[CIG-SHORT] mesh resolution

[tu xiang]

Hello, everyone
I want to construct a mesh grid model which is dense near the fault and is sparse far from the fault. The example of "cubit_cellsize" is a good example. But I do not know what is the meaning of the variable "cell_size_fn". Is it the maximum distance from one node to another? or the maximum size of the cell on the fault? or other meaning?
If I want ensure that the size of the cell on the fault must smaller than one constant value, what should I do?

The code of the example of "cubit_cellsize"
#!/usr/bin/env nemesis
# ----------------------------------------------------------------------
# PREREQUISITES: numpy, netCDF4, spatialdata (PyLith)

filenameExodus = "mesh_cellsize.exo"
filenameDB = "matprops.spatialdb"
minPeriod = 10.0

# ======================================================================
import sys
import numpy
import netCDF4

# ----------------------------------------------------------------------
# Cell size based on minimum wavelength with Vs from spatial database
def getCellSizeDB(points):

    from spatialdata.geocoords.CSCart import CSCart
    from spatialdata.spatialdb.SimpleDB import SimpleDB
    from spatialdata.spatialdb.SimpleIOAscii import SimpleIOAscii

    # Coordinate system for mesh (must match coordsys in ExodusII file)
    cs = CSCart()
    cs._configure()
    cs.initialize()

    # Spatial database with physical properties (Vs)
    dbIO = SimpleIOAscii()
    dbIO.inventory.filename = filenameDB
    dbIO._configure()
    db = SimpleDB()
    db.inventory.iohandler = dbIO
    db.inventory.label = "Physical properties"
    db.inventory.queryType = "linear"
    db._configure()

    (npoints, spacedim) = points.shape

    # Query database
    db.open()
    db.queryVals(["vs"])
    data = numpy.zeros((npoints, 1), dtype=numpy.float64)
    err = numpy.zeros((npoints,), dtype=numpy.int32)
    db.multiquery(data, err, points, cs)
    db.close()

    vs = data[:,0]
    cellSize = minPeriod*vs / 10.0
    return cellSize


# ----------------------------------------------------------------------
# Cell size based on analytical function of vertex coordinates.
def getCellSizeFn(points):
    """
    Cell size is based on distance from a target and grows at a
    geometric rate.
    """
    # Coordinates of target
    target = (5.0e+3, -10.0e+3, -10.0e+3)

    # Compute distance from target
    dist = ((points[:,0] - target[0])**2 + \
                (points[:,1] - target[1])**2 + \
                (points[:,2] - target[2])**2)**0.5
    bias_factor = 1.05 # Geometric rate
    dxStart = 1.0e+3 # Discretization size at target
    npts = numpy.ceil( numpy.log(1-dist/dxStart*(1-bias_factor))/numpy.log(bias_factor))
    cellSize = dxStart*bias_factor**npts
    return cellSize


# ----------------------------------------------------------------------
# Get coordinates of points from ExodusII file.
exodus = netCDF4.Dataset(filenameExodus, 'a')
points = exodus.variables['coord'][:].transpose()
cellSizeDB = getCellSizeDB(points)
cellSizeFn = getCellSizeFn(points)

# Add cell size info to ExodusII file
if not 'num_nod_var' in exodus.dimensions.keys():
    exodus.createDimension('num_nod_var', 2)

    name_nod_var = exodus.createVariable('name_nod_var', 'S1',
                                       ('num_nod_var', 'len_string',))
    name_nod_var[0,:] = netCDF4.stringtoarr("cell_size_db", 33)
    name_nod_var[1,:] = netCDF4.stringtoarr("cell_size_fn", 33)

    vals_nod_var = exodus.createVariable('vals_nod_var', numpy.float64,
                                       ('time_step', 'num_nod_var', 'num_nodes',))


time_whole = exodus.variables['time_whole']
time_whole[0] = 0.0
vals_nod_var = exodus.variables['vals_nod_var']
vals_nod_var[0,0,:] = cellSizeDB.transpose()
vals_nod_var[0,1,:] = cellSizeFn.transpose()

exodus.close()

# End of file


Hope someone would like to help me .
Best regards,
Tu Xiang

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.geodynamics.org/pipermail/cig-short/attachments/20180307/304abb71/attachment-0001.html>