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Two Demos. Simulation Efforts for GLEON CI for flood Monitoring. Simulation efforts for GLEON. Hydrostatic vs Non-hydrostatic Model (Chris Dallimore, Chin Wu) Two-phase Flows vs Coupling Schemes w/ meteorological models (Wen-Yi Chang et al)
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Two Demos • Simulation Efforts for GLEON • CI for flood Monitoring
Simulation efforts for GLEON • Hydrostatic vs Non-hydrostatic Model(Chris Dallimore, Chin Wu) • Two-phase Flows vs Coupling Schemes w/ meteorological models(Wen-Yi Chang et al) • CFD Coupling w/ Water Quality Model vs Ecological models coupling w/ physical models(David Hamilton, Tim Kratz et al)
Simulation efforts for GLEON • Possible issues for GLEON • Performance issues (CI supports: networks, computers, storages, visualization,e.g. TDW from CI communities of GLEON/CREON, e.g. QPSF, APAC, PRAGMA, Teragrid, OptiPuter … KING-tw etc.) • Complexity issues (different Env.) • Calibration of Physical Models & Ecological Models • Test bed for New Sim. Models (num. perspective) • Regional/Global issues • Meteorological models • Rivers/Ocean Current/Tidal Flows Interactions (interface to CREON) • Parameters from various shared sensor networks. (e.g. ADCP of Kenneth Chu) • Others
Approach • Governing Equations • Equation of continuity • Equations of motion • Weakly compressibility constraint Song and Yuan, 1988
Approach • Governing Equations • Weakly compressibility constraint ACM (Chorin, 1967) ( for steady flow calculation )
Results • Case 1 : Dam-breaking problem • Grid : 200*80 • Initial hydrostatic pressure • Test b Fig. 1 Illustration of dam-breaking problem
Results • Case 1 : Dam-breaking problem Fig. 2 Simulation of free surface evolution
Results • Case 1 : Dam-breaking problem Fig. 3 Comparison of the computed and measured surge front positions Fig. 4 Comparison of the computed and measured water column heights
Results • Case 1 : Dam-breaking problem Fig. 5 Normalized density profiles along the bottom and left sidewall of the container at time
Results • Case 1 : Dam-breaking problem (summary) • for obtaining time-accurate solutions • is inefficient • Computational time: ADM = 2/5 TVD scheme • ADM is more diffusive than TVD scheme
Results • Case 2 : Rayleigh-Taylor instability problem • Grid : 80*240 • Initial hydrostatic pressure • ADM Fig. 6 Illustration of Rayleigh-Taylor instability problem
Results • Case 2 : Rayleigh-Taylor instability problem Fig. 7 Simulation of the interface evolution
Results • Case 2 : Rayleigh-Taylor instability problem Fig. 8 Estimation of linear growth rate n of Rayleigh-Taylor instability Fig. 9 Comparison of the dimensionless growth rate and the theoretical value
Results • Case 3 : Bubble-rising problem • Grid : 120*140 • Initial hydrostatic pressure • TVD-MUSCL Fig . 10 Illustration of bubble-rising problem
Results • Case 3 : Bubble-rising problem Fig. 11 Simulation of the bubble-rising evolution
Results • Case 3 : Bubble-rising problem Zhao et al., 2002 Fig. 12 Simulation results of bubble-rising in the present study Fig. 13 Simulation results of bubble-rising by Zhao et al, 2002
CI for Flood Monitoring • Highly Geographical Distribution of Video Camera • Synthesized Multiple legacy systems w/ last miles and backbones, e.g. GSN/TWAREN. • Scale-up (Jyh-Horng Wu et al) • 2003 5 Video Camera: 3 in Fushan, 2 in Nanjenshan • 2005102 Video Camera • 2007 1000 Video Camera