Update / Add High pressure transport #1704

wandadars · 2024-06-05T21:57:31Z

This PR is a WIP

Changes proposed in this pull request

Updates to the current version of the HighPressureGasTransport class including:
- cleaner coding
- switching to mixture average properties as the multicomponent was incomplete and lacking implementations of required base class methods.
- New class that implements Chung's method from Poling's 2001 book.

I will add examples when the primary coding is complete. The original class had no tests or examples and was marked for deprecation, so I'm hoping that this effort will save it from deletion.

Checklist

The pull request includes a clear description of this code change
Commit messages have short titles and reference relevant issues
Build passes (scons build & scons test) and unit tests address code coverage
Style & formatting of contributed code follows contributing guidelines
The pull request is ready for review

codecov · 2024-06-06T23:43:32Z

Codecov Report

Attention: Patch coverage is 76.79325% with 110 lines in your changes missing coverage. Please review.

Project coverage is 73.67%. Comparing base (15a941e) to head (c4a16cc).
Report is 28 commits behind head on main.

Files with missing lines	Patch %	Lines
src/transport/HighPressureGasTransport.cpp	76.88%	94 Missing and 13 partials ⚠️
...clude/cantera/transport/HighPressureGasTransport.h	40.00%	3 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1704      +/-   ##
==========================================
+ Coverage   73.10%   73.67%   +0.56%     
==========================================
  Files         383      383              
  Lines       54632    54900     +268     
  Branches     9106     9122      +16     
==========================================
+ Hits        39940    40448     +508     
+ Misses      11692    11431     -261     
- Partials     3000     3021      +21

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wandadars · 2024-06-10T19:12:15Z

One thing that I noticed is that, while we may utilize the critical-properties.yaml file in the cubic equation of state to obtain critical properties, the input YAML file needs to also have its own "critical-paramters' section with the acentric-factor defined. This is the current way that the transport properties class obtains the quantity.

Also, the difference between using the tabulated values directly from the YAML data versus making a query to the cubic eos asking it for the mixture critical properties Tc, Pc, Vc, does seem to have a strong effect. In the Poling book, example 9-1 for Sulfur Dioxide, the tabulated critical volume is 122 cm^3/mol, but the Peng-Robinson equation of state gives a critical volume of 97.6 cm^3/mol. So we have a 20% difference in the critical properties between tabulated values and EOS-derived values.

wandadars · 2024-06-10T22:15:34Z

With regards to diffusion coefficients at high pressure, the Funazukuri, 1992 paper method that Poling mentions in the book might be worth checking out.

wandadars · 2024-06-17T21:26:48Z

One thing that might need to be checked is whether a user has provided an acentric-factor, because if they don't have it included in the "critical-properties" section in the YAML file, a default value of 0 is used quietly I think. That would be undesirable. So, even if a user provides the "acentric-factor" in the "equation-of-state" section, it won't be used by the transport model and a value of 0 is used.

I'm also working on checking the case of what happens if a user only has a subset of species defined as having critical properties (for cases where critical properties of the other mixture gases may not be known). I want to make sure that the mixing rules don't cause any FPEs when the EOS is asked for the critical values of Pc, Tc, Vc for a species that is ideal. I know for the PREOS, you can provide a=0 and b=0 to recover ideal behavior. I just want to make sure it all works out in that situation.

wandadars · 2024-06-18T20:50:21Z

@speth Is there a general guiding philosphy established for what types of statements should be in loglevel print statements? I have code blocks in the high pressure transport that I'm using for evaluating the operation of the model, but they're just cout blocks and I have them commented out. I was thinking that having them accessible via a loglevel might be useful.

speth · 2024-06-18T21:28:59Z

It looks like most of these blocks are just printing out parameter values on input to a function, right? I'd be inclined to just delete them. I think once you have this working, they will have served their purpose and won't be needed.

wandadars · 2024-06-19T20:57:41Z

This implementation is equation-heavy with references to the Poling book. I am trying to find a balance between having all equations replicated in the documentation versus referring to the book. Any thoughts on how I should proceed here?

speth · 2024-06-19T23:56:12Z

That's a good question. I guess the ideal would be to include all the equations that are needed to explain the calculations. That would provide users with the ability to understand what Cantera's doing without needing to consult a somewhat difficult to obtain reference, and makes it possible to more easily verify that the implementation corresponds to the equations. On the other hand, that may be an excessive number of equations and effort, and anything at all would be an improvement over the current version of this class.

wandadars · 2024-06-20T22:01:12Z

One issue I have is with regards to a unit test. I want to try and compare the result to something from the Poling book, but the critical volume estimated from the cubic EOS is 20% off of the tabulated/known value, so that generates an error in the viscosity or thermal conductivity.

wandadars · 2024-06-20T22:18:31Z

@speth I think this is mostly in a working state now. I know you guys have tons of other things to review. I think this is ready if anyone wants to start the process of reviewing the changes.

The general approach that I have taken with these Lucas and Chung method is that often in the Poling book, the mixture-based calculation is identical to the pure-species equation with the only difference being that mixture-average values of the parameters in the equations are used. So I implemented "blind" methods that are the pure-species versions of the low pressure viscosity and high pressure viscosity methods and then I left the calculation of the mixture values and the passing of those mixture values to the "blind" methods up to the main method (viscosity()).

I put the mixture values into a struct so they could be cleanly computed in one place and passed around if needed.

We have an updated Lucas method (The HighPressureGas class) and a new Chung method (ChungHighPressureGas) class.

Both of these classes use the same Takahasi method, so I moved that into a separate standalone function that both classes could call. I also have a standalone Neufeld collision integral function. This is used in the Poling book for estimating the Omega parameter in the viscosity equations. I know Cantera has it's own calculation of that value, but I wasn't sure how to go about getting it properly, so I put the standalone function in for now.

I tried to keep the comments clear and inside the methods, make reference to the equations in the Poling book (pdfs can be found online of the book).

wandadars · 2024-06-20T22:28:35Z

When looking into the Takahashi result, we can not interpolate the coefficients from the paper as it produces wild results that look nothing like the plots. I do believe that the authors used some sort of curve fit the data points in the table in order to generate the plots from their paper. For us, using the results from the table presented in the Takahashi paper produces piecewise linear segments between the data points. That's the best that can be done I think, without us introducing our own smooth curve fit to the data in the table, which I've always been taught to not do.

speth

Thanks for sharing this work-in-progress, @wandadars. I'm glad to see this capability getting some attention, and I like where this is going in terms of providing a well-documented implementation of these methods. I've left a variety of comments, some of which I realize are addressing issues that you've inherited from the existing implementation. I think this would be a good opportunity to clean these up. Besides the in-line comments, I had a couple of general points:

Please format all lines with a maximum of 88 characters.
I'd strongly recommend getting Doxygen up and running on your local machine so you can quickly see all the warning messages it emits and view the generated HTML output. I usually just run python -m http.server 8080 -d .\build\doc\html and leave that running so I can view the generated docs at http://localhost:8080 and just use "Ctrl+Shift+R" each time I run scons doxygen.
Have you given any thought to an example? Comparing properties calculated using these models with the ideal/low-pressure model might be interesting, and would give us a rare example focused on just transport properties.

include/cantera/transport/HighPressureGasTransport.h

speth · 2024-06-21T23:01:31Z

include/cantera/transport/HighPressureGasTransport.h

+//These are the parameters that are needed to calculate the viscosity using the Lucas method.
+struct LucasMixtureParameters
+{
+    double FQ_mix_o;
+    double FP_mix_o;
+    double Tr_mix;
+    double Pr_mix;
+    double Pc_mix;
+    double Tc_mix;
+    double MW_mix;
+    double P_vap_mix;
+};


I'm a little confused by this struct. If these are all properties of the mixture, would it be simpler to just make them member variables of the HighPressureGasTransport class?

Yes, that is true. I was just leaning towards encapsulating those variables into a group to make it clear what variables are being set by the method that computes them and returns the struct. I tend to dislike methods that change the state of an object across a series of variables. I know that essentially the same thing is done when the struct is updated.

Is there a way to group variables together in the doxygen system?

There is (although we don't use it anywhere yet). Not sure whether we should start.

@param x,y,z These variables do something

include/cantera/transport/HighPressureGasTransport.h

src/transport/MMCollisionInt.h

speth · 2024-06-22T16:29:17Z

src/transport/TransportFactory.cpp

@@ -46,6 +46,7 @@ TransportFactory::TransportFactory()
    addDeprecatedAlias("water", "Water");
    reg("high-pressure", []() { return new HighPressureGasTransport(); });
    addDeprecatedAlias("high-pressure", "HighP");
+    reg("high-pressure-chung", []() { return new ChungHighPressureGasTransport(); });


Should we consider giving the high-pressure model a more specific name (and if so, what would it be)? From my reading of the Poling book, it's not clear to me what set of models you'd want as a "default".

This is definitely open to suggestions. The high-pressure model is a selection of 3 different models lumped together. Lucas for the viscosity, Takahashi for the diffusion coefficient, and that Ely and Hanley method for the thermal conductivity. It's hard to slap a name on that. With the Chung class, at least it's 2/3rd of Chung's work, so the name makes a little more sense, but even that might be unclear because it's using Takahashi's method for diffusion coefficinets (there is no Chung method in the Poling book for diffusion coefficients sadly).

Maybe high-pressure-LET and high-pressure-CCT, or high-pressure-LTE and high-pressure-CT Where we just use the first letter of the model name for the viscosity, thermal conductivity, and diffusion coefficient.

The transport class is essentially 3 smaller transport classes in a trench coat.

"3 smaller transport classes in a trench coat" is a very apt description. In the long run (but definitely not right now), it might be worth thinking of a different code structure that was more amenable to mixing and matching the individual models. I'm OK with just using high-pressure and high-pressure-Chung (note the capitalization) as the names for now.

test/python/test_transport.py

wandadars · 2024-07-01T20:48:01Z

The Ely and Hanley method used by the original high pressure transport class appears to be this one. So at least we know now where it came from. I will update that method now that we have a source for it.

wandadars · 2024-07-05T17:02:49Z

Thanks for sharing this work-in-progress, @wandadars. I'm glad to see this capability getting some attention, and I like where this is going in terms of providing a well-documented implementation of these methods. I've left a variety of comments, some of which I realize are addressing issues that you've inherited from the existing implementation. I think this would be a good opportunity to clean these up. Besides the in-line comments, I had a couple of general points:

Please format all lines with a maximum of 88 characters.

I'd strongly recommend getting Doxygen up and running on your local machine so you can quickly see all the warning messages it emits and view the generated HTML output. I usually just run python -m http.server 8080 -d .\build\doc\html and leave that running so I can view the generated docs at http://localhost:8080 and just use "Ctrl+Shift+R" each time I run scons doxygen.

Have you given any thought to an example? Comparing properties calculated using these models with the ideal/low-pressure model might be interesting, and would give us a rare example focused on just transport properties.

This was really helpful. Just as the text is, I think it would be great to have it included in that "contributing to Cantera" documentation section. I can't find the section now, but it was that one that you linked to previously that had notes about how to structure an example and things like that.

wandadars · 2024-07-05T22:47:01Z

I've got most of the suggestions completed. I added a new example that plots Lucas, Chung, and Ideal viscosities (Lucas is just the standard HighPressureGasTransport class). I moved those repetitive calculations up into an init method for the critical properties as well as the other fluid properties that are used in the mixing rules.

wandadars · 2024-07-10T15:45:37Z

I have completed the documentation/description of the thermalConductivity() method that was implemented in the original HighPressureGasTransport class.

@speth With regards to an example, I was thinking of maybe taking Methane and running a case at 350K over a range of pressures from 101325 Pa up to 60MPa using the high-pressure and high-pressure-chung models. Then also having a data file with a set of NIST data for methane over that range and plotting them together. What's the proper way to handle a data file for an example? Put the file in the samples directory? Something else?

wandadars · 2024-07-10T19:08:29Z

It took some time, but I added what I think is a detailed description of the Ely and Hanley model to a doxygen header comment.

speth · 2024-07-10T22:11:05Z

With regards to an example, I was thinking of maybe taking Methane and running a case at 350K over a range of pressures from 101325 Pa up to 60MPa using the high-pressure and high-pressure-chung models. Then also having a data file with a set of NIST data for methane over that range and plotting them together. What's the proper way to handle a data file for an example? Put the file in the samples directory? Something else?

I think that would be a decent example. For the data, the best way to handle it depends a bit on what it is. We've started moving some of the YAML input data used for samples into a separate repository (https://github.com/Cantera/cantera-example-data), with it being installed so you can import it with something like ct.Solution("example_data/whatever.yaml"). For experimental reference data, if its not too large, you can also just embed it in the .py file directly, like we do in the continuous_reactor.py example. A separate file alongside the .py file doesn't work very well as there isn't a good way to make it downloadable with the example script.

ischoegl · 2024-07-27T17:24:43Z

As a minor comment, this PR would finally (!) close issue #267 ... 🎉

wandadars · 2024-08-18T04:40:03Z

I ran the chung-high-pressure method and compared it with NIST data for pure methane at the same conditions.

wandadars · 2024-08-18T07:24:35Z

Some thoughts:

We can only use this model in conjunction with an equation of state that can provide critical properties.
The unity lewis number assumption might be applicable for this transport model as well. I'm not totally sure about this, but the lewis number assumption seems like more of a modifier than a full transport model.
There's that issue of the cubic eos' getting their data from the critical-properties.yaml file, but the transport models read their acentric factor from a section in the standard Cantera input yaml file, and if one isn't found, a default value is quietly used.
Both high-pressure transport models use that Takahashi method. If we split the models up into separate files, that shared function between them needs to be located elsewhere. I don't want to create an entire header just for that one function.

speth · 2024-08-18T15:27:46Z

The unity lewis number assumption might be applicable for this transport model as well. I'm not totally sure about this, but the lewis number assumption seems like more of a modifier than a full transport model.

That's true, but I also feel like if you're using a Le=1 transport model, you can't be very concerned about accuracy, so why bother with the extra complexity of the high-pressure model for other properties.

There's that issue of the cubic eos' getting their data from the critical-properties.yaml file, but the transport models read their acentric factor from a section in the standard Cantera input yaml file, and if one isn't found, a default value is quietly used.

I agree that this is worth resolving. I think the place to do it is in an override of getTransportData() method, which can be made virtual. In the high pressure versions of this function, what I'd suggest is to extend the set of cases for places that it looks for a value of the acentric factor, in order:

a non-zero value in the species GasTransportData object
A value in the critical-parameters section of the species input
A value from critical-properties.yaml. For this, I'd suggest a similar structure to how the critPropsDb/dbSpecies variables are handled in RedlichKwongMFTP::initThermo, where we avoid reading the database unless there's a species where we have no data.

wandadars · 2024-08-19T02:03:44Z

If I have 2 yaml input files that I want to use to test the critical properties parsing, where is the best place to put them? Into test/data?

ischoegl · 2024-08-19T02:22:04Z

If I have 2 yaml input files that I want to use to test the critical properties parsing, where is the best place to put them? Into test/data?

Yes, correct. That is the place we use to store input data for unit tests.

wandadars · 2024-08-19T02:41:24Z

Another comparison, looking at all the models.

I'm going to look again at the Chung model to make sure there is not error in it anywhere because I think it should be closer to the NIST data. But overall, they're tracking the nist data trend fairly well.

…tation

…method

…vate class variables

…ies.yaml, if needed

…st that would never work

… ideal

…the method as well

… high pressure transport model

…input files

…common species to crit database, and updated keywords file to prevent CI failure for new example

wandadars · 2024-10-24T19:48:09Z

Can you rebase and modify commit 2899db3 so it doesn't change the example_data submodule? Currently, this PR is reverting the example_data submodule to a previous version. If this sounds tricky, just let me know and I can do it and push to your branch.

That's strange. I don't even remember doing anything that would have caused that. I'll try to get that resolved.

My guess (which you might be able to help confirm) is that it's caused by using git add . or git commit -a after rebasing onto a commit after the submodule was modified. The issue is that changing branches or rebasing doesn't change the commit that's checked out in the submodule, so you will then see it as as being changed compared to your current commit until you run git submodule update.

Yes, that's likely what happened, git add -u probably. I think I fixed the issue.

speth

Hi @wandadars, thanks for these updates. I think this PR is very nearly done. Most of my comments below are related to a few minor tweaks to the input data files and the new example.

In addition, there are a couple of documentation updates that need to be made:

Please add an entry for the high-pressure-Chung model to doc/sphinx/reference/transport/index.md and revise the entry for high-pressure to explain the differences between the two models.
Please add an entry for the new model in the YAML documentation, doc/sphinx/yaml/phases.rst, under the transport section.

Update: The one other request I'd make is for a few additional tests to improve coverage of the newly introduced methods. Right now, there are no tests of any of the newly introduced methods except incidentally through the tests that check that the input data is being handled as expected. While you've shown that it's hard to get a good "ground truth" reference value to compare to due to the limitations of the thermo models, we could at least introduce some regression tests, with the comparison values marked clearly as such and perhaps reference values from the textbook or NIST with a short explanation of why we don't expect to be able to match them exactly. If you can do this for both the new class as well as the HighPressureGasTransport class, I think we can finally mark #267 as completed.

data/methane_co2.yaml

data/critical-properties.yaml

doc/example-keywords.txt

samples/python/transport/high_pressure_transport.py

include/cantera/transport/HighPressureGasTransport.h

wandadars · 2024-11-04T21:10:42Z

I'm going to get rid of the test_acentric_factor_from_critical_properties test because I don't think it actually tests anything. I thought there was a failure mode where a user could provide a and b and leave out an acentric factor, but that isn't possible. So this test isn't actually useful.

wandadars · 2024-11-04T22:28:57Z

Hi @wandadars, thanks for these updates. I think this PR is very nearly done. Most of my comments below are related to a few minor tweaks to the input data files and the new example.

In addition, there are a couple of documentation updates that need to be made:

Please add an entry for the high-pressure-Chung model to doc/sphinx/reference/transport/index.md and revise the entry for high-pressure to explain the differences between the two models.

Please add an entry for the new model in the YAML documentation, doc/sphinx/yaml/phases.rst, under the transport section.

Update: The one other request I'd make is for a few additional tests to improve coverage of the newly introduced methods. Right now, there are no tests of any of the newly introduced methods except incidentally through the tests that check that the input data is being handled as expected. While you've shown that it's hard to get a good "ground truth" reference value to compare to due to the limitations of the thermo models, we could at least introduce some regression tests, with the comparison values marked clearly as such and perhaps reference values from the textbook or NIST with a short explanation of why we don't expect to be able to match them exactly. If you can do this for both the new class as well as the HighPressureGasTransport class, I think we can finally mark #267 as completed.

I added two new tests to test_transport.py that are modeled after the other tests in the test suite that utilize a reference data file for regression testing purposes. I don't quite see how we could use reference data beyond something like measuring an integrated error over a pressure range between the model's predictions and NIST data. I don't know if this would be any more useful than a standard regression test where we test the viscosity, thermal conductivity, and diffusion coefficient over a range of high pressures. (I may be misunderstanding your suggestion here)

…dels

speth

Thanks for the updates, @wandadars. Most of my comments here are about the documentation. I'd suggest looking through the generated HTML files to check these issues as you fix them.

I think the new tests are good -- a regression test that calculates values similar to what we're showing in the new example is a reasonable choice, and that example shows the degree of discrepancy between these models and the NIST data.

The one significant issue seems to be the one with the mixture-averaged diffusion coefficients. Right now, these appear to be identical to the ideal gas model because of the way the calculations are structured.

And one minor issue: please check the line lengths in HighPressureGasTransport.cpp to keep them to our 88 character limit -- there are some sections where this is being broken by a lot.

speth · 2024-11-12T20:04:58Z

include/cantera/transport/HighPressureGasTransport.h

+     * Where @f$ \eta_i^* @f$ is the referred to as the dilute gas viscosity and is the
+     * component that is temperature dependent described in @cite ely-hanley1981
+     * (see elyHanleyDilutePureSpeciesViscosity() ),
+     * @f$ MW_i @f$ is the molecular weight of species i, @f$ f_int @f$ is a constant


Suggested change

* @f$ MW_i @f$ is the molecular weight of species i, @f$ f_int @f$ is a constant

* @f$ MW_i @f$ is the molecular weight of species i, @f$ f_{int} @f$ is a constant

speth · 2024-11-12T20:08:51Z

include/cantera/transport/HighPressureGasTransport.h

+     * with @f$ h_{ij} @f$ defined by Equation 11 in @cite ely-hanley1983 :
+     *
+     * @f[
+     *   h_{ij} = \frac{1}{8} (h_i^{1/3} + h_j^{1/3})^3 (1 - l_{ij})


Suggested change

* h_{ij} = \frac{1}{8} (h_i^{1/3} + h_j^{1/3})^3 (1 - l_{ij})

* h_{ij} = \frac{1}{8} \left( h_i^{1/3} + h_j^{1/3} \right)^3 (1 - l_{ij})

speth · 2024-11-12T20:16:55Z

include/cantera/transport/HighPressureGasTransport.h

+     * Where @f$ MW_0 @f$ is the molecular weight of the reference fluid, @f$ MW_m @f$
+     * is the molecular weight of the mixture, @f$ f_{m,0} @f$ and @f$ h_{m,0} @f$ are


I think it would be good to be very clear that $MW_m$ is not the mixture molecular weight in the usual sense of that term, that is, just a mole-fraction weighted average of the species molecular weights, but instead some sort of "effective" molecular weight.

speth · 2024-11-12T20:21:44Z

include/cantera/transport/HighPressureGasTransport.h

+     * @note The correlations for the reference fluid viscosity return a value of
+     *       micro-grams/cm/s and the parts of the thermal conductivity that utilize
+     *       the correlation fit parameters give values in units of mW/m/K. Appropriate
+     *       conversions were made in the relevant functions.
+     *       @see elyHanleyDiluteReferenceViscosity()
+     *       @see elyHanleyReferenceThermalConductivity()


If you want to refer to these other two methods within the @note, you shouldn't use the special @see directive -- this causes them to be formatted in the HTML output as just general "see also" methods associated with the whole method, not specifically this note.

speth · 2024-11-12T20:23:46Z

include/cantera/transport/HighPressureGasTransport.h

+     * viscosity at high pressure is computed using the pure-fluid high pressure
+     * relation of Lucas with the difference being that mixture values of the
+     * model parameters are used. These mixture values are computed using the mixing
+     * rules described in @see computeMixtureParameters() .


Please check the resulting HTML documentation -- I don't think you want to use the @see directive here.

speth · 2024-11-12T23:00:54Z

doc/sphinx/reference/transport/index.md

+  phase entry to `high-pressure`. Implemented by class {ct}`HighPressureGasTransport`.
+
+Chung high-pressure Gas
+: A model for high-pressure gas transport properties that usesthe method of Chung


Suggested change

: A model for high-pressure gas transport properties that usesthe method of Chung

: A model for high-pressure gas transport properties that uses the method of Chung

speth · 2024-11-12T23:37:58Z

samples/python/transport/high_pressure_transport.py

+# Create the gas object using a subset of the gri30 mechanism for the methane-co2
+# system


Suggested change

# Create the gas object using a subset of the gri30 mechanism for the methane-co2

# system

# %%

# Create the gas object for the methane-CO2 system using reference state thermo from

# the GRI 3.0 mechanism, species critical properties from `critical-properties.yaml`,

# and the Peng-Robinson equation of state.

speth · 2024-11-13T00:04:48Z

test/python/test_transport.py

+        non-physical values. These non-physical values should trigger an error
+        in the high-pressure transport model.
+        """
+        gas = ct.Solution(test_data_path / 'methane_co2_noCritProp.yaml')


The test data path is automatically added to the Cantera search path, so you can just write:

Suggested change

gas = ct.Solution(test_data_path / 'methane_co2_noCritProp.yaml')

gas = ct.Solution('methane_co2_noCritProp.yaml')

and remove the fixture from the method.

The case where you need test_data_path is for accessing files that aren't read by Cantera's AnyMap/YAML functions.

speth · 2024-11-13T00:09:52Z

test/python/test_transport.py

+            thermal_conductivities.append(gas.thermal_conductivity)
+            diffusion_coefficients.append(gas.mix_diff_coeffs)
+
+        data = np.empty((len(viscosities), 3+len(diffusion_coefficients[0])))


Suggested change

data = np.empty((len(viscosities), 3+len(diffusion_coefficients[0])))

data = np.empty((len(viscosities), 3+gas.n_species))

speth · 2024-11-13T01:24:42Z

src/transport/HighPressureGasTransport.cpp

+}
+
+
+void HighPressureGasTransport::getBinaryDiffCoeffs(const size_t ld, double* const d)


I noticed that according to Codecov, this method doesn't get called, despite the fact that you've added a test that calculates the mixture-averaged diffusion coefficients which rely on the binary diffusion coefficients. I think the problem is that GasTransport::getMixDiffCoeffs just operates on the m_bdiff array directly, which here only contains the low-pressure binary diffusion coefficients.

Probably the most direct solution to this would be to override getMixDiffCoeffs, getMixDiffCoeffsMass, and getMixDiffCoeffsMole in HighPressureGasTransport so they use getBinaryDiffCoeffs.

ischoegl added the Transport label Jun 9, 2024

wandadars force-pushed the high_pressure_transport branch from 819f302 to 720e601 Compare June 10, 2024 21:41

speth self-requested a review June 21, 2024 00:36

speth requested changes Jun 22, 2024

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wandadars force-pushed the high_pressure_transport branch from 834d08d to da50a0c Compare August 18, 2024 04:09

wandadars force-pushed the high_pressure_transport branch from 675c8d0 to 1b334f8 Compare August 19, 2024 01:25

wandadars and others added 19 commits October 24, 2024 15:12

updates for documentation of the Ely and Hanley conductivity implemen…

f18aaa3

…tation

more work on documenting the Ely and Hanley method

06d878e

final updates for ely and hanley method

e87f571

detailed model description added for ely and hanley thermal conductivity

e6451c3

wrapped doxygen comment for thermal conductivity to 88 characters

b0a5768

[transport] fixed incorrect equation in binary diffusion coefficient …

a0e94e1

…method

[transport] removed mixture quantity structs and placed values as pri…

6df98a4

…vate class variables

[transport] changed the chung name to high-pressure-Chung

8c08115

[transport] added coding to get acentric factor from critical-propert…

516cf14

…ies.yaml, if needed

[transport] added new unit test, updated example, removed old unit te…

3013fdb

…st that would never work

[transport] fixed bug in debye to SI conversion, minor formatting tweaks

3b5082e

[transport] minor comment adjustments

254a6e5

[transport] limited ely/hanley methane correlation to 10,000 Kelvin

a21c5f8

[transport] change broken high-pressure test to use RK eos instead of…

ea15a8b

… ideal

[transport] cleaned up ely and hanley conduction, cleaned up docs on …

e7bb98f

…the method as well

[transport] prevent species that have a=0, b=0 from being used in the…

504bfd1

… high pressure transport model

[transport] added new unit test and fixed some issues with unit test …

d2395a9

…input files

[transport] fixed whitespace issues

58c8b23

[transport] fixed unit test failure for transport_models_test, added …

d0e2f75

…common species to crit database, and updated keywords file to prevent CI failure for new example

wandadars force-pushed the high_pressure_transport branch from 2079bf4 to d0e2f75 Compare October 24, 2024 19:13

speth requested changes Oct 25, 2024

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wandadars and others added 4 commits November 4, 2024 18:04

[transport] updated docs on high pressure transport models

666ed9e

[transport] added regression-type test for high pressure transport mo…

8c4f858

…dels

[transport] fixing formatting & removing unused files

29cbbc6

[transport] converted list to numpy array in sample

c4a16cc

ischoegl mentioned this pull request Nov 11, 2024

Tag beta version for Cantera 3.1.0 #1810

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speth requested changes Nov 13, 2024

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	* @f$ MW_i @f$ is the molecular weight of species i, @f$ f_int @f$ is a constant
	* @f$ MW_i @f$ is the molecular weight of species i, @f$ f_{int} @f$ is a constant

	* h_{ij} = \frac{1}{8} (h_i^{1/3} + h_j^{1/3})^3 (1 - l_{ij})
	* h_{ij} = \frac{1}{8} \left( h_i^{1/3} + h_j^{1/3} \right)^3 (1 - l_{ij})

		* Where @f$ MW_0 @f$ is the molecular weight of the reference fluid, @f$ MW_m @f$
		* is the molecular weight of the mixture, @f$ f_{m,0} @f$ and @f$ h_{m,0} @f$ are

	: A model for high-pressure gas transport properties that usesthe method of Chung
	: A model for high-pressure gas transport properties that uses the method of Chung

		# Create the gas object using a subset of the gri30 mechanism for the methane-co2
		# system

-# Create the gas object using a subset of the gri30 mechanism for the methane-co2
-# system
+# %%
+# Create the gas object for the methane-CO2 system using reference state thermo from
+# the GRI 3.0 mechanism, species critical properties from `critical-properties.yaml`,
+# and the Peng-Robinson equation of state.

	gas = ct.Solution(test_data_path / 'methane_co2_noCritProp.yaml')
	gas = ct.Solution('methane_co2_noCritProp.yaml')

	data = np.empty((len(viscosities), 3+len(diffusion_coefficients[0])))
	data = np.empty((len(viscosities), 3+gas.n_species))

		}


		void HighPressureGasTransport::getBinaryDiffCoeffs(const size_t ld, double* const d)

Update / Add High pressure transport #1704

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