1. Computational Fluid Dynamics P AVEL P ETRUNEAC B ACHELOR OF S CIENCE D ISSERTATION R ENEWABLE E NERGY OF TURBULENCE EFFECTS ON THE SEABED Supervisor(s): Dr. Justin Hinshelwood, Prof. Lars Johanning and Dr. Ian Ashton. 2 nd October 2015 – The Association of European Renewable Energy Research Centre

2. Outline Background Hydrodynamic Flume Experiment CFD Process Results Validation Conclusion

3. Offshore cables – Smart routing tools Most of subsea power cables are buried Rocky seabed requires solid fastening options Subsea cable challenges  Fatigue  Stability  Interaction with the seabed To minimize these effects, intelligent, smart routing tools are essential. 3

4. Project objective Validate experimental results with a numerical turbulence model which is meant to be used when velocity fields are generated in CFD software and used as input in Cable Analysis Software Tool (CAST), designed by Mojo Maritime Ltd. 4

5. 5 Source: University of Exeter (2014) Seabed profile selection

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7. 7 Seabed profile selection – CAD Profile

8. Physical Seabed Profile 8

9. Experiment Methodology - Instrumentation High-resolution acoustic velocimeter used to measure 3D water velocity Has one transmit transducer and four receive transducers Resolution as fine as 1mm over a 35mm range with an output rate as fast as 100Hz 9 Source: Nortek As (2013) Vectrino Profiler

10. Experiment Methodology - Instrumentation Software controlled Logs the exact time-stamped position Position accuracy ±0.05 mm in both vertical and horizontal axes 10 Source: HR Wallingford (2014) Traverse System

11. CFD Process – ANSYS Design Modeller Initially, the whole bathymetry was imported, but due to computational limitations only a small area was finally analyzed ‘boolean subtract’ used to create the computational domain Name selection created – used in CFX and meshing application 11

12. CFD Process – ANSYS Meshing Process of dividing the computational domain in tiny volume/elements. Structure vs. unstructured mesh: tetrahedral was used for the whole domain and hexahedral mesh for the bottom. Flow separation from the wall requires inflation layers: 30 layers were created. Due to complex geometry, the mesh code created some inconsistency in the fluid domain. 12

13. CFD Process – ANSYS CFX-Pre: Boundary Conditions Sensitivity analysis for 10 cases Three turbulence models selected: κ- ɛ, κ-ω SST and Reynolds model RSM SMC-BSL Fractional intensity varied from 0.01 to 0.03, 0.05 and 0.1 Turbulence length varied from 35mm to 15 with increments of 10 Fixed sand grain roughness ANSYS parametrisation ‘what-if’ analysis failed to update Design Points 13

14. Results - Experimental data 14

15. Results - Experimental data 15

16. Results – CFD data 16 The advantage of CFD is that it could interpolate the value of different variables in spatial-temporal domains where data is missing. The main data exported from the CFD simulations are point- measurements which correspond to the plane where the input velocity was taken from. Twelve points were selected in total, exporting the Velocity U in x direction.

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18. Validation 18

19. Validation 19

20. Validation 20

21. Validation 21

22. Validation 22

23. Validation 23

24. Validation k-ε model  predicts the onset of flow separation too late and under-predicts the amount of separation later on  it involves the complex nonlinear damping functions  has an inability to handle low turbulent Reynolds number computations  not applicable for flows with boundary layer separation and flows over curved surfaces Reynolds RSM SMC-BSL model  has an increased number of transport equations which leads to reduced numerical robustness  tends to be more suitable to complex flows  it proves to be inferior to two-equation models k-ω SST model  designed to bring more accuracy in the flow separation prediction  the code involves near-wall treatment for low Reynolds number  it proves to be more accurate and more robust  allows for a smooth shift from low to high Reynolds number  it is recommended for high accuracy in boundary layer simulations. 24

25. Conclusion  The offshore cables still remain a main area of concern due to the fatigue and cable stability issues.  CAST is designed to meet smart routing need, but more studies on guidelines on CFD modelling as input data are required.  The experimental trials have successfully run and the velocity profiles show the effect of the bathymetry on the flow.  The validation technique shows that k-ω SST has the lowest discrepancy between data, hence being a reliable turbulence model for seabed flow modelling.  The fractional intensity has little impact on the RSQ-eq when the turbulence model and length scale is constant. 25

26. Questions? 26 Pavel Petruneac Subsea Cables Research Engineer (PhD) Mojo Maritime Ltd. || University of Exeter T: +44 (0) 1326 218 218 E: pavel.petruneac@mojomaritime.compavel.petruneac@mojomaritime.com W: www.mojomaritime.comwww.mojomaritime.com