1. EFFECTS OF FLEXIBLE MOTION ON TSUNAMI WALL EFFICACY HARP REU 2011 Nicholas McClendon, Rice University Mentors: H.R. Riggs, Sungsu Lee, Krystian Paczkowski

2. Contents (1) Flexible wall study Background Models and Methods Adaptive Mesh Refinement Results (2) Adaptive mesh study Decomposed domain Whole domain (3) Domain decomposition study Setup Results

3. FLEXIBLE WALL STUDY

4. Background: Tsunami Walls Tsunami walls are designed to reduce the damage done by tsunami waves on coastal structures Typical design parameters: Material Typically reinforced concrete, can be steel Physical dimensions 1 – 12 meters high 100s of meters long Location Distance from sea affects forces sustained Distance from the coastal structures it’s protecting affects damage done

5. Flexible Wall Study Motivation Rigid walls are subject to quick and unpredictable failure Flexible walls absorb the force of incoming waves, increasing durability, reducing impact force, and allowing failure to be predicted more readily Goal To develop an understanding of the effects of flexible motion on tsunami wall efficacy for possible real-world application How? Compare forces sustained by a flexible wall to the forces sustained by a rigid one

6. Models and Methods Mathematical models: K-Epsilon turbulence model Newtonian transport model Linear viscous fluid model Numerical solvers interFoam solver Multiphase solver for two incompressible fluids Numerical technique is the Volume of Fluid Method interDyMFoam solver interFoam + mesh modification capabilities Flexible wall is modeled using a rigid block with a torsional spring applied at the base

7. Adaptive Mesh Refinement AMR refers to refinement of mesh during computation Static AMR Superimposes finer sub- grids on areas of interest Dynamic AMR Alters size, shape, orientation, and/or number of cells Layering, remeshing, and smoothing

8. Domain Setup Setup: 20m x 1.8m x 0.1m domain 2-dimensional simulation 2 phases Liquid (dambreak scenario) Gas Boundary conditions: Rigid wall on sides/bottom Atmosphere on top (permits inflow/outflow) 90,000-cell mesh Simulation’s dimensions are reasonable to test experimentally Test the simulation many times, varying the spring constant each time to determine how the spring constant and angle of deflection relate to the forces sustained by the wall

9. Domain Setup

10. Flexible Wall Simulations

11. Results (spring constant variance)

14. Conclusion: Allowing for deflection of the wall to absorb impact force of the wave does reduce the forces sustained by approximately 1 percent per degree of deflection. Flexible walls could provide effective impact force reduction of tsunami bores Further study: Walls which use the impact and uplift forces of the tsunami bore to raise into place

15. Results (mesh convergence)

17. ADAPTIVE MESH STUDY

18. Adaptive Mesh Study Goal: Observe the effects of adaptive meshing on the consistency of results of a control case interFoam Wall is simply part of boundary interDyMFoam Wall is a separate (fixed) object Adaptive meshing used

19. Adaptive Mesh Study interFoam, 8 processorsinterDyMFoam, 8 processors

20. Adaptive Mesh Study interFoam, 8 processors Velocity magnitude (m/s) snapshot at 1.05 seconds interDyMFoam, 8 processors Velocity magnitude (m/s) snapshot at 1.05 seconds

21. Adaptive Mesh Study interFoam vs. interDyMFoam, 1 processor

22. Adaptive Mesh Study Conclusions: Subdomain coupling for dynamic meshing ( dynamicMotionSolverFvMesh ) needs to be fixed if it is to be used in the future (otherwise cannot trust results from runs done in parallel) On a single processor, results obtained from the control case using static and dynamic meshing align very closely, so the use of dynamic meshing tools is validated for the 1-processor case

23. DOMAIN DECOMPOSITION STUDY

24. Domain Decomposition Study Setup a dambreak scenario Domain is 40m x 3.2m x 1m Dam is 1m x 20m Decomposed the domain into 1, 2, 4, 8, 16, 32, 64, and 128 subdomains Solved on HOSC using interFoam for multiphase Measured several key values (eg. splash height, computation time) from each trial Credit also goes to Adam Koenig and Trent Thurston for gathering and analyzing data for this study.

25. Results Number of processors 1248163264128 Time to reach wall4.40 s 4.35 s-4.40 s 4.35 s Peak force on wall22397 N (5.2s) 16696 N (5.1s) 14451 N (5.1s) 22259 N (5.15s) -13748 N (5.15s) -- Max splash height2.04 m (5.2s) 1.74 m (5.1s) 1.60 m (5.1s) 2.09 m (5.15s) -1.64 m (5.15s) 1.89 m (5.15s) 1.87 m (5.15s) Computation time (ClockTime) 182 h131 h93 h31 h-8 h7.6 h5.6 h Processor time182 h262 h373 h245 h-237 h786 h718 h * Red text denotes measurements extrapolated from partially-completed simulations.

26. Results # processors vs. clock time# processors vs. processor time

27. Results Conclusions: Alternating domain decomposition can result in unpredictable variations in results Computation clocktime reduces with increasing numbers of processors (up to 32 processors), then levels out Processor time remains low until # of processors exceeds 32 Too few processors doesn’t experience the benefits of parallel computing Too many processors loses time in communication between nodes It seems like 16 or 32 processors would be ideal, at least for this simulation, as computations can be executed most quickly without wasting resources

28. References http://www.tfd.chalmers.se/~hani/kurser/OS_CFD_2007/PiroozMorad nia/OpenFOAM-rapport.pdf http://www.tfd.chalmers.se/~hani/kurser/OS_CFD_2007/PiroozMorad nia/OpenFOAM-rapport.pdf http://perso.crans.org/kassiotis/openfoam/movingmesh.pdf http://openfoamwiki.net/index.php/Main_FAQ http://www.openfoam.com/docs/user/ http://www.tfd.chalmers.se/~hani/kurser/OS_CFD_2008/ErikEkedahl/ 6dofbeamer.pdf http://www.tfd.chalmers.se/~hani/kurser/OS_CFD_2008/ErikEkedahl/ 6dofbeamer.pdf http://web.student.chalmers.se/groups/ofw5/Advanced_Training/Dyna micMesh.pdf http://web.student.chalmers.se/groups/ofw5/Advanced_Training/Dyna micMesh.pdf

29. Acknowledgment and Disclaimer I’d like to thank the following people and organizations for their help and support: Dr. Brown, Dr. H.R. Riggs, Prof. Sungsu Lee, Krystian Paczkowski, The University of Hawaii at Manoa, UHM College of Engineering, National Science Foundation, the OpenFOAM community. This material is based upon work supported by the National Science Foundation under Grant No. 0852082. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.