6th International Congress on 3D Materials Science (3DMS 2022): 3D Data Processing II: Leveraging Big Data
Program Organizers: Dorte Juul Jensen, Technical University of Denmark; Marie Charpagne, University of Illinois; Keith Knipling, Naval Research Laboratory; Klaus-Dieter Liss, University of Wollongong; Matthew Miller, Cornell University; David Rowenhorst, Naval Research Laboratory
Monday 1:20 PM
June 27, 2022
Room: Columbia A&B
Location: Hyatt Regency Washington on Capitol Hill
Session Chair: Kelly Nygren, Cornell University
1:20 PM Invited
Pushing the Limits of HEDM / 3DXRD: Hemant Sharma1; Peter Kenesei1; Jun-Sang Park1; Jonathan Almer1; 1Argonne National Laboratory
High Energy Diffraction Microscopy enables in-situ non-destructive characterization of material microstructures in 3D. This talk will describe multiple experiments carried out at Sector 1, APS demonstrating significant advances in the HEDM technique. Leveraging improvements in both experimental and data reduction capabilities, materials with high deformations / large number of grains can be characterized with multiple modalities including near-field and far-field HEDM. The talk will also describe recent improvements in the MIDAS software package for reduction of HEDM and Tomography data.
1:50 PM
Robust, Automated Analysis of Intragranular Heterogeneity: Austin Gerlt1; Donald Boyce2; Joel Bernier3; Mark Obstalecki4; Paul Shade4; Stephen Niezgoda1; 1The Ohio State University; 2Cornell University; 3Lawrence Livermore National Laboratory; 4United States Air Force
Far-Field High Energy Diffraction Microscopy (ff-HEDM) is often used to investigate the orientation and average strain of individual grains within a polycrystalline material. Additionally though, analysis of per-grain data can provide valuable insight into the intragranular heterogeneity, notably the per-grain Orientation Distribution function (ODF) and stress/strain orientation distribution function (SODF). However, extracting this information takes a significant amount of post processing and specialist knowledge and is not available to the typical HEDM user.The purpose of this work is to significantly reduce the complexity of obtaining intragranular heterogeneity information by providing a high level generalized ODF and SODF solver for ff-HEDM data. This tool is written as an extension to HEXRD and is intended to help facilitate the rapid exploration by even casual users of distribution functions within single grains. Experimental demonstrations are provided to help highlight the questions that can be answered with this functionality.
2:10 PM
Deep Learning-Based 3D Damage Quantification for Natural Cellular Solids: Ziling Wu1; Ting Yang1; Ling Li1; Yunhui Zhu1; 1Virginia Tech
Quantitative descriptions of deformation processes in 3D are important for the understanding of the mechanical properties of structural materials. In particular, cellular solids represent a challenging group of lightweight complex structural materials. In this work, we present a deep learning-based computational framework for quantitative detection, registration, and analysis of different forms of damages during the entire deformation process collected from high-resolution synchrotron-based X-ray computed microtomography of a natural cellular solid, sea urchin spines. We developed two neural networks, CrackNet and DensifyNet in order to learn and detect the features of the destroyed struts, respectively. Our automatic detection method proves to be accurate and dramatically more efficient compared to manual labeling. The detected damage regions can be further registered to the cellular network to study the formation of damage and propagation patterns. This method could also be applied to other cellular solids’ damage characterization to investigate their deformation mechanisms.
2:30 PM
Geometric Reconstruction and Volumetric Meshing Procedures for Mesoscale Level Finite Element Simulations: Ottmar Klaas1; Adrian Loghin1; Mark Beall1; 1Simmetrix Inc.
Existing engineering design tools can provide digital technology to model-based quantification approaches in material design. Geometric modeling techniques and automated volume meshing algorithms available in CAD/CAE technology can be used to close the gap efficiently between a 3D microstructure representation and a finite element simulation. 3D microstructure examples (Ni-base superalloy, Ti64, W-Cu, Al 7075-T651) will be presented to describe techniques to (i) prepare a 3D voxel dataset, (ii) create a valid geometric model, and, (iii) create finite element meshes. The critical differentiator in the presented toolset is the creation of the geometric model which provides a high-level domain description to support definition of material properties, boundary conditions, etc. Standard mesh generation algorithms can then be applied to create multiple finite element meshes which are not constrained by the original voxel size.
2:50 PM Cancelled
Data-mining of In-situ TEM Experiments on CoCrFeMnNi Alloys: 4D Reconstruction of Dislocation Dynamics and Sampling of the Energy Landscape: Chen Zhang1; Hengxu Song1; Daniela Oliveros2; Marc Legros2; Stefan Sandfeld1; 1Forschungszentrum Jülich; 2CEMES-CNRS
During in-situ transmission electron microscopy (TEM) straining experiments of high entropy alloys (HEA), pinning points frequently hinder the motion of dislocations. They lead to abrupt changes in the curvature of moving dislocations in the middle of in situ samples. Because their nature remains a key question in HEA, we propose a data-mining strategy for extracting quantitative information from the real-time dynamics of dislocation lines to retrieve the local strength of these obstacles. An experiment on equimolar CoCrFeMnNi HEA (Cantor alloy) demonstrates the capabilities of our data-mining approach. We show how the 3D dislocation structure can be reconstructed and the force variation along the lines retrieved automatically. A novel coarse-graining method is employed to statistically extract quantitative information on the nature, dispersion and strength of pinning points, along with their evolution upon deformation. This subsequently provides new ideas for understanding deformation mechanisms in high-entropy alloys.
3:10 PM Break