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Sand transport by non-breaking waves and currents Highlights from the SANTOSS project

Sand transport by non-breaking waves and currents Highlights from the SANTOSS project. Jan S. Ribberink, Tom O’Donoghue and many others SANTOSS project funded by UK’s EPSRC (GR/T28089/01) and Dutch research organisation STW (TCB.6586). Contents presentation .

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Sand transport by non-breaking waves and currents Highlights from the SANTOSS project

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  1. Sand transport by non-breaking waves and currentsHighlights from the SANTOSS project Jan S. Ribberink, Tom O’Donoghue and many others SANTOSS project funded by UK’s EPSRC (GR/T28089/01) and Dutch research organisation STW (TCB.6586)

  2. Contents presentation • Introduction: Project background, aims and approach • Wave deformation: acceleration skewness (PhD-UAb) • Progressive surface waves vs. oscillatory flows (PhD-UT) • Process-based modelling (PhD-UT/Deltares) • Practical sand transport model • Conclusions SANTOSS

  3. INTRODUCTION SANTOSS

  4. Background SANTOSS (2005-2009) Research questions • How is sand transport affected by wave deformation (asymmetry and skewness) ? • Howis sand transport affected bywave-induced mean flows (e.g. boundary layer streaming) • How to develop a practical sand transport formula for this environment (wave+ current, different bed regimes, variable grain size) surfzone shoreface SANTOSS

  5. Bring together data from large-scale oscillatory flow experiments conducted in The Netherlands, the UK and elsewhere ( Database) 1. Data integration 2. New experiments 3. Exp’tal data analysis • Acceleration effects (UAb – PhD ) • Sheet flow under surface waves (UT - PhD) Identify and parameterise the most important physical processes determining transport in sheet flow conditions Research approach (1) SANTOSS

  6. 4. Process modelling 5. New transport model 1. Data integration 2. New expts 3. data analysis Models from Deltares, UWB and LU - use process models for understanding, parameterise important processes. “semi-empirical” model: “explicitly accounts for the most important physical processes through parameterisations based on the experimental data and sound understanding of the physical processes” (UT and UAb) Research approach (2) SANTOSS

  7. WAVE DEFORMATION SANTOSS

  8. Wave deformation: wave skewness SANTOSS

  9. Acceleration skewnessDominic van de A (UAb) Near-bed horizontal orbital flow: velocity and acceleration skewness SANTOSS

  10. 500mm fixed bed 7m Research Facility • Aberdeen oscillatory flow tunnel (AOFT) • 16m long, 0.3m wide, 0.75m high • T ≈ 5-12s, amax = 1.5m SANTOSS

  11. Reynolds stress asymmetry β = 0.75 T = 7s, u0max= 1.1m/s. d50=5. 65mm SANTOSS

  12. ‘Onshore’ net Sand Transport • Net transport against acceleration skewness SANTOSS

  13. PROGRESSIVE SURFACE WAVES vs. OSCILLATORY FLOWS SANTOSS

  14. wave tunnel Oscillatory flows Progressive surface waves wave flume Horizontal oscillatory flow Horizontal + vertical orbital flow Non-uniform flow SANTOSS

  15. ‘Large-scale’ wave flumes Delta Flume 2006 GWK Hannover 2007, 2008 Sand transport processes under progressive surface waves Jolanthe Schretlen (UT) SANTOSS

  16. 30° 10° Wave paddle Beach 10 mm TSS Vectrino UVPs UHCM CCMs SANTOSS

  17. Sheet flow layer offshore onshore Intra-wave boundary layer velocities H = 1.5 m T = 6.5 s Fine sand SANTOSS

  18. Wave-mean flow (streaming) Tunnels Mean oscillatory turbulent Reynolds stress Wave Reynolds Stress ‘offshore streaming’ (asymmetric waves) ‘onshore streaming’ Trowbridge & Madsen (1984) Davies and Villaret (1999) Longuet-Higgins (1958) SANTOSS

  19. Streaming in Tunnel and Wave flume Urms = 0.86-0.89 m/s T = 5 s R = 0.54 - 0.6 SANTOSS

  20. Sand transport rates (medium sand) GWK flume Tunnels SANTOSS

  21. Sand transport rates (fine sand) GWK flume Tunnels SANTOSS

  22. PROCESS-BASED MODELLING SANTOSS

  23. Process-based modellingWael Hassan (UT), Wouter Kranenburg (UT), Rob Uittenbogaard (Deltares) Wave boundary layer models with hydrostatic pressure distribution (1DV) Single-phase models (UWB, Deltares/UT-PSM: Wael Hassan) Two-phase flow model (UL) Full water depth model, non-hydrostatic for waves (1DV) Single-phase models (Deltares/UT-PSM) (Semi) two-phase model (Deltares/UT-PSM+) PhD: Wouter Kranenburg SANTOSS

  24. Mean Sediment flux (single-phase WBL) onshore (Hassan and Ribberink, 2010) SANTOSS

  25. Mean transport rate (single-phase WBL) medium sand fine sand SANTOSS

  26. Mean transport rate (single-phase, FWD) (Kranenburg et al., 2010) SANTOSS

  27. PRACTICAL SAND TRANSPORT MODEL SANTOSS

  28. New practical sand transport modelJebbe van der Werf (UT), Dominic van de A (UAb), Rene Buijsrogge (UT), Jan Ribberink (UT) Requirements • Simple formula for application in morphodyamic model • Cross-shore and alongshore transport (wave + current) • Wave shapes (velocity, acceleration-skewed) • Range of grain sizes (fine -> coarse sand) • Bed regimes: sheet-flow (flat beds) and rippled beds surfzone shoreface SANTOSS

  29. Transport model concept 2-layer schematization he Suspension adv-diff <U>.<C> Outer layer δ <U(t).C(t)> Transport formula Wave boundary layer zb SANTOSS

  30. Tt Basic model Half wave-cycle concept u onshore <uδ> time Phase-lag effect Tc (Dibajnia and Watanabe, 1996) SANTOSS

  31. Comparison with database Velocity-skewed wave (+current) data wave alone & wave+current ripples (52) sheet flow (86) SANTOSS

  32. Acceleration-skewed waves • ‘Acceleration’ corrections • Bed shear stress (τc >τt , friction factor ) • Phase-lag (Pc < Pt , settling periods) SANTOSS

  33. Comparison with database Acceleration-skewed wave (+current) data wave alone & wave+current medium sand (36) fine sand (21) SANTOSS

  34. onshore Transport model: acceleration skewness effect R = 0.62 β = 0.7 T = 6.5 s SANTOSS

  35. Progressive surface waves Settling phases wave Reynolds stress τwRe Lagrangian drift ‘Surface wave’ corrections • Additional onshore mean bed shear stress • Lagrangian drift grain motion (Pc < Pt , settling periods) • Grain settling velocity (ws,c > ws,t , Pc < Pt) SANTOSS

  36. Comparison with database All (surface) waves (+current) All waves (206) % factor 2 : 76 % r2 : 0.81 SANTOSS

  37. onshore Transport model: progressive surface wave effects R = 0.62 β = 0.5 T = 6.5 s h = 3.5 m Fine sand SANTOSS

  38. Comparison with ‘current alone’ data Current alone (137) % factor 2 : 87 % r2 : 0.73 SANTOSS

  39. Main conclusions • Through lab research and process-based modelling new insights were obtained in the influence of wave shape and surface wave processes on the sand transport process. • Acceleration skewness of wave-induced oscillatory flows leads to additional ‘onshore’ sand transport in the sheet flow regime. • For identical oscillatory flow the sand transport under progressive surface waves is more onshore than in wave tunnels, caused by the combined influence of surface wave processes such as WBL streaming and Lagrangian grain motion effects. • Based on the new insights and a new large dataset an improved sand transport formula was developed. The model performs well in a wide range of conditions: different wave shapes, wave+current, current alone, range of grain sizes, different bed regimes. SANTOSS

  40. THE END SANTOSS

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