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# |
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# $Id$ |
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# |
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####################################################### |
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# |
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# Copyright 2003-2007 by ACceSS MNRF |
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# Copyright 2007 by University of Queensland |
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# |
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# http://esscc.uq.edu.au |
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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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################################################ |
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## ## |
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## October 2006 ## |
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## ## |
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## 3D Rayleigh-Taylor instability benchmark ## |
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## by Laurent Bourgouin ## |
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## ## |
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################################################ |
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|
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### IMPORTS ### |
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from esys.escript import * |
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import esys.finley |
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from esys.finley import finley |
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from esys.escript.linearPDEs import LinearPDE |
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from esys.escript.pdetools import Projector, SaddlePointProblem |
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import sys |
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import math |
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|
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### DEFINITION OF THE DOMAIN ### |
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l0=1. |
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l1=1. |
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n0=10 # IDEALLY 80... |
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n1=10 # IDEALLY 80... |
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mesh=esys.finley.Brick(l0=l0, l1=l1, l2=l0, order=2, n0=n0, n1=n1, n2=n0) |
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|
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### PARAMETERS OF THE SIMULATION ### |
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rho1 = 1.0e3 # DENSITY OF THE FLUID AT THE BOTTOM |
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rho2 = 1.01e3 # DENSITY OF THE FLUID ON TOP |
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eta1 = 1.0e2 # VISCOSITY OF THE FLUID AT THE BOTTOM |
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eta2 = 1.0e2 # VISCOSITY OF THE FLUID ON TOP |
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penalty = 1.0e3 # PENALTY FACTOR FOT THE PENALTY METHOD |
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g=10. # GRAVITY |
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t_step = 0 |
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t_step_end = 2000 |
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reinit_max = 30 # NUMBER OF ITERATIONS DURING THE REINITIALISATION PROCEDURE |
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reinit_each = 3 # NUMBER OF TIME STEPS BETWEEN TWO REINITIALISATIONS |
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h = Lsup(mesh.getSize()) |
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numDim = mesh.getDim() |
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smooth = h*2.0 # SMOOTHING PARAMETER FOR THE TRANSITION ACROSS THE INTERFACE |
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|
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### DEFINITION OF THE PDE ### |
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velocityPDE = LinearPDE(mesh, numEquations=numDim) |
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|
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advectPDE = LinearPDE(mesh) |
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advectPDE.setReducedOrderOn() |
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advectPDE.setValue(D=1.0) |
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advectPDE.setSolverMethod(solver=LinearPDE.DIRECT) |
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|
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reinitPDE = LinearPDE(mesh, numEquations=1) |
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reinitPDE.setReducedOrderOn() |
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reinitPDE.setSolverMethod(solver=LinearPDE.LUMPING) |
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my_proj=Projector(mesh) |
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|
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### BOUNDARY CONDITIONS ### |
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xx = mesh.getX()[0] |
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yy = mesh.getX()[1] |
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zz = mesh.getX()[2] |
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top = whereZero(zz-l1) |
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bottom = whereZero(zz) |
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left = whereZero(xx) |
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right = whereZero(xx-l0) |
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front = whereZero(yy) |
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back = whereZero(yy-l0) |
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b_c = (bottom+top)*[1.0, 1.0, 1.0] + (left+right)*[1.0,0.0, 0.0] + (front+back)*[0.0, 1.0, 0.0] |
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velocityPDE.setValue(q = b_c) |
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|
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pressure = Scalar(0.0, ContinuousFunction(mesh)) |
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velocity = Vector(0.0, ContinuousFunction(mesh)) |
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|
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### INITIALISATION OF THE INTERFACE ### |
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func = -(-0.1*cos(math.pi*xx/l0)*cos(math.pi*yy/l0)-zz+0.4) |
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phi = func.interpolate(ReducedSolution(mesh)) |
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|
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|
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def advect(phi, velocity, dt): |
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### SOLVES THE ADVECTION EQUATION ### |
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|
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Y = phi.interpolate(Function(mesh)) |
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for i in range(numDim): |
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Y -= (dt/2.0)*velocity[i]*grad(phi)[i] |
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advectPDE.setValue(Y=Y) |
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phi_half = advectPDE.getSolution() |
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|
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Y = phi |
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for i in range(numDim): |
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Y -= dt*velocity[i]*grad(phi_half)[i] |
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advectPDE.setValue(Y=Y) |
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phi = advectPDE.getSolution() |
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|
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print "Advection step done" |
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return phi |
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|
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def reinitialise(phi): |
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### SOLVES THE REINITIALISATION EQUATION ### |
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s = sign(phi.interpolate(Function(mesh))) |
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w = s*grad(phi)/length(grad(phi)) |
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dtau = 0.3*h |
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iter =0 |
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previous = 100.0 |
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mask = whereNegative(abs(phi)-1.2*h) |
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reinitPDE.setValue(q=mask, r=phi) |
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print "Reinitialisation started." |
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while (iter<=reinit_max): |
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prod_scal =0.0 |
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for i in range(numDim): |
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prod_scal += w[i]*grad(phi)[i] |
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coeff = s - prod_scal |
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ps2=0 |
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for i in range(numDim): |
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ps2 += w[i]*grad(my_proj(coeff))[i] |
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reinitPDE.setValue(D=1.0, Y=phi+dtau*coeff-0.5*dtau**2*ps2) |
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phi = reinitPDE.getSolution() |
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error = Lsup((previous-phi)*whereNegative(abs(phi)-3.0*h))/h |
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print "Reinitialisation iteration :", iter, " error:", error |
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previous = phi |
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iter +=1 |
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print "Reinitialisation finalized." |
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return phi |
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|
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def update_phi(phi, velocity, dt, t_step): |
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### CALLS THE ADVECTION PROCEDURE AND THE REINITIALISATION IF NECESSARY ### |
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phi=advect(phi, velocity, dt) |
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if t_step%reinit_each ==0: |
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phi = reinitialise(phi) |
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return phi |
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def update_parameter(phi, param_neg, param_pos): |
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### UPDATES THE PARAMETERS TABLE USING THE SIGN OF PHI, A SMOOTH TRANSITION IS DONE ACROSS THE INTERFACE ### |
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mask_neg = whereNonNegative(-phi-smooth) |
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mask_pos = whereNonNegative(phi-smooth) |
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mask_interface = whereNegative(abs(phi)-smooth) |
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param = param_pos*mask_pos + param_neg*mask_neg + ((param_pos+param_neg)/2 +(param_pos-param_neg)*phi/(2.*smooth))*mask_interface |
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return param |
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|
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class StokesProblem(SaddlePointProblem): |
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""" |
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simple example of saddle point problem |
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""" |
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def __init__(self,domain,debug=False): |
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super(StokesProblem, self).__init__(self,debug) |
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self.domain=domain |
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self.__pde_u=LinearPDE(domain,numEquations=self.domain.getDim(),numSolutions=self.domain.getDim()) |
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self.__pde_u.setSymmetryOn() |
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self.__pde_p=LinearPDE(domain) |
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self.__pde_p.setReducedOrderOn() |
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self.__pde_p.setSymmetryOn() |
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def initialize(self,f=Data(),fixed_u_mask=Data(),eta=1): |
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self.eta=eta |
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A =self.__pde_u.createCoefficientOfGeneralPDE("A") |
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for i in range(self.domain.getDim()): |
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for j in range(self.domain.getDim()): |
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A[i,j,j,i] += self.eta |
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A[i,j,i,j] += self.eta |
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self.__pde_p.setValue(D=1/self.eta) |
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self.__pde_u.setValue(A=A,q=fixed_u_mask,Y=f) |
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def inner(self,p0,p1): |
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return integrate(p0*p1,Function(self.__pde_p.getDomain())) |
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|
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def solve_f(self,u,p,tol=1.e-8): |
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self.__pde_u.setTolerance(tol) |
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g=grad(u) |
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self.__pde_u.setValue(X=self.eta*symmetric(g)+p*kronecker(self.__pde_u.getDomain())) |
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return self.__pde_u.getSolution() |
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|
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def solve_g(self,u,tol=1.e-8): |
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self.__pde_p.setTolerance(tol) |
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self.__pde_p.setValue(X=-u) |
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dp=self.__pde_p.getSolution() |
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return dp |
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|
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sol=StokesProblem(velocity.getDomain(),debug=True) |
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def solve_vel_uszawa(rho, eta, velocity, pressure): |
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### SOLVES THE VELOCITY PROBLEM USING A PENALTY METHOD FOR THE INCOMPRESSIBILITY ### |
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Y = Vector(0.0,Function(mesh)) |
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Y[1] -= rho*g |
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sol.initialize(fixed_u_mask=b_c,eta=eta,f=Y) |
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velocity,pressure=sol.solve(velocity,pressure,iter_max=100,tolerance=0.01) #,accepted_reduction=None) |
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return velocity, pressure |
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|
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def solve_vel_penalty(rho, eta, velocity, pressure): |
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### SOLVES THE VELOCITY PROBLEM USING A PENALTY METHOD FOR THE INCOMPRESSIBILITY ### |
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velocityPDE.setSolverMethod(solver=LinearPDE.DIRECT) |
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error = 1.0 |
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ref = pressure*1.0 |
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p_iter=0 |
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while (error >= 1.0e-2): |
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A=Tensor4(0.0, Function(mesh)) |
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for i in range(numDim): |
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for j in range(numDim): |
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A[i,j,i,j] += eta |
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A[i,j,j,i] += eta |
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A[i,i,j,j] += penalty*eta |
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Y = Vector(0.0,Function(mesh)) |
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Y[1] -= rho*g |
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|
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X = Tensor(0.0, Function(mesh)) |
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for i in range(numDim): |
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X[i,i] += pressure |
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velocityPDE.setValue(A=A, X=X, Y=Y) |
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velocity = velocityPDE.getSolution() |
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p_iter +=1 |
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if p_iter >=500: |
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print "You're screwed..." |
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sys.exit(1) |
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pressure -= penalty*eta*(trace(grad(velocity))) |
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error = penalty*Lsup(trace(grad(velocity)))/Lsup(grad(velocity)) |
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print "\nPressure iteration number:", p_iter |
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print "error", error |
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ref = pressure*1.0 |
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return velocity, pressure |
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|
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### MAIN LOOP, OVER TIME ### |
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while t_step <= t_step_end: |
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print "######################" |
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print "Time step:", t_step |
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print "######################" |
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rho = update_parameter(phi, rho1, rho2) |
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eta = update_parameter(phi, eta1, eta2) |
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velocity, pressure = solve_vel_uszawa(rho, eta, velocity, pressure) |
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dt = 0.3*Lsup(mesh.getSize())/Lsup(velocity) |
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phi = update_phi(phi, velocity, dt, t_step) |
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### PSEUDO POST-PROCESSING ### |
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print "########## Saving image", t_step, " ###########" |
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saveVTK("phi3D.%2.2i.vtk"%t_step,layer=phi) |
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|
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t_step += 1 |
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|
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# vim: expandtab shiftwidth=4: |
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