Abstract
ABSTRACT This study proposes artificial neural networks (ANNs) that can solve structural engineering problems in general and design ductile concrete beams in particular. ANNs demonstrating a learning and memory capability similar to that of the human brain were implemented in the design of doubly reinforced concrete beams. ANNs are developed to map inputs into outputs based on large structural design datasets for engineering applications rather than being based on structural mechanics or knowledge. This study aims to develop design of doubly reinforced concrete beams based on ANN. In this study, a reverse design was presented with design charts in which the sequences of calculating inputs and outputs are exchanged, which is challenging to perform in conventional designs. Design charts suggested based on ANN for a design of doubly reinforced concrete beams were implemented with a design example. A prediction of multiple design parameters in an order that design charts offer consecutively is now possible in this study to help engineers solve reverse design problems in an accurate and rapid way. Accuracies were verified with structural calculations. AI-based reverse design provides engineers with preliminary design. Reverse techniques can be implemented in many areas of design.
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