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

The mixture proportioning of conventional concrete is commonly established using
regression analysis of experimental data. However, such traditional empirical procedures …

Chloride ingression is the main reason for causing durability degradation of reinforced
concrete (RC) structures. In this study, the distinguishing features of artificial neural network …

The advantages of using Metakaolin (MK) as a supplementary cementitious material have
led this highly active pozzolan to be widely used in the concrete industry. Awareness of the …

Foamed concrete is special not only in terms of its unique properties, but also in terms of its
challenging compositional mixture design, which necessitates multiple experimental trials …

In this research, a machine learning model namely extreme learning machine (ELM) is
proposed to predict the compressive strength of foamed concrete. The potential of the ELM …

Foamed concrete (FC) shows advantageous applications in civil engineering, such as
reduction in dead loads, contribution to energy conservation, or decrease the construction …

Among the many sustainability challenges in the construction industry, those related to the
application of concrete and its components are the most critical. Particularly, the production …

Engineered cementitious composite (ECC) has been intensively studied due to its excellent
tensile performance. However, classical micro-mechanical design theory of ECC is …

The hot deformation behavior in an AZ91 magnesium alloy was studied using Arrhenius
model and Back-Propagation Artificial Neural Network (BP-ANN) approaches. The hot …