The paper is devoted to the estimation of small failure probabilities, i.e. on the reliability analysis, using the non-parametric model of the large-scale structure. Two major questions are addressed in this respect: (i) What are the effects of the model uncertainties on the prediction of very small failure probabilities, i.e. on the tails of the response distribution? This question will be answered by studying the differences in the failure probabilities predicted by the non-parametric approach and by the parametric approach, respectively. (ii) The non-parametric model of uncertainties features a very large number of random variables, thus leading to a high-dimensional reliability problem [3]. Due to the non-linear nature of the response, ...
Abstract Monte Carlo Simulation (MCS) offers a powerful means for evaluating the reliability of a sy...
International audienceIn structural dynamics, a predictive model is constructed by developing a math...
This work is dedicated to the exploration of commonly used and development of new advanced stochasti...
A reliability analysis method is proposed that starts with the identification of all variables invol...
The work reported in this thesis is in the area of computational modeling of reliability of engineer...
In the reliability analysis of a complex engineering structure a very large number of the system par...
A critical appraisal of reliability procedures for high dimensions is presented. Available approxima...
The problem of reliability analysis of randomly parametered, linear (or) nonlinear, structures Subje...
In this paper we adopt a geometric perspective to highlight the challenges associated with solving h...
Monte Carlo simulation (MCS) offers a powerful means for evaluating the reliability of a system, due...
In this paper it is attempted to highlight some problems of failure probability estimation in high d...
In the reliability analysis of safety critical complex engineering structures, a very large number o...
This work is concerned with a Benchmark study on reliability estimation of structural systems, whic...
Probabilistic techniques in engineering problems are needed because they provide a deeper understand...
publisherThis study describes an efficient directional importance sampling method for the simulation...
Abstract Monte Carlo Simulation (MCS) offers a powerful means for evaluating the reliability of a sy...
International audienceIn structural dynamics, a predictive model is constructed by developing a math...
This work is dedicated to the exploration of commonly used and development of new advanced stochasti...
A reliability analysis method is proposed that starts with the identification of all variables invol...
The work reported in this thesis is in the area of computational modeling of reliability of engineer...
In the reliability analysis of a complex engineering structure a very large number of the system par...
A critical appraisal of reliability procedures for high dimensions is presented. Available approxima...
The problem of reliability analysis of randomly parametered, linear (or) nonlinear, structures Subje...
In this paper we adopt a geometric perspective to highlight the challenges associated with solving h...
Monte Carlo simulation (MCS) offers a powerful means for evaluating the reliability of a system, due...
In this paper it is attempted to highlight some problems of failure probability estimation in high d...
In the reliability analysis of safety critical complex engineering structures, a very large number o...
This work is concerned with a Benchmark study on reliability estimation of structural systems, whic...
Probabilistic techniques in engineering problems are needed because they provide a deeper understand...
publisherThis study describes an efficient directional importance sampling method for the simulation...
Abstract Monte Carlo Simulation (MCS) offers a powerful means for evaluating the reliability of a sy...
International audienceIn structural dynamics, a predictive model is constructed by developing a math...
This work is dedicated to the exploration of commonly used and development of new advanced stochasti...