Prediction of current-induced local scour around complex piers: Review, revisit, and integration

Baghbadorani, Danial Amini; Ataie-Ashtiani, Behzad; Beheshti, Aliasghar; Hadjzaman, Mahmoud; Jamali, Mirmosadegh

doi:10.1016/j.coastaleng.2017.12.006

Cited by 35 publications

(9 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This can be done by having a good understanding of the system hydraulics. In other words, GMDH is merely a tool that cannot be utilized without having insight into the problem (Amini Baghbadorani et al, 2018). This principle was carefully considered since the developed ELM in this paper uses only three of the most influential variables, which results in higher simplicity.…”

Section: Resultsmentioning

confidence: 99%

Experimental study on the discharge coefficient of triangular piano key weir*

Sanami

Afshar

Saneie

2021

Irrigation and Drainage

View full text Add to dashboard Cite

The present study aims to experimentally evaluate the hydraulic characteristics of a B-type triangular piano key weir (PKW). Equations are proposed for estimating the discharge coefficient (C d ) of type B triangular PKW. Nine PKW models were tested, and the discharge coefficients were obtained. To determine the PKW efficiency, in each flow condition, the experiment was repeated for a linear weir having the same height as the PKW. In particular, the flow rate of the triangular PKW was up to three times higher than that of the linear weir. Studying the flow behaviour showed that the sloping triangular surface of the PKW helps with the quick transfer of flow from the channel bed, especially in the outside keys. In addition, increasing the dimensionless parameters h/L e and h/P reduces the discharge coefficient in the weir. Empirical equations are presented for the triangular PKW discharge coefficient. For the regression analysis, analysis of variance was performed to list the most important variables. Subsequently, by performing sensitivity analysis, the most important dimensionless parameter for estimating the discharge coefficient was obtained. The group method of data handling was applied to the data to achieve higher accuracy. Finally, uncertainty analysis was conducted using the asymmetric loss function.

show abstract

Section: Resultsmentioning

confidence: 99%

Experimental study on the discharge coefficient of triangular piano key weir*

Sanami

Afshar

Saneie

2021

Irrigation and Drainage

View full text Add to dashboard Cite

show abstract

“…Piers of this configuration are referred to as complex piers [3]. Knowledge about local scour depth and scour mechanisms around complex piers has been investigated by many researchers [2][3][4][5][31][32][33][34][35][36][37]. All of research workers tried to develop a semi-empirical model to estimate the scour depth in non-uniform piers and complex piers with unexposed foundations using the concept of the primary vortex and sediment transport theory.…”

Section: Review Of Experimental Studymentioning

confidence: 99%

Application of Improved GMDH Models to Predict Local Scour Depth at Complex Bridge Piers

Ghodsi

Khanjani

2020

Civ Eng J

View full text Add to dashboard Cite

Scour depth prediction is a vital issue in bridge pier design. Recently, good progress has been made in the development of artificial intelligence (AI) to predict scour depth around hydraulic structures base such as bridge piers. In this study, two hybrid intelligence models based on combination of group method of data handling (GMDH) with harmony search algorithm (HS) and shuffled complex evolution (SCE) have been developed to predict local scour depth around complex bridge piers using 82 laboratory data measured by authors and 615 data points from published literature. The results were compared to conventional GMDH models with two kinds of transfer functions called GMDH1 and GMDH2. Based upon the pile cap location, data points were divided into three categories. The performance of all utilized models was evaluated by the statistical criteria of R, RMSE, MAPE, BIAS, and SI. Performances of developed models were evaluated by experimental data points collected in laboratory experiments, together with commonly empirical equations. The results showed that GMDH2SCE was the superior model in terms of all statistical criteria in training when the pile cap was above the initial bed level and completely buried pile cap. For a partially-buried pile cap, GMDH1SCE offered the best performance. Among empirical equations, HEC-18 produced relatively good performances for different types of complex piers. This study recommends hybrid GMDH models, as powerful tools in complex bridge pier scour depth prediction.

show abstract

“…As a result, the influence of pile cap may be changed from a protective to intensifying role at the scour process when it is entirely buried and exposed to the flow, respectively [7]. Such roles increase the complicity of scour mechanisms and prediction at CPs [8].…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Intelligence Approach to Enhance the Prediction Accuracy of Local Scour Depth at Complex Bridge Piers

et al. 2020

View full text Add to dashboard Cite

Local scour depth at complex piers (LSCP) cause expensive costs when constructing bridges. In this study, a hybrid artificial intelligence approach of random subspace (RS) meta classifier, based on the reduced error pruning tree (REPTree) base classifier, namely RS-REPTree, was proposed to predict the LSCP. A total of 122 laboratory datasets were used and portioned into training (70%: 85 cases) and validation (30%: 37 cases) datasets for modeling and validation processes, respectively. The statistical metrics such as mean absolute error (MAE), root mean squared error (RMSE), correlation coefficient (R), and Taylor diagram were used to check the goodness-of-fit and performance of the proposed model. The capability of this model was assessed and compared with four state-of-the-art soft-computing benchmark algorithms, including artificial neural network (ANN), support vector machine (SVM), M5P, and REPTree, along with two empirical models, including the Florida Department of Transportation (FDOT) and Hydraulic Engineering Circular No. 18 (HEC-18). The findings showed that machine learning algorithms had the highest goodness-of-fit and prediction accuracy (0.885 < R < 0.945) in comparison to the other models. The results of sensitivity analysis by the proposed model indicated that pile cap location (Y) was a more sensitive factor for LSCP among other factors. The result also depicted that the RS-REPTree ensemble model (R = 0.945) could well enhance the prediction power of the REPTree base classifier (R = 0.885). Therefore, the proposed model can be useful as a promising technique to predict the LSCP.

show abstract

Prediction of current-induced local scour around complex piers: Review, revisit, and integration

Cited by 35 publications

References 27 publications

Experimental study on the discharge coefficient of triangular piano key weir*

Experimental study on the discharge coefficient of triangular piano key weir*

Application of Improved GMDH Models to Predict Local Scour Depth at Complex Bridge Piers

A Hybrid Intelligence Approach to Enhance the Prediction Accuracy of Local Scour Depth at Complex Bridge Piers

Contact Info

Product

Resources

About