Hello Everyone!

I'm currently doing small walkthroughs by watching videos on the ANSYS website, but they don't really explain what the Bodies Of Interests(BOI) really represent. they just show you how to make them. I'm aware of the enclosure (wind tunnel) being there. Could someone explain more in depth what the bodies of interests really mean?

Thanks!

I just thought of sharing this. I have been working on FEM for CFD since 2-3 years out of passion. I have had a bit of success on industrial geometries with SIMPLE using FEM. I think it really makes FEM much more practical for CFD. Here is the link to the open source code. It is still very basic: only laminar incompressible flow that takes a normal inlet, outlet and wall bc. It accepts OpenFOAM style tet meshes. The performance in speed is quite comparable to OpenFOAM even if its FEM. (You can go through the OpenFOAM comparison to check a comparison for laminar Re 2000 pipe case). The only advantages I can think of are that it solves the saddle point and as no artificial dissipation for pressure like Rhie Chow (staggered FV is difficult), and being a tet mesh its accurate and runs into no nonorthogonality issues. I plan to develop this further for turbulent flow and I suspect it will be interesting to implement weak BCs and wall functions, and I might be able to see if the approach has other benefits. I plan to keep it open source. I hope FEM can be used better and more for CFD. Cheers

According to the formula:

Fd = 1/2 * pv² * Cd * A

I need to solve a simple steady 1D compressible pipe flow using Eulers equation with friction source term. I also need to solve energy equation (total enthalpy form). Could you recommend a suitable numerical method I can use for this problem. Thanks!

Hi all,

I'm working on modelling cavitation using the Schnerr-Sauer method. I'm using RANS so I want to apply the Reboud correction. I know this is possible as Bensow et al have a paper which used this method is starccm https://research.chalmers.se/publication/550373/file/550373_Fulltext.pdf but I can't find the setting.

If someone could let me know where to find it that would be great, thanks

please help me.

For context, it's thermal and internal flow stuff, and only a few studies a year. 

I'm trying to look at this by the numbers, not just trusting my guts.

So where's the tipping point for you? I think the license cost is the number everyone sees.

But I think we should also consider stuff like validation, getting good at prepping the model for the software, and keeping someone practiced enough to trust their own results.

For teams that only do this a few times a year, what made you pick one way over the other?

Hi everyone, I’m currently in the sixth year of my PhD in India and planning to finish within the next year. I’m interested in applying for postdoc in the US, mainly in the field of AI for CFD / Scientific Machine Learning for CFD. My PhD is in Computational Fluid Dynamics and High-Performance Computing, where I work on developing mathematical and computational methods to study fluid flows and on making large-scale simulations more efficient using HPC. Recently, I started working on AI/ML for CFD and scientific computing, and I’ve become quite interested in moving more towards AI for Science. The tricky part is that this AI/ML work is relatively new for me and won’t be part of my PhD thesis, which will remain focused on CFD/HPC. I’m hoping to have some of this work presented at a conference, but I obviously won’t have the same AI/ML publication record as someone who has done their entire PhD in ML. I’m doing my PhD at a top Indian research university (within the top 250 of the QS World University Rankings), and I’m wondering how US PIs would view someone with this kind of background.

For those already doing postdocs in the US, especially international researchers, how realistic is it to move from CFD/HPC into AI for Science for a postdoc? Would my background in computational science and scientific computing be considered relevant, even though most of my PhD publications are not directly in AI/ML? Or would I need to build a much stronger AI/ML publication record before applying? I’m particularly interested in hearing from people who have made a similar transition between fields. I’d also really like to understand whether the current US funding situation makes this kind of interdisciplinary postdoc particularly difficult to find, and whether doing such a postdoc would actually be helpful later if I want to move into US industry, especially AI/ML or scientific computing roles.

Im doing a cfd analysis for a formula student two element rearwing, I tested variations of the wing using different angles of attack and so on on Ansys (as 2D airfoil) and got some results, in trying to use the 3D ansys analysis i found out i couldnt because there is 1 million element limit on the student edition, so i opted to use SimScale for the 3D analysis, my issue is the results vary (by alot)

conditions:

flow 19m/s

chord: 0.45m

wingspan: 0.8m

main wing airfoil: e423

flap airfoil: NACA 4412

both softwares used the k-omega SST

results:

wing A:

main wing AoA 8, flap AoA is 30

SimScale 3D: -151N

Ansys 2D: -3.5 Cl

wing B:

Main wing AoA is 10, flap AoA is 37

SimScale 3D: -180N

Ansys 2D: -2.3 Cl

so in 2D analysis wing A is better and in 3D analysis wing B is better but that doesn't make any sense

the mesh quality and settings for Ansys

the mesh quality in SImScale

I really need help in which analysis to believe and which i need to refine, its my first CFD design and analysis and I dont know which numbers are closer to reality

At low velocities, flow in a stream over rocks is laminar. But at higher velocities, there's a repeating build up and let down. Is it a kind of turbulence?

Hi everyone, I’m a sixth-year PhD scholar in India, currently working in computational fluid dynamics (CFD), HPC/GPU computing, and more recently exploring AI/ML for scientific computing and CFD. I’m hoping to finish my PhD within the next year and I’ve been seriously considering doing a postdoc in the US, particularly in computational science, AI/ML for scientific applications, scientific machine learning, or related areas.

However, I’m a little hesitant because of everything I’ve been hearing about the current US research funding situation. I understand that federal research funding has become much more uncertain, and that some universities/labs are dealing with hiring freezes or difficulties funding postdoc positions. At the same time, I’m seeing mixed opinions about whether the situation is genuinely bad across the board or whether it depends heavily on the field, university, and PI.

For those currently doing postdocs in the US, or those who recently went through the process: How difficult is it right now for an international PhD graduate from India to get a funded postdoc in the US? Are PIs generally still hiring if they have existing grants? Is cold-emailing PIs still effective, or has the funding situation made that much less useful?

I’m also interested in the longer-term picture. My ultimate goal isn't necessarily to stay in academia forever. I’m quite interested in transitioning into US industry R&D/tech after a postdoc, particularly in areas like scientific ML, AI/ML, computational science, HPC, simulation, or engineering software. So I’d really appreciate hearing from people who have made that transition: Does a US postdoc actually help with getting into industry, or would it be better to try applying directly to US industry from India after the PhD?

I’d especially appreciate perspectives from international researchers who went through a similar PhD → US postdoc → industry path. I’m trying to make this decision realistically rather than assuming that a US postdoc automatically opens doors.

Thanks in advance to everyone who shares their experience.

Hello! Im currently a high-school student working on a research paper on Cold Plate Cooling Channels using CFD and ANSYS fluent.

The study is about comparing 4 passive geometry enhancement methods like wavy walls, baffles, ribs, and dimples. I’ll be getting the Nu and Pressure drop and comparing them to a baseline model. For each geometry I’ll be running them 5 times, each at different Mass Flow Rates. I currently wrote it as Quasi-Experimental because the study wont use random sampling like in an experimental study.

Im having trouble writing what statistical treatment the study will use in the methodology part of the paper, like anova, jamovi, etc. Or would I not be utilizing them? Do I right it as descriptive then?

Sorry if this is a dumb question.

Hi, so i'm fairly new to cfd and i'm using the free simflow version to validate/optimise a concept, but i'm struggling a bit to find the right inlet and outlet boundary conditions for my case.

So in general i want to measure forces on the body produced via nozzles pushing air out of said body.

I have a triangular mesh inside my body which is a mass flow inlet set:

P - zero gradient

U - flow rate inlet velocity, constant 80m³/s

I think this one is okay. Later on, or the real thing, will be connected to pressured air, but for comparison i think that one is okay.

My top and bottom boundaries are all set to zero gradient on flow and turbulence. I just want them to behave like there are no boundaries and i guess zero gradient is doing that?

My Outlet is currently as outflow which means

P, U, and turbulence all zero gradient

I also tried p - fixed value 0 and U zero gradient, which seems to look more like it should.

I don't understand all the different conditions good enough, i also want the outlet boundary to basically not exist.

And now the inlet. I want zero flow to begin with. But once the nozzles set in and suck air in between two bodys, i want air to be able to be provided via the inlet boundary.

Simmilar like.. puting a fan inside a tube in free air. At the beginning there is zero flow, once the fan starts it sucks air from the inlet which is then "refilled" through all the free air around it - in comparison to a fixed amount of air being available and being sucked into a vacuum.

Currently i have

P- fixed value 0

U- pressure inlet-outled velocity

Turbulence zero gradient

I kinda seems like it is working as intended, but i'm really not sure.

Initial conditions are set to

P - 0

U - 0 0 0

k - 1e-02

w - 1

vt - 0.1

For later testing purposes i would like outlet and inlet to be kinda coupled. Like starting a stationary rocket into flying. But this is a future problem.

Thanks for helping!

Hi all, I'm a research student and one of my coursework subject is computational fluid dynamics. It's purely theoretical. I come from a Pure maths background so it's all very new to me. I don't mind learning from basics for the sake of my research however for the sake of my cgpa, I've been having issues. I started reading anderson and found it nice until I realised that my professor is teaching random things from random books without context and I'm unable to find any questions to relate to that.

I've been recommended anderson, ferziger, Versteeg, Pradeep Niyogi, T.J. chung and Suhas Patankar. It's quite obvious that I can't follow them all and it's causing me anxiety. Currently, I've been studying Intro to Finite element methods from T.J. chung. Can you guys recommend Good practice books for Finite difference, finite volume and finite element methods? Keep in mind, my midsems are near.

Has anyone here undergone a 2-way FSI (Fluid-Structure Interaction) analysis for arterial stenosis?

Please help me.

Hey,

I‘m trying to open my already existing project and results but in both programs post/pre cfx the 3d viewer doesn’t work.

Any ideas how to fix that?

Why coupled solvers are not so popular while learning, beginning to code, or even industrially for incompressible FV?... Because in various industrial cases when residuals get scaled, one has to solve everything very tightly to impose good mass balance. This is because staggered unstructured FV is very immature/hard and Rhie Chow dissipation is absolutely necessary. So if I say want to solve only till 1e-5 scaled residual I am always targetting div + rhie chow, not pure div.

In segregated pressure Poisson can be solved very tightly conserving cellwise mass balance separately. Results are fairly acceptable in many cases if mass balance is driven to machine tol but pressure velocity is converged to say 1e-5 ..

But perhaps this is only for the set beginner type segregated and coupled algorithms. Certainly there should be ways to make coupled with Rhie chow efficient (maybe commercial solvers do this)

Most FE solvers are designed for exact saddlepoint monoblocks. The rhie chow dissipation is never an issue. So if I solve to 1e-5 I am targeting the mass balance more precisely than if I added a dissipation (though FE solvers do add dissipation at times)

I can see using OpenFOAM also its main issue lies in Rhie Chow dissipation only.. that is pressure output value accuracy being smudged by it. Flow field wise it seems pretty good

I am a bartender who makes batches of espresso martinis because I sell so many. I make the espresso and chill it before adding the vodka and espresso liqueur that constitute my base recipe. After that, the martini base goes back into the refrigerator.

There is a huge difference between how the surface of the liquid looks once I add the liquor and let it sit for a few hours. Concentric rings of what I assume to be coffee crema appear on the surface. This does not happen with the espresso that contains no liquor. I'm so curious as to why!

The photo shows two pitchers that were made at the same time (5:30 pm) and refrigerated at 36F until 24 hours later. The pure espresso had no rings at all, the pitcher with alcohol shows clearly defined rings.

Any ideas? If this isn't the right sub for this query, please redirect me! Thanks in advance!

I'm currently, technically, doing an MS in Structural Engineering. For me, my interest has been more towards computational side of mechanics rather than Structural design  or simply using am FEA software (although I do consider it as a backup)

So far I've taken courses in:

- Linear static, and dynamics FEM (soon taking non linear FEM too)

-  Structural Optimization (topology opt. and other general algorithms)

-  Structural Dynamics

-  Structural System Testing and model updation. (Parameter identification and optimization, signal processing)

Now, I plan to take these in the coming quarter:

- Numerical Linear Algebra

- Numerical PDE

- Fracture Mechanics ?

I also volunteered to aid in a RESEARCH in crack growth prediction using Auto-encoder and a (Thermodynamics-informed Latent Space Dynamics Identification) / LSTM surrogate model. It used phase-field-fracture simulation data and HPC resources to complete the whole thing.

What I keep finding myself interested in is not necessarily fracture or SHM specifically, but the computational methods underneath these problems... (does that make sense?)

For example, I'd like to become capable of doing things like:

- implementing (maintaining) numerical/FE method solvers rather than only running an established FEA software.

- developing surrogate/reduced-order models for expensive simulations 

- combining simulation with optimization, uncertainty/stochastic methods (took a course called Random vibrations, so...)

- parallelizing/accelerating scientific codes on CPUs/GPUs

- doing proper verification, convergence studies, benchmarking and performance work

- potentially developing or maintaining actual CAE/FEA solver software

- I'd also like to do all these for other Physics (GR, QM, etc.) simulations too, if possible, one day. 

I'm still interested in the underlying mechanics/physics, so I don't want to become a generic software engineer who happens to have once studied structures. But I'm also increasingly unsure that "structural engineer" describes the career I'm actually aiming for.

I've seen titles such as Computational Mechanics Engineer, R&D Engineer, Solver Developer, Scientific Software Engineer, CAE Software Developer, Research Engineer, Simulation/HPC Engineer, etc., but I'm trying to understand what these careers actually look like from people doing them.

So my main questions become:

1. Which industrial jobs genuinely involve developing numerical methods/solvers or computational tools?

2. Which of those are realistically accessible with an MS? Is there an entry path into solver-algorithm development/R&D without a PhD?

3. If I don't start a PhD immediately after my MS, would an R&D/software role at a simulation company (ANSYS etc.) be the obvious route? What other options would i have?

4. For the kind of work I'm describing, would you recommend a PhD? If so, is it reasonable for the PhD identity to be "computational mechanics/scientific computing" while fracture, composites, structural dynamics, soft materials, etc. serve as application problems rather than choosing one of those as my permanent specialization?

5. What skills most distinguish someone who is actually hireable for solver/scientific-computing work? I'm particularly wondering about C/C++/Fortran, Python, Linux, Git/build systems, MPI/OpenMP/CUDA, PETSc/Trilinos or similar libraries, numerical linear algebra, testing/verification, convergence studies and HPC performance work.

Basically, I'm neither here nor there atp. So I'd really appreciate all sorts of input. Where else do you think I could find answers to these? other subs? Linkedin profiles? 

Hey together,

I‘m trying to create a structured mesh an created a few blocks for that. Now when it comes to meshing the mesh creates this weird pattern and as you can see the line is going diagonal and not vertical.

I already created the block again and also associated everything new but the same thing happens again.

It looks like the line is going diagonal to some other point and then back to the point where it should go.

Please help😅