Dataset Information

Multi-modal Dataset of a Polycrystalline Metallic Material: 3D Microstructure and Deformation Fields.

ABSTRACT: The development of high-fidelity mechanical property prediction models for the design of polycrystalline materials relies on large volumes of microstructural feature data. Concurrently, at these same scales, the deformation fields that develop during mechanical loading can be highly heterogeneous. Spatially correlated measurements of 3D microstructure and the ensuing deformation fields at the micro-scale would provide highly valuable insight into the relationship between microstructure and macroscopic mechanical response. They would also provide direct validation for numerical simulations that can guide and speed up the design of new materials and microstructures. However, to date, such data have been rare. Here, a one-of-a-kind, multi-modal dataset is presented that combines recent state-of-the-art experimental developments in 3D tomography and high-resolution deformation field measurements.

SUBMITTER: Stinville JC

PROVIDER: S-EPMC9343453 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Multi-modal Dataset of a Polycrystalline Metallic Material: 3D Microstructure and Deformation Fields.

Stinville J C JC Hestroffer J M JM Charpagne M A MA Polonsky A T AT Echlin M P MP Torbet C J CJ Valle V V Nygren K E KE Miller M P MP Klaas O O Loghin A A Beyerlein I J IJ Pollock T M TM

Scientific data 20220801 1

The development of high-fidelity mechanical property prediction models for the design of polycrystalline materials relies on large volumes of microstructural feature data. Concurrently, at these same scales, the deformation fields that develop during mechanical loading can be highly heterogeneous. Spatially correlated measurements of 3D microstructure and the ensuing deformation fields at the micro-scale would provide highly valuable insight into the relationship between microstructure and macro ...[more]

PMID: 35915100

Similar Datasets

Project description:The right ventricular myocardium, much like the rest of the right side of the heart, has been consistently understudied. Presently, little is known about its mechanics, its microstructure, and its constitutive behavior. In this work, we set out to provide the first data on the mechanics of the mature right ventricular myocardium in both simple shear and uniaxial loading and to compare these data to the mechanics of the left ventricular myocardium. To this end, we tested ovine tissue samples of the right and left ventricle under a comprehensive mechanical testing protocol that consisted of six simple shear modes and three tension/compression modes. After mechanical testing, we conducted a histology-based microstructural analysis on each right ventricular sample that yielded high resolution fiber distribution maps across the entire samples. Equipped with this detailed mechanical and histological data, we employed an inverse finite element framework to determine the optimal form and parameters for microstructure-based constitutive models. The results of our study show that right ventricular myocardium is less stiff then the left ventricular myocardium in the fiber direction, but similarly exhibits non-linear, anisotropic, and tension/compression asymmetric behavior with direction-dependent Poynting effect. In addition, we found that right ventricular myocardial fibers change angles transmurally and are dispersed within the sheet plane and normal to it. Through our inverse finite element analysis, we found that the Holzapfel model successfully fits these data, even when selectively informed by rudimentary microstructural information. And, we found that the inclusion of higher-fidelity microstructural data improved the Holzapfel model's predictive ability. Looking forward, this investigation is a critical step towards understanding the fundamental mechanical behavior of right ventricular myocardium and lays the groundwork for future whole-organ mechanical simulations.

Dataset Information

Multi-modal Dataset of a Polycrystalline Metallic Material: 3D Microstructure and Deformation Fields.

Publications

Multi-modal Dataset of a Polycrystalline Metallic Material: 3D Microstructure and Deformation Fields.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets