Estimation of maximum scour depth downstream of an apron under submerged wall jets

Abstract

An analysis of laboratory experimental data pertaining to local scour downstream of a rigid apron developed under wall jets is presented. The existing equations for the prediction of the maximum scour depth under wall jets are applied to the available data to evaluate their performance and bring forth their limitations. A comparison of measured scour depth with that computed by the existing equations shows that most of the existing empirical equations perform poorly. Artificial neural network (ANN)- and adaptive neuro-fuzzy interference system (ANFIS)-based models are developed using the available data, which provide simple and accurate tools for the estimation of the maximum scour depth. The key parameters that affect the maximum scour depth are densimetric Froude number, apron length, tailwater level, and median sediment size. Results obtained from ANN and ANFIS models are compared with those of empirical and regression equations by means of statistical parameters. The performance of ANN (RMSE = 0.052) and ANFIS (RMSE = 0.066) models is more satisfactory than that of empirical and regression equations.

The Effect of Rough Rigid Apron on Scour Downstream of Sluice Gates

“…Many empirical equations are available in the literature to predict the maximum depth of scour around piers and under wall jets [35][36][37]. Aamir and Ahmad [38] compared the performance of the existing equations using the available laboratory data and concluded that the equation proposed by Dey and Sarkar [15] is superior to others. However, that equation does not account for roughness of the stiff apron and is applicable only to smooth aprons.…”

“…Empirical equations were obtained for characteristic lengths of scour hole in non-uniform and uniform sediments, and guidelines were provided for designing a launching apron [16]. Aamir and Ahmad [17,18] investigated experimentally the characteristics of submerged jets causing scour downstream of an apron and developed an empirical equation for the prediction of equilibrium scour depth. Recently, researchers used soft-computing techniques to predict scour downstream of sluice gates and other hydraulic structures [19][20][21][22][23][24].…”

Scour downstream of a corrugated apron under wall jets

“…Appropriate design of erosion protection works requires thorough study of the scour profile and dimensions, and the flow characteristics within the scour hole. Several studies of scour hole and flow characteristics downstream of sluice gates have been done (Hassan & Narayanan 1985;Chatterjee et al 1995;Balachandar & Kells 1997, 1998Balachandar et al 2000;Dey & Sarkar 2006;Bey et al 2007Bey et al , 2008Farhoudi & Smith 2010;Guan et al 2014;Melville & Lim 2014;Aamir & Ahmad 2015Pandey et al 2015). Different appurtenancese.g., chutes, sills, and baffle blocksare generally placed in stilling basins to stabilize flow by creating turbulence to dissipate energy.…”

“…According to Dey & Sarkar (2006), a launching apron (IRC-89 1985) of 18 mm stones downstream of a solid apron on an unconsolidated bed over a length twice the maximum scour depth can reduce scour depth significantly. A comprehensive review of scour due to wall jets was made by Aamir & Ahmad (2016).…”

Pipeline Scour Rates Prediction-Based Model Utilizing a Multilayer Perceptron-Colliding Body Algorithm

“…In this context, it could be concluded that the empirical models do not experience proper generalization ability for estimating the maximum scour below the PLs. In recent decades, soft computing models such as genetic programming (GP) [4][5][6][7], artificial neural network (ANN) [8][9][10][11], adaptive neuro fuzzy interface system (ANFIS) [12][13][14][15], and regression tree [16,17] were successfully utilized to forecast the scour depth below PLs. It should be noted that the scour rate is dependent on the flow direction, flow characteristics, PL diameter, and sediment properties.…”