The consideration of imprecise probability in engineering analysis to account for missing,
vague or incomplete data in the description of model uncertainties is a fast-growing field of …

Abstract Design optimization of structural and multidisciplinary systems under uncertainty
has been an active area of research due to its evident advantages over deterministic design …

Traditional structural uncertainty analysis is mainly based on probability models and
requires the establishment of accurate parametric probability distribution functions using …

Reliability assessment considering multi-failure dependency brings in highly complex
computing tasks, which is impracticable for some complex structures like turbine cooling …

Non-probabilistic convex model utilizes a convex set to quantify the uncertainty domain of
uncertain-but-bounded parameters, which is very effective for structural uncertainty analysis …

Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm
motivated by intelligent collective behavior of some animals such as flocks of birds or …

This paper presents a highly efficient and accurate approach to determine the bounds on the
first excursion probability of a linear structure that is subjected to an imprecise stochastic …

Uncertain static analysis of an engineering structure with diverse type of non-deterministic
system parameter is investigated in this study. Unlike the traditional hybrid uncertain static …

This paper proposes a new non-probabilistic robust topology optimization approach for
structures under interval uncertainty, as a complementarity of the probabilistic robust …

Based on the sub-interval perturbation analysis, a modified sub-interval perturbation finite
element method is proposed to determine the bounds of sound pressure in the 2D acoustic …