Approach for the structural reliability analysis by the modified sensitivity model based on response surface function- Kriging model

被引:10
作者
Lin, Zhu [1 ]
Qiu, Jianchun [1 ]
Min, Chen [2 ]
Jia, Minping [3 ]
机构
[1] Yangzhou Univ, Sch Mech Engn, Yangzhou 225001, Peoples R China
[2] Xian Jiaotong Liverpool Univ, Sch Adv Technol, Suzhou 215123, Peoples R China
[3] Southeast Univ, Sch Mech Engn, Nanjing 211189, Peoples R China
基金
中国国家自然科学基金;
关键词
Reliability; Kriging model; Sensitivity; Working conditions; Multiple coupling parameters; FATIGUE DAMAGE; OPTIMIZATION; DESIGN; CRASHWORTHINESS; UNCERTAINTY; COMPOSITES; FREQUENCY;
D O I
10.1016/j.heliyon.2022.e10046
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页数:13
相关论文
共 63 条
[1]   A global sensitivity analysis framework for hybrid simulation [J].
Abbiati, G. ;
Marelli, S. ;
Tsokanas, N. ;
Sudret, B. ;
Stojadinovic, B. .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2021, 146
[2]   A wave-based numerical scheme for damage detection and identification in two-dimensional composite structures [J].
Apalowo, R. K. ;
Chronopoulos, D. .
COMPOSITE STRUCTURES, 2019, 214 :164-182
[3]   Sobol' main effect index: an Innovative Algorithm (IA) using Dynamic Adaptive Variances [J].
Azzini, Ivano ;
Rosati, Rossana .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2021, 213
[4]   Empirical mode decomposition and its variants: a review with applications in structural health monitoring [J].
Barbosh, Mohamed ;
Singh, Premjeet ;
Sadhu, Ayan .
SMART MATERIALS AND STRUCTURES, 2020, 29 (09)
[5]   Symmetry properties of natural frequency and mode shape sensitivities in symmetric structures [J].
Bartilson, Daniel T. ;
Jang, Jinwoo ;
Smyth, Andrew W. .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2020, 143
[6]   A Critical Appraisal of Design of Experiments for Uncertainty Quantification [J].
Bhattacharyya, Biswarup .
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING, 2018, 25 (03) :727-751
[7]   Sobol' indices as dimension reduction technique in evolutionary-based reliability assessment [J].
Carneiro, Goncalo das Neves ;
Antonio, Carlos Conceicao .
ENGINEERING COMPUTATIONS, 2020, 37 (01) :368-398
[8]   Global sensitivity analysis of Alkali-Surfactant-Polymer enhanced oil recovery processes [J].
Carrero, Enrique ;
Queipo, Nestor V. ;
Pintos, Salvador ;
Zerpa, Luis E. .
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING, 2007, 58 (1-2) :30-42
[9]   Thermal effects of substrate on Marangoni flow in droplet evaporation: Response surface and sensitivity analysis [J].
Chen, Xue ;
Wang, Xun ;
Chen, Paul G. ;
Liu, Qiusheng .
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER, 2017, 113 :354-365
[10]   Further results on orthogonal arrays for the estimation of global sensitivity indices based on alias matrix [J].
Chen, Xue-ping ;
Lin, Jin-Guan ;
Wang, Xiao-di ;
Huang, Xing-fang .
STATISTICAL METHODS AND APPLICATIONS, 2015, 24 (03) :411-426