Please wait a minute...
Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)  2016, Vol. 17 Issue (12): 961-973    DOI: 10.1631/jzus.A1500255
Articles     
A structural reliability-based sensitivity analysis method using particles swarm optimization: relative convergence rate
Cheng-ming Lan , Hui Li, Jun-Yi Peng , Dong-Bai Sun
for Materials Service Safety, & Technology , 100083,; of Structural Monitoring and Control, , , 150090,; CITIC Construction Co., Ltd., 100027,
Download:     PDF (0 KB)     
Export: BibTeX | EndNote (RIS)      

Abstract  This paper proposes a novel reliability-based sensitivity analysis (SA) method, namely relative convergence rate of random variables using particles swarm optimization (). The convergence rate of a random variable during the optimum evolution process reflects the sensitivity of the objective function with respect to the random variables. An optimized group strategy is proposed to consider the fluctuation of the convergence rate of a variable during the optimum process. The coefficient of variation (COV) for candidate particles and the relative convergence rate of a random variable can be calculated using the particles in the optimized group. The smaller the COV for candidate particles, i.e., the larger the relative convergence rate, the more sensitive the objective function with respect to the variable. Three examples are available for the application of this method, and the results indicate that the sensitivity of the reliability index with respect to the variable obtained using the technique and gradient of limit-state function is the same in the quantitative sense.

Key wordsSensitivity analysis (SA)      Optimization      Structural reliability      Random variable     
Received: 10 September 2015      Published: 06 December 2016
CLC:  TU311.2  
Cite this article:

Cheng-ming Lan , Hui Li, Jun-Yi Peng , Dong-Bai Sun . A structural reliability-based sensitivity analysis method using particles swarm optimization: relative convergence rate. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2016, 17(12): 961-973.

URL:

http://www.zjujournals.com/xueshu/zjus-a/10.1631/jzus.A1500255     OR     http://www.zjujournals.com/xueshu/zjus-a/Y2016/V17/I12/961

[1] Peng Guo, Jun-hong Zhang. Numerical model and multi-objective optimization analysis of vehicle vibration[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2017, 18(5): 393-412.
[2] Tian-tian Zhang, Wei Huang, Zhen-guo Wang, Li Yan. A study of airfoil parameterization, modeling, and optimization based on the computational fluid dynamics method[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2016, 17(8): 632-645.
[3] Hossein Rezaei, Ramli Nazir, Ehsan Momeni. Bearing capacity of thin-walled shallow foundations: an experimental and artificial intelligence-based study[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2016, 17(4): 273-285.
[4] Bao-tong Li, Su-na Yan, Jun Hong. A growth-based topology optimizer for stiffness design of continuum structures under harmonic force excitation[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2016, 17(12): 933-946.
[5] Jin Cheng, Ming-yang Tang, Zhen-yu Liu, Jian-rong Tan. Direct reliability-based design optimization of uncertain structures with interval parameters[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2016, 17(11): 841-854.
[6] Liang Ye, Yin-fu Jin, Shui-long Shen, Ping-ping Sun, Cheng Zhou. An efficient parameter identification procedure for soft sensitive clays[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2016, 17(1): 76-88.
[7] Antoine Dumas, Jean-Yves Dantan, Nicolas Gayton, Thomas Bles, Robin Loebl. An iterative statistical tolerance analysis procedure to deal with linearized behavior models[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2015, 16(5): 353-360.
[8] Qing-long Meng, Xiu-ying Yan, Qing-chang Ren. Global optimal control of variable air volume air-conditioning system with iterative learning: an experimental case study[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2015, 16(4): 302-315.
[9] Lei Fu, Zhen-ping Feng, Guo-jun Li, Qing-hua Deng, Yan Shi, Tie-yu Gao. Experimental validation of an integrated optimization design of a radial turbine for micro gas turbines[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2015, 16(3): 241-249.
[10] Wei Wei, Ang Liu, Stephen C. Y. Lu, Thorsten Wuest. A multi-principle module identification method for product platform design[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2015, 16(1): 1-10.
[11] Abbas Al-Refaie. Applying process analytical technology framework to optimize multiple responses in wastewater treatment process[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2014, 15(5): 374-384.
[12] Chang-yu Cui, Bao-shi Jiang, You-bao Wang. Node shift method for stiffness-based optimization of single-layer reticulated shells[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2014, 15(2): 97-107.
[13] Yi-cong Gao, Yi-xiong Feng, Jian-rong Tan. Multi-principle preventive maintenance: a design-oriented scheduling study for mechanical systems[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2014, 15(11): 862-872.
[14] Jin Cheng, Gui-fang Duan, Zhen-yu Liu, Xiao-gang Li, Yi-xiong Feng, Xiao-hai Chen. Interval multiobjective optimization of structures based on radial basis function, interval analysis, and NSGA-II[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2014, 15(10): 774-788.
[15] José D. Martínez-Morales, Elvia R. Palacios-Hernández, Gerardo A. Velázquez-Carrillo. Modeling and multi-objective optimization of a gasoline engine using neural networks and evolutionary algorithms[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2013, 14(9): 657-670.