Robust topology optimization of structures under uncertain propagation of imprecise stochastic-based uncertain field

This study introduces a novel computational framework for Robust Topology Optimization (RTO) considering imprecise random field parameters. Unlike the worst-case approach, present method provides upper and lower bounds mean standard deviation of compliance as well optimized topological layouts structure various scenarios. In proposed variables are determined utilizing parameterized p -boxes with different confidence intervals. The Karhunen–Loève (K–L) expansion is extended to provide spectral description field. linear superposition in conjunction combination orthogonal functions employed obtain explicit mathematical expressions first second order statistical moments structural compliance. Then, an interval sensitivity analysis carried out, applying Orthogonal Similarity Transformation (OST) boundaries each intermediate variable searched efficiently at every iteration using Combinatorial Approach (CA). Finally, validity, accuracy, applicability work rigorously checked by comparing outputs approach those obtained particle swarm optimization (PSO) Quasi-Monte-Carlo Simulation (QMCS) methods. Three numerical examples loads presented show effectiveness feasibility study. • paper submitted Imprecise p-boxes An results both up three orders magnitude increase speed.