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 …

The use of deep generative models (DGMs) such as variational autoencoders,
autoregressive models, flow-based models, energy-based models, generative adversarial …

Predicting the nonlinear time-history responses of civil engineering structures under seismic
loading remains an essential task in earthquake engineering. This paper explores the …

A performance-based early design must assess the life cycle performance of a sizable
design space at low computational cost and limited data. This paper evaluates the relative …

While uncertainty quantification (UQ) has served a prominent role in ensuring the safety of
dynamical engineering systems, the lack of an integrated approach to handle the aleatory …

This study investigates the seismic behavior of eccentrically braced frames (EBFs) taking
into account the influence of masonry infill walls using a nonmodel scenario-based machine …

The global attention to using timber products as sustainable construction material urges
careful assessment of their performance against different hazards, particularly fire. However …

This study employs soft computing techniques, including artificial neural network (ANN)
models and gene expression programming (GEP), to enhance the prediction of ultimate load …

This paper investigates the application of mechanics-informed artificial intelligence to civil
structural systems. Structural analysis is a traditional practice that involves engineers to …

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