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tplot results for all c values - sphere - GPU-based 3D discrete element method … |
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git clone git://src.adamsgaard.dk/sphere |
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--- |
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commit ae993c5f50daa01d742ab7681b7215da75581145 |
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parent 75f00d3a5b69b8cb76c535aa57bcf66fbcbba7f9 |
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Author: Anders Damsgaard <[email protected]> |
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Date: Wed, 27 Aug 2014 10:16:39 +0200 |
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plot results for all c values |
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Diffstat: |
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M python/consolidation-curve.py | 82 ++++++++++++++++-------------… |
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1 file changed, 42 insertions(+), 40 deletions(-) |
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--- |
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diff --git a/python/consolidation-curve.py b/python/consolidation-curve.py |
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t@@ -9,8 +9,8 @@ import numpy |
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import matplotlib.pyplot as plt |
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c_phi = 1.0 |
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-#c_grad_p_list = [1.0, 0.1, 0.01] |
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-c_grad_p_list = [1.0] |
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+c_grad_p_list = [1.0, 0.1, 0.01] |
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+#c_grad_p_list = [1.0] |
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sigma0 = 10.0e3 |
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#sigma0 = 5.0e3 |
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t@@ -20,50 +20,52 @@ H = [[], [], []] |
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c = 0 |
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for c_grad_p in c_grad_p_list: |
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- sim = sphere.sim('cons-sigma0=' + str(sigma0) + '-c_phi=' + \ |
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- str(c_phi) + '-c_grad_p=' + str(c_grad_p), fluid=True) |
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- t[c] = numpy.empty(sim.status()) |
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- H[c] = numpy.empty(sim.status()) |
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+ sid = 'cons-sigma0=' + str(sigma0) + '-c_phi=' + \ |
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+ str(c_phi) + '-c_grad_p=' + str(c_grad_p) |
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+ if os.path.isfile('../output/' + sid + '.status.dat'): |
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+ sim = sphere.sim(sid, fluid=True) |
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+ t[c] = numpy.empty(sim.status()) |
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+ H[c] = numpy.empty(sim.status()) |
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- #sim.visualize('walls') |
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- #sim.writeVTKall() |
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+ #sim.visualize('walls') |
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+ #sim.writeVTKall() |
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- #sim.plotLoadCurve() |
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- #sim.readfirst(verbose=True) |
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- for i in numpy.arange(1, sim.status()+1): |
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- sim.readstep(i, verbose=False) |
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- t[c][i-1] = sim.time_current[0] |
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- H[c][i-1] = sim.w_x[0] |
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+ #sim.plotLoadCurve() |
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+ #sim.readfirst(verbose=True) |
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+ for i in numpy.arange(1, sim.status()+1): |
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+ sim.readstep(i, verbose=False) |
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+ t[c][i-1] = sim.time_current[0] |
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+ H[c][i-1] = sim.w_x[0] |
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- ''' |
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- # find consolidation parameters |
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- self.H0 = H[0] |
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- self.H100 = H[-1] |
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- self.H50 = (self.H0 + self.H100)/2.0 |
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- T50 = 0.197 # case I |
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+ ''' |
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+ # find consolidation parameters |
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+ self.H0 = H[0] |
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+ self.H100 = H[-1] |
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+ self.H50 = (self.H0 + self.H100)/2.0 |
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+ T50 = 0.197 # case I |
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- # find the time where 50% of the consolidation (H50) has happened by |
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- # linear interpolation. The values in H are expected to be |
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- # monotonically decreasing. See Numerical Recipies p. 115 |
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- i_lower = 0 |
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- i_upper = self.status()-1 |
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- while (i_upper - i_lower > 1): |
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- i_midpoint = int((i_upper + i_lower)/2) |
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- if (self.H50 < H[i_midpoint]): |
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- i_lower = i_midpoint |
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- else: |
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- i_upper = i_midpoint |
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- self.t50 = t[i_lower] + (t[i_upper] - t[i_lower]) * \ |
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- (self.H50 - H[i_lower])/(H[i_upper] - H[i_lower]) |
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+ # find the time where 50% of the consolidation (H50) has happened by |
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+ # linear interpolation. The values in H are expected to be |
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+ # monotonically decreasing. See Numerical Recipies p. 115 |
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+ i_lower = 0 |
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+ i_upper = self.status()-1 |
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+ while (i_upper - i_lower > 1): |
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+ i_midpoint = int((i_upper + i_lower)/2) |
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+ if (self.H50 < H[i_midpoint]): |
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+ i_lower = i_midpoint |
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+ else: |
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+ i_upper = i_midpoint |
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+ self.t50 = t[i_lower] + (t[i_upper] - t[i_lower]) * \ |
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+ (self.H50 - H[i_lower])/(H[i_upper] - H[i_lower]) |
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- self.c_v = T50*self.H50**2.0/(self.t50) |
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- if self.fluid == True: |
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- e = numpy.mean(sb.phi[:,:,3:-8]) # ignore boundaries |
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- else: |
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- e = sb.voidRatio() |
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- ''' |
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+ self.c_v = T50*self.H50**2.0/(self.t50) |
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+ if self.fluid == True: |
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+ e = numpy.mean(sb.phi[:,:,3:-8]) # ignore boundaries |
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+ else: |
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+ e = sb.voidRatio() |
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+ ''' |
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- H[c] -= H[c][0] |
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+ H[c] -= H[c][0] |
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c += 1 |
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