Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Particle swarm optimization model to predict scour depth around a bridge pier
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 d50 (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.
Particle swarm optimization model to predict scour depth around a bridge pier
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 d50 (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.
Particle swarm optimization model to predict scour depth around a bridge pier
Front. Struct. Civ. Eng.
Shamshirband, Shahaboddin (Autor:in) / Mosavi, Amir (Autor:in) / Rabczuk, Timon (Autor:in)
Frontiers of Structural and Civil Engineering ; 14 ; 855-866
01.08.2020
12 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Mapping scour depth around group bridge pier under controlled conditions
DOAJ | 2023
|GMDH to predict scour depth around a pier in cohesive soils
Online Contents | 2013
|GMDH to predict scour depth around a pier in cohesive soils
Elsevier | 2012
|Genetic Programming to Predict Bridge Pier Scour
Online Contents | 2010
|Genetic Programming to Predict Bridge Pier Scour
British Library Online Contents | 2010
|