Abstract Machine learning (ML) has become the most successful branch of artificial
intelligence (AI). It provides a unique opportunity to make structural engineering more …

Steel shear panel dampers are widely used as passive energy-dissipation devices in
earthquake-resistant structures. The out-of-plane buckling stress of the core plate included …

The design process of thin-walled structural members is highly complex due to the possible
occurrence of multiple instabilities. This research therefore aimed to develop machine …

Pultruded fiber-reinforced composites (FRP) are widely used in structural engineering due to
their excellent properties along the fiber direction. Its global buckling performance has …

High strength steel is regarded as a promising construction material due to its superior
mechanical properties. However, the codified failure load predictions for high strength steel …

This study introduces a machine learning (ML)-based model for predicting the ultimate
strength of circular concrete-filled fiber-reinforced polymer (FRP)–steel composite tube …

Large web openings introduce complex structural behaviors and additional failure modes of
steel cellular beams, which must be considered in the design using laborious calculations …

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 study aims to improve the loading capacities of cold-formed steel (CFS) built-up section
columns by optimizing cross-sectional geometric dimensions with constant material …

High strength steel has been attracting attention in the building industry due to its superior
mechanical properties. The accurate design of high strength steel structures is crucial to …