Analysis of a polynomial chaos-kriging metamodel for uncertainty quantification in aerospace applications

Justin Weinmeister, Nelson Xie, Xinfeng Gao, Aditi Krishna Prasad, Sourajeet Roy

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

Metamodeling can be effective for uncertainty quantification in computational fluid dynamics simulations. In this research, we introduce modifications to our existing metamodel1 that combines a reduced polynomial chaos expansion approach and universal Kriging (RPCK) and evaluate the new metamodel for aerospace applications. Focus is given to determine the impact of optimization functions and autocorrelation functions on the solution accuracy by measuring the errors. Additionally, a new adaptive refinement algorithm is explored and the methodology is presented. Results show the metamodel’s robustness for aerospace engineering applications, including the non-smooth output of separated airflow.

Original languageEnglish
Title of host publicationAIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624105326
DOIs
StatePublished - 2018
Externally publishedYes
EventAIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 2018 - Kissimmee, United States
Duration: Jan 8 2018Jan 12 2018

Publication series

NameAIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 2018

Conference

ConferenceAIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 2018
Country/TerritoryUnited States
CityKissimmee
Period01/8/1801/12/18

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