MS Title:
Coping with Imprecision in Structural Reliability Analysis

Description:
Reliability analysis quantifies the level of safety of structural systems. It is based on concepts of probability theory, and it is best suited for coping with aleatory uncertainty, that is, inherent randomness. However, in practical situations, uncertainty may be of the epistemic type, as it appears due to lack of knowledge, conflicting sources of information, vagueness, etc. In such a case, one is confronted with the challenge of coping with both aleatoric and epistemic uncertainty, leading to a problem of imprecise reliability analysis. This class of problem has proven to be extremely challenging, as it encompasses a collection of classical reliability analyses indexed by the model describing epistemic uncertainty. Therefore, the aim of this mini-symposium is addressing the very latest development on approaches for reliability under aleatoric and epistemic uncertainty. The scope of the mini-symposium is broad, as it covers: different models for representing uncertainty such as classical probabilities, intervals, fuzzy analysis, imprecise probabilities, evidence theory, etc.; novel formulations for coping with aleatoric and epistemic uncertainty; advanced simulation methods; development and application of surrogate models, etc. Both theoretical developments and applications involving systems of engineering interest are particularly welcomed in this session.

This activity is organized under auspices of the Committee on Probability and Statistics in Physical Sciences (C(PS)^2) of the Bernoulli Society for Mathematical Statistics and Probability

Session Chairs:
Matthias Faes, TU Dortmund University, Germany. E-mail: matthias.faes@tu-dortmund.de
Jingwen Song, Northwestern Polytechnical University, China, jingwensong@nwpu.edu.cn
Marcos Valdebenito, TU Dortmund University, Germany, marcos.valdebenito@tu-dortmund.de
Pengfei Wei, Northwestern Polytechnical University, China, pengfeiwei@nwpu.edu.cn
Xiukai Yuan, Xiamen University, China, xiukaiyuan@xmu.edu.cn