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At least 73 records · Page 4

Modeling material failure with a vectorized routine

The computational aspects of modelling material failure in structural wood members are presented with particular reference to vector processing aspects. Wood members are considered to be highly orthotropic, inhomogeneous, and discontinuous due to the complex microstructure of wood material and the presence of natural growth characteristics such as knots, cracks and cross grain in wood members. The simulation of strength behavior of wood members is accomplished through the use of a special purpose finite element/fracture mechanics routine, program STARW (Strength Analysis Routine for Wood). Program STARW employs quadratic finite elements combined with singular crack tip elements in a finite element mesh. Vector processing techniques are employed in mesh generation, stiffness matrix formation, simultaneous equation solution, and material failure calculations. The paper addresses these techniques along with the time and effort requirements needed to convert existing finite element code to a vectorized version. Comparisons in execution time between vectorized and nonvectorized routines are provided.

Cramer, S. M.↗

Modeling Material Interfaces with the Six-Equation Model in FLEXO

FLEXO is a multiphysics code developed at Sandia National Laboratories for predictive simulation of pulsed power target physics with extended magnetohydrodynamics modeling. Given this application space, FLEXO must be able to perform high-fidelity simulations of pulsed-power systems that include multiple materials. This work presents the augmentation of FLEXO with a six-equation model for multimaterial flow. We design and analyze discretizations of the six-equation model, emphasizing desirable properties for robust multimaterial simulation. We also present solution limiting, bounds preservation, and pressure equilibration/relaxation techniques that enhance the robustness of the overall multimaterial scheme. We present a suite of test problems to document these new capabilities of the FLEXO code.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Training material models using gradient descent algorithms

High temperature design requires accurate constitutive models to describe material inelastic deformation and failure behavior. Oftentimes, calibrating accurate models devolves into the problem of fitting the model parameters against experimental test data. Here, we present the pyopmat package, an open source framework for calibrating constitutive models against experiment data subjected to various loading conditions using machine learning techniques. The package calculates the exact gradient of the model response with respect to the parameters using a combination of automatic differentiation and the adjoint method. Given this exact gradient, we compare the performance of several gradient-based optimization techniques in fitting realistic constitutive models against data. Here, we demonstrate the efficiency and accuracy of our package through example problems using both synthetic data, generated using known parameter sets, under monotonic and cyclic loading conditions and also with an example applying the techniques developed here to actual high temperature creep-fatigue test data.

36 MATERIALS SCIENCE↗

Development of a Continuum Damage Mechanics Material Model of a Graphite-Kevlar(Registered Trademark) Hybrid Fabric for Simulating the Impact Response of Energy Absorbing Kevlar(Registered Trademark) Hybrid Fabric for Simulating the Impact Response of Energy Absorbing

This paper describes the development of input properties for a continuum damage mechanics based material model, Mat 58, within LS-DYNA(Registered Trademark) to simulate the response of a graphite-Kevlar(Registered Trademark) hybrid plain weave fabric. A limited set of material characterization tests were performed on the hybrid graphite-Kevlar(Registered Trademark) fabric. Simple finite element models were executed in LS-DYNA(Registered Trademark) to simulate the material characterization tests and to verify the Mat 58 material model. Once verified, the Mat 58 model was used in finite element models of two composite energy absorbers: a conical-shaped design, designated the "conusoid," fabricated of four layers of hybrid graphite-Kevlar(Registered Trademark) fabric; and, a sinusoidal-shaped foam sandwich design, designated the "sinusoid," fabricated of the same hybrid fabric face sheets with a foam core. Dynamic crush tests were performed on components of the two energy absorbers, which were designed to limit average vertical accelerations to 25- to 40-g, to minimize peak crush loads, and to generate relatively long crush stroke values under dynamic loading conditions. Finite element models of the two energy absorbers utilized the Mat 58 model that had been verified through material characterization testing. Excellent predictions of the dynamic crushing response were obtained.

Jackson, Karen E.↗

Quantification of Error Associated with Using Misaligned Meshes in Continuum Damage Mechanics Material Models for Matrix Crack Growth Predictions in Composites

The ability of a material model to capture in-plane matrix mode I and mode II crack growth is an essential component for modeling ply level damage evolution in composite structures. Previous studies using a continuum damage mechanics (CDM) approach have shown success in satisfying benchmark solutions for mode I and II crack growth. However, success was shown using a fiber-aligned meshing strategy, which encourages matrix cracks to propagate in a single band of elements, along the fiber direction. Generating a fiber-aligned mesh becomes a highly involved process for laminates including off-axis (non 0° or 90°) plies. The objective of this study is to quantify the effect of non-fiber aligned mesh discretization on predictions of in-plane matrix crack propagation. The approach taken incrementally varies the mesh orientation angle relative to the fiber orientation; more specifically, misaligned meshes are used to quantify the effect of element angle orientation relative to the initial crack orientation on the energy released during matrix crack propagation simulations using a CDM method. CDM solutions obtained with the misaligned meshes are evaluated against known benchmarks for mode I and II matrix crack growth. The CDM solutions reveal a near-polynomial trend of increased predicted failure stress with increased mesh misalignment angle; hence implying a potential relationship between element orientation angle and apparent fracture toughness.

Justusson, Brian↗

Summary of FY2024 Experimental Results to Support Development of New Inelastic Material Models and Validation of Section III, Division 5, Class A Design Rules

To address the data gap crucial for updating existing viscoplastic constitutive material models for the Class A materials in the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code, Section III, Division 5, High Temperature Reactors (ASME, 2023) for inelastic design analysis, Oak Ridge National Laboratory (ORNL) conducted experimental studies on Alloy 800H and Alloy 617 across a range of temperatures up to their maximum temperature limits in Section III, Division 5. The studies aim to characterize the materials' deformation behavior under both strain-controlled mechanical cyclic loading and thermal cycling conditions. This report summarizes ORNL's FY 2024 experimental findings on Alloy 800H and Alloy 617, focusing on pure fatigue tests, cyclic stress-strain curves, thermomechanical fatigue experiments, and verification of the high temperature cyclic damage summation design rules.

36 MATERIALS SCIENCE↗

A Case for High-Fidelity Material Response Modeling

Material response modeling of heatshields for planetary entry vehicles has remained largely unchanged since Aerotherm Corp. introduced the CMA program in 1967. Modern models, like FIAT, have tread the same path, introducing efficiencies and better material property data along the way, but otherwise following the same underlying model paradigm. The CMA approach has worked well for heatshield design up to this point. However, there are three motivations for the material response community to pursue higher fidelity beyond simplified, CMA-derived models. The first motivation is that missions are becoming increasingly demanding and complex and, as they do, confidence in simplified models naturally decreases. Second, reliability of materials is now as much or more of a driving concern for mission designers than thermal response. Third, NASA and other agencies are increasingly interested in flight instrumentation for engineering science. This latter motivation places far stricter requirements on model accuracy in order to meet requirements for flight environment reconstruction.

Barnhardt, Michael D.↗

Accelerating Multiscale Materials Modeling with Machine Learning

The focus of this project is to accelerate and transform the workflow of multiscale materials modeling by developing an integrated toolchain seamlessly combining DFT, SNAP, LAMMPS, (shown in Figure 1-1) and a machine-learning (ML) model that will more efficiently extract information from a smaller set of first-principles calculations. Our ML model enables us to accelerate first-principles data generation by interpolating existing high fidelity data, and extend the simulation scale by extrapolating high fidelity data (10 2 atoms) to the mesoscale (10 4 atoms). It encodes the underlying physics of atomic interactions on the microscopic scale by adapting a variety of ML techniques such as deep neural networks (DNNs), and graph neural networks (GNNs). We developed a new surrogate model for density functional theory using deep neural networks. The developed ML surrogate is demonstrated in a workflow to generate accurate band energies, total energies, and density of the 298K and 933K Aluminum systems. Furthermore, the models can be used to predict the quantities of interest for systems with more number of atoms than the training data set. We have demonstrated that the ML model can be used to compute the quantities of interest for systems with 100,000 Al atoms. When compared with 2000 Al system the new surrogate model is as accurate as DFT, but three orders of magnitude faster. We also explored optimal experimental design techniques to choose the training data and novel Graph Neural Networks to train on smaller data sets. These are promising methods that need to be explored in the future.

36 MATERIALS SCIENCE↗

Local Debonding and Fiber Breakage in Composite Materials Modeled Accurately

A prerequisite for full utilization of composite materials in aerospace components is accurate design and life prediction tools that enable the assessment of component performance and reliability. Such tools assist both structural analysts, who design and optimize structures composed of composite materials, and materials scientists who design and optimize the composite materials themselves. NASA Glenn Research Center's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) software package (http://www.grc.nasa.gov/WWW/LPB/mac) addresses this need for composite design and life prediction tools by providing a widely applicable and accurate approach to modeling composite materials. Furthermore, MAC/GMC serves as a platform for incorporating new local models and capabilities that are under development at NASA, thus enabling these new capabilities to progress rapidly to a stage in which they can be employed by the code's end users.

Bednarcyk, Brett A.↗

Semi-Empirical Material Model for Hydrogen Uptake Kinetics by 1,4-bis(phenylethynyl)benzene (DEB)-based Getters

We report on development of a semi-empirical model describing the kinetics of H 2 /D 2 reaction with 1,4-bis(phenylethynyl)benzene (DEB)-based getters in pellet and powder form. The physical basis of the model is solid-state diffusion of DEB plus reaction of DEB with H atoms on the surface of nanometer-scale Pd catalyst particles. The purpose of this material model is to facilitate more accurate predictions of performance for DEB-based getter assemblies. These predictions will be accomplished by integrating the model presented here into finite element, reaction/diffusion simulations of getter assembly hydrogen uptake performance. As of Fall 2020, this integration is underway.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Constitutive and damage material modeling in a high pressure hydrogen environment

Numerous components in reusable space propulsion systems such as the SSME are exposed to high pressure gaseous hydrogen environments. Flow areas and passages in the fuel turbopump, fuel and oxidizer preburners, main combustion chamber, and injector assembly contain high pressure hydrogen either high in purity or as hydrogen rich steam. Accurate constitutive and damage material models applicable to high pressure hydrogen environments are therefore needed for engine design and analysis. Existing constitutive and cyclic crack initiation models were evaluated only for conditions of oxidizing environments. The main objective is to evaluate these models for applicability to high pressure hydrogen environments.

Russell, D. A.↗

Modeling Materials: Design for Planetary Entry, Electric Aircraft, and Beyond

NASA missions push the limits of what is possible. The development of high-performance materials must keep pace with the agency's demanding, cutting-edge applications. Researchers at NASA's Ames Research Center are performing multiscale computational modeling to accelerate development times and further the design of next-generation aerospace materials. Multiscale modeling combines several computationally intensive techniques ranging from the atomic level to the macroscale, passing output from one level as input to the next level. These methods are applicable to a wide variety of materials systems. For example: (a) Ultra-high-temperature ceramics for hypersonic aircraft-we utilized the full range of multiscale modeling to characterize thermal protection materials for faster, safer air- and spacecraft, (b) Planetary entry heat shields for space vehicles-we computed thermal and mechanical properties of ablative composites by combining several methods, from atomistic simulations to macroscale computations, (c) Advanced batteries for electric aircraft-we performed large-scale molecular dynamics simulations of advanced electrolytes for ultra-high-energy capacity batteries to enable long-distance electric aircraft service; and (d) Shape-memory alloys for high-efficiency aircraft-we used high-fidelity electronic structure calculations to determine phase diagrams in shape-memory transformations. Advances in high-performance computing have been critical to the development of multiscale materials modeling. We used nearly one million processor hours on NASA's Pleiades supercomputer to characterize electrolytes with a fidelity that would be otherwise impossible. For this and other projects, Pleiades enables us to push the physics and accuracy of our calculations to new levels.

Supercomputing↗

Critical impact of experimentally-driven strut level anisotropic material models in advanced stress analysis of additively manufactured lattice structures

The rapid acceleration in materials discovery may overshadow the importance of thoroughly understanding the mechanical performance of newly developed materials in demanding environments. The recent interest in combining parametric studies with machine learning techniques to explore how changes in specific processing parameters or model inputs affect the overall behavior of a material system can only be truly beneficial if the governing constitutive relations describing material behavior are accurately established. In this study, we demonstrate the critical impact of accurately representing strut-level anisotropic material behavior in advanced stress analysis of additively manufactured lattice structures (AMLS). We introduce a systematic experimental and modeling approach for developing strut-level anisotropic elastoplastic material models that account for the influence of microstructural features such as porosity, texture, and surface roughness on the development of local anisotropic mechanical properties, which vary with strut orientation relative to the build direction (BD). As a result the presented material model captures and relates the statistics of spatially varying struts’ microstructural features to the local stress distribution. Our findings suggest that incorporating strut-level anisotropic material behavior into unit cell analysis significantly influences the load distribution and evolution of local stresses within the structure. Therefore, accounting for this anisotropy is critical for developing an understanding of unit cell behavior and performance, including subsequent topology/component design optimization based on this analysis.

Sahoo, Subhadip [University of Arizona]↗

Atomistic Materials Modeling of High-Pressure Hydrogen Interactions in Ethylene Propylene Diene Monomer (EPDM) Rubber

Elastomeric rubbers serve a vital role as sealing materials in the hydrogen storage and transport infrastructure. With applications including O-rings and hose-liners, these components are exposed to pressurized hydrogen at a range of temperatures, cycling rates, and pressure extremes. Cyclic (de)pressurization is known to degrade these materials through the process of cavitation. This readily visible failure mode occurs as a fracture or rupture of the material and is due to the oversaturated gas localizing to form gas bubbles. Computational modeling in the Hydrogen Materials Compatibility Program (H-Mat), co-led by Sandia National Laboratories and Pacific Northwest National Laboratory, employs multi-scale simulation efforts to build a predictive understanding of hydrogen-induced damage in materials. Modeling efforts within the project aim to provide insight into how to formulate materials that are less sensitive to high-pressure hydrogen-induced failure. In this document, we summarize results from atomistic molecular dynamics simulations, which make predictive assessments of the effects of compositional variations in the commonly used elastomer, ethylene propylene diene monomer (EPDM).

08 HYDROGEN↗