OpenFOAM

tahanson43206 · 2025-05-03 15:12:03

Update after a long day chasing bugs ...

Our attempt to add 25 new cells to a structure with thousands of existing ones has revealed dozens of ways to break the existing structure.

The process of resolving the error messages is challenging, because (it appears) a single point in the wrong place can cause a cascade of errors that adds up to many thousands.

My guess is that ChatGPT4o and I are close to finding that last pesky point, but OpenFOAM isn't much help. It tells us we have a point out of place, but it doesn't say where. Diagnosis is (apparently) 90% guess work and 10% ferreting hints out of the available data.

I sure am glad I didn't try to do anything more ambitious than adding a single ring of 25 cells to the end of the intake.

Update later:

In reviewing our steps, I went back to the beginning, and discovered that in the very first step, we somehow lost track of the count of points to be added. We added 51 instead of 52, so of course everything after that was off by that one point.
I've recreated the points and stored them in the points file.

(th)

tahanson43206 · 2025-05-04 12:44:59

If there is someone in the readership who enjoys working a numerical puzzle, here is a data file that ought to be a challenge:

https://www.dropbox.com/scl/fi/lgu7thih … 9potv&dl=0

This is the output of a Python program written by ChatGPT4o to find faces in a file for the Merlin Engine model.

The faces of interest are those associated with the points that comprise the leftmost set of points in the model.

The purpose of the exercise is to replicate the 25 cells that comprise the left edge of the structure (left = -X direction).

ChatGPT4o found 177 faces with at least one of the 52 points connected.

Of those a number are duplicates because more than one point will be associated with many of the faces.

I'm looking for a number like 101 faces that are unique, and are not part of the prior set of cells.

Each cell has six sides (top, bottom, East, West, North and South).

Update: Overnight, I figured out that the faces definitions must include both inside and outside.

25 cells have a total of 150 faces if they are standing alone. In combination, some faces are shared.

In addition, if the faces are defined as both "inside" and "outside" then we get counts that look closer to the 177 we found:

top: 25 cells so 50 faces
running total: 50 of 177
+X side: 25 cells so 50 faces
running total: 100 of 177
-X side: 25 cells so 50 faces
running total: 150 of 177
+ and - Y (with shared walls) 26 (no mirror because shared?)
running total: 176 of 177

By this accounting, I am short one face.

Perhaps one side facing out in Y is mirrored? But if one, why not both?

At any rate, the mystery of the 177 count seems almost resolved, if we assume OpenFOAM needs both inside and outside of each face.

Also, in thinking about this puzzle, I realized that the faces we found must have either four points (the top layer) or two points (all others) in common with the outside points. The list we have can be analyzed for the number of points shared with the top layer.

(th)

tahanson43206 · 2025-05-05 10:11:33

Work on the attempt to create a new layer of cells to be prepended to the existing Merlin Engine model is continuing.

Wording revised 2025/05/05:
In early study today, it has been confirmed that most of the 177 faces identified as connected to the leftmost points are mirror sets. This is consistent with the OpenFOAM structure of "inside" faces and "outside" ones. It appears that faces that do not have mirrors are faces that are shared between two cells. Study so far is still delivering mysteries. For example, a study to find mirrors in the 177 faces found earlier resulted in identification of six faces that do not meet the minimal criteria of a mirror. There may be another category of faces that do not have mirrors.

Investigation continues. I cracked open the 2011 documentation I have for about an hour today. I saw a lot that is familiar do to working on this project in 2025. The core features (the architecture) of OpenFOAM appears to have changed very little, but the software that performs the work sure has.

One thing I was surprised to find is that an "stl" file (such as created by Blender) can be fed into the OpenFOAM mesh create utility. And that was back in 2011, so I expect that feature is still available. That's an option, if the current effort to extrude the existing intake proves too difficult.

(th)

tahanson43206 · 2025-05-10 12:17:39

This post is to report a mini-milestone.

Setup:

The goal of the Optical Plane OpenFOAM project is to simulate the new engine gas heating system.

We are using an inherited Merlin Engine model, which works with modern OpenFOAM software.

The immediate challenge is to learn how to grow or extrude the left facing edge of the intake to create a pipe for heating.

A first attempt came close but failed, because neither ChatGPT4o or I understand what we are doing.

checkMesh is an OpenFOAM utility that looks at mesh created by automated systems (such as the Merlin engine) and human ones.

It likes the Merlin engine model.

It went blooey over the human created glob I was trying to stick on the front.

In an effort to try again, I've decided to print the points and faces on business cards.

The first phase of this effort is complete. I now have 52 business cards printed on Avery business card stock.

The next part of this process is to try to print the identical information on the backs of the existing business cards.

ChatGPT4o wrote a little line swapper utility for me, and it swapped the lines in the CSV input file so now the printout should appear on the back of the existing sheets with the columns swapped so the printout matches what is on the front. I'm hoping to complete that process today.

I'm hoping to have the 52 cards ready to show attendees of tomorrow's Google meeting.

Update at 21:20 New Hampshire time:

All 52 cards are printed front and back. The sequence of steps, and the specific steps themselves, are factors that lead to success or failure.

The default font is 12 so if you want a larger font (such as 16) you have to set ** that ** variable on the generated page of business cards ** before ** you start adding fields. There are several ways to add fields but only one seems to work (insert from top menu > fields > more fields)
You have to remember to newline each entry from the database. You have to remember to insert the Next Record after the last field, before you click Synchronize). To make things even more complicated, the default page configuration is for a book with left and right pages, so you have to remember to change that setting to Right Only. Fortunately, if you forget, at Print time, the Preview page will allow you to confirm you are about the print the correct page.

I got six good pages of business cards and only "wasted" two (used for practice). I wasted a ** lot ** of 8.5x11 paper!

The next print phase is 177 face cards, and ** that ** will be more complicated because many of these (if not all) must be printed with different information on front and back. The points cards were easy because they were printed the same on front and back. The only complication there was to swap columns when printing front and back, so the cards match front and back.

ChatGPT4o and I studied the cards I printed, and compared them the intake. it turns out the order of the cards is opposite to what I expected, because I sorted them (inadvertently) in positive Y instead of negative Y. At the time of the sort, my first concern was to insure that we got the + and - Z values adjacent to each other. I don't think the order with which we lay the cards on the table makes any difference to OpenFOAM. What ** is ** important is the ID of each point, because ** that is crucial for creating new faces that will eventually comprise the six sides of 25 new cells.

Here is what we were looking at:

(th)

tahanson43206 · 2025-05-11 10:01:02

This post is to report progress toward the next mini-milestone...

ChatGPT4o was able to create a Python program that collects the 25 faces we see in the end-on view of the Merlin intake.

The collected data is formatted for printing on business cards, so I will attempt to complete that operation today. The data includes both sides of the 25 cell outside faces, so there are a total of 50 lines of data. My intention is to attempt to print front and back.

(th)

tahanson43206 · 2025-05-13 19:29:59

This post is to report on another mini-milestone...

The printed business cards served their purpose.

The cards helped to create a mental structure that delivered an insight about what data to request.

ChatGPT4o generated a program that delivered all 150 faces of the outermost 25 cells of the existing model.

I'll print the cards tomorrow, and hope/expect to be able to visualize how to use that data to create the data that must be added to the existing mesh to prepend a layer of 25 cells. It is ** still ** going to be tricky to figure out how to create the new data, but this new result is definitely a step in the right direction. I won't print all 150 lines, but here is what a bit of it looks like:

cell_id,face_id,point_ids,face_type,rotation,orientation_hint,position_hint
0,0,"(0, 14117, 28307, 14190)",internal,CCW,card face angled,inside share
1,0,"(0, 14117, 28307, 14190)",internal,CCW,card face angled,inside share
0,1,"(0, 14190, 28379, 14189)",internal,CW,card face -X,inside share
1,2,"(14118, 28308, 14239, 49)",internal,CCW,card face angled,inside share
2,2,"(14118, 28308, 14239, 49)",internal,CCW,card face angled,inside share
1,3,"(0, 49, 14239, 14190)",internal,CW,card face -X,inside share

(th)

tahanson43206 · 2025-05-15 15:23:26

This is an update on the (somewhat tedius) process of attempting to visualize the structure of the OpenFOAM mesh we inherited, in order to prepend a new layer of cells to the existing ones.

An earlier attempt to write code to generate the new cells failed due to errors, caused in large part by lack of knowledge of the landscape.

I printed a couple hundred business cards to try to get a handle on the situation, and today I was able to match the sides of one cell (Cell zero) to the points at it's corners. The cell has six sides, and there are 8 points, and after some trial and error, I was able to lay all 14 cards so they make sense. I found the top and bottoms of the cell, the two sides that face the Z surfaces, and the two internal sides that are shared with adjacent cells. There's a bit of work still ahead. There are 150 sides in the new row, but we only need to define 101 of them. At the moment, I am not yet sure which 101 those are.

Generation of the new data for the new cells will involve:

52 new points (easy enough, because the change is only in the -X direction by .25 meters)
101 sides out of 150 that are involved. The top faces (outward facing) are easy enough.
The faces that front the Z sides are also easy enough to identify.
It is the shared faces that I'm unsure about. Those have to be defined by OpenFOAM rules, which I do not yet know.

(th)

tahanson43206 · 2025-05-16 08:55:53

This post is to report on reaching a milestone (as compared to previous mini-milestones)

This is a ** real ** milestone, because (as near as I can tell) we've achieved a balance in predicting the number of new faces that must be added to our mesh (the Merlin engine mesh inherited from an anonymous donor) to add a new layer to the intake.

If all goes well, the new layer will be replicated 240*4 (960) times, to create the heating tube for the Optical Plane space vessel engine.

Here is ChatGPT4o's version of the plan:

Merlin Engine Mesh Extension: Face and Ownership Accounting
We have successfully analyzed and balanced the required face definitions and ownership assignments for extending the Merlin intake mesh by one layer in the -X direction.
New Layer Summary:
- We are adding 25 new hexahedral cells at X = -0.65 meters.
- Each hexahedral cell has 6 faces, totaling 150 face references.
Face Type Breakdown
25 -X boundary faces (rear wall of new cells): new, appear in owner only
25 +X faces (shared with previous row): already exist, used in neighbour only
25 -Z boundary faces (floor): new, appear in owner only
25 +Z boundary faces (ceiling): new, appear in owner only
2 ±Y boundary faces (at ends): new, appear in owner only
24 +Y internal faces (shared between adjacent new cells): new, appear in owner and neighbour
Table of Entries
faces file: 101 new face definitions
owner file: 101 new entries (1 per face)
neighbour file: 24 new entries (for internal faces)
Total accounted references: 101 (owner) + 24 (neighbour) + 25 (reused +X faces) = 150
Conclusion
The arithmetic now balances:
25 cells × 6 faces = 150 face references
All required new faces are defined
Ownership and shared face assignments match OpenFOAM’s mesh specification rules
Next Step: Begin auto-generation of face geometry, owner, and neighbour entries based on this verified structure.
Thanks to all contributors who helped test and validate this mesh extension. This precision will help us scale to hundreds of rows with confidence.

There is a detail that lies ahead. The order in which points are entered into the mesh database for each new face is significant. The order must be clockwise for out facing faces and counterclockwise for inward facing ones. I have not yet learned how to tell the difference, so I'm hoping ChatGPT4o is able to solve that puzzle.

In the next phase, we will attempt (for the second time) to create the new faces. The exam will be given by checkMesh. 100% accuracy is required.

(th)

tahanson43206 · 2025-05-16 09:40:16

This post is about preparation for the next phase of the project to extend the intake to the Merlin engine model.

ChatGPT4o and i are trying to think through how a mass production set of software would work. The idea of a way of passing data between operations came up. Here is a tentative layout of a persistent_memory_file:

{
"layer_index": 0,
"last_layer_x": -0.400,
"next_layer_x": -0.650,
"points_start": 28380,
"points_count": 52,
"points_end": 28431,
"faces_start": 27890,
"faces_count": 101,
"faces_end": 27990,
"cells_start": 0,
"cells_count": 25,
"cells_end": 24
}

For readers who might not be familiar with the format above, it is called JSON (developed by JavaScript developers)
JSON is similar to something called XML developed by Microsoft.

The idea here is to facilitate adding one new layer at at time so we can verify that each new layer was done correctly, using checkMesh.

(th)

tahanson43206 · 2025-05-17 14:50:01

This post is about modest progress toward the goal of automatic calculation of all the updates needed for a new row of 25 cells. The past two day's I've put in a little under 8 hours per day in the attempt to have the new layer ready in time for Sunday's Google meeting. ChatGPt4o and I are building the new program feature by feature, and along the way adding new data files to hold key data from one iteration to the next. At this point, the points seem to be generated and stored correctly, and we spent most of today trying to figure out how to generate the new faces. This is the heart of the problem, so (from my perspective) it is not surprising progress is slow. ChatGPT4o is helping thousands of other customers while working with me, and it has to refresh it's memory of what we were doing every time I hit enter. f have to jog it's memory here and there, so we sometimes go around a stump several times before we eliminate it. As of this evening, I ** think ** we've developed a memory file for faces. My homework assignment is to compare my deck of 150 faces for the existing last row to the values stored in the new memory file. My plan is to mark the 101 face cards that are needed for the new face, and I should have 49 cards left over. Those are connected to the existing face and not needed for the new one.

(th)

tahanson43206 · 2025-05-18 20:49:58

Here is another image of the business end of the Merlin Engine model.

This image clearly shows the 25 panels I am attempting to extend in the -X direction. it also shows the constriction of the throat, and the huge flow region beyond, in perspective.

The work of generating a new layer of 25 cells is progressing slowly. A program to generate all the data for a new layer in a single operation is the immediate goal. The program has two phases. The easy phase is to create 52 new points in the -X direction, and add them to the points file. That part is working reliably. The far more difficult phase is to generate 101 new faces. That work is in progress, and I would estimate it at 85% correct. The slow tedious examination of each of the 101 proposed faces is under way. I am using printed business cards of the 150 faces of the existing layer to attempt to confirm ChatGPT4o's proposed new faces. I know there is at least one mistake which is easy enough to fix, but there must be one more to find, because all 101 faces have to be defined with the correct points and those points must be "rotated" clockwise or counter-clockwise, and at this point, I still don't know how to tell which is which.
(th)

tahanson43206 · 2025-05-19 11:36:23

This post is about the work being done by GW Johnson to help to solve the urgent problem of on-orbit transfer of cryogenic fluids.

OpenFOAM is an open source publicly supported CFD package that is widely used in both academia (where it began) and industry.

I asked Google's Gemini for advice on how to investigate fluid flow inside a cylinder with an active mechanical component such as a fan or auigur.

Conversation with Gemini
Hi Gemini! Thank you for your assistance with many previous requests. This one is similar to one we just investigated, because it involves OpenFOAM. This study is for a different client, and the focus is motion of fluid inside a cylinder in microgravity, under the influence of mechanical devices of various shades, such as vanes or fan blades. Please look to see if you can find existing model or tutorial that include these features. The goal here is to find an existing models created by someone and placed in the public domain. We are aware that OpenFOAM can be configured to perform studies of various kinds, so please don't spent any of your valuable time thinking about that.
***
It's great to hear from you again! I remember our previous OpenFOAM discussions. Let's dive right into finding some existing models for fluid motion inside a cylinder in microgravity with internal mechanical devices.
Based on my search, it looks like finding a single, ready-made tutorial or model that exactly matches all your criteria (cylinder, microgravity, internal mechanical devices like vanes or fan blades, and public domain) might be tricky. These kinds of specific configurations are often tailored for particular research questions.
However, I did find some resources that come close and could be very helpful as starting points or for adapting:
OpenFOAM Tutorials Related to Rotating Geometries: OpenFOAM has several tutorials that deal with rotating geometries, which is a key aspect of modeling fan blades or vanes. These often use the MRFSimpleFoam or pimpleFoam solvers with moving reference frames. Examples include:
tutorials/incompressible/simpleFoam/mixerVessel2D: This 2D tutorial simulates a stirred tank, which shares the concept of rotating internal parts within a cylindrical domain. While it's not microgravity, you can adjust the gravity settings in the g field of the constant/g file to be near zero.
tutorials/incompressible/pimpleFoam/RAS/cylinder: This is a simulation of flow around a rotating cylinder. Although the focus is external flow, the mesh generation and rotation setup could be adapted for internal rotating devices.
OpenFOAM Cases Involving Microgravity: While less common in the standard tutorials, microgravity conditions are usually implemented by setting the gravitational acceleration vector g to a value very close to zero (e.g., g=(0,0,1e−9) or even g=(0,0,0)) in the constant/g file. You might find discussions or examples on OpenFOAM forums or community repositories where users have specifically addressed microgravity simulations. Searching for terms like "OpenFOAM microgravity" or "OpenFOAM zero gravity" could yield relevant discussions or even case setups shared by other users.
Community Repositories (e.g., on GitHub or GitLab): Often, researchers and developers share their OpenFOAM cases on platforms like GitHub or GitLab. Searching these platforms with keywords like "OpenFOAM internal flow", "OpenFOAM rotating impeller", "OpenFOAM stirred tank", combined with terms like "microgravity" might uncover relevant projects. Be sure to check the licensing of any publicly available cases to ensure they meet your client's requirements.
How to Proceed:
Given the likely absence of a perfect, ready-to-use model, the most efficient approach would probably involve:

Selecting a base tutorial: Start with one of the rotating geometry tutorials (like the mixerVessel2D or adapt the cylinder case).

Modifying the geometry: Adjust the mesh and boundary conditions to represent the cylindrical container and the specific design of the vanes or fan blades. This might involve using meshing tools like blockMesh or snappyHexMesh.
Implementing microgravity: Set the gravitational acceleration in the constant/g file to a very small value.
Adapting the rotating motion: Ensure the rotational motion of the internal devices is correctly defined using the appropriate OpenFOAM features for moving zones or rotating boundary conditions.
While this involves some adaptation, leveraging existing OpenFOAM tutorials for rotating geometries will save significant time compared to building a case from scratch.
I'll keep an eye out for any more specific public domain models that might surface. In the meantime, exploring the tutorials mentioned above and searching community repositories with relevant keywords would be a good next step. Let me know if you have any other questions!
***
Thank you for this guidance! The suggestions for looking for tutorials of a fan or augur inside a cylinder look particularly promising. I'll pass these suggestions along to the client! Best wishes for all possible success as you attempt to help the thousands of not Millions of us customers.
***
You're very welcome! I'm glad those suggestions seem helpful. I sincerely appreciate your kind words and well wishes – it's truly my aim to assist everyone effectively. Please don't hesitate to reach out if you or your client have any further questions or if there's anything else I can help with down the line. Best of luck with the project!

It appears there may be some opportunities to save time by using existing models. The problem of solving for microgravity appears to be addressable by simply setting the gravity variable to zero.

(th)

tahanson43206 · 2025-05-20 08:50:40

This post is about the ongoing, very slow and pains taking process of manually documenting every point, and every face of the 101 faces that must be correctly duplicated to create a new layer for the intake of the Merlin Engine model we have inherited from an anonymous OpenFOAM developer.

ChatGPT4o did a great deal of the preparation for this phase, but now there appears to be no way to further automate the documentation process.

There are 25 cells to be documented. Each cell has 6 faces, and each face has 4 points. Of the 150 faces, only 101 are actually needed for the new layer, but those 101 must be exactly right, with the correct points, arranged in the correct order.

At this point a review of the 25 cells in in progress, and five are completed. Each of the six faces must be marked up with the correct notation from the two sets of points in play. After the markup, the new "persistent memory faces" file must be edited to reflect the results of the card review.

It may take all week to cover the 25 cells. After that, there will be gaps to fill, because I am deleting faces that should not be present in the starter file for the new layer.

I have no doubt there is a faster way to do this, but the risk of going faster is the introduction of errors, any one of which will be detected by the grading program "checkMesh", and unfortunately, there is no "grading on a curve". The work is either perfect, or is it rejected completely, with NO feedback on where the error might be.

Update later: Only one more cell was processed today, due to other obligations. Hopefully tomorrow will be more productive.

(th)

tahanson43206 · 2025-05-21 18:58:48

The count of cells completed is up to 9 out of 25. At the average rate of 30 minutes per cell, the work could be completed tomorrow, but that assumes no interruptions. The 30 minutes average takes into account all sorts of interruptions already.

I'm hoping the secret of how rotation works will seep in by osmosis.

(th)

tahanson43206 · 2025-05-24 11:33:39

Update on manual procedure to grok OpenFOAM structure...

The 25 cells were completed yesterday, so I asked ChatGPT4o to make a list of locations of the 104 points at the corners of the 25 cells.

The completed list is four pages long, consisting of landscape extended to 22 inches.

My idea is to label the corners of each cell with the correct point ID's. Hopefully this process will allow the structure to sink in by osmosis.

Whatever the structure is, it must be reproduced precisely in order to add a new layer of cells to the existing mesh.

I'll start work on cell 0 (Zero) shortly. I hope this goes faster than the 150 card label process went.

Update Saturday afternoon:

This phase is starting out slowly. I have applied labels to the -X face of Cell 0, and learned how OpenFOAM's output can be interpreted as A-B-C-D order on the face. I am still not clear on how OpenFOAM decides which point should be A in a particular case.

It is possible I don't need to know that detail, since we are going to be copying points from the existing row as we create faces from the new row.

There is something called the "right hand rule" and ChatGPT4o seems to think this works if you (the observer) is/are inside the cell facing the face in question. I note that when looking at the face from outside, the rotation is CCW. The question that I don't yet understand is which direction the thumb is pointing when the right hand rule is applied.

(th)

tahanson43206 · 2025-05-25 21:21:15

This is a report on a mini-milestone in the marathon to build the software to generate new cells for the Merlin Engine model we inherited.

I have created physical boxes to represent the cells, because I need the crutches to deal with the 3 dimensional chess involved.

ChatGPT4o has created numerous lists that work together to yield the coordinates to place on the boxes at the faces and the corners. I completed the first box for Cell 0 (of 25 from 0 to 24) and i discovered to my astonishment that the order of placement of cells was (is) Arabic and not English. Obviously I had expected the model to have been generated by a person of English speaking heritage, but in fact many users of OpenFOAM are academics from nations all around the world. My boxes are all labelled incorrectly, but since the points line up correctly, I can just re-label the boxes to match the actual cells.

Update the following day:

The left-right orientation of the cells at the leading edge of the intake to the Merlin Engine OpenFOAM model can be understood by changing the perspective of the view. I had been looking at the front edge of the intake as shown in the ParaView viewer. That is the perspective from the -X direction. It is possible that the software building the mesh was working from the +X perspective, in which case the placement of Cell Zero (0) at the far left is consistent with the English language convention. It ** also ** makes sense from a build point of view. The elements of the mesh are apparently laid down from a baseline at the far -X direction (ie, -0.4 meters), and added in rows until the extreme boundary is laid down in a distant +X direction.

The report below is intended to capture this moment in the long journey towards understanding OpenFOAM structure.

Verification of Face Orientation Using the Right-Hand Rule
As part of our detailed analysis of OpenFOAM mesh geometry, we have successfully confirmed that the point ordering and resulting face normal directions in our reconstructed model are consistent with OpenFOAM's conventions.
Key Observations from Cell 0 Physical Model:
The view is from the -X direction, looking toward +X.
In this view:
+Z is upward.
+Y is to the right.
The -X face of Cell 0 is defined by the following corner points:
A – upper left
B – upper right
C – lower right
D – lower left
The face point ordering is: A → B → C → D (clockwise).
Curling the fingers of the right hand from A to B to C causes the thumb to point along -X.
Conclusion:
This is a correct and proper application of the right-hand rule.
The face normal vector points outward along -X, consistent with being on the -X boundary of Cell 0.
This orientation matches OpenFOAM expectations for face definitions and boundary face treatment.
The clockwise point order (A-B-C-D) yields the expected outward-facing normal from within the cell.
This confirmation validates our model’s spatial coherence and provides a strong foundation for extending the mesh using programmatic generation of new cells and faces that will be accepted by OpenFOAM’s checkMesh tool.

(th)

tahanson43206 · 2025-05-28 08:56:46

The tedious process of creating physical models of the components of the intake of the Merlin Engine model in OpenFOAM mesh seems to be paying off. In this latest round with ChatGPT4o, we cleared up some errors I was making (not understanding the structure), and seem to have arrived at a point where construction of a Python program is starting to look feasible. A key discovery was that the placement of the origin point in an OpenFOAM face is completely arbitrary. Some software packages use a consistent starting point, such as placing the smallest numbered point as the origin, but it appears that OpenFOAM does not care in the slightest. We began to think about the functions that will be needed to process each face of the six sides of each cell, and we seem to have what looks like an outline of how to proceed.

One detail that I was worried about was how to deal with the "top" of the cell we are extending. It appears that we don't have to do much. All we do for those faces is to determine the needed information (? face ID ?) (? new cell ID?) and add it to the neighbour file.

You said:
We seem to be making crucial progress today. Please write a BBCode summary of the design of the Python program, including our plan for how to deal with the "floor" of our new cell. Because I logged off and you may have lost a portion of our active memory, I'll just remind you that "list" and "h" work well to organized your presentation. As you craft your presentation, please keep in mind it is likely to be helpful to us (you and me) as we pick up this process at a later date. What I am foreseeing is addition of logic for each of the six faces for each cell. When we complete that process, I ** think ** will have our program almost ready to go.

ChatGPT said:
Absolutely — today’s discussion has been a major step forward in establishing the logical foundation for the Python program. Below is a BBCode-formatted summary you can post to your forum or refer to later when you're ready to continue coding. It organizes the current design, with special focus on how to handle each of the six faces of each new cell, especially the important case of the shared “floor” face.
Design Summary: Python Program to Add a Row of Cells to an OpenFOAM Mesh
This document outlines the structure and logic for a Python program being developed to generate a new row of 25 cells in the –X direction of an existing OpenFOAM mesh. The goal is to create valid points, faces, owner, and neighbour entries that extend the intake of a Merlin engine simulation.
? Key Mesh Facts
Each hexahedral cell has 6 faces and 8 corner points.
The existing 25 cells at the intake end of the model define 150 total faces.
126 of those faces are boundaries (listed only in owner), and 24 are internal (shared between two cells, listed in both owner and neighbour).
Each face must:
Be listed once in the faces file,
Have exactly one entry in the owner file,
Optionally have one entry in the neighbour file (if it is internal).
The new cells will share one face (the “floor” face) with existing cells.
? Loop Logic: Processing One New Cell at a Time
For each of the 25 new cells, the program will:
Create 4 new corner points (shifted by –0.25 in X from the current layer) and reuse 4 old ones.
Define six faces in total:
Floor Face (shared with existing cell):
Already exists in the faces file.
Already has an owner (the existing cell).
✅ Do not add it again to faces.
✅ Do not add it again to owner.
✅ Do append its face index and the new cell ID to the neighbour file.
Top Face (–X side of new cell):
Completely new face.
✅ Add to faces.
✅ Add to owner.
Optionally: add to neighbour if it will later be shared.
Left, Right, Front, and Back Faces:
Each may be new or shared with another new cell.
✅ If new: add to faces and owner.
✅ If shared: add to neighbour with the new cell ID.
? Summary of Face Handling
Face Type Exists Already? Add to faces? Add to owner? Add to neighbour?
Floor (+X) ✅ Yes ❌ No ❌ No ✅ Yes
Top (–X) ❌ No ✅ Yes ✅ Yes (maybe)
Sides ❌ or ✅ ✅ If new ✅ If owner ✅ If shared
? Notes on Point Order and Orientation
OpenFOAM does not require a specific point to be first in a face (e.g., "A" point).
Point order must follow the right-hand rule so the face normal points outward from the owner cell.
When reusing a face (e.g., the floor), you must preserve its original point order exactly.
✅ Next Steps
Finalize functions to define new points and track point IDs.
Implement per-face logic for all 6 faces of a cell.
Build faces, owner, and neighbour lists for the new layer.
Test output with checkMesh to confirm correct structure.
This plan lays the foundation for a robust and flexible mesh extension tool. As each face-handling rule is encoded, the program will move closer to a working prototype ready for integration into your OpenFOAM workflow.
Let me know if you’d like to start implementing one of the face-generation rules next, or if you’d prefer to work on point indexing and tracking!

It's taken a while to reach this point, and I expect it will be a bit further before the program is running.

(th)

tahanson43206 · 2025-05-28 18:49:18

ChatGPT4o thinks there is a 95% probability that we finally nailed the New Row Update program.

Here is one of the outputs.

{
"layer_index": 1,
"last_layer_x": -0.65,
"next_layer_x": -0.9,
"x_increment": -0.25,
"new_points_start": 28431,
"points_count": 52,
"points_end": 29731,
"new_faces_start": 55964,
"faces_count": 150,
"faces_end": 56114,
"new_cells_start": 13899,
"cells_count": 25,
"cells_end": 13924
}

I have NO idea if anything actually happened. In previous runs we did not try to perform actual updates. We spent a lot of time trying to get the status report to work. In the current iteration, ChatGPT4o ** thinks ** it wrote output to the actual files we are trying to update. I'll wait until tomorrow to find out.

There are many details that have to be 100% correct, for the updates to be accepted by checkMesh.

Here is what the detail memory file looks like:

==> persistent_memory_cells_202505282031.json <==
{
"cell_13899": {
"id": 13899,
"faces": {
"_share": {
"face_id": 55964,
"point_ids": [
52,
14169,
28359,

The file itself goes on for hundreds of lines. If it is correct, it will feed into the next layer processing.

(th)

tahanson43206 · 2025-05-31 13:38:28

This has been a long day. Trying to reach the goal in this situation reminds me a bit of what it might be like to try to land a dingy in a rough sea. It seems as though we are ** almost ** at the landing, when a sea swells up and carries us back.

ChatGPT4o and I tackled the problem this evening, and seem to have landed the dingy. Here is a report on what we ** think ** is the correct inventory of work to be performed to create a new layer of cells in our Merlin Engine model:

Face Assignment Plan for a New Row of Boundary Cells in OpenFOAM
After detailed investigation and programmatic verification, we now have a clear picture of how faces are added or shared when a new row of boundary cells is created in OpenFOAM.
These new cells are on the boundary of the mesh and form a 2D layer in a 3D domain. This geometry has key consequences:
There is no sharing in the ±Z direction, as there are no adjacent cells in Z.
Faces in the ±Z directions must always be owned, even if adjacent visually.
Only the –Y and +Y directions offer opportunity for face sharing between adjacent cells in the row.
Each new cell shares its bottom face with the cell below, transitioning that cell from boundary to interior.
Per-Cell Face Assignment Summary
Each of the 25 new cells includes:
1 new –X face → top face (owned)
1 new –Z face → side wall (owned)
1 new +Z face → side wall (owned)
1 new –Y face → rear wall (owned)
1 shared +Y face → connects to next cell in row (24 of these shared across 25 cells)
1 shared bottom face → from layer below (25 shared faces)
Total Face Breakdown for the New Layer
New owned faces: 25 (–X) + 25 (–Z) + 25 (+Z) + 25 (–Y) + 1 (+Y endcap) = 101
Shared faces: 24 (+Y between cells) + 25 (bottoms) = 49
Grand total: 101 + 49 = 150 faces involved (exactly 6 per cell for 25 cells)
This clear face budget gives us a reliable map for implementing the next stage of our layer-building utility.
Special thanks to the program that analyzed face ownership, and to continued clarification and collaboration that surfaced key boundary handling rules in OpenFOAM.

Update:
In a short evening work session, ChatGPT4o and i added two more OpenFOAM files to our layer_addition_program. In addition, we changed the name of our "Master Memory" file to master_memory.json
Here is a copy of the terminal window report:

python3 layer_addition_program_V26.py
? Loaded persistent memory for 25 cells.
? Loaded master memory.
? Loaded faces: 55814 owner: 55814 neighbour: 27436
? Loaded points: 28432, entries found: 0
? Loaded boundary: 6, entries found: 38
? Add layer logic not yet implemented.
✅ Saved updated memory to persistent_memory_cells.json
✅ Saved updated memory to master_memory.json

(th)

tahanson43206 · 2025-06-04 08:54:30

This is an update on the manual editing of the command/control memory file for the new layer program.

The editing of all 150 faces is complete. The next step is to ask ChatGPt4o to write an additional section of code for the new layer program.

At present the new layer program is opening all the relevant OpenFOAM files, plus the master memory and the cells memory files, but only minimal checking is performed at this point. Today I'll attempt to persuade ChatGPt4o to write a section of code to compare the structure of the cells memory file to what is expected, and then to check the stored data against the existing structure.

When that is working, there is nothing left but to write the updates.
Update:
ChatGPT4o wrote a little section of code to check my work and it found two errors. I'll make the corrections and try again.

Update:
I corrected the two errors that ChatGPT4o found, and I found one more it did not find.

Update:
Version 36 of the layer_addition program is waiting for the big test later today.
This version loads all the files and checks them for consistency before proceeding to the update phase.
This most critical new feature is correct rotation of old points from top to bottom of new cells, and placement of new points in the correct order.

(th)

tahanson43206 · 2025-06-05 18:49:57

Today's work session went well. I had a big challenge lined up for ChatGPT4o, but I caught it on a good day, and it performed the task adroitly.

We had three programs going into today's session.

Program 1 was written a couple of weeks ago, and it updated points perfectly. However, we stopped work on that program because things went astray after points was completed.

Program 2 was completed a few days ago. it performed exhaustive validation of all input files (I think we're up to seven at this point) but did dummy updates.

Program 3 was completed (if that's the word for it) yesterday. I had given ChatGPT4o a chance to try (once again) to make the giant leap to the end state and what we got was a mix of good code and bad, and I was unable to figure out which was which.

Today I asked ChatGPT4o to merge the good code from the points program into the validation program, and we did something a bit unusual. It generated the new code to be installed (by me) into the validation program, so I had complete control over the merge. We made a couple of adjustments after the installation, and the final product appears to be generating new points reliably.

Tomorrow we'll tackle the far more difficult faces update. however, I think it is possible the code for that was generated in program #3, and we may be able to copy and paste it. We'll see.

(th)

tahanson43206 · 2025-06-06 10:03:49

This is an interim report...

Building on yesterday's success creating new points, ChatGPT4o and I created a new block of code to create faces. We were careful to let ** me ** perform the update. In the past, we have lost large sections of code when ChatGPT4o tries to do everything. I attribute this to the nature of storage in the environment where ChatGPT4o "lives". ChatGPT4o only has some (unspecified) number of "tokens" to hold data for a given customer session. When I ask ChatGPT4o to do more than it can handle, it doesn't have any way of knowing of data gets dropped.

We have moved into a phase of the project where I see us as very close to the end, and I don't need any more confusion.

The new code does everything for faces in a single block that I've added, and that block is called from a single execution line which I've added as well.

It will take some time to set up the test environment. All the needed files are stored in a restart folder.

Update later: ChatGPT4o and I seem to be getting into a groove! I have learned a few of it's failure modes and have learned how to head them off at the pass. It took multiple iterations to arrive at what looks like successful creation of 150 new faces for the new layer of the Merlin Engine model, and I still have quite a bit of checking to do to be sure files were actually updated correctly. Here is the report from the program:

python3 layer_addition_program_V41.py
? Loaded persistent memory for 25 cells.
? Loaded master memory.
✅ 'faces' count matches: 55814 entries.
✅ 'owner' count matches: 55814 entries.
✅ 'neighbour' count matches: 27436 entries.
? Loaded faces: 55814 owner: 55814 neighbour: 27436
✅ 'points' count matches: 28380 entries.
⚠️ WARNING: 'boundary' declared 5 entries, but 32 were read.
? Loaded boundary: 5, entries found: 32
? Verifying face label correctness and completeness:
✅ All face labels valid and complete for all cells.
? Generating new points...
✅ 52 new points added at X = -0.4
? Updated 'points' file with new layer of coordinates.
? Generating new face entries...
✅ Appended 150 new faces. Total is now 55964.
? Add layer logic not yet implemented.
✅ Saved updated memory to persistent_memory_cells.json
✅ Saved updated memory to master_memory.json

(th)

tahanson43206 · 2025-06-06 21:08:58

ChatGPT4o and I seem to have completed updates to handle faces.

We started work on owner and neighbour files, but there is more to do.

Here is the output of the latest version:

python3 layer_addition_program_V44.py
? Loaded persistent memory for 25 cells.
? Loaded master memory.
✅ 'faces' count matches: 55814 entries.
✅ 'owner' count matches: 55814 entries.
✅ 'neighbour' count matches: 27436 entries.
? Loaded faces: 55814 owner: 55814 neighbour: 27436
✅ 'points' count matches: 28380 entries.
⚠️ WARNING: 'boundary' declared 5 entries, but 32 were read.
? Loaded boundary: 5, entries found: 32
? Verifying face label correctness and completeness:
✅ All face labels valid and complete for all cells.
? Generating new points...
✅ 52 new points added at X = -0.4
? Updated 'points' file with new layer of coordinates.
? Generating new face entries...
✅ Appended 150 new faces. Total is now 55964.

? Updating 'owner' and 'neighbour' files...
✅ 'owner' count matches: 55814 entries.
✅ 'neighbour' count matches: 27436 entries.
✅ Appended 150 owner entries and 75 neighbour entries.
? Add layer logic not yet implemented.
✅ Saved updated memory to persistent_memory_cells.json
✅ Saved updated memory to master_memory.json

Update later:
The count of neighbour entries looks high to me, by 2.

It should be possible to determine the location of each face by looking at the points that comprise it.

For example, if all the X coordinates are the same, then the face is either a floor or a ceiling.

If the Z coordinates are the same, then the face is on either the +Z wall or the -Z wall.

If the Y coordinates are the same, then the face is either a +Y wall or a -Y wall.

If the X face is on the +X side then it is a floor (from our perspective) and it is shared with the previous layer.

There should be 25 of those shares.

If the Y face is on the far +Y side then it must be a boundary and cannot be a share.

If the Y faces is on the -Y side then it too must be a boundary and cannot be a share.

All the other Y faces must be shared, so the total would be 48, and the grand total would be 73.

The grand total of boundary faces should be 25 top, 25 +Z, 25 -Z and 2 Y faces so 77.

A utility program should be able to resolve the issue.

(th)

tahanson43206 · 2025-06-07 08:59:43

Today's opening work session was devoted to implementing a validation step for the faces we are passing via the persistent_memory_cells.json file. Every face is orthogonal to some axis (X, Y or Z) so all four points that define that face must have identical values in the field for the orthogonal coordinate. It is easy for a computer to check those points, since all the data is already in memory.

ChatGPT4o agreed with the proposal, and created a def (a function) to implement the new procedure. I'm not expecting any problems, because I spent a lot of time manually configuring the file, but it will be a relief to know the file passed this rigorous test.

This was another long but ultimately productive session. The new faces are created but today's task was to update the persistent memory file so the program could work on the next layer.

Regarding the procedure to check the memory file ... that turned out to be unhelpful because the faces in the existing intake are curving in toward the throat of the nozzle. The intake we are building will NOT slope, so we might return that code to service. In the mean time it is disconnected.

The latest version (#50) is reporting success at the terminal window, but what actually happened will require some time, and I'll put that off.
Update late on Saturday (local time)
We are up to version 53 of the layer program. We are adding functionality to the program incrementally, and isolating new code from the base as much as possible, to avoid damage to the working structure. In today's session we addressed some defects in the preparation for and writing of the memory cells save file. The program completed and reported success, but of course we won't know until the output is examined. I'll do that tomorrow. It's been a long day.
python3 layer_addition_program_V53.py
? Loaded persistent memory for 25 cells.
? Loaded master memory.
✅ 'faces' count matches: 55814 entries.
✅ 'owner' count matches: 55814 entries.
✅ 'neighbour' count matches: 27436 entries.
? Loaded faces: 55814 owner: 55814 neighbour: 27436
✅ 'points' count matches: 28380 entries.
⚠️ WARNING: 'boundary' declared 5 entries, but 32 were read.
? Loaded boundary: 5, entries found: 32
? Verifying face label correctness and completeness:
✅ All face labels valid and complete for all cells.

? Generating new points...
✅ 52 new points added at X = -0.4

? Updated 'points' file with new layer of coordinates.

? Generating new face entries...
✅ Appended 150 new faces. Total is now 55964.

? Updating 'owner' and 'neighbour' files...
✅ 'owner' count matches: 55814 entries.
✅ 'neighbour' count matches: 27436 entries.
✅ Appended 150 owner entries and 73 neighbour entries.

✅ Built 25 new cell entries for persistent memory.
? Add layer logic not yet implemented.
✅ Saved updated memory to persistent_memory_cells.json
✅ Saved updated memory to master_memory.json

(th)

tahanson43206 · 2025-06-10 12:01:31

After restarting work at Version 57, today ChatGPT4o and I tackled the tricky output of faces data.

The new/adjusted code seems to have run without causing a Python error, but the results will be examined later today.

$ python3 layer_addition_program_V58.py
? Loaded persistent memory for 25 cells.
? Loaded master memory.
✅ 'faces' count matches: 55814 entries.
✅ 'owner' count matches: 55814 entries.
✅ 'neighbour' count matches: 27436 entries.
? Loaded faces: 55814 owner: 55814 neighbour: 27436
✅ 'points' count matches: 28380 entries.
⚠️ WARNING: 'boundary' declared 5 entries, but 32 were read.
? Loaded boundary: 5, entries found: 32
? Verifying face label correctness and completeness:
✅ All face labels valid and complete for all cells.

? Generating new points...
✅ 52 new points added at X = -0.4

? Updated 'points' file with new layer of coordinates.
? Generating new face entries Version 58...
✅ Appended 150 new faces. Total is now 55964.

? Updating 'owner' and 'neighbour' files...
✅ 'owner' count matches: 55814 entries.
✅ 'neighbour' count matches: 27436 entries.
✅ Appended 150 owner entries and 73 neighbour entries.

✅ Built 25 new cell entries for persistent memory.
? Add layer logic not yet implemented.
✅ Saved updated memory to persistent_memory_cells.json
✅ Saved updated memory to master_memory.json

Even after the program is working completely, we won't know if all the details are correct until we submit the work to checkMesh.

(th)

New Mars Forums

Announcement

#51 2025-05-03 15:12:03

Re: OpenFOAM

#52 2025-05-04 12:44:59

Re: OpenFOAM

#53 2025-05-05 10:11:33

Re: OpenFOAM

#54 2025-05-10 12:17:39

Re: OpenFOAM

#55 2025-05-11 10:01:02

Re: OpenFOAM

#56 2025-05-13 19:29:59

Re: OpenFOAM

#57 2025-05-15 15:23:26

Re: OpenFOAM

#58 2025-05-16 08:55:53

Re: OpenFOAM

Merlin Engine Mesh Extension: Face and Ownership Accounting

Face Type Breakdown

Table of Entries

Conclusion

#59 2025-05-16 09:40:16

Re: OpenFOAM

#60 2025-05-17 14:50:01

Re: OpenFOAM

#61 2025-05-18 20:49:58

Re: OpenFOAM

#62 2025-05-19 11:36:23

Re: OpenFOAM

Selecting a base tutorial: Start with one of the rotating geometry tutorials (like the mixerVessel2D or adapt the cylinder case).

Modifying the geometry: Adjust the mesh and boundary conditions to represent the cylindrical container and the specific design of the vanes or fan blades. This might involve using meshing tools like blockMesh or snappyHexMesh.

#63 2025-05-20 08:50:40

Re: OpenFOAM

#64 2025-05-21 18:58:48

Re: OpenFOAM

#65 2025-05-24 11:33:39

Re: OpenFOAM

#66 2025-05-25 21:21:15

Re: OpenFOAM

Verification of Face Orientation Using the Right-Hand Rule

#67 2025-05-28 08:56:46

Re: OpenFOAM

Design Summary: Python Program to Add a Row of Cells to an OpenFOAM Mesh

? Key Mesh Facts

? Loop Logic: Processing One New Cell at a Time

? Summary of Face Handling

? Notes on Point Order and Orientation

✅ Next Steps

#68 2025-05-28 18:49:18

Re: OpenFOAM

#69 2025-05-31 13:38:28

Re: OpenFOAM

Face Assignment Plan for a New Row of Boundary Cells in OpenFOAM

Per-Cell Face Assignment Summary

Total Face Breakdown for the New Layer

#70 2025-06-04 08:54:30

Re: OpenFOAM

#71 2025-06-05 18:49:57

Re: OpenFOAM

#72 2025-06-06 10:03:49

Re: OpenFOAM

#73 2025-06-06 21:08:58

Re: OpenFOAM

#74 2025-06-07 08:59:43

Re: OpenFOAM

#75 2025-06-10 12:01:31

Re: OpenFOAM

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