Estimation of scour around twins and three piles using fuzzy c-means clustering of ANFIS Network

Authors

1 Ph.D. Candidate, Department of Water Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran

2 Water Engineering Department, Kermanshah Branch, Islamic Azad University, Kermanshah

3 Department of Water Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran

Abstract

Estimation and prediction of scouring around the piers play a significant role to design these structures since with increasing dimensions of scour hole, stability of the pier is threatened; as a result, the structure may be destructed. In this study, scour hole in the vicinity of twin and three piers is estimated by using fuzzy c-means clustering of ANFIS (ANFIS-FCM) network technique. To do this, firstly, the parameters affecting scour hole around twin and three piers including Froude number (Fr), the ratio of the pier diameter to the flow depth (D/h), and the ratio of the distance between the piers to the flow depth (d/h) were detected. Subsequently, seven ANFIS-FCM models were defined by means of these dimensional input parameters. It should be stated that 70% of the experimental data were utilized to training the models and 30% of the rest were applied to testing. Next, the superior ANFIS-FCM model and the most important input parameter were introduced by implementing a sensitivity analysis. The premium model as a function of all input parameters simulated the scour values with a reasonable accuracy. For instance, the correlation coefficient (R), the scatter index (SI), and the Nash-Sutcliff efficiency coefficient (NSC) are respectively computed to be 0.988, 0.106, and 0.976. Furthermore, the Froude number was considered as the most important input parameter. Lastly, a computer code was introduced so as to simulate the scour hole around the twin and three piers.

Keywords

References

Amini A, Melville BW, Ali TM and Ghazali AH, 2011. Clear-water local scour around pile groups in shallow-water flow. Journal of Hydraulic Engineering 138 (2): 177-185.
Ataie-Ashtiani B and Aslani-Kordkandi A, 2012. Flow field around side-by-side piers with and without a scour hole. European Journal of Mechanics-B/Fluids 36: 152-166.
Ataie-Ashtiani B and Beheshti A, 2006. Experimental investigation of clear-water local scour at pile groups. Journal of Hydraulic Engineering 132 (10): 1100-1104.
Ataie-Ashtiani B, Baratian-Ghorghi Z and Beheshti AA, 2010. Experimental investigation of clear-water local scour of compound piers. Journal of Hydraulic Engineering, 136 (6): 343-351.
Azimi H and Shabanlou S, 2020. U-shaped channels along the side weir for subcritical and supercritical flow regimes. Journal of Hydraulic Engineering 26 (4): 365-375.
Azimi H, Shabanlou S, Ebtehaj I and Bonakdari H, 2016. Discharge coefficient of rectangular side weirs on circular channels. International Journal of Nonlinear Sciences and Numerical Simulation 17(7-8) : 391-399.
Azimi H, Bonakdari H, Ebtehaj I, Shabanlou S, Talesh SHA and Jamali A, 2019. A pareto design of evolutionary hybrid optimization of ANFIS model in prediction abutment scour depth. Sādhanā 44 (7): 169.
Azimi H, Bonakdari H, Ebtehaj I, Talesh SHA, Michelson  DG and Jamali A, 2017. Evolutionary Pareto optimization of an ANFIS network for modeling scour at pile groups in clear water condition. Fuzzy Sets and Systems 319: 50-69.
Azimi, AH, Shabanlou S, Yosefvand F, Rajabi A and Yaghoubi B, 2020. Estimation of scour depth around cross-vane structures using a novel non-tuned high-accuracy machine learning approach. Sādhanā 45: 152 . https://doi.org/10.1007/s12046-020-01390-6
Das S, Das R and Mazumdar A, 2016. Comparison of local scour characteristics around two eccentric piers of different shapes. Arabian Journal for Science and Engineering 41 (4): 1199-1213.
Ebtehaj I, Bonakdari H, Moradi F, Gharabaghi B and Khozani ZS, 2018. An integrated framework of Extreme Learning Machines for predicting scour at pile groups in clear water condition. Coastal Engineering 135: 1-15.
Etemad-Shahidi A, Bonakdar L and Jeng DS, 2015. Estimation of scour depth around circular piers: applications of model tree. Journal of Hydroinformatics 17 (2): 226-238.
Gharib R, Heydari M, Kardar S and Shabanlou S, 2020. Simulation of discharge coefficient of side weirs placed on convergent canals using modern self-adaptive extreme learning machine. Applied Water Science 10 (50): 1-11.
Jang JS, 1993. ANFIS: adaptive-network-based fuzzy inference system. IEEE Transactions on Systems, Man, and Cybernetics 23 (3): 665-685.
Jang JSR, Sun CT and Mizutani E, 1997. Neuro-Fuzzy and Soft Computing. Prentice Hall. ISBN 0-13-261066-3.
Kohansarbaz A, Kohansarbaz A, Yaghoubi B, Izadbakhsh MA and Shabanlou S, 2021. An integration of adaptive neuro-fuzzy inference system and firefly algorithm for scour estimation near bridge piers. Earth Sci Inform 14,:1399–1411 (2021). https://doi.org/10.1007/s12145-021-00652-z
Muzzammil M, Alama J and Danish M, 2015. Scour prediction at bridge piers in cohesive bed using gene expression programming. Aquatic Procedia 4: 789-796.
Majedi Asl M, Daneshfaraz R and Valizadeh S, 2019. The Experimental study of river sand and gravel mining on scouring pattern around pier group. Journal of Hydraulics 14 (3): 129.
Majedi Asl M, Daneshfaraz R and Valizadeh S, 2020. A laboratory study of longitudinal, transverse and topography of the scouring the bridge pier group with sand mining. Water and Soil Science 24 (2): 69-85. (in Persian with English abstract)
Moghadam RG, Izadbakhsh MA, Yosefvand F and Shabanlou S, 2019. Optimization of ANFIS network using firefly algorithm for simulating discharge coefficient of side orifices. Applied Water Science 9 (84): 1-12.
Moghadam RG, Shabanlou S and Yosefvand F, 2020. Optimization of ANFIS Network Using Particle Swarm Optimization Modeling of Scour around Submerged Pipes. J. Marine. Sci. Appl. 19: 444–452. https://doi.org/10.1007/s11804-020-00166-y
Rezaie M, Daneshfaraz R and Dasineh M, 2018. Experimental investigation of adding clay and PAM on scour reduction bridge piers under the influence removal of river materials. Journal of Hydraulics 13 (3): 59-70.
Richardson EV and Davis SR, 2001. Evaluating Scour at Bridges. Hydraulic Engineering Circular 18 (HEC18), 4th Ed., Rep. No. FHWA NHI 01–001, Federal Highway Administration, Washington, D.C.
Shabanlou S, Azimi H, Ebtehaj I and Bonakdari H, 2018. Determining the scour dimensions around submerged vanes in a 180° bend with the Gene Expression Programming Technique. Journal of Marine Science and Application 17: 233–240.
Shabanlou S, 2018. Improvement of extreme learning machine using self-adaptive evolutionary algorithm for estimating discharge capacity of sharp-crested weirs located on the end of circular channels. Flow Measurement and Instrumentation 59: 63-71.
Shabanlou S and Khorami E, 2013. Study of the hydraulic properties of the cylindrical crested weirs. Flow Measurement and Instrumentation 33: 153-159.
Shahbazbeygi E, Yosefvand F, Yaghoubi B, Shabanlou S and Rajabi A, 2021a. Generalized structure of group method of data handling to prognosticate scour around various cross-vane structures. Arab J Geosci 14: 1121. https://doi.org/10.1007/s12517-021-07483-8
Shahbazbeygi E, Yosefvand F, Yaghoubi B, Shabanlou S and Rajabi A, 2021b. Stone weir scour modelling in curved canals using a weighted regularized extreme learning machine. Irrigation and Drainage 70(4): 757–772. Available from: https://doi.org/10.1002/ird.2592
Wang H, Tang H, Liu Q and Wang Y, 2016a. Local scouring around twin bridge piers in open-channel flows. Journal of Hydraulic Engineering 142 (9): 0601600-8.
Wang H, Tang H, Xiao J, Wang Y and Jiang S, 2016b. Clear-water local scouring around three piers in a tandem arrangement. Science China Technological Sciences 59 (6): 888-896.
Zarei S, Yosefvand F and Shabanlou S, 2020. Discharge coefficient of side weirs on converging channels using extreme learning machine modeling method. Measurement 152: 107321.
 
Water and Soil Science
Volume 34, Issue 1
March 2024
Pages 133-148

Files

Share

How to cite

Statistics