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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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Ideal energy dissipating mechanisms to synthesize weight or mass index in terms of pertinent design indices, structural efficiency and material efficiency parameters
The optimization of functional materials is important to enhance their properties, but their complex geometries pose great challenges to optimization. Data-driven algorithms efficiently navigate such complex design spaces by learning relationships between material structures and performance metrics to discover high-performance functional materials. Surrogate-based active learning, continually improving its surrogate model by iteratively including high-quality data points, has emerged as a cost-effective data-driven approach. Furthermore, it can be coupled with quantum computing to enhance optimization processes, especially when paired with a special form of surrogate model (i.e., quadratic unconstrained binary optimization), formulated by factorization machine (FM). However, current practices often overlook the variability in design space sizes when determining the initial data size for optimization. In this work, we investigate the optimal initial data sizes required for efficient convergence across various design space sizes. By employing averaged piecewise linear regression, we identify initiation points where convergence begins, highlighting the crucial role of employing adequate initial data in achieving efficient optimization. These results contribute to the efficient optimization of functional materials by ensuring faster convergence and reducing computational costs in FM-based active learning.
The accelerating pace and expanding scope of materials discovery demand optimization frameworks that efficiently navigate vast design spaces with complex response surfaces while judiciously allocating limited evaluation resources. We present a cost-aware, batch Bayesian optimization scheme powered by deep Gaussian process (DGP) surrogates and a heterotopic querying strategy. Our DGP surrogate, formed by stacking GP layers, models complex hierarchical relationships among high-dimensional compositional features and captures correlations across multiple target properties, propagating uncertainty through successive layers. We integrate evaluation cost into an upper-confidence-bound acquisition extension, which, together with heterotopic querying, proposes small batches of candidates in parallel, balancing exploration of under-characterized regions with exploitation of high-mean, low-variance predictions across correlated properties. Applied to refractory high-entropy alloys for high-temperature applications, our framework converges to optimal formulations in fewer iterations with cost-aware queries than conventional GP-based BO, highlighting the value of deep, uncertainty-aware, cost-sensitive strategies in materials campaigns.
The development of Vertical Take-off and Landing (VTOL) vehicles for the Urban Air Mobility (UAM) markets presents a need for light weight vehicle structures with effective occupant protection capabilities. The National Aeronautics and Space Administration (NASA) has been working to fill that need, recently developing a cadre of concept vehicles to help characterize UAM design feasibility. This paper describes a study, using these concept vehicles, to evaluate the use of advanced composite structure and energy attenuating designs in the UAM vehicle design space. A finite element model (FEM) of a single passenger quadrotor concept vehicle was developed in LS-Dyna® and simulated under nominal and off-nominal vertical impact conditions. A variety of energy attenuating design mechanisms were implemented within this model to quantify their effectiveness in improving occupant safety. The use of carbon composites in both the energy attenuation mechanisms and vehicle structure was evaluated. The results of this study found significant reduction in occupant injury risk with the implementation of energy absorbing composite crush tubes and landing gear within the vehicle design. Additionally the use of a carbon fiber as a structural material was found to provide significant weight reduction while maintaining similar occupant loads to that predicted with an aluminum structure. This work provides a preliminary evaluation of design mechanisms and materials that may be used to optimize occupant protection capabilities within the UAM market.
NASA missions push the limits of what is possible. The development of high-performance materials must keep pace with the agency's demanding, cutting-edge applications. Researchers at NASA's Ames Research Center are performing multiscale computational modeling to accelerate development times and further the design of next-generation aerospace materials. Multiscale modeling combines several computationally intensive techniques ranging from the atomic level to the macroscale, passing output from one level as input to the next level. These methods are applicable to a wide variety of materials systems. For example: (a) Ultra-high-temperature ceramics for hypersonic aircraft-we utilized the full range of multiscale modeling to characterize thermal protection materials for faster, safer air- and spacecraft, (b) Planetary entry heat shields for space vehicles-we computed thermal and mechanical properties of ablative composites by combining several methods, from atomistic simulations to macroscale computations, (c) Advanced batteries for electric aircraft-we performed large-scale molecular dynamics simulations of advanced electrolytes for ultra-high-energy capacity batteries to enable long-distance electric aircraft service; and (d) Shape-memory alloys for high-efficiency aircraft-we used high-fidelity electronic structure calculations to determine phase diagrams in shape-memory transformations. Advances in high-performance computing have been critical to the development of multiscale materials modeling. We used nearly one million processor hours on NASA's Pleiades supercomputer to characterize electrolytes with a fidelity that would be otherwise impossible. For this and other projects, Pleiades enables us to push the physics and accuracy of our calculations to new levels.
The design requirements for the Orbiter thermal protection system (TPS), the various TPS materials that are used, the different design approaches associated with each of the materials, and the performance experienced during the flight test program are described. The first five flights of the Orbiter Columbia have provided the necessary data to verify the TPS thermal performance, structural integrity, and reusability. The flight performance characteristics of each TPS material are discussed. This discussion is based on postflight inspections and postflight interpretation of the flight instrumentation data. The flights to date indicate that the thermal and structural design requirements for the Orbiter TPS have been met and that the overall performance has been outstanding.
Additive Manufacturing (AM) is expected to play a large role in the labs-wide goals of accelerating innovation and leading in modern engineering. More specifically, AM is seen as a key enabling technology for increasing the agility of nuclear deterrence and other national security applications involving complex coupled environments. However, the impact of AM on these initiatives has not been as wide-ranging as hoped because – despite its unique qualities – the focus has mostly been on detailed qualification to force AM components into pre-existing performance envelopes. This paradigm fundamentally precludes the novel possibilities afforded by the geometric and material flexibility of AM. In particular, the engineering of small-scale features to undergo buckling and contact can cause large geometric and symmetry changes which provide responsiveness to different environments. Despite almost a decade of observing such behavior, there exists no way to systematically design for AM to exploit it. Our goal for this project was to connect material design to multi-environment component performance by reconceptualizing how to design for AM to exploit the buckling and contact of small-scale features.
This paper is a study of optimal experiment design applied to the measure of thermal properties in functionally graded materials. As a first step, a material with linearly-varying thermal properties is analyzed, and several different tran- sient experimental designs are discussed. An optimality criterion, based on sen- sitivity coefficients, is used to identify the best experimental design. Simulated experimental results are analyzed to verify that the identified best experiment design has the smallest errors in the estimated parameters. This procedure is general and can be applied to design of experiments for a variety of materials.
This project was aimed at developing innovative theoretical methods and models to understand essential catalysis-relevant issues such as CO 2 conversion, fuel cells, and lithium batteries. Through collaborations with experimentalists, we strive to develop new quantum and machine learning methods for the understanding of surface and interfacial chemistry that can empower the design of energy and sustainability systems. Overall, our work under this grant brings cross-disciplinary insights into catalytic materials, microenvironments, and other conditions, which can serve to provide design rules for the next generation of catalysts.
Functionally graded materials (FGMs) are highly advanced continuous or discontinuous structures whose structural and material properties vary along a singular geometric dimension either in the axial or radial direction. Here, the radial gradient FGM design makes for an optimal structural design to incorporate a bi-metallic structure with a copper-based high entropy alloy (Cu-HEA) with good mechanical properties and high irradiation resistance, and Chromium (Cr) with great corrosion resistance. This study focuses on the experimental design of a metal powder loading mechanism to fabricate a bi-metallic radial gradient structure using Cu-HEA and 99.9 % pure Cr metal powders. The powder loading strategy uses custom-designed concentric cylindrical dividers to separate the individual compositions. Two benchtop trial runs were performed for design optimization. The optimized design was then implemented to eventually load the HEA and Cr powders for consolidation via powder metallurgy hot isostatic pressing (PM-HIP). The electron microscopy analysis reveals the successful fabrication of the radial gradient structure with the chemical mapping analysis, demonstrating the gradual composition shift from the HEA at the center to the pure-Cr at the periphery via a three-step gradient.
Rapid advances in additive manufacturing (AM) have enabled the creation of micro-architected materials—also known as mechanical metamaterials—with unprecedented control over fine-scale geometries and arrangements of multiple material constituents. These “materials” can achieve unique and extraordinary effective mechanical properties through their complex architectures rather than composition alone. A key challenge is to design for these bespoke effective mechanical responses within the constraints of available AM techniques (i.e., given a set of desired effective properties), identify a (often nonunique) micro-architecture and selection of material constituents that achieves them. Two main strategies have emerged. Gradient-based methods use sensitivity analysis to iteratively refine candidate designs, while data-driven methods learn micro-architecture-constituent relationships from existing examples to propose new designs. This article reviews these design approaches for micro-architected materials with tailored mechanical responses that can be fabricated by AM as well as their applications.
Overview of NASA Transformational Tools and Technologies Project's 2700F CMC/EBC Technology Challenge J. Hurst, NASA (National Aeronautics and Space Administration, Glenn Research Center, Cleveland, OH USA Key Words: ceramic matrix composites (CMCs), SiC/SiC composites, environmental barrier coatings (EBCs), CMC modeling, simulated engine testing As advanced gas turbine engine designs continue to move toward both higher operating temperatures and increased pressures, materials capable of functioning under these extreme conditions are being sought by both government and industry. As part of its mission, the NASA's Transformational Tools and Technologies Project, under the auspices of NASA's Aeronautics Research Mission Directorate, has been pursuing a five year Technology Challenge problem. This challenge problem has sought to develop high temperature materials for turbine engines that enable a 6% reduction in fuel burn for commercial aircraft, compared to current SOA materials. Specifically this is accomplished by the development and demonstration of a ceramic matrix composite (CMC) and environmental barrier coating (EBC) system capable of sustained performance at temperature of 2700F. The NASA Glenn Research Center has continued its two decade long interest in CMC/EBCs technology by pursuing this 2700F performance goal. This ambitious effort included an array of vendors, universities and engine companies. Included in this challenge was fiber development, fiber architecture considerations, ceramic matrix composition, environmental barrier compositions and processing routes as well as test development. Evaluation of the CMC/EBC materials included a variety of testing, from coupon testing for strength and creep resistance, to testing aimed at determining material behavior under more engine-like conditions. The development and validation of thermomechanical models and computational tools for design, analysis, and life prediction, have been an important part of this effort as well. Simulated engine testing of vane subcomponents by P&W was the final step following years of development. In addition to achieving the temperature goals and enhanced durability performance of the Tech Challenge, an additional goal achieved by this work was reaching a Technology Readiness Level of 5 for the 3-D CMC/EBC system. As this five year Technical Challenge comes to a conclusion, future development interests in environmental barrier coatings and environmental modeling are discussed.
In this paper numerical calculations are presented for the steady-periodic temperature in layered materials and functionally-graded materials to simulate photothermal methods for the measurement of thermal properties. No laboratory experiments were performed. The temperature is found from a new Green s function formulation which is particularly well-suited to machine calculation. The simulation method is verified by comparison with literature data for a layered material. The method is applied to a class of two-component functionally-graded materials and results for temperature and sensitivity coefficients are presented. An optimality criterion, based on the sensitivity coefficients, is used for choosing what experimental conditions will be needed for photothermal measurements to determine the spatial distribution of thermal properties. This method for optimal experiment design is completely general and may be applied to any photothermal technique and to any functionally-graded material.
Efficient energy storage systems are crucial to address the intermittency of renewable energy sources. As multivalent batteries, Zn-ion batteries (ZIBs), while inherently low voltage, offer a promising low-cost alternative to Li-ion batteries due to the viable use of zinc as the anode. However, to maximize the potential impact of ZIBs, rechargeable cathodes with improved Zn diffusion are needed. To better understand the chemical and structural factors influencing Zn-ion mobility within battery electrode materials, we employ a high-throughput computational screening approach to systematically evaluate candidate intercalation hosts for ZIB cathodes, expanding the chemical search space on empty intercalation hosts that do not contain Zn. We leverage a high-throughput screening funnel to identify promising cathodes in ZIBs, integrating screening criteria with density functional theory (DFT)-based calculations of Zn2+ intercalation and diffusion inside the host materials. Using these data, we identify the design principles that favor Zn-ion mobility in candidate cathode materials. Building on previous work on divalent-ion cathodes, this study broadens the chemical space for next-generation multivalent energy storage systems.
The objective of the 2003 study is to develop a mechanically processed, high temperature TiAl alloy for use in the Turbine Based Combined Cycle compressor. An aging study with 3 temperatures and 4 time periods at each temperature will be conducted to determine the optimum aging condition. High-magnification microscopic analyses shall be employed to define the size distribution of carbide as a function of aging temperature/time. The contractor shall define optimum materials' conditions by conducting tensile and creep testing for two over-aging conditions for both alloys and fatigue testing for one over-aging condition for each alloy.
One major obstacle to human space exploration is the possible limitations imposed by the adverse effects of long-term exposure to the space environment. Even before human spaceflight began, the potentially brief exposure of astronauts to the very intense random solar energetic particle (SEP) events was of great concern. A new challenge appears in deep space exploration from exposure to the low-intensity heavy-ion flux of the galactic cosmic rays (GCR) since the missions are of long duration and the accumulated exposures can be high. Since aluminum (traditionally used in spacecraft to avoid potential radiation risks) leads to prohibitively expensive mission launch costs, alternative materials need to be explored. An overview of the materials related issues and their impact on human space exploration will be given.
H 2 production using proton exchange membrane (PEM) water electrolysis (PEMWE) cells has received considerable attention because of the high efficiencies of these cells and no harmful emissions from the related process. In PEMWE cells, porous transport electrodes (PTEs) composed of a catalyst layer (CL) comprising O 2 evolution reaction (OER) catalysts, porous transport layer (PTL), and PEM play key roles in the stack performance and lifetime. Herein, Ir-based and non-precious-metal OER catalysts that are highly active and stable at low pH values and high anodic potentials are reviewed to understand their OER mechanisms. Various strategies are proposed for engineering CLs and PTLs to improve the interfacial properties and mass transfers of reactants and products to and from the active sites. Additionally, diagnoses of PTEs is significantly crucial for interpreting electrochemical processes and addressing their current challenges. Therefore, half-cell analyses, including diffusion electrode (DE), floating electrode (FE), and modified rotating disk electrode (MRDE) techniques, are explored, and membrane electrode assembly (MEA)-based analyses, such as the polarization technique, electrochemical impedance spectroscopy, and magnetic field analysis, are established. In conclusion, this study aims to provide an overview of recent technologies used for the engineering and diagnostic tools of PEMWE cells and insights into the advanced components and systems to be developed in this field.
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