sand transport by non-breaking waves and currents highlights from the santoss project
DESCRIPTION
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 . - PowerPoint PPT PresentationTRANSCRIPT
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Sand transport by non-breaking Sand transport by non-breaking waves and currentswaves and currents
Highlights from the SANTOSS projectHighlights from the SANTOSS project
Jan S. Ribberink, Tom O’DonoghueJan S. Ribberink, Tom O’Donoghueand many others and many others
SANTOSS project funded by UK’s EPSRC (GR/T28089/01) and SANTOSS project funded by UK’s EPSRC (GR/T28089/01) and Dutch research organisation STW (TCB.6586)Dutch research organisation STW (TCB.6586)
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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
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INTRODUCTION
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Research questions
• How is sand transport affected by wave deformation (asymmetry and skewness) ?
• How is sand transport affected by wave-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)
Background SANTOSS (2005-2009)
shoreface
surfzone
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Research approach (1)
1. Data integration
Bring together data from large-scale oscillatory flow experiments conducted in The Netherlands, the UK and elsewhere ( Database)
2. New experiments
1. Acceleration effects (UAb – PhD )
2. Sheet flow under surface waves (UT - PhD)
3. Exp’tal data analysis
Identify and parameterise the most important physical processes determining transport in sheet flow conditions
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4. Process modelling
Models from Deltares, UWB and LU - use process models for understanding, parameterise important processes.
5. New transport model
“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)
1. Data integration
2. New expts
3. data analysis
Research approach (2)
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WAVE DEFORMATION
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Wave deformation: wave skewness
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Acceleration skewness Dominic van de A (UAb)
max
max min
uu u
Near-bed horizontal orbital flow: velocity and acceleration skewness
max
max min
uR
u u
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Research Facility
Aberdeen oscillatory flow tunnel (AOFT)
- 16m long, 0.3m wide, 0.75m high
- T ≈ 5-12s, amax = 1.5m
500mm
7m
fixed bed
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Reynolds stress asymmetry
T = 7s, u0max= 1.1m/s. d50=5. 65mm
β = 0.75
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‘Onshore’ net Sand Transport
• Net transport against acceleration skewness
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PROGRESSIVE SURFACE WAVES vs. OSCILLATORY FLOWS
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Oscillatory flows Progressive surface waves
wave tunnel
wave flume
Horizontal oscillatory flow Horizontal + vertical orbital flow Non-uniform flow
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‘Large-scale’ wave flumes
Delta Flume 2006
GWK Hannover 2007, 2008
Sand transport processes under progressive surface waves
Jolanthe Schretlen (UT)
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10 mm
UVPsVectrino
CCMs
UHCM
TSS
30° 10°
Beach
Wave paddl
e
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Intra-wave boundary layer velocities
H = 1.5 mT = 6.5 sFine sand
Sheet flow layer
onshore
offshore
250
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Wave-mean flow (streaming)
xp
zwu
zu
zzu
z tt
1~~
]~~[])[(
Mean oscillatory turbulent Reynolds stress
Wave ReynoldsStress
‘offshore streaming’ (asymmetric waves)
‘onshore streaming’
Trowbridge & Madsen (1984)Davies and Villaret (1999)
Longuet-Higgins (1958)
Tunnels
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Streaming in Tunnel and Wave flume
Urms = 0.86-0.89 m/sT = 5 sR = 0.54 - 0.6
-10
-5
0
5
10
15
20
25
30
35
-0,1 -0,05 0 0,05 0,1
<U> m/s
z
mm tunnel - f ine
flume - f ine
250
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Medium sands Flume vs Oscillatory Flow Tunnel
-20
0
20
40
60
80
100
120
0 0.05 0.1 0.15 0.2 0.25 0.3
U3 (m3/s3)
net t
rans
port
(10
-6 m
2 /s)
Sand transport rates (medium sand)
Tunnels
GWK flume
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Sand transport rates (fine sand)
Fine Sands Flume vs Oscillatory Flow Tunnel
-100
-80
-60
-40
-20
0
20
40
60
80
100
0 0.05 0.1 0.15 0.2 0.25 0.3
<U 3> (m3/s3)
Net
Tra
nspo
rt (1
0-6
m2 /s
)
GWK flume
Tunnels
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PROCESS-BASED MODELLING
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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+)
Process-based modellingWael Hassan (UT), Wouter Kranenburg (UT), Rob Uittenbogaard (Deltares)
PhD: Wouter Kranenburg
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Mean Sediment flux (single-phase WBL)
0.0
1.0
2.0
3.0
4.0
-50.0 -30.0 -10.0 10.0 30.0 50.0
Total sediment-flux 10-3 (m/s)
z (c
m)
D = 0.15 mm
D = 0.28 mm
-1.0
0.0
1.0
2.0
3.0
4.0
-50.0 -30.0 -10.0 10.0 30.0 50.0
Total sediment-flux 10-3 (m/s)
z (c
m)
D = 0.15 mm
D = 0.28 mm
(Hassan and Ribberink, 2010)
250
onshore
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Mean transport rate (single-phase WBL)
0
50
100
0.2 0.4 0.6 0.8 1.0Urms (m/s)
<qs>
10-6
(m2/s)
RANS-model with S
RANS-model with HRANS-model with H&S
RANS-model without H&Smeasured D = 0.32 mm
-300
-250
-200
-150
-100
-50
0
50
0.2 0.4 0.6 0.8 1.0Urms (m/s)
<qs>
10-6
(m2/s)
RANS-model with S
RANS-model with H
RANS-model with H&S
RANS-model without H&S
measured D = 0.13 mm
250
medium sand fine sand
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Mean transport rate (single-phase, FWD)
250
(Kranenburg et al., 2010)
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PRACTICAL SAND TRANSPORT MODEL
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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
New practical sand transport model Jebbe van der Werf (UT), Dominic van de A (UAb), Rene Buijsrogge (UT), Jan Ribberink (UT)
shoreface
surfzone
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Transport model conceptTransport model concept
δ
zb
Outer layer he
Wave boundary layer
<U>.<C>
<U(t).C(t)>
2-layer schematization
Transport formula
Suspension adv-diff
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c cc tcc
cc
Basic model
350( 1)
s c tc t
q T TT Ts gd
ˆcu
t tt ctt
tt
timeonshore
u
Tc
Half wave-cycle concept
<uδ>
Tt
ˆtu
(Dibajnia and Watanabe, 1996)
Phase-lag effect
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Comparison with database Velocity-skewed wave (+current) data
wave alone &wave+current
ripples(52)sheet flow (86)
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Acceleration-skewed waves
‘Acceleration’ corrections
• Bed shear stress (τc > τt , friction factor )• Phase-lag (Pc < Pt , settling periods)
max
max min
uu u
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Comparison with database Acceleration-skewed wave (+current) data
wave alone &wave+current
medium sand(36)
fine sand(21)
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Transport model: acceleration skewness effect
Velocity + (acceleration) skewed wave (r = 0.62, b = 0.7)
-1.5E-04
-1.0E-04
-5.0E-05
0.0E+00
5.0E-05
1.0E-04
1.5E-04
0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Urms [m/s]
Calc
ulat
ed: Q
sx [m
2/s]
velocity + acceleration skewed
velocity + acceleration skewedvelocity skewed
velocity skewedmedium sand
fine sand
R = 0.62β = 0.7T = 6.5 s
onshore
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Progressive surface waves
Reb w uw
w
• Additional onshore mean bed shear stress
Settling phases
wave Reynolds stress τwRe Lagrangian drift
w
• Lagrangian drift grain motion (Pc < Pt , settling periods)• Grain settling velocity (ws,c > ws,t , Pc < Pt )
‘Surface wave’ corrections
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Comparison with database All (surface) waves (+current)
All waves (206)
% factor 2 : 76 %r2 : 0.81
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Transport model: progressive surface wave effects
onshore
R = 0.62β = 0.5T = 6.5 sh = 3.5 mFine sand
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Comparison with ‘current alone’ data
Current alone(137)
% factor 2 : 87 %r2 : 0.73
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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.
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THE END