Structural Reliability analysis (SRA) is one of the prominent fields in civil and mechanical
engineering. However, an accurate SRA in most cases deals with complex and costly …

This article introduces a simple and effective adaptive surrogate model to structural reliability
analysis using deep neural network (DNN). In this paradigm, initial design of experiments …

The reliability analysis of complex structures usually involves implicit performance function
and expensive-to-evaluate computational models, which pose a great challenge for the …

Vectorial modeling concept is proposed in this paper by introducing the matrix theory into
the point modeling concept (surrogate modeling strategy), and an adaptive vectorial …

The paper investigates the potential application of machine learning methods to estimate the
load-carrying capacity of semi-rigid connected steel structures. The database is developed …

This research has used 16 concrete mix designs containing 0.1, 0.3, and 0.5% steel fiber
(SF), and 20, 30, 40, 50, and 60% copper slag (CS) to examine their fresh and hardened …

To achieve multi-response prediction and reliability evaluation of complex structural system,
a high efficient and precision strategy, namely synchronous surrogate modeling-based …

For accurately and efficiently estimating the time-dependent failure probability (TDFP) of the
structure, a novel adaptive multiple-Kriging-surrogate method is proposed. In the proposed …

This study has examined how coarse CS (copper slag) aggregates (20–60%) and HESFs
(hooked-end steel fibers)(0.1–0.5%) affect the performance, microstructure, and …

In the field of reliability engineering, assessing the probability of failure of an event is usually
a computationally demanding task. One way of tackling this issue is by metamodelling, in …