Welcome to Sur’s documentation!¶
Sur is python library to calculate and plot envelopes and flashes for multicompound mixtures using equation of states.
It have been designed to be easy to use interactively, for example using Jupyter, although it could be used as a “backend” to develop your own programs.
Contents¶
Install¶
Sur is still under development (considered in alpha stage), but it’s ready to experiment with.
Attention
By the moment, Sur only works with Python 2.7.x. It may change in future versions.
For Windows users¶
Under Windows, Sur is easily installable via a recent version of [pip](https://pip.pypa.io/en/stable/). It’s bundle in recents version of Python.
Open a command line (Start » Run »
cmd.exe) and first, upgrade the version of pip (just in case):pip install -U pip
Then, in a 32bits OS:
pip install https://ci.appveyor.com/api/buildjobs/satlj7c3vteww2wi/artifacts/dist/sur-1.0.postf6ee05dfcf5c-cp27-cp27m-win32.whl
Or for 64 bits:
pip install https://ci.appveyor.com/api/buildjobs/0yyuyr7mb4skhk1l/artifacts/dist/sur-1.0.postf6ee05dfcf5c-cp27-cp27m-win_amd64.whl
Note
Those links are for the last stable (but still in develop) versions. You can try newer ones going to https://ci.appveyor.com/project/mgaitan/envelope-sur » Enviroment (x86 or x64) » Artifacts, and copy the the link to the .whl file)
For Linux users¶
(to do)
Sur crash course¶
This is a tutorial to dive in the key concepts of Sur and its usage under an interactive session.
Getting up¶
Sur has an object-oriented design. This means that the library provides classes to interact with. The very first step is to import the classes and some helper functions we will need.
In [1]:
from sur import Mixture, Compound, EosSetup, EosEnvelope, EosFlash, ExperimentalEnvelope, setup_database
We also need to create the database and load the built-in dataset of pure components constants. By default, Sur uses a database in memory, which is not persistence.
In [2]:
setup_database()
We are ready to start.
Define a mixture¶
As you know, a mixture is two or more compound which have been combined
such that each substance retains its own chemical identity. A
Mixture in sur is the same: a combination of compounds, each one
with its fraction (i.e, the sum of the fractions of all the compounds in
the mixture must be 1)
In [3]:
mixture = Mixture()
There are several ways to add compounds to a Mixture instance. For
instance, you can use as if it would be a dictionary.
In [4]:
mixture["co2"] = 0.5
mixture["n-decane"] = 0.25
mixture["methane"] = 0.25
In order to facilitate the definition of interaction matrixes, we could sort each fraction by its molecular weight, no matter the order we added them.
In [5]:
mixture.sort()
In [6]:
mixture
Out[6]:
[(<Compound: METHANE>, Decimal('0.25')), (<Compound: CARBON DIOXIDE>, Decimal('0.5')), (<Compound: n-DECANE>, Decimal('0.25'))]
Setup the EoS¶
To simulate the envelope, we need to choice and configurate an Equation
of State. This is done via an EosSetup instance. For example, to use
an RK-PR EoS with parameters \(k_{ij}\) and \(l_{ij}\) as
constants, we create a setup object like this:
In [7]:
setup = EosSetup.objects.create(eos='RKPR', kij_mode=EosSetup.CONSTANTS, lij_mode=EosSetup.CONSTANTS)
By default, the interaction parameter between two compounds is 0.0 (however, Sur may provide a better choice when appropiated). To customize the calculation with our own parameters, we can override the default values.
In [8]:
setup.set_interaction('kij', 'methane', 'co2', 0.1)
setup.set_interaction('kij', 'co2', 'n-decane', 0.091)
Out[8]:
<KijInteractionParameter: RKPR [<Compound: CARBON DIOXIDE>, <Compound: n-DECANE>]: 0.091>
A setup object is independent of a mixture. It just define the equation to be used and the bag of parameters to tune it when we simulate an envelope for a particular mixture, but to have interaction between compounds that don’t belong to a mixture is perfectly valid.
After set the interaction parameter, we probably want to see how the interaction matrix looks like for our particular compounds
In [9]:
setup.kij(mixture)
Out[9]:
array([[ 0. , 0.1 , 0. ],
[ 0.1 , 0. , 0.091],
[ 0. , 0.091, 0. ]])
By the way, it’d be also possible to define the whole matrix for a
particular mixture at once, using the method
setup.set_interaction_matrix()
Simulate the envelope¶
Having the mixture and the setup, we are able to obtain a the simulated envelope.
In [10]:
envelope = mixture.get_envelope(setup)
In this case, envelope is an instance of EosEnvelope, i.e. an
envelope that have been created via an equation of state.
Any kind of envelope has many attributes ready to be inspected. For instance, we have the array of pressure and temperature
In [11]:
envelope.p
Out[11]:
array([ 1.44200000e-02, 1.64600000e-02, 2.01600000e-02,
2.45700000e-02, 2.97800000e-02, 3.59200000e-02,
4.31100000e-02, 5.14700000e-02, 6.11500000e-02,
7.22700000e-02, 8.49900000e-02, 9.94400000e-02,
1.15800000e-01, 1.34100000e-01, 1.54500000e-01,
1.77100000e-01, 2.02000000e-01, 2.29200000e-01,
2.58800000e-01, 2.90700000e-01, 3.24900000e-01,
4.05600000e-01, 5.23400000e-01, 6.71100000e-01,
8.54900000e-01, 1.08200000e+00, 1.36100000e+00,
1.70100000e+00, 2.11100000e+00, 2.60400000e+00,
3.19200000e+00, 3.88700000e+00, 4.70400000e+00,
5.65700000e+00, 6.75900000e+00, 8.02800000e+00,
9.47500000e+00, 1.11200000e+01, 1.29700000e+01,
1.50400000e+01, 1.73400000e+01, 1.98900000e+01,
2.26900000e+01, 2.57500000e+01, 2.90700000e+01,
3.26600000e+01, 3.65200000e+01, 4.06600000e+01,
4.50600000e+01, 4.97300000e+01, 5.46600000e+01,
5.98400000e+01, 6.52700000e+01, 7.09400000e+01,
7.71600000e+01, 8.40100000e+01, 9.15900000e+01,
1.00000000e+02, 1.09400000e+02, 1.18800000e+02,
1.27600000e+02, 1.35800000e+02, 1.43600000e+02,
1.50900000e+02, 1.54400000e+02, 1.64100000e+02,
1.70000000e+02, 1.75400000e+02, 1.80400000e+02,
1.84800000e+02, 1.88700000e+02, 1.92100000e+02,
1.95000000e+02, 1.97400000e+02, 1.99300000e+02,
2.00700000e+02, 2.01200000e+02, 2.01600000e+02,
2.01800000e+02, 2.02000000e+02, 2.02000000e+02,
2.01600000e+02, 2.01200000e+02, 2.00700000e+02,
2.00000000e+02, 1.99200000e+02, 1.98200000e+02,
1.97100000e+02, 1.95900000e+02, 1.94600000e+02,
1.93300000e+02, 1.90200000e+02, 1.88200000e+02,
1.86100000e+02, 1.83900000e+02, 1.81700000e+02,
1.79400000e+02, 1.74600000e+02, 1.72000000e+02,
1.66500000e+02, 1.60900000e+02, 1.55200000e+02,
1.49500000e+02, 1.43900000e+02, 1.38400000e+02,
1.33100000e+02, 1.28000000e+02, 1.23000000e+02,
1.18400000e+02, 1.13900000e+02, 1.09600000e+02,
1.05500000e+02, 1.01700000e+02, 9.79600000e+01,
9.44300000e+01, 9.10500000e+01, 8.78100000e+01,
8.47000000e+01, 8.17100000e+01, 7.88300000e+01,
7.60400000e+01, 7.33500000e+01, 7.07400000e+01,
6.82100000e+01, 6.57500000e+01, 6.33700000e+01,
6.10400000e+01, 5.87900000e+01, 5.65900000e+01,
5.44400000e+01, 5.23600000e+01, 5.03300000e+01,
4.83500000e+01, 4.64300000e+01, 4.45600000e+01,
4.27400000e+01, 4.09700000e+01, 3.92500000e+01,
3.75900000e+01, 3.59700000e+01, 3.44000000e+01,
3.28800000e+01, 3.14100000e+01, 2.99800000e+01,
2.86000000e+01, 2.72700000e+01, 2.59800000e+01,
2.47400000e+01, 2.35400000e+01, 2.23900000e+01,
2.12800000e+01, 2.02100000e+01, 1.91800000e+01,
1.81900000e+01, 1.72400000e+01, 1.63300000e+01,
1.54500000e+01, 1.46200000e+01, 1.38100000e+01,
1.30500000e+01, 1.23100000e+01, 1.16100000e+01,
1.09400000e+01, 1.03000000e+01, 9.69100000e+00,
9.11100000e+00, 8.55800000e+00, 8.03200000e+00,
7.53200000e+00, 7.05800000e+00, 6.60800000e+00,
6.18100000e+00, 5.77700000e+00, 5.39400000e+00,
5.03200000e+00])
In [12]:
envelope.t
Out[12]:
array([ 310. , 312.0833, 315.3334, 318.5817, 321.8256, 325.0618,
328.287 , 331.4979, 334.6908, 337.8618, 341.0071, 344.1223,
347.2033, 350.2456, 353.2444, 356.1952, 359.0929, 361.9326,
364.7092, 367.4176, 370.0526, 375.4492, 381.889 , 388.4249,
395.0497, 401.7551, 408.5312, 415.3667, 422.2482, 429.1612,
436.0893, 443.0145, 449.9174, 456.7773, 463.5724, 470.2797,
476.8758, 483.3365, 489.6373, 495.7541, 501.6625, 507.3389,
512.7602, 517.904 , 522.749 , 527.2748, 531.462 , 535.2922,
538.7482, 541.8137, 544.4731, 546.7121, 548.5169, 549.8788,
550.8162, 551.236 , 551.015 , 549.9858, 547.9151, 544.911 ,
541.2341, 536.9976, 532.2864, 527.1669, 524.4715, 515.914 ,
509.8688, 503.5958, 497.1301, 490.5047, 483.751 , 476.8995,
469.9794, 463.0191, 456.0457, 449.0857, 445.4863, 441.9006,
438.332 , 434.7837, 431.2588, 424.291 , 420.3194, 416.3945,
412.5202, 408.7 , 404.9371, 401.2346, 397.5952, 394.0213,
390.5151, 383.7132, 379.7462, 375.8867, 372.1359, 368.4946,
364.9629, 358.2265, 354.6604, 347.9187, 341.4057, 335.2389,
329.4222, 323.9512, 318.8144, 313.9956, 309.4744, 305.2285,
301.2344, 297.4685, 293.9078, 290.5301, 287.3146, 284.2421,
281.2947, 278.4564, 275.7124, 273.0497, 270.4565, 267.9224,
265.4384, 262.9962, 260.589 , 258.2107, 255.8562, 253.5209,
251.2014, 248.8943, 246.5974, 244.3085, 242.0261, 239.7491,
237.4765, 235.2078, 232.9426, 230.681 , 228.423 , 226.1689,
223.9189, 221.6736, 219.4335, 217.1993, 214.9716, 212.7511,
210.5385, 208.3345, 206.1399, 203.9553, 201.7815, 199.6192,
197.4689, 195.3314, 193.2072, 191.097 , 189.0011, 186.9202,
184.8547, 182.8049, 180.7714, 178.7545, 176.7545, 174.7718,
172.8065, 170.8589, 168.9294, 167.0179, 165.1248, 163.2502,
161.3942, 159.5569, 157.7385, 155.9389, 154.1583, 152.3968,
150.6543])
There is also equivalent arrays for critical points, if any. In our example there is just one point.
In [13]:
envelope.t_cri, envelope.p_cri
Out[13]:
(array([ 520.3626]), array([ 159.1]))
Plotting¶
In addition, an envelope object is able to generate a predefined Matplotlib figure. Before run it, if you are using Sur through Jupyter, may be handy to use the magic command to embed matplotlib figures directly in the document (instead of raise a popup window)
In [14]:
%matplotlib inline
In [15]:
fig = envelope.plot()
As we saved the figure object (fig), we can use the matplotlib
API to manipulate it
(changing aspect, size, span, colors..., in fact, anything we want),
export, etc.
In [16]:
from matplotlib import pyplot as plt
ax = fig.get_axes()[0]
ax.set_yticks([0] + ax.get_yticks()[1:])
ax.set_ylim((-50/3, 220))
ax.set_title('Sur rocks!')
plt.setp(ax.lines, linewidth=3)
plt.setp(ax.lines[1:], linestyle='--')
fig.set_size_inches(fig.get_size_inches() * 2)
fig
Out[16]:
However, if that is too much power to your goal, you can pass some
format directives (as in pyplot’s
`plot() <http://matplotlib.org/users/pyplot_tutorial.html>`__)
directly to the method’s parameters. For example:
In [17]:
envelope.plot(format='k');
In [18]:
envelope.plot(critical_point='^', format='--y');
Compare with experimental data¶
Constrant the simulation against a known experimental dataset for an evelope is possible. Here we’ll mock this experimental data modifing the simulated one, but you should get it from a reliable source
In [19]:
import numpy as np
n = envelope.p.size
p_experimental = envelope.p[np.arange(0, n, 7)] * 1.1
t_experimental = envelope.t[np.arange(0, n, 7)]
exp_envelope = mixture.experimental_envelope(t_experimental, p_experimental)
In this case, the exp_envelope object is an instance of
ExperimentalEnvelope. In many way it works identically than an
EosEnvelope (strictly, both are subclasses of the same base class), and
they share attribute and methods. Of course, the key difference for an
experimental envelope is that we don’t need to calculate, we just set
the arrays manually.
Another difference is that the default plot style is slightly different.
In [20]:
exp_fig = exp_envelope.plot()
By the way, many envelope’s figures can be chained, passing a base one
to the method plot() as the first parameter. For example, here we
plot both the simulated and the experimental envelopes in the same
figure
In [21]:
envelope.plot(exp_fig)
Out[21]:
Calculate a flash¶
A flash represents a separation of the mixture in two with the same
compounds but different fractions. In Sur, we can get a flash instance
through the method get_flash()
In [22]:
flash = mixture.get_flash(setup, t=400, p=100)
In [23]:
flash.vapour_mixture
Out[23]:
[(<Compound: METHANE>, Decimal('0.360497')), (<Compound: CARBON DIOXIDE>, Decimal('0.625358')), (<Compound: n-DECANE>, Decimal('0.014145'))]
In [24]:
flash.liquid_mixture.z
Out[24]:
array([ 0.116292, 0.348308, 0.5354 ])
Which is the same than
In [25]:
flash.x
Out[25]:
array([ 0.116292, 0.348308, 0.5354 ])
The liquid_mixture and vapour_mixture attributes are Mixture
objects, meaning we can get its own evelopes and the plot all together
In [26]:
le = flash.liquid_mixture.get_envelope(setup)
ve = flash.vapour_mixture.get_envelope(setup)
final_fig = envelope.plot(ve.plot(le.plot()))
Advanced examples¶
Attention
These notebook examples are very raw, created as an internal practice, with no deep explanation of each step done. However, they may be useful to discover further possibilities of Sur.
Modeling Golzapour’s synthetic oil¶
In [1]:
c = """METHANE
PROPANE
n-PENTANE
n-DECANE
n-HEXADECANE"""
In [2]:
f = """0.8232
0.0871
0.0505
0.0198
0.0194
"""
In [3]:
from sur import Mixture, EosSetup, setup_database
setup_database()
In [4]:
m = Mixture()
In [5]:
m.add_many(c, f)
In [6]:
m.sort()
m
Out[6]:
[(<Compound: METHANE>, Decimal('0.8232')), (<Compound: PROPANE>, Decimal('0.0871')), (<Compound: n-PENTANE>, Decimal('0.0505')), (<Compound: n-DECANE>, Decimal('0.0198')), (<Compound: n-HEXADECANE>, Decimal('0.0194'))]
In [7]:
from itertools import combinations
In [8]:
setup = EosSetup.objects.create(eos='RKPR', kij_mode=EosSetup.T_DEP, lij_mode=EosSetup.CONSTANTS)
In [9]:
for c1, c2 in combinations(m.compounds, 2):
t = c1.tc if c1.weight < c2.weight else c2.tc
setup.set_interaction('tstar', c1, c2, t)
In [10]:
setup.tstar(m)
Out[10]:
array([[ 0. , 190.564, 190.564, 190.564, 190.564],
[ 190.564, 0. , 369.83 , 369.83 , 369.83 ],
[ 190.564, 369.83 , 0. , 469.7 , 469.7 ],
[ 190.564, 369.83 , 469.7 , 0. , 617.7 ],
[ 190.564, 369.83 , 469.7 , 617.7 , 0. ]])
In [11]:
setup.set_interaction('k0', 'methane', 'propane', 0.0572)
setup.set_interaction('k0', 'methane', 'n-pentane', 0.05616)
setup.set_interaction('k0', 'methane', 'n-decane', 0.06891)
setup.set_interaction('k0', 'methane', 'n-hexadecane', 0.14031);
In [12]:
setup.k0(m)
Out[12]:
array([[ 0. , 0.0572 , 0.05616, 0.06891, 0.14031],
[ 0.0572 , 0. , 0. , 0. , 0. ],
[ 0.05616, 0. , 0. , 0. , 0. ],
[ 0.06891, 0. , 0. , 0. , 0. ],
[ 0.14031, 0. , 0. , 0. , 0. ]])
In [13]:
setup.set_interaction('lij', 'methane', 'propane', -0.00272)
setup.set_interaction('lij', 'methane', 'n-pentane', -0.06603)
setup.set_interaction('lij', 'methane', 'n-decane', -0.09227)
setup.set_interaction('lij', 'methane', 'n-hexadecane', -0.12441);
In [14]:
setup.lij(m)
Out[14]:
array([[ 0. , -0.00272 , -0.06603 , -0.09227 , -0.12441 ],
[-0.00272 , 0. , -0.010835, -0.032481, -0.023269],
[-0.06603 , -0.010835, 0. , -0.02353 , -0.012501],
[-0.09227 , -0.032481, -0.02353 , 0. , 0.049878],
[-0.12441 , -0.023269, -0.012501, 0.049878, 0. ]])
In [15]:
envelope = m.get_envelope(setup)
In [17]:
%matplotlib inline
In [19]:
envelope.plot();
Debug attributes¶
There is possible to see the raw input and output data that sur
interchange with the EnvelopeSur.exe fortran program.
In [21]:
print(envelope.input_txt)
5 NC
0.8232 0.0871 0.0505 0.0198 0.0194 z1,z2...zNC
3 NMODEL (1:SRK / 2:PR / 3:RKPR)
0 1 ncomb, nTdep
METHANE(1)
190.564 45.99 0.0115478 0.116530154855 1.16 tc, pc, ohm, vc, zrat
2.30376807604 0.0304337956072 0.5 1.54083758839 ac, b, delta1, k
PROPANE(2)
369.83 42.48 0.152291 0.233012170918 1.16 tc, pc, ohm, vc, zrat
9.80216972295 0.0598748909487 1.663687 1.9574557212 ac, b, delta1, k
0.0572 k0
190.564 tstar
-0.00272 lij
n-PENTANE(3)
469.7 33.7 0.251506 0.366506659349 1.16 tc, pc, ohm, vc, zrat
20.2236971345 0.0936309815449 1.957315 2.28798764446 ac, b, delta1, k
0.05616 0.0 k0
190.564 369.83 tstar
-0.06603 -0.010835 lij
n-DECANE(4)
617.7 21.1 0.492328 0.756468369911 1.16 tc, pc, ohm, vc, zrat
56.6610724692 0.192140038284 2.239538 3.11337933794 ac, b, delta1, k
0.06891 0.0 0.0 k0
190.564 369.83 469.7 tstar
-0.09227 -0.032481 -0.02353 lij
n-HEXADECANE(5)
723.0 14.0 0.717404 1.34252502769 1.16 tc, pc, ohm, vc, zrat
116.426356444 0.341676477137 2.14291 3.90352446586 ac, b, delta1, k
0.14031 0.0 0.0 0.0 k0
190.564 369.83 469.7 617.7 tstar
-0.12441 -0.023269 -0.012501 0.049878 lij
In [22]:
print(envelope.output_txt)
METHANE(1)
Tc= 190.5640 Pc = 45.9900 Vc = 0.1005 OM = 0.0115
Zc= 0.2916 Zcrat= 1.1600 Zceos= 0.3382 Vceos= 0.1165
ac= 2.3038 b = 0.0304 del1= 0.5000 k = 1.5408
PROPANE(2)
Tc= 369.8300 Pc = 42.4800 Vc = 0.2009 OM = 0.1523
Zc= 0.2775 Zcrat= 1.1600 Zceos= 0.3219 Vceos= 0.2330
ac= 9.8022 b = 0.0599 del1= 1.6637 k = 1.9575
n-PENTANE(3)
Tc= 469.7000 Pc = 33.7000 Vc = 0.3160 OM = 0.2515
Zc= 0.2726 Zcrat= 1.1600 Zceos= 0.3163 Vceos= 0.3665
ac= 20.2237 b = 0.0936 del1= 1.9573 k = 2.2880
n-DECANE(4)
Tc= 617.7000 Pc = 21.1000 Vc = 0.6521 OM = 0.4923
Zc= 0.2679 Zcrat= 1.1600 Zceos= 0.3108 Vceos= 0.7565
ac= 56.6611 b = 0.1921 del1= 2.2395 k = 3.1134
n-HEXADECANE(5)
Tc= 723.0000 Pc = 14.0000 Vc = 1.1573 OM = 0.7174
Zc= 0.2695 Zcrat= 1.1600 Zceos= 0.3127 Vceos= 1.3425
ac= 116.4264 b = 0.3417 del1= 2.1429 k = 3.9035
Tc, Pc and Vc are given in K, bar and L/mol respectively
K0ij MATRIX
METHANE(1)
PROPANE(2) 0.05720
n-PENTANE(3) 0.05616 0.00000
n-DECANE(4) 0.06891 0.00000 0.00000
n-HEXADECANE(5) 0.14031 0.00000 0.00000 0.00000
T* MATRIX
METHANE(1)
PROPANE(2) 190.56400
n-PENTANE(3) 190.56400 369.83000
n-DECANE(4) 190.56400 369.83000 469.70000
n-HEXADECANE(5) 190.56400 369.83000 469.70000 617.70000
LIJ MATRIX
METHANE(1)
PROPANE(2) -0.00272
n-PENTANE(3) -0.06603 -0.01083
n-DECANE(4) -0.09227 -0.03248 -0.02353
n-HEXADECANE(5) -0.12441 -0.02327 -0.01250 0.04988
Combining rules:
0: Classical or van der Waals
Molar fractions: 0.823 0.087 0.051 0.020 0.019
x 0.8232E+00 0.8710E-01 0.5050E-01 0.1980E-01 0.1940E-01
y 0.8083E+00 0.9037E-01 0.5408E-01 0.2300E-01 0.2427E-01
x 0.8232E+00 0.8710E-01 0.5050E-01 0.1980E-01 0.1940E-01
y 0.8106E+00 0.8992E-01 0.5354E-01 0.2249E-01 0.2347E-01
x 0.8232E+00 0.8710E-01 0.5050E-01 0.1980E-01 0.1940E-01
y 0.8129E+00 0.8946E-01 0.5300E-01 0.2198E-01 0.2270E-01
x 0.8232E+00 0.8710E-01 0.5050E-01 0.1980E-01 0.1940E-01
y 0.8132E+00 0.8939E-01 0.5290E-01 0.2190E-01 0.2258E-01
x 0.8232E+00 0.8710E-01 0.5050E-01 0.1980E-01 0.1940E-01
y 0.8132E+00 0.8939E-01 0.5290E-01 0.2189E-01 0.2257E-01
T(K) P(bar) D(mol/L)
310.0000 0.2472E-03 0.9591E-05
312.0835 0.3052E-03 0.1176E-04
314.9521 0.4056E-03 0.1549E-04
317.8332 0.5364E-03 0.2030E-04
320.7258 0.7057E-03 0.2647E-04
323.6288 0.9239E-03 0.3434E-04
326.5410 0.1203E-02 0.4433E-04
329.4613 0.1560E-02 0.5694E-04
332.3882 0.2011E-02 0.7278E-04
335.3203 0.2580E-02 0.9255E-04
338.2562 0.3294E-02 0.1171E-03
341.1944 0.4183E-02 0.1475E-03
344.1330 0.5286E-02 0.1848E-03
347.0704 0.6646E-02 0.2303E-03
350.0046 0.8314E-02 0.2857E-03
352.9337 0.1035E-01 0.3527E-03
355.8556 0.1282E-01 0.4332E-03
358.7683 0.1579E-01 0.5294E-03
361.6694 0.1936E-01 0.6438E-03
364.5565 0.2361E-01 0.7790E-03
367.4272 0.2865E-01 0.9380E-03
370.2788 0.3459E-01 0.1124E-02
373.1088 0.4156E-01 0.1340E-02
375.9142 0.4967E-01 0.1590E-02
378.6923 0.5907E-01 0.1876E-02
381.4399 0.6989E-01 0.2204E-02
384.1540 0.8227E-01 0.2576E-02
386.8314 0.9636E-01 0.2997E-02
389.4689 0.1123E+00 0.3469E-02
392.0630 0.1302E+00 0.3995E-02
394.6103 0.1502E+00 0.4578E-02
397.1074 0.1723E+00 0.5221E-02
399.5507 0.1968E+00 0.5926E-02
401.9367 0.2235E+00 0.6692E-02
404.2616 0.2526E+00 0.7520E-02
406.5220 0.2841E+00 0.8409E-02
408.7141 0.3178E+00 0.9357E-02
410.8344 0.3537E+00 0.1036E-01
412.8793 0.3917E+00 0.1142E-01
414.9101 0.4329E+00 0.1256E-01
416.9662 0.4784E+00 0.1381E-01
419.0479 0.5287E+00 0.1519E-01
421.1556 0.5843E+00 0.1670E-01
423.2897 0.6457E+00 0.1837E-01
425.4506 0.7137E+00 0.2020E-01
427.6385 0.7887E+00 0.2221E-01
429.8540 0.8717E+00 0.2442E-01
435.2429 0.1106E+01 0.3061E-01
440.6600 0.1396E+01 0.3816E-01
446.0967 0.1751E+01 0.4732E-01
451.5439 0.2185E+01 0.5835E-01
456.9909 0.2711E+01 0.7157E-01
462.4262 0.3345E+01 0.8732E-01
467.8367 0.4105E+01 0.1060E+00
473.2085 0.5011E+01 0.1280E+00
478.5263 0.6083E+01 0.1537E+00
483.7736 0.7347E+01 0.1838E+00
488.9328 0.8827E+01 0.2186E+00
493.9850 0.1055E+02 0.2589E+00
498.9102 0.1255E+02 0.3052E+00
503.6871 0.1486E+02 0.3581E+00
508.2933 0.1750E+02 0.4185E+00
512.7048 0.2053E+02 0.4871E+00
516.8961 0.2397E+02 0.5647E+00
520.8398 0.2787E+02 0.6524E+00
524.5063 0.3228E+02 0.7510E+00
527.8631 0.3724E+02 0.8617E+00
531.8966 0.4504E+02 0.1036E+01
535.3488 0.5475E+02 0.1252E+01
537.9048 0.6687E+02 0.1523E+01
539.1107 0.8209E+02 0.1866E+01
538.2987 0.1013E+03 0.2305E+01
534.4547 0.1255E+03 0.2874E+01
525.9621 0.1564E+03 0.3625E+01
522.0429 0.1675E+03 0.3905E+01
517.8064 0.1783E+03 0.4182E+01
513.2952 0.1887E+03 0.4458E+01
508.5464 0.1989E+03 0.4732E+01
503.5934 0.2087E+03 0.5004E+01
498.4657 0.2181E+03 0.5272E+01
493.1902 0.2272E+03 0.5538E+01
487.7914 0.2358E+03 0.5801E+01
482.2913 0.2441E+03 0.6061E+01
476.7103 0.2521E+03 0.6317E+01
471.0667 0.2596E+03 0.6569E+01
465.3775 0.2667E+03 0.6818E+01
459.6579 0.2734E+03 0.7063E+01
453.9218 0.2797E+03 0.7303E+01
448.1818 0.2856E+03 0.7540E+01
442.4494 0.2911E+03 0.7772E+01
436.7347 0.2962E+03 0.7999E+01
431.0469 0.3010E+03 0.8223E+01
425.3940 0.3053E+03 0.8442E+01
419.7833 0.3093E+03 0.8656E+01
414.2209 0.3129E+03 0.8866E+01
408.7122 0.3161E+03 0.9072E+01
403.2617 0.3191E+03 0.9273E+01
397.8733 0.3216E+03 0.9470E+01
392.5500 0.3239E+03 0.9663E+01
387.2942 0.3258E+03 0.9852E+01
382.0379 0.3274E+03 0.1004E+02
376.7143 0.3288E+03 0.1023E+02
371.3183 0.3299E+03 0.1042E+02
365.8427 0.3307E+03 0.1061E+02
360.2784 0.3311E+03 0.1080E+02
354.6136 0.3313E+03 0.1099E+02
348.8328 0.3311E+03 0.1119E+02
342.9153 0.3306E+03 0.1139E+02
336.8332 0.3296E+03 0.1159E+02
330.5478 0.3282E+03 0.1180E+02
324.0036 0.3263E+03 0.1202E+02
317.1145 0.3238E+03 0.1224E+02
309.7443 0.3206E+03 0.1249E+02
301.6363 0.3164E+03 0.1275E+02
292.2243 0.3108E+03 0.1306E+02
284.4179 0.3054E+03 0.1331E+02
272.0585 0.2961E+03 0.1371E+02
265.9509 0.2911E+03 0.1391E+02
265.6858 0.2909E+03 0.1392E+02
Number of critical points found: 0
T(K) P(bar) D(mol/L)
Isochores¶
In [1]:
%config InlineBackend.close_figures=False
%matplotlib inline
from matplotlib import interactive
interactive(False)
In [2]:
from sur import *
setup_database()
In [3]:
m = Mixture()
m.add_many('methane propane n-pentane n-decane n-hexadecane',
'0.822 0.088 0.050 0.020 0.020')
s = EosSetup.objects.create(eos='RKPR', kij_mode=EosSetup.T_DEP, lij_mode='constants')
env = m.get_envelope(setup=s)
In [4]:
fig = env.plot()
fig
Out[4]:
In [15]:
help(m.get_isochore)
Help on method get_isochore in module sur.models:
get_isochore(self, setup, v, ts, ps, t_sup, t_step=5.0, t_inf=270.0) method of sur.models.Mixture instance
Get the isochore (isoV) for this mixture, calculated using
the setup EOS with its selected interaction parameters
mode.
In [5]:
isochore = m.get_isochore(setup=s, v=10., ts=467.01, ps=3.86, t_sup=465.0, t_step=5.0, t_inf=270.0)
You can get the raw input and output
In [6]:
print(isochore.input_txt)
5 NC
5 nplus
isoV Spec v(k), ts and ps
0.822 0.088 0.05 0.02 0.02 z1,z2...zNC
10.0 467.01 3.86 v(L/mol)+Ts+Ps
465.0 5.0 270.0 T(K)+dT+Tinf
3 NMODEL (1:SRK / 2:PR / 3:RKPR)
0 1 ncomb, nTdep
METHANE(1)
190.564 45.99 0.0115478 0.116530154855 1.16 tc, pc, ohm, vc, zrat
2.30376807604 0.0304337956072 0.5 1.54083758839 ac, b, delta1, k
PROPANE(2)
369.83 42.48 0.152291 0.233012170918 1.16 tc, pc, ohm, vc, zrat
9.80216972295 0.0598748909487 1.663687 1.9574557212 ac, b, delta1, k
0.013831 k0
190.564 tstar
-0.047134 lij
n-PENTANE(3)
469.7 33.7 0.251506 0.366506659349 1.16 tc, pc, ohm, vc, zrat
20.2236971345 0.0936309815449 1.957315 2.28798764446 ac, b, delta1, k
0.030221 0.0 k0
190.564 369.83 tstar
-0.084739 -0.010835 lij
n-DECANE(4)
617.7 21.1 0.492328 0.756468369911 1.16 tc, pc, ohm, vc, zrat
56.6610724692 0.192140038284 2.239538 3.11337933794 ac, b, delta1, k
0.068534 0.0 0.0 k0
190.564 369.83 469.7 tstar
-0.145519 -0.032481 -0.02353 lij
n-HEXADECANE(5)
723.0 14.0 0.717404 1.34252502769 1.16 tc, pc, ohm, vc, zrat
116.426356444 0.341676477137 2.14291 3.90352446586 ac, b, delta1, k
0.095928 0.0 0.0 0.0 k0
190.564 369.83 469.7 617.7 tstar
-0.121142 -0.023269 -0.012501 0.049878 lij
In [7]:
print(isochore.output_txt)
The plus fraction from component 5 is 2.000000000000000E-002
T(K) rho(mol/L) P(bar) v(L/mol) beta betav xplus yplus
iter
467.01 0.1000E+00 0.3860E+01 0.1000E+02 0.1000E+01 0.1000E+01
465.00 0.1000E+00 0.3845E+01 0.1000E+02 0.9984E+00 0.9999E+00 0.898332 0.018611 6
460.00 0.1000E+00 0.3792E+01 0.1000E+02 0.9950E+00 0.9998E+00 0.890882 0.015582 7
455.00 0.1000E+00 0.3740E+01 0.1000E+02 0.9919E+00 0.9997E+00 0.882580 0.012958 7
450.00 0.1000E+00 0.3689E+01 0.1000E+02 0.9892E+00 0.9996E+00 0.873347 0.010699 7
445.00 0.1000E+00 0.3640E+01 0.1000E+02 0.9869E+00 0.9995E+00 0.863099 0.008769 7
440.00 0.1000E+00 0.3591E+01 0.1000E+02 0.9848E+00 0.9994E+00 0.851757 0.007130 7
435.00 0.1000E+00 0.3544E+01 0.1000E+02 0.9829E+00 0.9994E+00 0.839247 0.005750 8
430.00 0.1000E+00 0.3498E+01 0.1000E+02 0.9812E+00 0.9993E+00 0.825509 0.004596 8
425.00 0.1000E+00 0.3451E+01 0.1000E+02 0.9797E+00 0.9993E+00 0.810500 0.003639 8
420.00 0.1000E+00 0.3406E+01 0.1000E+02 0.9783E+00 0.9992E+00 0.794204 0.002854 8
415.00 0.1000E+00 0.3361E+01 0.1000E+02 0.9770E+00 0.9992E+00 0.776641 0.002215 9
410.00 0.1000E+00 0.3316E+01 0.1000E+02 0.9758E+00 0.9992E+00 0.757877 0.001701 9
405.00 0.1000E+00 0.3271E+01 0.1000E+02 0.9746E+00 0.9991E+00 0.738030 0.001291 9
400.00 0.1000E+00 0.3227E+01 0.1000E+02 0.9734E+00 0.9991E+00 0.717280 0.000969 9
395.00 0.1000E+00 0.3182E+01 0.1000E+02 0.9723E+00 0.9991E+00 0.695871 0.000719 9
390.00 0.1000E+00 0.3138E+01 0.1000E+02 0.9711E+00 0.9991E+00 0.674107 0.000527 9
385.00 0.1000E+00 0.3094E+01 0.1000E+02 0.9699E+00 0.9990E+00 0.652340 0.000382 9
380.00 0.1000E+00 0.3050E+01 0.1000E+02 0.9687E+00 0.9990E+00 0.630950 0.000273 8
375.00 0.1000E+00 0.3006E+01 0.1000E+02 0.9675E+00 0.9990E+00 0.610313 0.000193 8
370.00 0.1000E+00 0.2962E+01 0.1000E+02 0.9664E+00 0.9990E+00 0.590768 0.000136 8
365.00 0.1000E+00 0.2918E+01 0.1000E+02 0.9652E+00 0.9990E+00 0.572588 0.000094 7
360.00 0.1000E+00 0.2874E+01 0.1000E+02 0.9641E+00 0.9989E+00 0.555955 0.000065 7
355.00 0.1000E+00 0.2831E+01 0.1000E+02 0.9631E+00 0.9989E+00 0.540952 0.000044 7
350.00 0.1000E+00 0.2788E+01 0.1000E+02 0.9621E+00 0.9989E+00 0.527568 0.000030 6
345.00 0.1000E+00 0.2745E+01 0.1000E+02 0.9613E+00 0.9989E+00 0.515708 0.000020 6
340.00 0.1000E+00 0.2703E+01 0.1000E+02 0.9604E+00 0.9989E+00 0.505214 0.000013 6
335.00 0.1000E+00 0.2660E+01 0.1000E+02 0.9597E+00 0.9989E+00 0.495883 0.000008 6
330.00 0.1000E+00 0.2618E+01 0.1000E+02 0.9590E+00 0.9989E+00 0.487479 0.000005 6
325.00 0.1000E+00 0.2576E+01 0.1000E+02 0.9583E+00 0.9988E+00 0.479748 0.000003 6
320.00 0.1000E+00 0.2534E+01 0.1000E+02 0.9577E+00 0.9988E+00 0.472422 0.000002 6
315.00 0.1000E+00 0.2493E+01 0.1000E+02 0.9570E+00 0.9988E+00 0.465218 0.000001 7
310.00 0.1000E+00 0.2451E+01 0.1000E+02 0.9563E+00 0.9988E+00 0.457840 0.000001 7
305.00 0.1000E+00 0.2409E+01 0.1000E+02 0.9556E+00 0.9988E+00 0.449965 0.000000 7
300.00 0.1000E+00 0.2366E+01 0.1000E+02 0.9547E+00 0.9988E+00 0.441244 0.000000 7
295.00 0.1000E+00 0.2324E+01 0.1000E+02 0.9536E+00 0.9988E+00 0.431283 0.000000 8
290.00 0.1000E+00 0.2281E+01 0.1000E+02 0.9523E+00 0.9988E+00 0.419647 0.000000 8
285.00 0.1000E+00 0.2237E+01 0.1000E+02 0.9507E+00 0.9988E+00 0.405877 0.000000 8
280.00 0.1000E+00 0.2193E+01 0.1000E+02 0.9487E+00 0.9987E+00 0.389552 0.000000 8
275.00 0.1000E+00 0.2147E+01 0.1000E+02 0.9460E+00 0.9987E+00 0.370439 0.000000 9
270.00 0.1000E+00 0.2100E+01 0.1000E+02 0.9427E+00 0.9987E+00 0.348747 0.000000 9
Monophasic Region:
T(K) rho(mol/L) P(bar) v(L/mol)
467.01 0.1000E+00 0.3860E+01 0.1000E+02
472.01 0.1000E+00 0.3910E+01 0.1000E+02
477.01 0.1000E+00 0.3952E+01 0.1000E+02
482.01 0.1000E+00 0.3994E+01 0.1000E+02
487.01 0.1000E+00 0.4036E+01 0.1000E+02
492.01 0.1000E+00 0.4078E+01 0.1000E+02
497.01 0.1000E+00 0.4120E+01 0.1000E+02
502.01 0.1000E+00 0.4162E+01 0.1000E+02
507.01 0.1000E+00 0.4204E+01 0.1000E+02
512.01 0.1000E+00 0.4246E+01 0.1000E+02
517.01 0.1000E+00 0.4288E+01 0.1000E+02
522.01 0.1000E+00 0.4330E+01 0.1000E+02
527.01 0.1000E+00 0.4372E+01 0.1000E+02
532.01 0.1000E+00 0.4414E+01 0.1000E+02
537.01 0.1000E+00 0.4456E+01 0.1000E+02
542.01 0.1000E+00 0.4498E+01 0.1000E+02
547.01 0.1000E+00 0.4540E+01 0.1000E+02
552.01 0.1000E+00 0.4582E+01 0.1000E+02
557.01 0.1000E+00 0.4624E+01 0.1000E+02
562.01 0.1000E+00 0.4666E+01 0.1000E+02
567.01 0.1000E+00 0.4708E+01 0.1000E+02
572.01 0.1000E+00 0.4750E+01 0.1000E+02
577.01 0.1000E+00 0.4792E+01 0.1000E+02
582.01 0.1000E+00 0.4834E+01 0.1000E+02
587.01 0.1000E+00 0.4876E+01 0.1000E+02
592.01 0.1000E+00 0.4918E+01 0.1000E+02
597.01 0.1000E+00 0.4960E+01 0.1000E+02
602.01 0.1000E+00 0.5002E+01 0.1000E+02
607.01 0.1000E+00 0.5044E+01 0.1000E+02
612.01 0.1000E+00 0.5086E+01 0.1000E+02
617.01 0.1000E+00 0.5128E+01 0.1000E+02
622.01 0.1000E+00 0.5170E+01 0.1000E+02
627.01 0.1000E+00 0.5212E+01 0.1000E+02
632.01 0.1000E+00 0.5254E+01 0.1000E+02
637.01 0.1000E+00 0.5296E+01 0.1000E+02
642.01 0.1000E+00 0.5338E+01 0.1000E+02
647.01 0.1000E+00 0.5380E+01 0.1000E+02
652.01 0.1000E+00 0.5422E+01 0.1000E+02
657.01 0.1000E+00 0.5464E+01 0.1000E+02
662.01 0.1000E+00 0.5506E+01 0.1000E+02
667.01 0.1000E+00 0.5548E+01 0.1000E+02
672.01 0.1000E+00 0.5590E+01 0.1000E+02
677.01 0.1000E+00 0.5632E+01 0.1000E+02
682.01 0.1000E+00 0.5674E+01 0.1000E+02
687.01 0.1000E+00 0.5716E+01 0.1000E+02
692.01 0.1000E+00 0.5758E+01 0.1000E+02
697.01 0.1000E+00 0.5800E+01 0.1000E+02
702.01 0.1000E+00 0.5842E+01 0.1000E+02
707.01 0.1000E+00 0.5884E+01 0.1000E+02
712.01 0.1000E+00 0.5926E+01 0.1000E+02
717.01 0.1000E+00 0.5967E+01 0.1000E+02
722.01 0.1000E+00 0.6009E+01 0.1000E+02
727.01 0.1000E+00 0.6051E+01 0.1000E+02
732.01 0.1000E+00 0.6093E+01 0.1000E+02
737.01 0.1000E+00 0.6135E+01 0.1000E+02
742.01 0.1000E+00 0.6177E+01 0.1000E+02
747.01 0.1000E+00 0.6219E+01 0.1000E+02
752.01 0.1000E+00 0.6261E+01 0.1000E+02
757.01 0.1000E+00 0.6303E+01 0.1000E+02
762.01 0.1000E+00 0.6345E+01 0.1000E+02
767.01 0.1000E+00 0.6387E+01 0.1000E+02
772.01 0.1000E+00 0.6429E+01 0.1000E+02
777.01 0.1000E+00 0.6471E+01 0.1000E+02
782.01 0.1000E+00 0.6513E+01 0.1000E+02
787.01 0.1000E+00 0.6554E+01 0.1000E+02
792.01 0.1000E+00 0.6596E+01 0.1000E+02
797.01 0.1000E+00 0.6638E+01 0.1000E+02
802.01 0.1000E+00 0.6680E+01 0.1000E+02
807.01 0.1000E+00 0.6722E+01 0.1000E+02
812.01 0.1000E+00 0.6764E+01 0.1000E+02
817.01 0.1000E+00 0.6806E+01 0.1000E+02
822.01 0.1000E+00 0.6848E+01 0.1000E+02
827.01 0.1000E+00 0.6890E+01 0.1000E+02
832.01 0.1000E+00 0.6932E+01 0.1000E+02
837.01 0.1000E+00 0.6974E+01 0.1000E+02
842.01 0.1000E+00 0.7015E+01 0.1000E+02
847.01 0.1000E+00 0.7057E+01 0.1000E+02
852.01 0.1000E+00 0.7099E+01 0.1000E+02
857.01 0.1000E+00 0.7141E+01 0.1000E+02
862.01 0.1000E+00 0.7183E+01 0.1000E+02
867.01 0.1000E+00 0.7225E+01 0.1000E+02
872.01 0.1000E+00 0.7267E+01 0.1000E+02
877.01 0.1000E+00 0.7309E+01 0.1000E+02
882.01 0.1000E+00 0.7351E+01 0.1000E+02
887.01 0.1000E+00 0.7392E+01 0.1000E+02
892.01 0.1000E+00 0.7434E+01 0.1000E+02
897.01 0.1000E+00 0.7476E+01 0.1000E+02
902.01 0.1000E+00 0.7518E+01 0.1000E+02
907.01 0.1000E+00 0.7560E+01 0.1000E+02
912.01 0.1000E+00 0.7602E+01 0.1000E+02
917.01 0.1000E+00 0.7644E+01 0.1000E+02
922.01 0.1000E+00 0.7686E+01 0.1000E+02
927.01 0.1000E+00 0.7728E+01 0.1000E+02
932.01 0.1000E+00 0.7769E+01 0.1000E+02
937.01 0.1000E+00 0.7811E+01 0.1000E+02
942.01 0.1000E+00 0.7853E+01 0.1000E+02
947.01 0.1000E+00 0.7895E+01 0.1000E+02
952.01 0.1000E+00 0.7937E+01 0.1000E+02
957.01 0.1000E+00 0.7979E+01 0.1000E+02
962.01 0.1000E+00 0.8021E+01 0.1000E+02
967.01 0.1000E+00 0.8063E+01 0.1000E+02
972.01 0.1000E+00 0.8104E+01 0.1000E+02
977.01 0.1000E+00 0.8146E+01 0.1000E+02
982.01 0.1000E+00 0.8188E+01 0.1000E+02
987.01 0.1000E+00 0.8230E+01 0.1000E+02
992.01 0.1000E+00 0.8272E+01 0.1000E+02
997.01 0.1000E+00 0.8314E+01 0.1000E+02
1002.01 0.1000E+00 0.8356E+01 0.1000E+02
los vectores t y p son recortados en dos partes, como se generan
In [8]:
isochore.t
Out[8]:
array([ 467.01, 465. , 460. , 455. , 450. , 445. , 440. ,
435. , 430. , 425. , 420. , 415. , 410. , 405. ,
400. , 395. , 390. , 385. , 380. , 375. , 370. ,
365. , 360. , 355. , 350. , 345. , 340. , 335. ,
330. , 325. , 320. , 315. , 310. , 305. , 300. ,
295. , 290. , 285. , 280. , 275. , 270. ])
In [9]:
isochore.p
Out[9]:
array([ 3.86 , 3.845, 3.792, 3.74 , 3.689, 3.64 , 3.591, 3.544,
3.498, 3.451, 3.406, 3.361, 3.316, 3.271, 3.227, 3.182,
3.138, 3.094, 3.05 , 3.006, 2.962, 2.918, 2.874, 2.831,
2.788, 2.745, 2.703, 2.66 , 2.618, 2.576, 2.534, 2.493,
2.451, 2.409, 2.366, 2.324, 2.281, 2.237, 2.193, 2.147, 2.1 ])
In [10]:
isochore.t_monophasic
Out[10]:
array([ 467.01, 472.01, 477.01, 482.01, 487.01, 492.01,
497.01, 502.01, 507.01, 512.01, 517.01, 522.01,
527.01, 532.01, 537.01, 542.01, 547.01, 552.01,
557.01, 562.01, 567.01, 572.01, 577.01, 582.01,
587.01, 592.01, 597.01, 602.01, 607.01, 612.01,
617.01, 622.01, 627.01, 632.01, 637.01, 642.01,
647.01, 652.01, 657.01, 662.01, 667.01, 672.01,
677.01, 682.01, 687.01, 692.01, 697.01, 702.01,
707.01, 712.01, 717.01, 722.01, 727.01, 732.01,
737.01, 742.01, 747.01, 752.01, 757.01, 762.01,
767.01, 772.01, 777.01, 782.01, 787.01, 792.01,
797.01, 802.01, 807.01, 812.01, 817.01, 822.01,
827.01, 832.01, 837.01, 842.01, 847.01, 852.01,
857.01, 862.01, 867.01, 872.01, 877.01, 882.01,
887.01, 892.01, 897.01, 902.01, 907.01, 912.01,
917.01, 922.01, 927.01, 932.01, 937.01, 942.01,
947.01, 952.01, 957.01, 962.01, 967.01, 972.01,
977.01, 982.01, 987.01, 992.01, 997.01, 1002.01])
In [11]:
isochore.p_monophasic
Out[11]:
array([ 3.86 , 3.91 , 3.952, 3.994, 4.036, 4.078, 4.12 , 4.162,
4.204, 4.246, 4.288, 4.33 , 4.372, 4.414, 4.456, 4.498,
4.54 , 4.582, 4.624, 4.666, 4.708, 4.75 , 4.792, 4.834,
4.876, 4.918, 4.96 , 5.002, 5.044, 5.086, 5.128, 5.17 ,
5.212, 5.254, 5.296, 5.338, 5.38 , 5.422, 5.464, 5.506,
5.548, 5.59 , 5.632, 5.674, 5.716, 5.758, 5.8 , 5.842,
5.884, 5.926, 5.967, 6.009, 6.051, 6.093, 6.135, 6.177,
6.219, 6.261, 6.303, 6.345, 6.387, 6.429, 6.471, 6.513,
6.554, 6.596, 6.638, 6.68 , 6.722, 6.764, 6.806, 6.848,
6.89 , 6.932, 6.974, 7.015, 7.057, 7.099, 7.141, 7.183,
7.225, 7.267, 7.309, 7.351, 7.392, 7.434, 7.476, 7.518,
7.56 , 7.602, 7.644, 7.686, 7.728, 7.769, 7.811, 7.853,
7.895, 7.937, 7.979, 8.021, 8.063, 8.104, 8.146, 8.188,
8.23 , 8.272, 8.314, 8.356])
In [12]:
isochore.rho, isochore.rho_monophasic,
Out[12]:
(array([ 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1,
0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1,
0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1,
0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1]),
array([ 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1,
0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1,
0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1,
0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1,
0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1,
0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1,
0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1,
0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1,
0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1,
0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1]))
In [13]:
isochore.plot()
Out[13]:
También se le puede pasar una figura ya generada, para que superponga el nuevo plot
In [14]:
isochore.plot(fig)
Out[14]:
Advanced plots¶
In [1]:
%config InlineBackend.close_figures=False
%matplotlib inline
from matplotlib import interactive
interactive(False)
from sur import *
setup_database()
m = Mixture()
m.add_many("methane co2 n-decane", "0.25 0.50 0.25")
In [2]:
s1 = EosSetup.objects.create(eos='RKPR', kij_mode=EosSetup.CONSTANTS, lij_mode=EosSetup.CONSTANTS)
s1.set_interaction('kij', 'methane', 'co2', .1)
s1.set_interaction('kij', 'co2', 'n-decane', 0.091)
s1.set_interaction('lij', 'co2', 'n-decane', -0.90)
env1 = m.get_envelope(s1, label="Envelope 1")
In [3]:
s2 = EosSetup.objects.create(eos='RKPR', kij_mode=EosSetup.CONSTANTS, lij_mode=EosSetup.CONSTANTS)
s2.set_interaction('kij', 'methane', 'co2', .11)
s2.set_interaction('kij', 'co2', 'n-decane', 0.081)
s2.set_interaction('lij', 'co2', 'n-decane', -0.93)
env2 = m.get_envelope(s2, label="Envelope 2")
In [4]:
from sur.plots import multiplot
In [6]:
fig = multiplot([env1, env2], legends='best')
In [7]:
fig
Out[7]:
You can use the bbox_to_anchor keyword argument to place the legend
partially outside the axes and/or decrease the font size.
In [8]:
ax = fig.get_axes()[0]
ax.legend(bbox_to_anchor=(1.1, 1.1))
fig
Out[8]:
In [9]:
ax.legend(bbox_to_anchor=(1.4, 1))
fig
Out[9]:
Similarly, you can make the legend more horizontal and/or put it at the top of the figure (I’m also turning on rounded corners and a simple drop shadow):
In [10]:
ax.legend(loc='upper center', bbox_to_anchor=(0.5, 1.05),
ncol=3, fancybox=True, shadow=True)
fig
Out[10]:
Alternatively, you can shrink the current plot’s width, and put the legend entirely outside the axis of the figure
In [11]:
# Shink current axis by 20%
box = ax.get_position()
ax.set_position([box.x0, box.y0, box.width * 0.8, box.height])
# Put a legend to the right of the current axis
ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))
fig
Out[11]:
And in a similar manner, you can shrink the plot vertically, and put the a horizontal legend at the bottom
In [12]:
# Shink current axis's height by 10% on the bottom
box = ax.get_position()
ax.set_position([box.x0, box.y0 + box.height * 0.1,
box.width, box.height * 0.9])
# Put a legend below current axis
ax.legend(loc='upper center', bbox_to_anchor=(0.5, -0.2),
fancybox=True, shadow=True, ncol=5)
fig
Out[12]:
Configure fonts¶
In [13]:
# reset figure
fig = multiplot([env1, env2], legends='upper right')
ax = fig.get_axes()[0]
from matplotlib.font_manager import FontProperties
fontP = FontProperties()
fontP.set_size('small')
fontP.set_family('serif')
fontP.set_weight('bold')
ax.legend(loc='best', prop=fontP)
fig
Out[13]:
Setup a development enviroment¶
This document is a guide to install an enviroment to contribute to the development of Sur library. It’s fully based on modern Ubuntu Linux distributions (particularly Ubuntu 15.10) but should be straight forward follow this on any other linux distribution.
Install system packages¶
Install system packages:
$ sudo apt-get install git python-dev python-pip wine gfortran \ g++ libfreetype6-dev libpng12-dev xclip $ sudo pip install virtualenvwrapper
Note
To code, of course you’ll also need an editor. Could be anyone you prefer!
Some people prefers simple ones like gedit (installed by default)
or geany. Some other prefers something more geeky like vim
or even more complete tools like pydev or ninja-ide.
Make a virtual enviroment¶
We use virtualenv (using virtualenvwrapper) to isolate our enviroment for other projects and system-wide python packages
Setup virtualenvwrapper
2.1 Create a directory to hold your virtualenvs:
mkdir ~/.virtualenvs mkdir ~/projects mkdir ~/.pip_download_cache
2.2 Edit you
~/.bashrcadding these lines:export WORKON_HOME=$HOME/.virtualenvs source /usr/local/bin/virtualenvwrapper.sh export PROJECT_HOME=$HOME/projects #folder for new projects. Could be what you want
2.3 And reload that:
$ source ~/.bashrc
Now create the project sur:
$ mkproject sur
This will create a new virtualenv in the WORKON_HOME binded to a project directory in PROJECT_HOME
Note
Next times, when you want to active the sur’s virtualenv you’ll run:
$ workon sur
When you want to deactive the virtualenv, on any path
(sur)~/projects/sur$ deactivate
Checkout the code¶
sur’s git repo isn’t public, so you need to have credentials to read and/or write it. Please if you don’t have a Bitbucket account, create one:
Go to https://bitbucket.org/account/signup/ and sign up
Let me know (gaitan@gmail.com) your username and ask for dev permissions on Sur. If you don’t have an user on bitbucket also let me know first. I’ll send and invitation
Setup a ssh-key
$ ssh-keygen $ xclip -sel clip < ~/.ssh/id_rsa.pub and paste this on https://bitbucket.org/account/user/<your_userr>/ssh-keys/
Then we go:
(sur)~/projects/sur$ git clone git@bitbucket.org:phasety/envelope-sur.git . (sur)~/projects/sur$ git checkout develop
Remember to configure your identity (so, your future great code will be recognized):
(sur)$ git config --global user.name "Juan Perez" (sur)$ git config --global user.email perez@phasety.com
Install in dev mode¶
(sur)~/projects/sur$ pip install -U numpy pip jupyter nose (sur)~/projects/sur$ pip install -e .
Tip
The flag -e on the last command means this package will be editable.
Every change on the code of Sur will impact automatically.
It’s the same than python setup.py develop
Then check if it was installed:
(sur) $ ipython
In [1]: import sur # may take few seconds to load
Run tests:
(sur) $ nosetests
And open an example notebook for lib usage:
(sur) $ jupyter notebook examples/basic_envelope.ipynb
¡Happy coding!
API reference¶
sur.apps module¶
sur.envelope module¶
sur.envelope_sp module¶
sur.eos module¶
-
class
sur.eos.SRK¶ Bases:
sur.eos.CubicModelSoave modification of Redlich–Kwong EOS
-
MODEL_ID= 1¶
-
MODEL_NAME= 'SRK'¶
-
-
class
sur.eos.PR¶ Bases:
sur.eos.CubicModelPeng–Robinson equation of state
-
MODEL_ID= 2¶
-
MODEL_NAME= 'PR'¶
-
-
class
sur.eos.RKPR¶ Bases:
sur.eos.CubicModelRKPR equation of state
-
MODEL_ID= 3¶
-
MODEL_NAME= 'RKPR'¶
-
classmethod
from_constants(tc, pc, acentric_factor, vc=None, del1=None, rhoLsat_t=(), pvdat=())¶ Given the constants of a pure compound, returns a tuple of arrays with the same constants adjusted and the arrays of correspond model’s parameters.
Constants requires tc, pc, and acentric_factor as mandatory and vc or del1 or rhoLsat_t=(rhoLsat, T).
If a point pvdat = (P, T) is given, it’s used as a constraint to calculate the vapor pressure
Returns: (constants, model_parameters) Where:
constants = array([tc, pc, acentric_factor, vc]) models_parameters = array([ac, b, del1, rk])
-
classmethod
from_parameters(ac, b, del1, rk)¶ Given the model’s parameters, returns a tuple of arrays with the pure compound constants adjusted and the the ajusted model’s array of parameters.
Returns: (constants, model_parameters) Where:
constants = array([Tc, Pc, acentric_factor, Vc]) models_parameters = array([ac, b, del1, rk])
-
-
sur.eos.get_eos(model)¶
sur.manage module¶
sur.models module¶
sur.plots module¶
Plot shortcuts utilities
-
sur.plots.multiplot(envelopes=None, experimental_envelopes=None, formats=None, critical_point='o', experimental_colors=None, experimental_markers=None, legends=None)¶ merge the plot of multiples envelopes
sur.settings module¶
sur.tools module¶
sur.units module¶
Module contents¶
-
sur.data(a)¶
-
sur.setup_database()¶ this is a hackish trick.
It setup the django enviroment through setup_environ(settings)
Then populates the database but, instead of fixtures, it dumps db on disk (‘disk’) to a memory one (‘default’), and then syncs the missing tables on the latter.