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4 spaces per indentation level, no tabs, no trailing whitespace, and a single newline at end of each file.
113 lines
3.2 KiB
Python
Executable File
113 lines
3.2 KiB
Python
Executable File
""" Solve a steady-state problem by combined damped Newton iteration
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and time integration. Function solve is no longer used, now that the
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functional equivalent has been added to the Cantera C++ kernel. """
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from Cantera import CanteraError
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from Cantera.num import array
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import math, types
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print
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"""
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module solve is deprecated, and may be removed in a future release. If you
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use it and do not want it removed, send an e-mail to cantera-help@caltech.edu.
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"""
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def solve(sim, loglevel = 0, refine_grid = 1, plotfile = '', savefile = ''):
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"""
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Solve a steady-state problem by combined damped Newton iteration
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and time integration.
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"""
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new_points = 1
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# get options
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dt = sim.option('timestep')
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ft = sim.option('ftime')
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# sequence of timesteps
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_steps = sim.option('nsteps')
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if type(_steps) == types.IntType: _steps = [_steps]
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len_nsteps = len(_steps)
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dt = sim.option('timestep')
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ll = loglevel
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soln_number = -1
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max_timestep = sim.option('max_timestep')
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sim.collect()
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# loop until refine adds no more points
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while new_points > 0:
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istep = 0
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nsteps = _steps[istep]
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# loop until Newton iteration succeeds
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ok = 0
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while ok == 0:
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# Try to solve the steady-state problem by damped
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# Newton iteration.
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try:
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if loglevel > 0:
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print 'Attempt Newton solution of ',\
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'steady-state problem...',
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sim.newton_solve(loglevel-1)
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if loglevel > 0:
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print 'success.\n\n'
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print '%'*79+'\n'
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print 'Problem solved on ',sim.npts,' point grid(s).\n'
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print '%'*79+'\n'
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ok = 1
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soln_number += 1
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sim.finish()
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except CanteraError:
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# Newton iteration failed.
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if loglevel > 0: print '\n'
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# Take nsteps time steps, starting with step size
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# dt. The final dt may be smaller than the initial
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# value if one or more steps fail.
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if loglevel == 1:
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print 'Take',nsteps,' timesteps',
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dt = sim.py_timeStep(nsteps,dt,loglevel=ll-1)
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if loglevel == 1: print dt, math.log10(sim.ssnorm())
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istep += 1
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if istep >= len_nsteps:
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nsteps = _steps[-1]
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dt *= 2.0
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else:
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nsteps = _steps[istep]
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if dt > max_timestep: dt = max_timestep
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# A converged solution was found. Save and/or plot it, then
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# check whether the grid should be refined.
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# Add the solution to the plot file
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if plotfile:
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sim.outputTEC(plotfile,"flame","p"+`sim.npts`,append=soln_number)
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# If a filename has been specified for a save file, add
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# the solution to this file
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if savefile:
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sim.save(savefile, soln_name+'_'+`sim.npts`+'_points')
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if loglevel > 2: sim.show()
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if refine_grid:
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# Call refine to add new points, if needed
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new_points = sim.refine(loglevel = loglevel - 1)
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else:
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new_points = 0
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