tvisualize mean pressures as time series (incomplete) - sphere - GPU-based 3D discrete element method algorithm with optional fluid coupling
(HTM) git clone git://src.adamsgaard.dk/sphere
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---
(DIR) commit c502aa76c0c7154f05fe425ad4f16f60743ba3d2
(DIR) parent 64696bcfffc330d89cebbd151b578e8b282282ca
(HTM) Author: Anders Damsgaard <anders.damsgaard@geo.au.dk>
Date: Wed, 1 Oct 2014 12:39:41 +0200
visualize mean pressures as time series (incomplete)
Diffstat:
A python/shear-results-pressures.py | 76 +++++++++++++++++++++++++++++++
1 file changed, 76 insertions(+), 0 deletions(-)
---
(DIR) diff --git a/python/shear-results-pressures.py b/python/shear-results-pressures.py
t@@ -0,0 +1,76 @@
+#!/usr/bin/env python
+import matplotlib
+matplotlib.use('Agg')
+matplotlib.rcParams.update({'font.size': 18, 'font.family': 'serif'})
+matplotlib.rc('text', usetex=True)
+matplotlib.rcParams['text.latex.preamble']=[r"\usepackage{amsmath}"]
+import shutil
+
+import os
+import numpy
+import sphere
+from permeabilitycalculator import *
+import matplotlib.pyplot as plt
+from matplotlib.ticker import MaxNLocator
+
+matplotlib.rcParams['image.cmap'] = 'bwr'
+
+sigma0 = float(sys.argv[1])
+#c_grad_p = 1.0
+c_grad_p = float(sys.argv[2])
+c_phi = 1.0
+
+sid = 'shear-sigma0=' + str(sigma0) + '-c_phi=' + \
+ str(c_phi) + '-c_grad_p=' + str(c_grad_p) + '-hi_mu-lo_visc'
+sim = sphere.sim(sid, fluid=True)
+sim.readfirst(verbose=False)
+
+# cell midpoint cell positions
+zpos_c = numpy.zeros(sim.num[2])
+dz = sim.L[2]/sim.num[2]
+for i in numpy.arange(sim.num[2]):
+ zpos_c[i] = i*dz + 0.5*dz
+
+shear_strain = numpy.zeros(sim.status())
+
+dev_pres = numpy.zeros((sim.num[2], sim.status()))
+
+for i in numpy.arange(sim.status()):
+
+ sim.readstep(i, verbose=False)
+
+ '''
+ dev_pres[:,i] = numpy.average(numpy.average(sim.p_f, axis=0), axis=0)
+
+ for z in numpy.arange(0, sim.w_x[0]+1):
+ pres_static = (sim.w_x[0] - zpos_c[z])*sim.rho_f*numpy.abs(sim.g[2])\
+ + sim.p_f[0,0,-1]
+ dev_pres[z,i] -= pres_static
+ '''
+ dev_pres[:,i] = numpy.arange(0, sim.num[2])
+
+ shear_strain[i] = sim.shearStrain()
+
+
+#fig = plt.figure(figsize=(8,4*(len(steps))+1))
+fig = plt.figure(figsize=(8,6))
+
+plt.pcolormesh(shear_strain, zpos_c, dev_pres/1000.0, rasterized=True)
+plt.xlim([0, shear_strain[-1]])
+plt.ylim([zpos_c[0], sim.w_x[0]])
+plt.xlabel('Shear strain $\\gamma$ [-]')
+plt.ylabel('Vertical position $z$ [m]')
+cb = plt.colorbar()
+cb.set_label('Deviatoric pressure $p_\\text{f}$ [kPa]')
+cb.solids.set_rasterized(True)
+
+
+#plt.MaxNLocator(nbins=4)
+plt.tight_layout()
+plt.subplots_adjust(wspace = .05)
+#plt.MaxNLocator(nbins=4)
+
+filename = 'shear-' + str(int(sigma0/1000.0)) + 'kPa-pressures.pdf'
+plt.savefig(filename)
+shutil.copyfile(filename, '/home/adc/articles/own/2-org/' + filename)
+print(filename)