With the informatization of the building and infrastructure industry, conventional analysis
methods are gradually proving inadequate in meeting the demands of the new era, such as …

Hysteresis is a natural phenomenon that widely exists in structural and mechanical systems.
The characteristics of structural hysteretic behaviors are complicated. Therefore, numerous …

This paper proposes a real-time prediction method for key monitoring physical parameters
(KMPPs) for early warning of fire-induced building collapse using machine learning. Since …

This paper presents a framework to predict the entire displacement time histories of all floors
of buildings using a novel double-head neural network composed of causal Convolution …

Artificial neural networks have been proven promisingly powerful in developing a data-
driven surrogate model for rapid seismic response modeling, while very few of them embody …

This paper presents a hybrid deep learning methodology for seismic structural monitoring,
damage detection, and localization of instrumented buildings. The proposed methodology …

Engineering structures often exhibit multiple potential vulnerable positions during strong
earthquakes, such as porcelain insulators and connection flanges of electrical equipment in …

The precast segmental self-centering concrete-filled steel tube (PSCFST) bridge is not only
the ideal choice for fast and environmentally friendly construction but also has good seismic …

To address the issue of costly computational expenditure related to high‐fidelity numerical
models, surrogate models have been widely used in various engineering tasks, including …

Regional seismic loss estimation (RSLE) is a crucial process in both immediate post-
earthquake emergency response and long-term reconstruction endeavors. Over the years …