Probabilistic failure analysis for icme using an adjoint-based lattice particle method

Yi Gao, Yongming Liu

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

Abstract

The discontinuous model has the benefits that spatial singularities or even discontinuities can be avoided compared with the conventional continuum-based computation models. For that reason, an adjoint-based lattice particle method is developed for probabilistic failure analysis of ICME. The performance function value is estimated by Lattice Particle Model (LPM) and the model can be equivalent to solving the system of linear equations consistent with the finite element analysis. The response of the LPM model is regarded as the additional constraints in the probabilistic analysis. And the reliability analysis will be converted to a constrained optimization problem based on FORM. Then, the failure probability is calculated by the efficient gradient-based optimization approach, in which the gradient information is evaluated by the dimension-unrelated adjoint method. The method can overcome the difficulty of “curse of dimensionality” and can be used to solve the extremely large-dimensional problems with a very low computational cost. The demonstrated example shows the good feasibility and efficiency of the method. Finally, several potential future research works are discussed following the conclusions.

Original languageEnglish (US)
Title of host publicationAIAA Scitech 2019 Forum
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624105784
DOIs
StatePublished - 2019
EventAIAA Scitech Forum, 2019 - San Diego, United States
Duration: Jan 7 2019Jan 11 2019

Publication series

NameAIAA Scitech 2019 Forum

Conference

ConferenceAIAA Scitech Forum, 2019
Country/TerritoryUnited States
CitySan Diego
Period1/7/191/11/19

ASJC Scopus subject areas

  • Aerospace Engineering

Fingerprint

Dive into the research topics of 'Probabilistic failure analysis for icme using an adjoint-based lattice particle method'. Together they form a unique fingerprint.

Cite this