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######################################################## |
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# |
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# Copyright (c) 2003-2009 by University of Queensland |
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# Earth Systems Science Computational Center (ESSCC) |
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# http://www.uq.edu.au/esscc |
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# |
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# Primary Business: Queensland, Australia |
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# Licensed under the Open Software License version 3.0 |
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# http://www.opensource.org/licenses/osl-3.0.php |
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# |
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######################################################## |
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|
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__copyright__="""Copyright (c) 2003-2009 by University of Queensland |
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Earth Systems Science Computational Center (ESSCC) |
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http://www.uq.edu.au/esscc |
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Primary Business: Queensland, Australia""" |
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__license__="""Licensed under the Open Software License version 3.0 |
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http://www.opensource.org/licenses/osl-3.0.php""" |
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__url__="https://launchpad.net/escript-finley" |
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|
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import unittest |
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import tempfile |
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|
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from esys.escript import * |
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from esys.finley import Rectangle |
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from esys.escript.models import DarcyFlow |
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import sys |
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import os |
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try: |
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FINLEY_WORKDIR=os.environ['FINLEY_WORKDIR'] |
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except KeyError: |
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FINLEY_WORKDIR='.' |
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|
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|
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VERBOSE=False # or True |
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|
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from esys.escript import * |
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from esys.escript.models import StokesProblemCartesian, PowerLaw, IncompressibleIsotropicFlowCartesian |
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from esys.finley import Rectangle, Brick |
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|
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from esys.escript.models import Mountains |
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from math import pi |
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|
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#==================================================================================================================== |
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class Test_StokesProblemCartesian2D(unittest.TestCase): |
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def setUp(self): |
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NE=6 |
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self.TOL=1e-3 |
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self.domain=Rectangle(NE,NE,order=2,useFullElementOrder=True) |
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def tearDown(self): |
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del self.domain |
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def test_PCG_P_0(self): |
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ETA=1. |
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P1=0. |
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|
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x=self.domain.getX() |
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F=-P1*x[1]*[1.,0]+(2*ETA-P1*x[0])*[0.,1.] |
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mask=whereZero(x[0]) * [1.,1.] \ |
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+whereZero(x[0]-1) * [1.,1.] \ |
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+whereZero(x[1]) * [1.,0.] \ |
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+whereZero(x[1]-1) * [1.,1.] |
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|
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sp=StokesProblemCartesian(self.domain) |
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|
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sp.initialize(f=F,fixed_u_mask=mask,eta=ETA) |
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u0=(1-x[0])*x[0]*[0.,1.] |
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p0=Scalar(-P1,ReducedSolution(self.domain)) |
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sp.setTolerance(self.TOL) |
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u,p=sp.solve(u0,p0,verbose=VERBOSE,max_iter=100,usePCG=True) |
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|
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error_v0=Lsup(u[0]-u0[0]) |
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error_v1=Lsup(u[1]-u0[1])/0.25 |
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error_p=Lsup(p+P1*x[0]*x[1]) |
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self.failUnless(error_p<10*self.TOL, "pressure error too large.") |
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self.failUnless(error_v0<10*self.TOL, "0-velocity error too large.") |
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self.failUnless(error_v1<10*self.TOL, "1-velocity error too large.") |
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|
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def test_PCG_P_small(self): |
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ETA=1. |
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P1=1. |
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|
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x=self.domain.getX() |
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F=-P1*x[1]*[1.,0]+(2*ETA-P1*x[0])*[0.,1.] |
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mask=whereZero(x[0]) * [1.,1.] \ |
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+whereZero(x[0]-1) * [1.,1.] \ |
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+whereZero(x[1]) * [1.,0.] \ |
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+whereZero(x[1]-1) * [1.,1.] |
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|
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sp=StokesProblemCartesian(self.domain) |
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|
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sp.initialize(f=F,fixed_u_mask=mask,eta=ETA) |
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u0=(1-x[0])*x[0]*[0.,1.] |
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p0=Scalar(-P1,ReducedSolution(self.domain)) |
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sp.setTolerance(self.TOL*0.2) |
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u,p=sp.solve(u0,p0, verbose=VERBOSE,max_iter=100,usePCG=True) |
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error_v0=Lsup(u[0]-u0[0]) |
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error_v1=Lsup(u[1]-u0[1])/0.25 |
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error_p=Lsup(P1*x[0]*x[1]+p) |
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self.failUnless(error_v0<10*self.TOL, "0-velocity error too large.") |
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self.failUnless(error_v1<10*self.TOL, "1-velocity error too large.") |
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self.failUnless(error_p<10*self.TOL, "pressure error too large.") |
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|
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def test_PCG_P_large(self): |
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ETA=1. |
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P1=1000. |
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|
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x=self.domain.getX() |
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F=-P1*x[1]*[1.,0]+(2*ETA-P1*x[0])*[0.,1.] |
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mask=whereZero(x[0]) * [1.,1.] \ |
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+whereZero(x[0]-1) * [1.,1.] \ |
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+whereZero(x[1]) * [1.,0.] \ |
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+whereZero(x[1]-1) * [1.,1.] |
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|
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sp=StokesProblemCartesian(self.domain) |
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|
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sp.initialize(f=F,fixed_u_mask=mask,eta=ETA) |
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u0=(1-x[0])*x[0]*[0.,1.] |
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p0=Scalar(-P1,ReducedSolution(self.domain)) |
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sp.setTolerance(self.TOL) |
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u,p=sp.solve(u0,p0, verbose=VERBOSE,max_iter=100,usePCG=True) |
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|
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error_v0=Lsup(u[0]-u0[0]) |
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error_v1=Lsup(u[1]-u0[1])/0.25 |
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error_p=Lsup(P1*x[0]*x[1]+p)/P1 |
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self.failUnless(error_p<10*self.TOL, "pressure error too large.") |
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self.failUnless(error_v0<10*self.TOL, "0-velocity error too large.") |
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self.failUnless(error_v1<10*self.TOL, "1-velocity error too large.") |
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|
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def test_GMRES_P_0(self): |
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ETA=1. |
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P1=0. |
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|
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x=self.domain.getX() |
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F=-P1*x[1]*[1.,0]+(2*ETA-P1*x[0])*[0.,1.] |
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mask=whereZero(x[0]) * [1.,1.] \ |
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+whereZero(x[0]-1) * [1.,1.] \ |
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+whereZero(x[1]) * [1.,0.] \ |
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+whereZero(x[1]-1) * [1.,1.] |
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|
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sp=StokesProblemCartesian(self.domain) |
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|
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sp.initialize(f=F,fixed_u_mask=mask,eta=ETA) |
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u0=(1-x[0])*x[0]*[0.,1.] |
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p0=Scalar(-P1,ReducedSolution(self.domain)) |
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sp.setTolerance(self.TOL) |
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u,p=sp.solve(u0,p0, verbose=VERBOSE,max_iter=50,usePCG=False,iter_restart=18) |
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|
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error_v0=Lsup(u[0]-u0[0]) |
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error_v1=Lsup(u[1]-u0[1])/0.25 |
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error_p=Lsup(P1*x[0]*x[1]+p) |
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self.failUnless(error_p<10*self.TOL, "pressure error too large.") |
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self.failUnless(error_v0<10*self.TOL, "0-velocity error too large.") |
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self.failUnless(error_v1<10*self.TOL, "1-velocity error too large.") |
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|
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def test_GMRES_P_small(self): |
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ETA=1. |
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P1=1. |
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|
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x=self.domain.getX() |
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F=-P1*x[1]*[1.,0]+(2*ETA-P1*x[0])*[0.,1.] |
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mask=whereZero(x[0]) * [1.,1.] \ |
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+whereZero(x[0]-1) * [1.,1.] \ |
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+whereZero(x[1]) * [1.,0.] \ |
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+whereZero(x[1]-1) * [1.,1.] |
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|
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sp=StokesProblemCartesian(self.domain) |
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|
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sp.initialize(f=F,fixed_u_mask=mask,eta=ETA) |
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u0=(1-x[0])*x[0]*[0.,1.] |
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p0=Scalar(-P1,ReducedSolution(self.domain)) |
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sp.setTolerance(self.TOL*0.1) |
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u,p=sp.solve(u0,p0, verbose=VERBOSE,max_iter=20,usePCG=False) |
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|
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error_v0=Lsup(u[0]-u0[0]) |
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error_v1=Lsup(u[1]-u0[1])/0.25 |
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error_p=Lsup(P1*x[0]*x[1]+p) |
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self.failUnless(error_p<10*self.TOL, "pressure error too large.") |
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self.failUnless(error_v0<10*self.TOL, "0-velocity error too large.") |
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self.failUnless(error_v1<10*self.TOL, "1-velocity error too large.") |
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|
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def test_GMRES_P_large(self): |
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ETA=1. |
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P1=1000. |
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|
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x=self.domain.getX() |
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F=-P1*x[1]*[1.,0]+(2*ETA-P1*x[0])*[0.,1.] |
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mask=whereZero(x[0]) * [1.,1.] \ |
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+whereZero(x[0]-1) * [1.,1.] \ |
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+whereZero(x[1]) * [1.,0.] \ |
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+whereZero(x[1]-1) * [1.,1.] |
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|
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sp=StokesProblemCartesian(self.domain) |
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|
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sp.initialize(f=F,fixed_u_mask=mask,eta=ETA) |
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u0=(1-x[0])*x[0]*[0.,1.] |
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p0=Scalar(-P1,ReducedSolution(self.domain)) |
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sp.setTolerance(self.TOL) |
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u,p=sp.solve(u0,p0, verbose=VERBOSE,max_iter=100,usePCG=False) |
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|
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error_v0=Lsup(u[0]-u0[0]) |
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error_v1=Lsup(u[1]-u0[1])/0.25 |
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error_p=Lsup(P1*x[0]*x[1]+p)/P1 |
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self.failUnless(error_p<10*self.TOL, "pressure error too large.") |
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self.failUnless(error_v0<10*self.TOL, "0-velocity error too large.") |
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self.failUnless(error_v1<10*self.TOL, "1-velocity error too large.") |
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#==================================================================================================================== |
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class Test_StokesProblemCartesian3D(unittest.TestCase): |
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def setUp(self): |
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NE=6 |
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self.TOL=1e-4 |
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self.domain=Brick(NE,NE,NE,order=2,useFullElementOrder=True) |
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def tearDown(self): |
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del self.domain |
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def test_PCG_P_0(self): |
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ETA=1. |
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P1=0. |
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|
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x=self.domain.getX() |
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F=-P1*x[1]*x[2]*[1.,0.,0.]-P1*x[0]*x[2]*[0.,1.,0.]+(2*ETA*((1-x[0])*x[0]+(1-x[1])*x[1])-P1*x[0]*x[1])*[0.,0.,1.] |
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x=self.domain.getX() |
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mask=whereZero(x[0]) * [1.,1.,1.] \ |
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+whereZero(x[0]-1) * [1.,1.,1.] \ |
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+whereZero(x[1]) * [1.,0.,1.] \ |
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+whereZero(x[1]-1) * [1.,1.,1.] \ |
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+whereZero(x[2]) * [1.,1.,0.] \ |
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+whereZero(x[2]-1) * [1.,1.,1.] |
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|
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|
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sp=StokesProblemCartesian(self.domain) |
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|
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sp.initialize(f=F,fixed_u_mask=mask,eta=ETA) |
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u0=(1-x[0])*x[0]*(1-x[1])*x[1]*[0.,0.,1.] |
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p0=Scalar(-P1,ReducedSolution(self.domain)) |
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sp.setTolerance(self.TOL) |
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u,p=sp.solve(u0,p0, verbose=VERBOSE ,max_iter=100,usePCG=True) |
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|
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error_v0=Lsup(u[0]-u0[0]) |
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error_v1=Lsup(u[1]-u0[1]) |
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error_v2=Lsup(u[2]-u0[2])/0.25**2 |
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error_p=Lsup(P1*x[0]*x[1]*x[2]+p) |
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self.failUnless(error_p<10*self.TOL, "pressure error too large.") |
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self.failUnless(error_v0<10*self.TOL, "0-velocity error too large.") |
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self.failUnless(error_v1<10*self.TOL, "1-velocity error too large.") |
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self.failUnless(error_v2<10*self.TOL, "2-velocity error too large.") |
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|
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def test_PCG_P_small(self): |
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ETA=1. |
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P1=1. |
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|
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x=self.domain.getX() |
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F=-P1*x[1]*x[2]*[1.,0.,0.]-P1*x[0]*x[2]*[0.,1.,0.]+(2*ETA*((1-x[0])*x[0]+(1-x[1])*x[1])-P1*x[0]*x[1])*[0.,0.,1.] |
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mask=whereZero(x[0]) * [1.,1.,1.] \ |
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+whereZero(x[0]-1) * [1.,1.,1.] \ |
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+whereZero(x[1]) * [1.,0.,1.] \ |
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+whereZero(x[1]-1) * [1.,1.,1.] \ |
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+whereZero(x[2]) * [1.,1.,0.] \ |
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+whereZero(x[2]-1) * [1.,1.,1.] |
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|
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|
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sp=StokesProblemCartesian(self.domain) |
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|
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sp.initialize(f=F,fixed_u_mask=mask,eta=ETA) |
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u0=(1-x[0])*x[0]*(1-x[1])*x[1]*[0.,0.,1.] |
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p0=Scalar(-P1,ReducedSolution(self.domain)) |
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sp.setTolerance(self.TOL*0.1) |
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u,p=sp.solve(u0,p0, verbose=VERBOSE ,max_iter=100,usePCG=True) |
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error_v0=Lsup(u[0]-u0[0]) |
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error_v1=Lsup(u[1]-u0[1]) |
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error_v2=Lsup(u[2]-u0[2])/0.25**2 |
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error_p=Lsup(P1*x[0]*x[1]*x[2]+p) |
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self.failUnless(error_p<10*self.TOL, "pressure error too large.") |
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self.failUnless(error_v0<10*self.TOL, "0-velocity error too large.") |
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self.failUnless(error_v1<10*self.TOL, "1-velocity error too large.") |
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self.failUnless(error_v2<10*self.TOL, "2-velocity error too large.") |
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|
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def test_PCG_P_large(self): |
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ETA=1. |
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P1=1000. |
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|
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x=self.domain.getX() |
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F=-P1*x[1]*x[2]*[1.,0.,0.]-P1*x[0]*x[2]*[0.,1.,0.]+(2*ETA*((1-x[0])*x[0]+(1-x[1])*x[1])-P1*x[0]*x[1])*[0.,0.,1.] |
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mask=whereZero(x[0]) * [1.,1.,1.] \ |
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+whereZero(x[0]-1) * [1.,1.,1.] \ |
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+whereZero(x[1]) * [1.,0.,1.] \ |
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+whereZero(x[1]-1) * [1.,1.,1.] \ |
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+whereZero(x[2]) * [1.,1.,0.] \ |
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+whereZero(x[2]-1) * [1.,1.,1.] |
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|
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|
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sp=StokesProblemCartesian(self.domain) |
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|
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sp.initialize(f=F,fixed_u_mask=mask,eta=ETA) |
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u0=(1-x[0])*x[0]*(1-x[1])*x[1]*[0.,0.,1.] |
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p0=Scalar(-P1,ReducedSolution(self.domain)) |
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sp.setTolerance(self.TOL) |
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u,p=sp.solve(u0,-p0, verbose=VERBOSE ,max_iter=100,usePCG=True) |
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|
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error_v0=Lsup(u[0]-u0[0]) |
| 300 |
error_v1=Lsup(u[1]-u0[1]) |
| 301 |
error_v2=Lsup(u[2]-u0[2])/0.25**2 |
| 302 |
error_p=Lsup(P1*x[0]*x[1]*x[2]+p)/P1 |
| 303 |
self.failUnless(error_p<10*self.TOL, "pressure error too large.") |
| 304 |
self.failUnless(error_v0<10*self.TOL, "0-velocity error too large.") |
| 305 |
self.failUnless(error_v1<10*self.TOL, "1-velocity error too large.") |
| 306 |
self.failUnless(error_v2<10*self.TOL, "2-velocity error too large.") |
| 307 |
|
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def test_GMRES_P_0(self): |
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ETA=1. |
| 310 |
P1=0. |
| 311 |
|
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x=self.domain.getX() |
| 313 |
F=-P1*x[1]*x[2]*[1.,0.,0.]-P1*x[0]*x[2]*[0.,1.,0.]+(2*ETA*((1-x[0])*x[0]+(1-x[1])*x[1])-P1*x[0]*x[1])*[0.,0.,1.] |
| 314 |
x=self.domain.getX() |
| 315 |
mask=whereZero(x[0]) * [1.,1.,1.] \ |
| 316 |
+whereZero(x[0]-1) * [1.,1.,1.] \ |
| 317 |
+whereZero(x[1]) * [1.,1.,1.] \ |
| 318 |
+whereZero(x[1]-1) * [1.,1.,1.] \ |
| 319 |
+whereZero(x[2]) * [1.,1.,0.] \ |
| 320 |
+whereZero(x[2]-1) * [1.,1.,1.] |
| 321 |
|
| 322 |
|
| 323 |
sp=StokesProblemCartesian(self.domain) |
| 324 |
|
| 325 |
sp.initialize(f=F,fixed_u_mask=mask,eta=ETA) |
| 326 |
u0=(1-x[0])*x[0]*(1-x[1])*x[1]*[0.,0.,1.] |
| 327 |
p0=Scalar(-P1,ReducedSolution(self.domain)) |
| 328 |
sp.setTolerance(self.TOL) |
| 329 |
u,p=sp.solve(u0,p0, verbose=VERBOSE,max_iter=100,usePCG=False,iter_restart=20) |
| 330 |
|
| 331 |
error_v0=Lsup(u[0]-u0[0]) |
| 332 |
error_v1=Lsup(u[1]-u0[1]) |
| 333 |
error_v2=Lsup(u[2]-u0[2])/0.25**2 |
| 334 |
error_p=Lsup(P1*x[0]*x[1]*x[2]+p) |
| 335 |
self.failUnless(error_p<10*self.TOL, "pressure error too large.") |
| 336 |
self.failUnless(error_v0<10*self.TOL, "0-velocity error too large.") |
| 337 |
self.failUnless(error_v1<10*self.TOL, "1-velocity error too large.") |
| 338 |
self.failUnless(error_v2<10*self.TOL, "2-velocity error too large.") |
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def test_GMRES_P_small(self): |
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ETA=1. |
| 341 |
P1=1. |
| 342 |
|
| 343 |
x=self.domain.getX() |
| 344 |
F=-P1*x[1]*x[2]*[1.,0.,0.]-P1*x[0]*x[2]*[0.,1.,0.]+(2*ETA*((1-x[0])*x[0]+(1-x[1])*x[1])-P1*x[0]*x[1])*[0.,0.,1.] |
| 345 |
mask=whereZero(x[0]) * [1.,1.,1.] \ |
| 346 |
+whereZero(x[0]-1) * [1.,1.,1.] \ |
| 347 |
+whereZero(x[1]) * [1.,1.,1.] \ |
| 348 |
+whereZero(x[1]-1) * [1.,1.,1.] \ |
| 349 |
+whereZero(x[2]) * [1.,1.,0.] \ |
| 350 |
+whereZero(x[2]-1) * [1.,1.,1.] |
| 351 |
|
| 352 |
|
| 353 |
sp=StokesProblemCartesian(self.domain) |
| 354 |
|
| 355 |
sp.initialize(f=F,fixed_u_mask=mask,eta=ETA) |
| 356 |
u0=(1-x[0])*x[0]*(1-x[1])*x[1]*[0.,0.,1.] |
| 357 |
p0=Scalar(-P1,ReducedSolution(self.domain)) |
| 358 |
sp.setTolerance(self.TOL*0.1) |
| 359 |
u,p=sp.solve(u0,p0, verbose=VERBOSE,max_iter=100,usePCG=False) |
| 360 |
|
| 361 |
error_v0=Lsup(u[0]-u0[0]) |
| 362 |
error_v1=Lsup(u[1]-u0[1]) |
| 363 |
error_v2=Lsup(u[2]-u0[2])/0.25**2 |
| 364 |
error_p=Lsup(P1*x[0]*x[1]*x[2]+p)/P1 |
| 365 |
self.failUnless(error_v0<10*self.TOL, "0-velocity error too large.") |
| 366 |
self.failUnless(error_v1<10*self.TOL, "1-velocity error too large.") |
| 367 |
self.failUnless(error_v2<10*self.TOL, "2-velocity error too large.") |
| 368 |
self.failUnless(error_p<10*self.TOL, "pressure error too large.") |
| 369 |
def test_GMRES_P_large(self): |
| 370 |
ETA=1. |
| 371 |
P1=1000. |
| 372 |
|
| 373 |
x=self.domain.getX() |
| 374 |
F=-P1*x[1]*x[2]*[1.,0.,0.]-P1*x[0]*x[2]*[0.,1.,0.]+(2*ETA*((1-x[0])*x[0]+(1-x[1])*x[1])-P1*x[0]*x[1])*[0.,0.,1.] |
| 375 |
mask=whereZero(x[0]) * [1.,1.,1.] \ |
| 376 |
+whereZero(x[0]-1) * [1.,1.,1.] \ |
| 377 |
+whereZero(x[1]) * [1.,0.,1.] \ |
| 378 |
+whereZero(x[1]-1) * [1.,1.,1.] \ |
| 379 |
+whereZero(x[2]) * [1.,1.,0.] \ |
| 380 |
+whereZero(x[2]-1) * [1.,1.,1.] |
| 381 |
|
| 382 |
|
| 383 |
sp=StokesProblemCartesian(self.domain) |
| 384 |
|
| 385 |
sp.initialize(f=F,fixed_u_mask=mask,eta=ETA) |
| 386 |
u0=(1-x[0])*x[0]*(1-x[1])*x[1]*[0.,0.,1.] |
| 387 |
p0=Scalar(-P1,ReducedSolution(self.domain)) |
| 388 |
sp.setTolerance(self.TOL) |
| 389 |
u,p=sp.solve(u0,p0, verbose=VERBOSE ,max_iter=100,usePCG=False) |
| 390 |
|
| 391 |
error_v0=Lsup(u[0]-u0[0]) |
| 392 |
error_v1=Lsup(u[1]-u0[1]) |
| 393 |
error_v2=Lsup(u[2]-u0[2])/0.25**2 |
| 394 |
error_p=Lsup(P1*x[0]*x[1]*x[2]+p)/P1 |
| 395 |
self.failUnless(error_p<10*self.TOL, "pressure error too large.") |
| 396 |
self.failUnless(error_v0<10*self.TOL, "0-velocity error too large.") |
| 397 |
self.failUnless(error_v1<10*self.TOL, "1-velocity error too large.") |
| 398 |
self.failUnless(error_v2<10*self.TOL, "2-velocity error too large.") |
| 399 |
#==================================================================================================================== |
| 400 |
class Test_Darcy(unittest.TestCase): |
| 401 |
# this is a simple test for the darcy flux problem |
| 402 |
# |
| 403 |
# |
| 404 |
# p = 1/k * ( 1/2* (fb-f0)/xb* x **2 + f0 * x - ub*x ) + p0 |
| 405 |
# |
| 406 |
# with f = (fb-f0)/xb* x + f0 |
| 407 |
# |
| 408 |
# u = f - k * p,x = ub |
| 409 |
# |
| 410 |
# we prescribe pressure at x=x0=0 to p0 |
| 411 |
# |
| 412 |
# if we prescribe the pressure on the bottom x=xb we set |
| 413 |
# |
| 414 |
# pb= 1/k * ( 1/2* (fb-f0)* xb + f0 * xb - ub*xb ) + p0 = 1/k * ((fb+f0)/2 - ub ) * xb + p0 |
| 415 |
# |
| 416 |
# which leads to ub = (fb+f0)/2-k*(pb-p0)/xb |
| 417 |
# |
| 418 |
def rescaleDomain(self): |
| 419 |
x=self.dom.getX().copy() |
| 420 |
for i in xrange(self.dom.getDim()): |
| 421 |
x_inf=inf(x[i]) |
| 422 |
x_sup=sup(x[i]) |
| 423 |
if i == self.dom.getDim()-1: |
| 424 |
x[i]=-self.WIDTH*(x[i]-x_sup)/(x_inf-x_sup) |
| 425 |
else: |
| 426 |
x[i]=self.WIDTH*(x[i]-x_inf)/(x_sup-x_inf) |
| 427 |
self.dom.setX(x) |
| 428 |
def getScalarMask(self,include_bottom=True): |
| 429 |
x=self.dom.getX().copy() |
| 430 |
x_inf=inf(x[self.dom.getDim()-1]) |
| 431 |
x_sup=sup(x[self.dom.getDim()-1]) |
| 432 |
out=whereZero(x[self.dom.getDim()-1]-x_sup) |
| 433 |
if include_bottom: out+=whereZero(x[self.dom.getDim()-1]-x_inf) |
| 434 |
return wherePositive(out) |
| 435 |
def getVectorMask(self,include_bottom=True): |
| 436 |
x=self.dom.getX().copy() |
| 437 |
out=Vector(0.,Solution(self.dom)) |
| 438 |
for i in xrange(self.dom.getDim()): |
| 439 |
x_inf=inf(x[i]) |
| 440 |
x_sup=sup(x[i]) |
| 441 |
if i != self.dom.getDim()-1: out[i]+=whereZero(x[i]-x_sup) |
| 442 |
if i != self.dom.getDim()-1 or include_bottom: out[i]+=whereZero(x[i]-x_inf) |
| 443 |
return wherePositive(out) |
| 444 |
|
| 445 |
def setSolutionFixedBottom(self, p0, pb, f0, fb, k): |
| 446 |
d=self.dom.getDim() |
| 447 |
x=self.dom.getX()[d-1] |
| 448 |
xb=inf(x) |
| 449 |
u=Vector(0.,Solution(self.dom))+kronecker(d)[d-1]*((f0+fb)/2.-k*(pb-p0)/xb) |
| 450 |
p=1./k*((fb-f0)/(xb*2.)* x**2 - (fb-f0)/2.*x)+(pb-p0)/xb*x + p0 |
| 451 |
f= ((fb-f0)/xb* x + f0)*kronecker(Function(self.dom))[d-1] |
| 452 |
return u,p,f |
| 453 |
|
| 454 |
def testConstF_FixedBottom_smallK(self): |
| 455 |
k=1.e-10 |
| 456 |
mp=self.getScalarMask(include_bottom=True) |
| 457 |
mv=self.getVectorMask(include_bottom=False) |
| 458 |
u_ref,p_ref,f=self.setSolutionFixedBottom(p0=2500,pb=4000.,f0=10.,fb=10.,k=k) |
| 459 |
p=p_ref*mp |
| 460 |
u=u_ref*mv |
| 461 |
df=DarcyFlow(self.dom) |
| 462 |
df.setValue(g=f, |
| 463 |
location_of_fixed_pressure=mp, |
| 464 |
location_of_fixed_flux=mv, |
| 465 |
permeability=Scalar(k,Function(self.dom))) |
| 466 |
df.setTolerance(rtol=self.TOL) |
| 467 |
v,p=df.solve(u_ref,p, max_iter=100, verbose=VERBOSE) |
| 468 |
self.failUnless(Lsup(v-u_ref)<self.TOL*10.*Lsup(u_ref), "flux error too big.") |
| 469 |
self.failUnless(Lsup(p-p_ref)<self.TOL*10.*Lsup(p_ref), "pressure error too big.") |
| 470 |
def testConstF_FixedBottom_mediumK(self): |
| 471 |
k=1. |
| 472 |
mp=self.getScalarMask(include_bottom=True) |
| 473 |
mv=self.getVectorMask(include_bottom=False) |
| 474 |
u_ref,p_ref,f=self.setSolutionFixedBottom(p0=2500,pb=4000.,f0=10.,fb=10.,k=k) |
| 475 |
p=p_ref*mp |
| 476 |
u=u_ref*mv |
| 477 |
df=DarcyFlow(self.dom) |
| 478 |
df.setValue(g=f, |
| 479 |
location_of_fixed_pressure=mp, |
| 480 |
location_of_fixed_flux=mv, |
| 481 |
permeability=Scalar(k,Function(self.dom))) |
| 482 |
df.setTolerance(rtol=self.TOL) |
| 483 |
v,p=df.solve(u,p,max_iter=100, verbose=VERBOSE ) |
| 484 |
self.failUnless(Lsup(p-p_ref)<self.TOL*10.*Lsup(p_ref), "pressure error too big.") |
| 485 |
self.failUnless(Lsup(v-u_ref)<self.TOL*10.*Lsup(u_ref), "flux error too big.") |
| 486 |
|
| 487 |
def testConstF_FixedBottom_largeK(self): |
| 488 |
k=1.e10 |
| 489 |
mp=self.getScalarMask(include_bottom=True) |
| 490 |
mv=self.getVectorMask(include_bottom=False) |
| 491 |
u_ref,p_ref,f=self.setSolutionFixedBottom(p0=2500,pb=4000.,f0=10.,fb=10.,k=k) |
| 492 |
p=p_ref*mp |
| 493 |
u=u_ref*mv |
| 494 |
df=DarcyFlow(self.dom) |
| 495 |
df.setValue(g=f, |
| 496 |
location_of_fixed_pressure=mp, |
| 497 |
location_of_fixed_flux=mv, |
| 498 |
permeability=Scalar(k,Function(self.dom))) |
| 499 |
df.setTolerance(rtol=self.TOL) |
| 500 |
v,p=df.solve(u,p, max_iter=100, verbose=VERBOSE) |
| 501 |
self.failUnless(Lsup(v-u_ref)<self.TOL*10.*Lsup(u_ref), "flux error too big.") |
| 502 |
self.failUnless(Lsup(p-p_ref)<self.TOL*10.*Lsup(p_ref), "pressure error too big.") |
| 503 |
|
| 504 |
def testVarioF_FixedBottom_smallK(self): |
| 505 |
k=1.e-10 |
| 506 |
mp=self.getScalarMask(include_bottom=True) |
| 507 |
mv=self.getVectorMask(include_bottom=False) |
| 508 |
u_ref,p_ref,f=self.setSolutionFixedBottom(p0=2500,pb=4000.,f0=10.,fb=30.,k=k) |
| 509 |
p=p_ref*mp |
| 510 |
u=u_ref*mv |
| 511 |
df=DarcyFlow(self.dom) |
| 512 |
df.setValue(g=f, |
| 513 |
location_of_fixed_pressure=mp, |
| 514 |
location_of_fixed_flux=mv, |
| 515 |
permeability=Scalar(k,Function(self.dom))) |
| 516 |
df.setTolerance(rtol=self.TOL) |
| 517 |
v,p=df.solve(u,p, max_iter=100, verbose=VERBOSE) |
| 518 |
self.failUnless(Lsup(v-u_ref)<self.TOL*10.*Lsup(u_ref), "flux error too big.") |
| 519 |
self.failUnless(Lsup(p-p_ref)<self.TOL*10.*Lsup(p_ref), "pressure error too big.") |
| 520 |
|
| 521 |
def testVarioF_FixedBottom_mediumK(self): |
| 522 |
k=1. |
| 523 |
mp=self.getScalarMask(include_bottom=True) |
| 524 |
mv=self.getVectorMask(include_bottom=False) |
| 525 |
u_ref,p_ref,f=self.setSolutionFixedBottom(p0=2500,pb=4000.,f0=10.,fb=30.,k=k) |
| 526 |
p=p_ref*mp |
| 527 |
u=u_ref*mv |
| 528 |
df=DarcyFlow(self.dom) |
| 529 |
df.setValue(g=f, |
| 530 |
location_of_fixed_pressure=mp, |
| 531 |
location_of_fixed_flux=mv, |
| 532 |
permeability=Scalar(k,Function(self.dom))) |
| 533 |
df.setTolerance(rtol=self.TOL) |
| 534 |
v,p=df.solve(u,p, max_iter=100, verbose=VERBOSE) |
| 535 |
self.failUnless(Lsup(v-u_ref)<self.TOL*10.*Lsup(u_ref), "flux error too big.") |
| 536 |
self.failUnless(Lsup(p-p_ref)<self.TOL*10.*Lsup(p_ref), "pressure error too big.") |
| 537 |
|
| 538 |
def testVarioF_FixedBottom_largeK(self): |
| 539 |
k=1.e10 |
| 540 |
mp=self.getScalarMask(include_bottom=True) |
| 541 |
mv=self.getVectorMask(include_bottom=False) |
| 542 |
u_ref,p_ref,f=self.setSolutionFixedBottom(p0=2500,pb=4000.,f0=10.,fb=30.,k=k) |
| 543 |
p=p_ref*mp |
| 544 |
u=u_ref*mv |
| 545 |
df=DarcyFlow(self.dom) |
| 546 |
df.setValue(g=f, |
| 547 |
location_of_fixed_pressure=mp, |
| 548 |
location_of_fixed_flux=mv, |
| 549 |
permeability=Scalar(k,Function(self.dom))) |
| 550 |
df.setTolerance(rtol=self.TOL) |
| 551 |
v,p=df.solve(u,p, max_iter=100, verbose=VERBOSE) |
| 552 |
self.failUnless(Lsup(v-u_ref)<self.TOL*10.*Lsup(u_ref), "flux error too big.") |
| 553 |
self.failUnless(Lsup(p-p_ref)<self.TOL*10.*Lsup(p_ref), "pressure error too big.") |
| 554 |
|
| 555 |
def testConstF_FreeBottom_smallK(self): |
| 556 |
k=1.e-10 |
| 557 |
mp=self.getScalarMask(include_bottom=False) |
| 558 |
mv=self.getVectorMask(include_bottom=True) |
| 559 |
u_ref,p_ref,f=self.setSolutionFixedBottom(p0=2500,pb=4000.,f0=10.,fb=10.,k=k) |
| 560 |
p=p_ref*mp |
| 561 |
u=u_ref*mv |
| 562 |
df=DarcyFlow(self.dom) |
| 563 |
df.setValue(g=f, |
| 564 |
location_of_fixed_pressure=mp, |
| 565 |
location_of_fixed_flux=mv, |
| 566 |
permeability=Scalar(k,Function(self.dom))) |
| 567 |
df.setTolerance(rtol=self.TOL) |
| 568 |
v,p=df.solve(u,p, max_iter=100, verbose=VERBOSE) |
| 569 |
self.failUnless(Lsup(v-u_ref)<self.TOL*10.*Lsup(u_ref), "flux error too big.") |
| 570 |
self.failUnless(Lsup(p-p_ref)<self.TOL*10.*Lsup(p_ref), "pressure error too big.") |
| 571 |
|
| 572 |
def testConstF_FreeBottom_mediumK(self): |
| 573 |
k=1. |
| 574 |
mp=self.getScalarMask(include_bottom=False) |
| 575 |
mv=self.getVectorMask(include_bottom=True) |
| 576 |
u_ref,p_ref,f=self.setSolutionFixedBottom(p0=2500,pb=4000.,f0=10.,fb=10.,k=k) |
| 577 |
p=p_ref*mp |
| 578 |
u=u_ref*mv |
| 579 |
df=DarcyFlow(self.dom) |
| 580 |
df.setValue(g=f, |
| 581 |
location_of_fixed_pressure=mp, |
| 582 |
location_of_fixed_flux=mv, |
| 583 |
permeability=Scalar(k,Function(self.dom))) |
| 584 |
df.setTolerance(rtol=self.TOL) |
| 585 |
v,p=df.solve(u,p, max_iter=100, verbose=VERBOSE) |
| 586 |
self.failUnless(Lsup(v-u_ref)<self.TOL*10.*Lsup(u_ref), "flux error too big.") |
| 587 |
self.failUnless(Lsup(p-p_ref)<self.TOL*10.*Lsup(p_ref), "pressure error too big.") |
| 588 |
|
| 589 |
def testConstF_FreeBottom_largeK(self): |
| 590 |
k=1.e10 |
| 591 |
mp=self.getScalarMask(include_bottom=False) |
| 592 |
mv=self.getVectorMask(include_bottom=True) |
| 593 |
u_ref,p_ref,f=self.setSolutionFixedBottom(p0=2500,pb=4000.,f0=10.,fb=10.,k=k) |
| 594 |
p=p_ref*mp |
| 595 |
u=u_ref*mv |
| 596 |
df=DarcyFlow(self.dom) |
| 597 |
df.setValue(g=f, |
| 598 |
location_of_fixed_pressure=mp, |
| 599 |
location_of_fixed_flux=mv, |
| 600 |
permeability=Scalar(k,Function(self.dom))) |
| 601 |
df.setTolerance(rtol=self.TOL) |
| 602 |
v,p=df.solve(u,p, max_iter=100, verbose=VERBOSE) |
| 603 |
self.failUnless(Lsup(v-u_ref)<self.TOL*10.*Lsup(u_ref), "flux error too big.") |
| 604 |
self.failUnless(Lsup(p-p_ref)<self.TOL*10.*Lsup(p_ref), "pressure error too big.") |
| 605 |
|
| 606 |
def testVarioF_FreeBottom_smallK(self): |
| 607 |
k=1.e-10 |
| 608 |
mp=self.getScalarMask(include_bottom=False) |
| 609 |
mv=self.getVectorMask(include_bottom=True) |
| 610 |
u_ref,p_ref,f=self.setSolutionFixedBottom(p0=2500,pb=4000.,f0=10.,fb=30.,k=k) |
| 611 |
p=p_ref*mp |
| 612 |
u=u_ref*mv |
| 613 |
df=DarcyFlow(self.dom) |
| 614 |
df.setValue(g=f, |
| 615 |
location_of_fixed_pressure=mp, |
| 616 |
location_of_fixed_flux=mv, |
| 617 |
permeability=Scalar(k,Function(self.dom))) |
| 618 |
df.setTolerance(rtol=self.TOL) |
| 619 |
v,p=df.solve(u,p, max_iter=100, verbose=VERBOSE) |
| 620 |
self.failUnless(Lsup(v-u_ref)<self.TOL*25.*Lsup(u_ref), "flux error too big.") # 25 because of disc. error. |
| 621 |
self.failUnless(Lsup(p-p_ref)<self.TOL*25.*Lsup(p_ref), "pressure error too big.") |
| 622 |
|
| 623 |
def testVarioF_FreeBottom_mediumK(self): |
| 624 |
k=1. |
| 625 |
mp=self.getScalarMask(include_bottom=False) |
| 626 |
mv=self.getVectorMask(include_bottom=True) |
| 627 |
u_ref,p_ref,f=self.setSolutionFixedBottom(p0=2500,pb=4000.,f0=10.,fb=30.,k=k) |
| 628 |
p=p_ref*mp |
| 629 |
u=u_ref*mv |
| 630 |
df=DarcyFlow(self.dom) |
| 631 |
df.setValue(g=f, |
| 632 |
location_of_fixed_pressure=mp, |
| 633 |
location_of_fixed_flux=mv, |
| 634 |
permeability=Scalar(k,Function(self.dom))) |
| 635 |
df.setTolerance(rtol=self.TOL) |
| 636 |
v,p=df.solve(u,p, max_iter=100, verbose=VERBOSE) |
| 637 |
self.failUnless(Lsup(v-u_ref)<self.TOL*10.*Lsup(u_ref), "flux error too big.") |
| 638 |
self.failUnless(Lsup(p-p_ref)<self.TOL*10.*Lsup(p_ref), "pressure error too big.") |
| 639 |
|
| 640 |
def testVarioF_FreeBottom_largeK(self): |
| 641 |
k=1.e10 |
| 642 |
mp=self.getScalarMask(include_bottom=False) |
| 643 |
mv=self.getVectorMask(include_bottom=True) |
| 644 |
u_ref,p_ref,f=self.setSolutionFixedBottom(p0=2500,pb=4000.,f0=10.,fb=30.,k=k) |
| 645 |
p=p_ref*mp |
| 646 |
u=u_ref*mv |
| 647 |
df=DarcyFlow(self.dom) |
| 648 |
df.setValue(g=f, |
| 649 |
location_of_fixed_pressure=mp, |
| 650 |
location_of_fixed_flux=mv, |
| 651 |
permeability=Scalar(k,Function(self.dom))) |
| 652 |
df.setTolerance(rtol=self.TOL) |
| 653 |
v,p=df.solve(u,p, max_iter=100, verbose=VERBOSE) |
| 654 |
self.failUnless(Lsup(v-u_ref)<self.TOL*10.*Lsup(u_ref), "flux error too big.") |
| 655 |
self.failUnless(Lsup(p-p_ref)<self.TOL*10.*Lsup(p_ref), "pressure error too big.") |
| 656 |
|
| 657 |
class Test_Darcy2D(Test_Darcy): |
| 658 |
TOL=1e-4 |
| 659 |
WIDTH=1. |
| 660 |
def setUp(self): |
| 661 |
NE=40 # wrning smaller NE may case a failure for VarioF tests due to discretization errors. |
| 662 |
self.dom = Rectangle(NE,NE) |
| 663 |
self.rescaleDomain() |
| 664 |
def tearDown(self): |
| 665 |
del self.dom |
| 666 |
class Test_Darcy3D(Test_Darcy): |
| 667 |
TOL=1e-4 |
| 668 |
WIDTH=1. |
| 669 |
def setUp(self): |
| 670 |
NE=25 # wrning smaller NE may case a failure for VarioF tests due to discretization errors. |
| 671 |
self.dom = Brick(NE,NE,NE) |
| 672 |
self.rescaleDomain() |
| 673 |
def tearDown(self): |
| 674 |
del self.dom |
| 675 |
|
| 676 |
|
| 677 |
class Test_Mountains3D(unittest.TestCase): |
| 678 |
def setUp(self): |
| 679 |
NE=16 |
| 680 |
self.TOL=1e-4 |
| 681 |
self.domain=Brick(NE,NE,NE,order=1,useFullElementOrder=True) |
| 682 |
def tearDown(self): |
| 683 |
del self.domain |
| 684 |
def test_periodic(self): |
| 685 |
EPS=0.01 |
| 686 |
|
| 687 |
x=self.domain.getX() |
| 688 |
v = Vector(0.0, Solution(self.domain)) |
| 689 |
a0=1 |
| 690 |
a1=1 |
| 691 |
n0=2 |
| 692 |
n1=2 |
| 693 |
n2=0.5 |
| 694 |
a2=-(a0*n0+a1*n1)/n2 |
| 695 |
v[0]=a0*sin(pi*n0*x[0])* cos(pi*n1*x[1])* cos(pi*n2*x[2]) |
| 696 |
v[1]=a1*cos(pi*n0*x[0])* sin(pi*n1*x[1])* cos(pi*n2*x[2]) |
| 697 |
v[2]=a2*cos(pi*n0*x[0])* cos(pi*n1*x[1])* sin(pi*n2*x[2]) |
| 698 |
|
| 699 |
mts=Mountains(self.domain,eps=EPS) |
| 700 |
mts.setVelocity(v) |
| 701 |
Z=mts.update() |
| 702 |
|
| 703 |
error_int=integrate(Z) |
| 704 |
self.failUnless(error_int<self.TOL, "Boundary intergral is too large.") |
| 705 |
|
| 706 |
class Test_Mountains2D(unittest.TestCase): |
| 707 |
def setUp(self): |
| 708 |
NE=16 |
| 709 |
self.TOL=1e-4 |
| 710 |
self.domain=Rectangle(NE,NE,order=1,useFullElementOrder=True) |
| 711 |
def tearDown(self): |
| 712 |
del self.domain |
| 713 |
def test_periodic(self): |
| 714 |
EPS=0.01 |
| 715 |
|
| 716 |
x=self.domain.getX() |
| 717 |
v = Vector(0.0, Solution(self.domain)) |
| 718 |
a0=1 |
| 719 |
n0=1 |
| 720 |
n1=0.5 |
| 721 |
a1=-(a0*n0)/n1 |
| 722 |
v[0]=a0*sin(pi*n0*x[0])* cos(pi*n1*x[1]) |
| 723 |
v[1]=a1*cos(pi*n0*x[0])* sin(pi*n1*x[1]) |
| 724 |
|
| 725 |
H_t=Scalar(0.0, Solution(self.domain)) |
| 726 |
mts=Mountains(self.domain,eps=EPS) |
| 727 |
mts.setVelocity(v) |
| 728 |
Z=mts.update() |
| 729 |
|
| 730 |
error_int=integrate(Z) |
| 731 |
self.failUnless(error_int<self.TOL, "Boundary intergral is too large.") |
| 732 |
|
| 733 |
|
| 734 |
|
| 735 |
class Test_Rheologies(unittest.TestCase): |
| 736 |
""" |
| 737 |
this is the program used to generate the powerlaw tests: |
| 738 |
|
| 739 |
TAU_Y=100. |
| 740 |
N=10 |
| 741 |
M=5 |
| 742 |
|
| 743 |
def getE(tau): |
| 744 |
if tau<=TAU_Y: |
| 745 |
return 1./(0.5+20*sqrt(tau)) |
| 746 |
else: |
| 747 |
raise ValueError,"out of range." |
| 748 |
tau=[ i* (TAU_Y/N) for i in range(N+1)] + [TAU_Y for i in range(M)] |
| 749 |
e=[ tau[i]/getE(tau[i]) for i in range(N+1)] |
| 750 |
e+= [ (i+1+j)* (max(e)/N) for j in range(M) ] |
| 751 |
|
| 752 |
print tau |
| 753 |
print e |
| 754 |
""" |
| 755 |
TOL=1.e-8 |
| 756 |
def test_PowerLaw_Init(self): |
| 757 |
pl=PowerLaw(numMaterials=3,verbose=VERBOSE) |
| 758 |
|
| 759 |
self.failUnlessEqual(pl.getNumMaterials(),3,"num materials is wrong") |
| 760 |
self.failUnlessEqual(pl.validMaterialId(0),True,"material id 0 not found") |
| 761 |
self.failUnlessEqual(pl.validMaterialId(1),True,"material id 1 not found") |
| 762 |
self.failUnlessEqual(pl.validMaterialId(2),True,"material id 2 not found") |
| 763 |
self.failUnlessEqual(pl.validMaterialId(3),False,"material id 3 not found") |
| 764 |
|
| 765 |
self.failUnlessEqual(pl.getFriction(),None,"initial friction wrong.") |
| 766 |
self.failUnlessEqual(pl.getTauY(),None,"initial tau y wrong.") |
| 767 |
pl.setDruckerPragerLaw(tau_Y=10,friction=3) |
| 768 |
self.failUnlessEqual(pl.getFriction(),3,"friction wrong.") |
| 769 |
self.failUnlessEqual(pl.getTauY(),10,"tau y wrong.") |
| 770 |
|
| 771 |
self.failUnlessEqual(pl.getElasticShearModulus(),None,"initial shear modulus is wrong") |
| 772 |
pl.setElasticShearModulus(1000) |
| 773 |
self.failUnlessEqual(pl.getElasticShearModulus(),1000.,"shear modulus is wrong") |
| 774 |
|
| 775 |
e=pl.getEtaN() |
| 776 |
self.failUnlessEqual(len(e),3,"initial length of etaN is wrong.") |
| 777 |
self.failUnlessEqual(e,[None, None, None],"initial etaN are wrong.") |
| 778 |
self.failUnlessEqual(pl.getEtaN(0),None,"initial material id 0 is wrong") |
| 779 |
self.failUnlessEqual(pl.getEtaN(1),None,"initial material id 1 is wrong") |
| 780 |
self.failUnlessEqual(pl.getEtaN(2),None,"initial material id 2 is wrong") |
| 781 |
self.failUnlessRaises(ValueError, pl.getEtaN, 3) |
| 782 |
|
| 783 |
self.failUnlessRaises(ValueError,pl.setPowerLaws,eta_N=[10,20,30,40],tau_t=[2], power=[5,6,7]) |
| 784 |
self.failUnlessRaises(ValueError,pl.setPowerLaws,eta_N=[10,20,30],tau_t=[2,4,5,5], power=[5,6,7]) |
| 785 |
self.failUnlessRaises(ValueError,pl.setPowerLaws,eta_N=[10,20,30],tau_t=[2,1,2], power=[5,6,7,7]) |
| 786 |
|
| 787 |
pl.setPowerLaws(eta_N=[10,20,30],tau_t=[100,200,300], power=[1,2,3]) |
| 788 |
self.failUnlessEqual(pl.getPower(),[1,2,3],"powers are wrong.") |
| 789 |
self.failUnlessEqual(pl.getTauT(),[100,200,300],"tau t are wrong.") |
| 790 |
self.failUnlessEqual(pl.getEtaN(),[10,20,30],"etaN are wrong.") |
| 791 |
|
| 792 |
pl.setPowerLaw(id=0,eta_N=40,tau_t=400, power=4) |
| 793 |
self.failUnlessEqual(pl.getPower(),[4,2,3],"powers are wrong.") |
| 794 |
self.failUnlessEqual(pl.getTauT(),[400,200,300],"tau t are wrong.") |
| 795 |
self.failUnlessEqual(pl.getEtaN(),[40,20,30],"etaN are wrong.") |
| 796 |
|
| 797 |
self.failUnlessRaises(ValueError,pl.getPower,-1) |
| 798 |
self.failUnlessEqual(pl.getPower(0),4,"power 0 is wrong.") |
| 799 |
self.failUnlessEqual(pl.getPower(1),2,"power 1 is wrong.") |
| 800 |
self.failUnlessEqual(pl.getPower(2),3,"power 2 is wrong.") |
| 801 |
self.failUnlessRaises(ValueError,pl.getPower,3) |
| 802 |
|
| 803 |
self.failUnlessRaises(ValueError,pl.getTauT,-1) |
| 804 |
self.failUnlessEqual(pl.getTauT(0),400,"tau t 0 is wrong.") |
| 805 |
self.failUnlessEqual(pl.getTauT(1),200,"tau t 1 is wrong.") |
| 806 |
self.failUnlessEqual(pl.getTauT(2),300,"tau t 2 is wrong.") |
| 807 |
self.failUnlessRaises(ValueError,pl.getTauT,3) |
| 808 |
|
| 809 |
self.failUnlessRaises(ValueError,pl.getEtaN,-1) |
| 810 |
self.failUnlessEqual(pl.getEtaN(0),40,"eta n 0 is wrong.") |
| 811 |
self.failUnlessEqual(pl.getEtaN(1),20,"eta n 1 is wrong.") |
| 812 |
self.failUnlessEqual(pl.getEtaN(2),30,"eta n 2 is wrong.") |
| 813 |
self.failUnlessRaises(ValueError,pl.getEtaN,3) |
| 814 |
|
| 815 |
def checkResult(self,id,gamma_dot_, eta, tau_ref): |
| 816 |
self.failUnless(eta>=0,"eta needs to be positive (test %s)"%id) |
| 817 |
error=abs(gamma_dot_*eta-tau_ref) |
| 818 |
self.failUnless(error<=self.TOL*tau_ref,"eta is wrong: error = gamma_dot_*eta-tau_ref = %s * %s - %s = %s (test %s)"%(gamma_dot_,eta,tau_ref,error,id)) |
| 819 |
|
| 820 |
def test_PowerLaw_Linear(self): |
| 821 |
taus= [0.0, 10.0, 20.0, 30.0, 40.0, 50.0, 60.0, 70.0, 80.0, 90.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0] |
| 822 |
gamma_dot_s=[0.0, 5.0, 10.0, 15.0, 20.0, 25.0, 30.0, 35.0, 40.0, 45.0, 50.0, 55.0, 60.0, 65.0, 70.0, 75.0] |
| 823 |
pl=PowerLaw(numMaterials=1,verbose=VERBOSE) |
| 824 |
pl.setDruckerPragerLaw(tau_Y=100.) |
| 825 |
pl.setPowerLaw(eta_N=2.) |
| 826 |
pl.setEtaTolerance(self.TOL) |
| 827 |
for i in xrange(len(taus)): self.checkResult(i,gamma_dot_s[i], pl.getEtaEff(gamma_dot_s[i]),taus[i]) |
| 828 |
|
| 829 |
def test_PowerLaw_QuadLarge(self): |
| 830 |
taus=[0.0, 10.0, 20.0, 30.0, 40.0, 50.0, 60.0, 70.0, 80.0, 90.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0] |
| 831 |
gamma_dot_s=[0.0, 405.0, 1610.0, 3615.0, 6420.0, 10025.0, 14430.0, 19635.0, 25640.0, 32445.0, 40050.0, 44055.0, 48060.0, 52065.0, 56070.0, 60075.0] |
| 832 |
pl=PowerLaw(numMaterials=2,verbose=VERBOSE) |
| 833 |
pl.setDruckerPragerLaw(tau_Y=100.) |
| 834 |
pl.setPowerLaws(eta_N=[2.,0.01],tau_t=[1, 25.], power=[1,2]) |
| 835 |
pl.setEtaTolerance(self.TOL) |
| 836 |
for i in xrange(len(taus)): self.checkResult(i,gamma_dot_s[i], pl.getEtaEff(gamma_dot_s[i]),taus[i]) |
| 837 |
|
| 838 |
def test_PowerLaw_QuadSmall(self): |
| 839 |
taus=[0.0, 10.0, 20.0, 30.0, 40.0, 50.0, 60.0, 70.0, 80.0, 90.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0] |
| 840 |
gamma_dot_s=[0.0, 5.4, 11.6, 18.6, 26.4, 35.0, 44.4, 54.6, 65.6, 77.4, 90.0, 99.0, 108.0, 117.0, 126.0, 135.0] |
| 841 |
pl=PowerLaw(numMaterials=2,verbose=VERBOSE) |
| 842 |
pl.setDruckerPragerLaw(tau_Y=100.) |
| 843 |
pl.setPowerLaws(eta_N=[2.,10.],tau_t=[1, 25.], power=[1,2]) |
| 844 |
pl.setEtaTolerance(self.TOL) |
| 845 |
for i in xrange(len(taus)): self.checkResult(i,gamma_dot_s[i], pl.getEtaEff(gamma_dot_s[i]),taus[i]) |
| 846 |
|
| 847 |
def test_PowerLaw_CubeLarge(self): |
| 848 |
taus=[0.0, 10.0, 20.0, 30.0, 40.0, 50.0, 60.0, 70.0, 80.0, 90.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0] |
| 849 |
gamma_dot_s=[0.0, 8.90625, 41.25, 120.46875, 270.0, 513.28125, 873.75, 1374.84375, 2040.0, 2892.65625, 3956.25, 4351.875, 4747.5, 5143.125, 5538.75, 5934.375] |
| 850 |
pl=PowerLaw(numMaterials=2,verbose=VERBOSE) |
| 851 |
pl.setDruckerPragerLaw(tau_Y=100.) |
| 852 |
pl.setPowerLaws(eta_N=[2.,1./16.],tau_t=[1, 64.], power=[1,3]) |
| 853 |
pl.setEtaTolerance(self.TOL) |
| 854 |
for i in xrange(len(taus)): self.checkResult(i,gamma_dot_s[i], pl.getEtaEff(gamma_dot_s[i]),taus[i]) |
| 855 |
|
| 856 |
def test_PowerLaw_CubeSmall(self): |
| 857 |
taus=[0.0, 10.0, 20.0, 30.0, 40.0, 50.0, 60.0, 70.0, 80.0, 90.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0] |
| 858 |
gamma_dot_s=[0.0, 5.0390625, 10.3125, 16.0546875, 22.5, 29.8828125, 38.4375, 48.3984375, 60.0, 73.4765625, 89.0625, 97.96875, 106.875, 115.78125, 124.6875, 133.59375] |
| 859 |
pl=PowerLaw(numMaterials=2,verbose=VERBOSE) |
| 860 |
pl.setDruckerPragerLaw(tau_Y=100.) |
| 861 |
pl.setPowerLaws(eta_N=[2.,25./4.],tau_t=[1, 64.], power=[1,3]) |
| 862 |
pl.setEtaTolerance(self.TOL) |
| 863 |
for i in xrange(len(taus)): self.checkResult(i,gamma_dot_s[i], pl.getEtaEff(gamma_dot_s[i]),taus[i]) |
| 864 |
|
| 865 |
def test_PowerLaw_QuadLarge_CubeLarge(self): |
| 866 |
taus=[0.0, 10.0, 20.0, 30.0, 40.0, 50.0, 60.0, 70.0, 80.0, 90.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0] |
| 867 |
gamma_dot_s=[0.0, 408.90625, 1641.25, 3720.46875, 6670.0, 10513.28125, 15273.75, 20974.84375, 27640.000000000004, 35292.65625, 43956.25, 48351.875, 52747.5, 57143.125, 61538.75, 65934.375] |
| 868 |
|
| 869 |
pl=PowerLaw(numMaterials=3,verbose=VERBOSE) |
| 870 |
pl.setDruckerPragerLaw(tau_Y=100.) |
| 871 |
pl.setPowerLaws(eta_N=[2.,0.01,1./16.],tau_t=[1, 25.,64.], power=[1,2,3]) |
| 872 |
pl.setEtaTolerance(self.TOL) |
| 873 |
for i in xrange(len(taus)): self.checkResult(i,gamma_dot_s[i], pl.getEtaEff(gamma_dot_s[i]),taus[i]) |
| 874 |
|
| 875 |
def test_PowerLaw_QuadLarge_CubeSmall(self): |
| 876 |
taus=[0.0, 10.0, 20.0, 30.0, 40.0, 50.0, 60.0, 70.0, 80.0, 90.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0] |
| 877 |
gamma_dot_s=[0.0, 405.0390625, 1610.3125, 3616.0546875, 6422.5, 10029.8828125, 14438.4375, 19648.3984375, 25660.0, 32473.4765625, 40089.0625, 44097.96875, 48106.875, 52115.78125, 56124.6875, 60133.59375] |
| 878 |
|
| 879 |
pl=PowerLaw(numMaterials=3,verbose=VERBOSE) |
| 880 |
pl.setDruckerPragerLaw(tau_Y=100.) |
| 881 |
pl.setPowerLaws(eta_N=[2.,0.01,25./4.],tau_t=[1, 25.,64.], power=[1,2,3]) |
| 882 |
pl.setEtaTolerance(self.TOL) |
| 883 |
for i in xrange(len(taus)): self.checkResult(i,gamma_dot_s[i], pl.getEtaEff(gamma_dot_s[i]),taus[i]) |
| 884 |
|
| 885 |
def test_PowerLaw_QuadSmall_CubeLarge(self): |
| 886 |
taus=[0.0, 10.0, 20.0, 30.0, 40.0, 50.0, 60.0, 70.0, 80.0, 90.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0] |
| 887 |
gamma_dot_s=[0.0, 9.30625, 42.85, 124.06875, 276.4, 523.28125, 888.15, 1394.44375, 2065.6, 2925.05625, 3996.25, 4395.875, 4795.5, 5195.125, 5594.75, 5994.375] |
| 888 |
pl=PowerLaw(numMaterials=3,verbose=VERBOSE) |
| 889 |
pl.setDruckerPragerLaw(tau_Y=100.) |
| 890 |
pl.setPowerLaws(eta_N=[2.,10.,1./16.],tau_t=[1, 25.,64.], power=[1,2,3]) |
| 891 |
pl.setEtaTolerance(self.TOL) |
| 892 |
for i in xrange(len(taus)): self.checkResult(i,gamma_dot_s[i], pl.getEtaEff(gamma_dot_s[i]),taus[i]) |
| 893 |
|
| 894 |
def test_PowerLaw_QuadSmall_CubeSmall(self): |
| 895 |
taus=[0.0, 10.0, 20.0, 30.0, 40.0, 50.0, 60.0, 70.0, 80.0, 90.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0] |
| 896 |
gamma_dot_s=[0.0, 5.4390625, 11.9125, 19.6546875, 28.9, 39.8828125, 52.8375, 67.9984375, 85.6, 105.8765625, 129.0625, 141.96875, 154.875, 167.78125, 180.6875, 193.59375] |
| 897 |
pl=PowerLaw(numMaterials=3,verbose=VERBOSE) |
| 898 |
pl.setDruckerPragerLaw(tau_Y=100.) |
| 899 |
pl.setPowerLaws(eta_N=[2.,10.,25./4.],tau_t=[1, 25.,64.], power=[1,2,3]) |
| 900 |
pl.setEtaTolerance(self.TOL) |
| 901 |
for i in xrange(len(taus)): self.checkResult(i,gamma_dot_s[i], pl.getEtaEff(gamma_dot_s[i]),taus[i]) |
| 902 |
|
| 903 |
def test_PowerLaw_withShear(self): |
| 904 |
taus=[0.0, 10.0, 20.0, 30.0, 40.0, 50.0, 60.0, 70.0, 80.0, 90.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0] |
| 905 |
gamma_dot_s=[0.0, 15.0, 30.0, 45.0, 60.0, 75.0, 90.0, 105.0, 120.0, 135.0, 150.0, 165.0, 180.0, 195.0, 210.0, 225.0] |
| 906 |
pl=PowerLaw(numMaterials=1,verbose=VERBOSE) |
| 907 |
pl.setDruckerPragerLaw(tau_Y=100.) |
| 908 |
pl.setPowerLaw(eta_N=2.) |
| 909 |
pl.setElasticShearModulus(3.) |
| 910 |
dt=1./3. |
| 911 |
pl.setEtaTolerance(self.TOL) |
| 912 |
self.failUnlessRaises(ValueError, pl.getEtaEff,gamma_dot_s[0]) |
| 913 |
for i in xrange(len(taus)): self.checkResult(i,gamma_dot_s[i], pl.getEtaEff(gamma_dot_s[i],dt=dt),taus[i]) |
| 914 |
|
| 915 |
class Test_IncompressibleIsotropicFlowCartesian(unittest.TestCase): |
| 916 |
TOL=1.e-6 |
| 917 |
VERBOSE=False |
| 918 |
A=1. |
| 919 |
P_max=100 |
| 920 |
NE=2*getMPISizeWorld() |
| 921 |
tau_Y=10. |
| 922 |
N_dt=10 |
| 923 |
|
| 924 |
# material parameter: |
| 925 |
tau_1=5. |
| 926 |
tau_2=5. |
| 927 |
eta_0=100. |
| 928 |
eta_1=50. |
| 929 |
eta_2=400. |
| 930 |
N_1=2. |
| 931 |
N_2=3. |
| 932 |
def getReference(self, t): |
| 933 |
|
| 934 |
B=self.tau_Y/sqrt((self.dom.getDim()-1)*self.dom.getDim()*0.5) |
| 935 |
x=self.dom.getX() |
| 936 |
|
| 937 |
s_00=min(self.A*t,B) |
| 938 |
tau=sqrt((self.dom.getDim()-1)*self.dom.getDim()*0.5)*abs(s_00) |
| 939 |
inv_eta= 1./self.eta_0 + 1./self.eta_1*(tau/self.tau_1)**(self.N_1-1.) + 1./self.eta_2*(tau/self.tau_2)**(self.N_2-1.) |
| 940 |
|
| 941 |
alpha=0.5*inv_eta*s_00 |
| 942 |
if s_00 <= B and self.mu !=None: alpha+=1./(2*self.mu)*self.A |
| 943 |
u_ref=x*alpha |
| 944 |
u_ref[self.dom.getDim()-1]=(1.-x[self.dom.getDim()-1])*alpha*(self.dom.getDim()-1) |
| 945 |
sigma_ref=kronecker(self.dom)*s_00 |
| 946 |
sigma_ref[self.dom.getDim()-1,self.dom.getDim()-1]=-s_00*(self.dom.getDim()-1) |
| 947 |
|
| 948 |
p_ref=self.P_max |
| 949 |
for d in range(self.dom.getDim()): p_ref=p_ref*x[d] |
| 950 |
p_ref-=integrate(p_ref)/vol(self.dom) |
| 951 |
return u_ref, sigma_ref, p_ref |
| 952 |
|
| 953 |
def runIt(self, free=None): |
| 954 |
x=self.dom.getX() |
| 955 |
B=self.tau_Y/sqrt((self.dom.getDim()-1)*self.dom.getDim()*0.5) |
| 956 |
dt=B/int(self.N_dt/2) |
| 957 |
if self.VERBOSE: print "dt =",dt |
| 958 |
if self.latestart: |
| 959 |
t=dt |
| 960 |
else: |
| 961 |
t=0 |
| 962 |
v,s,p=self.getReference(t) |
| 963 |
|
| 964 |
mod=IncompressibleIsotropicFlowCartesian(self.dom, stress=s, v=v, p=p, t=t, numMaterials=3, verbose=self.VERBOSE) |
| 965 |
mod.setDruckerPragerLaw(tau_Y=self.tau_Y,friction=None) |
| 966 |
mod.setElasticShearModulus(self.mu) |
| 967 |
mod.setPowerLaws([self.eta_0, self.eta_1, self.eta_2], [ 1., self.tau_1, self.tau_2], [1.,self.N_1,self.N_2]) |
| 968 |
mod.setTolerance(self.TOL) |
| 969 |
mod.setFlowTolerance(self.TOL) |
| 970 |
|
| 971 |
BF=Vector(self.P_max,Function(self.dom)) |
| 972 |
for d in range(self.dom.getDim()): |
| 973 |
for d2 in range(self.dom.getDim()): |
| 974 |
if d!=d2: BF[d]*=x[d2] |
| 975 |
v_mask=Vector(0,Solution(self.dom)) |
| 976 |
if free==None: |
| 977 |
for d in range(self.dom.getDim()): |
| 978 |
v_mask[d]=whereZero(x[d])+whereZero(x[d]-1.) |
| 979 |
else: |
| 980 |
for d in range(self.dom.getDim()): |
| 981 |
if d == self.dom.getDim()-1: |
| 982 |
v_mask[d]=whereZero(x[d]-1.) |
| 983 |
else: |
| 984 |
v_mask[d]=whereZero(x[d]) |
| 985 |
mod.setExternals(F=BF,fixed_v_mask=v_mask) |
| 986 |
|
| 987 |
n=self.dom.getNormal() |
| 988 |
N_t=0 |
| 989 |
errors=[] |
| 990 |
while N_t < self.N_dt: |
| 991 |
t_ref=t+dt |
| 992 |
v_ref, s_ref,p_ref=self.getReference(t_ref) |
| 993 |
mod.setExternals(f=matrixmult(s_ref,n)-p_ref*n, v_boundary=v_ref) |
| 994 |
mod.update(dt, iter_max=100, inner_iter_max=20, verbose=self.VERBOSE, usePCG=True) |
| 995 |
self.check(N_t,mod,t_ref,v_ref, s_ref,p_ref) |
| 996 |
t+=dt |
| 997 |
N_t+=1 |
| 998 |
|
| 999 |
def check(self,N_t,mod,t_ref,v_ref, s_ref,p_ref): |
| 1000 |
p=mod.getPressure() |
| 1001 |
p-=integrate(p)/vol(self.dom) |
| 1002 |
error_p=Lsup(mod.getPressure()-p_ref)/Lsup(p_ref) |
| 1003 |
error_s=Lsup(mod.getDeviatoricStress()-s_ref)/Lsup(s_ref) |
| 1004 |
error_v=Lsup(mod.getVelocity()-v_ref)/Lsup(v_ref) |
| 1005 |
error_t=abs(mod.getTime()-t_ref)/abs(t_ref) |
| 1006 |
if self.VERBOSE: print "time step ",N_t,"time = ",mod.getTime(),"errors s,p,v = ",error_s, error_p, error_v |
| 1007 |
self.failUnless( error_p <= 10*self.TOL, "time step %s: pressure error %s too high."%(N_t,error_p) ) |
| 1008 |
self.failUnless( error_s <= 10*self.TOL, "time step %s: stress error %s too high."%(N_t,error_s) ) |
| 1009 |
self.failUnless( error_v <= 10*self.TOL, "time step %s: velocity error %s too high."%(N_t,error_v) ) |
| 1010 |
self.failUnless( error_t <= 10*self.TOL, "time step %s: time marker error %s too high."%(N_t,error_t) ) |
| 1011 |
def tearDown(self): |
| 1012 |
del self.dom |
| 1013 |
|
| 1014 |
def test_D2_Fixed_MuNone_LateStart(self): |
| 1015 |
self.dom = Rectangle(self.NE,self.NE,order=2) |
| 1016 |
self.mu=None |
| 1017 |
self.latestart=True |
| 1018 |
self.runIt() |
| 1019 |
def test_D2_Fixed_Mu_LateStart(self): |
| 1020 |
self.dom = Rectangle(self.NE,self.NE,order=2) |
| 1021 |
self.mu=555. |
| 1022 |
self.latestart=True |
| 1023 |
self.runIt() |
| 1024 |
def test_D2_Fixed_MuNone(self): |
| 1025 |
self.dom = Rectangle(self.NE,self.NE,order=2) |
| 1026 |
self.mu=None |
| 1027 |
self.latestart=False |
| 1028 |
self.runIt() |
| 1029 |
def test_D2_Fixed_Mu(self): |
| 1030 |
self.dom = Rectangle(self.NE,self.NE,order=2) |
| 1031 |
self.mu=555. |
| 1032 |
self.latestart=False |
| 1033 |
self.runIt() |
| 1034 |
def test_D2_Free_MuNone_LateStart(self): |
| 1035 |
self.dom = Rectangle(self.NE,self.NE,order=2) |
| 1036 |
self.mu=None |
| 1037 |
self.latestart=True |
| 1038 |
self.runIt(free=0) |
| 1039 |
def test_D2_Free_Mu_LateStart(self): |
| 1040 |
self.dom = Rectangle(self.NE,self.NE,order=2) |
| 1041 |
self.mu=555. |
| 1042 |
self.latestart=True |
| 1043 |
self.runIt(free=0) |
| 1044 |
def test_D2_Free_MuNone(self): |
| 1045 |
self.dom = Rectangle(self.NE,self.NE,order=2) |
| 1046 |
self.mu=None |
| 1047 |
self.latestart=False |
| 1048 |
self.runIt(free=0) |
| 1049 |
def test_D2_Free_Mu(self): |
| 1050 |
self.dom = Rectangle(self.NE,self.NE,order=2) |
| 1051 |
self.mu=555. |
| 1052 |
self.latestart=False |
| 1053 |
self.runIt(free=0) |
| 1054 |
|
| 1055 |
def test_D3_Fixed_MuNone_LateStart(self): |
| 1056 |
self.dom = Brick(self.NE,self.NE,self.NE,order=2) |
| 1057 |
self.mu=None |
| 1058 |
self.latestart=True |
| 1059 |
self.runIt() |
| 1060 |
def test_D3_Fixed_Mu_LateStart(self): |
| 1061 |
self.dom = Brick(self.NE,self.NE,self.NE,order=2) |
| 1062 |
self.mu=555. |
| 1063 |
self.latestart=True |
| 1064 |
self.runIt() |
| 1065 |
def test_D3_Fixed_MuNone(self): |
| 1066 |
self.dom = Brick(self.NE,self.NE,self.NE,order=2) |
| 1067 |
self.mu=None |
| 1068 |
self.latestart=False |
| 1069 |
self.runIt() |
| 1070 |
def test_D3_Fixed_Mu(self): |
| 1071 |
self.dom = Brick(self.NE,self.NE,self.NE,order=2) |
| 1072 |
self.mu=555. |
| 1073 |
self.latestart=False |
| 1074 |
self.runIt() |
| 1075 |
def test_D3_Free_MuNone_LateStart(self): |
| 1076 |
self.dom = Brick(self.NE,self.NE,self.NE,order=2) |
| 1077 |
self.mu=None |
| 1078 |
self.latestart=True |
| 1079 |
self.runIt(free=0) |
| 1080 |
def test_D3_Free_Mu_LateStart(self): |
| 1081 |
self.dom = Brick(self.NE,self.NE,self.NE,order=2) |
| 1082 |
self.mu=555. |
| 1083 |
self.latestart=True |
| 1084 |
self.runIt(free=0) |
| 1085 |
def test_D3_Free_MuNone(self): |
| 1086 |
self.dom = Brick(self.NE,self.NE,self.NE,order=2) |
| 1087 |
self.mu=None |
| 1088 |
self.latestart=False |
| 1089 |
self.runIt(free=0) |
| 1090 |
def test_D3_Free_Mu(self): |
| 1091 |
self.dom = Brick(self.NE,self.NE,self.NE,order=2) |
| 1092 |
self.mu=555. |
| 1093 |
self.latestart=False |
| 1094 |
self.runIt(free=0) |
| 1095 |
|
| 1096 |
if __name__ == '__main__': |
| 1097 |
suite = unittest.TestSuite() |
| 1098 |
suite.addTest(unittest.makeSuite(Test_StokesProblemCartesian2D)) |
| 1099 |
suite.addTest(unittest.makeSuite(Test_Darcy3D)) |
| 1100 |
suite.addTest(unittest.makeSuite(Test_Darcy2D)) |
| 1101 |
suite.addTest(unittest.makeSuite(Test_StokesProblemCartesian3D)) |
| 1102 |
suite.addTest(unittest.makeSuite(Test_Mountains3D)) |
| 1103 |
suite.addTest(unittest.makeSuite(Test_Mountains2D)) |
| 1104 |
suite.addTest(unittest.makeSuite(Test_Rheologies)) |
| 1105 |
suite.addTest(unittest.makeSuite(Test_IncompressibleIsotropicFlowCartesian)) |
| 1106 |
s=unittest.TextTestRunner(verbosity=2).run(suite) |
| 1107 |
if not s.wasSuccessful(): sys.exit(1) |
| 1108 |
|
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