Hi, I'm trying to install OpenFoam v2606 on my Arch system from user repositories (AUR). I'm neither a Linux nor OpenFoam expert, so I'm not sure if my question is better suited for this subreddit or an arch/linux one.

What I've done so far on:

- manually installed all dependencies,
- cloned openfoam-com repo,
- run makepkg -s in the cloned repo directory.

My build seems to be done. It ends with "Build failed with 0 executables and libraries". Which I believe means that it has succeeded. Now the folder contains the following files:

Finished build

Normally I would just run:

pacman -U package_name-version-architecture.pkg.tar.zst

As per arch wiki but unfortunately there is no file with the .pkg.tar.zst extension.

If nothing works out, I might try building from source, though I doubt I will be successful since I've never tried that before.

Did anyone go through the process recently and can point me in the right direction?

Hey guys, I've got about a year of experience with OpenFOAM. I've run different types of simulations — SIMPLE, PIMPLE, incompressible, compressible, laminar, turbulent — on 2D airfoils and 3D aircraft, like the NASA N2A HWB model, with decent mesh quality and case setup. The post-processed results matched the reference data pretty well. Just sharing this to give some context on where I'm at with OpenFOAM, but I'm still learning and exploring more of it.

Lately I've been seeing AI/ML being used in CFD, and since I come from a non-coding background (I'm a Mechanical Engineer), AI/ML and neural networks still feel like a black box to me. I don't really know how they work under the hood.

So I wanted to ask — how can I actually use AI/ML and neural networks in aviation-related CFD work?

For context, my future work will mostly revolve around optimization studies, detailed aircraft analysis, and static/dynamic stability analysis of aircraft. So I'm hoping to understand how AI/ML can help speed things up, and ideally how to align with whatever the industry is currently doing in this space.

I'm interested in how FEA/CFD teams deal with the gap between simulation results and real-world test results.

For example, if a simulation predicts one result but the physical test gives something noticeably different:

• How do you determine what caused the discrepancy?
• Do you have a systematic process for correlating the simulation to the test?
• What data/tools do you normally use?
• Is this usually handled manually by the engineer?
• How much time can this investigation take?
• Are there particular parts of this process that are consistently painful?

I'm especially interested in how this works in industry rather than academic/research settings.

I'm trying to understand whether this is actually a significant engineering problem or just something that looks more painful from the outside.

I'm researching the workflow engineers use to manage CFD/FEA simulations, particularly when you have dozens or hundreds of runs with different meshes, solver settings, boundary conditions, models, etc.

I'm considering building a tool that would:

• track each simulation run and its settings
• keep runs organized/versioned
• compare results between runs
• automatically check things like convergence and mesh independence
• generate verification/validation reports

Before building anything, I want to understand how people actually handle this today.

For those of you who regularly use Fluent, ANSYS, OpenFOAM, Abaqus, etc.:

1. How do you currently organize your simulation runs?
2. Do you use folders, Excel, scripts, Git, a PLM system, or something else?
3. How do you compare a large number of runs?
4. How much of your verification/convergence/mesh-independence analysis is manual?
5. Do you have to manually create reports documenting your simulation methodology and results?
6. What's the most annoying part of this workflow?
7. If a tool automated some of this, what would it need to do for you to actually use it?
8. Would this be something you'd pay for? If so, what pricing model would make sense?

I'm particularly interested in hearing from people who have dealt with 20–100+ simulation runs rather than just a few cases.

I'm not trying to sell anything here — I'm trying to find out whether this is actually a problem worth solving before I spend months building it.

I've been working on a small open-source tool called OFGS (OpenFOAM Gnuplot Suite) to make some of the routine plotting/monitoring around OpenFOAM cases a bit easier.

It detects supported data in a case and can generate graphs, open individual plots or a dashboard, and live-monitor results while a simulation is running. There's also a doctorcommand for checking the OFGS/OpenFOAM environment.

It's deliberately pretty lightweight, essentially a CLI built around gnuplot rather than a replacement for ParaView or proper post-processing tools. There are definitely limitations to what data/plots it understands, and I'm sure there are OpenFOAM workflows I haven't accounted for.

I'm also not an OpenFOAM or engineering expert, I'm a humble HPC sysadmin who spends a lot of time around OpenFOAM users and wanted to streamline some of the repetitive workflow.
It's packaged for Debian 12 and Rocky Linux 9, or you can install/use it from source.

Would genuinely appreciate feedback from people who use OpenFOAM properly, especially anything OFGS gets wrong or could handle better.

Well, I decided to simulate free vortex (same as performed in our lab) using openfoam. I used ai to write the code but decided on Reynolds and some other values myself is it the correct way am I supposed to write the code on my own ?? Please I need guidance on what to learn in the code