Abstract. In the reliability analysis of a complex engineering structures a very large number of system parameters can be considered to be random variables. The difficulty in computing the failure probability increases rapidly with the number of variables. In this paper, a few methods are proposed whereby the number of variables can be reduced without compromising the accuracy of the reliability calculation. Based on the sensitivity of the failure surface, three new reduction methods, namely (a) gradient iteration method, (b) dominant gradient method, and (c) relative importance variable method, have been proposed. Numerical examples are provided to illustrate the proposed methods
ABSTRACT: In many practical applications of structural reliability analysis, one is interested in kn...
Response of the proposed algorithm to the random changes incorporated in (a) r0, (b) DCJ, (c) ρ0, an...
Abstract: The work attempts to choose the handy methods for analyzing structural reliability. Compar...
In the reliability analysis of a complex engineering structure a very large number of the system pa-...
AbstractCombining the advantages of the stratified sampling and the importance sampling, a stratifie...
In order to reduce sample points and make full use of information resources of sample points, an imp...
The problem of response surface modeling of limit surface lying within two hyper spheres of prescrib...
To select a method for analyzing structural reliability problems, including pptimization under relia...
Most reliability methods are applicable only for relatively simple structural systems with analytica...
Abstract: A new efficient and accurate method for reliability sensitivity analysis of mechanical com...
The application of dimensionality reduction method on the reliability and reliability sensitivity an...
This thesis' subject is sensitivity analysis in a structural reliability context. The general frame...
A robust and sophisticated structural reliability evaluation procedure is presented. Reliability of ...
This paper presents an efficient numerical method for approximating the parameter sensitivity of the...
An important segment of the reliability-based optimization problems is to get access to the sensitiv...
ABSTRACT: In many practical applications of structural reliability analysis, one is interested in kn...
Response of the proposed algorithm to the random changes incorporated in (a) r0, (b) DCJ, (c) ρ0, an...
Abstract: The work attempts to choose the handy methods for analyzing structural reliability. Compar...
In the reliability analysis of a complex engineering structure a very large number of the system pa-...
AbstractCombining the advantages of the stratified sampling and the importance sampling, a stratifie...
In order to reduce sample points and make full use of information resources of sample points, an imp...
The problem of response surface modeling of limit surface lying within two hyper spheres of prescrib...
To select a method for analyzing structural reliability problems, including pptimization under relia...
Most reliability methods are applicable only for relatively simple structural systems with analytica...
Abstract: A new efficient and accurate method for reliability sensitivity analysis of mechanical com...
The application of dimensionality reduction method on the reliability and reliability sensitivity an...
This thesis' subject is sensitivity analysis in a structural reliability context. The general frame...
A robust and sophisticated structural reliability evaluation procedure is presented. Reliability of ...
This paper presents an efficient numerical method for approximating the parameter sensitivity of the...
An important segment of the reliability-based optimization problems is to get access to the sensitiv...
ABSTRACT: In many practical applications of structural reliability analysis, one is interested in kn...
Response of the proposed algorithm to the random changes incorporated in (a) r0, (b) DCJ, (c) ρ0, an...
Abstract: The work attempts to choose the handy methods for analyzing structural reliability. Compar...