Fast: Flexible Aerodynamic Solver Technolgy

Preamble

Fast is a common/front module for all Fast series solvers.

Fast is only available for use with the pyTree interface. You must import the module:

import Fast.PyTree as Fast

List of functions

– Actions

Fast.PyTree.setNum2Base

Set numeric data dictionary in bases.

Fast.PyTree.setNum2Zones

Set numeric data dictionary in zones.

Fast.PyTree.load

Load tree and connectivity tree.

Fast.PyTree.save

Save tree and connectivity tree.

Fast.PyTree.loadFile

Load tree and connectivity tree.

Fast.PyTree.saveFile

Save tree in file.

Contents

Actions

Fast.PyTree.setNum2Base(a, numb)

Set the numb dictionary to bases. Exists also as in place version (_setNum2Base) that modifies a and returns None.

Parameters:

  • a (Base, pyTree) – input data

  • numb (dictionary) – numerics for base

the keys of numb dictionary are:

Example of use:

# - setNum2Base (pyTree) -
import Converter.PyTree as C
import Converter.Internal as Internal
import Fast.PyTree as Fast

a = C.newPyTree(['Base'])

numb = { 'temporal_scheme': 'explicit',
         'ss_iteration': 30,
         'modulo_verif':20 }

Fast._setNum2Base(a, numb)
Internal.printTree(a)
Fast.PyTree.setNum2Zones(a, numz)

Set the numz dictionary to zones. Exists also as in place version (_setNum2Zones) that modifies a and returns None.

Parameters:

  • a (Zone, Base, pyTree) – input data

  • numz (dictionary) – input data

the keys of numz dictionary are:

  • ‘scheme’: possible values are

  • ‘slope’: possible values are

    • ‘o3’ (third order, see p50 https://tel.archives-ouvertes.fr/pastel-00834850/document)

    • ‘o3sc’ (third order with limiter, see Lugrin scheme)

    • ‘o5’ (fifth order)

    • ‘o5sc’ (fifth order with limiter)

    • ‘o1’ (first order, only valid for roe scheme)

    • ‘minmod’ (second order with minmod limiter, only valid for roe scheme)

    • default value is ‘o3’

  • ‘senseurType’: only valid for ‘senseur’ scheme. Possible values are

    • 0 : correction for speed only

    • 1 : correction for speed, density and pressure

  • ‘motion’: possible values are

  • ‘time_step’:

    • value of time step

    • default value is 1e-4

  • ‘time_step_nature’:

    • ‘global’

    • ‘local’

    • default value is ‘global’

  • ‘epsi_newton’:

    • newton stopping criteria on Loo norm

    • default value is 0.1

  • ‘inj1_newton_tol’:

    • Newton tolerence for BCinj1 inflow condition

    • default value is 1e-5

  • ‘inj1_newton_nit’:

    • Newton Iteration for BCinj1 inflow condition

    • default value is 10

  • ‘psiroe’:

    • Harten correction

    • default value is 0.1

  • ‘cfl’:

    • usefull only if ‘time_step_nature’=’local’

    • default value is 1

  • ‘prandtltb’:

    • turbulent Prandtl number (only active for ‘model’=’NSTurbulent’)

    • default value is 0.92

  • ‘ransmodel’: possible values are

  • ‘SA_add_RotCorr’: possible values are

    • True: add rotation correction to spalart model.

    • False

    • default value is False

  • ‘SA_add_LowRe’: possible values are

    • True: add low Reynolds correction to spalart model.

    • False

    • default value is False

  • ‘DES’: possible values are

  • ‘DES_debug’: possible values are

    • “none”

    • “active” (save delta and fd functions in the FlowSolution#Centers node)

    • default value is ‘none’

  • ‘sgsmodel’: possible values are

    • “Miles” (ViscosityEddy==LaminarViscosity)

    • “smsm” (Selective Mixed Scale model, Lenormand et al, (2000), LES of sub and supersonic channel flow at moderate Re. Int. J. Numer. Meth. Fluids, 32: 369–406)

    • default value is ‘Miles’

  • ‘extract_res’: possible values are

    • 0

    • 1 (save div(F_Euler-F_viscous) in the FlowSolution#Centers node)

    • 2 (save dqdt + div(F_Euler-F_viscous) in the FlowSolution#Centers node)

    • default value is 0

  • ‘source’: possible values are

    • 0

    • 1 (read a source terme in the FlowSolution#Centers node. The conservative variables centers:Density_src, centers:MomentumX_src, centers:MomentumY_src, centers:MomentumZ_src and centers:EnergyStagnationDensity_src are used.)

    • default value is 0

  • ‘ratiom’:

    • cut-off max of mut/mu

    • default value is 10000.

Example of use:

# - setNum2Zones (pyTree) -
import Converter.PyTree as C
import Converter.Internal as Internal
import Fast.PyTree as Fast
import Generator.PyTree as G

a = G.cart((0,0,0), (1,1,1), (10,10,10) )
t = C.newPyTree(['Base', a])

numz = { 'scheme': 'ausmpred',
         'time_step_nature': 'global',
         'time_step': 0.001 }

Fast._setNum2Zones(t, numz)
Internal.printTree(t)
Fast.PyTree.load(fileName='t.cgns', fileNameC='tc.cgns', fileNameS='tstat.cgns', split='single')

Load computation tree t from file. Optionaly load tc (connectivity file) or tstat (statistics file). Returns also the graph as a dictionary {‘graphID’, ‘graphIBC’, ‘procDict’, ‘procList’}. If split=’single’, a single file is loaded. If split=’multiple’, mulitple file format is loaded (restart/restart_0.cgns, …).

Parameters:

  • a (pyTree) – input data

  • fileName (string) – name of file for save

  • split (string) – ‘single’ or ‘multiple’

Returns:

t, tc, ts, graph

Return type:

tuple

# - load (pyTree) -
import Fast.PyTree as Fast
import Converter.PyTree as C
import Generator.PyTree as G
import Converter.Internal as Internal
import Connector.PyTree as X
import Converter.Mpi as Cmpi

# Create case
if Cmpi.rank == 0:
    a = G.cart((0,0,0),(1,1,1),(11,11,11))
    a = Cmpi.setProc(a,0)
    b = G.cart((10,0,0),(1,1,1),(11,11,11))
    b = Cmpi.setProc(b,1)
    t = C.newPyTree(['Base',a,b])
    
    t = X.connectMatch(t, dim=3)
    t = Internal.addGhostCells(t,t,2,adaptBCs=0)
    C.convertPyTree2File(t, 't.cgns')
    tc = C.node2Center(t)
    tc = X.setInterpData(t, tc, loc='centers', storage='inverse')
    C.convertPyTree2File(tc, 'tc.cgns')
Cmpi.barrier()

t,tc,ts,graph = Fast.load('t.cgns', 'tc.cgns', split='single')

#print(t)
#print(tc)
#print(ts)
#print('procDict = ', graph['procDict'])
#print('graphID = ', graph['graphID'])
Fast.PyTree.save(t, fileName='restart.cgns', split='single', temporal_scheme='implicit', NP=0)

Save computation tree t in file. If you run in mpi, NP must be the number of processor. If you run in seq mode, NP must be 0 or a negative number. If split=’single’, a single file is written. If split=’multiple’, different files are created depending on the proc number of each zone (restart/restart_0.cgns, …).

Parameters:

  • a (pyTree) – input data

  • fileName (string) – name of file for save

  • split (string) – ‘single’ or ‘multiple’

  • NP (int) – number of processors

Example of use:

# - save (pyTree) -
import Fast.PyTree as Fast
import Converter.PyTree as C
import Generator.PyTree as G
import Converter.Mpi as Cmpi

a = G.cart((0,0,0),(1,1,1),(11,11,11))
a = Cmpi.setProc(a,0)
b = G.cart((10,0,0),(1,1,1),(11,11,11))
b = Cmpi.setProc(b,1)
t = C.newPyTree(['Base',a,b])
Fast.save(t, fileName='t.cgns', split='single', NP=0)
Fast.PyTree.loadFile(fileName='t.cgns', split='single', mpirun=False)

Load tree from file. The tree must be already distributed (with ‘proc’ nodes). The file can be a single CGNS file (“t.cgns”) or a splitted per processor CGNS file (“t/t_1.cgns”, “t/t_2.cgns”, …)

If you run in sequential mode, mpirun must be false. The function returns a full tree.

If you run in mpi mode, mpirun must be true. The function returns a partial tree on each processor.

Parameters:

  • fileName (string) – name of file for load

  • split (string) – ‘single’ or ‘multiple’

  • mpirun (boolean) – true if python is run with mpirun

Returns:

t

Return type:

CGNS tree

# - loadFile (pyTree) -
import Fast.PyTree as Fast
import Converter.PyTree as C
import Generator.PyTree as G
import Converter.Mpi as Cmpi

# Save a file
a = G.cart((0,0,0),(1,1,1),(11,11,11))
a = Cmpi.setProc(a,0)
b = G.cart((10,0,0),(1,1,1),(11,11,11))
b = Cmpi.setProc(b,1)
t = C.newPyTree(['Base',a,b])
Fast.saveFile(t, fileName='t.cgns', split='single', mpirun=False)

# Load it back
Fast.loadFile(fileName='t.cgns', split='single', mpirun=False)
Fast.PyTree.saveFile(fileName='t.cgns', split='single', mpirun=False)

Save tree to file. The tree must be already distributed (with ‘proc’ nodes).

The file can be a single CGNS file (“t.cgns”) or a splitted per processor CGNS file (“t/t_1.cgns”, “t_2.cgns”, …)

If you run in seq mode, mpirun must be false.

If you run in mpi mode, mpirun must be true.

Parameters:

  • fileName (string) – name of file for load

  • split (string) – ‘single’ or ‘multiple’

  • mpirun – true if python is run with mpirun

# - saveFile (pyTree) -
import Fast.PyTree as Fast
import Converter.PyTree as C
import Generator.PyTree as G
import Converter.Mpi as Cmpi

a = G.cart((0,0,0),(1,1,1),(11,11,11))
a = Cmpi.setProc(a,0)
b = G.cart((10,0,0),(1,1,1),(11,11,11))
b = Cmpi.setProc(b,1)
t = C.newPyTree(['Base',a,b])
Fast.saveFile(t, fileName='t.cgns', split='single', mpirun=False)

Index