ICME 2023: ICME for Non-Metals: III
Program Organizers: Charles Ward, AFRL/RXM; Heather Murdoch, U.S. Army Research Laboratory
Thursday 9:00 AM
May 25, 2023
Room: Caribbean VI & VII
Location: Caribe Royale
9:00 AM Invited
Multiscale Modeling and Machine Learning-based Digital Twin for Piezocomposite Damage Sensing: Somnath Ghosh1; 1Johns Hopkins University
This talk will discuss the development of a machine learning-enabled, multiscale-multiphysics computational platform for multifunctional piezocomposites. It will constitute a digital twin for detecting location-specific damage evolution from surface electric field sensors. The integrated platform incorporates modules involving bottom-up and top-down multiscale modeling coupled with various machine learning operations. The first module involves development of a finite deformation parametrically upscaled coupled constitutive-damage models (PUCCDM) for structural-scale electromechanical response, by hierarchical modeling of microstructures undergoing progressive damage. The PUCCDM incorporates microstructural morphology in its coefficients in the form of representative aggregated microstructural parameters (RAMPs), determined using machine learning on data generated by micromechanical analysis. The micromechanical model consists of a coupled electromechanical finite deformation phase field model for crack initiation and propagation in nonuniform piezocomposite microstructures. Finally, coupled convolutional neural and long-short term memory networks (ConvLSTM) are deployed to predict current damage for correlating sensor-based electric signals to subsurface damage indicators.
9:30 AM
True Multiscale Simulations of Virtual Coupon Tests in Composites.: Kedar Malusare1; Kennedy Neves1; Luiz Lima1; Flavio Souza1; 1Siemens
Characterization of the mechanical response of composite layups is often done by means of the so-called coupon testing, in which representative specimen of the layups are tested under the guidelines of ASTM standards. Recently, virtual coupon testing is being used as an alternative or preliminary step to the actual tests. In these virtual tests, finite element simulations of the layups are solved under the same conditions given by the standards, allowing a broader design space and a faster, cheaper material design.In this work, a true multiscale approach is proposed for capturing the complexity of the material behavior in virtual composite coupon testing. Finite element models of representative volume elements at the microstructural level are solved simultaneously with the solution in the coupon level for a better representation of the phenomena happening in all scales of the test. Results are compared with experimental results from the literature, showing good agreement.
9:50 AM
Damage Prediction of Sintered α-SiC Using Thermo-mechanical Coupled Fracture Model: Jason Sun1; Joseph Marziale1; James Chen1; 1University at Buffalo
A coupled thermo-mechanical fracture model is presented to predict the damage of α-SiC as a representation of brittle ceramics over a wide range of temperatures (20-1400°C). Temperature-dependent damage prediction is a crucial link of ICME for ceramics in applications like thermal protection systems of hypersonic vehicles. The model, which has been implemented into MOOSE, links between material properties and performance. The model contains modules of elasticity, damage phase field, and heat conduction. Analytical approaches for determining crack length scales of simple shear and tension are presented. Validation tests are conducted for both flexural strength and fracture toughness over the specified range of temperatures. Both the flexural strength simulation results and mode I fracture toughness results agree with the experimental data. Mode II and mixed mode fracture toughness simulations results are presented with the modified G-criterion. Finally, the parallel computing capabilities of the model are considered in various scalability tests.
10:10 AM
Machine-learned Structural Descriptors for Metallic and Covalent Glassy Materials: Thomas Hardin1; 1Sandia National Laboratories
Glassy materials, like polycrystalline metals, have a mutable internal structural state that affects stress-strain response and functional properties. The internal structural state of polycrystalline metals is well-represented by grain sizes, dislocation densities, and so forth. However, a concise set of physically real, broadly applicable structural descriptors remains enigmatic for many glasses. This gap hobbles the development of multi-scale and continuum models with engineering relevance for these materials. We report a dimensionality reduction method based on diffusion maps that parameterizes the low-dimensional manifold of local structural states found in the glass. Distributions of these machine-learned parameters constitute a computationally convenient structural description of the glass. We show how the machine-learned structural description can be linked to fracture behavior in silica glass, and to plasticity in metallic glass. SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525 (SAND2022-16339 A).
10:30 AM
Design of Titanium Aluminum Reinforced with TiB2 Composite for Powder Manufacturing Using Integrated Computational Materials Engineering: Ayodeji Afolabi1; Peter Olubambi1; 1University of Johannesburg
Extensive risk reduction demonstrations and stringent requirements for efficient aero-engines cleared the way for the commercial launch of titanium aluminides. Low-pressure turbine blades (LPTBs), which usually replace cast nickel superalloys in advanced aero engines, are currently the most alluring application. Fabricating titanium aluminium matrix composites (TAMCs) with ceramic in the metal matrix offers a possible solution. While maintaining low density, TAMCs often have more advanced qualities than matrix alloys, including a high specific modulus, strength, wear resistance, and thermal stability. The isotropic characteristics, simplicity of manufacture, and low cost of particle-reinforced titanium aluminium matrix composites (PRTAMCs) make them one of the best TAMCs. The summary of current developments, issues with reproducibility, and potentially discussed and how TiAl-TiB2 LPTB development went from successful laboratory tests to successful production insertions in industrially scaled commercial jet engines. The framework and toolkits for integrated computational materials engineering modelling created by academics will be shown.
10:50 AM Break