Fix k_ij for PC-SAFT

e97aaad9 · Ian Bell · 2ede6dec · e97aaad9
Commit e97aaad9 authored 2 years ago by Ian Bell
--- a/doc/source/models/PCSAFT.ipynb
+++ b/doc/source/models/PCSAFT.ipynb
@@ -75,7 +75,7 @@
   "source": [
    "## Adjusting k_ij\n",
    "\n",
-    "Fine-tuned values of $k_{ij}$ can be provided when instantiating the model, for Peng-Robinson and SRK.  A complete matrix of all the $k_{ij}$ values must be provided. This allows for asymmetric mixing models in which $k_{ij}\\neq k_{ji}$."
+    "Fine-tuned values of $k_{ij}$ can be provided when instantiating the model.  A complete matrix of all the $k_{ij}$ values must be provided. This allows for asymmetric mixing models in which $k_{ij}\\neq k_{ji}$."
   ]
  },
  {
@@ -87,7 +87,7 @@
    {
     "data": {
      "text/plain": [
-       "<teqp.teqp.PCSAFTEOS at 0x19478910bf0>"
+       "<teqp.teqp.PCSAFTEOS at 0x26ec5dde870>"
      ]
     },
     "execution_count": 3,
@@ -97,7 +97,7 @@
   ],
   "source": [
    "k_01 = 0.01; k_10 = k_01\n",
-    "kmat = [[0,k_01,0],[k_01,0,0],[0,0,0]]\n",
+    "kmat = [[0,k_01,0],[k_10,0,0],[0,0,0]]\n",
    "teqp.PCSAFTEOS(coeffs, kmat)"
   ]
  },

 %% Cell type:markdown id:f406bbb5 tags:
 # PC-SAFT
 The PC-SAFT implementation in teqp is based on the implementation of Gross and Sadowski (https://doi.org/10.1021/ie0003887), with the typo from their paper fixed.  It does NOT include the association contribution, only the dispersive contributions.
 The model in teqp requires the user to specify the values of ``sigma``, ``epsilon/kB``, and ``m`` for each substance.  A very few substances are hardcoded in teqp, for testing purposes.
 %% Cell type:code id:7bbd7129 tags:
 ``` python
 import teqp
 TeXkey = 'Gross-IECR-2001'
 ms = [1.0, 1.6069, 2.0020]
 eoverk = [150.03, 191.42, 208.11]
 sigmas = [3.7039, 3.5206, 3.6184]
 coeffs = []
 for i in range(len(ms)):
    c = teqp.SAFTCoeffs()
    c.m = ms[i]
    c.epsilon_over_k = eoverk[i]
    c.sigma_Angstrom = sigmas[i]
    coeffs.append(c)
 model = teqp.PCSAFTEOS(coeffs)
 ```
 %% Cell type:markdown id:578630c8 tags:
 The model parameters can be queried:
 %% Cell type:code id:d4e47e54 tags:
 ``` python
 model.get_m(), model.get_epsilon_over_k_K(), model.get_sigma_Angstrom()
 ```
 %% Output
    (array([1.    , 1.6069, 2.002 ]),
     array([150.03, 191.42, 208.11]),
     array([3.7039, 3.5206, 3.6184]))
 %% Cell type:markdown id:5cbb382d tags:
 ## Adjusting k_ij
-Fine-tuned values of $k_{ij}$ can be provided when instantiating the model, for Peng-Robinson and SRK.  A complete matrix of all the $k_{ij}$ values must be provided. This allows for asymmetric mixing models in which $k_{ij}\neq k_{ji}$.
+Fine-tuned values of $k_{ij}$ can be provided when instantiating the model.  A complete matrix of all the $k_{ij}$ values must be provided. This allows for asymmetric mixing models in which $k_{ij}\neq k_{ji}$.
 %% Cell type:code id:a32c41b5 tags:
 ``` python
 k_01 = 0.01; k_10 = k_01
-kmat = [[0,k_01,0],[k_01,0,0],[0,0,0]]
+kmat = [[0,k_01,0],[k_10,0,0],[0,0,0]]
 teqp.PCSAFTEOS(coeffs, kmat)
 ```
 %% Output
-    <teqp.teqp.PCSAFTEOS at 0x19478910bf0>
+    <teqp.teqp.PCSAFTEOS at 0x26ec5dde870>
 %% Cell type:markdown id:ca52e844 tags:
 ## Superancillary
 The superancillary equation for PC-SAFT has been developed, and is much more involved than that of the cubic EOS. As a consequence, the superancillary equation has been provided as a separate package rather than integrating it into to teqp to minimize the computational overhead. It can be installed from PYPI with: ``pip install PCSAFTsuperanc``