Upload
delftsoftwaredays
View
290
Download
3
Embed Size (px)
Citation preview
Grid design in estuaries and lagoons
using Delft3D Flexible Mesh
Bas van Maren, Arnold van Rooijen, Arthur van Dam,
Giselle Lemos (Technital), Herman Kernkamp
Introduction
Delft3D-FLOW * D-Flow FM **
Morphodynamics 2015?
Sand-mud interaction 2016?
Vegetation
3D flow
Resolution
Numerical aspects: conveyance & definition of fluxes
Case studies: Wadden Sea & Venice Lagoon
* Delft3D-FLOW = hydrodynamic simulation engine of Delft3D 4
** D-Flow FM = hydrodynamic simulation engine of Delft3D Flexible Mesh
Model resolution
This presentation:
- Short introduction on computational methods in D-Flow FM related
to model resolution (conveyance and 2nd order fluxes)
- Comparison of D-Flow FM – Delft3D-FLOW, for two lagoons:
- Wadden Sea
- Venice Lagoon
5
Delft3D-FLOW: tile depths - uniform friction and depth per cell
D-Flow FM: bed levels at cell corners. 2D analytical conveyance -
compute friction integral along entire cell’s edge, based on
bathymetry at cell’s corner points.
Model resolution: conveyance
KfKI, Bremerhaven, 2 November 2011 6
Delft3D-FLOW,
3 cells
The computed discharge
does not converge when
increasing # cells, when
using tile depths.
Correct discharge ≈ 497 m3/s
KfKI, Bremerhaven, 2 November 2011 7
The computed discharge
does not converge when
increasing # cells, when
using tile depths.
Correct discharge ≈ 497 m3/s
Delft3D-FLOW,
48 cells
KfKI, Bremerhaven, 2 November 2011 8
The computed discharge
now does converge
when using 2D
conveyance.
Correct discharge ≈ 497 m3/s
D-Flow FM,
48 cells
KfKI, Bremerhaven, 2 November 2011 9
The computed discharge
now does converge
when using 2D
conveyance.
Correct discharge ≈ 497 m3/s
D-Flow FM,
3 cells
Less curvilinear cells needed in
D-Flow FM compared to
Delft3D-FLOW because of
friction formulation
Model resolution: triangular or curvilinear
Less curvilinear cells needed in
case of simple topographies
Channels in an D-Flow FM model are preferentially
designed with a curvilinear grid
But also: larger cells larger
timestep possible
QQc
QQc
juc
jdcjcjuc
1
12
,ju
j
j jQ
j
j
u tc c S
xc cc
jc
jc
Triangular grids lead to
cross-flow numerical diffusion
Model resolution: triangular or curvilinear
Channels in an D-Flow FM model are preferentially
designed with a curvilinear grid
Model resolution: conclusions
- Less curvilinear cells needed in D-Flow FM compared to
Delft3D-FLOW because of the bed schematization (conveyance)
- Curvilinear cells are more efficient than triangular cells for simple
geometry
- Less grid cells needed
- Larger grid cells larger timestep possible
- Triangular grids lead to cross-flow numerical diffusion
Use curvilinear grids when
possible and triangular grids
when needed
Case study: the Wadden Sea
Curvilinear grid
(Borsje et al. 2008) Unstructured grid
Grid Time step
Delft3D-FLOW curvilinear 1 min
D-Flow FM: CL curvilinear 1 min
D-Flow FM unstructured ≈ 20 sec (CFL-
condition based)
Case study: the Wadden Sea
- Delft3D-FLOW model most accurate
- Related to numerical settings optimization needed in the
D-Flow FM model (and practical experience)
RMSE (cm) Den
Oever
Harlingen Kornwerder
zand
Delft3D-FLOW 9.9 6.8 8.2
D-Flow FM: CL 10.0 8.7 9.1
D-Flow FM 11.1 8.8 12.4
Case study: the Wadden Sea
- D-Flow FM is 2.5 times faster than Delft3D-FLOW for the
curvilinear grid
- The new D-Flow FM model is much slower, because of much
higher resolution
Model run Wall clock time # time steps x
1000
# grid cells
Delft3D-FLOW 143 m 176 20829
D-Flow FM: CL 63 m 187 20829
D-Flow FM 464 m 602 45134
Case study: the Venice Lagoon
- Venice lagoon model setup in
Delft3D-FLOW and D-Flow FM
(various configurations, see
presentation Giselle Lemos)
- Continuous improvements in the past
years
Case study: the Venice Lagoon
10 november 2014
VENICE LAGOON: SOUTHERN PART 3D-FLOW VENICE MODEL: SOUTHERN PART D-FLOW VENICE MODEL: SOUTHERN PART
Triangular cells used as ‘glue’.
Curvilinear cells when possible,
triangular when needed
Case study: the Venice Lagoon – curvilinear grid
10 november 2014
D-Flow FM and Delft3D-FLOW
give similar results on the same
curvilinear grid, but D-Flow FM
is 2 times faster
Case study: the Venice Lagoon – new grid
Fluxes Water levels
New grid: D-Flow FM slightly
better, but computationally more
demanding
Conclusions
D-Flow FM is more accurate in complex topographies less grid
cells required
D-Flow FM is faster combined with less grid cells the model should
be much faster
Case studies: D-Flow FM is >2 times faster on same curvilinear grid
and comparably accurate
Pitfall: increase the horizontal resolution (too much…) resulting in
(much) slower models
Setting up an D-Flow FM grid takes time – think carefully before actual
grid design
Need to improve hands-on experience for accurate numerical settings
Use curvilinear grids when possible and triangular grids when needed
(‘glue’)