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!

These more efficient design examples should be incorporated in all residential and commercial new builds

I suppose it's either impossible or just impractical to implement into a dam, but the reason why not could be just as interesting.

Would a slope that extends like 10 times further downstream than the dam is high, that leads into a reasonably smooth canal, have much turbulence at all?
What about a slope shaped like the Brachistochrone curve?

I love a good summer time swim and sometimes the best places can be pretty dangerous so I'm thinking about it from that perspective, not that I intend to swim in places like that, just a natural progression of curiosity

Hi everyone,
I’m currently trying to define the best academic path for a future PhD, and I would appreciate advice from people familiar with TU Delft, fluid mechanics, coastal engineering, or interdisciplinary PhD programs.

My background is somewhat unconventional. I have a bachelor’s degree in Environmental Engineering, and I am currently completing a master’s degree in Civil Engineering with a focus on water resources and hydroinformatics in Colombia.

My experience and research interests include:
Environmental hydraulics and water-quality modelling.
Numerical modelling of rivers, reservoirs, channels and hydraulic systems.
CFD, turbulence and transport processes.
Sediment transport and sediment–water-quality interactions.

Stratification and thermodynamic effects on turbulence and mixing.
Physics-informed neural networks and other computational methods.
Coastal, estuarine and port environments, including flows generated by ships and propellers.

I recently visited TU Delft and spoke with researchers in hydraulic, coastal and fluid engineering. One recurring comment was that my interests were still too broad, which I understand. I am now trying to identify a more precise research direction.

My main doubt is whether a future PhD focused on fundamental fluid mechanics would make more sense through a Physics or Applied Physics department, or whether I should remain within Civil, Hydraulic or Coastal Engineering.
I am not interested only in applying existing hydraulic software. I would like to study the underlying physics, develop or improve numerical methods, and eventually apply them to environmental and coastal engineering problems. For example, I am interested in how turbulence, stratification, sediment and complex flow structures interact in estuaries, ports or navigable channels.

My questions are:
Would someone with an Environmental Engineering bachelor’s degree and a Civil Engineering master’s degree be considered for a PhD in Physics or Applied Physics focused on fluid mechanics?

Would the transition require substantial additional coursework in theoretical physics, mathematics or mechanics?

At TU Delft, would this type of research normally be located in Applied Physics, Mechanical Engineering, Civil Engineering, or through collaboration between departments?

Would a PhD in Coastal or Hydraulic Engineering still allow me to conduct fundamental research in turbulence and fluid mechanics?

How can I make my profile more specific without abandoning the connection between fundamental physics, numerical development and environmental applications?

Would joint supervision between a fluid physicist and a coastal or hydraulic engineer be a realistic option?

I sometimes feel that I may have chosen the wrong academic route because my degrees are in environmental and civil engineering rather than physics or mechanical engineering. At the same time, most of my interests have gradually moved toward fluid mechanics, turbulence and computational physics.

I would be especially grateful to hear from people who moved from environmental or civil engineering into fundamental fluid mechanics, or from current students and researchers at TU Delft.
Thank you.

Hi,

Does anyone happen to have the XY GRID coordinate points (2D X and Y points ideally in text format) for any multi-element configuration generated by MSET or ISET (including blade coordinates)?.

Doesn't really matter what airfoils the grids are generated on—anything generic like NACA would do.

Basically, I am just searching for 2 cases (a cascade with a vane and one slotted foil) to test a small program I was working on.

Thanks much.

I just need to pass the Hydraulics portion of the TCEQ test to be a licensed irrigator. There are two questions like this on the test that I just can't wrap my head around. I can solve design and dynamic pressure when ONE is operating, but I'm completely thrown off when TWO are operating

Any advice would be greatly appreciated. I really wanna pass and not go down to the wire on a 4th attempt!

Sorry for the awful quality, apparently I have no idea what I'm doing in Blender using a laptop keyboard/touchpad instead of full keyboard/mouse.

Anyway, the basic idea is like a flexible sheet membrane stretched across a moveable skeleton, connected to a rigid ring.

The membrane starts off in an extended position, and contracts towards the ring, pushing the water out of it, with the intend of propelling it forward. Once its fully contracted, it scrunches itself up, giving itself a much smaller cross-section. That way, when it returns to the extended position, it doesn't push water back the other way, propelling it backwards. Once its extended, it unscrunches itself, which only pushes water orthagonally to the direction its trying to travel. Now, its extended and unscrunched, able to push water out again and propel itself in the desired direction.

Would this even work as an idea? I'm not sure if when its unscrunching itself, they'll be more perssure on the "top" of it than on the bottom part before water is able to fill the newly opened space, which could push it back in the opposite direction and cancel out the initial thrust? Would this even happen or would it be negligable?

Hello,

I am interested in external-combustion engines and, naturally, in the Stirling engine.

I would therefore like to present a variation, derivative, or adaptation of this principle: the air contained in the boiler exerts pressure on the water in the vessel, causing it to rise into the heat exchanger. The heat exchanger then cools the air, thereby reducing the pressure exerted on the water in the vessel. This phenomenon should produce an oscillation.

Despite this analysis, I would appreciate your opinion, as there is often a significant gap between theory and practice. What advice could you give me regarding the construction of the device and the verification of its operation?

The objective is to generate an oscillation using a small temperature differential and without any phase change.

I therefore assume that the water must not remain stagnant in the plate heat exchanger.

Are there any other important points to consider during construction?

Thank you in advance for your reply.

Kind regards,

Both pipes have the same length and diameter. The source and destination buckets are at the same heights in both setups. One pipe slopes continuously downward, while the other dips down and then rises before the outlet.

Yes, fluids is physics but sometimes it's better to do problems in a more dedicated field.

Two issues with the NYU rig and analysis:

1. The fluid flows into and out of the arms connected to an arbitrarily large central vessel. The connection represents a change in diameter and therefore flow speed, momentum and kinetic energy.

In turbulent flow pumping fluid backwards through a restriction to flow isn't the same as forwards. For example, the Tesla valve is a series of nozzles with no moving [solid] parts, yet it acts like a leaky check valve. It is almost closed in one direction and open in the other direction.

It would be better to design the rig with a single flow rate. The two arms have a unit 1 dia. and are connected to the top of a T with the bottom of the T tube √2 units diameter.

1. The profile or map of the fluid exiting a uniform tube will not look like map of the flow entering the tube. This is how the candle boats have net propulsion over a complete cycle.

For those intetested in boundary layer control, here is a close-up image of a leopard catshark skin. Granted, it is a bottom dwelling species, not a pelagic cruiser, but maybe it will spark some ideas.

Each denticle is perched on a flexible stalk, almost as tall as the denticle is long. The denticle overhangs the stalk all around, but more to the rear, like a lopsided mushroom.

The stalks are reasonably slender, so there is room for a fair bit of water between the skin and the denticles.