New methods for system reliability analysis of soil slopes

2011 ◽  
Vol 48 (7) ◽  
pp. 1138-1148 ◽  
Author(s):  
J. Zhang ◽  
L.M. Zhang ◽  
Wilson H. Tang
Keyword(s):  
Reliability Analysis ◽  
Failure Probability ◽  
System Reliability ◽  
Slope Failure ◽  
Slip Surface ◽  
System Failure ◽  
Critical Slip Surface ◽  
New Methods ◽  
Slip Surfaces ◽  
System Reliability Analysis

A slope may have many possible slip surfaces. As sliding along any slip surface can cause slope failure, the system failure probability of a slope is different from the probability of failure along an individual slip surface. In this paper, we first suggest an efficient method for evaluating the system failure probability of a slope that considers a large number of possible slip surfaces. To obtain more insights into the system failure probability of a slope, we also propose a method to identify a few representative slip surfaces most important for system reliability analysis among a large number of potential slip surfaces and to calculate the system failure probability based on these representative slip surfaces. An equation for estimating the bounds of system failure probability based on the failure probability of the most critical slip surface is also suggested. The system failure probability is governed by only a few representative slip surfaces. For a homogenous slope, the failure probability of the most critical slip surface is a good approximation of the system failure probability. For a slope in layered soils, the system failure probability can be significantly larger than the failure probability of the most critical slip surface.

scholarly journals An Overview of Various Importance Measures of Reliability System

2017 ◽  
Vol 2 (3) ◽  
pp. 150-171 ◽  
Author(s):  
Kalpesh P. Amrutkar ◽  
Kirtee K. Kamalja
Keyword(s):  
Reliability Analysis ◽  
System Reliability ◽  
System Failure ◽  
Numerical Rank ◽  
Reliability Improvement ◽  
System Reliability Analysis ◽  
Component Importance ◽  
Critical Components ◽  
The Impact ◽  
Reliability Systems

One of the purposes of system reliability analysis is to identify the weaknesses or the critical components in a system and to quantify the impact of component’s failures. Various importance measures are being introduced by many researchers since 1969. These component importance measures provide a numerical rank to determine which components are more important to system reliability improvement or more critical to system failure. In this paper, we overview various components importance measures and briefly discuss them with examples. We also discuss some other extended importance measures and review the developments in study of various importance measures with respect to some of the popular reliability systems.

scholarly journals Resilience Assessment Based on Time-Dependent System Reliability Analysis

2016 ◽  
Vol 138 (11) ◽  
Author(s):  
Zhen Hu ◽  
Sankaran Mahadevan
Keyword(s):  
Reliability Analysis ◽  
System Reliability ◽  
Assessment Method ◽  
Time Dependent ◽  
Design Stage ◽  
System Failure ◽  
System Reliability Analysis ◽  
System Resilience ◽  
Resilience Assessment ◽  
Time Dependent System

Significant efforts have been recently devoted to the qualitative and quantitative evaluation of resilience in engineering systems. Current resilience evaluation methods, however, have mainly focused on business supply chains and civil infrastructure, and need to be extended for application in engineering design. A new resilience metric is proposed in this paper for the design of mechanical systems to bridge this gap, by investigating the effects of recovery activity and system failure paths on system resilience. The defined resilience metric is connected to design through time-dependent system reliability analysis. This connection enables us to design a system for a specific resilience target in the design stage. Since computationally expensive computer simulations are usually used in design, a surrogate modeling method is developed to efficiently perform time-dependent system reliability analysis. Based on the time-dependent system reliability analysis, dominant system failure paths are enumerated and then the system resilience is estimated. The connection between the proposed resilience assessment method and design is explored through sensitivity analysis and component importance measure (CIM). Two numerical examples are used to illustrate the effectiveness of the proposed resilience assessment method.

Estimation of System Reliability by Monte Carlo Simulation

2009 ◽  
Author(s):  
A. Naess ◽  
B. J. Leira ◽  
O. Batsevych
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Reliability Analysis ◽  
Failure Probability ◽  
Failure Criterion ◽  
System Reliability ◽  
Substantial Reduction ◽  
Structural Systems ◽  
System Failure ◽  
Simulation Monte Carlo

A new method for estimating the reliability of structural systems is proposed. The method is based on the use of Monte Carlo simulation. Monte Carlo based methods for system reliability analysis has several attractive features, the most important being that the system failure criterion is usually relatively easy to check almost irrespective of the complexity of the system. The disadvantage of such methods is the amount of computational efforts that may be involved. However, by reformulating the reliability problem to depend on a parameter and exploiting the regularity of the failure probability as a function of this parameter, it is shown that a substantial reduction of the computational efforts involved can be obtained.

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