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

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 …

Shear walls are typically the major lateral load-carrying components in high-rise buildings
owing to their high lateral strength and stiffness. This study introduces a technique for …

Because the proportion between the compressive strength of high‐performance concrete
(HPC) and its composition is highly nonlinear, more advanced regression methods are …

Accurate prediction of the shear capacity of reinforced concrete shear walls (RCSW) is
essential for the wind and seismic design of buildings. However, due to the diverse structural …

In steel plate girders (SPGs), a patch loading usually causes a local failure in the vicinity of
the loading area of the girder web. However, estimating the patch loading resistance (PLR) …

Tapered steel plate girders are commonly used in large span industrial structures and
composite bridges. The tapered thin steel web plates under stress gradients in such …

The aim of this study is to develop a hybrid Artificial Neural Network-Particle Swarm
Optimization (ANN-PSO) model for improving shear strength prediction of reinforced …

Assessing the collapse region in the progressive collapse of buildings is one of the
important issues in urban planning for disaster recovery. A rapid visual simulation method …

Connections are crucial zones in steel buildings since they provide interaction between
principal structural components (ie, beams, columns) and provide stability to the entire …