Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “materials modelling”

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 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Five year ground exposure of composite materials used on the Bell Model 206L flight service evaluation

Part of the results of a U.S. Army/NASA-Langley sponsored research program to establish the long term-term effects of realistic ground based exposure on advanced composite materials is presented. Residual strengths and moisture absorption as a function of exposure time and exposure location are reported for four different composite material systems that were exposed for five years on the North American Continent.

Baker, Donald J.↗
DOE OSTI2021

Considering computational speed vs. accuracy: Choosing appropriate mesoscale RVE boundary conditions

Modeling a material’s microstructure using continuum theories allows for inspection of the relationship between coarse scale and fine scale behaviors. Computational limits generally require selection of a sub-volume from a bulk sample in order to directly model the microstructure. Boundary conditions are applied to the sub-volume to mimic the excluded bulk material. Appropriate selection of boundary conditions helps effectively determine the appropriate spatial scale required of the sub-volume. Applicable boundary conditions include direct displacement, periodic, and uniform traction. While direct displacement and periodic boundary conditions are commonly used, uniform traction boundary conditions have seen limited use due to rigid body stability issues in simulations of compression or shear deformation. A new application of uniform traction boundary conditions was developed through linear constraint equations, similar to approaches employed by direct displacement and periodic boundary conditions, to quench rigid body motions with minimal interference of the relative deformation of the model. These boundary conditions were tested by compressing several synthetically generated periodic microstructures using the finite element method. Evaluating the effective stiffness along the compression axis, the direct displacement boundary condition produced the stiffest response, whereas the uniform traction boundary condition produced the most compliant. Periodic boundary conditions produced the same response for all volumes analyzed and both the direct displacement and uniform traction boundary conditions trended toward the periodic response as the domain volume increased. Computational performance was also evaluated for each boundary condition using implicit and explicit solvers. Direct displacement boundary conditions presented the lowest computational cost of all of the boundary conditions followed by periodic then uniform traction. The computational expense of periodic and uniform traction boundary conditions limited the viable spatial scale and mesh resolutions able to be simulated. Selection of appropriate boundary conditions for specific uses need to be a balance between allowable computational expense and accuracy of the method. Techniques for evaluating which boundary conditions to use are discussed.

42 ENGINEERING↗
DOE OSTI2024

Machine learning materials properties with accurate predictions, uncertainty estimates, domain guidance, and persistent online accessibility

One compelling vision of the future of materials discovery and design involves the use of machine learning (ML) models to predict materials properties and then rapidly find materials tailored for specific applications. However, realizing this vision requires both providing detailed uncertainty quantification (model prediction errors and domain of applicability) and making models readily usable. At present, it is common practice in the community to assess ML model performance only in terms of prediction accuracy (e.g. mean absolute error), while neglecting detailed uncertainty quantification and robust model accessibility and usability. Here, we demonstrate a practical method for realizing both uncertainty and accessibility features with a large set of models. We develop random forest ML models for 33 materials properties spanning an array of data sources (computational and experimental) and property types (electrical, mechanical, thermodynamic, etc). All models have calibrated ensemble error bars to quantify prediction uncertainty and domain of applicability guidance enabled by kernel-density-estimate-based feature distance measures. All data and models are publicly hosted on the Garden-AI infrastructure, which provides an easy-to-use, persistent interface for model dissemination that permits models to be invoked with only a few lines of Python code. We demonstrate the power of this approach by using our models to conduct a fully ML-based materials discovery exercise to search for new stable, highly active perovskite oxide catalyst materials.

domain of applicability↗
DOE OSTI2023

Towards inverse microstructure-centered materials design using generative phase-field modeling and deep variational autoencoders

The field of Integrated Computational Materials Engineering (ICME) combines a broad range of methods to study materials’ responses over a spectrum of length scales. A relatively unexplored aspect of microstructure-sensitive materials design is uncertainty propagation and quantification (UP/UQ) of materials’ microstructure, as well as establishing process-structure–property (PSP) relationships for inverse material design. In this study, an efficient UP technique built on the idea of changing probability measures and a deep generative unsupervised representative machine learning method for microstructure-based design of thermal conductivity of materials is proposed. Probability measures are used to represent microstructure space, and Wasserstein metrics are used to test the efficiency of the UP method. By using deep Variational AutoEncoder (VAE), we identify the correlations between the material/process parameters and the thermal conductivity of heterogeneous dual-phase microstructures. Through high-throughput screening, UP, and the deep-generative VAE method, PSP relationships that are too complex can be revealed by exploiting the materials’ design space with an emphasis on microstructures. As a last point, we demonstrate generative machine learning serves as a useful tool for inverse microstructure-centered materials design, and we demonstrate this by examining the inverse design of thermal conductivity in nano-structured materials. Here, the results reveal the effects of morphology, volume fraction, characteristic length scale, and the individual thermal diffusivity of phases on the thermal conductivity of dual-phase alloys. Our findings emphasize the advantages of high-throughput phase-field modeling and generative deep learning for linking PSP and inverse microstructure-centered materials design.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Modular Linear Thermoviscoelastic Model

Time-dependent, viscoelastic responses of materials like polymers and glasses have long been studied. As such, a variety of models have been put forth to describe the behavior including simple rheological models (e.g. Maxwell, Kelvin), linear "fading memory" theories, and hereditary integral based linear thermal viscoelastic approaches as well as more recent nonlinear theories that are either integral, fictive temperature, or differential internal state variable based. The current work details a new LINEAR_THERMOVISCOELASTIC model that has been added to LAME. This formulation represents a viscoelastic theory that neglects some of the phenomenological details of the PEC/SPEC models in favor of efficiency and simplicity. Furthermore, this new model is a first step towards developing "modular" viscoelastic capabilities akin to those available with hardening descriptions for plasticity models in LAME. Specifically, multiple different (including user-defined) shift-factor forms are implemented with each being easily selected via parameter specification rather than requiring distinct material models.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Elucidating Structural Disorder in Ultra‐Thin Bi‐Rich Bismuth Oxyhalide Photocatalysts

Abstract Advancing the field of photocatalysis requires the elucidation of structural properties that underpin the photocatalytic properties of promising materials. The focus of the present study is layered, Bi‐rich bismuth oxyhalides, which are widely studied for photocatalytic applications yet poorly structurally understood, due to high levels of disorder, nano‐sized domains, and the large number of structurally similar compounds. By connecting insights from multiple scattering techniques, utilizing electron‐, X‐ray‐ and neutron probes, the crystal phase of the synthesized materials is allocated as layered Bi 24 O 31 X 10 (X = Cl, Br), albeit with significant deviation from the reported 3D crystalline model. The materials comprise anisotropic platelet‐shaped crystalline domains, exhibiting significant in‐plane ordering in two dimensions but disorder and an ultra‐thin morphology in the layer stacking direction. Increased synthesis pH tailored larger, more ordered crystalline domains, leading to longer excited state lifetimes determined via femtosecond transient absorption spectroscopy (fs‐TAS). Although this likely contributes to improved photocatalytic properties, assessed via the photooxidation of benzylamine, increasing the overall surface area facilitated the most significant improvement in photocatalytic performance. This study, therefore, enabled both phase allocation and a nuanced discussion of the structure‐property relationship for complicated, ultra‐thin photocatalysts.

Chemistry↗
NASA NTRS1973

Three models of the vibrating ulna.

Evaluation of the ability of three models of the ulna to predict ulnar resonant frequency. The ulna is considered to be a uniform cylindrical tube made of homogeneous isotropic material. In model I the tube is attached at each end to rigid supports by hinges, in model II the tube is attached to rigid supports by springs rather than hinges, while model III is the same as model II except for the addition of a spring-mass system simulating an accelerometer strapped to the wrist. It is found that all three models exhibit comparable effectiveness in predicting the allowed cyclic vibration frequency, although model I is marginally better than models II or III in predicting this parameter. All three models also yield relatively realistic values for Young's modulus. In terms of results, therefore, there is no clear choice between the models. However, owing to greater costs incurred with models II and III, it is concluded that model I is the most useful, even though it is the least 'realistic' of the three models evaluated.-

Jurist, J. M.↗
NASA NTRS1992

Superplastic forming of ceramic insulation

Superplasticity has been demonstrated in many fine-grained structural ceramics and ceramic composites, including yttria-stabilized tetragonal zirconia polycrystal (YTZP), alumina, and Al2O3-reinforced zirconia (Al2O3/YTZ) duplex composites and SiC-reinforced Si3N4. These superplastic ceramics obviously offer the potential benefit of forming net shape or near net shape parts. This could be particularly useful for forming complicated shapes that are difficult to achieve using conventional forming techniques, or require elaborate, subsequent machining. In the present study, we successfully demonstrated the following: (1) superplastic 3Y-TXP and 20 percent Al2O3/YTZ composite have for the first time been successfully deformed into hemispherical caps via a biaxial gas-pressure forming technique; (2) no experimental difficulty was encountered in applying the required gas pressures and temperatures to achieve the results, thus, it is certain that higher rates of deformation than those presented in this study will be possible by using the current test apparatus at higher temperatures and pressures; and (3) an analytical model incorporating material parameters, such as variations during forming in the strain rate sensitivity exponent and grain growth-induced strain hardening, is needed to model accurately and therefore precisely control the biaxial gas-pressure forming of superplastic ceramics. Based on the results of this study, we propose to fabricate zirconia insulation tubes by superplastic extrusion of zirconia polycrystal. This would not only reduce the cost, but also improve the reliability of the tube products.

Nieh, T. G.↗
NASA NTRS1993

Test model designs for advanced refractory ceramic materials

The next generation of space vehicles will be subjected to severe aerothermal loads and will require an improved thermal protection system (TPS) and other advanced vehicle components. In order to ensure the satisfactory performance system (TPS) and other advanced vehicle materials and components, testing is to be performed in environments similar to space flight. The design and fabrication of the test models should be fairly simple but still accomplish test objectives. In the Advanced Refractory Ceramic Materials test series, the models and model holders will need to withstand the required heat fluxes of 340 to 817 W/sq cm or surface temperatures in the range of 2700 K to 3000 K. The model holders should provide one dimensional (1-D) heat transfer to the samples and the appropriate flow field without compromising the primary test objectives. The optical properties such as the effective emissivity, catalytic efficiency coefficients, thermal properties, and mass loss measurements are also taken into consideration in the design process. Therefore, it is the intent of this paper to demonstrate the design schemes for different models and model holders that would accommodate these test requirements and ensure the safe operation in a typical arc jet facility.

Tran, Huy Kim↗
DOE OSTI2021

Phase-field simulations of fission gas bubbles in high burnup UO2 during steady-state and LOCA transient conditions

To improve the economics of commercial nuclear energy generation, U.S. utilities are currently seeking licensing approval to operate UO2 fuel to higher burnups. One significant safety issue that must be addressed to obtain approval is the potential for fine fragmentation/pulverization of the fuel during a loss-of-coolant accident (LOCA). It has been hypothesized this is caused by the rapid increase of pressure in fission gas bubbles in the high burnup region of the fuel. To better understand this phenomenon, a novel phase-field model of the fission gas bubble microstructure in UO2 has been developed and implemented in Idaho National Laboratory's Marmot application for phase-field simulation of nuclear materials. Simulations of bubble growth in the high burnup region during steady-state conditions showed that initially overpressurized bubbles decreased in pressure during growth, but still remained above equilibrium pressure. During a LOCA transient, simulations of bubbles in the high burnup region showed that bubble size did not change significantly, and the pressure increase due to the transient was calculated and passed to a phase-field model of fracture.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1989

Extension-torsion coupling behavior of advanced composite tilt-rotor blades

An analytic model was developed to study the extension-bend-twist coupling behavior of an advanced composite helicopter or tilt-rotor blade. The outer surface of the blade is defined by rotating an arbitrary cross section about an initial twist axis. The cross section can be nonhomogeneous and composed of generally anisotropic materials. The model is developed based upon a three dimensional elasticity approach that is recast as a coupled two-dimensional boundary value problem defined in a curvilinear coordinate system. Displacement solutions are written in terms of known functions that represent extension, bending, and twisting and unknown functions for local cross section deformations. The unknown local deformation functions are determined by applying the principle of minimum potential energy to the discretized two-dimensional cross section. This is an application of the Ritz method, where the trial function family is the displacement field associated with a finite element (8-node isoparametric quadrilaterals) representation of the section. A computer program was written where the cross section is discretized into 8-node quadrilateral subregions. Initially the program was verified using previously published results (both three-dimensional elasticity and technical beam theory) for pretwisted isotropic bars with an elliptical cross section. In addition, solid and thin-wall multi-cell NACA-0012 airfoil sections were analyzed to illustrate the pronounced effects that pretwist, initial twist axis location, and spar location has on coupled behavior. Currently, a series of advanced composite airfoils are being modeled in order to assess how the use of laminated composite materials interacts with pretwist to alter the coupling behavior of the blade. These studies will investigate the use of different ply angle orientations and the use of symmetric versus unsymmetric laminates.

Kosmatka, J. B.↗
DOE OSTI2025

Many-body expansion based machine learning models for octahedral transition metal complexes

Abstract Graph-based machine learning (ML) models for material properties show great potential to accelerate virtual high-throughput screening of large chemical spaces. However, in their simplest forms, graph-based models do not include any 3D information and are unable to distinguish stereoisomers such as those arising from different orderings of ligands around a metal center in coordination complexes. In this work we present a modification to revised autocorrelation descriptors, a molecular graph featurization method, for predicting spin state dependent properties of octahedral transition metal complexes (TMCs). Inspired by analytical semi-empirical models for TMCs, the new modeling strategy is based on the many-body expansion (MBE) and allows one to tune the captured stereoisomer information by changing the truncation order of the MBE. We present the necessary modifications to include this approach in two commonly used ML methods, kernel ridge regression and feed-forward neural networks. On a test set composed of all possible isomers of binary TMCs, the best MBE models achieve mean absolute errors (MAEs) of 2.75 kcal mol −1 on spin-splitting energies and 0.26 eV on frontier orbital energy gaps, a 30%–40% reduction in error compared to models based on our previous approach. We also observe improved generalization to previously unseen ligands where the best-performing models exhibit MAEs of 4.00 kcal mol −1 (i.e. a 0.73 kcal mol −1 reduction) on the spin-splitting energies and 0.53 eV (i.e. a 0.10 eV reduction) on the frontier orbital energy gaps. Because the new approach incorporates insights from electronic structure theory, such as ligand additivity relationships, these models exhibit systematic generalization from homoleptic to heteroleptic complexes, allowing for efficient screening of TMC search spaces.

Meyer, Ralf (ORCID:0000000322360261)↗
DOE OSTI2022

CRADA NO. NFE-22-00001 Between CNS and Northrop Grumman Systems Corporation

Consolidated Nuclear Security, LLC (CNS) and Northrop Grumman Systems Corporation (NGC) have established a partnership through the subject Cooperative Research and Development Agreement (CRADA) in three areas of collaboration: (1) Additive Manufacturing (AM) of manufactured carbon-carbon composite materials, (2) modeling and simulation, and (3) specialized chip and circuit board manufacturing for supply chain assurance.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Multiscale Investigation of the Mechanisms Controlling Materials Degradation in the Fusion Energy Environment (DE-SC0006661: Final Report)

Realizing the promise of fusion as a commercially attractive energy source requires the development of advanced structural materials capable of sustained operation in an incredibly hostile environment. The fusion environment presents many challenges associated with high cyclic thermal-mechanical loadings, welding and joining disparate materials, and achieving chemical compatibility with coolants and tritium breeders. Yet, the overarching concern is the degradation of physical and mechanical properties, resulting from a neutron energy spectrum peaked at 14 MeV. The high-energy fusion neutron irradiation produces both displacement damage and high levels of hydrogen and helium through transmutation reactions. Advanced materials development for use in such a hostile environment is predicated on understanding the underlying mechanisms responsible for physical and material property degradation. This project has closely combined computational, theoretical and experimental techniques within a multiscale materials science paradigm to determine the mechanisms controlling material degradation in the fusion environment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1985

Degradation studies of SMRM Teflon

A working group was organized to study materials and components of the Solar Max Satellite (SMS) that was returned by the STS 41C. These materials were exposed in space for 50 months and represent the only real time long term exposure data available to date. In the molecular modeling of material and energetic oxygen atom interaction, it is pointed out that the importance of developing correlation between accelerated exposure data from STS and some real time data. In particular, it was predicted that Teflon which showed no detectable degradation on various STS flights may be susceptible to atomic oxygen degradation under real time conditions. Initial inspection of returned SMS samples showed that Teflon suffered visual damage such as cracking and yellowing. The results of examination of these samples are given.

Liang, R. H.↗
NASA NTRS1992

Development of 3D electromagnetic modeling tools for airborne vehicles

The main goal of this project is to develop methodologies for scattering by airborne composite vehicles. Although our primary focus continues to be the development of a general purpose code for analyzing the entire structure as a single unit, a number of other tasks are also pursued in parallel with this effort. These tasks are important in testing the overall approach and in developing suitable models for materials coatings, junctions and, more generally, in assessing the effectiveness of the various parts comprising the final code. Here, we briefly discuss our progress on the five different tasks which were pursued during this period. Our progress on each of these tasks is described in the detailed reports (listed at the end of this report) and the memoranda included. The first task described below is, of course, the core of this project and deals with the development of the overall code. Undoubtedly, it is the outcome of the research which was funded by NASA-Ames and the Navy over the past three years. During this year we developed the first finite element code for scattering by structures of arbitrary shape and composition. The code employs a new absorbing boundary condition which allows termination of the finite element mesh only 0.3 lambda from the outer surface of the target. This leads to a remarkable reduction of the mesh size and is a unique feature of the code. Other unique features of this code include capabilities to model resistive sheets, impedance sheets and anisotropic materials. This last capability is the latest feature of the code and is still under development. The code has been extensively validated for a number of composite geometries and some examples are given. The validation of the code is still in progress for anisotropic and larger non-metallic geometries and cavities. The developed finite element code is based on a Galerkin's formulation and employs edge-based tetrahedral elements for discretizing the dielectric sections and the region between the target and the outer mesh termination boundary (ATB). This boundary is placed in conformity with the target's outer surface, thus resulting in additional reduction of the unknown count.

Volakis, John L.↗
DOE OSTI2021

Prediction of moisture transfer in cement-based materials: Use of a porous network model to access transfer parameters

Knowing the water transport phenomena is fundamental for understanding the durability of cement-based materials. The moisture content within cementitious materials is of primary importance because it has a direct influence on mechanical (shrinkage, creep) and chemical (penetration of aggressive agents) degradation. Many models based on the determination of the transfer properties of the material under study already exist but require fitting of the parameters to find the experimental kinetics. Transfer parameters are generally estimated from the empirical approaches developed for soils by Van Genuchten and the water vapour diffusion reduction factor is often calculated via Millington's semi-empirical model. In this paper, we make a proposal to improve the prediction of moisture transfer, through mechanisms such as drying, capillary imbibition and water vapour permeability in cement-based materials, by using a porous network model to access the transfer parameters.

36 MATERIALS SCIENCE↗