Artificial Intelligence to Model the Performance of Concrete Mixtures and Elements: A Review

Concrete is the most widely used man-made material in the construction of structures, pavements, bridges, dams, and infrastructures. Depending on the type of components and mixture proportions, different behavior can be expected from different types of concretes, which necessitates the study of concrete behavior in designing procedures. The properties of the concrete mixtures and elements can be estimated through expensive and time-taking laboratory-based experiments. Alternatively, these properties can be estimated through predictive models developed using statistical or artificial intelligence (AI) techniques. AI techniques, because of their capabilities in knowledge processing and pattern recognition, are among the leading methods to find solutions for engineering problems. In this paper, the available studies on the applications of AI techniques to model the behavior of concrete elements and estimate the properties of concrete mixtures are reviewed. In addition, the capabilities of various AI techniques in handling different types of data are discussed. This paper also provides recommendations on the selection of the appropriate input variables in developing the predictive models. It is hoped that this paper will provide the interested practicing engineers with the information needed to fully exploit the resources available on the use of AI techniques in the concrete industry. Moreover, this paper will be helpful to the researchers to explore future avenues of research on the applications of AI techniques in the field of concrete mixtures and elements.

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