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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Two-Dimensional Nonlinear Finite Element Analysis of CMC Microstructures

A research program has been developed to quantify the effects of the microstructure of a woven ceramic matrix composite and its variability on the effective properties and response of the material. In order to characterize and quantify the variations in the microstructure of a five harness satin weave, chemical vapor infiltrated (CVI) SiC/SiC composite material, specimens were serially sectioned and polished to capture images that detailed the fiber tows, matrix, and porosity. Open source quantitative image analysis tools were then used to isolate the constituents, from which two dimensional finite element models were generated which approximated the actual specimen section geometry. A simplified elastic-plastic model, wherein all stress above yield is redistributed to lower stress regions, is used to approximate the progressive damage behavior for each of the composite constituents. Finite element analyses under in-plane tensile loading were performed to examine how the variability in the local microstructure affected the macroscopic stress-strain response of the material as well as the local initiation and progression of damage. The macroscopic stress-strain response appeared to be minimally affected by the variation in local microstructure, but the locations where damage initiated and propagated appeared to be linked to specific aspects of the local microstructure.

Mital, Subodh K.↗
DOE OSTI2022

A thermochemical study of iron aluminate-based materials: a preferred class for isothermal water splitting

The use of hydrogen as a renewable fuel has been stymied by our inability to produce it cleanly and economically. The conventional solar thermochemical approach considers a two-step redox cycle with benchmark ceria or a perovskite in a temperature swing configuration, where reduction occurs at a temperature much higher than oxidation. Isothermal redox cycling is feasible and avoids the solid–solid heat recuperation and material stability challenges associated with temperature swing; yet, it has long been thought to be inefficient due to the thermodynamic unfavorability of operating the exothermic oxidation reaction at higher temperatures. Here, in this work, we show that this setback can be overcome with iron aluminate-based spinel solid solutions that preferentially exhibit large changes in oxygen content within the range of oxygen partial pressures expected in large-scale systems. We explain the experimental results with a defect model that assigns cation – not oxygen – vacancies as the predominant point defect responsible for their superior water-splitting ability. When operated isothermally at 1400 °C, the iron aluminate-based materials demonstrate a capacity for hydrogen production greater than 500 μmol g–1 and, as a result, remain viable even under high conversion conditions (i.e., pO 2 < 500 : 1 H 2 O : H 2 ), exceeding the hydrogen yields of ceria and two attractive perovskite candidates following a 400 °C (or less) temperature swing. Isothermal water splitting using iron aluminate-based materials opens the door for more simple, robust, and efficient production of renewable hydrogen.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Machine Intelligence-Centered System for Automated Characterization of Functional Materials and Interfaces

Classic design of experiment relies on a time-intensive workflow that requires planning, data interpretation, and hypothesis building by experienced researchers. Here, in this paper, we describe an integrated, machine-intelligent experimental system which enables simultaneous dynamic tests of electrical, optical, gravimetric, and viscoelastic properties of materials under a programmable dynamic environment. Specially designed software controls the experiment and performs on-the-fly extensive data analysis and dynamic modeling, real-time iterative feedback for dynamic control of experimental conditions, and rapid visualization of experimental results. The system operates with minimal human intervention and enables time-efficient characterization of complex dynamic multifunctional environmental responses of materials with simultaneous data processing and analytics. The system provides a viable platform for artificial intelligence (AI)-centered material characterization, which, when coupled with an AI-controlled synthesis system, could lead to accelerated discovery of multifunctional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Accelerating discrete dislocation dynamics simulations with graph neural networks

Discrete dislocation dynamics (DDD) is a widely employed computational method to study plasticity at the mesoscale that connects the motion of dislocation lines to the macroscopic response of crystalline materials. However, the computational cost of DDD simulations remains a bottleneck that limits its range of applicability. Here, we introduce a new DDD-GNN framework in which the expensive time-integration of dislocation motion is entirely substituted by a graph neural network (GNN) model trained on DDD trajectories. As a first application, we demonstrate the feasibility and potential of our method on a simple yet relevant model of a dislocation line gliding through an array of obstacles. We show that the DDD-GNN model is stable and reproduces very well unseen ground-truth DDD simulation responses for a range of straining rates and obstacle densities, without the need to explicitly compute nodal forces or dislocation mobilities during time-integration. Our approach opens new promising avenues to accelerate DDD simulations and to incorporate more complex dislocation motion behaviors.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Spatiotemporal Modeling of Real World Backsheets Field Survey Data: Hierarchical (Multilevel) Generalized Additive Models

Assessing photovoltaic module backsheet durability is critical to increasing module lifetime. Laboratory-based accelerating testing has recently failed to predict large scale failures of widely adopted polymeric materials. Additionally, there is a growing concern on characterizing the non-uniformity of field exposure. Therefore, data from field surveys are critical to assess the performance of component lifetimes. Using a documented field survey protocol, 19 field surveys were conducted. The focus of this survey strategy is to investigate spatial continuity in degradation modes. By combining field survey data with real-time satellite weather data, stressor / response models have been trained. Generalized additive Models (GAM) model was created to predict the value of degradation based on measured predictors. Two different GAM constructions were testing using different implementations of basis splines. The model includes variables on the environmental stressors of the system and the location of each measurement in the PV mounting structure. The incorporation of hierarchical structure into the models allowed for material specific degradation rates, while maintaining the assumption of a global trend. The model performed well with an adjusted R2 of 0.975 for yellowness index prediction.

backsheet↗
DOE OSTI2023

Bead–Spring Simulation of Ionomer Melts—Studying the Effects of Chain-Length and Associating Group Fraction on Equilibrium Structure and Extensional Flow Behavior

Ionomers are associative polymers with diverse applications ranging from selective membranes and high-performance adhesives to abrasion- and chemical-resistant coatings, insulation layers, vacuum packaging, and foamed sheets. Within equilibrium melt, the ionic or associating groups are known to form thermally reversible, associative clusters whose presence can significantly affect the system’s mechanical, viscoelastic, and transport properties. It is, thus, of great interest to understand how to control such clusters’ size distribution, shape, and stability through the designed choice of polymer architecture and the ionic groups’ fraction, arrangement, and interaction strength. In this work, we represent linear associating polymers using a Kremer–Grest type bead–spring model and perform large-scale MD simulations to explore the effect of polymer chain-length (l) and fraction (f s ) of randomly placed associating groups on the size distribution and stability of formed clusters. We consider different chain-lengths (below and above entanglement), varying fractions of associating groups (represented by ‘sticky’ beads) between 5 and 20%, and a fixed sticky–sticky nonbond interaction strength of four times that between regular non-associating beads. For all melts containing associating groups the equilibrium structure factor S(q) displays a signature ionomer peak at low wave vector q whose intensity increases with increasing f s and l. The average cluster size Nc increases with f s . However, the effect of chain-length on Nc appears to be pronounced only at higher values of f s . Under extensional flows, the computed stress (and viscosity) is higher at higher f s and l regardless of strain rate. Beyond a critical strain rate, we observe fragmentation of the associative clusters, which has interesting effects on the stress/viscous response.

36 MATERIALS SCIENCE↗
NASA NTRS1998

Modeling of Substitutional Site Preference in Ordered Intermetallic Alloys

We investigate the site substitution scheme of specific alloying elements in ordered compounds and the dependence of site occupancy on compound stoichiometry, alloy concentration. This basic knowledge, and the interactions with other alloying additions are necessary in order to predict and understand the effect of various alloying schemes on the physical properties of a material, its response to various temperature treatments, and the resulting mechanical properties. Many theoretical methods can provide useful but limited insight in this area, since most techniques suffer from constraints in the type of elements and the crystallographic structures that can be modeled. With this in mind, the Bozzolo-Ferrante-Smith (BFS) method for alloys was designed to overcome these limitations, with the intent of providing an useful tool for the theoretical prediction of fundamental properties and structure of complex systems. After a brief description of the BFS method, its use for the determination of site substitution schemes for individual as well as collective alloying additions to intermetallic systems is described, including results for the concentration dependence of the lattice parameter. Focusing on B2 NiAl, FeAl and CoAl alloys, the energetics of Si, Ti, V, Cr, Fe, Co, Ni, Cu, Zr, Nb, Mo, Ru, Hf, Ta and W alloying additions are surveyed. The effect of single additions as well as the result of two simultaneous additions, discussing the interaction between additions and their influence on site preference schemes is considered. Finally, the BFS analysis is extended to ternary L1(sub 2) (Heusler phase) alloys. A comparison between experimental and theoretical results for the limited number of cases for which experimental data is available is also included.

Bozzolo, Guillermo↗
DOE OSTI2025

High-Temperature Gas Sensor Materials with Properties Predicted via First-Principles Calculations with Machine Learning Modeling and Experimental Corroboration

Understanding the temperature dependence of functional properties of sensing materials is vital for their applications in combustion environments. The electron-phonon coupling that derives the electronic structure change with temperatures is a key property of interest as it affects other sensing responses. Herein, we first assess the temperature dependence of band gap renormalization in sensing materials by employing Allen-Heine-Cardona (AHC) theory with density functional theory (DFT) simulations corroborated with experimental observation. As the AHC calculations are impractical for high-throughput screening of materials, we employ data-driven Gaussian process regression to predict the parameters employed in the O’Donnell empirical model from a set of physical features. To mitigate the reliability issues arising from the small size of the dataset, we apply a Bayesian technique to improve the generalizability of the data-driven models as well as to quantify the uncertainty associated with theoretical predictions. These models capture well the overall trend of the O’Donnell parameters with respect to a reduced feature set obtained by transforming the available physical features. Quantifying the associated uncertainty helps us understand the reliability of the predictions and, therefore, the variation of bandgap as a function of temperature for other novel materials. The predicted candidates from machine learning models are further validated by experiments and DFT calculations.

bandgap renormalization↗
DOE OSTI2020

Modeling of Magnetic Properties of Magnetorheological Elastomers Using JA Hysteresis Model

Magnetorheological elastomers (MREs) are composite materials that consist of magnetically permeable particles in a nonmagnetic polymeric matrix. Under the influence of an external magnetic field, a reversible deformation change occurs in the mechanical properties of these materials. Due to their coupled magnetomechanical response, these materials have been found suitable for a range of applications including tunable vibration absorbers, sensors, and actuators. Notably, improvement of such devices are prerequisites to efficient energy conversion systems, hence the need to understand further the MRE technology. The Jiles-Atherton (JA) theory takes into consideration the magneto-coupling experienced by effective domains in a magnetic material. Algorithm based on the theory yields five model parameters; saturation magnetization (M s ), domain density (a), domain coupling (α), loss coefficient (k), and reversibility (c). Using JA theory, model parameters were calculated and linked to the physical attributes of Fe powder and isotropic MRE. The results show that the calculated Ms for the MRE is reasonably related to that of the Fe powder by a factor of the particle's volume fraction used in the MRE. Further, the calculated k, a, and α provided support for the reduced pinning factor, domain density, and increased domain coupling in the MRE due to the changes in the domain structure between the two materials. From the calculated JA parameters, finite-element modeling (FEM) of the MRE hysteresis loop was performed. The analysis showed that the modeled magnetic properties including coercivity, remanence, and coordinates of the hysteresis loop tip vary with geometric position.

42 ENGINEERING↗
NASA NTRS2001

Thermomechanical Response of Shape Memory Alloy Hybrid Composites

This study examines the use of embedded shape memory alloy (SMA) actuators for adaptive control of the thermomechanical response of composite structures. A nonlinear thermomechanical model is presented for analyzing shape memory alloy hybrid composite (SMAHC) structures exposed to steady-state thermal and dynamic mechanical loads. Also presented are (1) fabrication procedures for SMAHC specimens, (2) characterization of the constituent materials for model quantification, (3) development of the test apparatus for conducting static and dynamic experiments on specimens with and without SMA, (4) discussion of the experimental results, and (5) validation of the analytical and numerical tools developed in the study. Excellent agreement is achieved between the predicted and measured SAMHC responses including thermal buckling, thermal post-buckling and dynamic response due to inertial loading. The validated model and thermomechanical analysis tools are used to demonstrate a variety of static and dynamic response behaviors including control of static (thermal buckling and post-buckling) and dynamic responses (vibration, sonic fatigue, and acoustic transmission). and SMAHC design considerations for these applications. SMAHCs are shown to have significant advantages over conventional response abatement approaches for vibration, sonic fatigue, and noise control.

Turner, Travis L.↗
NASA NTRS2016

Development of a Subcell Based Modeling Approach for Modeling the Architecturally Dependent Impact Response of Triaxially Braided Polymer Matrix Composites

Understanding the high velocity impact response of polymer matrix composites with complex architectures is critical to many aerospace applications, including engine fan blade containment systems where the structure must be able to completely contain fan blades in the event of a blade-out. Despite the benefits offered by these materials, the complex nature of textile composites presents a significant challenge for the prediction of deformation and damage under both quasi-static and impact loading conditions. The relatively large mesoscale repeating unit cell (in comparison to the size of structural components) causes the material to behave like a structure rather than a homogeneous material. Impact experiments conducted at NASA Glenn Research Center have shown the damage patterns to be a function of the underlying material architecture. Traditional computational techniques that involve modeling these materials using smeared homogeneous, orthotropic material properties at the macroscale result in simulated damage patterns that are a function of the structural geometry, but not the material architecture. In order to preserve heterogeneity at the highest length scale in a robust yet computationally efficient manner, and capture the architecturally dependent damage patterns, a previously-developed subcell modeling approach where the braided composite unit cell is approximated as a series of four adjacent laminated composites is utilized. This work discusses the implementation of the subcell methodology into the commercial transient dynamic finite element code LS-DYNA (Livermore Software Technology Corp.). Verification and validation studies are also presented, including simulation of the tensile response of straight-sided and notched quasi-static coupons composed of a T700/PR520 triaxially braided [0deg/60deg/-60deg] composite. Based on the results of the verification and validation studies, advantages and limitations of the methodology as well as plans for future work are discussed.

finite element method↗
DOE OSTI2025

Odd-Parity Magnetism Driven by Antiferromagnetic Exchange

Realizing odd-parity, time-reversal-preserving, nonrelativistic spin splitting is a central goal for spintronics applications. We propose a group-theory-based microscopic framework to induce odd-parity spin splitting from coplanar antiferromagnetic (AFM) states without spin-orbit coupling (SOC). We develop phenomenological models for 421 conventional period-doubling AFM systems in nonsymmorphic space groups and construct minimal microscopic models for 119 of these. We find that these AFM states can attain three possible competing ground states. These ground states all break symmetries in addition to those broken by the usual AFM order. Specifically, they give rise to either odd-parity spin-splitting, nematic order, or scalar odd-parity order related to multiferroicity. Our microscopic theories reveal that the odd-parity spin-splitting energy scale is generically large and further reveal that the scalar odd-parity order gives a nonzero Berry curvature dipole without SOC. We identify 67 materials in the Magndata database for which our theory applies. We provide density-functional theory (DFT) calculations on Fe-based materials that reveal an ℎ-wave spin splitting consistent with our symmetry arguments and apply our microscopic model to determine the nonrelativistic Edelstein response for CeNiAsO.

Antiferromagnets↗
DOE OSTI2024

Mechanical Characterization of Electrolyzer Membranes and Components Under Compression

Proton-exchange membrane (PEM) water electrolysis is a promising technology for producing clean hydrogen by electrochemically splitting water when paired with renewable energy sources. A major roadblock to improving electrolyzer durability is the mechanical degradation of the cell components, which requires an understanding of their mechanical response under device-relevant conditions. However, there is a lack of studies on the mechanical characterization of the PEM and other components, as well as and their interactions. This study aims to address this gap by using a custom-designed testing apparatus to investigate the mechanics of electrolyzer components in uniaxial compression at 25 and 80 °C. Findings show stress-strain response of components have a varying degree of nonlinearity owing to their distinct deformation mechanisms and morphologies, from porous structures to polymers. These results are used to develop an expression for compressive stress-strain response of Nafion membranes and then analyze the deformation of components under applied pressure by using a 1-D spring network model of cell assembly. This work provides a new understanding of mechanical responses of the electrolyzer membrane and cell components, which can help assess material design and cell assembly strategies for improved electrolyzer durability.

08 HYDROGEN↗
DOE OSTI2021

First principles calculations in support of Pu aging: calculating the effects of lattice imperfections on thermodynamics

Plutonium (Pu) has, in theory, well defined crystal structures: its atoms are arranged in regular spatial patterns. But Pu is radioactive, and as its nuclei decay those regular spatial patterns are interrupted. The interruptions are lattice imperfections, which are known to affect how materials respond to their environment. To adequately model Pu, we need to know which lattice imperfections are present, how they interact with each other, and how they affect the material’s response to its environment. The work presented here aims to use density functional theory (DFT) calculations to begin to answer the latter, in particular, how individual lattice imperfections affect measurable effects including thermal expansion (the change in volume in response to a change in temperature), heat capacity (the amount of thermal energy needed to change a material’s temperature), and elastic moduli (a material’s resistance to applied stresses). Pu poses many computational challenges. The $\textit{f}$ electrons require special attention. Of all the elements, Pu has the largest number of electrons that must be included in the calculations. Thermal effects require calculating the phonons (the lattice vibrations), which for systems containing lattice imperfections demand large, complex computational cells - but computational resources limit the size and complexity. With careful restructuring of how the calculations are performed, all these challenges have been met to enable calculations that provide insight into how lattice imperfections affect Pu’s response to its environment. Reported here are the computational challenges and the advances developed to meet them, along with the first results showing the strong effect that one prototype lattice imperfection (an interstitial Pu atom in a delta-phase Pu lattice) has on Pu’s response to its environment.

36 MATERIALS SCIENCE↗
NASA NTRS1977

Charging characteristics of materials: Comparison of experimental results with simple analytical models

An understanding of the behavior of materials, of dielectrics in particular, under charged particle bombardment is essential to the prediction and prevention of the adverse effects of spacecraft charging. A one-dimensional model for charging of samples in a test facility was used in conjunction with experimental data taken to develop "material charging characteristics" for silvered Teflon. These characteristics were then used in a one-dimensional model for charging in space to examine expected response. Relative charging rates as well as relative charging levels for silvered Teflon and metal are discussed.

Purvis, C. K.↗
NASA NTRS1985

Delamination micromechanics analysis

A three-dimensional finite element analysis was developed which includes elastoplastic, orthotropic material response, and fracture initiation and propagation. Energy absorption due to physical failure processes characteristic of the heterogeneous and anisotropic nature of composite materials is modeled. A local energy release rate in the presence of plasticity was defined and used as a criterion to predict the onset and growth of cracks in both micromechanics and macromechanics analyses. This crack growth simulation technique is based upon a virtual crack extension method. A three-dimensional finite element micromechanics model is used to study the effects of broken fibers, cracked matrix and fiber-matrix debond on the fracture toughness of the unidirectional composite. The energy release rates at the onset of unstable crack growth in the micromechanics analyses are used as critical energy release rates in the macromechanics analysis. This integrated micromechanical and macromechanical fracture criterion is shown to be very effective in predicting the onset and growth of cracks in general multilayered composite laminates by applying the criterion to a single-edge notched graphite/epoxy laminate subjected to implane tension normal to the notch.

Adams, D. F.↗
NASA NTRS1988

Thermal Response Of Composite Insulation

Engineering model gives useful predictions. Pair of reports presents theoretical and experimental analyses of thermal responses of multiple-component, lightweight, porous, ceramic insulators. Particular materials examined destined for use in Space Shuttle thermal protection system, test methods and heat-transfer theory useful to chemical, metallurgical, and ceramic engineers needing to calculate transient thermal responses of refractory composites.

Stewart, David A.↗
NASA NTRS1991

Analysis of shell-type structures subjected to time-dependent mechanical and thermal loading

This report deals with the development of a general mathematical model and solution methodology for analyzing the structural response of thin, metallic shell-like structures under dynamic and/or static thermomechanical loads. In the mathematical model, geometric as well as the material-type of nonlinearities are considered. Traditional as well as novel approaches are reported and detailed applications are presented in the appendices. The emphasis for the mathematical model, the related solution schemes, and the applications, is on thermal viscoelastic and viscoplastic phenomena, which can predict creep and ratchetting.

Simitses, G. J.↗