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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Modelling of photodegradation in solar cell modules of substrate and superstrate design made with ethylene-vinyl acetate as pottant material

A computer model was developed which can generate realistic concentration versus time profiles of the chemical species formed during photooxidation of hydrocarbon polymers using as input data a set of elementary reactions with corresponding rate constants and initial conditions. The results of computer simulation have been shown to be consistent with the general experimental observations of the photooxidation of polyethylene exposed to sunlight at ambient temperatures. The useful lifetime (5% oxidation) of the unstabilized polyethylene is predicted to vary from a few months in hot weather (100 F) to almost two years in cool weather (45 F) with an apparent net activation energy of 10 kcal/mol. Modelling studies of alternate mechanisms for stabilization of clear, amorphous, linear polyethylene suggest that the optimum stabilizer would be a molecularly dispensed additive in very low concentration which can trap peroxy radicals and also decompose hydroperoxides.

Somersall, A. C.↗
NASA NTRS1995

Aeronautical engineering: A continuing bibliography with indexes (supplement 316)

This bibliography lists 413 reports, articles, and other documents introduced into the NASA scientific and technical information system in April 1995. Subject coverage includes: aeronautics; mathematical and computer sciences; chemistry and material sciences; geosciences; design, construction and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics.

Source record↗
NASA NTRS2017

Designing and Developing Web-Based Administrative Tools for Program Management

The task assigned for this internship was to develop a new tool for tracking projects, their subsystems, the leads, backups, and other employees assigned to them, as well as all the relevant information related to the employee (WBS (time charge) codes, time distribution, certifications, and assignments). Currently, this data is tracked manually using a number of different spreadsheets and other tools simultaneously by a number of different people; some of these documents are then merged into one large document. This often leads to inconsistencies and loss in data due to human error. By simplifying the process of tracking this data and aggregating it into a single tool, it is possible to significantly decrease the potential for human error and time spent collecting and checking this information. II. Objective The main objective of this internship is to develop a web-based tool using Ruby on Rails to serve as a method of easily tracking projects, subsystems, and points of contact, along with employees, their assignments, time distribution, certifications, and contact information. Additionally, this tool must be capable of generating a number of different reports based on the data collected. It was important that this tool deliver all of this information using a readable and intuitive interface.

Material↗
NASA NTRS2019

Heatshield Entry Modeling Using a Design, Analysis, and Optimization Toolbox

The Mars Science Laboratory (MSL) was protected during its Mars atmospheric entry by an instrumented heatshield that used NASA's Phenolic Impregnated Carbon Ablator (PICA). PICA is a lightweight carbon fiber/polymeric resin material that offers excellent performances for protecting probes during planetary entry. The Mars Entry Descent and Landing Instrument (MEDLI) suite on MSL offers unique in-flight validation data for models of atmospheric entry and material response. MEDLI recorded, among others, time-resolved in-depth temperature data of PICA using thermocouple sensors assembled in the MEDLI Integrated Sensor Plugs (MISP). The objective of this work is to showcase the capability of the Design, Analysis, and Optimization of Thermal Protection Materials (DAOTPM) software. DAO-TPM is a Python based framework that works as a link between mission design, aerothermal and radiative environment computation, Thermal Protection Systems (TPS) microstructure analysis, material response and optimization tools. The toolbox has a Graphical User Interface (GUI) that allows the user to build as well as run the various software and utilities used to design, analyze and optimize a heatshield during atmospheric entry.

Meurisse, Jeremie B. E.↗
DOE OSTI2023

An Implicit Approach to Phase Field Modeling of Solidification for Additively Manufactured Alloys [Slides]

We are leveraging modern algorithms and computational science to provide a route to predictive simulation of microstructure evolution on emerging exascale architectures. We are utilizing the fastest supercomputers in the world for modeling and simulation of microstructure evolution for generation of data under AM conditions. Solidification conditions in AM can be tailored for the reliable design of materials to specific performance requirements. Developing computational tools to further characterize alloys and correlate the processing-structure-properties-performance (PSPP) relationship.

36 MATERIALS SCIENCE↗
NASA NTRS2014

Physics-based Entry, Descent and Landing Risk Model

A physics-based risk model was developed to assess the risk associated with thermal protection system failures during the entry, descent and landing phase of a manned spacecraft mission. In the model, entry trajectories were computed using a three-degree-of-freedom trajectory tool, the aerothermodynamic heating environment was computed using an engineering-level computational tool and the thermal response of the TPS material was modeled using a one-dimensional thermal response tool. The model was capable of modeling the effect of micrometeoroid and orbital debris impact damage on the TPS thermal response. A Monte Carlo analysis was used to determine the effects of uncertainties in the vehicle state at Entry Interface, aerothermodynamic heating and material properties on the performance of the TPS design. The failure criterion was set as a temperature limit at the bondline between the TPS and the underlying structure. Both direct computation and response surface approaches were used to compute the risk. The model was applied to a generic manned space capsule design. The effect of material property uncertainty and MMOD damage on risk of failure were analyzed. A comparison of the direct computation and response surface approach was undertaken.

descent and landing↗
NASA NTRS2004

adwTools Developed: New Bulk Alloy and Surface Analysis Software for the Alloy Design Workbench

A suite of atomistic modeling software, called the Alloy Design Workbench, has been developed by the Computational Materials Group at the NASA Glenn Research Center and the Ohio Aerospace Institute (OAI). The main goal of this software is to guide and augment experimental materials research and development efforts by creating powerful, yet intuitive, software that combines a graphical user interface with an operating code suitable for real-time atomistic simulations of multicomponent alloy systems. Targeted for experimentalists, the interface is straightforward and requires minimum knowledge of the underlying theory, allowing researchers to focus on the scientific aspects of the work. The centerpiece of the Alloy Design Workbench suite is the adwTools module, which concentrates on the atomistic analysis of surfaces and bulk alloys containing an arbitrary number of elements. An additional module, adwParams, handles ab initio input for the parameterization used in adwTools. Future modules planned for the suite include adwSeg, which will provide numerical predictions for segregation profiles to alloy surfaces and interfaces, and adwReport, which will serve as a window into the database, providing public access to the parameterization data and a repository where users can submit their own findings from the rest of the suite. The entire suite is designed to run on desktop-scale computers. The adwTools module incorporates a custom OAI/Glenn-developed Fortran code based on the BFS (Bozzolo- Ferrante-Smith) method for alloys, ref. 1). The heart of the suite, this code is used to calculate the energetics of different compositions and configurations of atoms.

Bozzolo, Guillermo↗
NASA NTRS2000

NASA Tech Briefs, May 2000

Topics include: Sensors: Test and Measurement; Computer-Aided Design and Engineering; Electronic Components and Circuits; Electronic Systems; Composites and Plastics; Materials; Computer Programs; Mechanics;

Source record↗
NASA NTRS1997

Computational Modeling Method for Superalloys

Computer modeling based on theoretical quantum techniques has been largely inefficient due to limitations on the methods or the computer needs associated with such calculations, thus perpetuating the notion that little help can be expected from computer simulations for the atomistic design of new materials. In a major effort to overcome these limitations and to provide a tool for efficiently assisting in the development of new alloys, we developed the BFS method for alloys, which together with the experimental results from previous and current research that validate its use for large-scale simulations, provide the ideal grounds for developing a computationally economical and physically sound procedure for supplementing the experimental work at great cost and time savings.

Bozzolo, Guillermo↗
DOE OSTI2022

ArQTiC: A Full-stack Software Package for Simulating Materials on Quantum Computers

ArQTiC is an open-source, full-stack software package built for the simulations of materials on quantum computers. It currently can simulate materials that can be modeled by any Hamiltonian derived from a generic, one-dimensional, time-dependent Heisenberg Hamiltonian. ArQTiC includes modules for generating quantum programs for real- and imaginary-time evolution, quantum circuit optimization, connection to various quantum backends via the cloud, and post-processing of quantum results. By enabling users to seamlessly design, execute, and analyze materials simulations on quantum computers, ArQTiC opens this field to a broader community of scientists from a wider range of scientific domains.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2003

Micromechanics-Based Computational Simulation of Ceramic Matrix Composites

Advanced high-temperature Ceramic Matrix Composites (CMC) hold an enormous potential for use in aerospace propulsion system components and certain land-based applications. However, being relatively new materials, a reliable design properties database of sufficient fidelity does not yet exist. To characterize these materials solely by testing is cost and time prohibitive. Computational simulation then becomes very useful to limit the experimental effort and reduce the design cycle time, Authors have been involved for over a decade in developing micromechanics- based computational simulation techniques (computer codes) to simulate all aspects of CMC behavior including quantification of scatter that these materials exhibit. A brief summary/capability of these computer codes with typical examples along with their use in design/analysis of certain structural components is the subject matter of this presentation.

Murthy, Pappu L. N.↗
DOE OSTI2022

Structured illumination with thermal imaging (SI-TI): A dynamically reconfigurable metrology for parallelized thermal transport characterization

The recent push for the “materials by design” paradigm requires synergistic integration of scalable computation, synthesis, and characterization. Among these, techniques for efficient measurement of thermal transport can be a bottleneck limiting the experimental database size, especially for diverse materials with a range of roughness, porosity, and anisotropy. Traditional contact thermal measurements have challenges with throughput and the lack of spatially resolvable property mapping, while non-contact pump-probe laser methods generally need mirror smooth sample surfaces and also require serial raster scanning to achieve property mapping. Here, we present structured illumination with thermal imaging (SI-TI), a new thermal characterization tool based on parallelized all-optical heating and thermometry. Experiments on representative dense and porous bulk materials as well as a 3D printed thermoelectric thick film (~50 μm) demonstrate that SI-TI (1) enables paralleled measurement of multiple regions and samples without raster scanning; (2) can dynamically adjust the heating pattern purely in software, to optimize the measurement sensitivity in different directions for anisotropic materials; and (3) can tolerate rough (~3 μm) and scratched sample surfaces. Here, this work highlights a new avenue in adaptivity and throughput for thermal characterization of diverse materials.

42 ENGINEERING↗
NASA NTRS1988

Multi-color pyrometer for materials processing in space

The design, construction and calibration of a computer-linked multicolor pyrometer is described. The device was constructed for ready adaptation to a spacecraft and for use in the control of thermal processes for manufacturing materials in space. The pyrometer actually uses only one color at a time, and is relatively insensitive to uncertainties in the heated object's emissivity because the product of the color and the temperature has been selected to be within a regime where the radiant energy emitted from the body increases very rapidly with temperature. The instrument was calibrated and shown to exceed its design goal of temperature measurements between 300 and 2000 C, and its accuracy in the face of imprecise knowledge of the hot object's emissivity was demonstrated.

Frish, Michael B.↗
DOE OSTI2020

An active learning high-throughput microstructure calibration framework for solving inverse structure–process problems in materials informatics

Determining a process–structure–property relationship is the holy grail of materials science, where both computational prediction in the forward direction and materials design in the inverse direction are essential. Problems in materials design are often considered in the context of process–property linkage by bypassing the materials structure, or in the context of structure–property linkage as in microstructure-sensitive design problems. However, there is a lack of research effort in studying materials design problems in the context of process–structure linkage, which has a great implication in reverse engineering. In this paper, given a target microstructure, we propose an active learning high-throughput microstructure calibration framework to derive a set of processing parameters, which can produce an optimal microstructure that is statistically equivalent to the target microstructure. The proposed framework is formulated as a noisy multi-objective optimization problem, where each objective function measures a deterministic or statistical difference of the same microstructure descriptor between a candidate microstructure and a target microstructure. Furthermore, to significantly reduce the physical waiting wall-time, we enable the high-throughput feature of the microstructure calibration framework by adopting an asynchronously parallel Bayesian optimization to exploit high-performance computing resources. Case studies in additive manufacturing and grain growth are used to demonstrate the applicability of the proposed framework, where kinetic Monte Carlo (kMC) simulation is used as a forward predictive model, such that for a given target microstructure, the target processing parameters that produced this microstructure are successfully recovered.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Deep Learning Coordinate-Free Quantum Chemistry

Computing quantum chemical properties of small molecules and polymers can provide insights valuable to physicists, chemists and biologists when designing new materials, catalysts, biological probes and drugs. Deep learning can compute quantum chemical properties accurately in a fraction of the time required by commonly used methods such as density functional theory (DFT). However, many of these deep learning architectures require energy minimized molecular geometries as input, which is also computationally expensive, and decreasing the reproducibility and throughput of these methods. In this study, we demonstrate that accurate quantum chemical computations can be performed without optimized geometries by operating in the coordinate-free domain using deep learning on graph encodings. Furthermore, we also find that the choice of graph-encoding architecture substantially affects the performance of these methods. The Wave architecture outperforms graph convolution architectures, particularly on complex molecules. Furthermore, the structures of these graph encoding architectures provide an opportunity to probe an important, outstanding question in quantum mechanics: What types of quantum chemical properties can be represented by local-variable models? We find that Wave, a local-variable model, is more accurately calculates quantum chemical properties. Graph convolutional architectures require global variables, and are not as effective as as Wave. We anticipate that coordinate-free, deep-learning models of quantum chemistry will become valuable tools in chemistry and biology, enabling researchers to rapidly screen chemical databases or identify new molecules using automated, de-novo design algorithms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1992

Flight 20 (STS-45) polysulfide gas path investigation

This report documents the results of the investigation into causes of gas paths on the 20A and 20B case-to-nozzle joints on STS-42. The investigation was conducted by the Investigation Board appointed by the senior vice president and general manager of Space Operations, Mr. R. E. Lindstrom, on 7 Feb. 1992. The probability of gas path occurrence in the nozzle-to-case-joint polysulfide had been identified during joint redesign. However, actual flight gas path incidence has been limited to RSRM-11 and the 20A and 20B segments. The blow-by condition on the 20A segment was a first time occurrence which was a special concern. The investigation covered all technical aspects associated with the gas path and blow-by conditions: materials and processing history, design requirements and as-built compliance to the design, thermal and structural analyses, computer modeling, and laboratory experimentation with the materials involved. The investigation was coordinated with Mr. Ken Jones at NASA Marshall in bi-weekly teleconferences. The Board also supported Dr. James C. Blair's independent NASA investigation team by providing copies of collected data, conducting requested analyses, and supporting several all-day teleconferences to provide understanding and resolve issues. The Dr. Blair support requirement was successfully concluded on 4 Mar. 1992.

Bjorkman, Rey C.↗
DOE OSTI2026

Operando microscopy for neuromorphic hardware

Microscopy techniques can uncover the physical properties and dynamic behaviours of materials, driving the discovery of emergent phenomena and guiding the design of next-generation computing hardware. As artificial intelligence becomes pervasive, the demand for high-performance materials to support sustainable information technologies is growing. Here, this Review highlights state-of-the-art imaging from electron and X-ray to optical techniques to probe the dynamics of neuromorphic materials, including operando characterization of devices. We examine design principles for neuromorphic materials, along with obstacles that hinder their development. Emphasis is placed on spatially and temporally resolved approaches that capture state changes including phase transitions, ferroic switching and spin-wave propagation that emulate biological components such as neurons, synapses and their connectivity. We discuss challenges in operando characterization and the integration of artificial intelligence-driven analysis for feedback-guided material discovery. Finally, we outline opportunities for real-time imaging of neuromorphic systems, paving the way towards adaptive, brain-inspired hardware.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

TCR Central Shutdown Rod Fine Motion Control

Transformational Challenge Reactor (TCR) is a Helium cooled 3 MWt test reactor that leverages advances in materials and manufacturing, computing, and AI in its design. Classical design of a shutdown rod uses either gravity, pneumatic, or springs to quickly release the Central Shutdown Rod (CSR) containing neutron absorber into the reactor core stopping nuclear reaction. Generally, the motor/actuator resides outside the reactor, but the motion is transmitted through a penetration into the pressure vessel. There are also designs where the control rod drive incorporates magnetic latches with coil residing outside the pressure boundary for precise position control of the rod. We are proposing a magnetic coupling to position the shutdown rod without any penetration into the pressure vessel for the entire drive length of TCR shutdown rod. Electromagnets are currently used in non-power nuclear reactors for shutdown rods, but these electromagnets are resident inside the reactor pressure vessel. This paper will describe the use of an electromagnet outside the pressure vessel to position and release the shutdown rod. A prototype was developed at ORNL to demonstrate the concept, and a design optimization of the ferritic core and material was conducted to maximize the lift force of the electromagnet. An elevated temperature testing was also performed to ensure that the system will perform under the temperature conditions inside an operating reactor.

Fountain, Eliott J.↗