# All Duckies Shall Pass! 🐣 ## Метаданные - **Канал:** Two Minute Papers - **YouTube:** https://www.youtube.com/watch?v=2wrOHdvAiNc - **Дата:** 22.01.2021 - **Длительность:** 5:51 - **Просмотры:** 242,682 ## Описание ❤️ Check out Lambda here and sign up for their GPU Cloud: https://lambdalabs.com/papers 📝 The paper "Interlinked SPH Pressure Solvers for Strong Fluid-Rigid Coupling" is available here: https://cg.informatik.uni-freiburg.de/publications/2019_TOG_strongCoupling_v1.pdf 📸 Our Instagram page is available here: https://www.instagram.com/twominutepapers/ 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Aleksandr Mashrabov, Alex Haro, Alex Serban, Alex Paden, Andrew Melnychuk, Angelos Evripiotis, Benji Rabhan, Bruno Mikuš, Bryan Learn, Christian Ahlin, Eric Haddad, Eric Lau, Eric Martel, Gordon Child, Haris Husic, Jace O'Brien, Javier Bustamante, Joshua Goller, Lorin Atzberger, Lukas Biewald, Matthew Allen Fisher, Michael Albrecht, Nikhil Velpanur, Owen Campbell-Moore, Owen Skarpness, Ramsey Elbasheer, Robin Graham, Steef, Taras Bobrovytsky, Thomas Krcmar, Torsten Reil, Tybie Fitzhugh. If you wish to support the series, click here: https://www.patreon.com/TwoMinutePapers Károly Zsolnai-Fehér's links: Instagram: https://www.instagram.com/twominutepapers/ Twitter: https://twitter.com/twominutepapers Web: https://cg.tuwien.ac.at/~zsolnai/ ## Содержание ### [0:00](https://www.youtube.com/watch?v=2wrOHdvAiNc) Segment 1 (00:00 - 05:00) Dear Fellow Scholars, this is Two Minute Papers with Dr. Károly Zsolnai-Fehér. In this paper, you will not only see an amazing technique for two-way coupled fluid-solid simulations, but you will also see some of the most creative demonstrations of this new method I’ve seen in a while. But first things first, what is this two way coupling thing? Two-way coupling in a fluid simulation means being able to process contact. You see, the armadillos can collide with the fluids, but the fluids are also allowed to move the armadillos. And this new work can compute this kind of contact. And by this I mean lots and lots of contact. But one of the important lessons of this paper is that we don’t necessarily need a scene this crazy to be dominated by two-way coupling. Have a look at this experiment with these adorable duckies, and below, the propellers are starting up, please don’t be one of those graphics papers. Okay... okay, good. We dodged this one. So the propellers are not here to dismember things, they are here to spin up to 160 rpm, and since they are two-way coupled, they pump water from one tank to the other, raising the water levels, allowing the duckies to pass. An excellent demonstration of a proper algorithm that can compute two-way coupling really well. And simulating this scene is much, much more challenging than we might think. Why is that? Note that the speed of the propellers is quite high, which is a huge challenge to previous methods. If we wish to complete the simulation in a reasonable amount of time, it simulates the interaction incorrectly and no ducks can pass. The new technique can simulate this correctly, and not only that, but it is also 4. 5 times faster than the previous method. Also, check out this elegant demonstration of two-way coupling. We start slowly unscrewing this bolt…and…nothing too crazy going on here. However, look! We have tiny cutouts in the bolt, allowing the water to start gushing out. The pipe was made transparent so we can track the water levels slowly decreasing, and finally, when the bolt falls out, we get some more two-way coupling action with the water. Once more, such a beautiful demonstration of a difficult to simulate phenomenon. Loving it. A traditional technique cannot simulate this properly, unless we add a lot of extra computation. At which point, it is still unstable… ouch! And with even more extra computation, we can finally do this, but hold on to your papers, because the new proposed technique can do it about 10 times faster. It also supports contact against rich geometry as well. Look, we have a great deal going on here. You are seeing up to 38 million fluid particles interacting with these walls given with lots of rich geometry, and there will be interaction with mud, and elastic trees as well. This can really do them all. And did you notice that throughout this video, we saw a lot of delta t-s. What are those? Delta t is something that we call time step size. The smaller this number is, the tinier the time steps with which we can advance the simulation when computing every interaction, and hence, the more steps there are to compute. In simpler words, generally, time step size is an important factor in the computation time, and the smaller this is, the slower, but more accurate the simulation will be. This is why we needed to reduce the time steps by more than 30 times to get a stable simulation here with the previous method. And this paper proposes a technique that can get away with time steps that are typically from 10 times to a 100 times larger than previous methods. And it is still stable. That is an incredible achievement. So what does that mean in a practical case? Well, hold on to your papers, because this means that it is up to 58 times faster than previous methods. 58 times! Whoa. With a previous method, I would need to run something for nearly two months, and the new method would be able to compute the same within a day. Witchcraft, I’m telling you. What a time to be alive! Also, as usual, I couldn’t resist creating a slow-motion version of some of these videos, so if this is something that you wish to see, make sure to visit our Instagram page in the video description ### [5:00](https://www.youtube.com/watch?v=2wrOHdvAiNc&t=300s) Segment 2 (05:00 - 05:00) for more. Thanks for watching and for your generous support, and I'll see you next time! --- *Источник: https://ekstraktznaniy.ru/video/13995*