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

Population growth, economic development, and rapid urbanization in many areas have led
to increased exposure and vulnerability of structural and infrastructure systems to hazards …

This study investigates the use of Self-Magnetic Flux Leakage (SMFL) monitoring to assess
the load-bearing capacity of RC bridges under vehicular loading. Cyclic tensile experiments …

Engineering structures and infrastructure continue to be used despite approaching or having
reached their design lifetime. While contact-based measurement techniques are challenging …

Origami has attracted tremendous attention in recent years owing to its capability of inspiring
and enabling the design and development of reconfigurable structures and mechanisms for …

Determining the risk priorities for the building stock in highly seismic-prone regions and
making the final decisions about the buildings is one of the essential precautionary …

Abstract Precast Ultra-High-Performance Concrete (UHPC) segmental bridges (PUSBs) are
among the most promising structural systems owing to their potential for application in …

Structural health monitoring (SHM) systems are used to analyze the health of infrastructures
such as bridges, using data from various types of sensors. While SHM systems consist of …

The chaos game optimization (CGO) algorithm is a recently developed metaheuristic
inspired by chaos theory and fractal configurations. In CGO, possible optimal solutions are …

This study tries to establish a powerful machine learning (ML) model for predicting the
compressive strength of cement-based mortars by using dynamic elasticity data. The ML …