Structural Assessment under Uncertain Parameters via the Interval Optimization Method Using the Slime Mold Algorithm

Damage detection of civil and mechanical structures based on measured modal parameters using model updating schemes has received increasing attention in recent years. In this study, for uncertainty-oriented damage identification, a non-probabilistic structural identification (NSDI) technique an optimization algorithm interval mathematics is proposed. order to take into account the uncertainty quantification, elastic modulus described as unknown-but-bounded values proposed new scheme determines upper lower bounds index. method, can provide supports health diagnosis under uncertain conditions by considering uncertainties variables algorithm. The subsequently used predict interval-bound Elemental Stiffness Parameter (ESP). slime mold (SMA) main updating. addition, enhanced variant SMA (ESMA) developed, which removes unchanged after defined number iterations. method implemented three well-known numerical examples domain monitoring single multi-damage scenarios with different degrees uncertainty. results show that NSDI methodology reduced computation time, at least 30%, comparison probabilistic methods. Furthermore, ESMA capability detect damaged elements higher certainty cost original SMA.