Journal Home Online First Current Issue Archive For Authors Journal Information 中文版

Frontiers of Structural and Civil Engineering >> 2020, Volume 14, Issue 4 doi: 10.1007/s11709-020-0619-2

Particle swarm optimization model to predict scour depth around a bridge pier

. Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Vietnam.. Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam.. Institute of Automation, Kando Kalman Faculty of Electrical Engineering, Obuda University, Budapest 1034, Hungary.. Department of Mathematics and Informatics, J. Selye University, Komarno 94501, Slovakia.. School of the Built Environment, Oxford Brookes University, Oxford OX30BP, UK.. Institute of Structural Mechanics, Bauhaus-Universität Weimar, Weimar 99423, Germany

Received: 2020-05-27 Accepted: 2020-06-28 Available online: 2020-06-28

Next Previous


Scour depth around bridge piers plays a vital role in the safety and stability of the bridges. The former approaches used in the prediction of scour depth are based on regression models or black box models in which the first one lacks enough accuracy while the later one does not provide a clear mathematical expression to easily employ it for other situations or cases. Therefore, this paper aims to develop new equations using particle swarm optimization as a metaheuristic approach to predict scour depth around bridge piers. To improve the efficiency of the proposed model, individual equations are derived for laboratory and field data. Moreover, sensitivity analysis is conducted to achieve the most effective parameters in the estimation of scour depth for both experimental and filed data sets. Comparing the results of the proposed model with those of existing regression-based equations reveal the superiority of the proposed method in terms of accuracy and uncertainty. Moreover, the ratio of pier width to flow depth and ratio of 50 (mean particle diameter) to flow depth for the laboratory and field data were recognized as the most effective parameters, respectively. The derived equations can be used as a suitable proxy to estimate scour depth in both experimental and prototype scales.

Related Research