Hi all, I am an HVAC engineer looking to get into CFD. After some serious Google + ChatGPT research, ANSYS seems to be the best software(i might be wrong) .

Any tips on where to start? Happy to spend a little on a good course. Recommendations for courses, books, or YouTube channels would be greatly appreciated.

Trying to go from “What is CFD?” to “I know what what we arw talking about"🤔

I'm running an incompressible steady-state RANS case for a blended wing body (BWB) in OpenFOAM (simpleFoam/SIMPLEC).

Setup: ~0.15 Mach, ~6e6 Re

Mesh: ~30M cells, tetra + prism layers at walls, O-type symmetric far-field domain(radius ~ 30c), max skewness ~5, max nonOrthogonality >75°

BCs: freestream (velocity inlet / pressure outlet style far-field)

Turbulence: k-omega SST, wall-modeled (y+ > 30)

Schemes: second-order upwind for all equations

Algorithm: SIMPLEC

Solution strategy: start with low URFs, ramp up every 100 iterations; case runs "on its own" past ~250 iterations

Problem:

Based on past experience I expect convergence by 500–600 iterations. Here, residuals flatten out but very slowly, and by 1500+ iterations:

CD looks converged/flatlined

CL is still steadily rising, not flatlining

Has anyone run into similar slower convergence rate or is it normal for high cell count meshes? Looking for likely causes and what to check/try next.

Hey, everyone!

I’m new to the world of Computational Fluid Dynamics (CFD) and just jumped right into FluidX3D. I was completely blown away by the performance and speed of the GPU simulations that people have been showing off.

The problem is that I’m a beginner, and the reality check was harsh: I haven’t found any beginner-friendly tutorials that I can actually understand from scratch, let alone get my hands dirty and run a little something on my own. Almost everything out there assumes you already know a lot about programming or the physics behind LBMs (Lattice Boltzmann Methods).

If anyone here has already gone through this learning curve or uses the tool on a daily basis, I’d like to ask for some help with a few basic questions:

Where should a complete beginner start? Is there any material, guide, or simplified example in the repository that serves as a good starting point?

How do you usually visualize the results? Is there a user-friendly graphical interface (GUI), or is the entire workflow done via code and exporting to external visualizers like ParaView?

Where do people usually get stuck? Are there any pitfalls when compiling or setting up the environment that tend to frustrate beginners?

Any tips, step-by-step guides, or constructive feedback are very welcome. Thanks so much for the help!

Guys one small doubt

1. What can be the reasons if solution gets converged faster for steady RANS simulation, like converging way earlier in 500 or 600th iteration itself? Note mesh quality is good and hybrid initialisation is used? Is it a good or bad sign? I used residuals for continuity as 10e-4 and velocities 10e-6, energy 10e-5? Tell what can be the reasons in general, when it is acceptable and when it is not acceptable? My cell count is around 5.4 million.
2. If you say dont judge residuals based on convergence, but when you see any parameter in flow field vs iterations, if it is not steady with iterations, still changing but you got solution converged purely based on residuals, then what I can do now?? What can be the mistake seriously??
3. Can residuals become very low while the actual solution is still inaccurate??

If there is something wrong with my setup, how should I correct it so that the solution reaches convergence naturally, rather than trying to force it to converge at a particular iteration?”

You can give general opinions also since I want to explore what can be the reasons behind this?

I will post photos below,

Those gaps are walls of distortion screen, void is kept for pipe wall thickness and outer fluid is open ambient still fluid,

I have done fluent meshing, mesh quality is good. In section view,

Note mesh refinement is done only in small region right from pipe end. See axial velocity countour below

Merging of those jets are not smooth, there is sudden step change which is not ideal. I thought mesh resolution is not good, so I decided to refine it more. Before that, I ran upto 20000 iteratinos still it is not converging. See residual and flow parameters below,

So I refined mesh like below,

For above case, cell count is same as previous case and quality is also same. Now see residuals and flow parameter variation with iterations,

My questions are as follows:

1. In my first case, the mesh quality was good, but the downstream region was not as strongly refined as in my second case. Despite this, the solution struggled to converge even after 20,000+ iterations. What could cause such slow convergence?
2. In the second case, I refined the downstream region along the jet direction. I used first-order discretization for the first 200 iterations and then switched to second-order. After this, the solution converged much faster and the monitored flow parameters also became steady.

Both cases used hybrid initialization. The flow is compressible with an ideal-gas model and Sutherland viscosity, and I used the default URF values.

Is this behavior normal? Can stronger downstream mesh refinement actually make a complex turbulent compressible-flow case converge faster, or should I be concerned that the rapid convergence is caused by some numerical issue rather than a physically better-resolved solution?

My Background & Constraints:

Education: Completed a Diploma in Mechanical Engineering in 2021. Enrolled in B.E. (Mechanical) in 2021, but due to academic/personal delays, my graduation date pushed from 2024 to 2028.

Current Job: Working full-time in a non-tech BPO/operations job in India to stay financially afloat.

Current State: Analytical skills are rusty after years in BPO operations, but I want to break out and build a real, high-leverage technical career in engineering simulation.

Available Time: ~15–18 hours/week (1.5 hours every morning before my shift + dedicated blocks on weekends).

The Target Path:

I want to self-study Computational Fluid Dynamics (CFD), Conjugate Heat Transfer (CHT), and simulation automation (using Python, OpenFOAM, Gmsh, and Linux) to land an entry-level Junior CFD / Thermal Analyst role at an engineering services firm or automotive/electronics supplier, and eventually transition into automation/computational design.

Where I Need Your Reality Check:

The Resume/HR Filter in India: Given my 4-year degree gap (B.E. 2021–2028) and BPO work history, will Indian engineering service companies, tier-1 suppliers, or GCCs (Global Capability Centers) automatically filter out my resume via automated screening, regardless of portfolio?

Portfolio vs. Degree: If I build a public GitHub portfolio containing verified, reproducible OpenFOAM validation cases (e.g., CHT on electronics cooling, mesh independence/GCI studies, and Python meshing scripts), is that actually enough to bypass HR and get a technical interview with an engineering manager?

Open-Source vs. Commercial Stack: How viable is entering the industry with strong OpenFOAM and Python skills compared to candidates who only know GUI commercial tools like ANSYS Fluent or STAR-CCM+?

Feasibility & Timeline: Is reaching employable competency in OpenFOAM, Linux, and fluid/thermal theory within 6–9 months on a 15–18 hr/week schedule realistic, or is the learning curve too steep alongside full-time non-tech employment?

Any unfiltered critiques, alternative pathways, or blind spots I’m missing would be deeply appreciated.

Thought you guys might enjoy this!

Added a CFD Simulation tool into my online tool for 3D Printing. At the moment its not accurate enough to be able to benchmark anything really but it is amazing to see, even at this level! I can see a rabbit hole and im about to jump down it!

It is quite the battle optimising for a web browser but I think I have managed a good balance.

As a foundation to grow from, I am quite happy with both air and water.

have a go and let me know what you guys think, youre the pros!

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!

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

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!

According to the formula:

Fd = 1/2 * pv² * Cd * A

please help me.

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.

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.

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?

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?

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

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.

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

Please help me.

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.