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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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__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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""" |
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Author: Antony Hallam antony.hallam@uqconnect.edu.au |
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""" |
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# To solve the problem it is necessary to import the modules we require. |
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from esys.escript import * # This imports everything from the escript library |
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from esys.escript.linearPDEs import LinearPDE, Poisson # This defines LinearPDE as LinearPDE |
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from esys.finley import Rectangle, ReadMesh, Domain # This imports the rectangle domain function from finley |
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import os #This package is necessary to handle saving our data. |
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from esys.escript.unitsSI import * # A useful unit handling package which will make sure all our units match up in the equations. |
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import numpy as np |
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import pylab as pl |
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from esys.escript.pdetools import * |
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##ESTABLISHING VARIABLES |
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#DOMAIN |
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mymesh = ReadMesh("heatrefraction_mesh003.fly") |
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#~ print Function(mymesh).getListOfTags() |
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qin=70*Milli*W/(m*m) #our heat source temperature is now zero |
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Ti=290.15*K # Kelvin #the starting temperature of our iron bar |
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# set up kappa (thermal conductivity across domain) using tags |
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kappa=Scalar(0,Function(mymesh)) |
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kappa.setTaggedValue("tblockloop",2.0) |
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kappa.setTaggedValue("bblockloopl",3.0) |
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kappa.setTaggedValue("bblockloopr",4.0) |
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|
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#... generate functionspace... |
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#... open PDE ... |
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mypde=LinearPDE(mymesh) |
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#define first coefficient |
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mypde.setValue(A=kappa*kronecker(mymesh)) |
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# ... set initial temperature .... |
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x=mymesh.getX() |
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qH=qin*whereZero(x[1]+6000) |
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mypde.setValue(q=Ti*whereZero(x[1]),r=Ti) |
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mypde.setValue(Y=qH,y=17*Celsius) |
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# get steady state solution and export to vtk. |
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T=mypde.getSolution() |
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saveVTK("tempheatrefract.xml",sol=T, q=-kappa*grad(T)) |
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# rearrage mymesh to suit solution function space |
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oldspacecoords=mymesh.getX() |
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coords=Data(oldspacecoords, T.getFunctionSpace()) |
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# calculate gradient of solution for quiver plot |
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qu=-kappa*grad(T) |
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# create quiver locations |
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quivshape = [20,20] #quivers x and quivers y |
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numquiv = quivshape[0]*quivshape[1] # total number of quivers |
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maxx = 5000. # maximum x displacement |
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dx = maxx/quivshape[0]+1. # quiver x spacing |
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maxy = -6000. # maximum y displacement |
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dy = maxy/quivshape[1]+1. # quiver y spacing |
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qulocs=np.zeros([numquiv,2],float) # memory for quiver locations |
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# fill qulocs |
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for i in range(0,quivshape[0]-1): |
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for j in range(0,quivshape[1]-1): |
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qulocs[i*quivshape[0]+j,:] = [dx+dx*i,dy+dy*j] |
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# retreive values for quivers direction and shape from qu |
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quL = Locator(qu.getFunctionSpace(),qulocs.tolist()) |
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qu = quL(qu) #array of dx,dy for quivers |
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qu = np.array(qu) #turn into a numpy array |
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qulocs = quL.getX() #returns actual locations from data |
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qulocs = np.array(qulocs) #turn into a numpy array |
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kappaT = kappa.toListOfTuples(scalarastuple=False) |
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coordsK = Data(oldspacecoords, kappa.getFunctionSpace()) |
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coordsK = np.array(coordsK.toListOfTuples()) |
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coordKX = coordsK[:,0] |
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coordKY = coordsK[:,1] |
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coords = np.array(coords.toListOfTuples()) |
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tempT = T.toListOfTuples(scalarastuple=False) |
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coordX = coords[:,0] |
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coordY = coords[:,1] |
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xi = np.linspace(0.0,5000.0,100) |
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yi = np.linspace(-6000.0,0.0,100) |
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# grid the data. |
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zi = pl.matplotlib.mlab.griddata(coordX,coordY,tempT,xi,yi) |
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ziK = pl.matplotlib.mlab.griddata(coordKX,coordKY,kappaT,xi,yi) |
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# contour the gridded data, plotting dots at the randomly spaced data points. |
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pl.matplotlib.pyplot.autumn() |
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CKL = pl.contour(xi,yi,ziK,1,linewidths=1.0) |
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CK = pl.contourf(xi,yi,ziK,1) |
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CS = pl.contour(xi,yi,zi,5,linewidths=0.5,colors='k') |
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pl.clabel(CS, inline=1, fontsize=8) |
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CB = pl.colorbar(CS, shrink=0.8, extend='both') |
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pl.savefig("temp.png") |
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#~ dx = np.zeros(82,float) |
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#~ dy = np.zeros(82,float) |
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#~ vlocs = np.zeros([82,2],float) |
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#~ delx = 5000.0/100 |
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#~ dely = 6000.0/100 |
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#~ ind = 0 |
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#~ |
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#~ for i in range(1,10): |
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#~ for j in range(1,10): |
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#~ iloc = i*10 |
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#~ jloc = j*10 |
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#~ ind += 1 |
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#~ |
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#~ vlocs[ind,0] = iloc*delx; vlocs[ind,1]=-jloc*dely |
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#~ |
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#~ print zi[iloc,jloc], zi[iloc+5,jloc] |
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#~ print zi[iloc,jloc], zi[iloc,jloc+5] |
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#~ dx[ind] = (zi[iloc,jloc] - zi[iloc+5,jloc])/delx |
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#~ dy[ind] = (zi[iloc,jloc] - zi[iloc,jloc+5])/dely |
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#~ zpoints = [zi[iloc,jloc],zi[iloc+2,jloc],zi[iloc+4,jloc]] |
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#~ xpoints = [vlocs[ind,0],vlocs[ind+2,0],vlocs[ind+4,0]] |
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#~ print pl.matplotlib.mlab.slopes(xpoints,zpoints) |
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#~ dx[ind] = pl.matplotlib.mlab.slopes(xpoints,zpoints) |
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#~ |
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#~ ypoints = [vlocs[ind,1],vlocs[ind+2,1],vlocs[ind+4,]] |
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#~ zpoints = [zi[iloc,jloc],zi[iloc,jloc+2],zi[iloc,jloc+4]] |
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#~ dy[ind] = pl.matplotlib.mlab.slopes(ypoints,zpoints) |
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#~ |
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pl.quiver(qulocs[:,0],qulocs[:,1],qu[:,0],qu[:,1],angles='xy',color="green") |
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pl.savefig("temp2.png") |
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