Accurate Modeling of Material Nonlinearities in a Wind Turbine Spar Cap.
Abstract not provided.
Clarke, Ryan↗
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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.
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Fractional Modeling in Action: A Survey of Nonlocal Models for Subsurface Transport, Turbulent Flows, and Anomalous Materials
Modeling of phenomena such as anomalous transport via fractional-order differential equations has been established as an effective alternative to partial differential equations, due to the inherent ability to describe large-scale behavior with greater efficiency than fully-resolved classical models. In this review article, we first provide a broad overview of fractional-order derivatives with a clear emphasis on the stochastic processes that underlie their use. We then survey three exemplary application areas – subsurface transport, turbulence, and anomalous materials – in which fractional-order differential equations provide accurate and predictive models. For each area, we report on the evidence of anomalous behavior that justifies the use of fractional-order models, and survey both foundational models as well as more expressive state-of-the-art models. We also propose avenues for future research, including more advanced and physically sound models, as well as tools for calibration and discovery of fractional-order models.
97 MATHEMATICS AND COMPUTING↗
Pulsed radiolysis of model aromatic polymers and epoxy based matrix materials
Models of primary processes leading to deactivation of energy deposited by a pulse of high energy electrons were derived for epoxy matrix materials and polyl-vinyl naphthalene. The basic conclusion is that recombination of initially formed charged states is complete within 1 nanosecond, and subsequent degradation chemistry is controlled by the reactivity of these excited states. Excited states in both systems form complexes with ground state molecules. These excimers or exciplexes have their characteristics emissive and absorptive properties and may decay to form separated pairs of ground state molecules, cross over to the triplet manifold or emit fluorescence. ESR studies and chemical analyses subsequent to pulse radiolysis were performed in order to estimate bond cleavage probabilities and net reaction rates. The energy deactivation models which were proposed to interpret these data have led to the development of radiation stabilization criteria for these systems.
Gupta, A.↗
Towards a circular economy for PET bottle resin using a system dynamics inspired material flow model
Not Available
Ghosh, Tapajyoti (ORCID:0000000205220235)↗
SNL will be able to provide well-calibrated models to weapons systems analysts by integrating an engine for constitutive model calibration with the GRANTA materials database
Researchers at Sandia National Laboratories have integrated the GRANTA materials database with the MatCal calibration engine to calibrate material models from characterization data. GRANTA is gaining acceptance across the NNSA Tri-lab complex and is being populated with weapons-specific test data by Sandia experimentalists. To use that data to create material models for use by weapons systems analysts, MatCal has been enabled import calibration data and test conditions from GRANTA to quickly and reproducibly produce a calibrated set of parameters for a given constitutive model. The team is currently working to store the parameters characterizing material behavior in GRANTA to make them accessible by all weapons analysts.
36 MATERIALS SCIENCE↗
NEML2: A High Performance Library for Constitutive Modeling
NEML2, the New Engineering Material model Library, version 2, is an offshoot of NEML, an earlier material modeling code developed at Argonne National Laboratory. NEML2 extends the key philosophy of its predecessor, i.e., material models are flexible, modular, and can be built from smaller blocks. It also provides modern features that do not exist in the framework of its predecessor such as material model vectorization, automatic differentiation, device-portable just-in-time compilation, operator fusion, lazy tensor evaluation, etc. Moreover, NEML2 can seamlessly integrate with the popular machine learning package PyTorch to take advantage of modern and fast-growing machine learning techniques. In this fiscal year, the development of core library features and capabilities are complete. The purpose of this report is not to serve as a verbatim copy of the software API reference (which is available online at https://reverendbedford.github.io/neml2/). Instead, this report documents the motivation, implementation, design choices, and usage of each core capability as well as their applications in solving practical engineering problems. This report is compiled based on the NEML2 major release 2.0.0.
36 MATERIALS SCIENCE↗
Calibrating a finite-strain phase-field model of fracture for bonded granular materials with uncertainty quantification
To study the mechanical behavior of mock high explosives, an experimental and simulation program was developed to calibrate, with quantified uncertainty, a material model of the bonded granular material Idoxuridine and nitroplasticized Estane-5703. This paper reports on the efficacy of such a framework as a generalizable methodology for calibrating material models against experimental data with uncertainty quantification. Additionally, this paper studies the effect of two manufacturing temperatures and three initial granular configurations on the unconfined compressive behavior of the resulting bonded granular materials. In each of these cases, the same calibration framework was used; in that, hundreds of high-fidelity direct numerical simulations using a new, graphics processing unit-enabled, high-performance finite element method software, Ratel, were run to calibrate a finite-strain phase-field fracture model against experimental data. It was found that manufacturing temperature influenced the elastic response of the mock high explosives, with higher temperatures yielding a stiffer response. By contrast, it was found that the initial configuration of the grains had a negligible impact on the overall behavior of the mock high explosives though it remains possible that local damage accumulation within the specimens could be altered by the initial configurations. Overall, the calibration framework was successful at creating well-calibrated models, showing its usefulness as an engineering and scientific tool.
36 MATERIALS SCIENCE↗
Application of the MAT 213 Composite Impact Model to NASA Problems of Interest
A material model has been developed which incorporates several key capabilities which have been identified as lacking in currently available composite impact models. The material model utilizes experimentally based tabulated input to define the evolution of plasticity and damage as opposed to specifying discrete input parameters (such as modulus and strength). The material model has been implemented into LS-DYNA® as MAT 213. The model can simulate the nonlinear deformation, damage and failure that takes place in a composite under dynamic loading conditions. The deformation model utilizes an orthotropic plasticity formulation. For the damage model, the nonlinear unloading response that is observed prior to the point where the peak stress is reached can be simulated, as well as the stress degradation response that occurs after the peak stress is reached. A variety of failure models, including a generalized tabulated failure model which facilitates the utilization of general failure surfaces, have been implemented into MAT 213. Recent studies at NASA have concentrated on using MAT 213 to analyze both the impact and crush response of a variety of laminated and textile architectures. Several of these studies will be discussed in the presented paper. For example, a woven carbon/Kevlar composite is currently being examined for use in an energy absorber system for rotorcraft structures. MAT 213 analyses have been conducted to examine the ability of the model to accurately simulate the dynamic crush response of this material. Studies are also being conducted to examine the ability of MAT 213 to simulate the ballistic impact response of representative laminated and woven thermoplastic and thermoset matrix composites. NASA efforts are also concentrated on developing methods and processes for improving characterization methods and developing “best practices” for using MAT 213, a summary of which will be discussed in the paper.
Polymer Matrix Composites↗
Exploiting Machine Learning in Multiscale Modelling of Materials
Recent developments in efficient machine learning algorithms have spurred significant interest in the materials community. The inherently complex and multiscale problems in Materials Science and Engineering pose a formidable challenge. The present scenario of machine learning research in Materials Science has a clear lacunae, where efficient algorithms are being developed as a separate endeavour, while such methods are being applied as ‘black-box’ models by others. The present article aims to discuss pertinent issues related to the development and application of machine learning algorithms for various aspects of multiscale materials modelling. The authors present an overview of machine learning of equivariant properties, machine learning-aided statistical mechanics, the incorporation of ab initio approaches in multiscale models of materials processing and application of machine learning in uncertainty quantification. In addition to the above, the applicability of Bayesian approach for multiscale modelling will be discussed. Critical issues related to the multiscale materials modelling are also discussed.
42 ENGINEERING↗
Verification and Validation of a Three-Dimensional Composite Impact Model with Tabulated Input
A material model which incorporates several key capabilities which have been identified by the aerospace community as lacking in the composite impact models currently available in the commercial transient dynamic finite element code LS-DYNA® has been developed. The material model utilizes experimentally based tabulated input to define the evolution of plasticity and damage as opposed to specifying discrete input parameters (such as modulus and strength. The plasticity portion of the orthotropic, three-dimensional, macroscopic composite constitutive model is based on an extension of the Tsai-Wu composite failure model into a generalized yield function with a non-associative flow rule. The capability to account for the rate and temperature dependent deformation response of composites has also been incorporated into the material model. For the damage model, a strain equivalent formulation is utilized to allow for the uncoupling of the deformation and damage analyses. In the damage model, a diagonal damage tensor is defined to account for the directionally dependent variation of damage. However, the terms in the damage matrix are semi-coupled such that the damage in a particular coordinate direction is a function of the stresses and plastic strains in all of the coordinate directions. For the failure model, a tabulated approach is utilized in which a stress or strain based invariant is defined as a function of the location of the current stress state in stress space to define the initiation of failure, which allows an arbitrarily shaped failure surface to be defined. A systematic series of validation and verification studies, at a variety of length scales ranging from single element simulations to simulations of a flat panel impact test, have been performed to fully exercise and evaluate the capabilities of the developed model.
Impact↗
Paradigm Shift in Data Content and Informatics Infrastructure Required for Generalized Constitutive Modeling of Materials Behavior
Materials property information such as composition and thermophysical/mechanical properties abound in the literature. Oftentimes, however, the corresponding response curves from which these data are determined are missing or at the very least difficult to retrieve. Further, the paradigm for collecting materials property information has historically centered on (1) properties for materials comparison/selection purposes and (2) input requirements for conventional design/analysis methods. However, just as not all materials are alike or equal, neither are all constitutive models (and thus design/ analysis methods) equal; each model typically has its own specific and often unique required materials parameters, some directly measurable and others indirectly measurable. Therefore, the type and extent of materials information routinely collected is not always sufficient to meet the current, much less future, needs of the materials modeling community. Informatics has been defined as the science concerned with gathering, manipulating, storing, retrieving, and classifying recorded information. A key aspect of informatics is its focus on understanding problems and applying information technology as needed to address those problems. The primary objective of this article is to highlight the need for a paradigm shift in materials data collection, analysis, and dissemination so as to maximize the impact on both practitioners and researchers. Our hope is to identify and articulate what constitutes "sufficient" data content (i.e., quality and quantity) for developing, characterizing, and validating sophisticated nonlinear time- and history-dependent (hereditary) constitutive models. Likewise, the informatics infrastructure required for handling the potentially massive amounts of materials data will be discussed.
Arnold, S. M.↗
Materials constitutive models for nonlinear analysis of thermally cycled structures
Effects of inelastic materials models on computed stress-strain solutions for thermally loaded structures were studied by performing nonlinear (elastoplastic creep) and elastic structural analyses on a prismatic, double edge wedge specimen of IN 100 alloy that was subjected to thermal cycling in fluidized beds. Four incremental plasticity creep models (isotropic, kinematic, combined isotropic kinematic, and combined plus transient creep) were exercised for the problem by using the MARC nonlinear, finite element computer program. Maximum total strain ranges computed from the elastic and nonlinear analyses agreed within 5 percent. Mean cyclic stresses, inelastic strain ranges, and inelastic work were significantly affected by the choice of inelastic constitutive model. The computing time per cycle for the nonlinear analyses was more than five times that required for the elastic analysis.
Kaufman, A.↗
Validation of a Thermo-Ablative Model of Elastomeric Internal Insulation Materials
In thermo-ablative material modeling, as in many fields of analysis, the quality of the existing models significantly exceeds that of the experimental data required for their validation. In an effort to narrow this gap, a laboratory-scale internal insulation test bed was developed that exposes insulation samples to realistic solid rocket motor (SRM) internal environments while being instrumented to record real-time rates of both model inputs (i.e., chamber pressure, total surface heat flux, and radiative heat flux) as well as model outputs (i.e., material decomposition depths (MDDs) and in-depth material temperatures). In this work, the measured SRM internal environment parameters were used in conjunction with equilibrium thermochemistry codes as inputs to one-dimensional thermo-ablative models of the PBINBR and CFEPDM insulation samples used in the lab-scale test firings. The computed MDD histories were then compared with those deduced from real-time X-ray radiography of the insulation samples, and the calculated in-depth temperatures were compared with those measured by embedded thermocouples. The results of this exercise emphasize the challenges of modeling and testing elastomeric materials in SRM environments while illuminating the path forward to improved fidelity.
Martin, Heath T.↗
MEDLI2 Material Response Model Development and Validation
During the entry of Mars Science Laboratory (MSL) the heatshield was equipped with the instrumentation suite Mars Entry, Descent, and Landing Instruments (MEDLI). In-depth thermocouple (TC) data was used to reconstruct the surface heating and temperatures. Discrepancies between MEDLI’s recorded in-depth heating data and the predicted thermal response and recession led to a campaign to characterize and test Mars Entry, Descent, and Landing Instrument 2 (MEDLI2) flight lot thermal protection materials (TPS) at relevant temperatures and pressures for Martian entry conditions. This paper covers the development and validation of MEDLI2 flight lot material response models for the heatshield material Phenolic Impregnated Carbon Ablator (PICA) and the backshell material Super-Lightweight Ablator (SLA-561V). Virgin and char thermal conductivities were updated as a function of temperature and pressure in the MEDLI2 specific material response models. Other material properties such as virgin and char density, emissivity, absorptivity, and specific heat capacitance was also characterized and compared to the “Heritage” models used during the TPS design phase of Mars 2020. Fully Implicit Ablation and Thermal response (FIAT) simulations were completed using the Heritage and MEDLI2 material response models to provide evidence of the increased accuracy of the MEDLI2 model. FIAT predicted in-depth temperatures were compared to flight lot certification ground-test arc jet test data and MEDLI2 flight thermocouple data.
Material response↗
Constitutive modeling and computational implementation for finite strain plasticity
This paper describes a simple alternate approach to the difficult problem of modeling material behavior. Starting from a general representation for a rate-tpe constitutive equation, it is shown by example how sets of test data may be used to derive restrictions on the scalar functions appearing in the representation. It is not possible to determine these functions from experimental data, but the aforementioned restrictions serve as a guide in their eventual definition. The implications are examined for hypo-elastic, isotropically hardening plastic, and kinematically hardening plastic materials. A simple model for the evolution of the 'back-stress,' in a kinematic-hardening plasticity theory, that is entirely analogous to a hypoelastic stress-strain relation is postulated and examined in detail in modeling finitely plastic tension-torsion test. The implementation of rate-type material models in finite element algorithms is also discussed.
Reed, K. W.↗
Nuclear Materials Process Modeling at the Y-12 National Security Complex
The Y-12 National Security Complex (Y-12) has implemented process modeling for various accountable nuclear materials operations that are performed throughout the plant. Using a discrete, event-based dynamic simulation program, key nuclear material streams are modeled, allowing Y-12 to effectively manage numerous points of interest within the plant’s production operations. Integration of the various material processes into a single, interdependent supply and demand model is one of the ongoing focuses within Y-12’s process modeling effort. The primary purpose of using dynamic simulation modeling is to allow for analysis of the nuclear materials inventories and forecasted supplies based on future demands. Analysis of these inventories includes capacity evaluation, bottleneck mitigation, and assessments of individual pieces of equipment to inform future facility investment decisions and associated project schedules. Modeling of the nuclear materials processes throughout the complex also allows for incorporation of changes relevant to production capabilities such as the upcoming transition of specific operations to the new Uranium Processing Facility. Prior to implementation of process modeling, Y-12 forecasted supply and demand of accountable nuclear materials streams using Microsoft Excel. With deterministic models such as Microsoft Excel, the annual forecasts, generated within data input condition parameters, can only provide a fixed point of data. Fixed data cannot simulate integrated material streams and account for the possibility of occurrences and other changes that dynamic simulations take into consideration. Y-12’s dynamic process modeling allows integrated simulations of multiple accountable nuclear materials processes, including supply and demand forecasting and analysis, and is a coordinated effort involving many steps of verification and validation (V&V), site briefings, testing, reporting, data mining, planning, and documentation that spans various programs throughout the Y-12 complex.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
User Manual - HydraGNN v5.0: Distributed Implementation of Multi-Tasking Graph Neural Networks
This document serves as the user manual for HydraGNN v5.0, a scalable graph neural network (GNN) architecture for simultaneous prediction of multiple target properties using multi-task learning (MTL). This version of HydraGNN has been developed primarily to support the development, training, and deployment of predictive graph-based deep learning (DL) models for atomistic materials modeling. HydraGNN is templated over 13 message-passing policies, including invariant models (GIN, PNA, PNAPlus, GAT, MFC, CGCNN, SAGE, SchNet, DimeNet) and equivariant models (EGNN, PNAEq, PAINN, MACE), and supports distributed training via distributed data parallelism (DDP), DeepSpeed, and Fully Sharded Data Parallelism (FSDP) on leadership-class supercomputers. Although HydraGNN can be applied to problems beyond atomistic materials modeling, its current use is confined to homogeneous graphs. Additional capabilities include machine-learned interatomic potentials with energy-conserving forces, General, Powerful, and Scalable Graph Transformer (GraphGPS) global attention, periodic boundary conditions, hyperparameter optimization, mixed-precision training, and uncertainty quantification.
97 MATHEMATICS AND COMPUTING↗
Code-to-Code Comparison, and Material Response Modeling of Stardust and MSL using PATO and FIAT
This report provides a code-to-code comparison between PATO, a recently developed high fidelity material response code, and FIAT, NASA's legacy code for ablation response modeling. The goal is to demonstrates that FIAT and PATO generate the same results when using the same models. Test cases of increasing complexity are used, from both arc-jet testing and flight experiment. When using the exact same physical models, material properties and boundary conditions, the two codes give results that are within 2% of errors. The minor discrepancy is attributed to the inclusion of the gas phase heat capacity (cp) in the energy equation in PATO, and not in FIAT.
ablative materials↗