Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Computational materials design”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
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.↗
DOE OSTI2021

Deep reinforcement learning for predicting kinetic pathways to surface reconstruction in a ternary alloy

Abstract The majority of computational catalyst design focuses on the screening of material components and alloy composition to optimize selectivity and activity for a given reaction. However, predicting the metastability of the alloy catalyst surface at realistic operating conditions requires an extensive sampling of possible surface reconstructions and their associated kinetic pathways. We present CatGym, a deep reinforcement learning (DRL) environment for predicting the thermal surface reconstruction pathways and their associated kinetic barriers in crystalline solids under reaction conditions. The DRL agent iteratively changes the positions of atoms in the near-surface region to generate kinetic pathways to accessible local minima involving changes in the surface compositions. We showcase our agent by predicting the surface reconstruction pathways of a ternary Ni 3 Pd 3 Au 2 (111) alloy catalyst. Our results show that the DRL agent can not only explore more diverse surface compositions than the conventional minima hopping method, but also generate the kinetic surface reconstruction pathways. We further demonstrate that the kinetic pathway to a global minimum energy surface composition and its associated transition state predicted by our agent is in good agreement with the minimum energy path predicted by nudged elastic band calculations.

36 MATERIALS SCIENCE↗
NASA NTRS1996

Design and implementation of a Windows NT network to support CNC activities

The Manufacturing, Materials, & Processes Technology Division is undergoing dramatic changes to bring it's manufacturing practices current with today's technological revolution. The Division is developing Computer Automated Design and Computer Automated Manufacturing (CAD/CAM) abilities. The development of resource tracking is underway in the form of an accounting software package called Infisy. These two efforts will bring the division into the 1980's in relationship to manufacturing processes. Computer Integrated Manufacturing (CIM) is the final phase of change to be implemented. This document is a qualitative study and application of a CIM application capable of finishing the changes necessary to bring the manufacturing practices into the 1990's. The documentation provided in this qualitative research effort includes discovery of the current status of manufacturing in the Manufacturing, Materials, & Processes Technology Division including the software, hardware, network and mode of operation. The proposed direction of research included a network design, computers to be used, software to be used, machine to computer connections, estimate a timeline for implementation, and a cost estimate. Recommendation for the division's improvement include action to be taken, software to utilize, and computer configurations.

Shearrow, C. A.↗
NASA NTRS1997

ICAN Computer Code Adapted for Building Materials

The NASA Lewis Research Center has been involved in developing composite micromechanics and macromechanics theories over the last three decades. These activities have resulted in several composite mechanics theories and structural analysis codes whose applications range from material behavior design and analysis to structural component response. One of these computer codes, the Integrated Composite Analyzer (ICAN), is designed primarily to address issues related to designing polymer matrix composites and predicting their properties - including hygral, thermal, and mechanical load effects. Recently, under a cost-sharing cooperative agreement with a Fortune 500 corporation, Master Builders Inc., ICAN was adapted to analyze building materials. The high costs and technical difficulties involved with the fabrication of continuous-fiber-reinforced composites sometimes limit their use. Particulate-reinforced composites can be thought of as a viable alternative. They are as easily processed to near-net shape as monolithic materials, yet have the improved stiffness, strength, and fracture toughness that is characteristic of continuous-fiber-reinforced composites. For example, particlereinforced metal-matrix composites show great potential for a variety of automotive applications, such as disk brake rotors, connecting rods, cylinder liners, and other hightemperature applications. Building materials, such as concrete, can be thought of as one of the oldest materials in this category of multiphase, particle-reinforced materials. The adaptation of ICAN to analyze particle-reinforced composite materials involved the development of new micromechanics-based theories. A derivative of the ICAN code, ICAN/PART, was developed and delivered to Master Builders Inc. as a part of the cooperative activity.

Murthy, Pappu L. N.↗
DOE OSTI2026

Finding the perfect imperfection: Accelerated, computationally driven discovery and design of quantum defects

Optically addressable spin defects have emerged as the leading platforms for quantum sensing and communication in solid-state systems. While traditional efforts have concentrated on a focused set of well-studied defects, recent advances in high-throughput computational methods have shown promise for large-scale exploration of defects across diverse semiconductor hosts. By cataloging key properties of quantum defects in computational databases, high-throughput screening techniques can systematically suggest and design novel candidates. In this article, we highlight recent advances in data-driven quantum defect design aimed at addressing critical materials science challenges such as host materials selection, defect stability, and desirable electronic and optical properties. Here, we emphasize the importance of electronic-structure-guided searches across various materials and illustrate how high-throughput computations contribute to our understanding of design principles for quantum defects. Additionally, we outline ongoing challenges and emerging opportunities in this rapidly developing field.

Xiong, Yihuang [Dartmouth College, Hanover, NH (Un↗
DOE OSTI2025

Database of Nonaqueous Proton-Conducting Materials

This work presents the assembly of 48 papers, representing 74 different compounds and blends, into a machine-readable database of nonaqueous proton-conducting materials. SMILES was used to encode the chemical structures of the molecules, and we tabulated the reported proton conductivity, proton diffusion coefficient, and material composition for a total of 3152 data points. The data spans a broad range of temperatures ranging from -70 to 260 °C. To explore this landscape of nonaqueous proton conductors, DFT was used to calculate the proton affinity of 18 unique proton carriers. The results were then compared to the activation energy derived from fitting experimental data to the Arrhenius equation. It was found that while the widely recognized positive correlation between the activation energy and proton affinity may hold among closely related molecules, this correlation does not necessarily apply across a broader range of molecules. This work serves as an example of the potential analyses that can be conducted using literature data combined with emerging research tools in computation and data science to address specific materials design problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

An Atom-Precise Approach to Damp First-Order Phase Transitions and Its Implications for Neuromorphic Signal Processing

Neuromorphic computing inspired by mammalian intelligence aims to emulate the nonlinear dynamics of biological neurons and synapses to achieve fast, low-energy, and highly efficient information processing. Brain-inspired computing relies on the design and discovery of materials exhibiting nonlinear current–voltage profiles, frequently underpinned by electronic state transitions, to achieve spiking neurons and dynamically tunable synapses. A signature challenge in the design of artificial neurons is controlling the steepness of first-order transitions in active elements, as abrupt transitions are at risk of driving unstable voltage and temperature oscillations, which result in catastrophic device failure. A critical knowledge gap is the lack of structure–function correlations mapping the composition and atomistic structure of crystalline solids to nonlinear dynamical response characteristics. Here, we address the key question of how modification of atomistic structure correlates with alteration of neuron-like functionality. Constructing oscillator circuits from millimeter-scale single crystals enables high-resolution atomic structure solutions, which we use to demonstrate that the selective positioning of Pb cations modifies charge ordering along a one-dimensional CuxV2O5 framework even at low insertion stoichiometries, thereby providing an atom-precise design parameter for damping first-order transitions. We use temperature-variant X-ray diffraction and X-ray spectroscopy to elucidate the suppression of Cu-ion shuttling based on the precise positioning of Pb ions in seven-coordinated tunnel interstitial sites as the mechanistic basis for transition broadening, thus bridging a critical gap between statistical mechanics and quantum chemical descriptions of phase transitions. Such mechanistic understanding thus paves the way to site-selective modification strategies for modulating the sharpness of first-order transitions, with an exemplary demonstration here in tuning neuronal signal processing.

Crystal structure↗
NASA NTRS1990

The NASP Program - An update

The NASP Program has made substantial technical progress and undergone significant change since the last report to the Society in 1987. This paper will focus on the technical progress that has been made in the areas of propulsion, materials, computational fluid dynamics (CFD) validation, and overall design of the X-30. The impact that the flight test community has had on the approach to the development and test of the X-30 will also be included. A short discussion of the transition to a new management and program execution process through use of a National Contractor Team will also be presented along with the new revised schedule for the overall program.

Wierzbanowski, Ted↗
NASA NTRS2000

Application of Rapid Prototyping and Wire Arc Spray to the Fabrication of Injection Mold Tools (MSFC Center Director's Discretionary Fund)

Rapid prototyping (RP) is a layer-by-layer-based additive manufacturing process for constructing three-dimensional representations of a computer design from a wax, plastic, or similar material. Wire arc spray (WAS) is a metal spray forming technique, which deposits thin layers of metal onto a substrate or pattern. Marshall Space Flight Center currently has both capabilities in-house, and this project proposed merging the two processes into an innovative manufacturing technique, in which intermediate injection molding tool halves were to be fabricated with RP and WAS metal forming.

Cooper, K. G.↗
DOE OSTI2022

Two-dimensional parametric design of short pulse laser driven iron opacity experiments

High intensity short pulse lasers are commonly used to create high temperature and high density plasmas. These plasmas are used to study fundamental properties such as the equation of state and opacity. The targets often use small-diameter, thin buried layers of the materials of interest, surrounded by a tamper of low atomic number material such as plastic. Computational modeling is used to design and interpret experiments with short pulse lasers. Most of the modeling to date has assumed one-dimensional plane-parallel geometry. In this paper, the effects of radial gradients in the irradiation of thin planar targets are studied with one- and two-dimensional radiation/hydrodynamic simulations. It is found that the main effect of radial gradients is the averaging of plasma conditions and x-ray emission over the pattern of irradiation. Additionally, differences between one- and two-dimensional simulations arise because the plasma conditions and x-ray emission are, in general, nonlinear functions of the temperature of the plasma and thereby also nonlinear functions of the irradiation intensity. The differences increase with the ratio of the buried layer radius to the laser spot radius. The root mean square difference in the inferred iron L-shell opacity is less than 30% when the ratio is less than 1.0 and about 70% when the ratio is 1.5.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1980

PASCO: Structural panel analysis and sizing code, capability and analytical foundations

A computer code denoted PASCO which can be used for analyzing and sizing uniaxially-stiffened composite panels is described. Buckling and vibration analyses are carried out with a linked-plate analysis computer code denoted VIPASA, which is incorporated in PASCO. Sizing is based on nonlinear mathematical programming techniques and employs a computer code denoted CONMIN, also incorporated in PASCO. Design requirements considered are initial buckling, material strength, stiffness, and vibration frequency. The capability of the PASCO computer code and the approach used in the structural analysis and sizing are described.

Stroud, W. J.↗
NASA NTRS1978

A Special Purpose Architecture for Finite Element Analysis

The analysis of aerospace structures by the finite element method consumes considerable computer time. The cost of this resource and the designer's desire to have rapid feedback concerning such questions as the effect of a change in loading of the structure or in a parameter of some structural material led to the design of a special purpose parallel computing system for finite element analysis. As a special purpose computer, the architecture of this finite element computer is closely tied to computational aspects of the particular problem. Various aspects of an MIMD array of microprocessors are related to the requirements of the class of finite element analysis problems which it is intended to solve.

Jordan, H. F.↗
DOE OSTI2026

Inverse design of hypoeutectoid pearlite steel microstructures using a deep learning and genetic algorithm optimization framework

Goal-oriented microstructure design in metallic materials is a challenging task due to complex structure-property relationships. Traditional experimental and computational approaches are time-intensive and economically inefficient, limiting their applicability for large-scale design space exploration. Here, in this work, we propose an end-to-end framework that integrates deep learning models with genetic optimization to design microstructures with targeted mechanical properties. Deep learning models enable accurate forward design, while their integration with genetic optimization enables efficient inverse design within a few hours, compared to days or weeks using conventional finite element simulations. The framework combines experimental characterization and finite element modeling to analyze the influence of microstructural features on the mechanical behavior of hypoeutectoid steels. Data from both experiments and simulations are used to train the deep learning models. To demonstrate its effectiveness, we apply the framework to 0.63% carbon steel with proeutectoid ferrite and pearlite phases, commonly used in industrial applications. In this study, 2D microstructures were used for modeling, selected primarily for computational efficiency and to establish proof of concept. The framework successfully optimizes microstructures for targeted yield strength, ultimate strength, and stress concentration factors while significantly reducing computational time. Beyond hypoeutectoid steels, this scalable framework can be extended to other material systems and integrated with additive manufacturing, offering an efficient approach for accelerating microstructure design for specific engineering applications.

ConvLSTM↗
DOE OSTI2020

Rechargeable Alkali-Ion Battery Materials: Theory and Computation

Since its development in the 1970s, the rechargeable alkali-ion battery has proven to be a truly transformative technology, providing portable energy storage for devices ranging from small portable electronics to sizable electric vehicles. Here, we present a review of modern theoretical and computational approaches to the study and design of rechargeable alkali-ion battery materials. Additionally, starting from fundamental thermodynamics and kinetics phenomenological equations, we rigorously derive the theoretical relationships for key battery properties, such as voltage, capacity, alkali diffusivity, and other electrochemically relevant computable quantities. We then present an overview of computational techniques for the study of rechargeable alkali-ion battery materials, followed by a critical review of the literature applying these techniques to yield crucial insights into battery operation and performance. Finally, we provide perspectives on outstanding challenges and opportunities in the theory and computation of rechargeable alkali-ion battery materials.

25 ENERGY STORAGE↗
NASA NTRS2000

NASA Tech Briefs, January 2000

Topics include: Data Acquisition; Computer-Aided Design and Engineering; Electronic Components and Circuits; Electronic Systems; Bio-Medical; Physical Sciences; Materials; Computer Programs; Mechanics; Machinery/Automation; Information Sciences; Books and reports.

Source record↗
NASA NTRS2000

NASA Tech Briefs, June 2000

Topics include: Computer-Aided Design and Engineering; Electronic Components and Circuits; Electronic Systems; Test and Measurement; Physical Sciences; Materials; Computer Programs; Computers and Peripherals;

Source record↗