Just curious about how different is ChemE transport 1 (momentum transfer) from MechE's Fluid Mechanics.
In my uni transport 1 is 5 credits vs 6 credits of FM.
Wondering if there are fundamental differences or is it mostly the same as far as depth and difficulty.
For reference we study transport from BSL and MechEs study from Frank White's fluid dynamics
I had this thought about an air pocket at the bottom of a vase-like shape that goes into water.
If you were able to maintain the air pocket, wouldn’t the weight of the water overcome the air pressure, creating continuous flow?
I was bored when i noticed the vortices appearing when i mixed my chocolate-oreo-sugar menjurje lol
I have being studying Compressible Fluid Dynamics and 1D Euler equations. I learnt that information propagate in three waves speeds: u-c, u, u+c. So the domain of dependence and range of influence must be bounded by them. I did not understand this?
So we have a linear hyperbolic homogeneous PDE,
del U / del t + A * del U / del x = 0
Assuming A is a 3x3 matrix, we can diagonalise it as A = Q^-1 D Q and let dV = Q^-1 dU. Now, we get three ODE,
Here, lambda_1, lambda_2, lambda_3 are eigenvalues of matrix A. So far so good.
Now, how did we come to the conclusion that the domain of dependence and range of influence must be bounded by the smallest and largest wave speed (eigenvalue)?
I expose two documents that belong to an ongoing program. They are not presented as closed results, but rather as a set of derivations and open points that I would like to submit to technical scrutiny. Both are written in a deliberately programmatic register: they distinguish postulates from consequences, and mark explicitly what remains open.
It proposes an ontology in which the relational radius is quantised in binary octaves, Rϵ=2−ϵ, and space is generated as a proportion to that radius. From this one obtains, without an independent postulate, k=1/R, hence the dispersion Ω(k)=ck—identical to the linear dispersion of the continuum—but now with thresholds at kϵ=2ϵ. The period is ln2.
The result I would like to subject to examination is the following: the bare continuum, without imposed structure, shows no peak in the log-wavenumber autocorrelation at Δ=ln2; the same test, applied to the response modulated with the predicted octave periodicity, detects the peak and its harmonics. The discriminant is operative, at least in simulation on the continuum itself. The falsifiable prediction is therefore modest but sharp: log-autocorrelation in the ringing band, with a local maximum at Δ=ln2.
The technical question I would like to discuss is whether this test is truly blind to other mechanisms—for example, boundary conditions or geometric modes with built-in scale symmetry—and whether the choice of detrending (polynomial degree 3–6) and band truncation could introduce false positives. The document includes a status table (derived / postulated / open) which I consider honest, but I would welcome criticism on whether any of those labels is too optimistic.
It is an anchor note that addresses a question left open in the first document: whether the pending sign—the unresolved branch of a square root—is recursive or not. The answer I find is affirmative: n↦n2↦(n2−1,n2+1), and the difference of squares reproduces the Mersenne identity M2k=Mk(2k+1). Hence the recursion is log-periodic with period ln2ln2, intrinsically.
In addition, the factorisation of the Mersenne spectrum separates two arithmetic modes:
The first pure-crystallisation level is ϵ=6, which coincides (by two independent routes) with the first level where Ior>0, i.e. the first nested pending sign. The proton appears as the base case: 4=2 with branches 3 and 5, whose product is M4.
The limitation I declare explicitly is that this structure is arithmetic and internal; I have not demonstrated that crystals, genes or discharge structures grow by this mechanism, although the analogy is tempting.
The technical question here is: is the identification of "new information = new prime factor" a forced interpretation, or is there some deeper reason that justifies it? Is the coincidence at ϵ=6 genuinely significant, or an artefact of small-number arithmetic?
I do not seek validation, but technical review: someone with more experience in spectral theory, signal processing, or number theory to examine whether the derivations are solid, whether the discriminant test has any hidden bias, or whether the connection between the continuum band and the octave ladder rests on some implicit normalisation I am not seeing.
I am also interested in whether the absence of a dynamical mechanism—what resolves the sign in the real world—invalidates the programme, or whether it can be treated as a geometry of possible states awaiting coupling to local boundary conditions.
The documents are written with their postulates exposed, and they do not attempt to conceal their weak flanks (especially the underived ϵ=4, and Postulate 3 as an undischarged root). Precisely for that reason, they seem to me suitable for open discussion.
I thank in advance for readings, objections, and references to analogous work I may have overlooked.
Final note: if anyone wishes to run the factorisations or the autocorrelation test, the scripts are short and described in the appendices; I can pass the code if there is interest .
Title:
STAR-CCM+ Francis Turbine CFD – Pressure-limited cells increasing despite good mesh. Should I keep iterating?
Body:
Hi everyone,
I’m simulating a Francis turbine in STAR-CCM+ and would appreciate some advice before I spend many more hours running the case.
Turbine (published design point)
Discharge: Q = 2.25 m³/s
Mass flow: 2250 kg/s
Net head: 38.335 m
Speed: 1000 rpm
Hydraulic efficiency: 0.93
Published shaft power: 786.9 kW
CFD setup
Steady-state
MRF (Multiple Reference Frame)
Water (incompressible)
Mass Flow Inlet = 2250 kg/s (Constant)
Pressure Outlet = 0 Pa gauge
MRF = +1000 rpm
Turbulence model: k-ω SST
Initial CFL was reduced (around 30–45) because higher CFL caused instability.
Pressure and torque monitored throughout the run.
Mesh
Total cells: ~7.3 million
Mesh diagnostics:
No negative volume cells.
Mesh is topologically valid.
Minimum face validity ≈ 0.784
99.96% of cells have face validity = 1.
Volume change statistics also look good.
So I don’t think the mesh quality itself is the issue.
Moment report
The moment report is calculated on the runner (cark) boundaries only, excluding the rotating interfaces.
Problem
Around 360 iterations:
Torque (moment) appears to be stabilizing around 2–4 kN·m.
TKE residual is now decreasing.
Outlet flow is becoming steadier.
However, STAR-CCM+ keeps reporting:
“Minimum absolute pressure limited to 1000 Pa on XXX,XXX cells”
The number of pressure-limited cells has actually been increasing over roughly the last 10 iterations.
Things I’ve already checked
Tried both +1000 rpm and −1000 rpm. The torque sign flipped with the rotation sign, so I’m currently using +1000 rpm.
Verified the rotating region contains only the runner.
Verified the interfaces.
Verified the outlet boundary.
Mesh quality appears good.
Using the published operating speed (1000 rpm) and published flow rate (2250 kg/s).
My questions
Is it normal for the pressure-limited cell count to keep increasing while the torque and TKE residual are stabilizing?
Would you continue running for another few hundred iterations, or would you stop and investigate before wasting more computation time?
If a steady solution converges but still reports a large number of pressure-limited cells every iteration, would you trust the resulting torque and efficiency?
What would you check next in this situation (boundary conditions, MRF setup, pressure reference, head calculation, something else)?
Any advice from people with STAR-CCM+ or hydraulic turbine CFD experience would be greatly appreciated.
Thanks!
Can the flow through an orifice cause backwater on itself even if the outlet pipe has sufficient capacity to convey the intended flow through the orifice?
Let’s say the outflow through the orifice causes the flow depth on the outlet side to rise above the centroid of the orifice, would that reduce the effective head? (Subtract from head on upstream side) Even though it’s not downstream conditions causing tailwater back onto orifice, but it’s just the flow depth on the outlet side caused by the orifice flow itself? Does that flow depth cause backwater?
Let us consider a circular pipe, initially empty, and an external body of water moving at a constant velocity $v$. At a certain instant $t$, this body of water enters the pipe through its inlet cross-section, which we will denote as $S_{0}$.
According to the no-slip boundary condition, the velocity of the outermost annular layer of fluid, which is in contact with the pipe wall, must be zero. This outer layer, in turn, slows down the adjacent layer. However, it does not have sufficient time to transmit this deceleration to the innermost layers.
In other words, at cross-section $S_{0}$ and at time $t$, the fluid layer in contact with the wall has zero velocity, the adjacent layer has a slightly reduced velocity, while the remaining inner layers still move at the original velocity $v$.
This implies that, over a time interval $dt$, the inner layers travel a distance $v\,dt$, which is greater than the distance covered by the outer layers (zero for the layer immediately adjacent to the wall). It would then seem that, at time $t + dt$, a gap should appear near the wall at the next cross-section $S_{1}$.
What exactly happens at this point? Do the fluid particles from the inner region move radially outward to fill this gap, somewhat like the flow in a fountain? If so, they would have to come to rest upon reaching the wall. Meanwhile, the particles passing above them are slowed down, but this effect still has not propagated to the innermost layers within such a short time interval.
Applying the same reasoning to the subsequent cross-sections $S_{2}$, $S_{3}$, $\ldots$, $S_{n}$ would seemingly imply that a boundary layer never forms.
So where is the flaw in this reasoning? How is this apparent paradox resolved? What is the actual physical mechanism by which an initially empty pipe becomes filled with fluid?
I recently made a YT video that explains flow through a venturi at the molecular level. The sim code is written in Processing.
I had some remnant code from an earlier simulation, and accidentally hit a key programmed to trigger a pressure pulse. The top image shows the pressure contribution of individual molecules, i.e. collision impulse magniude and frequency avaraged over a time interval. Bottom image shows drift velocity, again averaged over time.
Molecules exiting the screen to the right are inserted back into the high pressure region on the left.
You can clearly see the diverging flow go supersonic at some point, as well as a normal shock downstream.
Here is a link to the molecular flow explanation: https://youtu.be/7OAIH0vpZBc
Played around with oobleck under the microscope last year. Non-Newtonian fluids are so fun.
This video demonstrates a high-fidelity 2D simulation of the Magnus effect by modelling the trajectories of spinning spheres falling through a fluid medium.
Videos also available at
For code click https://github.com/zombimann/Mathematical-video-animations-and-visualization/blob/main/Bernoulli_Equations_Magnus_Effect.ipynb
You might also like https://np.reddit.com/r/3Blue1Brown/s/qxXGRIK2m2
I have a 2D pipe with pressure-driven flow. Inside the pipe there is a fluid blob of the same density as of semi molten metal but with infinite viscosity.
My objective is to observe how the surrounding metal flows past the blob and how the blob deforms under pressure.
The blob boundary should behave similar to a no-slip interface, while the pipe wall can be treated as a slip if required.
It is needed to be done in ANSYS FLUENT.
Any suggestions, example cases, or Fluent setup recommendations would be greatly appreciated.
Thank you!
Just curious on what brand of oil everyone is using for differentials and transfer case? I have. 2021 37PP. What brand or just stick with Motorcraft
I’m trying to understand what would happen in this pipe geometry.
If water enters from the top-left vertical section, would the pipe eventually fill completely with water, or would some air remain trapped in the lower horizontal section like in the image?
Pipe diameter is 3,8mm
In reality, this is not just one pipe, but two pipes with chambers: one arranged like in the image, and a second one mirrored to the right right next to it.
Any explanation about the flow behavior, air displacement, and pressure conditions would be appreciated.
Modern cities are currently being strangled by a "Surface Bottleneck" of our own making. For decades, traditional transit systems have functioned as immovable linear obstacles, monopolizing vital urban real estate to create artificial land scarcity and severe community severance. It is a profound mechanical inefficiency: the very highways and rails meant to connect us have become the walls that tear our urban fabric apart. To move forward, we must stop building barriers and start building bridges.
The Ringway system fundamentally reimagines physical infrastructure by abandoning the requirement for continuous, heavy ground corridors. At the heart of this shift is the Moving Cantilever Principle. In this model, the vehicle itself acts as a continuously moving cantilever beam, supported strictly at discrete, pillars spaced along its path. By dynamically shifting its structural weight across these sparse support points, the system eliminates the need for massive, light-blocking concrete viaducts. There is a structural elegance in this approach; by replacing crushing weight with a synchronized balance of forces, the system bridges open air with absolute integrity while leaving the urban canopy untouched.
The transition to a frictionless future is powered by the Magnetoplasmaionic (MPI) engine, a propulsion masterpiece that treats the atmosphere as a resource rather than a waste site. Unlike the fossil-fuel dependence of the traditional paradigm, the MPI engine operates through a sophisticated three-step cycle: Atmospheric Ion Harvest: The forward motion of the vehicle—aided by the pillar systems which act as active collectors—harvests ambient atmospheric ions from the surrounding air. Plasma Conversion: These ions are channeled into the onboard engine core, where they undergo highly controlled plasma-based energy conversion. Controlled Thrust: The resulting plasma state generates powerful, clean thrust, exhausting only safe, breathable air back into the environment. This effectively turns the surrounding air into fuel, delivering high-yield acceleration with zero localized emissions and decoupling our mobility from the carbon-heavy infrastructure of the past.
The modular nature of the Ringway allows it to overcome geographic scarcity that would stymie any traditional rail project. It requires no extensive terraforming, allowing it to be deployed in diverse environments from European mountain passes to arid deserts—where specialized deep-pile anchoring secures the pillars against shifting sands and canyon wind shear. Critically, the system enables seamless heritage integration. By maintaining a strict "Frictionless Gap" through pure magnetic levitation, the system offers Zero Vibration Impact. High-speed transit can now glide past ancient monuments and sensitive architectural sites without the mechanical degradation or acoustic pollution inherent in high-friction contact systems. We can finally connect our future without sacrificing our history.
How can I derive the continuity equation from Bernoulli’s equation. I feel like I’m missing an assumption for either equation, but from everything i remember they should have similar enough assumptions for this problem. Is it a difference between point velocity and average velocity, or does the continuity equation assume no pressure drop?
I'm trying to understand centrifugal pumps and I'm stuck on what seems like a contradiction.
In a centrifugal pump, the impeller accelerates the fluid — especially giving it a high circumferential velocity as it moves from the center toward the outer diameter. The fluid also gains kinetic energy.
At the same time, the law of conservation of mass (continuity) says that the mass flow rate must be constant: what enters the pump must exit (Qin = Qout for steady flow), as well as through the pump.
How is it possible that the fluid speeds up while the flow rate stays the same?
So in this case Container A is being pump fed by a 12000l/h pump and container B is being drained by multiple ways how do i make sure both water levels stay constant and the same on both?
is there any resource for this? do i just go overkill on 2 or 3 inch pipe?
Ich habe einen Radialverdichter, dessen gewünschter Düsenbetriebspunkt (geringer Volumenstrom, hohe Druckerhöhung) links der Pumpgrenze liegt und daher instabil ist.
Kann ich den Verdichter stattdessen auf einem stabilen Betriebspunkt mit derselben Druckerhöhung, aber höherem Volumenstrom betreiben und den überschüssigen Volumenstrom über einen Bypass abführen, sodass die Düse trotzdem den gewünschten Volumenstrom und Totaldruck erhält?
Oder verschiebt sich durch das Öffnen des Bypasses der Betriebspunkt zwangsläufig so (höherer Gesamtvolumenstrom, geringere Druckerhöhung), dass dies grundsätzlich nicht funktioniert?
A few weeks ago, I posted an overview of a turbulence course I'm putting together. The first lecture is now up: https://www.youtube.com/watch?v=myI2dymuUHM
It covers briefly how the flow transitions from a laminar to a turbulent state and highlight the role of Reynolds number which is derived properly from scaling arguments on the momentum equation. Alongside, the limiting cases (Stokes and Euler), what the characteristic scales actually mean for pipe flow and flat plate boundary layers, and a look at the Kelvin-Helmholtz instability is discussed.
It's aimed at senior undergrad, postgrad students and engineers who want a deeper understanding, not just the results. Notes are shared in the comments of the video. Feedback (both positive and constructive) is welcomed and appreciated.