[Faculty] Fwd: [CSRC-SDSU COLLOQUIUM]: Validation of the General Curvilinear Coastal Ocean Model (GCCOM) for the case of 3D Nonhydrostatic Stratified Flow.

[Jose Castillo]

*DATE: * Friday, June 9th, 2017

*TITLE:*  Validation of the General Curvilinear Coastal Ocean Model (GCCOM)
for the case of 3D Nonhydrostatic Stratified Flow.

*TIME: * 3:00 PM

*LOCATION: * GMCS 314

*SPEAKER: *Mariangel Garcia, PhD, Research Associate
Computational Science Research Center

*ABSTRACT:* We present the stratified nonhydrostatic capabilities of the
General Curvilinear Coastal Ocean Model (GCCOM), which is a 3D Navier
Stokes model that has the ability to run in a fully three-dimensional
general curvilinear coordinate system. Earlier versions of this model were
described for flow over complex terrain; however, these earlier versions
treated stratification with a simplified buoyancy forcing term and did not
explicitly take into account hydrostatic pressure gradients. The latest
version of this model more accurately computes the density effects by
removing the buoyancy term and adding a horizontal pressure gradient force
that arises from the hydrostatic component of pressure. This
representation, more accurately captures gravity-driven flows and internal
waves. Furthermore, the pressure solver was updated to a multigrid solver,
 to allow for a lower computational cost. GCCOM has also demonstrated the
ability to nest within a regional hydrostatic model, allowing for the
efficient simulation of multiscale processes, and it includes a data
assimilation framework.

In this contribution, we focus on the validation of the nonhydrostatic
capabilities of the model in a stratified environment. In particular, we
use a suite of test cases widely used as benchmarks for assessing the
nonhydrostatic capabilities for gravity-driven flows and internal waves.
The numerical experiments  include an internal seiche, a lock release, and
a tidally-forced stratified flow over a seamount aimed at investigating the
formation of internal wave beams. Our results collectively demonstrate the
accuracy of GCCOM for these types of flows.


Sponsored by the SDSU-SIAM  Student Chapter
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Jose E. Castillo  Ph.D.

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Computational Science Research Center

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