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Theoretical and Computational

Fluid Dynamics Laboratory

Research Overview

High Performance Computing

Use of non-standard hardware accelerators to increase the performance of parallel supercomputers by at least an order of magnitude.

CFD with Graphics Processors
Scientific Computing with Graphics Processors

Tilera Pro64 (64 core processor)

Supported by DOE/Oak Ridge (Steve Poole)


Numerical Methods

Design of 'mimetic' numerical methods that capture the physics of partial differential equations well.

Discrete Calculus Methods
Unstructured Staggered Mesh Methods
Secondary Conservation
Fractional Step Methods

Supported by a Stanford subcontract from DOE (ASCI)


Turbulence Modeling

Development of equation systems which mimic Navier-Stokes equations but which are computationally tractable on a PC.

Oriented-Eddy Collision Model
Universal RANS/LES (k/eps, RST)
Dissipation Tensor
Decay Rate
Turbine Blades
Turbulent Potential Model

Supported by:
NSF (Fluid Dynamics)
ONR (Pat Purtell/ Ron Joslin)
AFOSR (Tom Beutner)

Superhydrophobic Drag Reduction

Analysis of the fundamental physical mechanisms underlying superhydrophobic drag reduction.

High Reynolds Number Simulations
Turbulent Simulations
Laminar Theory
Experiments (2000)

Data Archive.


Turbulence Simulation

Direct Numerical Simulation of canonical turbulent flows which use physically realistic initial conditions and which use parallel staggered-mesh numerical methods that conserve mass, momentum, kinetic energy and vorticity/circulation, and

Rotating Decay
Plane Strain

Isotropic Decay
Superhydrophobic Surfaces
Shear-Free Turbulent Boundary Layers

Data Archive.

Supported by NSF (Fluid Dynamics)


Free-Surface Simulation

Calculation methods for the simulation of two phase flows with very large density discontinuities. High resolution of the free-surface interface with moving and adaptive staggered mesh methods.


Supported by NSF exploratory grant (SGER)

Interactive Computational Fluid Dynamics

Real-Time Direct Numerical Solution of Turbulent fluid flow. Allows the user to push the fluid with the mouse and obtain an intuitive feel for turbulence. An application for hardware acceleration (below).

PollenSeed (3D) {just email if this need a dll}
Stir Crazy (2D)

Source Code

Local Supercomputing

Parallel Machines built and maintained by the Theoretical and Computational Fluid Dynamics Laboratory.

Orion (8 GPUs, 1924 cores, pictured)
Cyclops (608 cores)
von Karman
(500 cores, decomissioned)

Supported by:
ONR (Pat Purtel/Candice Wark)
UMass College of Engineering (Mike Malone)
Department of Energy
(Steve Poole)