Application of artificial neural network for interpreting ultrasonic readings of concrete

Concrete is an essential material for civil engineers. However, its properties can vary considerably, depending on the nature and proportions of the constituents, the construction methods and the loading and environmental conditions. Therefore, the development of methods to determine the state condition and ascertain the quality of concrete elements is critical. This paper describes a study carried out to evaluate the feasibility of developing Artificial Neural Networks (ANN) that use data about concrete properties and ultrasonic readings to estimate compressive strength. The results obtained indicate that the estimation power of a neural network can surpass that of traditional statistical techniques and that this might become a very interesting tool to model certain problems in civil engineering.