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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Application of Guided Acoustic Waves to Delamination Detection

The occurrence of delamination in laminate structures is one of the major reliability concerns for using these materials. There are continuing needs for developing delamination inspection techniques to measure specimens of various material structure as well as to accommodate different test environments. In the case of disbond-detection in the skin of an aircraft, for some practical reasons, an efficient technique should be capable of inspecting a large surface area in a reasonably short amount of time and with a high degree of accuracy. While most existing measurements can provide satisfactory accuracy, the required high inspection rate may not be met. Thus, for assessment of large surface area with an ultrasonic technique, our approach is to generate sound waves of particular modes, which are capable of propagating in a relatively extended area on the surface of a plate and at meantime interrogating the structural integrity of the plate. It is well known in waveguide theory [1-3] that certain modes of sound waves are capable of propagating a relatively long distance in a material of plate configuration, and that their propagation properties are determined in part by the product of sound frequency and plate thickness. Recently, it was found experimentally that, with this thickness dependence, certain modes of these plate waves provided a different approach to probe the flaws in a laminate structure, and with potential application to the large area disbond and crack inspection.

Sun, Keun J.↗
DOE OSTI2023

Phase-Field Modeling of Materials Interfaces and Nanostructures

Nanostructured materials offer unique properties for a wide range of energy applications. Among various known processing methods, liquid metal dealloying (LMD)—the selective dissolution of a base alloy element into a metallic melt—has emerged as a powerful technique to produce a new class of nano-/meso-scale open porous and bicontinuous composite structures with ultra-high interfacial area. LMD has recently been complemented by the advent of vapor phase dealloying (VPD), a novel technique that exploits the selective evaporation of one element from a parent alloy containing elements with very different vapor pressures, thereby enabling to fabricate open nanoporous structures of various elements from less-noble metals to inorganic elements regardless of their chemical activity without requiring high LMD temperatures and chemical etching. Together LMD and VPD have greatly expanded the scope of dealloying techniques, limited by traditional electrochemical means to noble metals, and boosted the design of new functional and structural materials that combine a wide variety of elements. Topologically-connected open porous structures with ultra-high surface area allow mass transport within the structure while preserving structural integrity, enabling them to serve as catalysts, fuel cells, supercapacitors, or high-capacity battery materials. Bicontinuous composite structures in turn can display high strength and high ductility or superior radiation-damage resistance due to the ultra-high interface area between interpenetrating solid phases. This research program makes use of state-of-the-art computational methods to understand at a basic level the self-organizing dealloying process with main focus on dealloying kinetics and interfacial pattern formation at the dealloying front controlling initial structure size, topology, and phase compositions. Phase-field simulation studies of LMD focus on solid solutions, line compounds, and intermetallic systems that can form ternary composites by nucleation and growth of a new phase. Studies of VPD employ phase-field modeling and a hybrid method combining a kinetic Monte Carlo (KMC) model of evaporation and surface diffusion with molecular dynamics for vapor-phase transport inside nanopores. Simulations explore mechanisms of interface- and diffusion-controlled dealloying kinetics, both observed in VPD but not fundamentally understood. In addition, our newly developed multi-physics phase-field approach of large-volume-change phase transformations is being used to model novel 3D anode geometries based on dealloyed nanoporous structures including novel sandwiched graphene/Si/silica for highrate Li ion battery. Those studies are aimed at elucidating geometric design principles that improve mechanical stability. We expect this research to enhance the capability to tailor nano-/mesoscale structures for a wide range of energy-related materials applications and to yield further advances in computational methodologies that benefit a broad materials research community.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Deformation, dislocation evolution and the non-Schmid effect in body-centered-cubic single- and polycrystal tantalum

A physically-informed continuum crystal plasticity model is presented to elucidate deformation mechanisms, dislocation evolution and the non-Schmid effect in body-centered-cubic (bcc) tantalum widely used as a key structural material for mechanical and thermal extremes. We show the unified structural modeling framework informed by mesoscopic dislocation dynamics simulations is capable of capturing salient features of the large inelastic behavior of tantalum at quasi-static (10 -3 s -1 ) to extreme strain rates (5000 s -1 ) and at low (77 K) to high temperatures (873 K) at both single- and polycrystal levels. Here we also present predictive capabilities of the model for microstructural evolution in the material. To this end, we investigate the effects of dislocation interactions on slip activities, instability and the non-Schmid behavior at the single crystal level. Furthermore, ex situ measurements on crystallographic texture evolution and dislocation density growth are carried out for polycrystal tantalum specimens at increasing strains. Numerical simulation results also support that the modeling framework is capable of capturing the main features of the polycrystal behavior over a wide range of strains, strain rates and temperatures. The theoretical, experimental and numerical results at both single- and polycrystal levels provide critical insight into the underlying physical pictures for micro- and macroscopic responses and their relations in this important class of refractory bcc materials undergoing large inelastic deformations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Production and validation of scintillating structural components from low-background Poly(ethylene naphthalate)

Poly Ethylene Naphthalate (PEN) is an industrial polymer plastic which is investigated as a low background, transparent, scintillating and wavelength shifting structural material. PEN scintillates in the blue region and has excellent mechanical properties both at room and cryogenic temperatures. Thus, it is an ideal candidate for active structural components in experiments for the search of rare events like neutrinoless double-beta decay or dark matter recoils. Such optically active structures improve the identification and rejection efficiency of backgrounds events, like this improving the sensitivity of experiments. This paper reports on the production of radiopure and transparent PEN plates These structures can be used to mount germanium detectors operating in cryogenic liquids (LAr, LN). Thus, as first application PEN holders will be used to mount the Ge detectors in the LEGEND-200 experiment. The whole process from cleaning the raw material to testing the PEN active components under final operational conditions is reported.

47 OTHER INSTRUMENTATION↗
NASA NTRS1985

Damage and Repair of Composite Structures

NASA technical memorandum reports on research in damage and repair of composite-material structures of types used in airplane. Research includes: Identifying defect areas, determining whether particular kind of damage weakens structure in manner that degrades performance in intended application, developing repair procedures, and testing to demonstrate given repair procedure enables component to serve during remainder of its design life.

Deaton, J. W.↗
NASA NTRS1987

Materials analysis by ultrasonics: Metals, ceramics, composites

Research results in analytical ultrasonics for characterizing structural materials from metals and ceramics to composites are presented. General topics covered by the conference included: status and advances in analytical ultrasonics for characterizing material microstructures and mechanical properties; status and prospects for ultrasonic measurements of microdamage, degradation, and underlying morphological factors; status and problems in precision measurements of frequency-dependent velocity and attenuation for materials analysis; procedures and requirements for automated, digital signal acquisition, processing, analysis, and interpretation; incentives for analytical ultrasonics in materials research and materials processing, testing, and inspection; and examples of progress in ultrasonics for interrelating microstructure, mechanical properties, and dynamic response.

Vary, Alex↗
DOE OSTI2020

Scalable Deep-Learning-Accelerated Topology Optimization for Additively Manufactured Materials

Topology optimization (TO) is a popular and powerful computational approach for designing novel structures, materials, and devices. Two computational challenges have limited the applicability of TO to a variety of industrial applications. First, a TO problem often involves a large number of design variables to guarantee sufficient expressive power. Second, many TO problems require a large number of expensive physical model simulations, and those simulations cannot be parallelized. To address these issues, we propose a general scalable deep-learning (DL) based TO framework, referred to as SDL-TO, which utilizes parallel schemes in high performance computing (HPC) to accelerate the TO process for designing additively manufactured (AM) materials. Unlike the existing studies of DL for TO, our framework accelerates TO by learning the iterative history data and simultaneously training on the mapping between the given design and its gradient. The surrogate gradient is learned by utilizing parallel computing on multiple CPUs incorporated with a distributed DL training on multiple GPUs. The learned TO gradient enables a fast online update scheme instead of an expensive update based on the physical simulator or solver. Using a local sampling strategy, we achieve to reduce the intrinsic high dimensionality of the design space and improve the training accuracy and the scalability of the SDL-TO framework. The method is demonstrated by benchmark examples and AM materials design for heat conduction. The proposed SDL-TO framework shows competitive performance compared to the baseline methods but significantly reduces the computational cost by a speed up of around 8.6x over the standard TO implementation.

Bi, Sirui↗
DOE OSTI2026

On the uncertainties in helium generation predictions for fission and fusion alloys

With ongoing advances in fusion and advanced fission reactors, quantifying irradiation effects in materials is critical. Transmutation-induced helium in cladding and structural materials can drive swelling and embrittlement, thereby reducing these components’ lifespans. Yet most studies ignore the considerable uncertainties in predicting helium generation rates. In this work, we created a code wrapper, F-SCATTER, that automatically performs simulations in FISPACT-II. We used this tool to investigate potential variance in helium generation rate, or He/dpa, calculations based on deviations in alloy composition, irradiating neutron flux spectrum, computational methodology, and nuclear data sources. We used 12 wt% Cr HT9 steel as the reference case and observed a 6.5%–98.3% He/dpa spread based on compositional variation within a single chemical specification, a 1.8%–11.5% He/dpa variation upon the incorporation of a 15% artificial uncertainty in flux at each energy, and a He/dpa difference as high as 231% when using ENDF/B-VIII.0 versus TENDL-2021 data libraries. Similar results were found for other prominent iron-based alloys, including Grade 91, castable nano-structured alloy, and 316H—where additional variations exist based on reactor type (e.g. thermal, fast, or fusion) and alloying elements such as carbon, nitrogen, and nickel. Based on the simulated results, we conclude that a significant part of the heat-to-heat variability in swelling responses of Fe-based alloys can be driven by impurity content in alloy compositions, and, therefore, chemical control should be a key element in supply chain design for advanced nuclear energy systems. Furthermore, we provide critical recommendations on best practices for evaluating and reporting helium production and lattice damage rates when computing predictions with multiphysics programs such as FISPACT-II.

FISPACT-II↗
DOE OSTI2020

Applying Dynamic Strain on Thin Oxide Films Immobilized on a Pseudoelastic Nickel-Titanium Alloy

Direct alteration of materials structure/function through strain is a burgeoning area of research that has allowed for novel properties of materials to emerge. Tuning materials structure can be achieved by controlling an external force imposed on materials and inducing stress-strain responses (i.e., applying dynamic strain). Electroactive thin films are typically deposited on shape or volume tunable elastic substrates, where mechanical loading (i.e. compression or tension) can affect films structure and function through imposed strain. Here we summarize methods for straining n-type doped titanium dioxide (TiO2) films prepared by a thermal treatment of a pseudo-elastic nickel-titanium alloy. The main purpose of the described methods is to study how strain affects electrocatalytic activities of metal oxide, specifically hydrogen evolution and oxygen evolution reactions. The same system can be adapted to study the effect of strain more broadly. Strain engineering can be applied for optimization of a material function, as well as for design of adjustable, multifunctional (photo)electrocatalytic materials under external stress control.

92 SC - Basic Energy Sciences (BES) (SC-22)↗
DOE OSTI2020

Determination of Stress-Free Lattice Spacing (D₀) for Residual Stress Relaxation Measurement in Ni-based Superalloys by Neutron Diffraction

The residual stress and its relaxation in critical engineering components are key to structural materials reliability. The determination of residual stress in bulk engineering structures like Ni-based superalloys can be conducted by measuring the lattice strain with penetrating neutron diffraction. The state-of-the-art engineering diffraction beamline VULCAN at the Oak Ridge National Laboratory (ORNL) Spallation Neutron Source (SNS) provides the critical capability to evaluate the residual strain/stress relaxation in engineering component thanks to the high flux and event data features. By the means of residual stress/strain calculation, it is critical to accurately determine the stress-free lattice spacing d₀, which can be altered by the change of chemistry, unrelieved stress, and measurement scheme. Here we reported d₀ determination for determining residual stress relaxation and distribution in Alloy 718 superalloys after different quenching treatments. Selection of locations for d₀ measurement was discussed by considering the neutron path, attenuation and sample alignment. A dynamic d₀ that resulted from atom diffusion and chemistry change was estimated as function of time for the in-situ relaxation characterization. It demonstrated how the dynamic d₀ values may influence on the strain calculation in different thermally treated samples. The results highlight the importance of dynamic d₀ for in-situ relaxation involving chemical changes and provide guidance to the dynamic d₀ measurement and simulation.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Experimental and Analytical Verification of ASME Section IiII Division 5 Creep-Fatigue Design Rules

The continuous advancement of structural materials and the growing demands for more reliable and economical structural components in high-temperature reactor applications have necessitated the development of comprehensive design methodologies and design rules. Mechanical degradation of structural components at elevated temperatures subjected to cyclic deformation is controlled by the creep-fatigue damage. Over the past few decades, diligent research efforts have been dedicated to refining the development of elevated temperature design rules in the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code (BPVC), Section III, Division 5 and to develop conservative design rules that can effectively guard against the risk of creep-fatigue failure. In ASME Section III, Division 5, for a design to pass the creep-fatigue acceptance criteria, creep damage and fatigue damage are evaluated separately, and these damages must not violate the bi-linear creep-fatigue interaction diagram, i.e., the so-called D-diagram. The creep-fatigue damage evaluation procedure assumes that the effects of the actual cyclic loading sequence can be bounded by assuming that the individual loading cycles are uniformly distributed throughout the component design life. In this study, creep-fatigue experiments with variable amplitudes and loading sequencies were designed and performed on Alloy 617 at high temperatures. The results were analyzed to evaluate the loading history effect on creep-fatigue damage accumulation and to verify the assumptions for the creep-fatigue evaluation design rules.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Factorization Machine‐Based Active Learning for Functional Materials Design with Optimal Initial Data

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.

active learning↗
DOE OSTI2024

Phonon modal analysis of thermal transport in ThO 2 with point defects using equilibrium molecular dynamics

Defects can significantly degrade the thermal conductivity of ThO 2 , an advanced nuclear fuel material as well as a surrogate for other fluorite-structured materials. Here, we investigate how point defects in ThO 2 impact phonon mode-resolved thermal transport. By incorporating phonon modes from lattice dynamics, we decompose the trajectory and heat flux to phonon normal mode space and extract key phonon properties, including phonon relaxation times and their contributions to thermal conductivity. We implement two methods. The first method is based on the Green Kubo formalism to resolve the contribution of each phonon mode to thermal conductivity. The second resolves the lifetime of individual phonon modes and the thermal conductivity is calculated using the Boltzmann transport equation within relaxation time approximation. Notably, a lower contribution of acoustic modes is revealed compared to perturbative approaches considering only three-phonon scattering processes. The effects of four types of point defects are evaluated. The strongest impact on a reduction in thermal conductivity is from Th interstitials, followed by Th vacancies. O interstitials/vacancies have a similar impact, albeit smaller than defects on the thorium sublattice. These observations are consistent with previous studies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Defect diffusion graph neural networks (d2gnn)

SAND2025-01004O Defect Diffusion Graph Neural Networks (d2gnn) is a software tool that assists in the discovery of new materials for high-temperature, clean-energy applications. It uses advanced graph neural networks to model the relationship between material structures and their defect properties. The application helps predict how materials will behave under different conditions and accelerates the development of innovative materials. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Witman, Matthew [Sandia National Lab. (SNL-CA), Li↗
DOE OSTI2023

Research Plan and Preliminary Results in Developing the Fabrication Parameters for Alloy 709 in Different Product Forms―Grain Coarsening Temperature Evaluation

The Advanced Reactor Technologies (ART) Program has established a multi-year plan to develop Alloy 709 advanced stainless steel (A709), generate the data package and develop material-specific design parameters in qualifying it as a new structural material for Class A component design in the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code, Section III, Division 5, High Temperature Reactors. In collaboration with material vendors, the Advanced Materials Development activities under ART have successfully scaled the A709 plate form production from a laboratory heat of 500 pounds to commercial heats totaling 133,000 pounds of A709 plate fabricated from three heats. The goal of the overall A709 development program is to establish the necessary microstructural and mechanical properties relationship for A709 to ultimately develop fabrication parameters for other product forms such as bars, piping and forging using the available ART A709 materials. The objective of this A709 development work at ORNL in FY2023 is to experimentally determine grain coarsening behavior for the A709 heats and to experimentally generate the continuous cooling precipitation (CCP) diagram for A709 using the as-rolled commercial heat plate materials. Integral to this work is the characterization of the as-rolled materials and the determination of an effective solution annealing process. This report summarizes the work performed to identify the grain coarsening temperature for commercial heat 58776-3RB fabricated by G. O. Carlson and heat 529900-02 fabricated by Allegheny Technologies Incorporated (ATI) Flat Rolled Products.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Towards Thermomechanical Processing of Alloy 709: Progress in Defining High-Temperature Deformation-Recrystallization "Space"

The Advanced Reactor Technologies (ART) Program has established a multi-year plan to develop Alloy 709 advanced stainless steel, generate the data package and develop material-specific design parameters in qualifying it as a new structural material for Class A construction in the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code, Section III, Division 5, High Temperature Reactors (ASME 2025). In collaboration with material vendors, the Advanced Materials Development activities under ART have successfully scaled the Alloy 709 plate form production from a laboratory heat of 500 pounds to commercial heats totaling 133,000 pounds of Alloy 709 plate fabricated from three heats. The goal of the overall Alloy 709 development program is to establish the necessary microstructural and mechanical properties relationship for Alloy 709 to ultimately develop fabrication parameters for other product forms such as bars, pipes, and forgings using the available ART Alloy 709 materials. This study will enable its deployment in the industry as an advanced construction material for high-temperature components. The objective of this Alloy 709 development work in FY 2025 is to experimentally determine the high-temperature deformation-recrystallization response of the Alloy 709 heats and to experimentally generate true stress-true strain data for Alloy 709 using the available commercial heat plate materials. Integral to this work is the previous characterization of the as-rolled materials and the determination of an effective solution-annealing process, which was reported in Y. Wang et al., 2023, and the evaluation of the effect of controlled cooling on the resultant precipitation in these commercial heats. This report summarizes and builds on the results of the previous reports to assess the high-temperature deformation behavior as a function of deformation temperature, strain and strain rate using commercial Alloy 709 heat 58776-3RB fabricated by G. O. Carlson and heat 529900-02 fabricated by Allegheny Technologies Incorporated (ATI) Specialty Rolled Products.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Remaining Useful Strength (RUS) Prediction of SiCf-SiCm Composite Materials Using Deep Learning and Acoustic Emission

Prognosis techniques for prediction of remaining useful life (RUL) are of crucial importance to the management of complex systems for they can lead to appropriate maintenance interventions and improvements in reliability. While various data-driven methods have been introduced to predict the remaining useful life (RUL) of machinery systems or batteries, no research has been reported on the remaining useful strength (RUS) prediction of silicon carbide fiber reinforced silicon carbide matrix (SiCf-SiCm) materials with pivotal role in its potential usage as a structural material in nuclear reactors and turbine engines. Knowledge of its degradation process is of the utmost importance to the manufacturers. For this purpose, two approaches based on the machine-learning techniques of random-forest (RF) and convolutional neural network (CNN) are proposed to predict the RUS of SiCf-SiCm using only acoustic emission (AE) signals generated during the material’s stress applying process. Experimental results show that the CNN models achieved better predictive performance than the RF models but the latter with expert-engineered features achieves better prediction for AE signals in the early stage of degradation. Additionally, our results demonstrate that both models can correctly predict the SiCf-SiCm RUS as evaluated by our robust testing method from which the best average root mean square error (RMSE) and Pearson correlation coefficient of 3.55 ksi units and 0.85 were obtained.

36 MATERIALS SCIENCE↗
NASA NTRS1995

BMDO materials testing in the EOIM-3 experiment

The NASA Evaluation of Oxygen Interactions with Materials-3 (EOIM-3) experiment served as a testbed for a variety of materials that are candidates for Ballistic Missile Defense Organization (BMDO) space assets. The materials evaluated on this flight experiment were provided by BMDO contractors and technology laboratories. A parallel ground-based exposure evaluation was conducted using the Fast Atom Sample Tester (FAST) atomic-oxygen simulation facility at Physical Sciences, Inc. The EOIM-3 flight materials were exposed to an atomic oxygen fluence of approximately 2.3 x 10(exp 20) atoms/sq cm. The ground-based exposure fluence of 2.0 - 2.5 x 10(exp 20) atoms/sq cm permits direct comparison with that of the flight-exposed specimens. The results from the flight test conducted aboard STS-46 and the correlative ground-based exposure are summarized here. A more detailed correlation study is presented in the JPL Publication 93-31 entitled 'Flight-and Ground-Test Correlation Study of BMDO SDS Materials: Phase 1 Report'. In general, the majority of the materials survived the AO environment with their performance tolerances maintained for the duration of the exposure. Optical materials, baffles, and coatings performed extremely well as did most of the thermal coatings and tribological materials. A few of the candidate radiator, threat shielding, and structural materials showed significant degradation. Many of the coatings designed to protect against AO erosion of sensitive materials performed this function well.

Chung, Shirley Y.↗