Using Artificial Intelligence for Optimizing Natural Frequency of Recycled Concrete for Mechanical Machine Foundation

Abstract

This paper investigates the mechanical properties of two different types of recycled concrete, which use wood and rubber, relative to those characteristics of pure concrete, in terms of maximum load and natural frequencies. This paper contributes to the state of the art in this area in a number of ways. Firstly, the paper provides furtherance to the progressively growing literature in the field of recycled concrete and mechanical properties of materials. Secondly, the paper investigates the mechanical properties of two different types of recycled concrete by means of investigating the natural frequency of the samples, which is a new contribution. Lastly, the results from predicting the natural frequencies of concrete using fuzzy logic have been effectively assessed and compared with the analytical results. Results from the study show that the pure concrete samples produced maximum natural frequency, then concrete samples with wood, and lastly, concrete samples with rubber. The tolerance between the lab test results and fuzzy logic is approximately 5%. These results could have significant implications for furthering recycled concrete research and for designing machine foundations. Evidence of the applicability of fuzzy logic as a predictive and analysis tool for the mechanical properties of recycled concrete are discussed.