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Added Syltherm800 for @adesideri
This commit is contained in:
Jorrit Wronski
@@ -617,7 +617,31 @@ class Pirobloc(PureData):
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self.reference = "http://www.fluidotermico.com"
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self.reshapeAll()
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class Syltherm800(PureData):
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"""
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Syltherm800 is a fluid for high temperature heat transfer.
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"""
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def __init__(self):
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PureData.__init__(self)
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self.density.source = self.density.SOURCE_DATA
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self.viscosity.source = self.viscosity.SOURCE_DATA
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self.specific_heat.source = self.specific_heat.SOURCE_DATA
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self.conductivity.source = self.conductivity.SOURCE_DATA
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self.saturation_pressure.source = self.saturation_pressure.SOURCE_DATA
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self.temperature.data = np.array([-4.000E+01, -3.800E+01, -3.600E+01, -3.400E+01, -3.200E+01, -3.000E+01, -2.800E+01, -2.600E+01, -2.400E+01, -2.200E+01, -2.000E+01, -1.800E+01, -1.600E+01, -1.400E+01, -1.200E+01, -1.000E+01, -8.000E+00, -6.000E+00, -4.000E+00, -2.000E+00, 0.000E+00, 2.000E+00, 4.000E+00, 6.000E+00, 8.000E+00, 1.000E+01, 1.200E+01, 1.400E+01, 1.600E+01, 1.800E+01, 2.000E+01, 2.200E+01, 2.400E+01, 2.600E+01, 2.800E+01, 3.000E+01, 3.200E+01, 3.400E+01, 3.600E+01, 3.800E+01, 4.000E+01, 4.200E+01, 4.400E+01, 4.600E+01, 4.800E+01, 5.000E+01, 5.200E+01, 5.400E+01, 5.600E+01, 5.800E+01, 6.000E+01, 6.200E+01, 6.400E+01, 6.600E+01, 6.800E+01, 7.000E+01, 7.200E+01, 7.400E+01, 7.600E+01, 7.800E+01, 8.000E+01, 8.200E+01, 8.400E+01, 8.600E+01, 8.800E+01, 9.000E+01, 9.200E+01, 9.400E+01, 9.600E+01, 9.800E+01, 1.000E+02, 1.020E+02, 1.040E+02, 1.060E+02, 1.080E+02, 1.100E+02, 1.120E+02, 1.140E+02, 1.160E+02, 1.180E+02, 1.200E+02, 1.220E+02, 1.240E+02, 1.260E+02, 1.280E+02, 1.300E+02, 1.320E+02, 1.340E+02, 1.360E+02, 1.380E+02, 1.400E+02, 1.420E+02, 1.440E+02, 1.460E+02, 1.480E+02, 1.500E+02, 1.520E+02, 1.540E+02, 1.560E+02, 1.580E+02, 1.600E+02, 1.620E+02, 1.640E+02, 1.660E+02, 1.680E+02, 1.700E+02, 1.720E+02, 1.740E+02, 1.760E+02, 1.780E+02, 1.800E+02, 1.820E+02, 1.840E+02, 1.860E+02, 1.880E+02, 1.900E+02, 1.920E+02, 1.940E+02, 1.960E+02, 1.980E+02, 2.000E+02, 2.020E+02, 2.040E+02, 2.060E+02, 2.080E+02, 2.100E+02, 2.120E+02, 2.140E+02, 2.160E+02, 2.180E+02, 2.200E+02, 2.220E+02, 2.240E+02, 2.260E+02, 2.280E+02, 2.300E+02, 2.320E+02, 2.340E+02, 2.360E+02, 2.380E+02, 2.400E+02, 2.420E+02, 2.440E+02, 2.460E+02, 2.480E+02, 2.500E+02, 2.520E+02, 2.540E+02, 2.560E+02, 2.580E+02, 2.600E+02, 2.620E+02, 2.640E+02, 2.660E+02, 2.680E+02, 2.700E+02, 2.720E+02, 2.740E+02, 2.760E+02, 2.780E+02, 2.800E+02, 2.820E+02, 2.840E+02, 2.860E+02, 2.880E+02, 2.900E+02, 2.920E+02, 2.940E+02, 2.960E+02, 2.980E+02, 3.000E+02, 3.020E+02, 3.040E+02, 3.060E+02, 3.080E+02, 3.100E+02, 3.120E+02, 3.140E+02, 3.160E+02, 3.180E+02, 3.200E+02, 3.220E+02, 3.240E+02, 3.260E+02, 3.280E+02, 3.300E+02, 3.320E+02, 3.340E+02, 3.360E+02, 3.380E+02, 3.400E+02, 3.420E+02, 3.440E+02, 3.460E+02, 3.480E+02, 3.500E+02, 3.520E+02, 3.540E+02, 3.560E+02, 3.580E+02, 3.600E+02, 3.620E+02, 3.640E+02, 3.660E+02, 3.680E+02, 3.700E+02, 3.720E+02, 3.740E+02, 3.760E+02, 3.780E+02, 3.800E+02, 3.820E+02, 3.840E+02, 3.860E+02, 3.880E+02, 3.900E+02, 3.920E+02, 3.940E+02, 3.960E+02, 3.980E+02])+273.15
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self.density.data = np.array([ 9.917E+02, 9.898E+02, 9.879E+02, 9.860E+02, 9.841E+02, 9.822E+02, 9.803E+02, 9.784E+02, 9.765E+02, 9.746E+02, 9.728E+02, 9.709E+02, 9.690E+02, 9.672E+02, 9.653E+02, 9.635E+02, 9.616E+02, 9.598E+02, 9.579E+02, 9.561E+02, 9.542E+02, 9.524E+02, 9.506E+02, 9.487E+02, 9.469E+02, 9.451E+02, 9.433E+02, 9.415E+02, 9.397E+02, 9.378E+02, 9.360E+02, 9.342E+02, 9.324E+02, 9.306E+02, 9.288E+02, 9.270E+02, 9.252E+02, 9.235E+02, 9.217E+02, 9.199E+02, 9.181E+02, 9.163E+02, 9.145E+02, 9.128E+02, 9.110E+02, 9.092E+02, 9.074E+02, 9.056E+02, 9.039E+02, 9.021E+02, 9.003E+02, 8.986E+02, 8.968E+02, 8.950E+02, 8.933E+02, 8.915E+02, 8.897E+02, 8.880E+02, 8.862E+02, 8.844E+02, 8.827E+02, 8.809E+02, 8.791E+02, 8.774E+02, 8.756E+02, 8.738E+02, 8.721E+02, 8.703E+02, 8.685E+02, 8.668E+02, 8.650E+02, 8.632E+02, 8.615E+02, 8.597E+02, 8.579E+02, 8.562E+02, 8.544E+02, 8.526E+02, 8.509E+02, 8.491E+02, 8.473E+02, 8.455E+02, 8.437E+02, 8.420E+02, 8.402E+02, 8.384E+02, 8.366E+02, 8.348E+02, 8.330E+02, 8.312E+02, 8.294E+02, 8.276E+02, 8.258E+02, 8.240E+02, 8.222E+02, 8.204E+02, 8.186E+02, 8.168E+02, 8.150E+02, 8.132E+02, 8.114E+02, 8.095E+02, 8.077E+02, 8.059E+02, 8.040E+02, 8.022E+02, 8.004E+02, 7.985E+02, 7.967E+02, 7.948E+02, 7.930E+02, 7.911E+02, 7.892E+02, 7.874E+02, 7.855E+02, 7.836E+02, 7.818E+02, 7.799E+02, 7.780E+02, 7.761E+02, 7.742E+02, 7.723E+02, 7.704E+02, 7.685E+02, 7.666E+02, 7.646E+02, 7.627E+02, 7.608E+02, 7.588E+02, 7.569E+02, 7.550E+02, 7.530E+02, 7.510E+02, 7.491E+02, 7.471E+02, 7.451E+02, 7.432E+02, 7.412E+02, 7.392E+02, 7.372E+02, 7.352E+02, 7.332E+02, 7.311E+02, 7.291E+02, 7.271E+02, 7.250E+02, 7.230E+02, 7.210E+02, 7.189E+02, 7.168E+02, 7.148E+02, 7.127E+02, 7.106E+02, 7.085E+02, 7.064E+02, 7.043E+02, 7.022E+02, 7.001E+02, 6.979E+02, 6.958E+02, 6.936E+02, 6.915E+02, 6.893E+02, 6.872E+02, 6.850E+02, 6.828E+02, 6.806E+02, 6.784E+02, 6.762E+02, 6.740E+02, 6.717E+02, 6.695E+02, 6.673E+02, 6.650E+02, 6.627E+02, 6.605E+02, 6.582E+02, 6.559E+02, 6.536E+02, 6.513E+02, 6.490E+02, 6.466E+02, 6.443E+02, 6.420E+02, 6.396E+02, 6.372E+02, 6.349E+02, 6.325E+02, 6.301E+02, 6.277E+02, 6.253E+02, 6.228E+02, 6.204E+02, 6.179E+02, 6.155E+02, 6.130E+02, 6.105E+02, 6.080E+02, 6.055E+02, 6.030E+02, 6.005E+02, 5.980E+02, 5.954E+02, 5.929E+02, 5.903E+02, 5.877E+02, 5.851E+02, 5.825E+02, 5.799E+02, 5.773E+02, 5.747E+02, 5.720E+02, 5.693E+02, 5.667E+02, 5.640E+02, 5.613E+02, 5.586E+02, 5.559E+02, 5.531E+02, 5.504E+02])
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self.specific_heat.data = np.array([ 3.310E-01, 3.340E-01, 3.380E-01, 3.410E-01, 3.450E-01, 3.480E-01, 3.520E-01, 3.550E-01, 3.580E-01, 3.620E-01, 3.650E-01, 3.690E-01, 3.720E-01, 3.750E-01, 3.790E-01, 3.820E-01, 3.860E-01, 3.890E-01, 3.930E-01, 3.960E-01, 3.990E-01, 4.030E-01, 4.060E-01, 4.100E-01, 4.130E-01, 4.160E-01, 4.200E-01, 4.230E-01, 4.270E-01, 4.300E-01, 4.330E-01, 4.370E-01, 4.400E-01, 4.440E-01, 4.470E-01, 4.510E-01, 4.540E-01, 4.570E-01, 4.610E-01, 4.640E-01, 4.680E-01, 4.710E-01, 4.740E-01, 4.780E-01, 4.810E-01, 4.850E-01, 4.880E-01, 4.920E-01, 4.950E-01, 4.980E-01, 5.020E-01, 5.050E-01, 5.090E-01, 5.120E-01, 5.150E-01, 5.190E-01, 5.220E-01, 5.260E-01, 5.290E-01, 5.330E-01, 5.360E-01, 5.390E-01, 5.430E-01, 5.460E-01, 5.500E-01, 5.530E-01, 5.560E-01, 5.600E-01, 5.630E-01, 5.670E-01, 5.700E-01, 5.730E-01, 5.770E-01, 5.800E-01, 5.840E-01, 5.870E-01, 5.910E-01, 5.940E-01, 5.970E-01, 6.010E-01, 6.040E-01, 6.080E-01, 6.110E-01, 6.140E-01, 6.180E-01, 6.210E-01, 6.250E-01, 6.280E-01, 6.320E-01, 6.350E-01, 6.380E-01, 6.420E-01, 6.450E-01, 6.490E-01, 6.520E-01, 6.550E-01, 6.590E-01, 6.620E-01, 6.660E-01, 6.690E-01, 6.730E-01, 6.760E-01, 6.790E-01, 6.830E-01, 6.860E-01, 6.900E-01, 6.930E-01, 6.960E-01, 7.000E-01, 7.030E-01, 7.070E-01, 7.100E-01, 7.130E-01, 7.170E-01, 7.200E-01, 7.240E-01, 7.270E-01, 7.310E-01, 7.340E-01, 7.370E-01, 7.410E-01, 7.440E-01, 7.480E-01, 7.510E-01, 7.540E-01, 7.580E-01, 7.610E-01, 7.650E-01, 7.680E-01, 7.720E-01, 7.750E-01, 7.780E-01, 7.820E-01, 7.850E-01, 7.890E-01, 7.920E-01, 7.950E-01, 7.990E-01, 8.020E-01, 8.060E-01, 8.090E-01, 8.130E-01, 8.160E-01, 8.190E-01, 8.230E-01, 8.260E-01, 8.300E-01, 8.330E-01, 8.360E-01, 8.400E-01, 8.430E-01, 8.470E-01, 8.500E-01, 8.540E-01, 8.570E-01, 8.600E-01, 8.640E-01, 8.670E-01, 8.710E-01, 8.740E-01, 8.770E-01, 8.810E-01, 8.840E-01, 8.880E-01, 8.910E-01, 8.940E-01, 8.980E-01, 9.010E-01, 9.050E-01, 9.080E-01, 9.120E-01, 9.150E-01, 9.180E-01, 9.220E-01, 9.250E-01, 9.290E-01, 9.320E-01, 9.350E-01, 9.390E-01, 9.420E-01, 9.460E-01, 9.490E-01, 9.530E-01, 9.560E-01, 9.590E-01, 9.630E-01, 9.660E-01, 9.700E-01, 9.730E-01, 9.760E-01, 9.800E-01, 9.830E-01, 9.870E-01, 9.900E-01, 9.940E-01, 9.970E-01, 1.000E+00, 1.000E+00, 1.010E+00, 1.010E+00, 1.010E+00, 1.020E+00, 1.020E+00, 1.020E+00, 1.030E+00, 1.030E+00, 1.030E+00, 1.040E+00, 1.040E+00, 1.040E+00, 1.050E+00, 1.050E+00, 1.050E+00, 1.060E+00, 1.060E+00, 1.060E+00, 1.070E+00, 1.070E+00, 1.080E+00, 1.080E+00])*1e3
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self.conductivity.data = np.array([ 8.600E-02, 8.600E-02, 8.600E-02, 8.500E-02, 8.500E-02, 8.400E-02, 8.400E-02, 8.400E-02, 8.300E-02, 8.300E-02, 8.300E-02, 8.200E-02, 8.200E-02, 8.100E-02, 8.100E-02, 8.100E-02, 8.000E-02, 8.000E-02, 8.000E-02, 7.900E-02, 7.900E-02, 7.800E-02, 7.800E-02, 7.800E-02, 7.700E-02, 7.700E-02, 7.600E-02, 7.600E-02, 7.600E-02, 7.500E-02, 7.500E-02, 7.500E-02, 7.400E-02, 7.400E-02, 7.300E-02, 7.300E-02, 7.300E-02, 7.200E-02, 7.200E-02, 7.200E-02, 7.100E-02, 7.100E-02, 7.000E-02, 7.000E-02, 7.000E-02, 6.900E-02, 6.900E-02, 6.900E-02, 6.800E-02, 6.800E-02, 6.700E-02, 6.700E-02, 6.700E-02, 6.600E-02, 6.600E-02, 6.600E-02, 6.500E-02, 6.500E-02, 6.400E-02, 6.400E-02, 6.400E-02, 6.300E-02, 6.300E-02, 6.300E-02, 6.200E-02, 6.200E-02, 6.100E-02, 6.100E-02, 6.100E-02, 6.000E-02, 6.000E-02, 6.000E-02, 5.900E-02, 5.900E-02, 5.800E-02, 5.800E-02, 5.800E-02, 5.700E-02, 5.700E-02, 5.700E-02, 5.600E-02, 5.600E-02, 5.500E-02, 5.500E-02, 5.500E-02, 5.400E-02, 5.400E-02, 5.400E-02, 5.300E-02, 5.300E-02, 5.200E-02, 5.200E-02, 5.200E-02, 5.100E-02, 5.100E-02, 5.100E-02, 5.000E-02, 5.000E-02, 4.900E-02, 4.900E-02, 4.900E-02, 4.800E-02, 4.800E-02, 4.800E-02, 4.700E-02, 4.700E-02, 4.600E-02, 4.600E-02, 4.600E-02, 4.500E-02, 4.500E-02, 4.500E-02, 4.400E-02, 4.400E-02, 4.300E-02, 4.300E-02, 4.300E-02, 4.200E-02, 4.200E-02, 4.200E-02, 4.100E-02, 4.100E-02, 4.000E-02, 4.000E-02, 4.000E-02, 3.900E-02, 3.900E-02, 3.900E-02, 3.800E-02, 3.800E-02, 3.700E-02, 3.700E-02, 3.700E-02, 3.600E-02, 3.600E-02, 3.600E-02, 3.500E-02, 3.500E-02, 3.400E-02, 3.400E-02, 3.400E-02, 3.300E-02, 3.300E-02, 3.200E-02, 3.200E-02, 3.200E-02, 3.100E-02, 3.100E-02, 3.100E-02, 3.000E-02, 3.000E-02, 2.900E-02, 2.900E-02, 2.900E-02, 2.800E-02, 2.800E-02, 2.800E-02, 2.700E-02, 2.700E-02, 2.600E-02, 2.600E-02, 2.600E-02, 2.500E-02, 2.500E-02, 2.500E-02, 2.400E-02, 2.400E-02, 2.300E-02, 2.300E-02, 2.300E-02, 2.200E-02, 2.200E-02, 2.200E-02, 2.100E-02, 2.100E-02, 2.000E-02, 2.000E-02, 2.000E-02, 1.900E-02, 1.900E-02, 1.900E-02, 1.800E-02, 1.800E-02, 1.700E-02, 1.700E-02, 1.700E-02, 1.600E-02, 1.600E-02, 1.600E-02, 1.500E-02, 1.500E-02, 1.400E-02, 1.400E-02, 1.400E-02, 1.300E-02, 1.300E-02, 1.300E-02, 1.200E-02, 1.200E-02, 1.100E-02, 1.100E-02, 1.100E-02, 1.000E-02, 1.000E-02, 1.000E-02, 9.000E-03, 9.000E-03, 8.000E-03, 8.000E-03, 8.000E-03, 7.000E-03, 7.000E-03, 7.000E-03, 6.000E-03, 6.000E-03, 5.000E-03, 5.000E-03, 5.000E-03, 4.000E-03, 4.000E-03])
|
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self.viscosity.data = np.array([ 5.100E+01, 4.720E+01, 4.380E+01, 4.070E+01, 3.800E+01, 3.550E+01, 3.320E+01, 3.110E+01, 2.920E+01, 2.750E+01, 2.590E+01, 2.440E+01, 2.310E+01, 2.180E+01, 2.070E+01, 1.960E+01, 1.860E+01, 1.770E+01, 1.690E+01, 1.610E+01, 1.530E+01, 1.460E+01, 1.400E+01, 1.340E+01, 1.280E+01, 1.230E+01, 1.180E+01, 1.130E+01, 1.080E+01, 1.040E+01, 1.000E+01, 9.650E+00, 9.290E+00, 8.950E+00, 8.630E+00, 8.320E+00, 8.030E+00, 7.760E+00, 7.490E+00, 7.240E+00, 7.000E+00, 6.770E+00, 6.560E+00, 6.350E+00, 6.150E+00, 5.960E+00, 5.780E+00, 5.600E+00, 5.430E+00, 5.270E+00, 5.120E+00, 4.970E+00, 4.830E+00, 4.690E+00, 4.560E+00, 4.430E+00, 4.310E+00, 4.190E+00, 4.080E+00, 3.970E+00, 3.860E+00, 3.760E+00, 3.660E+00, 3.570E+00, 3.480E+00, 3.390E+00, 3.300E+00, 3.220E+00, 3.140E+00, 3.070E+00, 2.990E+00, 2.920E+00, 2.850E+00, 2.780E+00, 2.710E+00, 2.650E+00, 2.590E+00, 2.530E+00, 2.470E+00, 2.410E+00, 2.360E+00, 2.310E+00, 2.250E+00, 2.210E+00, 2.160E+00, 2.110E+00, 2.060E+00, 2.020E+00, 1.980E+00, 1.930E+00, 1.890E+00, 1.850E+00, 1.810E+00, 1.780E+00, 1.740E+00, 1.700E+00, 1.670E+00, 1.630E+00, 1.600E+00, 1.570E+00, 1.540E+00, 1.510E+00, 1.480E+00, 1.450E+00, 1.420E+00, 1.390E+00, 1.370E+00, 1.340E+00, 1.310E+00, 1.290E+00, 1.260E+00, 1.240E+00, 1.220E+00, 1.190E+00, 1.170E+00, 1.150E+00, 1.130E+00, 1.110E+00, 1.090E+00, 1.070E+00, 1.050E+00, 1.030E+00, 1.010E+00, 9.950E-01, 9.770E-01, 9.600E-01, 9.430E-01, 9.270E-01, 9.110E-01, 8.950E-01, 8.800E-01, 8.650E-01, 8.500E-01, 8.360E-01, 8.220E-01, 8.080E-01, 7.950E-01, 7.810E-01, 7.690E-01, 7.560E-01, 7.440E-01, 7.320E-01, 7.200E-01, 7.080E-01, 6.970E-01, 6.860E-01, 6.750E-01, 6.640E-01, 6.540E-01, 6.430E-01, 6.330E-01, 6.240E-01, 6.140E-01, 6.050E-01, 5.950E-01, 5.860E-01, 5.770E-01, 5.690E-01, 5.600E-01, 5.520E-01, 5.430E-01, 5.350E-01, 5.270E-01, 5.200E-01, 5.120E-01, 5.050E-01, 4.970E-01, 4.900E-01, 4.830E-01, 4.760E-01, 4.690E-01, 4.630E-01, 4.560E-01, 4.500E-01, 4.430E-01, 4.370E-01, 4.310E-01, 4.250E-01, 4.190E-01, 4.130E-01, 4.080E-01, 4.020E-01, 3.970E-01, 3.910E-01, 3.860E-01, 3.810E-01, 3.760E-01, 3.710E-01, 3.660E-01, 3.610E-01, 3.560E-01, 3.520E-01, 3.470E-01, 3.420E-01, 3.380E-01, 3.340E-01, 3.290E-01, 3.250E-01, 3.210E-01, 3.170E-01, 3.130E-01, 3.090E-01, 3.050E-01, 3.010E-01, 2.980E-01, 2.940E-01, 2.900E-01, 2.870E-01, 2.830E-01, 2.800E-01, 2.760E-01, 2.730E-01, 2.700E-01, 2.670E-01, 2.630E-01, 2.600E-01, 2.570E-01, 2.540E-01, 2.510E-01, 2.480E-01])/1e3
|
||||
self.saturation_pressure.data = np.array([ np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, np.NAN, 1.000E-03, 1.000E-03, 1.000E-03, 1.000E-03, 1.000E-03, 1.000E-03, 1.000E-03, 2.000E-03, 2.000E-03, 2.000E-03, 3.000E-03, 3.000E-03, 4.000E-03, 4.000E-03, 5.000E-03, 6.000E-03, 6.000E-03, 7.000E-03, 8.000E-03, 9.000E-03, 1.000E-02, 1.200E-02, 1.300E-02, 1.500E-02, 1.600E-02, 1.800E-02, 2.000E-02, 2.200E-02, 2.500E-02, 2.700E-02, 3.000E-02, 3.300E-02, 3.600E-02, 4.000E-02, 4.400E-02, 4.800E-02, 5.200E-02, 5.700E-02, 6.200E-02, 6.800E-02, 7.300E-02, 7.900E-02, 8.600E-02, 9.300E-02, 1.000E-01, 1.080E-01, 1.170E-01, 1.250E-01, 1.350E-01, 1.450E-01, 1.550E-01, 1.660E-01, 1.780E-01, 1.900E-01, 2.030E-01, 2.160E-01, 2.300E-01, 2.450E-01, 2.610E-01, 2.770E-01, 2.940E-01, 3.120E-01, 3.310E-01, 3.500E-01, 3.700E-01, 3.910E-01, 4.140E-01, 4.370E-01, 4.600E-01, 4.850E-01, 5.110E-01, 5.380E-01, 5.660E-01, 5.950E-01, 6.250E-01, 6.560E-01, 6.880E-01, 7.210E-01, 7.550E-01, 7.910E-01, 8.280E-01, 8.660E-01, 9.050E-01, 9.460E-01, 9.870E-01, 1.030E+00, 1.080E+00, 1.120E+00, 1.170E+00, 1.220E+00, 1.270E+00, 1.320E+00, 1.370E+00, 1.420E+00, 1.480E+00, 1.540E+00, 1.600E+00, 1.660E+00, 1.720E+00, 1.780E+00, 1.840E+00, 1.910E+00, 1.980E+00, 2.050E+00, 2.120E+00, 2.190E+00, 2.270E+00, 2.340E+00, 2.420E+00, 2.500E+00, 2.580E+00, 2.670E+00, 2.750E+00, 2.840E+00, 2.920E+00, 3.020E+00, 3.110E+00, 3.200E+00, 3.300E+00, 3.390E+00, 3.490E+00, 3.590E+00, 3.700E+00, 3.800E+00, 3.910E+00, 4.020E+00, 4.130E+00, 4.240E+00, 4.350E+00, 4.470E+00, 4.590E+00, 4.710E+00, 4.830E+00, 4.960E+00, 5.080E+00, 5.210E+00, 5.340E+00, 5.470E+00, 5.610E+00, 5.740E+00, 5.880E+00, 6.020E+00, 6.160E+00, 6.310E+00, 6.450E+00, 6.600E+00, 6.750E+00, 6.900E+00, 7.060E+00, 7.210E+00, 7.370E+00, 7.530E+00, 7.690E+00, 7.860E+00, 8.020E+00, 8.190E+00, 8.360E+00, 8.530E+00, 8.710E+00, 8.880E+00, 9.060E+00, 9.240E+00, 9.430E+00, 9.610E+00, 9.800E+00, 9.990E+00, 1.020E+01, 1.040E+01, 1.060E+01, 1.080E+01, 1.100E+01, 1.120E+01, 1.140E+01, 1.160E+01, 1.180E+01, 1.200E+01, 1.220E+01, 1.240E+01, 1.260E+01, 1.280E+01, 1.310E+01, 1.330E+01, 1.350E+01])*1e3
|
||||
self.Tmin = np.min(self.temperature.data)
|
||||
self.Tmax = np.max(self.temperature.data)
|
||||
self.TminPsat = np.min(self.temperature.data[~np.isnan(self.saturation_pressure.data)])
|
||||
self.name = "S800"
|
||||
self.description = "Syltherm 800"
|
||||
self.reference = "Dow Chemical Company - FLUIDFILE Software accessed February 2016"
|
||||
self.reshapeAll()
|
||||
|
||||
|
||||
|
||||
|
||||
114
dev/incompressible_liquids/json/S800.json
Normal file
114
dev/incompressible_liquids/json/S800.json
Normal file
@@ -0,0 +1,114 @@
|
||||
{
|
||||
"T_freeze": {
|
||||
"NRMS": null,
|
||||
"coeffs": "null",
|
||||
"type": "notdefined"
|
||||
},
|
||||
"Tbase": 4.521500e+02,
|
||||
"Tmax": 6.711500e+02,
|
||||
"Tmin": 2.331500e+02,
|
||||
"TminPsat": 3.071500e+02,
|
||||
"conductivity": {
|
||||
"NRMS": 3.512507e-03,
|
||||
"coeffs": [
|
||||
[
|
||||
4.509024e-02
|
||||
],
|
||||
[
|
||||
-1.879693e-04
|
||||
],
|
||||
[
|
||||
4.139256e-11
|
||||
],
|
||||
[
|
||||
-2.987631e-12
|
||||
]
|
||||
],
|
||||
"type": "polynomial"
|
||||
},
|
||||
"density": {
|
||||
"NRMS": 6.451330e-05,
|
||||
"coeffs": [
|
||||
[
|
||||
7.938949e+02
|
||||
],
|
||||
[
|
||||
-9.273680e-01
|
||||
],
|
||||
[
|
||||
-4.763441e-04
|
||||
],
|
||||
[
|
||||
-1.674039e-06
|
||||
]
|
||||
],
|
||||
"type": "polynomial"
|
||||
},
|
||||
"description": "Syltherm 800",
|
||||
"mass2input": {
|
||||
"NRMS": null,
|
||||
"coeffs": "null",
|
||||
"type": "notdefined"
|
||||
},
|
||||
"mole2input": {
|
||||
"NRMS": null,
|
||||
"coeffs": "null",
|
||||
"type": "notdefined"
|
||||
},
|
||||
"name": "S800",
|
||||
"reference": "Dow Chemical Company - FLUIDFILE Software accessed February 2016",
|
||||
"saturation_pressure": {
|
||||
"NRMS": 7.477874e-03,
|
||||
"coeffs": [
|
||||
-2.322952e+03,
|
||||
-1.469809e+02,
|
||||
-1.396011e+01
|
||||
],
|
||||
"type": "exponential"
|
||||
},
|
||||
"specific_heat": {
|
||||
"NRMS": 1.321123e-03,
|
||||
"coeffs": [
|
||||
[
|
||||
7.050167e+02
|
||||
],
|
||||
[
|
||||
1.707952e+00
|
||||
],
|
||||
[
|
||||
-9.204780e-06
|
||||
],
|
||||
[
|
||||
-5.660168e-08
|
||||
]
|
||||
],
|
||||
"type": "polynomial"
|
||||
},
|
||||
"viscosity": {
|
||||
"NRMS": 8.195934e-03,
|
||||
"coeffs": [
|
||||
[
|
||||
-6.701381e+00
|
||||
],
|
||||
[
|
||||
-9.157252e-03
|
||||
],
|
||||
[
|
||||
1.925359e-05
|
||||
],
|
||||
[
|
||||
-5.658791e-08
|
||||
]
|
||||
],
|
||||
"type": "exppolynomial"
|
||||
},
|
||||
"volume2input": {
|
||||
"NRMS": null,
|
||||
"coeffs": "null",
|
||||
"type": "notdefined"
|
||||
},
|
||||
"xbase": 0.000000e+00,
|
||||
"xid": "pure",
|
||||
"xmax": 1.000000e+00,
|
||||
"xmin": 0.000000e+00
|
||||
}
|
||||
Reference in New Issue
Block a user