Design of gradient nanotwinned metal materials using adaptive Gaussian process based surrogate models

Haofei Zhou, Xin Chen, Yumeng Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Inspired by gradient structures in the nature, Gradient Nanostructured (GNS) metals have emerged as a new class of materials with tunable microstructures. GNS metals can exhibit unique combinations of material properties in terms of ultrahigh strength, good tensile ductility and enhanced strain hardening, superior fatigue and wear resistance. However, it is still challenging to fully understand the fundamental gradient structure-property relationship, which hinders the rational design of GNS metals with optimized target properties. In this paper, we developed an adaptive design framework based on simulation-based surrogate modeling to investigate how the grain size gradient and twin thickness gradient affect the strength of GNS metals. The Gaussian Process (GP) based surrogate modeling technique with adaptive sequential sampling is employed for the development of surrogate models for the gradient structure-property relationship. The proposed adaptive design integrates physics-based simulation, surrogate modeling, uncertainty quantification and optimization, which can efficiently explore the design space and identify the optimized design of GNS metals with maximum strength using limited sampling data generated from high fidelity but computational expensive physics-based simulations.

Original languageEnglish (US)
Title of host publication45th Design Automation Conference
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791859186
DOIs
StatePublished - Jan 1 2019
EventASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2019 - Anaheim, United States
Duration: Aug 18 2019Aug 21 2019

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
Volume2A-2019

Conference

ConferenceASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2019
CountryUnited States
CityAnaheim
Period8/18/198/21/19

Keywords

  • Design
  • Engineering materials
  • Gaussian processes
  • Gradient nanostructured metals
  • Surrogate modeling

ASJC Scopus subject areas

  • Mechanical Engineering
  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Modeling and Simulation

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  • Cite this

    Zhou, H., Chen, X., & Li, Y. (2019). Design of gradient nanotwinned metal materials using adaptive Gaussian process based surrogate models. In 45th Design Automation Conference (Proceedings of the ASME Design Engineering Technical Conference; Vol. 2A-2019). American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/DETC2019-97659