@article { author = {Zolfaghari, M.R. and Beheshti Aval, S.B. and Khojastehfar, E.}, title = {Uncertainty Analysis Using Fuzzy Randomness Method Towards Development of Fragility Curves For Moment-Resisting Steel Structures}, journal = {Scientia Iranica}, volume = {22}, number = {1}, pages = {131-143}, year = {2015}, publisher = {Sharif University of Technology}, issn = {1026-3098}, eissn = {2345-3605}, doi = {}, abstract = {Seismic fragility analysis is one of the main steps of consequence based earthquake engineering process. Accurate uncertainties modeling involved in this methodology, affects the final results of seismic fragility analysis and hence assessment of decision variables which are the final products of performance-based seismic analysis. One aspect of such efforts is to incorporate the sources of uncertainties associated with various factors controlling seismic loads on the buildings as well as structural responses to such excitations. Probabilistic approach are usually used to model quantitative sources of such uncertainties, however, there are other factors with descriptive nature which probabilistic approach may not well incorporate them. In this paper a fuzzy randomness approach is used to model epistemic uncertainties as an alternative to the conventional probabilistic method. The approach is used to model those uncertainties which have not been addressed by the others, in particular the definition of the collapse limit state. To illustrate the efficiency of the proposed approach, fragility curves for a sample moment-resisting steel frame are developed.The results demonstrate the superiority of fuzzy solution in comparison with excising probabilistic methods to incorporate epistemic uncertainty in view of much less computational effort.}, keywords = {Seismic Fragility Curves,Fuzzy randomness method,First order second moment method,Uncertainty treatment,Monte Carlo method}, url = {https://scientiairanica.sharif.edu/article_1849.html}, eprint = {https://scientiairanica.sharif.edu/article_1849_592b8f196bf7cc68d052585699ece555.pdf} }