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Intelligent vectorial surrogate modeling framework for multi-objective reliability estimation of aerospace engineering structural systems

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Intelligent vectorial surrogate modeling framework for multi-objective reliability estimation of aerospace engineering structural systems
To improve the computational efficiency and accuracy of multi-objective reliability esti-mation for aerospace engineering structural systems,the Intelligent Vectorial Surrogate Modeling(IVSM)concept is presented by fusing the compact support region,surrogate modeling methods,matrix theory,and Bayesian optimization strategy.In this concept,the compact support region is employed to select effective modeling samples;the surrogate modeling methods are employed to establish a functional relationship between input variables and output responses;the matrix the-ory is adopted to establish the vector and cell arrays of modeling parameters and synchronously determine multi-objective limit state functions;the Bayesian optimization strategy is utilized to search for the optimal hyperparameters for modeling.Under this concept,the Intelligent Vectorial Neural Network(IVNN)method is proposed based on deep neural network to realize the reliability analysis of multi-objective aerospace engineering structural systems synchronously.The multi-output response function approximation problem and two engineering application cases(i.e.,land-ing gear brake system temperature and aeroengine turbine blisk multi-failures)are used to verify the applicability of IVNN method.The results indicate that the proposed approach holds advantages in modeling properties and simulation performances.The efforts of this paper can offer a valuable ref-erence for the improvement of multi-objective reliability assessment theory.

Intelligent vectorial surro-gate modelingIntelligent vectorial neural networkAerospace engineering struc-tural systemsMulti-objective reliability estimationMatrix theory

Da TENG、Yunwen FENG、Junyu CHEN、Cheng LU

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School of Aeronautics,Northwestern Polytechnical University,Xi'an 710072,China

Intelligent vectorial surro-gate modeling Intelligent vectorial neural network Aerospace engineering struc-tural systems Multi-objective reliability estimation Matrix theory

2024

10.1016/j.cja.2024.06.020

中国航空学报(英文版)
中国航空学会

中国航空学报(英文版)

CSTPCDEI
影响因子：0.847
ISSN：1000-9361
年,卷(期)：2024.37(12)