Wednesday, July 16

(This session will run until 5:45PM)

3:15 PM-5:45 PM
Terman Auditorium

MS50
Numerical Methods for Low Speed and All Speed Flows

Low speed flows are difficult to simulate numerically due to the presence of sound waves. In many applications, neither an incompressible approximation nor a full compressible numerical scheme would be appropriate. To make the low speed flow problem numerically feasible, one needs to be able to advance the fluid flow in time steps unrestricted by the sound speed. One way to achieve this goal is to separate the acoustics from the flow field. In this symposium, the speakers will present various techniques for splitting the flow field, results of numerical experiments, and applications to aeroacoustics and combustion computations.

The purpose of this symposium is to facilitate communications between various schools of thought on the subjects of computations of low mach number flow and computational aeroacoustics. The intended audience include engineers and mathematicians interested in computational methods for slightly compressible flow computations and/or sound generation by fluid flows.

Organizer: Karen Pao
Los Alamos National Laboratory

3:15 A Solution Adaptive All-Speed Flow Algorithm For Overlapping Grids

William D. Henshaw, Los Alamos National Laboratory; Heinz-Otto Kreiss, University of California, Los Angeles; and Karen Pao, Organizer

3:45 Using Low Mach Number Asymptotics in Extending a Godunov-Type Compressible Flow Solver to the Weakly Compressible Regime

Karl J. Geratz, Institute fuer Technische Mechanik- RWTH, Germany; Sabine Roller and Claus-Dieter Munz, INR-Karlsruhe, Germany; and Rupert Klein, Universitaet Wuppertal, Germany

4:15 On Numerical Cancellation in the Computation of Compressible Low Mach Number Flows

Joern L. Sesterhenn, University of Washington

4:45 A Projection Method for the Slightly Compressible Eulers Equations

Phillip Colella, University of California, Berkeley; and Karen Pao, Organizer

5:15 Computation of Flow Generated Sound

Sanjiva K. Lele, Stanford University

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