Approach for the structural reliability analysis by the modified sensitivity model based on response surface function - Kriging model
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 func...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-08-01
|
| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844022013342 |
| _version_ | 1811188042469212160 |
|---|---|
| author | Lin Zhu Jianchun Qiu Min Chen Minping Jia |
| author_facet | Lin Zhu Jianchun Qiu Min Chen Minping Jia |
| author_sort | Lin Zhu |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-11T14:13:54Z |
| format | Article |
| id | doaj.art-bd2e1308faa24822b80fd6473a94f022 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-11T14:13:54Z |
| publishDate | 2022-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-bd2e1308faa24822b80fd6473a94f0222022-12-22T04:19:37ZengElsevierHeliyon2405-84402022-08-0188e10046Approach for the structural reliability analysis by the modified sensitivity model based on response surface function - Kriging modelLin Zhu0Jianchun Qiu1Min Chen2Minping Jia3School of Mechanical Engineering, Yangzhou University, Yangzhou 225001, China; Corresponding author.School of Mechanical Engineering, Yangzhou University, Yangzhou 225001, ChinaSchool of Advanced Technology, Xi'an Jiaotong-Liverpool University, Suzhou 215123, ChinaSchool of Mechanical Engineering, Southeast University, Nanjing 211189, ChinaThe 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.http://www.sciencedirect.com/science/article/pii/S2405844022013342ReliabilityKriging modelSensitivityWorking conditionsMultiple coupling parameters |
| spellingShingle | Lin Zhu Jianchun Qiu Min Chen Minping Jia Approach for the structural reliability analysis by the modified sensitivity model based on response surface function - Kriging model Heliyon Reliability Kriging model Sensitivity Working conditions Multiple coupling parameters |
| title | Approach for the structural reliability analysis by the modified sensitivity model based on response surface function - Kriging model |
| title_full | Approach for the structural reliability analysis by the modified sensitivity model based on response surface function - Kriging model |
| title_fullStr | Approach for the structural reliability analysis by the modified sensitivity model based on response surface function - Kriging model |
| title_full_unstemmed | Approach for the structural reliability analysis by the modified sensitivity model based on response surface function - Kriging model |
| title_short | Approach for the structural reliability analysis by the modified sensitivity model based on response surface function - Kriging model |
| title_sort | approach for the structural reliability analysis by the modified sensitivity model based on response surface function kriging model |
| topic | Reliability Kriging model Sensitivity Working conditions Multiple coupling parameters |
| url | http://www.sciencedirect.com/science/article/pii/S2405844022013342 |
| work_keys_str_mv | AT linzhu approachforthestructuralreliabilityanalysisbythemodifiedsensitivitymodelbasedonresponsesurfacefunctionkrigingmodel AT jianchunqiu approachforthestructuralreliabilityanalysisbythemodifiedsensitivitymodelbasedonresponsesurfacefunctionkrigingmodel AT minchen approachforthestructuralreliabilityanalysisbythemodifiedsensitivitymodelbasedonresponsesurfacefunctionkrigingmodel AT minpingjia approachforthestructuralreliabilityanalysisbythemodifiedsensitivitymodelbasedonresponsesurfacefunctionkrigingmodel |