Neural Networks Applicability for Design of Reinforced Concrete Sections for Bending

Abstract

Solving engineering design tasks requires the use of analytical formulas and dependencies. The direct inclusion of mathematical expressions in the artificial neural network (ANN) is not possible. This research studies the possibility of applying the neural networks method for designing of single or double-side reinforced concrete sections. A Visual Basic for Applications (VBA) macro was developed in the MS Excel environment to solve the task of determining the required area of the reinforcement by given geometric dimensions and bending moment and applying classical analytical formulas for reinforced concrete sections design. The training of the pre-configured neural network is performed by approximately 34000 sets of matching input parameters. The presented results from the trained ANN are compared and analysed against the exact analytical solutions. The study presents an approach to the application of structural design calculations. The results suggest that the approach is applicable to more complicated structural design problems.