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A novel ensemble model for predicting the performance of a novel vertical slot fishway

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Abstract

We investigate the performance of a novel vertical slot fishway by employing finite volume and surrogate models. Multiple linear regression, multiple log equation regression, gene expression programming, and combinations of these models are employed to predict the maximum turbulence, maximum velocity, resting area, and water depth of the middle pool in the fishway. The statistical parameters and error terms, including the coefficient of determination, root mean square error, normalized square error, maximum positive and negative errors, and mean absolute percentage error were employed to evaluate and compare the accuracy of the models. We also conducted a parametric study. The independent variables include the opening between baffles (OBB), the ratio of the length of the large and small baffles, the volume flow rate, and the angle of the large baffle. The results show that the key parameters of the maximum turbulence and velocity are the volume flow rate and OBB.

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References

  1. Fao D V W K. Fish Passes: Design, Dimensions, and Monitoring. Rome: Food and Agriculture Organization of the United Nations, 2002

    Google Scholar 

  2. Katopodis C, Williams J G. The development of fish passage research in a historical context. Ecological Engineering, 2012, 48: 8–18

    Google Scholar 

  3. Rajaratnam N, Van der Vinne G, Katopodis C. Hydraulics of vertical slot fishways. Journal of Hydraulic Engineering, 1986, 112(10): 909–927

    Google Scholar 

  4. Rajaratnam N, Katopodis C, Solanki S. New designs for vertical slot fishways. Canadian Journal of Civil Engineering, 1992, 19(3): 402–414

    Google Scholar 

  5. Cea L, Pena L, Puertas J, Vázquez-Cendón M E, Peña E. Application of several depth-averaged turbulence models to simulate flow in vertical slot fishways. Journal of Hydraulic Engineering, 2007, 133(2): 160–172

    Google Scholar 

  6. Bermúdez M, Puertas J, Cea L, Pena L, Balairón L. Influence of pool geometry on the biological efficiency of vertical slot fishways. Ecological Engineering, 2010, 36(10): 1355–1364

    Google Scholar 

  7. Marriner B A, Baki A B M, Zhu D Z, Thiem J D, Cooke S J, Katopodis C. Field and numerical assessment of turning pool hydraulics in a vertical slot fishway. Ecological Engineering, 2014, 63: 88–101

    Google Scholar 

  8. Katopodis C. Introduction to Fishway Design. Winnipeg: Freshwater Institute, 1992

    Google Scholar 

  9. Liu M, Rajaratnam N, Zhu D Z. Mean flow and turbulence structure in vertical slot fishways. Journal of Hydraulic Engineering, 2006, 132(8): 765–777

    Google Scholar 

  10. Chorda J, Maubourguet M M, Roux H, Larinier M, Tarrade L, David L. Two-dimensional free surface flow numerical model for vertical slot fishways. Journal of Hydraulic Research, 2010, 48(2): 141–151

    Google Scholar 

  11. Tarrade L, Texier A, David L, Larinier M. Topologies and measurements of turbulent flow in vertical slot fishways. Hydro-biology, 2008, 609(1): 177–188

    Google Scholar 

  12. Tarrade L, Pineau G, Calluaud D, Texier A, David L, Larinier M. Detailed experimental study of hydrodynamic turbulent flows generated in vertical slot fishways. Environmental Fluid Mechanics, 2011, 11(1): 1–21

    Google Scholar 

  13. Bombač M, Novak G, Rodič P, Četina M. Numerical and physical model study of a vertical slot fishway. Journal of Hydrology and Hydromechanics, 2014, 62(2): 150–159

    Google Scholar 

  14. Bombač M, Novak G, Mlačnik J, Četina M. Extensive field measurements of flow in vertical slot fishway as data for validation of numerical simulations. Ecological Engineering, 2015, 84: 476–484

    Google Scholar 

  15. Larinier M, Travade F, Porcher J P. Fishways: Biological basis, design criteria and monitoring. Bulletin Francais de la Peche et de la Pisciculture, 2002, 364: 1–208

    Google Scholar 

  16. Fuentes-Pérez J F, Silva A T, Tuhtan J A, García-Vega A, Carbonell-Baeza R, Musall M, Kruusmaa M. 3D modelling of non-uniform and turbulent flow in vertical slot fishways. Environmental Modelling & Software, 2018, 99: 156–169

    Google Scholar 

  17. Fuentes-Pérez J F, Eckert M, Tuhtan J A, Ferreira M T, Kruusmaa M, Branco P. Spatial preferences of Iberian barbel in a vertical slot fishway under variable hydrodynamic scenarios. Ecological Engineering, 2018, 125: 131–142

    Google Scholar 

  18. Li G, Sun S, Zhang C, Liu H, Zheng T. Evaluation of flow patterns in vertical slot fishways with different slot positions based on a comparison passage experiment for juvenile grass carp. Ecological Engineering, 2019, 133: 148–159

    Google Scholar 

  19. Wu S, Rajaratnam N, Katopodis C. Structure of flow in vertical slot fishway. Journal of Hydraulic Engineering, 1999, 125(4): 351–360

    Google Scholar 

  20. Rodríguez T T, Agudo J P, Mosquera L P, González E P. Evaluating vertical-slot fishway designs in terms of fish swimming capabilities. Ecological Engineering, 2006, 27(1): 37–48

    Google Scholar 

  21. Wang R W, David L, Larinier M. Contribution of experimental fluid mechanics to the design of vertical slot fish passes. Knowledge and Management of Aquatic Ecosystems, 2010, 2(396): 78–83

    Google Scholar 

  22. Fuentes-Pérez J F, Sanz-Ronda F J, Martínez de Azagra Paredes A, García-Vega A. Modeling water-depth distribution in vertical-slot fishways under uniform and nonuniform scenarios. Journal of Hydraulic Engineering, 2014, 140(10): 06014016

    Google Scholar 

  23. Marriner B A, Baki A B, Zhu D Z, Cooke S J, Katopodis C. The hydraulics of a vertical slot fishway: A case study on the multi-species Vianney-Legendre fishway in Quebec, Canada. Ecological Engineering, 2016, 90: 190–202

    Google Scholar 

  24. Lepper P. Manual on the Methodological Framework to Derive Environmental Quality Standards for Priority Substances in Accordance with Article 16 of the Water Framework Directive (2000/60/EC). Schmallenberg: Fraunhofer-Institute Molecular Biology and Applied Ecology, 2005

    Google Scholar 

  25. Ciuha D, Povž M, Kvaternik K, Brenčič M, Muck P. The design and technical solutions of passages for aquatic organisms at the HPP on the lower Sava River reach, with an emphasis on the passage at HPP Arto—Blanca. In: Proceedings of the Mišicev Vodarski Dan. Maribor, Slovenia, 2014, 228–236 (in Slovenian)

  26. Kolman G, Mikoš M, Povž M. Fish passages on hydroelectric power dams in Slovenia. Nature conservation, 2010, 24: 85–96

    Google Scholar 

  27. Maddock I, Harby A, Kemp P, Wood P J. Ecohydraulics: An integrated approach. Worcester: John Wiley & Sons, 2013

    Google Scholar 

  28. Calluaud D, Pineau G, Texier A, David L. Modification of vertical slot fishway flow with a supplementary cylinder. Journal of Hydraulic Research, 2014, 52(5): 614–629

    Google Scholar 

  29. Goodwin R, Anderson J, Nestler J. Decoding 3-D movement patternsof fish in response to hydrodynamics and water quality for forecast simulation. In: Proceedings of the 6th International Conference in Hydroinformatics. Singapore: World scientific, 2004

    Google Scholar 

  30. Rodriguez Á, Bermúdez M, Rabuñal J R, Puertas J, Dorado J, Pena L, Balairón L. Optical fish trajectory measurement in fishways through computer vision and artificial neural networks. Journal of Computing in Civil Engineering, 2011, 25(4): 291–301

    Google Scholar 

  31. Duguay J M, Lacey R W J, Gaucher J. A case study of a pool and weir fishway modeled with OpenFOAM and FLOW-3D. Ecological Engineering, 2017, 103: 31–42

    Google Scholar 

  32. Puertas J, Pena L, Teijeiro T. Experimental approach to the hydraulics of vertical slot fishways. Journal of Hydraulic Engineering, 2004, 130(1): 10–23

    Google Scholar 

  33. Clay C H. Design of Fishways and Other Fish Facilities. 2nd ed. Ottawa: Department of Fisheries of Canada, 1995

    Google Scholar 

  34. Bell M C. Fisheries Handbook of Engineering Requirements and Biological Criteria. Portland, OR: Fisheries Engineering Research Program, 1973

    Google Scholar 

  35. Shiri J, Sadraddini A A, Nazemi A H, Kisi O, Landeras G, Fakheri Fard A, Marti P. Generalizability of Gene Expression Programming-based approaches for estimating daily reference evapotranspiration in coastal stations of Iran. Journal of Hydrology (Amsterdam), 2014, 508: 1–11

    Google Scholar 

  36. Traore S, Guven A. New algebraic formulations of evapotranspiration extracted from gene-expression programming in the tropical seasonally dry regions of West Africa. Irrigation Science, 2013, 31(1): 1–10

    Google Scholar 

  37. Azamathulla H M, Yusoff M A M. Soft computing for prediction of river pipeline scour depth. Neural Computing & Applications, 2013, 23(7–8): 2465–2469

    Google Scholar 

  38. Azamathulla H M, Ahmad Z, Ab. Ghani A. An expert system for predicting Manning’s roughness coefficient in open channels by using gene expression programming. Neural Computing & Applications, 2013, 23(5): 1343–1349

    Google Scholar 

  39. Guven A, Aytek A. New approach for stage–discharge relationship: gene-expression programming. Journal of Hydrologic Engineering, 2009, 14(8): 812–820

    Google Scholar 

  40. Azamathulla H M. Gene expression programming for prediction of scour depth downstream of sills. Journal of Hydrology (Amsterdam), 2012, 460–461: 156–159

    Google Scholar 

  41. Kumar A, Goyal P. Forecasting of air quality in Delhi using principal component regression technique. Atmospheric Pollution Research, 2011, 2(4): 436–444

    Google Scholar 

  42. Shishegaran A, Amiri A, Jafari M A. Seismic performance of boxplate, box-plate with UNP, box-plate with L-plate and ordinary rigid beam-to-column moment connections. Journal of Vibroengineering, 2018, 20(3): 1470–1487

    Google Scholar 

  43. Chenini I, Khemiri S. Evaluation of ground water quality using multiple linear regression and structural equation modeling. International Journal of Environmental Science and Technology, 2009, 6(3): 509–519

    Google Scholar 

  44. Chen W B, Liu W C. Water quality modeling in reservoirs using multivariate linear regression and two neural network models. Advances in Artificial Neural Systems, 2015, 2015: 1–6

    Google Scholar 

  45. Nasir M F M, Samsudin M S, Mohamad I, Awaluddin M R A, Mansor M A, Juahir H, Ramli N. River water quality modeling using combined principle component analysis (PCA) and multiple linear regressions (MLR): A case study at Klang River, Malaysia. World Applied Sciences Journal, 2011, 14: 73–82

    Google Scholar 

  46. An R, Li J, Liang R, Tuo Y. Three-dimensional simulation and experimental study for optimising a vertical slot fishway. Journal of Hydro-environment Research, 2016, 12: 119–129

    Google Scholar 

  47. Hirt C, Nichols B. Volume of fluid (VOF) method for the dynamics of free boundaries. Journal of Computational Physics, 1981, 39(1): 201–225

    MATH  Google Scholar 

  48. Prosperetti A, Tryggvason G. Computational Methods for Multiphase Flow. Cambridge: Cambridge University, 2007

    MATH  Google Scholar 

  49. Oertel M, Bung D B. Initial stage of two-dimensional dam-break waves: laboratory versus VOF. Journal of Hydraulic Research, 2012, 50(1): 89–97

    Google Scholar 

  50. Hirsch C. Numerical Computation of Internal and External Flows: The Fundamentals of Computational Fluid Dynamics. Burlington: Elsevier, 2007

    Google Scholar 

  51. Bayon A, Valero D, García-Bartual R, Vallés-Morán F J, López-Jiménez P A. Performance assessment of OpenFOAM and FLOW-3D in the numerical modeling of a low Reynolds number hydraulic jump. Environmental Modelling & Software, 2016, 80: 322–335

    Google Scholar 

  52. Keyes D, Ecer A, Satofuka N, Fox P, Periaux J. Parallel Computational Fluid Dynamics’ 99: Towards Teraflops, Optimization and Novel Formulations. Amsterdam: Elsevier, 2000

    MATH  Google Scholar 

  53. Chen L, Li Y. A numerical method for two-phase flows with an interface. Environmental Modelling & Software, 1998, 13(3–4): 247–255

    Google Scholar 

  54. Hyman J M. Numerical methods for tracking interfaces. Physica D. Nonlinear Phenomena, 1984, 12(1–3): 396–407

    MATH  Google Scholar 

  55. Bayon-Barrachina A, Lopez-Jimenez P A. Numerical analysis of hydraulic jumps using OpenFOAM. Journal of Hydroinformatics, 2015, 17(4): 662–678

    Google Scholar 

  56. Ubbink O. Numerical prediction of two fluid systems with sharp interfaces. Dissertation for the Doctoral Degree. London: University of London and Diploma of Imperial College, 1997

    Google Scholar 

  57. Bung D, Schlenkhoff A. Self-aerated skimming flow on embankment stepped spillways: The effect of additional micro-roughness on energy dissipation and oxygen transfer. In: Proceedings from first IAHR European congress: May 2010, Edinburgh. Edinburgh: Heriot-Watt University, 2010

    Google Scholar 

  58. Pfister M. Chute aerators: Steep deflectors and cavity subpressure. Journal of Hydraulic Engineering, 2011, 137(10): 1208–1215

    Google Scholar 

  59. Chanson H. Hydraulics of aerated flows: Qui pro quo? Journal of Hydraulic Research, 2013, 51(3): 223–243

    Google Scholar 

  60. Lobosco R J, Schulz H E, Simões A L A. Hydrodynamics-Optimizing Methods and Tools. Sao Paulo, 2011, 1–25

  61. Tøge G E. The significance of Froude number in vertical pipes: A CFD study. Thesis for the Master’s Degree. Norway: University of Stavanger, 2012

    Google Scholar 

  62. Valero D, Bung D B. Hybrid investigations of air transport processes in moderately sloped stepped spillway flows. In: E-Proceedings of the 36th IAHR World Congress. The Hague, the Netherlands, 1–10

  63. Ma J, Oberai A A, Lahey R T, Drew D A. Modeling air entrainment and transport in a hydraulic jump using two-fluid RANS and DES turbulence models. Heat and Mass Transfer, 2011, 47(8): 911–919

    Google Scholar 

  64. Valero D, García-Bartual R. Calibration of an air entrainment model for CFD spillway applications. In: Advances in hydroinformatics. Singapore: Springer, 2016, 571–582

    Google Scholar 

  65. Kim J J, Baik J J. A numerical study of the effects of ambient wind direction on flow and dispersion in urban street canyons using the RNG k–ε turbulence model. Atmospheric Environment, 2004, 38(19): 3039–3048

    Google Scholar 

  66. Bombardelli F A, Meireles I, Matos J. Laboratory measurements and multi-block numerical simulations of the mean flow and turbulence in the non-aerated skimming flow region of steep stepped spillways. Environmental Fluid Mechanics, 2011, 11(3): 263–288

    Google Scholar 

  67. Xu T, Jin Y C. Numerical investigation of flow in pool-and-weir fishways using a meshless particle method. Journal of hydraulic research, 2014, 52(6): 849–861

    Google Scholar 

  68. Quaranta E, Katopodis C, Revelli R, Comoglio C. Turbulent flow field comparison and related suitability for fish passage of a standard and a simplified low-gradient vertical slot fishway. River Research and Applications, 2017, 33(8): 1295–1305

    Google Scholar 

  69. Guiny E, Ervine D, Armstrong J. Hydraulic and biological aspects of fish passes for Atlantic salmon. Journal of Hydraulic Engineering, 2005, 131(7): 542–553

    Google Scholar 

  70. Morrison R R, Hotchkiss R H, Stone M, Thurman D, Horner-Devine A R. Turbulence characteristics of flow in a spiral corrugated culvert fitted with baffles and implications for fish passage. Ecological Engineering, 2009, 35(3): 381–392

    Google Scholar 

  71. Silva A T, Santos J M, Ferreira M T, Pinheiro A N, Katopodis C. Effects of water velocity and turbulence on the behaviour of Iberian barbel (Luciobarbus bocagei, Steindachner 1864) in an experimental pool-type fishway. River Research and Applications, 2011, 27(3): 360–373

    Google Scholar 

  72. Hamdia K M, Rabczuk T. Fracture, Fatigue and Wear. Singapore: Springer, 2018

    Google Scholar 

  73. Badawy M F, Msekh M A, Hamdia K M, Steiner M K, Lahmer T, Rabczuk T. Hybrid nonlinear surrogate models for fracture behavior of polymeric nanocomposites. Probabilistic Engineering Mechanics, 2017, 50: 64–75

    Google Scholar 

  74. Nguyen V P, Lian H, Rabczuk T, Bordas S. Modelling hydraulic fractures in porous media using flow cohesive interface elements. Engineering Geology, 2017, 225: 68–82

    Google Scholar 

  75. Rabczuk T, Gracie R, Song J H, Belytschko T. Immersed particle method for fluid-structure interaction. International Journal for Numerical Methods in Engineering, 2010, 81(1): 48–71

    MathSciNet  MATH  Google Scholar 

  76. Wall W A, Rabczuk T. Fluid-structure interaction in lower airways of CT-based lung geometries. International Journal for Numerical Methods in Fluids, 2008, 57(5): 653–675

    MathSciNet  MATH  Google Scholar 

  77. Rabczuk T, Samaniego E, Belytschko T. Simplified model for predicting impulsive loads on submerged structures to account for fluid-structure interaction. International Journal of Impact Engineering, 2007, 34(2): 163–177

    Google Scholar 

  78. Nguyen-Thoi T, Phung-Van P, Rabczuk T, Nguyen-Xuan H, LeVan C. An application of the ES-FEM in solid domain for dynamic analysis of 2D fluid-solid interaction problems. International Journal of Computational Methods, 2013, 10(1): 1340003

    MathSciNet  MATH  Google Scholar 

  79. Najafi B, Faizollahzadeh Ardabili S, Shamshirband S, Chau K W, Rabczuk T. Application of ANNs, ANFIS and RSM to estimating and optimizing the parameters that affect the yield and cost of biodiesel production. Engineering Applications of Computational Fluid Mechanics, 2018, 12(1): 611–624

    Google Scholar 

  80. Zhou S, Zhuang X, Rabczuk T. Phase-field modeling of fluid-driven dynamic cracking in porous media. Computer Methods in Applied Mechanics and Engineering, 2019, 350: 169–198

    MathSciNet  MATH  Google Scholar 

  81. Ferreira C. Soft Computing and Industry. London: Springer, 2002, 635–653

    Google Scholar 

  82. Bates J M, Granger C W. The combination of forecasts. Journal of the Operational Research Society, 1969, 20(4): 451–468

    Google Scholar 

  83. Takezawa K. A revision of AIC for normal error models. Open Journal of Statistics, 2012, 2(3): 309–312

    Google Scholar 

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Authors and Affiliations

  1. Department of Water and Environmental Engineering, School of Civil Engineering, Iran University of Science and Technology, Tehran, 1684613114, Iran

    Aydin Shishegaran

  2. Department of Water and Environmental Engineering, School of Civil Engineering, Semnan University, Semnan, 35131-19111, Iran

    Mohammad Shokrollahi & Ali Mirnorollahi

  3. Department of Water and Environmental Engineering, School of Civil Engineering, Islamic Azad University Central Tehran Branch, Tehran, 1987745815, Iran

    Arshia Shishegaran

  4. School of Progress Engineering, Iran University of Science and Technology, Tehran, 1684613114, Iran

    Mohammadreza Mohammad Khani

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  1. Aydin Shishegaran
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  2. Mohammad Shokrollahi
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Shishegaran, A., Shokrollahi, M., Mirnorollahi, A. et al. A novel ensemble model for predicting the performance of a novel vertical slot fishway. Front. Struct. Civ. Eng. 14, 1418–1444 (2020). https://doi.org/10.1007/s11709-020-0664-x

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