Approach for the structural reliability analysis by the modified sensitivity model based on response surface function - Kriging model. Issue 8 (August 2022)

• Record Type: Journal Article
• Authors: Zhu, Lin; Qiu, Jianchun; Chen, Min; Jia, Minping
• Is Part Of: Heliyon. Volume 8:Issue 8(2022)
• Publication Date: 2022-08
• Subjects: Reliability -- Kriging model -- Sensitivity -- Working conditions -- Multiple coupling parameters; Research -- Periodicals; Medical sciences -- Periodicals; Natural history -- Periodicals; Social sciences -- Periodicals; Earth sciences -- Periodicals; Physical sciences -- Periodicals; 507.2
• DOI: 10.1016/j.heliyon.2022.e10046
• Languages: English
• ISSNs: 2405-8440

Abstract

Abstract: The sensitivity analysis model is widely used to describe the impacts of condition parameters on structural reliability. However, the classical sensitivity analysis model is limited to the small number of influence parameters and has no high prediction accuracy. Integrating the response surface function - Kriging model with Sobol sensitivity algorithm, a revised sensitivity model is proposed in this paper. And the quantitative sensitivity analysis for the influence of condition parameters on structural reliability are achieved through combining the revised sensitivity model with the experimental design of coupling parameters, range verification, the multi-body dynamics analysis and the structural statics analysis. The proposed analysis model is mainly applied in large structures with multiple influence parameters. Finally, a typical port crane is adopted to verify the accuracy and effectiveness of the proposed model. The results reveal that among the multiple parameters, the biggest sensitivity influence is the trolley position, while the least one is the lifting speed. The average prediction accuracy of the quantitative structural reliability index for the influencing parameters is up to 95.91%. The revised sensitivity model enables the accurate assessment of structural relativity with plenty of coupling condition parameters. Abstract : Reliability; Kriging model; Sensitivity; Working conditions; Multiple coupling parameters