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Trajectory and Invariant Manifold Computation for Flows in the Chesapeake Bay
Nathan Brasher
February 13, 2005
Acknowledgements
AdvisersProf. Reza Malek-MadaniAssoc. Prof. Gary Fowler
CAD-Interactive Graphics Lab Staff
Chesapeake Bay Analysis
QUODDY Computer ModelFinite-Element
ModelFully 3-
Dimensional9700 nodes
QUODDY
Boussinesq Equations Temperature Salinity
Sigma Coordinates No normal flow Winds, tides and river
inflow included in model
Bathymetry
Trajectory Computation
Surface Flow Computation Radial Basis Function Interpolation Runge-Kutta 4th order method Residence Time Calculations Synoptic Lagrangian Maps
Method of displaying large amounts of trajectory data
Trajectory Computation
Invariant Manifolds
Application of dynamical systems structures to oceanographic flows
Create invariant regions and direct mass transport
Manifolds move with the flow in non-autonomous dynamical systems
yxy
xx
2
Algorithm
Linearize vector field about hyperbolic trajectory
5-node initial segment along eigenvectors
Evolve segment in time, interpolate and insert new nodes
Algorithm due to Wiggins et. al.
Algorithm
1 2
1 1
2 2
1 1 1 1
11 1
2 21 1
1
{ , }
,
/ 2
uj N
j j j j
j
j j j j j j j j
j jj j j jj j
j j j j
j j j
W x x x x
x x x x
x x x x x x x x
x xw ww
w w x x
Redistribution
1
1
1
2
1
old
j j j j
n
new jj
jold
l jk new
x x
n
np i
n
Redistribution algorithm due to Dritschel [1989]
Chesapeake Results
Hyperbolicity appears connected to behavior near boundaries
Manifolds observed in few locations
Interesting fine-scale structure observed
Synoptic Lagrangian Maps
Improved AlgorithmUses data from previous time-sliceImproves efficiency and resolutionNeeds residence time computation for
80-100 particles to maintain ~10,000 total data points
Old Method
Square Grid Each data point
recomputed for each time-slice
New Method
Initial hex-mesh Advect points to
next time-slice Insert new points
to fill gaps Compute
residence time for new points only
New Method
New Method
New Method
Final Result
Scattered Data Interpolated to square grid in MATLAB for plotting purposes
Day 1
Day 3
Day 5
Day 7
Computational Improvement
SLM Computation no longer requires a supercomputing cluster15 Hrs for initial time-slice + 35 Hrs to
extend the SLM for a one-week computation = 50 total machine – hours
Old Method 15*169 = 2185 machine-hours = 3 ½ MONTHS!!!
Accomplishments
Improvement of SLM AlgorithmWeekend run on a single-processor
workstation Implementation of algorithms in
MATLABPlatform independent for the scientific
community Investigation of hyperbolicity and
invariant manifolds in complex geometry
References
Dritschel, D.: Contour dynamics and contour surgery: Numerical algorithms for extended, high-resolution modelling of vortex dynamics in two-dimensional, inviscid, incompressible flows, Comp. Phys. Rep., 10, 77–146, 1989.
Mancho, A., Small, D., Wiggins, S., and Ide, K.: Computation of stable and unstable manifolds of hyperbolic trajectories in two-dimensional, aperiodically time-dependent vector fields, Physica D, 182, 188–222, 2003.
Mancho A., Small D., and Wiggins S. : Computation of hyperbolic trajectories and their stable and unstable manifolds for oceanographic flows represented as data sets, Nonlinear Processes in Geophysics (2004) 11: 17–33