Practical reliability analysis and design by Monte Carlo Simulation in spreadsheet

2018 ◽  
pp. 331-366
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Reliability Analysis ◽  
Analysis And Design

Reliability Analysis and Design Considering Disjointed Active Failure Regions

2015 ◽  
Author(s):  
Pingfeng Wang ◽  
Xiaolong Cui ◽  
Zequn Wang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Reliability Analysis ◽  
Failure Modes ◽  
Kriging Model ◽  
Engineering Systems ◽  
Random Input ◽  
Performance Function ◽  
Analysis And Design ◽  
Practical Engineering

Failure of practical engineering systems could be induced by several correlated failure modes, and consequently reliability analysis are conducted with multiple disjointed failure regions in the system random input space. Problems with disjointed failure regions create a great challenge for existing reliability analysis approaches due to the discontinuity of the system performance function between these regions. This paper presents a new enhanced Monte Carlo simulation (EMCS) approach for reliability analysis and design considering disjointed failure regions. The ordinary Kriging method is adopted to construct surrogate model for the performance function so that Monte Carlo simulation (MCS) can be used to estimate the reliability. A maximum failure potential based sampling scheme is developed to iteratively search failure samples and update the Kriging model. Two case studies are used to demonstrate the efficacy of the proposed methodology.

Reliability Analysis and Design Considering Disjointed Active Failure Regions

2015 ◽  
Author(s):  
Pingfeng Wang ◽  
Xiaolong Cui
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Reliability Analysis ◽  
Failure Modes ◽  
Kriging Model ◽  
Engineering Systems ◽  
Random Input ◽  
Performance Function ◽  
Analysis And Design ◽  
Practical Engineering

Failure of practical engineering systems could be induced by several correlated failure modes, and consequently reliability analysis are conducted with multiple disjointed failure regions in the system random input space. Problems with disjointed failure regions create a great challenge for existing reliability analysis approaches due to the discontinuity of the system performance function between these regions. This paper presents a new enhanced Monte Carlo simulation (EMCS) approach for reliability analysis and design considering disjointed failure regions. The ordinary Kriging method is adopted to construct surrogate model for the performance function so that Monte Carlo simulation (MCS) can be used to estimate the reliability. A maximum failure potential based sampling scheme is developed to iteratively search failure samples and update the Kriging model. Two case studies are used to demonstrate the efficacy of the proposed methodology.

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
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