As engineering applications become increasingly complex, they are often characterized by implicit response functions that are both expensive to evaluate and nonlinear in their behavior. Reliability assessment given this type of response is difficult with available methods. Current reliability methods focus on the discovery of a single most probable point of failure, and then build a low-order a...

• Ordering: pf ≤ p X 6 →Z f ≤ p R,X 6 →Z f and p S f ≤ p RS f ≤ p R,X 6 →Z f . • Strong independence: Complete information about the uncertain limit state function is needed. • Epistemic irrelevance: Sufficient to know q which condenses the uncertain limit state function. q could be a starting point for uncertainty modelling. • Random set independence: Possibility to combine upper probabilities...

In this study, an efficient method based on Monte Carlo simulation, utilized with Adaptive Neuro-Fuzzy Inference System (ANFIS) is introduced for reliability analysis of structures. Monte Carlo Simulation is capable of solving a broad range of reliability problems. However, the amount of computational efforts that may involve is a draw back of such methods. ANFIS is capable of approximating str...

In this research, a two-phase algorithm based on the artificial neural network (ANN) and a harmony search (HS) algorithm has been developed with the aim of assessing the reliability of structures with implicit limit state functions. The proposed method involves the generation of datasets to be used specifically for training by Finite Element analysis, to establish an ANN model using a proven AN...