Turbulence is Everywhere! Examples of Turbulence and Canonical Flows 

You can always apply to Washington University :)

Wow, thank you!

Thanks, I really love that pipe flow video -- super cool!

My pleasure!

Thanks so much!!

I appreciate it -- it was fun to make too! :)

Thanks! I'll put it on the list. I'm not a heat transfer expert, but there are definitely some really interesting connections there.

Thanks Matt!

I am an undergraduate student trying to enter the field of CFD and turbulence modeling, I because of this entry hurdle unable to get grip on OpenFOAM but loved you instructions

@@MuhammadUsman-ny5rh Thanks. I hope they were helpful and you were able to solve your problem.

Yikes, very scary. Glad you made it out safely. Wake vortices are no joke.

Pilot probably had a long word with ATC after that one.

Interesting observation -- I like that.

Thanks for fixing the link! Yes, must have been autocorrect. I really love their videos!

Thanks! I am not an expert in these material science topics, but I believe people are using computational modeling extensively for these fields too. I've seen some work on crack propagation, which is really challenging because it is multiscale, from the molecular level up to the macroscale. Characterizing advanced materials computationally is one of the biggest modern challenges, since the performance of the material will depend on the composition of the material at all scales (from very small to very large). We don't even know the performance envelope for these materials; biological materials, like a sea-shell, are often heterogeneous and non-isotropic at many different scales, which makes them incredibly challenging to simulate (a lot like turbulence!)... I'm really fascinated by this topic.

@@Eigensteve Thanks for the response! I'm interested in if surface chemistry and transport phenomena have an effect on crack propagation in devices under mechanical load in some chemical solution. Examples of this could be a beam under stress in a river or a neural probe within an organism. What's interesting here is that mathematics more or less exists to explain transport phenomena, thermodynamics, and material failure - but attempting to model all of these on a multiscale level would be a computational nightmare. I think that such devices could have sensors on or in them that could let us know what their 'state' is. That in combination with the algorithms being pioneered by yourself and Prof Kutz could then give us the most important equations at play with regard to what stresses these devices are under. I could type more, but I should probably be doing homework! I look forward to learning from you directly once I conclude my undergraduate degree.

@@LucasDimoveo Wow, that sounds like a very interesting (and tough) problem! I agree, some combination of first principles and data-driven modeling would be interesting here. Keep in touch, as I'd love to hear how things go after you graduate!

Thank you!

Thank you!

Awesome, welcome to the channel!

Thanks for the suggestion -- I will likely cover some of this, but it might take a while to get there. Numerical methods for DNS is not my core area, but definitely very interesting.

@@Eigensteve in that case, guest lecture from Nathan Kutz? ;) Actually I see that he's got some lectures on DNS from back in the Before Times. But it'd be nice to see similar material from a different point of view. Whatever the case I really look forward to seeing what you have to say about ML in fluid dynamics. This definitely seems to be a hot new area!

Thanks!

Definitely -- There is a lot of work in putting multiscale physics simulations on GPUs since they are getting so powerful. There are issues, like shared memory, communications, and how much of the core computation can be written as a matrix operation.

Your idea is not wrong, in fact I would suggest you to give a look at the works of Theo Geisel and peoples that worked with him at the MPIDS. I do believe you can find some interesting information about your idea.

@@GabrieleNunnari Thank you. Definitely an interesting institute. I'll get reading

Not at all. That is a very good connection. For a long time there have been connections between turbulence research and neuroscience, as they both involve high-dimensional, nonlinear, multiscale systems, where we only have partial measurements. Thanks for the comment!

@@GabrieleNunnari Thanks for this info!

@@Eigensteve 'Rethinking Innateness - A connectionist perspective on development' a great book exploring the non-linearity of the brain. I'm still reading it. Some of the computational concepts and maths are a little tough for me but I'm sure you guys would have no problem there.

Thanks! There are increasingly some great open source codes out there. nek5000 and openfoam are both really popular. The IBPM code is great to get started with simulations, although it won't go up to turbulence (github.com/cwrowley/ibpm)

@@Eigensteve many thanks! I'll be sure to have a peek.

Sounds great!

Indeed, good eye!

I agree!

I'm going to have a video on this soon, with some examples. A few key groups/papers you can look into: review paper by Duraisamy, Iaccarino and Xiao (www.annualreviews.org/doi/abs/10.1146/annurev-fluid-010518-040547) has a lot of good refs in it; Ling et al JFM 2016; Maulik et al JFM 2019; more recently github.com/lululxvi/deepxde and arxiv.org/abs/2010.08895

I agree! First place I visited in Germany. Rich history of great scientists and engineers there.