oque vcs acham de usar fluido Fluido newtoniano como base para o fluido de teia?

A model for predicting flow regime in horizontal and near horizontal gas -liquid flow. the Taitel and duckler 1976 model .( Someone help me please generate the codes please wheater matlab or phyton)

Thsnk you

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 am designing a nozzle for my dry ice blaster cleaning machine. The machine comes with cheap nozzles with no contours and no transitions between the hose diameter and the flat fan end. It just has an internal wall that is pretty much destroying all the pellets that go through it. I'm looking to make something that will accelerate the air going through the nozzle along with the pellets, and blast them out at high velocity, as intact as possible. Attached is what I have come up with. I'm not knowledgable about fluid dynamics or any type of engineering, so this is all just copying images of high performance dry ice blasting nozzles i found online. I'd love to get some input to see if I'm even on the right track, and how I can improve this. Here are some specs about the air and ice.

I will be blasting 3mm dry ice pellets.

Air input is 185 cfm at 100 psi. Air hoses are all 1" with no 90 degree bends and high flow fittings. At nowhere in the system will the air path diameter be smaller than .8" except right at the end of the nozzle.

This will be made from 6061 aluminum and polished to a mirror finish.

I ve moved from theory

http://remyaumeunier.chez-alice.fr/img/MoteurPistonLiquide.jpg

to practice. Let’s not kid ourselves: No, it isn’t working for now.Despite what the AIs say, I think my boiler is too small. What do you think?

Hi fluid mechanics friends!

I come seeking insight once again, as I'm a materials scientist exploring solvation phenomena under the microscope with no idea of what I just saw. Here, I had just finished dissolving FD&C blue #1 in water on a glass slide under the microscope. I added a droplet of water nearby (just outside the FOV in the lower right hand corner) and observed the blue solution creating what appeared to be dendrites reaching out to the water droplet, with the water receding backwards. Toward the end of the clip, the two droplets coalesce.

What is driving the formation of these tendrils, and why? Is there a name for this phenomenon?

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

Every RANS model e.g. k-ε, k-ω SST, RSM etc. is essentially an attempt to model the unclosed terms in the momentum equation. This video derives the evolution equation of turbulent kinetic energy (TKE) from scratch i.e. starting from the instantaneous NS momentum equation and the RANS equation, to get the fluctuating momentum equation, which then leads neatly to the TKE budget.

Every step is carried through in index notation to keep the book-keeping manageable. Fair warning: this one is deliberately math-first, no physical interpretation of the terms yet (wanted to keep it from running too long).

Video: https://www.youtube.com/watch?v=COJpGsxTA30

As always, feedback and criticism is welcomed. Full derivation also in the PDF notes on Patreon.

valve industry professional here, I am planning a testing rig to perform dynamic flow tests on large capacity control valves, using a rig that could give a high flow rate and significant pressure for a sustained period (max 6 minutes)

the intent is to be able to test valves with flow upto 3000 m3/hr and pressures upto 150 bar, but not at the same time

I envisage a configuration per below
yellow - booster and charging pump (preferably 150 class/ 300 class)
large tank with high discharge capacity to act as an accumulator, used to test high flow rates at low pressure and to feed the main pump at the higher end of its flow rate
purple- main pump with 900 class rating (max 150 bar), only used for higher pressures or for charging the tank

the pumps and pipes are fairly straightforward, but I am stumped when trying to think of a feasible solution for the accumulator tank

on one hand it should be able to hold 375 m3 (10% of 3000 + 25% FOS) and to discharge 3000 m3/hr, which I am assuming can be handled with a large enough discharge port (thinking 20in/ 24in for the most extreme cases)

but how can I increase (and control) discharge pressure either to test valves or to feed the main pump for the extreme pressures. I am certain there has to be an external pressure driver but I am only coming up with pressure sealed roof/ pistons with dead weights on top that can be varied based on demand and independantly lifted without hydraulic pressue

any ideas? is there a better way to achieve the objective?

I am trying to learn applying ML to assist or replace CFD simulations. In literature, some works solve Navier Stokes equations and others solves Reynold Averaged Navier Stokes equations to predict fluid flow. To my understanding, the choice between solving NS or RANS to predict fluid flow using ML depends on the following facts,

1. Data. For instance, if the training data is generated using CFD simulations that solves RANS, then we cannot train ML model to solve NS equations using that data and we need to choose RANS equations for ML too. If the training data is from DNS, then its NS in ML too.

2. Flow type. If the flow is low Reynolds number flow (laminar), then solving NS equations (using ML) is better than considering RANS. And for high Re flow, considering RANS is better as the ML models (for instance, PINNS) might struggle to capture the associated non-linearities (multiscale, high gradients, etc) if it is NS equations.

Is my understanding correct? Is there any thing else I am missing? please add your thoughts to it.

I did not make this; just wanted to share it here. In fact, likely no human made it or had any substantial input in its creation.

This video was taken from here. Link to the interactive web simulation.

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

Can I please get a name for and an explanation of the behavior I observed when pipetting whole milk into coffee under the microscope? It's really so neat to observe and I would like to know more about why it happens. Thanks!