short of any manufacturing information, our MCF is equivalent to the inverse of TRL. As more manufacturing information is available, our MCF is a better representation (than TRL) of the fabrication processes involved. The most likely application for MCF is in cost modeling for trade studies. On-going work is being pursued to expand the potential applications of MCF.

Bao, Han P.↗
NASA NTRS1989

Materials properties numerical database system established and operational at CINDAS/Purdue University

A computerized comprehensive numerical database system on the mechanical, thermophysical, electronic, electrical, magnetic, optical, and other properties of various types of technologically important materials such as metals, alloys, composites, dielectrics, polymers, and ceramics has been established and operational at the Center for Information and Numerical Data Analysis and Synthesis (CINDAS) of Purdue University. This is an on-line, interactive, menu-driven, user-friendly database system. Users can easily search, retrieve, and manipulate the data from the database system without learning special query language, special commands, standardized names of materials, properties, variables, etc. It enables both the direct mode of search/retrieval of data for specified materials, properties, independent variables, etc., and the inverted mode of search/retrieval of candidate materials that meet a set of specified requirements (which is the computer-aided materials selection). It enables also tabular and graphical displays and on-line data manipulations such as units conversion, variables transformation, statistical analysis, etc., of the retrieved data. The development, content, accessibility, etc., of the database system are presented and discussed.

Ho, C. Y.↗
DOE OSTI2022

A representation-independent electronic charge density database for crystalline materials

Abstract In addition to being the core quantity in density-functional theory, the charge density can be used in many tertiary analyses in materials sciences from bonding to assigning charge to specific atoms. The charge density is data-rich since it contains information about all the electrons in the system. With the increasing prevalence of machine-learning tools in materials sciences, a data-rich object like the charge density can be utilized in a wide range of applications. The database presented here provides a modern and user-friendly interface for a large and continuously updated collection of charge densities as part of the Materials Project. In addition to the charge density data, we provide the theory and code for changing the representation of the charge density which should enable more advanced machine-learning studies for the broader community.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A representation-independent electronic charge density database for crystalline materials

In addition to being the core quantity in density functional theory, the charge density can be used in many tertiary analyses in materials sciences from bonding to assigning charge to specific atoms. The charge density is data-rich since it contains information about all the electrons in the system. With increasing utilization of machine-learning tools in materials sciences, a data-rich object like the charge density can be utilized in a wide range of applications. The database presented here provides a modern and user-friendly interface for a large and continuously updated collection of charge densities as part of the Materials Project. In addition to the charge density data, we provide the theory and code for changing the representation of the charge density which should enable more advanced machine-learning studies for the broader community.

36 MATERIALS SCIENCE↗
NASA NTRS2014

Expanding the REE Partitioning Database for Lunar Materials

Positive europium anomalies are ubiquitous in the plagioclase-rich rocks of the lunar highlands, and complementary negative Eu anomalies are found in most lunar basalts. This is taken as evidence of a large-scale differentation event, with crystallization of a global-scale lunar magma ocean (LMO) resulting in a plagioclase flotation crust and a mafic lunar interior from which mare basalts were later derived. However, the extent of the Eu anomaly in lunar rocks is variable. Some plagioclase grains in a lunar impact rock (60635) have been reported to display a negative Eu anomaly, or in some cases single grains display both positive and neagtive anomalies. Cathodoluminescence images reveal that some crystals have a negative anomaly in the core and positive at the rim, or vice versa, and the negative anomalies are not associated with crystal overgrowths. Oxygen fugacity is known to affect Eu partitioning into plagioclase, as under low fO2 conditions Eu can be divalent, and has an ionic radius similar to Ca2+ - significant in lunar samples where plagioclase compositions are predominantly anorthitic. However, there are very few experimental studies of rare earth element (REE) partitioning in plagioclase relevant to lunar magmatism, with only two plagioclase DEu measurements from experiments using lunar materials, and little data in low fO2 conditions relevant to the Moon. We report on REE partitioning experiments on lunar compositions. We investigate two lunar basaltic compositions, high-alumina basalt 14072 and impact melt breccia 60635. These samples span a large range of lunar surface bulk compositions. The experiments are carried out at variable fO2 in 1 bar gas mixing furnaces, and REE are analysed by and LA-ICP-MS. Our results not only greatly expand the existing plagioclase DREE database for lunar compositions, but also investigate the significance of fO2 in Eu partitioning, and in the interpretation of Eu anomalies in lunar materials.

Rapp, Jennifer F.↗
NASA NTRS2016

In-Space Manufacturing Baseline Property Development

The In-Space Manufacturing (ISM) project at NASA Marshall Space Flight Center currently operates a 3D FDM (fused deposition modeling) printer onboard the International Space Station. In order to enable utilization of this capability by designer, the project needs to establish characteristic material properties for materials produced using the process. This is difficult for additive manufacturing since standards and specifications do not yet exist for these technologies. Due to availability of crew time, there are limitations to the sample size which in turn limits the application of the traditional design allowables approaches to develop a materials property database for designers. In this study, various approaches to development of material databases were evaluated for use by designers of space systems who wish to leverage in-space manufacturing capabilities. This study focuses on alternative statistical techniques for baseline property development to support in-space manufacturing.

Stockman, Tom↗
DOE OSTI2020

Tight-Binding-Based Method for Simulations of Complex Materials with Accompanying Database

The NRL-Tight-Binding (NRL-TB) method has been applied successfully to many monatomic, binary, and a few ternary systems. The method consists of a fit to Density Functional Theory (DFT) results and has transferability beyond the fitted DFT database including performing tight-binding molecular dynamics simulations. We are working on a new website with a detailed guide of how to use the method in performing the fit to DFT results (Fitting Code) and obtaining non-orthogonal TB parameters expressed in a polynomial form as environment-dependent Slater-Koster parameters (on-site terms), and neighbor distance-dependent Hamiltonian and Overlap terms. These parameters are then used in a Static Code to verify or make predictions for large systems often beyond the computational capabilities of standard DFT codes. Our starting point was a website developed at NRL some years ago which NRL no longer supports. We have now been augmenting that website with new examples of expanding the original capabilities of the method such as incorporating in the codes f-electron states. Our website (esd.cos.gmu.edu/tb) contains two separate branches: One named NRL-TB with the full documentation of the method including source codes and examples. The other branch, named ESD-dB, is a library of electronic structure calculations for all the monatomic elements (a subset of the elements also found in a recent book by the author of this proposal. See reference 22) and an approximately 700 hundred compounds in specific crystal structures. We discuss below the progress made so far in improving and expanding the capabilities of our TB method and the plans for further extensions of our approach.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Deep learning of electrochemical CO 2 conversion literature reveals research trends and directions

Large-scale and openly available material science databases are mainly composed of computer simulation results rather than experimental data. Some examples include the Materials Project, Open Quantum Materials Database, and Open Catalyst 2022. Unfortunately, building large-scale experimental databases remains challenging due to the difficulties in consolidating locally distributed datasets. In this work, focusing on the catalysis literature of CO 2 reduction reactions (CO 2 RRs), we present a machine learning (ML)-based protocol for selecting highly relevant papers and extracting important experimental data. First, we report a document embedding method (Doc2Vec) for collecting papers of greatest relevance to the specific target domain, which yielded 3154 CO 2 RR-related papers from six publishers. Next, we developed named entity recognition (NER) models to extract twelve entities related to material names (catalyst, electrolyte, etc.) and catalytic performance (Faradaic efficiency, current density, etc.). Further, among several tested models, the MatBERT-based approach achieved the highest accuracy, with an average F1-score of 90.4% and an F1-score of 95.2% in a boundary relaxation evaluation scheme. The accurate and accelerated NER-based data extraction from a large volume of catalysis literature enables temporal trend analyses of the CO 2 RR catalysts, products, and performances, revealing the potentially effective material space in CO 2 RRs. While this work demonstrates the effectiveness of our ML-based text mining methods for specifically CO 2 RR literature, the methods and approach are applicable to and may be used to accelerate the development of other catalytic chemical reactions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Path Forward: Materials Data Modernization for ASME Codes and Standards in the Artificial Intelligence Era

Development of the ASME Materials Properties Database was initiated in the early 2010s to support the ASME Codes and Standards. As information technologies advance at an accelerated pace with the artificial intelligence era on the horizon, the ASME Materials Properties Database must be further modernized from a database to a knowledgebase to ride the wave of digital information revolution and effectively support the ASME Codes and Standards in the new era. This paper is intended to provide an overview of the ASME Materials Properties Database and discuss a roadmap for its future development to facilitate understanding of and participation from different sectors of the Codes and Standards community. Further, it first reviews the basic concepts of data, information, knowledge, database, and database system as well as the pros and cons in different types of data management and then discusses the path forward for a desired evolution of the database into a self-explanatory and machine-readable knowledgebase that is consistent with human cognitive processes for the Codes and Standards development and, furthermore, provides resources for data processing and analysis to reach an eventual goal of streamlining the Codes and Standards development from the initial inquiry, throughout data submission, analysis, …, to Codes and Standards rule establishment for final publication.

36 MATERIALS SCIENCE↗