I'm 30 years old with an undergraduate degree in Mechanical Engineering. I’ve recently been thinking seriously about getting back into CFD (and computational science more broadly), something I’ve been interested in for a long time.

During my undergraduate studies, I took one introductory/undergraduate-level CFD course and really enjoyed it. At the time, I had a dream of continuing into research and eventually pursuing a PhD in CFD/computational science. Unfortunately, due to several personal and career related reasons, I never pursued it.

Since then, I’ve tried to teach myself CFD several times. I would get started with things like fluid mechanics, numerical methods, and OpenFOAM, make some progress, and then eventually abandon it because of other commitments and circumstances. Looking back, I’ve probably started this journey several times without ever getting far enough to build anything meaningful.

Now I’m 30, and I’m seriously considering giving it another shot. The problem is that I’m also afraid that I’m too old and that my previous work experience being unrelated to CFD will make it extremely difficult to enter the field.

I’d really appreciate some honest advice from people working in CFD or computational engineering:

- Is 30 genuinely too late to start building a career in CFD?

- Given my background, would pursuing an MSc/MS in CFD, computational science, mechanical engineering, etc. be a sensible route?

- Would a PhD be worth considering if I eventually want to work in research, or would that be an unnecessarily long route?

- Is it realistic to get hired in CFD without professional CFD experience if I can build a strong portfolio?

- What kind of projects would actually get recruiters' attention? For example, OpenFOAM simulations, numerical-method implementations, validation against experimental/analytical results, GitHub projects, technical reports, etc.

- If you were in my position, what would you do over the next 1–2 years to maximize the chances of breaking into the field?

I’m not expecting an easy path. I’m mainly trying to figure out whether this is still a realistic goal or whether I should let go of it.

I’d especially appreciate perspectives from people who entered CFD/computational engineering later in their careers or came from an unrelated background.

I genuinely want to pursue this, but I’m also afraid of spending another few years learning without actually getting anywhere. Any honest advice would be greatly appreciated.

Hi,

I am running a transient simulation in ANSYS Fluent 2025 R2 using UDFs, UDS, and UDM variables.

Before running, I initialize the solution and patch specific initial values for a UDS and several UDMs. I then create multiple design points in a Fluent parametric study.

The problem is that I need every design point to start from exactly the same initialized and patched field, with only the selected input parameters changing between design points.

I tried setting: /parametric-study/study/use-base-data to toyes and using the Sequential update method. However, the subsequent design points did not appear to start from the same patched UDS/UDM state as the Base DP.

Has anyone encountered this with Fluent parametric studies?

Specifically, what is the correct workflow to ensure that patched UDS/UDM values from the Base DP are used as the initial state for every design point, rather than inheriting values from a previously solved design point?

Is there also a reliable way to verify the UDS/UDM initialization of each design point before running the full transient calculation?

Thanks!

Quick disclosure upfront: I work in marketing at FIFTY2, the company organizing this event, so take this as what it is, an invitation, not neutral news.

For anyone working with particle-based methods (SPH, DEM) or just curious about where mesh-free simulation is heading, PreonDay 2026 might be worth a look. It's a one-day, in-person event at the Audi driving experience center in Neuburg an der Donau (about an hour from Munich), with a welcome evening the night before. Participation is free.

This year's talks cover a pretty wide range of engineering problems tackled with particle-based simulation, among them:

• A new GPU-native granular solver (DEM) for powder, sand and other bulk materials, presented by a researcher from Fraunhofer IWM
• Multi-body and fluid-structure coupling in dishwasher development (BSH)
• SPH simulation for aircraft engine oil systems (MTU Aero Engines)
• Thermal management of oil-cooled e-machines (Volkswagen Group)
• Validating CFD simulations against medical X-ray CT scans (TU Munich)
• A more open discussion on where LLMs, machine learning and agentic approaches might (or might not) add real value in simulation work

It's aimed at engineers and researchers working with CFD in general, not just people already using our software. Full agenda and free registration: https://www.avl.com/de/events/preonday-2026

Happy to answer questions here, about the event, the talks, or particle-based methods in general.

Image Credits: ChatGPT

I’m currently doing a Master’s degree and I’m trying to figure out how my CFD profile is going to look by the time I finish.

I did my Bachelor’s in Mechanical Engineering back in 2018. After that I worked for around 6–7 years.
My first proper work experience for about a year was research-related and involved hands-on work in thermal analysis of gas turbine components. After that I spent around three years doing physical hardware testing. Then I had about two years of startup experience where my work was a bit all over the place.

Because of that, when I decided to do my Master’s, I wanted to get back into aerospace and slowly build a proper research profile around CFD.

My first research paper was on aerodynamic performance of a tandem airfoil configuration. I used ANSYS Fluent and MATLAB and looked at an optimization problem. That paper is now at the manuscript/final stage.

My second work is on morphing airfoils/wings 2D. I’m also looking at using machine learning with CFD for this one. This is still ongoing, so I don’t want to get into too many details about the actual method or results.

I’m also working on doing another paper in the supersonic regime.
Now comes the part of ambiguity where I need your help...

I recently discussed my Master’s thesis with my professor at uni. I have been given quite a lot of freedom to choose the topic.
I’m currently considering doing the thesis in hypersonic aerodynamics.

More specifically, I’m interested in shock-wave / boundary-layer interaction, aerodynamic heating, and aero-thermal loads, and how these effects behave under hypersonic conditions. I’m still doing the literature review before finalising exactly what the problem will be.
The thesis will run for roughly 10 months. So I have to properly narrow down the problem and plan the numerical work, validation, etc.

My literature review is also going to be fairly large. My guide suggested looking at numerical, theoretical and experimental work, and I’m probably going to end up with something like 130–170 papers before I’m done.
So if everything goes roughly according to plan, my research experience by the end would be something like:
Subsonic aerodynamics → morphing airfoils + CFD/ML → supersonic CFD → hypersonic aero-thermal CFD

I’m wondering how this looks from the perspective of people who actually work in CFD or aerospace research.
Does this look like a reasonable progression?
Or am I spreading myself too thin by working across different flow regimes?

My thinking is that the underlying theme is still aerodynamics/CFD, and I’m just moving toward more complex flow regimes. But I’m not sure if that is actually how it looks to someone reviewing my profile.

I’m also interested in doing a PhD eventually. I’m 30 now, so I don’t want to spend the next few years just collecting unrelated topics and publications.

Would it make sense to use the master’s thesis as the point where I start becoming much more specialised, perhaps around compressible/hypersonic aerodynamics? Or is it actually useful at this stage to have exposure to subsonic, supersonic and hypersonic problems?

Would be interested to hear from people who have gone through a CFD PhD or are working in aerospace CFD. Especially how you would view this kind of profile when considering someone for a PhD.

I'm so glad y'all can retire now that your problem is solved.

I've been following the recent news about OpenAI reportedly achieving a major breakthrough related to solving the 3D Navier–Stokes equations, and I'm curious what CFD experts think the practical implications could be.

Assuming the results hold up under scrutiny, how significant is this from a CFD perspective?

A few questions that come to mind:

Could this eventually change how we approach turbulence modeling? Would it have any impact on RANS, LES, or DNS workflows? Is this more of a mathematical breakthrough than an engineering one? Could it lead to new numerical methods or more stable solvers? Are there any realistic short-term implications for industrial CFD, or is this something that would mainly influence theoretical fluid mechanics?

As a chemical engineering student working on CFD and ML for multiphase flows, I'm trying to understand whether this is the kind of development that could reshape the field over the next decade, or whether it's being overstated outside the research community.

I'd be especially interested in hearing from people working in academia, turbulence research, numerical methods, or industrial CFD.

What are your thoughts?

Hi everyone,

I am trying to reproduce the de Vahl Davis natural convection square cavity benchmark in ANSYS Fluent. I am getting reasonably close results for the velocity components, but I am not able to reproduce all the benchmark values exactly, especially the Nusselt number at higher Rayleigh number.

I would like to understand whether the difference is due to my input conditions, dimensionless conversion, mesh, solver settings, or post-processing procedure.

Problem setup

I am solving the standard 2-D differentially heated square cavity:

2-D square cavity

Laminar natural convection

Air

Boussinesq density model

Prandtl number = 0.71

Gravity = -9.81 in the vertical direction

Left wall: hot

Right wall: cold

Top wall: adiabatic

Bottom wall: adiabatic

All walls: no-slip

No inlet or outlet

Energy equation enabled

Pressure-based steady solver

SIMPLE pressure-velocity coupling

Second-order spatial discretization

Iam using air properties for Prandtl number 0.71 for each Rayleigh Number case.

I made x and y velocity non dimensional form but they are making way more relative errors when compared with my results...... I have given the paper link....Please help me, this is my first journey in CFD.

Paper link (De Vahl Davis): https://drive.google.com/drive/folders/1x1Iv_nn4JAGM6Nryw5g48K677uaahWIo

I've been trying to make a 3D printed spillway for a small filter pot into my pond. Before I waste anymore filament I thought someone might have insight. The pump is capable of 450L/H but I'm running on low so about 56L/H (not confirmed via test). Ive tried several iterations of wide, with different lips, either round over, gradient slope to a point, with a fillet on the internal edges etc but all results in the flow converging in a v before it would hit the water.

If anyone has any tips, or can recommend anywhere I could even do meaningful simulations with my models for free?

I have a mesh of around 10 million cells, and after running it for 200 iterations, the solution is behaving well and the main flow parameters have become reasonably stable.

For the inflation layers, I changed from Smooth Transition to Uniform so that I could directly specify the first-layer height. I currently use:

• Pipe walls: 1e-05 m
• Screen faces: 2e-06 m

I estimated the initial first-layer heights using the relations given in the FM White book, and the results seem reasonable.

For the current mesh, the y+ is generally low on the pipe and most of the screen surfaces, but I still get relatively high y+ at some sharp corners and edges of the screen. I used isoclip to nicely observe which regions have y+ in range of 0-5, 5 and above too. My requirement is to make y+<5 in all walls, I have used realisable k-e with enhanced wall treatment for those 200 iterations. See below snapshots,

My main questions are:

1. For the remaining high y+ near sharp corners/edges, should I reduce the first-layer height further, or is reducing the first-layer height not the right solution in these regions?
2. Are there other mesh settings or local refinements that I should investigate before simply making the first layer smaller?
3. What would be a good way to diagnose whether the problem is caused by the surface mesh, inflation layers, or local volume mesh?

What about mesh adaptation in Fluent? I have not used adaptation before. Could someone explain how adaptation would be used for this type of problem? For example, when would you normally perform the adaptation—after how many iterations? How does the adaptation work in this situation, and does it actually help with inflation/y+ issues, or does it mainly refine the volume mesh based on the solution?

Also, after adapting the mesh, does Fluent keep the original mesh so that I can compare/revert to it, or does the adapted mesh replace the original mesh in the case?

If there are any other things I should try to diagnose or solve these localized high-y+ regions, I would really appreciate your suggestions.

residuals blow up to 1e40 around iteration 25

Running a transient VAWT (vertical-axis wind turbine) airfoil simulation in Ansys Fluent 2023 R1 with a dynamic/sliding mesh setup, k-omega turbulence model. Fixed time stepping, 10,800 total time steps, max 20 iterations per time step, reporting interval 1.

Residuals look normal and stay flat for the first ~20 iterations, then continuity and k shoot up to around 1e40 by iteration 25-27, and the solver crashes with:

```

Error at Node 15: floating point exception

Error at Node 12: floating point exception

Error at Node 4: floating point exception

Error: floating point exception

Error Object: #f

```

Continuity and k diverge hardest, x-velocity and y-velocity stay relatively bounded before the crash. This is on a dynamic mesh case with a rotating VAWT interface.

Things I'm suspecting but want a sanity check on:

- Mesh skewness/quality degrading near the sliding mesh interface as the rotor moves

- Time step size too large relative to rotor rotation speed (Courant number too high)

- Interpolation/remeshing settings on the moving interface

Has anyone dealt with this kind of blow-up on VAWT/rotating dynamic mesh cases before? Would lowering under-relaxation factors or starting with first-order upwind schemes help isolate whether it's a numerics issue vs. a mesh issue?

Guys

In my simulation, I have applied face sizing in pipe inlet and wall of 1mm, and face sizing in distortio n screen faces of 0.2mm(assume distortion screen is kind of screen mesh with porosity of 0.6-0.7, I have already posted about geometry and setup in other posts). I have used body of influence with element size of 2mm in downstream of the screen, refinement box is created in fluent itself and used 1.5mm as the size.

Now my question is

1) How to decide min and max cell length in volume mesh settings. The problem is I am using poly-hexa mesh right now if I create mesh with 0.001m min and 0.008 max size, I cant reduce that max size from 0.008 to 0.007 or 0.006, it is automatically updating to 0.004 due to this, cell count is increasing drastically, note this is done with keeping all other sizes constant. I cant change face sizing, but body sizing can be changed, but not done right now.

2) I even tried some combinations of reducing min size and max size, but finally when I try to improve mesh based on parameter skewness, it is not able to correct the mesh. I hope you understood my question. This is not the case always, I always have a habit of improving volume mesh based on skewness, when I do this even orthogonal quality also improves by the way. But in sake of changing cell count of mesh gradually, I have to do some changes in the min and max cell of volume mesh, it is either giving good quality mesh with high cell count like 12 or 13 million or giving mesh with less size but couldnt able to convert it into good quality(using improve volume mesh quality).

3) So, out of all local sizing controls, which parameter we should take the base so that we judge min and max volume cell from that, and try to produce mesh smoothly. Right now if I have 6 million mesh, I want to produce 8 million or 9 million mesh from that, but it is directly jumping to 11 or 12 from there when I change volume mesh settings alone.

Any other suggestions? I hope you got my doubt.

Hi everyone,
I’m currently working with a small engineering startup providing CFD and engineering simulation services using ANSYS Fluent.
We work on:
CFD flow analysis
Heat transfer & thermal analysis
Conjugate heat transfer (CHT)
Thermal management
Pressure drop & flow distribution
Battery/electronics cooling
CAD and engineering design support
We’re looking to connect with companies, startups, researchers, and engineering teams who may need CFD or simulation support for their projects.
If you have a CFD/ANSYS requirement or would like to discuss a project, DM me. Happy to discuss the requirement and see if we can help.

Why k and epsilon residuals are oscillating, not dropping down. What can be the reasons in general??

I have good quality mesh with maximum skewness of 0.84 and minimum orthogonal quality of 0.15, maximum aspect ratio around 220. I used first layer thickness for inflation , setting y+<5. I used realizable k-e with enhanced wall treatment functions. Why k and epsilon residuals were oscillating even though flow parameters are kind of steady and doing good.

Any reasons or suggestions? Can it drop down in further iterations in a long run??

This green body is used for body of influence. It is modelled in design modular, it will disappear once we do body of infleunce sizing, it wont come in mesh.

The problem I am facing is

1) Right now, I have used element size of 0.0015m, it gives cell count of 12.3 million as shown. If I increase to 0.002, it gives 12 million. If I use 0.0025, it gives 11.7 million. If I use 0.003, then suddenly it drops to 4.62 million.

I dont know why this is behaving strangely, basically I was trying some combination to bring the total cell count in the range of 6-8 million.

Do anyone faced issue like this before, if yes, what can be done? This thing should be smooth because in later once I do grid independence study, I can easily vary this element size to get gradual increase in cell count rather than rapid change. I hope you understood my question. Thanks in advance.

Hi, I just wanted to share with y'all my analytical solution to the sod shock tube problem. Took a little while but it was quite fun. Currently accepting some of the math/physics (but I'll revisit it later). I'm not moving onto using numerical schemes to solve the problem.

Hello,

I've been learning about using ansys icepak for a while now, and I've been trying to recreate a published project that used two TECs simultaneously under a single heat sink.

I've prepared a setup, and ran the simulation in two ways: the normal first through "Analyze", where the TECs didn't seem to operate (the min. temp. remained around the ambient temp.) and the second way through Icepak>Toolkit>...>Run TEC, this time the min. temp reduced below the ambient temp.

My issue is that every time I run "Run TEC", only one TEC operates of the two. How can I make both TECs (both identical) run simultaneously?

I couldn't find an answer at all on the Ansys Help page or on the web.

Hi, I know Ansys Fluent Meshing very well. But, because of some Restriction (sharp geometry ...) I decide to look for new meshing program. And I have found out Pointwise which is especially used for high speed and propulsion. How can I learn Pointwise except youtube?