treturn vertical hydraulic conductivity - 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 e45ccf746f5e6fc208262e43703f94532e54e5ee
 (DIR) parent 220a48e1d79afa0ec97dba98f0fa4cdbe65a0131
 (HTM) Author: Anders Damsgaard <anders.damsgaard@geo.au.dk>
       Date:   Wed, 13 Aug 2014 12:30:03 +0200
       
       return vertical hydraulic conductivity
       
       Diffstat:
         M python/permeability-results.py      |       4 ++--
         M python/permeabilitycalculator.py    |       2 +-
       
       2 files changed, 3 insertions(+), 3 deletions(-)
       ---
 (DIR) diff --git a/python/permeability-results.py b/python/permeability-results.py
       t@@ -4,9 +4,9 @@ import matplotlib.pyplot as plt
        from permeabilitycalculator import *
        
        sids = [
       -    'permeability-dp=1000.0',
            'permeability-dp=1000.0-c_phi=1.0-c_grad_p=0.01',
            'permeability-dp=1000.0-c_phi=1.0-c_grad_p=0.5',
       +    'permeability-dp=1000.0',
            'permeability-dp=20000.0-c_phi=1.0-c_grad_p=0.01',
            'permeability-dp=20000.0-c_phi=1.0-c_grad_p=0.1',
            'permeability-dp=20000.0-c_phi=1.0-c_grad_p=0.5',
       t@@ -28,6 +28,6 @@ for sid in sids:
        fig = plt.figure()
        plt.xlabel('Pressure gradient coefficient $c$ [-]')
        plt.ylabel('Hydraulic conductivity $K$ [m/s]')
       -plt.plot(c_grad_p, K)
       +plt.plot(c_grad_p, K, '+')
        plt.grid()
        plt.savefig('c_grad_p-vs-K.png')
 (DIR) diff --git a/python/permeabilitycalculator.py b/python/permeabilitycalculator.py
       t@@ -37,7 +37,7 @@ class PermeabilityCalc:
                self.K = -self.Q * self.dL / (self.A * self.dP)
        
            def conductivity(self):
       -        return self.K[0]
       +        return self.K[2]
        
            def c_grad_p(self):
                return self.sim.c_grad_p[0]