Prediction of the depth of local scouring at a bridge pier using a gene expression programming method

Abstract

Local scouring around the piers of a bridge is the one of the major reasons for bridge failure, potentially resulting in heavy losses in terms of both the economy and human life. Prediction of accurate depth of local scouring is a difficult task due to the many factors that contribute to this process, however. The main aim of this study is thus to offer a new formula for the prediction the local depth of scouring around the pier of a bridge using a modern fine computing modelling technique known as gene expression programming (GEP), with data obtained from numerical simulations used to compare GEP performance with that of a standard non-linear regression (NLR) model. The best technique for prediction of the local scouring depth is then determined based on three statistical parameters: the determination coefficient (R2), mean absolute error (MAE), and root mean squared error (RMSE). A total data set of 243 measurements, obtained by numerical simulation in Flow-3D, for intensity of flow, ratio of pier width, ratio of flow depth, pier Froude number, and pier shape factor is divided into training and validation (testing) datasets to achieve this. The results suggest that the formula from the GEP model provides better performance for predicting the local depth of scouring as compared with conventional regression with the NLR model, with R2 = 0.901, MAE = 0.111, and RMSE = 0.142. The sensitivity analysis results further suggest that the ratio of the depth of flow has the greatest impact on the prediction of local scour depth as compared to the other input parameters. The formula obtained from the GEP model gives the best predictor of depth of scouring, and, in addition, GEP offers the special feature of providing both explicit and compressed arithmetical terms to allow calculation of such depth of scouring.

Analysis of Variables Influencing Scour on Large Sand-Bed Rivers Conducted Using Field Data

“…Hassan and Jalal [50] (HJ abbreviated) numerically simulated scour around the bridge pier on a real scale to evaluate the performance of predicting scour depth with the GEP model. They used a numerical dataset consisting of 243 observations collected in a clearwater regime and calibrated with the results from the Melville laboratory model [51].…”

“…Unfortunately, only ranges of nondimensional variables are given in their study, so the real span of variable values remains unknown. However, it can be assumed that Hassan and Jalal [50] collected numerical data in terms of lower water depths since flow depth turned out to be the most significant variable. This assumption is supported by the work of Melville and Sutherland [52], as they claim that flow depth does not play an important role in scour when the y/b ef ratio is above 2.6.…”

Estimation of local scour depth around twin piers using gene expression programming (local scour around twin piers)

“…Furthermore, to carry out the relationship, a few assumptions are made (1) viscous effect is not present; (2) sediment particles are well graded; and (3) influence of pier shape factor is not present, as the value of shape factor for the circular pier is 1. The author (Hassan & Jalal 2021) considered nine pier shapes for experimental study. The results of his research state that the pier shape factor does not play a key role in scour depth prediction.…”

Assessing Artificial Recharge on Groundwater Quantity Using Wells Recharge

“…As an alternate supply, treated wastewater can be utilized for irrigation to meet agricultural water needs and for artificial recharge of aquifers to slow the depletion of groundwater. Many countries, such as the USA, Canada, the Netherlands, Mexico, France, Brazil, Qatar, Egypt, Saudi Arabia, China, Cyprus, and India, use such methods [14][15][16][17][18][19]. Artificial water recharge is one way to sustainably manage the decline of groundwater levels in nations like Iraq, which are located in arid regions [20][21][22][23][24][25].…”