A dynamic reliability analysis method based on support vector machine and Monte Carlo simulation

2020 ◽  
Vol 20 (1) ◽  
pp. 149-155
Author(s):  
Xiuqiang Pan ◽  
Yangu Zhang ◽  
Yi Wan
Keyword(s):  
Support Vector Machine ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Reliability Analysis ◽  
Support Vector ◽  
Analysis Method ◽  
Dynamic Reliability

A New Reliability Analysis Method Combining Adaptive Kriging With Weight Index Monte Carlo Simulation

2018 ◽  
Vol 54 (3) ◽  
pp. 1-4 ◽  
Author(s):  
Jiangang Ma ◽  
Ziyan Ren ◽  
Guoxin Zhao ◽  
Yanli Zhang ◽  
Chang-Seop Koh
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Reliability Analysis ◽  
Analysis Method ◽  
Weight Index ◽  
Adaptive Kriging

Reliability Analysis of Foundation Pit Based on Response Surface of Support Vector Machine

2013 ◽  
Vol 671-674 ◽  
pp. 240-244
Author(s):  
Chang Ning Sun ◽  
Jing Cao ◽  
Hai Ming Liu ◽  
Hui Min Zhao
Keyword(s):  
Support Vector Machine ◽  
Reliability Analysis ◽  
Response Surface ◽  
Safety Factor ◽  
Lateral Displacement ◽  
Support Vector ◽  
Probability Density Distribution ◽  
Analysis Method ◽  
Foundation Pit ◽  
Random Samples

Traditional analysis methods of reliability in the foundation pit engineering have larger error and larger amount of calculation. Therefore, the response surface method has attracted much attention because it can effectively use the finite element analysis method (FEAM) and reduce the number of the numerical simulation. This paper combines uniform design (UD) with support vector machine (SVM). On this base, a reliability analysis method of the foundation pit is put forward based on the response surface of support vector machine (RSSVM). The UD structures random samples and the FEAM is used to obtain corresponding response parameters including the lateral displacement of wall, settlement of ground, safety factor of overall stability and safety factor of against overturning. Then, SVM trains the above random samples and corresponding response parameters to get response surface (RS) respectively. The probability density distribution of each response parameter is obtained by combining the Monte Carlo method with RSSVM. The instance analysis shows that the method has high computing efficiency and less amount of calculation, and the result is reasonable. It provides an effective way for the reliability analysis of the foundation pit engineering.

scholarly journals An Efficient Monte-Carlo Simulation for the Dynamic Reliability Analysis of Jacket Platforms Subjected to Random Wave Loads

2021 ◽  
Vol 9 (4) ◽  
pp. 380
Author(s):  
Wei Lin ◽  
Cheng Su
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Reliability Analysis ◽  
Degrees Of Freedom ◽  
Structural Reliability ◽  
Time History ◽  
Random Wave ◽  
Wave Loads ◽  
Dynamic Reliability ◽  
Small Failure Probability

The growing demand for the application of jacket platforms in deep water requires more attention on the assessment of structural reliability. This paper is devoted to the dynamic reliability analysis of jacket platforms subjected to random wave loads with Monte-Carlo simulation (MCS), in which a sample size of the order of magnitude of 104 to 105 for repeated time–history analyses is required for small failure probability problems, and a duration time up to three hours needs to be considered in the time–history analyses for a specific sea condition. To tackle the difficulty involved in MCS, the explicit time-domain method (ETDM) is used for the required time–history analyses of jacket platforms, in which truncated explicit expressions of critical responses with regards to the contributing loading terms are first established and then used for numerous repeated sample analyses. The use of ETDM greatly enhances the computational efficiency of MCS, making it feasible for the dynamic reliability analysis of jacket platforms under random wave loads. A jacket platform with 11,688 degrees of freedom was analyzed for the evaluation of dynamic reliability under a given sea condition, indicating the accuracy and efficiency of the present approach and its feasibility to practical structures.

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