For many systems in science and engineering, the governing differential equation is either
not known or known in an approximate sense. Analyses and design of such systems are …

Due to the absence of adequate control at different stages of complex manufacturing
process, material and geometric properties of composite structures are often uncertain. For a …

Support vector regression (SVR) based metamodel is a powerful mean to alleviate
computational challenge of Monte Carlo simulation (MCS) based reliability analysis of …

A three-stage adaptive support vector regression (SVR) based metamodel is built by
sampling training data sequentially close to a limit state function (LSF). The approach …

Abstract Iron Oxide Nanoparticle, maghemite (γ-Fe2O3) has received great interest and
extensively used in biomedical field. Optimization studies were carried out in the production …

Sparse polynomial chaos expansion (PCE) combined with the bootstrap resampling method
is a viable alternative to obtain an active learning algorithm for reliability analysis. The …

The application of adaptive support vector regression (SVR) models in tunnel reliability
analysis is limited. A two-stage adaptive SVR-based metamodel is proposed for tunnel …

We propose a novel approach for solving high-dimensional reliability analysis problems.
The basic premise is to train the surrogate model on a low-dimensional manifold, discovered …

Robust design optimization (RDO) is a field of optimization in which certain measure of
robustness is sought against uncertainty. Unlike conventional optimization, the number of …

This paper presents a simulation free framework for solving reliability analysis problems.
The method proposed is rooted in a recently developed deep learning approach, referred to …