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docs:utils:couette

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couette

couette integrates plane Couette or channel flow from a given initial condition and save velocity fields to disk at a regular interval. (It should probably be called integrate; I might change it to that in the next release.)

main options

  -T0       --T0                <real>      default == 0           start time
  -T1       --T1                <real>      default == 100         end time
  -dt       --dt                <real>      default == 0.03125     timestep
  -dT       --dT                <real>      default == 1           save interval
  -ts       --timestepping      <string>    default == sbdf3       timestepping algorithm
  -nl       --nonlinearity      <string>    default == rot         method of calculating nonlinearity,
  -o        --outdir            <string>    default == data/       output directory
  -R        --Reynolds          <real>      default == 400         Reynolds number
  -c        --channel                                              channelflow instead of plane Couette
  -b        --bulkvelocity                                         hold bulk velocity fixed, not pressure gradient
  -P        --dPdx              <real>      default == 0           value for fixed pressure gradient
  -U        --Ubulk             <real>      default == 0           value for fixed bulk velocity
  <flowfield>      (trailing arg 1)                                initial condition

Complete option list

time intervals

The integration starts at t=T0 and saves data at times t = T0 + n dT, exactly. The dt value is approximate. Channelflow actually rounds dt to the closest integral divisor of dT so that the save interval is exactly what you asked for. Data is saved to disk in files named u0.ff, u1.ff, u2.ff, … if t takes on integer values or filenames with four-digit precision if t otherwise, e.g. u0.000.ff, u0.125.ff, u0.250.ff, …. The integration stops when t = T0 + n dT > T1.

timestepping

The -ts or –timestepping sets the finite-difference time stepping algorithm. It takes the following values

value O(dt^n) algorithm
cnfe1 1 Crank-Nicolson Forward Euler
cnab2 2 Crank-Nicolson Adams-Bashforth
smrk2 2 Spalart-Moser Runge-Kutta
sbdf1 1 Semi-implict Backwards Differentiation
sbdf2 2 Semi-implict Backwards Differentiation
sbdf3 3 Semi-implict Backwards Differentiation
sbdf4 4 Semi-implict Backwards Differentiation

nonlinearity

Usage examples

Integrate

docs/utils/couette.1234542747.txt.gz · Last modified: 2009/02/13 08:32 by gibson