MIXED-VARIABLE GLOBAL SENSITIVITY ANALYSIS WITH APPLICATIONS TO DATA-DRIVEN COMBINATORIAL MATERIALS DESIGN

Yigitcan Comlek, Liwei Wang, Wei Chen*

*Corresponding author for this work

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

1 Scopus citations

Abstract

Global Sensitivity Analysis (GSA) is the study of the influence of any given inputs on the outputs of a model. In the context of engineering design, GSA has been widely used to understand both individual and collective contributions of design variables on the design objectives. So far, global sensitivity studies have often been limited to design spaces with only quantitative (numerical) design variables. However, many engineering systems also contain, if not only, qualitative (categorical) design variables in addition to quantitative design variables. In this paper, we integrate the novel Latent Variable Gaussian Process (LVGP) with Sobol' analysis to develop the first metamodel-based mixed-variable GSA method. Through two analytical case studies, we first validate and demonstrate the effectiveness of our proposed method for mixed-variable problems. Furthermore, while the new metamodel-based mixed-variable GSA method can benefit various engineering design applications, we employ our method with multi-objective Bayesian optimization (BO) to accelerate the Pareto front design exploration in many-level combinatorial design spaces. Specifically, we implement a sensitivity-aware design framework for metal-organic framework (MOF) materials that are constructed only from qualitative design variables and show the benefits of our method for expediting the exploration of novel MOF candidates from a many-level large combinatorial design space.

Original languageEnglish (US)
Title of host publication49th Design Automation Conference (DAC)
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791887318
DOIs
StatePublished - 2023
EventASME 2023 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2023 - Boston, United States
Duration: Aug 20 2023Aug 23 2023

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
Volume3B

Conference

ConferenceASME 2023 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2023
Country/TerritoryUnited States
CityBoston
Period8/20/238/23/23

Keywords

  • Bayesian Optimization
  • Global Sensitivity Analysis
  • Latent Variable Gaussian Process
  • Metamodels
  • Mixed-Variable Design Spaces

ASJC Scopus subject areas

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

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