Deflection Predictions of Tapered Cellular Steel Beams Using Analytical Models and an Artificial Neural Network

Abstract

Cellular steel beams are primarily used to accommodate electrical and mechanical services within their structural depth, helping to reduce the floor-to-ceiling height in buildings. These beams are often tapered for various reasons, such as connecting members (e.g., beams) of different depths, adjusting stiffness in specific areas, or enhancing architectural design. This paper presents an algorithm developed using MATLAB R2019a and an artificial neural network (ANN) to predict the deflection of tapered cellular steel beams. The approach considers the web I-section variation parameter (α), along with shear and bending effects that contribute to additional deflections. It also accounts for the influence of the stiffness of the upper and lower T-sections at the centreline of the web opening. To validate the model, a total of 1415 finite element models were analysed. The deflections predicted by the analytical and ANN models were compared with finite element results, showing good agreement.