 |
tadd force chain statistics script - sphere - GPU-based 3D discrete element met… |
 |
git clone git://src.adamsgaard.dk/sphere |
 |
Log |
|
Files |
|
Refs |
|
LICENSE |
|
--- |
|
commit dfce171595e257cf25c6fc52744f673663865807 |
|
parent 2dc0f7a74374dce778a1b3b77efdf4349c924ace |
|
Author: Anders Damsgaard <[email protected]> |
|
Date: Mon, 23 Feb 2015 10:40:30 +0100 |
|
|
|
add force chain statistics script |
|
|
|
Diffstat: |
|
A python/halfshear-darcy-forcechainm… | 96 +++++++++++++++++++++++++++… |
|
|
|
1 file changed, 96 insertions(+), 0 deletions(-) |
|
--- |
|
diff --git a/python/halfshear-darcy-forcechainmapper.py b/python/halfshear-darc… |
|
t@@ -0,0 +1,96 @@ |
|
+#!/usr/bin/env python |
|
+import matplotlib |
|
+matplotlib.use('Agg') |
|
+#matplotlib.rcParams.update({'font.size': 18, 'font.family': 'serif'}) |
|
+matplotlib.rcParams.update({'font.size': 7, 'font.family': 'sans-serif'}) |
|
+matplotlib.rc('text', usetex=True) |
|
+matplotlib.rcParams['text.latex.preamble']=[r"\usepackage{amsmath}"] |
|
+import shutil |
|
+ |
|
+import os |
|
+import sys |
|
+import numpy |
|
+import sphere |
|
+import matplotlib.pyplot as plt |
|
+ |
|
+sids =\ |
|
+ ['halfshear-darcy-sigma0=80000.0-k_c=3.5e-13-mu=1.04e-07-ss=10000.0-A=… |
|
+ #['halfshear-darcy-sigma0=80000.0-k_c=3.5e-13-mu=1.797e-06-ss=10000.0-… |
|
+outformat = 'pdf' |
|
+fluid = True |
|
+#threshold = 100.0 # [N] |
|
+ |
|
+ |
|
+ |
|
+for sid in sids: |
|
+ |
|
+ sim = sphere.sim(sid, fluid=fluid) |
|
+ |
|
+ #nsteps = 2 |
|
+ #nsteps = 10 |
|
+ nsteps = sim.status() |
|
+ |
|
+ t = numpy.empty(nsteps) |
|
+ n = numpy.empty(nsteps) |
|
+ coordinationnumber = numpy.empty(nsteps) |
|
+ nkept = numpy.empty(nsteps) |
|
+ |
|
+ for i in numpy.arange(nsteps): |
|
+ sim.readstep(i+1) |
|
+ t[i] = sim.currentTime() |
|
+ #n[i] = countLoadedContacts(sim, threshold) |
|
+ |
|
+ if i > 0: |
|
+ loaded_contacts_prev = numpy.copy(loaded_contacts) |
|
+ pairs_prev = numpy.copy(sim.pairs) |
|
+ |
|
+ loaded_contacts = sim.findLoadedContacts( |
|
+ threshold = sim.currentNormalStress()*2.) |
|
+ #sim.currentNormalStress()/1000.) |
|
+ n[i] = numpy.size(loaded_contacts) |
|
+ |
|
+ sim.findCoordinationNumber() |
|
+ coordinationnumber[i] = sim.findMeanCoordinationNumber() |
|
+ |
|
+ nfound = 0 |
|
+ if i > 0: |
|
+ for a in loaded_contacts[0]: |
|
+ for b in loaded_contacts_prev[0]: |
|
+ if (sim.pairs[:,a] == pairs_prev[:,b]).all(): |
|
+ nfound += 1; |
|
+ |
|
+ nkept[i] = nfound |
|
+ |
|
+ print coordinationnumber[i] |
|
+ print nfound |
|
+ |
|
+ #fig = plt.figure(figsize=[8,8]) |
|
+ fig = plt.figure(figsize=[3.5,7]) |
|
+ |
|
+ ax1 = plt.subplot(3,1,1) |
|
+ #ax1.plot(t, n) |
|
+ ax1.semilogy(t, n, 'k') |
|
+ ax1.set_xlabel('Time $t$ [s]') |
|
+ #ax1.set_ylabel(\ |
|
+ #'Heavily loaded contacts $||\\boldsymbol{{f}}_n|| \\geq {}$ N'.fo… |
|
+ #threshold)) |
|
+ ax1.set_ylabel(\ |
|
+ 'Heavily loaded contacts $\sigma_c \\geq \\sigma_0\\times 4$ Pa') |
|
+ #'Heavily loaded contacts $||\\boldsymbol{{\sigma}}_c|| \\geq \\si… |
|
+ |
|
+ ax2 = plt.subplot(3,1,2) |
|
+ ax2.semilogy(t, n - nkept, 'k') |
|
+ ax2.set_xlabel('Time $t$ [s]') |
|
+ ax2.set_ylabel(\ |
|
+ 'New heavily loaded contacts $\sigma_c \\geq \\sigma_0\\times 4$ P… |
|
+ #'Heavily loaded contacts $||\\boldsymbol{{\sigma}}_c|| \\geq \\si… |
|
+ |
|
+ ax3 = plt.subplot(3,1,3) |
|
+ #ax3.semilogy(t, coordinationnumber) |
|
+ ax3.plot(t, coordinationnumber, 'k') |
|
+ ax3.set_xlabel('Time $t$ [s]') |
|
+ ax3.set_ylabel('Coordination number $z$') |
|
+ |
|
+ |
|
+ |
|
+ plt.savefig(sid + '-nloaded.' + outformat) |
