FUZZY PROBABILITY METHODS IN APPLICATIONS TO RELIABILITY ANALYSIS OF EUROCODE RULES FOR STEEL STRUCTURE DESIGN
Zdeněk Kala
Abstract
Open-access reader
Zdeněk Kala
Abstract
Open-access reader
The topic of the paper is the probabilistic analysis of the ultimate limit state of a steel strut loaded by permanent and long-time single variation action. The failure probability misalignment according to the EN 1990 concept of a structure designed according to the EUROCODE 3 is analyzed here. In the stochastic model, material and geometrical characteristics of a hot-rolled steel cross-section are considered according to the experimental research results. The initial curvature shape and size variability of the beam axis is modelled, in detail, by applying the random fields. The functional dependence between the failure probability and the correlation length of a random field is analyzed here. The probabilistic analysis is completed by the fuzzy analysis of the influence of uncertainties on the failure probability. The fuzzification process of coefficients of model uncertainties and the deffuzification process of the fuzzy number of the output failure probability are described. The failure probability fuzzy analysis was evaluated according to the general extension principle, the failure probability having been solved by the Monte Carlo method.
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The topic of the paper is the probabilistic analysis of the ultimate limit state of a steel strut loaded by permanent and long-time single variation action. The failure probability misalignment according to the EN 1990 concept of a structure designed according to the EUROCODE 3 is analyzed here. In the stochastic model, material and geometrical characteristics of a hot-rolled steel cross-section are considered according to the experimental research results. The initial curvature shape and size variability of the beam axis is modelled, in detail, by applying the random fields. The functional dependence between the failure probability and the correlation length of a random field is analyzed here. The probabilistic analysis is completed by the fuzzy analysis of the influence of uncertainties on the failure probability. The fuzzification process of coefficients of model uncertainties and the deffuzification process of the fuzzy number of the output failure probability are described. The failure probability fuzzy analysis was evaluated according to the general extension principle, the failure probability having been solved by the Monte Carlo method.
Key concepts: Fuzzy logic, Probabilistic logic, Monte Carlo method, Limit state design, Mathematics, Probability distribution, Random variable, Structural engineering