The three-body problem broke Newton, broke Poincaré (who ended up inventing chaos theory trying), and was finally cracked open by Chenciner & Montgomery in 2000 — the figure-8 in clip 4 is their proof. Šuvakov & Dmitrašinović added 13 more families by 2013. Every clip is a real numerical integration of F = G·m₁m₂/r² with equal masses, no fudging. Math from 1687 still has surprises in it.
I created my first FDM CFD demo using Desmos. Currently, it can only process square grid, but I plan to use an FVM approach capable of handling unstructured meshes in the future. (I will likely build it in Python then.)
SPH fluid sim built from scratch in C++/CUDA + OpenGL, inspired by Sebastian Lague.
No prebuilt solver — physics implemented from scratch using Müller et al. 2003 equations
SSF renderer and simple sphere mode, switchable at runtime
Configurable UI — tune almost every parameter on the fly, dynamic sky, emitter controls
Hybrid sim time — runs realtime or stepped for long offline clips (for recording clips)
CUDA-OpenGL interop
REQUIRES NVIDIA GPU
uses only 3 terms : density, pressure and viscosity.
Optimized on RTX 2050 laptop— NVIDIA only, may have issues on other hardware.
1 million particles achievable in simulation mode.
SSF and UI production had AI assistance.
i wat made for interest in fluid dynamics and for astrophysics(n-body) project for future :)
if you like the project ,star my repo :XD
Does OpenFOAM support parallel processing for CPU and/or GPU native solve or co-solve?
Additionally, is possible to do any of this in WSL/WSL2?
I’m currently working on a simplified 3D CAD model of a CSOV designed in Solid Edge. I have two configurations: one with the W2W gangway stowed, and another with it deployed to its maximum length of 30 meters.
I need to run a basic CFD analysis to compare the drag/resistance between these two variants. I have like 2 day to give my masters papers to the supervisor.
I need a datatable (or chart) with resistance on Y and Speed on X, for those 2 cases, maybe free surface representation (i am not sure, i am looking at some other papers and they have stuff like this)
i know it might be imposible, i tried openFoam but it took me like 4h to set it up and still couldnt make it work. Siemens has Star CCM+ Trial but i cant upload my model there
Been working on this for a while now. It's a finite-volume solver for the compressible Euler/Navier-Stokes equations on unstructured meshes, written in C with MPI parallelism. The video shows the flow around a sphere at Mach 0.3, Re 1000.
The numerics are quite standard, but I think what sets it apart is that it can partition and redistribute the domain across MPI ranks at runtime, and can restart a simulation onto a completely different mesh.
Source on GitHub: https://github.com/hheinzer/teal
Happy to answer questions!
I wanted to ask what is the difference between shared topology and contact interfaces. Do they give same results? For a project of a big heat exchanger, which one would you do?
Can someone tell me how to do simulations in ansys fluent on Propeller ? Where to find affordable tutorials on srf , mrf , dynamic meshing and other things related to this?
Hi everyone! I've been invested in fluid mechanics research for a while now, and I've wanted to put together an introductory course on turbulence for some time. One that connects the physics directly to the equations that are derived from first principles. I've just posted an overview video kicking off that series. It's aimed at senior undergrads, postgrad students, and engineers who use turbulence models in solvers like ANSYS or OpenFOAM and want to understand what's actually going on under the hood.
The course covers two halves: the first on flow physics (Reynolds decomposition, RANS derivation, TKE budget, Kolmogorov theory, wall-bounded and free shear flows), and the second on modelling and computation (k-ε, k-ω SST, LES, solver implementation and data analysis). Lecture notes will be shared alongside each video.
If that sounds like something useful, the overview is here: https://www.youtube.com/watch?v=436HwwfMH4A
Happy to hear any thoughts on the structure or topics, always useful to know what gaps people feel are missing in existing resources.
I am a 2nd year mechanical engineering student, I want to get better at ansys i.e.analyses and simulations
If you could provide me with sources to learn more from, then that would be very helpful full
I also have animation videos of it but for some reason I am unable to upload them together with images
Edit: From the comments I understood that I should have plotted for the coefficient of lift and drag not just the force. And this geometry has 0° angle of attack, it was provided to us by the faculty. The domain is small because I was told so to make it this size. I learnt today that it should be 10x
Again thank you for the comments
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I am modeling premixed propane combustion in an atmospheric burner with conjugate heat transfer (CHT). The object is not a baking oven. It’s the MICCA laboratory combustion chamber from EM2C. It has a very low maximum mass-flow-averaged velocity of 0.6 m/s.
I use the SST turbulence model and the eddy dissipation model for combustion, together with the Westbrook and Dryer 2-step mechanism. I started modeling with only a tetrahedral mesh and without solid domains, because I got errors involving extremely low temperature in the boundary prismatic layers. After the first solution was interpolated onto the fluid mesh with prismatic boundary layers, I also got a normal solution. Unfortunately, when I tried to interpolate the last solution onto the CHT case, I got the same error after 70 iterations. The solid domain was initialized with a temperature of 300 K.
The time step for the fluid is 0.0002 s, and for the solid it is 0.01 s. After the first time steps, the temperature in the boundary layers decreased to 200 K.
For the solid-fluid interfaces, I use a conservative interface flux with zero thermal contact resistance.
Where am I making a mistake?
I am a MEng fresher with a passion for aerodynamics and fluid behavior. My interest in this field began with self study in high school and has grown into a focused career goal in Computational Fluid Dynamics.
I have already begun building my foundation by completing an aerodynamics study in OpenFOAM, specifically a square cylinder flow analysis at Re 100, 200, and 300, where I successfully achieved mesh independence. Additionally, I serve as an Aerodynamics and Chassis Engineer for my university's Formula SAE team, where I am currently learning ANSYS.
While I am dedicated to learning, I am finding the sheer volume of online resources overwhelming. To ensure I build a rigorous foundation, I would value your perspective on the following:* Learning Structure: How would you recommend a "fresher" structure their learning to transition from basic simulations to advanced CFD proficiency?
Project Selection: What types of projects should I prioritize to build a strong professional portfolio, and how should I approach them to demonstrate true technical depth?
Al Integration: Where do you see the most significant scope for Artificial Intelligence within the CFD workflow?
Skills & Pitfalls: Beyond software proficiency, what relevant skills are most critical for a CFD engineer today, and what common learning mistakes should I avoid?
Even a small piece of advice from your experience could be a major turning point for my career
Hi everyone,
I’m new to the sub. I’m a postdoc in a research group where we use micro-turbines to pneumatically spin rotors for chemical applications. We are currently pushing the limits of spinning frequencies (>50 kHz, goal: 200 kHz range) using very small rotors (approx. 0.5-2 mm).
Historically, cylindrical rotor designs have been used, but we are now transitioning to spherical rotor designs and improving their spinning efficiency. The stator for these spherical rotors is sort of a "cup" with air nozzles. I am looking to perform a multi-parameter optimization of the stator (nozzle count/angles, cup depth, exhaust geometry) to improve torque efficiency and stability.
Coming from a computational chemistry background, I’m used to Machine Learning Interatomic Potentials (MLIPs) that can solve chemical problems with the accuracy of classical quantum packages (computationally expensive) but at a fraction of the computational cost. Nowadays, we can even do calculations on personal laptops with the same accuracy of calculations that used to take a few days in HPCs with multi-node setups.
I’m wondering: Is there a CFD equivalent that is mature enough for this?
Specifically:
Are there any foundation models that actually handle high-frequency, transonic micro-flows well? Or am I better off sticking to a traditional package like OpenFOAM?
My goal is to run through a massive candidate space for optimization. If you were starting this from scratch today, would you build a PINN, use a Neural Operator, or just script a massive OpenFOAM parallel run on a cluster?
Disclaimer: I’m a CFD novice but a experienced in molecular simulations and HPC calculations. I’d love to hear from anyone using AI/ML to bypass the "re-meshing nightmare" of parametric optimization.
Thanks and feel free to correct me if I am saying something or assuming something that is wrong!
Hi there,
I have been working with external incompressible flows for Aerodynamics using OpenFOAM for my Master's thesis. I have recently become curious about numerical combustion, and I have been accepted into a PhD program. I am starting in the fall, and I understand there is a huge learning curve ahead. What resources do you recommend I keep using to get a head start on my PhD?
Been working on this for a while and finally released it. YFoil Aero runs entirely in your browser — open the link, start analyzing. No installation, no backend, completely free.
The entire thing — physics engine, panel solver, LLT, and the full NACA polar database — lives in a single HTML file. That was a deliberate choice: zero friction for the end user.
Under the hood: Nonlinear LLT (30 Fourier modes), Hess-Smith panel solver with Head boundary layer, real NACA polar data from Abbott & von Doenhoff (1959), wave drag, ground effect, static margin, XFOIL polar import.
Not trying to replace XFOIL or OpenVSP. Just wanted something fast and accessible for students doing early-stage design or trying to understand wing aerodynamics without a 2-hour setup. Accuracy limits are fully documented.
🔗 Live: https://mechanicfurkan.github.io/YFoil-Aero
🔗 Source: https://github.com/mechanicfurkan/YFoil-Aero
Happy to discuss the physics or compare results if anyone's interested.
I've been running some boltzmann equation simulation using an algorithm I've been working on involving a picard iteration type of thing derived from the boltzmann equation and the duhamel formula (which I've been doing some theory with).
I haven't been able to find much on this method in the literature. This is a car simulation I ran (on my work laptop not super powerful). Could anyone give me any resources or let me know if this is standard or something I haven't really done any serious CFD before just beginning to work in kinetic theory. But this seems like it could possibly be quite efficient in quite a few interesting domains if its not already known.
Hey everyone,
I’m actually an electrical engineer and I have basically no experience with CFD whatsoever, but I currently have a project where I need to simulate a canopy structure and study how the surrounding temperatures affect the people inside.
I also want to simulate adding fans inside the canopy and see how they affect the airflow and temperature distribution inside the area.
Right now I’m a bit lost on how to start, what workflow people usually follow, and what software would be best for this kind of project. It would be great if the software is free or at least budget-friendly.
Any recommendations for:
I’d really appreciate any advice. Thanks!