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Ana L. Quaresma PhD Student, IST António N. Pinheiro

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1 Numerical modelling of flows in pool-type fishways equipped with bottom orifices
Ana L. Quaresma PhD Student, IST António N. Pinheiro Full Professor, IST

2 Introduction Rivers are becoming increasingly fragmented with their longitudinal connectivity compromised by man-made obstacles such as dams which affect fish movements leading to populations decrease and genetic deterioration. Fishways re-establish this connectivity allowing for fish migration. Penide hydroelectric plant pool fishway (Santo, 2005) In Portugal, the most common fish pass is the pool-type one (Santos et al., 2006). It consists of a series of pools, arranged in a stepped pattern, separated by cross-walls that can be equipped with vertical slots, submerged orifices and surface notches. Hydraulic characteristics vary according to pool dimensions, configuration and dimensions of slots, orifices and notches, slope and discharge. Cross-walls with notches and bottom orifices (Santo, 2005) 1

3 Framework In recent years, intense experimental work studying the behaviour of cyprinid species was done in an indoor full scale pool-type fishway, 10 m long, 1 m wide and 1.2 m high of adjustable slope, located in LNEC (Portuguese National Laboratory of Civil Engineering) LNEC’s prototype pool-type fishway facility A 1:2.5 scaled fishway of the existing at LNEC, equipped with a recirculation hydraulic circuit was built at IST (Technical Superior Institute), to make pool-type fishway hydraulic studies easier and allow performing a larger number of experiments in a shorter period of time. LNEC’s facility will be used for experiments with fishes IST’s 1:2.5 scaled pool-type fishway facility 2

4 Physical Model IST’s 1:2.5 scaled fishway is 5.7 m long, 0.4 m wide and 0.5 m high of adjustable slope. It consists of adjustable pools (now 4 pools 0.76 m long x 0.40 m wide x 0.50 m high) divided by five cross-walls equipped with bottom orifices (0.8 x 0.8 m). Consecutive orifices were positioned on opposite sides of the cross-walls, creating a sinusoidal flow path. IST’s 1:2.5 scaled pool-type fishway facility In this configuration notches remained closed Cross-walls detail: consecutive orifices positioned in opposite sides of the cross-walls IST’s experimental fishway facility: elevation 3

5 Objectives The fishway located at IST is used to calibrate numerical simulations with hydraulic measurements using ADV (Acoustic Doppler Velocimeter) and PIV (Particle Image Velocimeter) equipment to measure velocities IST’s 1:2.5 scaled pool-type fishway facility Our goal is to develop innovative design solutions with different geometries using FLOW-3D CFD modelling (varying slopes, basins, slots, orifices and notches dimensions). Velocity magnitude calculation using FLOW-3D To determine the configurations that better suit species capabilities to progress upstream parameters like turbulence, Reynolds shear stress and kinetic energy will be correlated with fish behaviour. The chosen configurations will be tested with fishes at LNEC’s facility to verify their efficiency. LNEC’s prototype pool-type fishway facility 4

6 Numerical Model - Geometry
4 components: Bed Cross-walls Walls Auxiliary solids x z Bed Bed, cross-walls and walls detail Auxiliary solids detail 7 flux surface baffles: 1 flux surface baffle upstream, 5 at the cross-walls and one dowstream Initial conditions: Hydrostatic pressure, with gravity g = -9.8 m/s2 in z direction Initial fluid elevation = 1 m (dowstream water surface elevation) Rendered bed and cross-walls (0.03 m cells) 5

7 Numerical Model - Meshing
Geometry 1 Cubic cells Mesh block planes at cross-walls, walls and orifices (12 in x and z direction and 6 in y direction) 1 mesh block Mesh block details Mesh block planes detail Specified pressure in X Min and X Max Simmetry in Z Min and Z Max and Wall in Y Min and Y Max Boundaries Mesh block boundaries 6

8 Numerical Model - Geometry
Bed Cross-walls Walls Auxiliary solids 4 components rotated to make fishway bed paralel to x direction: x z Rotated bed Initial bed 1 flux surface baffle upstream at the entrance of the flume, 1 at the beginning of the horizontal bed, 5 at the cross-walls and one downstream Hydrostatic pressure, with gravity gx = m/s2 in x direction and gz = m/s2 in z direction Initial fluid elevation = m (downstream water surface elevation) Rotated geometry detail 8 flux surface baffles: Rendered bed and cross-walls (containing block: 0.02 m cells and nested blocks: 0.01 m cells) Initial conditions: 7

9 Numerical Model - Meshing
Geometry 2 Cubic cells The containing block cell size is multiple of the nested block cell size, 2:1 and has mesh planes at all six edges of the nested block 6 mesh blocks, 5 nested blocks at cross-walls Mesh block detail Containing block Specified pressure in X Min and X Max Simmetry in Z Min and Z Max and Wall in Y Min and Y Max Nested blocks Simmetry in all boundaries Mesh block planes detail Boundaries: Mesh block boundaries 8

10 Model setup Physics: Numerics:
Geometry Gravity g = m/s2 in z direction Geometry Gravity gx = m/s2 in x direction and gz = m/s2 in z direction Viscosity and turbulence: Renormalized group model (RNG) No-slip Physics: Volume-of-fluid advection: Default VOF and Split Lagrangian Method Momentum advection: First order and Second order monotonicity preserving Numerics: 9

11 Calibration - Approach to steady state
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12 Calibration - Approach to steady state
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13 Calibration - Surface Elevation
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14 Calibration - Surface Elevation
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15 Calibration - Surface Elevation
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16 Calibration - Surface Elevation
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17 Calibration - VOF Method
Computation time for 100 s of simulation (h) Geometry 1 – Default VOF 0.54 Geometry 1 – Split Lagrangian Method 0.55 Geometry 2 – Default VOF 14.0 Geometry 2 – Split Lagrangian Method 14.9 Intel(R) Core(TM) i7 CPU GHz, 6.0GB RAM 16

18 Calibration - VOF Method
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19 Calibration - Mesh Dependency study
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20 Calibration - TLEN 19

21 Calibration – Roughness study
ks = m (glass min) increases Flow rate Q 0.04% (Geom. 1) and 0.7 % (Geom. 2) ks = m (glass max) decreases Flow rate Q 0.36% (Geom. 1) and increases Q 0.9 % (Geom. 2) ks = m (concrete max) decreases Flow rate Q 1.11% ks = x 10-7 m (hyd. smooth) increases Flow rate Q 0.08% 20

22 Calibration – Roughness study
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23 Calibration – Computation Time
Computation time for 100 s of simulation (h) Total number of cells (active and passive) Total number of active cells 0.03 cells; 2nd order monotonicity preserving (a) 0.54 46 803 0.03 cells; 1st order (a) 0.49 0.02 cells; 2nd order monotonicity preserving (a) 2.1 0.02 cells; 1st order (b) 1.9 0.01 cells Restart; 2nd order monotonicity preserv. (a) 42.7 0.01 cells Restart; 1st order (a) 26.1 0.02 cells; 0.01 cells at crosswalls; 2nd order mon. p. (a) 14.0 0.02 cells; 0.01 cells at crosswalls; 1st order (a) 11.5 0.01 cells; cells at crosswalls; Rest.; 2nd o. m. p. (c) 119.5 ( ≈ 5 days) 0.01 cells; cells at crosswalls; Restart; 1st order (c) 40.2 (a) Intel(R) Core(TM) i7 CPU GHz, 6.0GB RAM (b) Intel Core2 Quad CPU GHz, 3.0GB RAM (c) Intel(R) Core(TM) i GHz, 32.0GB RAM Geometry 1 Geometry 2 (rotated) 22

24 Calibration – Final Results
Renormalized group model (RNG); Default VOF method; st order momentum advection; TLEN = 0.10 ks = m (glass max) Flowrate Q – Average Q = 4.98 l/s Physical Model Average Q = 4.44 l/s Dif. = 12.3% Free surface elevation – Largest Dif. = m Dif. = 3.4% Computation time for 100 s of simulation time (h) – 21.8 h Geometry 1: Renormalized group model (RNG); Default VOF method; st order momentum advection; TLEN = 0.10 Flowrate Q – Average Q = 4.60 l/s Physical Model Average Q = 4.44 l/s Dif. = 3.5% Free surface elevation – Largest Dif. = m Dif. = 3.4% Computation time for 100 s of simulation time (h) – 11.8 h Geometry 2: 23

25 Physical Model vs Numerical Model
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26 Physical Model vs Numerical Model
Flowrate Q – Average Q = 4.60 l/s Physical Model Average Q = 4.44 l/s Dif. = 3.5% 25

27 Physical Model vs Numerical Model
Flowrate Q – Average Q = 4.60 l/s Physical Model Average Q = 4.44 l/s Dif. = 3.5% 26

28 Numerical Model – Velocity Magnitude
Velocity magnitude (m/s) Z = 0.04 m above bottom (orifice axis) Z = m above bottom (25% hm) Z = m above bottom (50% hm) Z = m above bottom (80% hm) 27

29 Physical Model vs Numerical Model Velocity Magnitude
3rd Pool Z (X,Y) VPhysical model (m/s) VFlow 3D (m/s) Dif. (%) 4 cm above bottom (orifice axis) (4, 4) 1.08 0.83 22.8 (4,36) 0.11 0.10 9.9 (12,4) 0.82 0.7 (28,36) 0.14 0.16 11.6 17.6 cm above bottom (50% hm) (4,4) 0.06 39.7 0.30 0.24 19.2 28

30 Numerical Model – Turbulent Energy
Turbulent Energy (J/kg) Z = 0.04 m above bottom (orifice axis) Z = m above bottom (25% hm) Z = m above bottom (50% hm) Z = m above bottom (80% hm) 29

31 Conclusions It is very important to calibrate and validate a model
In the present case study: Significant changes in results depending on: Cell size Momentum advection method Some changes dependig on: Specified TLEN instead of Dynamically computed TLEN Neglectible changes depending on: VOF Method Surface roughness Still work to do but promising results Reynolds shear stress as an additional output variable would be a good followup 30

32 Acknowledgements References
The authors thank Raúl Martín from Simulaciones y proyectos, SL for his suggestions. Ana Quaresma was supported by a grant from UTL (Technical University of Lisbon in the beginning of the work and afterwards by a grant (SFRH/BD/87843/2012) from FCT (Science and Technology Foundation). References FLOW-3D. Advanced Hydraulics Training, th FLOW-3D European Users Conference. Santo, M. (2005), Dispositivos de passagem para peixes em Portugal. DGRF, Lisboa. Santos, J.M., Ferreira, M.T., Pinheiro, A.N., Bochechas, J., Effects of small hydropower plants on fish assemblages in medium-sized streams in Central and Northern Portugal. Aquatic Conservation, 16: 373–388.

33 Numerical modelling of flows in pool-type fishways equipped with bottom orifices
Questions? Comments? Ana L. Quaresma António N. Pinheiro


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