-
-
Notifications
You must be signed in to change notification settings - Fork 349
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Revive 1D radiation improvements of PR965 #1799
Open
wandadars
wants to merge
2
commits into
Cantera:main
Choose a base branch
from
wandadars:1d_radiation_update
base: main
Could not load branches
Branch not found: {{ refName }}
Loading
Could not load tags
Nothing to show
Loading
Are you sure you want to change the base?
Some commits from the old base branch may be removed from the timeline,
and old review comments may become outdated.
Open
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
We should integrate RadLib into Cantera. The library is written in C++ and has Python and Fortran interfaces. It is well-documented, and published. I can provide details, and would like to be involved.
Repository:
https://github.com/BYUignite/radlib
Publication:
V.B. Stephens, S. Jensen, I. Wheeler, D.O. Lignell, “RadLib: a radiative heat transfer model library for CFD,” Computer Physics Communications, 272:108227<https://doi.org/10.1016/j.cpc.2021.108227>, (2022).
Documentation:
<https://ignite.byu.edu/radlib_documentation>
RadLib: RadLib<https://ignite.byu.edu/radlib_documentation>
ignite.byu.edu<https://ignite.byu.edu/radlib_documentation>
[X]<https://ignite.byu.edu/radlib_documentation>
David O. Lignell
Professor, Chemical Engineering
Brigham Young University
801-422-1772 | http://ignite.byu.edu
On Oct 21, 2024, at 9:10 PM, Chris Neal ***@***.***> wrote:
I was looking through the open pull requests and saw #965<#965> . It seemed like it was something that could be pushed across the finish line given the recent updates to Cantera that allow for easier handling of data in the YAML file.
Potentially allows for the discussions in Cantera/enhancements#72<Cantera/enhancements#72> to be realized.
I added some of the data from the original pull request into the gri30.yaml file (attached), and ran the 1D diffusion flame example<https://cantera.org/examples/python/onedim/diffusion_flame.py.html>
gri30.txt<https://github.com/user-attachments/files/17469322/gri30.txt>
From the discussions in the #965<#965> it seemed like there was more than one possibility for handling that absorption coefficient calculation, so I added a keyword of fit-type which can be table or polynomial. The polynomial type is what was originally used and the table is the log linear interpolation data that was apparently better. PMAC is Plank Mean Absorption Coefficient. I'm pretty clueless on radiation modeling, so if anyone else knows more about this, please chime in.
As an example this would be the YAML entry for a species C2H6 that used the log-linear interpolation tabulated data.
- name: C2H6
composition: {C: 2, H: 6}
thermo:
model: NASA7
temperature-ranges: [200.0, 1000.0, 3500.0]
data:
- [4.29142492, -5.5015427e-03, 5.99438288e-05, -7.08466285e-08, 2.68685771e-11,
-1.15222055e+04, 2.66682316]
- [1.0718815, 0.0216852677, -1.00256067e-05, 2.21412001e-09, -1.9000289e-13,
-1.14263932e+04, 15.1156107]
note: L8/88
transport:
model: gas
geometry: nonlinear
well-depth: 252.3
diameter: 4.302
rotational-relaxation: 1.5
radiation:
model: PMAC
fit-type: table
temperatures: [200.0, 300.0, 400.0, 500.0, 600.0,
700.0, 800.0, 900.0, 1000.0, 1100.0, 1200.0, 1300.0, 1400.0, 1500.0, 1600.0,
1700.0, 1800.0, 1900.0, 2000.0, 2100.0, 2200.0, 2300.0, 2400.0, 2500.0, 2600.0,
2700.0, 2800.0, 2900.0, 3000.0, 3100.0, 3200.0, 3300.0, 3400.0, 3500.0]
data: [0.38479552555827473, 0.330335973067736, 0.4412642688261878, 0.7234904395389986,
1.3047333754840624, 2.4582817867678797,
4.728954047788753, 9.185141033669707, 17.899543021230603, 34.850795560924084,
67.58893234939407, 130.26844542962587, 249.09122926085138, 471.9318246172849,
885.130031885148, 1642.3336783887491, 3013.480869817436, 5466.6396914389925,
9803.371388627636, 17379.457798083575, 30460.7202083096, 52790.33601327037,
90480.336797945, 153407.43112853833, 257355.273339689, 427303.61580306507,
702366.9359563864, 1143267.5642510268, 1843354.9491235327, 2944846.812649131,
4662659.170473707, 7318745.5983123155, 11391692.329199707, 17587602.579628713]
And for the case where the older polynomial fits (I'm not sure how prevalent/standardized this form is) are used, we specify using:
radiation:
model: PMAC
fit-type: polynomial
data: [-0.23093, -1.12390, 9.41530, -2.99880, 0.51382, -1.86840e-5]
Tagging the original creator of the pull request and the user who opened the enhancement. @lavrenyukiv<https://github.com/lavrenyukiv> @BYUignite<https://github.com/BYUignite>
…________________________________
You can view, comment on, or merge this pull request online at:
#1799
Commit Summary
* a9bf1e5<a9bf1e5> [oneD] reproducing PR965 with yaml file addition
File Changes
(3 files<https://github.com/Cantera/cantera/pull/1799/files>)
* M include/cantera/oneD/Flow1D.h<https://github.com/Cantera/cantera/pull/1799/files#diff-33e21ca309e69ad7952e02cc9817dd9a4ce057e21c59a8276888d732a08bef6d> (34)
* M src/oneD/Flow1D.cpp<https://github.com/Cantera/cantera/pull/1799/files#diff-14affd62b2c5b0e4c4d0001f3d72e5f0d3044785ac027e39455a5ebbcde5121b> (115)
* A test/data/air_radiation.yaml<https://github.com/Cantera/cantera/pull/1799/files#diff-89aaafb4bfefb80fc680b8d43085d4181f8a8d8819c75755c1085bfb5306095b> (274)
Patch Links:
* https://github.com/Cantera/cantera/pull/1799.patch
* https://github.com/Cantera/cantera/pull/1799.diff
—
Reply to this email directly, view it on GitHub<#1799>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/AD5XI7IHQ3XVMWIHZXOSZV3Z4W64HAVCNFSM6AAAAABQLOYRYKVHI2DSMVQWIX3LMV43ASLTON2WKOZSGYYDIMBZG42DANY>.
You are receiving this because you were mentioned.Message ID: ***@***.***>
|
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
I was looking through the open pull requests and saw #965 . It seemed like it was something that could be pushed across the finish line given the recent updates to Cantera that allow for easier handling of data in the YAML file.
Potentially allows for the discussions in Cantera/enhancements#72 to be realized.
I added some of the data from the original pull request into the gri30.yaml file (attached), and ran the 1D diffusion flame example
gri30.txt
From the discussions in the #965 it seemed like there was more than one possibility for handling that absorption coefficient calculation, so I added a keyword of
fit-type
which can betable
orpolynomial
. Thepolynomial
type is what was originally used and thetable
is the log linear interpolation data that was apparently better. PMAC isPlank Mean Absorption Coefficient
. I'm pretty clueless on radiation modeling, so if anyone else knows more about this, please chime in.As an example this would be the YAML entry for a species C2H6 that used the log-linear interpolation tabulated data.
And for the case where the older polynomial fits (I'm not sure how prevalent/standardized this form is) are used, we specify using:
Tagging the original creator of the pull request and the user who opened the enhancement. @lavrenyukiv @BYUignite