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Title: Adjoint-based optimization of mechanical performance in polycrystalline materials and structures through texture control

Abstract

The texture of a polycrystalline material refers to the preferred orientation of the grains within the material. In metallic materials, texture can significantly affect the mechanical properties such as elastic moduli, yield stress, strain hardening, and fracture toughness. Recent advances in additive manufacturing of metallic materials offer the possibility in the not too distant future of controlling the spatial variation of texture. In this work, we investigate the advantages, in terms of mechanical performance, of allowing the texture to vary spatially. We use an adjoint-based gradient optimization algorithm within a finite element solver (COMSOL) to optimize several engineering quantities of interest in a simple structure (hole in a plate) and loading (uniaxial tension) condition. As a first step to general texture optimization, we consider the idealized case of a pure fiber texture in which the homogenized properties are transversely isotropic. In this special case, the only spatially varying design variables are the three Euler angles that prescribe the orientation of the homogenized material at each point within the structure. This work paves a new way to design metallic materials for tunable mechanical properties at the microstructure level.

Authors:
 [1];  [1];  [1]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1375571
Report Number(s):
SAND-2017-8614R
656192
DOE Contract Number:
AC04-94AL85000
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE

Citation Formats

Gu, Grace, Brown, Judith Alice, and Bishop, Joseph E. Adjoint-based optimization of mechanical performance in polycrystalline materials and structures through texture control. United States: N. p., 2017. Web. doi:10.2172/1375571.
Gu, Grace, Brown, Judith Alice, & Bishop, Joseph E. Adjoint-based optimization of mechanical performance in polycrystalline materials and structures through texture control. United States. doi:10.2172/1375571.
Gu, Grace, Brown, Judith Alice, and Bishop, Joseph E. Tue . "Adjoint-based optimization of mechanical performance in polycrystalline materials and structures through texture control". United States. doi:10.2172/1375571. https://www.osti.gov/servlets/purl/1375571.
@article{osti_1375571,
title = {Adjoint-based optimization of mechanical performance in polycrystalline materials and structures through texture control},
author = {Gu, Grace and Brown, Judith Alice and Bishop, Joseph E.},
abstractNote = {The texture of a polycrystalline material refers to the preferred orientation of the grains within the material. In metallic materials, texture can significantly affect the mechanical properties such as elastic moduli, yield stress, strain hardening, and fracture toughness. Recent advances in additive manufacturing of metallic materials offer the possibility in the not too distant future of controlling the spatial variation of texture. In this work, we investigate the advantages, in terms of mechanical performance, of allowing the texture to vary spatially. We use an adjoint-based gradient optimization algorithm within a finite element solver (COMSOL) to optimize several engineering quantities of interest in a simple structure (hole in a plate) and loading (uniaxial tension) condition. As a first step to general texture optimization, we consider the idealized case of a pure fiber texture in which the homogenized properties are transversely isotropic. In this special case, the only spatially varying design variables are the three Euler angles that prescribe the orientation of the homogenized material at each point within the structure. This work paves a new way to design metallic materials for tunable mechanical properties at the microstructure level.},
doi = {10.2172/1375571},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Aug 01 00:00:00 EDT 2017},
month = {Tue Aug 01 00:00:00 EDT 2017}
}

Technical Report:

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