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 …

Computer-aided engineering (CAE) is now an essential instrument that aids in engineering
decision-making. Statistical model calibration and validation has recently drawn great …

The single-loop approach (SLA) for reliability-based design optimization (RBDO) is one of
the most efficient schemes for optimization problems with linear and weak nonlinear …

To achieve an optimal design of complicated structures with stochastic parameters, the
reliability-based design optimization (RBDO) usually needs to handle the nested double …

With the time-consuming computations incurred by nested double-loop strategy and multiple
performance functions, the enhancement of computational efficiency for the non-probabilistic …

Statistical model calibration is a framework for inference on unknown model parameters and
modeling discrepancy between simulation and experiment through an inverse method in the …

Even though many efforts have been devoted to effective strategies to build accurate
surrogate models, surrogate model uncertainty is inevitable due to a limited number of …

Epistemic uncertainties are critical for reliable design of corroded pipes made of high-
strength grade steel. In this work, corrosion defects geometries and operating pressure are …

The statistical model is commonly used in the reliability-based design optimization (RBDO).
However, it is difficult to obtain sufficient data to construct a reasonable statistical model in …

In practical engineering problems, it is frequently challenging to collect sufficient data to
construct high-precision probabilistic models. In this case, probabilistic models typically …