https://github.com/geodynamics/citcoms
Revision bcf06ab870d4cfd4a7c8594146ed51e41b23d5f9 authored by Eh Tan on 09 August 2007, 22:57:28 UTC, committed by Eh Tan on 09 August 2007, 22:57:28 UTC
Two non-dimensional parameters are added: "dissipation_number" and "gruneisen" under the Solver component. One can use the original incompressible solver by setting "gruneisen=0". The code will treat this as "gruneisen=infinity". Setting non-zero value to "gruneisen" will switch to compressible solver. One can use the TALA solver for incompressible case by setting "gruneisen" to a non-zero value while setting "dissipation_number=0". This is useful when debugging the compressible solver. Two implementations are available: one by Wei Leng (U. Colorado) and one by Eh Tan (CIG). Leng's version uses the original conjugate gradient method for the Uzawa iteration and moves the contribution of compressibility to the RHS, similar to the method of Ita and King, JGR, 1994. Tan's version uses the bi-conjugate gradient stablized method for the Uzawa iteration, similar to the method of Tan and Gurnis, JGR, 2007. Both versions agree very well. In the benchmark case, 33x33x33 nodes per cap, Di/gamma=1.0, Ra=1.0, delta function of load at the mid mantle, the peak velocity differs by only 0.007%. Leng's version is enabled by default. Edit function solve_Ahat_p_fhat() in lib/Stokes_flow_Incomp.c to switch to Tan's version.
1 parent 91bcb85
Tip revision: bcf06ab870d4cfd4a7c8594146ed51e41b23d5f9 authored by Eh Tan on 09 August 2007, 22:57:28 UTC
Finished the compressible Stokes solver for TALA.
Finished the compressible Stokes solver for TALA.
Tip revision: bcf06ab
Controller.py
#!/usr/bin/env python
#
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#
#<LicenseText>
#
# CitcomS.py by Eh Tan, Eun-seo Choi, and Pururav Thoutireddy.
# Copyright (C) 2002-2005, California Institute of Technology.
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
#
#</LicenseText>
#
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#
def controller(name="controller", facility="controller"):
return Controller(name, facility)
from pyre.components.Component import Component
import journal
class Controller(Component):
def __init__(self, name, facility):
Component.__init__(self, name, facility)
self.done = False
self.solver = None
return
# Set these attributes as read-only properties, so that they are
# always in accordance with their counterparts in the C code
clock = property(lambda self: self.solver.t)
dt = property(lambda self: self.solver.dt)
step = property(lambda self: self.solver.step)
def initialize(self, app):
self.solver = app.solver
self.solver.initialize(app)
return
def launch(self, app):
# 0th step
self.solver.launch(app)
# do io for 0th step
self.save()
### XXX: if stokes: advection tracers and terminate
return
def march(self, totalTime=0, steps=0):
"""explicit time loop"""
if (self.step + 1) >= steps:
self.endSimulation()
return
while 1:
# notify solvers we are starting a new timestep
self.startTimestep()
# compute an acceptable timestep
dt = self.stableTimestep()
# advance
self.advance(dt)
# notify solver we finished a timestep
self.endTimestep(totalTime, steps)
# do io
self.save()
# are we done?
if self.done:
break
# end of time advance loop
# Notify solver we are done
self.endSimulation()
return
def startTimestep(self):
self.solver.newStep()
return
def stableTimestep(self):
dt = self.solver.stableTimestep()
return dt
def advance(self, dt):
self.solver.advance(dt)
return
def endTimestep(self, totalTime, steps):
# are we done?
if steps and self.step >= steps:
self.done = True
if totalTime and self.clock >= totalTime:
self.done = True
# solver can terminate time marching by returning True
self.done = self.solver.endTimestep(self.done)
return
def endSimulation(self):
self.solver.endSimulation()
return
def save(self):
self.solver.save(self.inventory.monitoringFrequency)
self.solver.checkpoint(self.inventory.checkpointFrequency)
return
class Inventory(Component.Inventory):
import pyre.inventory
monitoringFrequency = pyre.inventory.int("monitoringFrequency", default=100)
checkpointFrequency = pyre.inventory.int("checkpointFrequency", default=100)
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