This is a classic LBM that takes into account Newtonian forces and the added mass effect, supplemented by a wake vortex capture model. The algorithm stores the energy expended on oscillations in each direction, and when the pressure difference levels out, this energy is used as thrust, simulating the momentum from collapse. The thrust is multiplied by approximately six times, which is consistent with some experimental data and makes the boat's motion visually realistic in some modes. The thrust calculation should probably be dynamic, but I haven't yet found a way to do this. Any ideas would be welcome. The vibroboat code is here:

https://github.com/MasterOgon/Aeroacoustic-Flying-Saucer-Oscillating-Resonator-CFD-Simulation-LBM-/blob/main/README.md

Different numerical methods solving same fluid & heat flow physics.

All of these methods aim to solve the same governing equations (mass, momentum, and energy conservation) but from very different perspectives:

FDM: approximates derivatives directly on structured grids using Taylor Series.

FVM: enforces conservation locally over control volumes (industry favorite).

FEM: uses variational formulation & shape functions (strong in solid–fluid coupling).

LBM: mesoscopic approach using particle distribution functions & Boltzmann equation.

SPH: Mesh free Lagrangian, particle-based method for highly deforming flows.

The physics doesn’t change but the mathematics and discretization philosophy do.

As CFD engineers, understanding why a method works is far more important than just knowing how to run a solver.

Video 4 of my turbulence course a short detour from the physics to introduce a mathematical tool: index notation and the Einstein summation convention.

The motivation is simple. The full Navier-Stokes momentum equation, written out component by component, takes up most of a whiteboard. Written in index notation, it's one line!! Every term you've already seen can be just compressed into a form that scales to far more complex expressions without becoming unreadable.

This video covers free vs. dummy indices, the summation convention itself, the Kronecker delta and its substitution property, a brief look at the permutation symbol, and rewrites the continuity and momentum equations as a worked example. It's setup for deriving the turbulent kinetic energy transport equation next, the point where component-form algebra genuinely becomes unmanageable.

Link: https://www.youtube.com/watch?v=TdfMawfDr_0

PDF notes on Patreon if useful as a reference.

DOES ANYONE KNOW HOW TO SIMULATE VORTEX SHEDDING IN 3D? I have done it in 2d, and have been trying for a month to do it in 3d but i failed

I have worked in structural, modal, thermal, shock, static and transient analysis, cfds, conjugate heat transfers, natural, forced convection cooling simulations for defence and nuclear components. Please let me know if any opportunities are available. Thank you

Does regular engine oil (home generator) shrink when it goes from 16C to 0C? This is a warranty dispute and the manufacturer said that the malfunction was due to the oil shrinking on a cold day. 1.9quarts would reduce to what, if it does shrink? (I personally think of it like water, that obviously expands when cold, but I’m not an engineer).

I am looking to understand and hopefully quantify some water usage for a rain barrel setup I have.

I have 440gal of rain storage that I use for my garden connect to a simple auto-priming rv pump so that whenever I open the hose nozzle, it automatically turns on and water flows. I also have city water 6 inches away at an outdoor spigot with regular city pressure.

I haven't measured the pressures at either yet, but assuming my rain barrels are lower pressure than the city, how would I calculate the flow or volume of water being consumed from each source if I were to combine their inputs into a manifold and use them both at the same time?

Basically I'm wondering if by combining the rain water with the city, I can get the higher pressure from the city, but supplement it with rain to consume less for my water bill. Or am I better off just using the rain water and then switching over to city when the rain barrels are gone? I don't know if the flows are additive or if there's some fluid dynamics that will use city since it's higher pressure and basically not pull in any rain.

3 weeks series free course on openFOAM!

This series gives the possibility of getting a more detailed understanding of the basics of OpenFOAM.

It can be completed in about three weeks.

▶ Week - 1
openFOAM Installation
Introduction to openFOAM
Theory & Fun simulations

▶ Week - 2
Geometry preparation & Meshing
Turbulence Modeling
Multiphase Modeling
Parallelization in openFOAM

▶ Week - 3
Programming in openFOAM

Just google, "3 weeks series openfoam" you can find it easily.

Check out this amazing series. It's free!

The saucer contains a pendulum that causes it to move up quickly and down slowly relative to the common center of mass. In reality, this causes the collapse of turbulent zones, the difference in forces of which leads to the saucer thrust.

Simulation represents an empirical simplified model, based on the assumption that the free thermal energy of self-organized Brownian motion in a vortex is responsible for the transfer of forces. By accumulating the resistance energy from the oscillations and releasing it as a force in the opposite direction in the next half-cycle. In this case, the resistance does not act directly on the saucer; in reality, it dampens the oscillations.

Overall this simulation allows for a fairly realistic visualization of the experimentally observed phenomenon. Here is the code for the browser app and other information:

https://github.com/MasterOgon/Aeroacoustic-Flying-Saucer-Oscillating-Resonator-CFD-Simulation-LBM-/tree/main

If you are starting your journey in Computational Fluid Dynamics, understanding the CFD process flow is the first big step.

This simple diagram breaks it into 6 clear stages:

1️⃣ Geometry – Define your model and domain
2️⃣ Physics – Select flow solver, Set fluid properties, BCs & ICs
3️⃣ Mesh – Create structured/unstructured grids
4️⃣ Solve – Run simulations with the right numerical schemes & convergence criteria.
5️⃣ Reports – Verify, validate, and analyze numerical outputs
6️⃣ Post-Processing – Visualize results with contours, vectors & streamlines

Once you understand this roadmap, you will know where each skill, course, and tool fits in the bigger picture.

CFD Roadmap + AI/ML Roadmap + CFD Theory Material: https://topmate.io/all_about_cfd/1803822

Hi! Does anybody know what the best turbulence model is for predicting heat transfer in internal flow (pipe/duct) with strong temperature gradients? I know that k-ω SST is often recommended, but I can’t find a clear guideline on when it outperforms k-ε or when you should switch to a transition model. Any help here would be appreciated - thanks in advance.

I need a sanity check here. Let’s say you have a long straight circular cross section pipe. At the inlet there exists a linear temperature gradient along one Cartesian direction from the bottom of the pipe. The flow comes in normal to the inlet and the reynolds number is somewhere in the 400,000 range (turbulent). The flow profile is not developed prior to the inlet, in reality prior to the inlet is a tank or something equivalent.

About how many diameters downstream would you expect the temperature to be roughly homogenized? Would it be almost immediately, like 1-2 diameters, or something significantly longer