Jakson Simulation in Formula One: The Future of Racing Technology w/ Gerson Garsed-Brand täydellinen litterointi

coming up is the 24 hour, in the beginning of June. 00:04:59.125 --> 00:05:01.125 So, yeah, getting busy for that. 00:05:01.125 --> 00:05:04.125 So, yeah, I think that's a, a good summary of who I am. 00:05:04.125 --> 00:05:06.708 What do I do? And what say does I. 00:05:06.708 --> 00:05:07.540 Perfect summary. 00:05:07.540 --> 00:05:12.125 So let's maybe start out from the top generally speaking simulation. 00:05:12.125 --> 00:05:12.540 Right. 00:05:12.540 --> 00:05:16.875 Again you mentioned you guys are you guys are in business AVL is in business. 00:05:16.875 --> 00:05:19.875 as well when it comes to simulation tools. 00:05:19.915 --> 00:05:21.040 But tell me a little bit. 00:05:21.040 --> 00:05:28.083 Whereas where has formula one maybe we stick with Formula One for a moment, the big ones. 00:05:28.458 --> 00:05:35.165 And but also when has Formula One's really started to adopt and use simulation? 00:05:35.165 --> 00:05:38.415 Because again, you mentioned, you know, Ayrton Senna, right? 00:05:38.415 --> 00:05:45.958 I mean, I remember watching him, and several other guys back in the days when I remember my dad watching Formula One races. 00:05:47.458 --> 00:05:50.750 if I look back, I would never think that they used simulation, right. 00:05:50.750 --> 00:05:54.125 As was sort of trial and error, in my opinion at least. 00:05:54.125 --> 00:05:56.290 But again, I'm not I'm not an expert. There. 00:05:56.290 --> 00:06:12.290 But when it relates to simulation, again, as we reimagine mobility for simulation, certainly anywhere in the mobility space for electrification to autonomous to big data, all of that stuff, digital twins and simulation tools play a bigger and bigger role. 00:06:12.708 --> 00:06:17.958 So tell us a little bit when has formula one auto racing in general? 00:06:17.958 --> 00:06:37.040 But again, certainly the big guys formula one started using that and then as a next step, then I want to go to and where is it going and how much more progress can there be made or are we already at using the cutting edge of what simulation technology today allows in formula one? 00:06:37.040 --> 00:06:39.500 And really in passenger vehicles? 00:06:39.500 --> 00:06:43.540 We're the ones that then benefit from what formula one is inventing or doing. 00:06:44.000 --> 00:06:48.833 And it's not the passenger vehicle guys showing the formula one guys and how to use simulation. 00:06:48.833 --> 00:06:51.000 So a lot of questions in here. 00:06:51.000 --> 00:06:56.750 But never want to share that at So it would be I'm interested in I'm sure our listeners as well. 00:06:56.750 --> 00:06:57.125 Yeah. 00:06:57.125 --> 00:07:02.625 And I should say I'm not I'm not I don't still qualify to comment on other areas of simulation than mine. 00:07:02.625 --> 00:07:04.915 But I do hear the rumors. 00:07:04.915 --> 00:07:18.750 And also, I think when things started in the 80s, 90s, I was, I was a child, so I don't quite know, you know, the, the background, but for

sure, simulation has been around for a very long time, I think, 80s, 90s, you know, some, you know, fluid dynamics and stress. 00:07:18.750 --> 00:07:22.125 It was all there, and growing. 00:07:22.125 --> 00:07:25.583 And then from fomula one was the one of the first, to introduce composites. 00:07:25.583 --> 00:07:26.915 So carbon fiber, I think. 00:07:26.915 --> 00:07:33.665 And then that pushed the, you know, nonlinear stress simulation and so on, on, on the air versus competition fluid dynamics. 00:07:34.125 --> 00:07:36.208 We'd be very much dependent on computational power. 00:07:36.208 --> 00:07:44.958 So, although that was, a already a push in the late 90s to, to start using us very, very limited in this area. 00:07:44.958 --> 00:07:47.875 When I started my career in from aligning the late. 00:07:47.875 --> 00:07:50.875 So it was 2008. I was nine when I started. 00:07:51.165 --> 00:07:56.000 I still I still think the computational power available then was not good enough for what we needed. 00:07:56.000 --> 00:08:07.000 So, CFD, which stands for competition through dynamics, was very much a, a complementary to, kind of supporting tool for wind. 00:08:07.165 --> 00:08:20.375 the development release, but that's, and that's been seen as kind of the traditional approach of forward development has been you do things, you CFD first and then what's good you move to the tunnel and then it continues to move says is good. 00:08:20.375 --> 00:08:22.583 We come and say is good and that goes to the racecar. 00:08:22.583 --> 00:08:25.790 So I totally like a linear, serial process. 00:08:27.000 --> 00:08:44.000 but over the last decade, I would say there has been quite a transformation in that sense where, we now have much, much better, CFD that simulations, but partially because of the availability of resources, but partly because of new models, better models and so on. 00:08:44.000 --> 00:08:52.125 And, CFD safety analytics, in my view, is, is a, side by side with the wind tunnel in the aero development. 00:08:52.125 --> 00:08:55.375 So we do wind tunnel CFD has limitations for sure. 00:08:55.916 --> 00:08:57.332 So does the wind tunnel. 00:08:57.332 --> 00:09:02.500 Both are tools and they are now used in combination, to make decisions about performance. 00:09:02.500 --> 00:09:03.791 So that's really interesting. 00:09:05.666 --> 00:09:14.250 I think from Milan is a bit of a weird environment in that we, we are regulated, in terms of, we are restricted in terms of our development. 00:09:14.250 --> 00:09:26.750 So when you think about wind tunnel, there is a limitation with how many runs we can do it and how much time we can spend and time when we think about CFD, there is a there is a limitation in terms of how many geometries we can test and computational power. 00:09:26.750 --> 00:09:30.416 So there's a, there's a metric for how much solar time you are. 00:09:30.457 --> 00:09:44.500 You have to heat. So, because for that reason there is a bit of from a one end up converging to a slightly different balance sometimes in terms of the model accuracy you intend to end up working with, maybe at lower accuracy. 00:09:44.500 --> 00:09:47.832 Not not in the lower accuracy, but at lower accuracy than possible. 00:09:47.832 --> 00:09:48.957 The model than possible. 00:09:50.207 --> 00:09:54.666 to be able to get more answers more quickly, evaluate the more more options, more quotations. 00:09:54.666 --> 00:10:06.500 So it's a bit of a funny one in that sense, but but yeah, it's and and I think you ask me about, how someone brings, I think, things to, to the wider world. 00:10:06.500 --> 00:10:12.125 If I think one thing from one is very good at from the one is very resourceful and the pace is super fast. 00:10:12.125 --> 00:10:19.207 So, you know, there is from which and is the one really pushing for the latest processor technology. 00:10:19.582 --> 00:10:30.125 now we are, embarking into, which is already available is becoming more and more, common, GPU being used for CFD compilation as well. 00:10:30.125 --> 00:10:33.416 so all these technologies are very much pushed hard. 00:10:33.416 --> 00:10:44.666 And when we, we work with, you know, suppliers, cloud computing suppliers or HPC suppliers, we you know, people are we are they are used to people doing 1 or 2 simulations a day and in front of one team. 00:10:44.666 --> 00:10:46.666 And we are doing each 151 day. 00:10:46.666 --> 00:10:59.666 So when you think about that, the, you know, the bottom max in terms of, storage bandwidth, memory, you know, at but there's a whole everything is very different when, when you are working at that scale. 00:10:59.666 --> 00:11:02.125 So the scale in the space is just unbelievable. 00:11:03.541 --> 00:11:08.875 And, and then I think so one final thing is are you talking about where we are going? 00:11:08.875 --> 00:11:11.750 I think that's, I think I could speak here for a few hours. 00:11:11.750 --> 00:11:17.416 on that subject, I think we are in a very interesting time. 00:11:17.416 --> 00:11:19.666 I find I find interesting and exciting. 00:11:19.666 --> 00:11:23.000 I think some some people find maybe potential to be scary. 00:11:23.707 --> 00:11:26.041 which is the. What? 00:11:26.041 --> 00:11:27.916 Where are you going with AI? 00:11:27.916 --> 00:11:39.916 and then I think, so I'm in a very fortunate position to be, talking to people and finding out what technologies are there and behind me a fair amount of resources to make those things happen. 00:11:40.207 --> 00:11:52.166 so getting what I think it is, a fact is that over the next 5 to 10 years, there will be a huge transformation on how we do things in terms of er in terms of development. 00:11:52.166 --> 00:12:03.666 I think I'll talk from for my field in areo dynamics, but I do believe that will translate to other areas of simulation, where the way we do things will change very dramatically. 00:12:03.832 --> 00:12:06.832 And when things change

there's always winners and losers. 00:12:06.916 --> 00:12:20.875 And so there will be surprises coming. But, yeah, we what we are experience now, I think is there are some I mean, AI is a very broad term. 00:12:20.875 --> 00:12:24.916 I think there, you know, a linear regression is a form of machine learning. 00:12:24.916 --> 00:12:27.625 But, and it's been done for many, many years. 00:12:27.625 --> 00:12:49.082 But I think some of the technologies coming through now will vastly transform the way we do things in terms of, so taking as an example, CFD, where we are talking about very significant costs to run a simulation and maybe, you know, from one environment, 1 hour to 2 hours to get a full car simulation, we're going to be talking about doing that in less than a second. 00:12:49.541 --> 00:12:56.750 And therefore, instead of doing each shared analysis, doing three a day, there now can be minutes a day. 00:12:56.957 --> 00:12:59.875 And then the statistics of that are unbelievable. 00:12:59.875 --> 00:13:09.832 So if you think about millions a day and you should think, well, even if 99.9% are not very good, there's 2.1%, which is a huge number of good options coming out. 00:13:11.250 --> 00:13:12.791 you know, so this is where we are going. 00:13:12.791 --> 00:13:23.375 And for that reason, I think, the entire concept of what tonight aerodynamicist is or what that engineer developing, whatever they are developing will change the way they do. 00:13:23.375 --> 00:13:25.000 Things will have to change. 00:13:25.000 --> 00:13:27.000 People. Interesting. 00:13:27.000 --> 00:13:28.666 So. Well, let's take it. 00:13:28.666 --> 00:13:32.875 Maybe let's take it a a step up and just look at racing as a whole. 00:13:32.875 --> 00:13:33.207 Right? 00:13:33.207 --> 00:13:36.166 I mean, to me again, a I don't watch racing. 00:13:36.166 --> 00:13:39.750 I love the technology, but I'm not necessarily a racing guy. 00:13:39.750 --> 00:13:43.791 I've gone to maybe 3 or 4 races, in my life. 00:13:43.791 --> 00:13:49.957 My son loves it, but to me it seems you know where F1 is, the big ones, right? 00:13:49.957 --> 00:13:53.500 And then maybe in the US, it's certainly NASCAR, right? 00:13:54.000 --> 00:14:21.332 When we look at technology, when we look at things that you guys are doing, simulation tools, fluid dynamics, whatever it is, let's keep it as generic as you want or as specific as you want. Now, in the automotive space, you have different players that use simulation to a different degree, maybe because it's they're used to it or they need to because faster development, because of cost cutting, whatever it might be. 00:14:21.416 --> 00:14:37.000 Explain a little bit how is racing today and where do you see go is really the formula one teams and maybe the NASCAR guys that use it and all the other, because there's so many different racing series that that I'm at least aware of, and it's probably even more than I don't even know. 00:14:37.000 --> 00:14:43.416 There may be more more basic, still more doing it, the quote unquote traditional way. 00:14:43.791 --> 00:14:54.166 But paint a little picture on how it looks like as it relates to technology and specifically simulation technology adoption in the different types of areas of of racing. 00:14:54.916 --> 00:14:55.375 Yeah. 00:14:55.375 --> 00:14:58.332 I mean, it raises an interesting one. 00:14:58.332 --> 00:15:03.041 So it's, you know, obviously the more resources you have, the more money you spend, the faster you go. 00:15:03.041 --> 00:15:12.041 So so if left unchecked, every category will become, you know, there'll be a bit of a Cold war going on and the spending war and the richest we win. 00:15:12.416 --> 00:15:19.541 So. So I think in general, categories realized that they, they have to put some restrictions to, to limit that. 00:15:19.875 --> 00:15:24.375 I think in more basic, basic categories, they try to really constrain that. 00:15:24.375 --> 00:15:31.457 So you, you only get a car or you can do is to change the suspension set up and tire pressure even or come, you know, very basic changes in win angle. 00:15:31.457 --> 00:15:33.916 But you you really don't have much. 00:15:35.250 --> 00:15:36.082 much more to do. 00:15:36.082 --> 00:15:40.707 You cannot develop new car and, and that's it very much intentional to to keep the costs down and, and keep it. 00:15:40.707 --> 00:15:44.625 I try to I mean, I worked with, Lima. 00:15:44.625 --> 00:15:48.500 so the cars and the equivalents in in U.S would be the IMSa. 00:15:48.500 --> 00:15:55.582 So the LMD cars, sorry, nine IMSa is the, I forget the name of the championship where whether, figured out. 00:15:55.582 --> 00:16:08.000 But, anyway, the cars racing there which is the equivalent and a, that those cars are, you know, they are constrained by a set of regulations, but fundamentally they are motivated, so they are obligated to win tunnel. 00:16:08.000 --> 00:16:10.125 And then once that is done, you cannot change the car. 00:16:10.125 --> 00:16:12.416 And until you come from a real motivation. 00:16:12.416 --> 00:16:15.291 So the again, the idea there is to freeze the design. 00:16:15.291 --> 00:16:19.457 And then also, in that in those categories you have a balance of performance. 00:16:19.457 --> 00:16:23.957 So I will differences change the difference in performance. 00:16:23.957 --> 00:16:27.375 Then it balanced out by weight with weight and power limitations. 00:16:27.707 --> 00:16:30.041 So that again is trying to keep the cost down. 00:16:30.041 --> 00:16:31.666 And competitiveness. 00:16:31.666 --> 00:16:52.041 I cannot comment so much about, NASCAR and IndyCar because I my, my understanding is I think it would be wrong for me to comment and my understanding is limited in formula one, though, although we do have these limitations in terms of budget cost and we pay spending, the scope of work is too unbelievably interesting. 00:16:52.541 --> 00:16:59.416 So, you know,

even with the restrictions, we have teams running wind tunnels, five days a week, two shifts. 00:16:59.750 --> 00:17:08.540 That's 12, 16 hours if anyway, they're doing and, and, you know, data gathering is almost unlimited. 00:17:08.540 --> 00:17:15.040 So we have say, say in aerodynamics, we, we have, pressure topics in the car. 00:17:15.040 --> 00:17:31.083 So we are talking about now, hundreds to potentially thousands of measurements of pressure on the race car and therefore the data sitting back and, you know, and then various various different tools and methodologies to correlate that to CFD, you know, and understand if the car is doing the same thing. 00:17:33.250 --> 00:17:33.540 yeah. 00:17:33.540 --> 00:17:43.750 So technology wise, if you, and I think that formula one needs to pushing the limits there and just and it is simply a case of resources. 00:17:43.750 --> 00:17:48.290 So the the amount of resources available and the, you know, the money behind it is unbelievable. 00:17:48.290 --> 00:17:50.875 So it is great. Great. 00:17:50.875 --> 00:17:52.915 You push the boundaries. 00:17:52.915 --> 00:17:53.790 yeah. 00:17:53.790 --> 00:17:56.000 I don't know if I quite answer your question on that one. 00:17:56.000 --> 00:17:59.000 you know, I think I think it's good. 00:17:59.125 --> 00:18:05.000 I mean, again, I guess, you know, where I'm getting that is like from our business in in racing. Right? 00:18:05.000 --> 00:18:06.875 I got to keep it general here. 00:18:06.875 --> 00:18:13.333 But from our business in racing at AVL, I see a very, very competitive space. 00:18:13.333 --> 00:18:15.625 Right. Very, very competitive. 00:18:15.625 --> 00:18:22.500 when I compare that with passenger vehicle OEMs and their competitiveness, it just doesn't. 00:18:22.500 --> 00:18:23.958 It's really not on the same scale. 00:18:23.958 --> 00:18:25.540 It's just not on the same level. Right. 00:18:25.540 --> 00:18:36.833 So then the question is how much or or some formula I see with formula one or again to racing that, you know, the monde or the formula one that, that you're very familiar with. 00:18:37.915 --> 00:18:39.415 What are the different levels? 00:18:39.415 --> 00:18:48.083 Different companies are using simulation because in passenger vehicles or the heavy duty truck space that do, we do most of our work, right. 00:18:48.625 --> 00:18:57.958 That we can definitely point out which ones are the ones that are adopting and embracing simulation technology way, way more than the auto ones, though, right? 00:18:57.958 --> 00:19:00.958 There's the leaders, there's a large field in the middle. 00:19:01.040 --> 00:19:04.375 And then you have, let's call in the lagers maybe right. 00:19:04.875 --> 00:19:27.040 Is formula one similar though, or does anybody in formula one recognize if you don't do it full blast out, you're not even going to have a chance of winning because you you need to take advantage of every little thing or the the stack up of the differences make it impossible for the driver to make up that difference in technology and capability. 00:19:27.540 --> 00:19:28.833 So share a little bit there. 00:19:28.833 --> 00:19:34.375 And then also again with always looking into the future, what does the future look like. Right. 00:19:34.375 --> 00:19:40.665 So if for example, everybody right now is on the same level, is simulation never going to be a differentiator? 00:19:40.665 --> 00:19:48.165 Is the next best tool the differentiator and the ones that are really eating are just always on the cutting edge of the next better tool. 00:19:48.208 --> 00:19:50.208 Yeah. 00:19:50.208 --> 00:19:53.415 in In formula one, everyone is pushing every single limit. 00:19:53.415 --> 00:19:57.625 So yeah, everyone is into simulation one way or another. 00:19:57.625 --> 00:20:01.665 I think, the quality of their models, is probably will vary. 00:20:01.665 --> 00:20:07.208 And, you know, someone like, like myself wouldn't have the visibility of what other teams has in terms of quality. 00:20:07.208 --> 00:20:26.915 But everyone is pushing I think is everyone agrees that simulation is is a super powerful tool, both in terms of, saving costs and, you know, reducing, reducing, the life cycle and, and, and also look, so the on this aspect of simulation is obviously understanding what's happening. 00:20:26.915 --> 00:20:31.208 And you have much more visibility, much more information about the problem you are trying to solve. 00:20:31.208 --> 00:20:41.750 I think what, what, from a one is really, different is, because of the amount of cost, amount of resources and testing we do, we have a lot of data to correlate. 00:20:41.750 --> 00:20:52.040 You. So I think the models are very much tweaked and, over time have been adjusted and, and accuracy improved. 00:20:52.040 --> 00:21:03.540 and then again, I'll come to I now as in, I think another area that is being exploited very heavily is how do I integrate experimental data to, computational data. 00:21:03.540 --> 00:21:13.165 I think anyone in the I think I think all of us in the simulation environment have been, we are used to the people questioning the quality of our models. 00:21:13.915 --> 00:21:15.540 I always felt. But as he. 00:21:15.540 --> 00:21:20.083 That's definitely the case in CFD, the thing certainly has been on the back side over for a long time. 00:21:20.540 --> 00:21:26.083 but I think very few people over the years crash the experimental data as well. 00:21:26.083 --> 00:21:28.583 And how that does that represents the track. Why. 00:21:28.583 --> 00:21:34.290 So now now I think where we're coming in my field, we are coming to a point where we have a good understanding of the limitations of both sides. 00:21:34.290 --> 00:21:35.958 But we are saying, hold on a second. 00:21:35.958 --> 00:21:38.290 We have all this information. 00:21:38.290 --> 00:21:41.333 My simulation might explain very well these relationships. 00:21:41.333 --> 00:21:46.708

My experimental model gives me this quite good, accurate information of those points, but only those. 00:21:46.708 --> 00:21:52.583 How can I couple those two now and, and, you know, make a better prediction of what's going to happen in reality. 00:21:52.583 --> 00:21:55.625 So so, to give you an example, here it is again. 00:21:55.625 --> 00:22:01.040 I'll try to stay on my side, but, my, my area, but, tire shape is a big thing for us. 00:22:01.040 --> 00:22:12.415 So we we have a car, we're on the track, huge deformations of the tire and from on from there, then on this use, that's crucial to understand how the tire, the forms and model, the shape and the safety model and the wind tunnel. 00:22:13.125 --> 00:22:16.165 And that's a big source of correlation across tools. 00:22:16.875 --> 00:22:23.625 and yeah, you can go in a, in a, in a test rig and, you know, apply some preload to some natural lobe and measure that. 00:22:23.625 --> 00:22:24.708 But that's not the race car. 00:22:24.708 --> 00:22:27.208 Right. The, the, the racing environment. 00:22:27.208 --> 00:22:37.040 So it and then you can go and create a simulation model that tire and you know that exploit different different loading that you cannot do experimentally. 00:22:37.040 --> 00:22:39.165 But then you have all the limitations in terms of accuracy. 00:22:39.165 --> 00:22:46.125 So now where we are coming to is, you know, I can combine those two very well and have a much better prediction of weapons on track. 00:22:46.290 --> 00:22:51.875 so I think that that is a very powerful aspect of what's happening now in terms of enhancing simulation. 00:22:51.875 --> 00:22:56.833 Well, this I think in terms of how it goes to automotive. 00:22:56.833 --> 00:22:58.250 I work with automotive as well. 00:22:58.250 --> 00:23:11.290 I think, everyone, you know, at least from the high end engineering, you know, fast cars out there and luxury cars, you know, the usual million dollar cars that kind of thing. 00:23:11.583 --> 00:23:15.915 You know, people making those cars, they obviously they they do have their digital twins. 00:23:15.915 --> 00:23:16.625 That's the intention. 00:23:16.625 --> 00:23:19.625 I think everyone understand the value of simulation. 00:23:20.415 --> 00:23:22.333 but obviously the resources are much more limited. 00:23:22.333 --> 00:23:27.875 So, you know, like how they run the simulations, the quality of the model, the correlation levels are reduced. 00:23:27.875 --> 00:23:30.875 But I think throws off to the idea is the same. 00:23:31.625 --> 00:23:32.665 Interesting. 00:23:32.665 --> 00:23:36.958 So maybe one more question generic to to simulation then. 00:23:37.540 --> 00:23:40.000 Yeah. Excuse me. 00:23:40.000 --> 00:23:41.665 You've been in this space for a while. 00:23:41.665 --> 00:23:50.540 You said you've been in the simulation space and just formula or not formula one but just racing in general I would say again and stay with the ones you're certainly familiar with. 00:23:51.375 --> 00:24:03.708 What areas do you see specifically with AI pushing into not only development but during race, probably data analysis and Post data analysis and all of this stuff. 00:24:04.375 --> 00:24:16.000 What areas in racing, in your opinion, is simulation technology or AI, or the analysis of data that we may have or may not even know we have? 00:24:16.750 --> 00:24:24.750 Where are we not pushing simulation technologies yet in in in the racing space where we are not pushing? 00:24:24.790 --> 00:24:27.250 That's an interesting question. 00:24:27.250 --> 00:24:36.708 really I mean, I guess I give you an idea riding in passenger vehicles, we're pushing. 00:24:36.708 --> 00:24:52.583 I am, from my perspective, slowly but surely into assessing with the use of AI and the data we're collecting from driver monitoring cameras, for example, the behavior of the reaction behavior and reaction of people. 00:24:52.958 --> 00:25:13.875 That is not the purpose of a driver monitoring camera necessarily, but it gives us information as relates to the way the car breaks, the way the car accelerates to maybe how annoying or not annoying, asserted a certain audible or visual warning or sign is right. 00:25:14.000 --> 00:25:18.083 that is really, I would say, somewhat of, of a new area. 00:25:18.083 --> 00:25:20.958 Right. It's sort of an area that's being trailblazer now. 00:25:20.958 --> 00:25:29.540 And I think we'll come out on, there's other areas where we use data from a driver for more from a, from a medical perspective. 00:25:29.540 --> 00:25:29.708 Right. 00:25:29.708 --> 00:25:34.458 And how well is his or her heart rate doing, in certain situations? 00:25:34.708 --> 00:25:47.208 should some will be allowed to, drive level three autonomous on the road when he or she is upset, out of breath, drunken impaired right, whatever it is. 00:25:47.540 --> 00:25:49.665 Those are some areas we're pushing into. 00:25:49.665 --> 00:25:57.875 That simulation is only, I think, at, at, not at the forefront, but at, sort of at the beginning of what we can do. 00:25:58.250 --> 00:26:01.040 And I'm interested that there's got to be areas too. 00:26:01.040 --> 00:26:19.665 I would be surprised if those not in, in racing where, where you see the opportunity with the data, we either have or could get the we need a create models to simulate some of these things for the better obviously then improve the technology to speed of the vehicle, maybe to safety. 00:26:20.833 --> 00:26:39.583 or also areas where you could see we could collect data that then really would allow us to create new products, maybe for your company, for other companies or new areas to really, again, not only reimagine mobility, but reimagine maybe how a driver, a race car driver drives the race car. 00:26:39.583 --> 00:26:41.915 So that's what I'm about here. 00:26:41.915 --> 00:26:44.915 yeah, I think I, yeah. 00:26:45.040 --> 00:26:45.540 Okay. 00:26:45.540 --> 00:26:51.165 I would

start with racing, then I'd like to move into aerospace, which I think would be more relevant in these ones. 00:26:51.165 --> 00:27:04.583 I think, one area that I cannot say is not being pushed is, teams have been trying to push, but I think is an area where there is still a steep learning curve going on. 00:27:04.583 --> 00:27:11.083 It is, coupling, experimental data with simulation through, machine learning models. 00:27:11.083 --> 00:27:16.750 So, I'd say one thing is, so, for example, how we characterize the aerodynamic performance of a car. 00:27:16.750 --> 00:27:18.250 And that applies for both cars as well. 00:27:18.250 --> 00:27:23.125 But it's just that doing that kind of analysis is a little bit less relevant in, in a race car. 00:27:23.540 --> 00:27:24.665 So we go we don't know that. 00:27:24.665 --> 00:27:28.625 We know where there is, you know, a quasi static or, slow motion. 00:27:28.625 --> 00:27:30.875 And we measured in different conditions. 00:27:30.875 --> 00:27:37.833 And then we create these maps, air maps that, you know, explain the, you know, kind of give the, the performance over several conditions. 00:27:37.833 --> 00:27:46.375 So on, and likewise, you CFD what we tend to do is we do this quasi, quasi static simulation where we are running steady state in various points. 00:27:46.375 --> 00:27:49.165 So we don't have the transient behavior. 00:27:46.375 --> 00:27:49.165 We can we could do it. 00:27:49.165 --> 00:27:56.540 But these very expensive units and one recent case from Milan, the the recent regulation that occurs is the effect of porpoising. 00:27:56.540 --> 00:28:01.665 So we have this coupling between the diffuser and so the car, the teams want to run the car as low as possible. 00:28:02.040 --> 00:28:07.790 But then the car priest so much downforce he sucks the car down into stalls and then pulls up again. 00:28:05.540 --> 00:28:07.790 So you have this dynamic. 00:28:07.790 --> 00:28:10.458 I have dynamic coupling. 00:28:10.458 --> 00:28:18.958 and, you know, it's essentially a transient effect that has to be models and, and, you know, the tools are not quite there to do that easily. 00:28:18.958 --> 00:28:30.290 And, and again, I need to be careful here because there are all the teams maybe might watch these and say, hey, we've been doing this for four years and I'm aware that they, I would say is in the early stages of, of that development. 00:28:30.290 --> 00:28:31.833 And I think there is a there are opportunities here. 00:28:31.833 --> 00:28:46.375 If were using, existing or experimental data or race car data from the track and, and then combine, to simulation data and make predictions about what would be the transient behavior. 00:28:46.583 --> 00:28:51.790 Now moving to an aerospace example, which I can talk about, which I just my company, developed. 00:28:51.790 --> 00:29:02.333 So we, we recently had been working on a, a new concept of an electric propeller, for a eVTOLs is targeting new eVTOLs, but

essentially could be applied for. 00:29:02.458 --> 00:29:06.415 And so with the idea is that the electric is that the motors would be moved to the rim. 00:29:06.415 --> 00:29:09.000 So we don't have the motor at the center anymore. 00:29:09.000 --> 00:29:11.125 And there are several advantages. 00:29:11.125 --> 00:29:15.040 You know, it runs in low rpm, side torque, lower rpm. 00:29:15.040 --> 00:29:21.500 So it's quieter and, and, and there is an efficiency gain because of the, air losses that the, the tips from north there. 00:29:23.500 --> 00:29:30.083 and one, one interesting aspect of that one is, we have done that parallel project using AI. 00:29:31.375 --> 00:29:41.333 and the idea was say, well, if you imagine I'm flying my, my aircraft, my craft, let's call it, it could be different shapes for my craft and fly my craft. 00:29:41.333 --> 00:29:45.708 And, and then I have a few discrete sensors in my craft, pressure sensors that tell me. 00:29:45.708 --> 00:29:56.290 So let's say I have, 1050, you know, that a reasonable number of tool and you don't have a full map of what's happening next. 00:29:57.040 --> 00:30:15.375 so we then developed the technology where we, we're using CFD data, where we have all the pressure on the surface, force various conditions, and then we can create relationships that say, well, if my the pressure at that point where I have my sensors here, here, here and there is telling me, give these numbers, then I can. 00:30:15.915 --> 00:30:22.415 So then the pressure everywhere else would be such and and what that allows is in principle. 00:30:22.415 --> 00:30:35.000 And I think that could be interesting in terms of sustainability in the future, is that you can trim your craft or you can predict behaviors, you know, you can in theory, you can predict early signs of a stall from that. 00:30:35.000 --> 00:30:49.000 Or you can, you can optimize, you can trim your craft to run a slightly more efficient, angle of attack and can to condition based on using, you know, that that very raw, very simple piece of information isn't correct. 00:30:49.000 --> 00:30:55.250 So I, I see this problem on the water based, very incomplete set of information coming from the, the, the real life application. 00:30:55.583 --> 00:30:58.790 But he hadn't seen it with all the computation and the simulation data. 00:30:59.665 --> 00:31:01.208 So that that's an area that he that is growing. 00:31:01.208 --> 00:31:03.665 I think some people are exploring, but it's not quite there yet. 00:31:03.665 --> 00:31:06.625 It's good, it's good, it's good, it's good. It's interesting. 00:31:06.625 --> 00:31:08.583 So we have two questions to wrap it up. 00:31:08.583 --> 00:31:10.208 One for you. 00:31:10.208 --> 00:31:17.290 Gerson, what excites you most that's going to happen in the next five years and let's leave it racing. 00:31:17.333 --> 00:31:18.458 What excites you the most? 00:31:18.458 --> 00:31:23.583 Is it the new requirements that are coming out with Formula One, where you now also have a battery in it? 00:31:23.583 --> 00:31:37.040 So you kind of have a hybrid now is it is it the pure EV races that are popping up more and more and gaining in popularity, is it more different, more and or different technologies? 00:31:37.290 --> 00:31:39.500 What excites you the most about the space? 00:31:40.458 --> 00:31:41.125 yeah. 00:31:41.125 --> 00:31:48.750 Well, I, I'm sorry for being, going on the same, same note again, but I would say I think I'm actually quite excited about how everything would change with AI. 00:31:48.750 --> 00:31:56.290 And I think, you know, fundamentally, I think, motorsport would be the first layer to see that, how significant the change will be. 00:31:57.415 --> 00:32:04.375 and I just think, you know, we we, we are we talked to here at, you know, be particular about simulation, but we think the simulation works. 00:32:04.375 --> 00:32:04.625 Really. 00:32:04.625 --> 00:32:09.625 There are other areas, such as you'd run a simulation, you need to make a decision about that. 00:32:09.625 --> 00:32:14.125 And, the decision accelerating decision making is another very important area. 00:32:14.125 --> 00:32:20.415 So, you know, can I run my simulation and get a very detailed report already telling me why something happened? 00:32:20.415 --> 00:32:29.833 And instead of spending an hour doing that and in the formula one workflow, is that super important new shaving those minutes of time, I think I think, it's an exciting area. 00:32:29.833 --> 00:32:39.750 I think I, I feel slightly I think probably most people feel slightly scared about what's going to happen because there's a change coming and he's never, you know, comfortable. 00:32:40.415 --> 00:32:42.415 but I chose to embrace it. 00:32:42.415 --> 00:33:00.833 And I'm, I think I'm really excited about the changes that are coming in terms of, at the courtesy, I think I think what we should be seeing is, in, in, in some industries and more which it, say is talking about mobility now thinking about, like, commercial aircraft. 00:33:00.833 --> 00:33:05.250 I think they, you know, the concept of wing, a car, a aircraft where the we get stabilizer. 00:33:05.250 --> 00:33:06.333 It's been there forever. 00:33:06.333 --> 00:33:09.458 There's a lot of data, so it's unlikely to change very quickly. 00:33:09.458 --> 00:33:12.540 But you think about EV e-tolls, for example, is a completely new thing. 00:33:12.540 --> 00:33:15.583 And and that people are question what what is what shape should that be. 00:33:16.000 --> 00:33:19.375 And I think that's where it again where you can generate a million options. 00:33:19.375 --> 00:33:27.333 And overnight we are going to be some very wacky shapes coming and things that a human potentially wouldn't think about. 00:33:27.915 --> 00:33:39.790 so, so you know, that that area, I think there are some, some, some key areas where, where I think we going to see more on, on the automotive, side and,

and transportation and automotive transportation. 00:33:39.790 --> 00:33:42.875 I think in the, in the end of the day, there's a practicality element. 00:33:42.875 --> 00:33:47.290 So we want cars which are can see a certain number of people. 00:33:47.290 --> 00:33:52.915 You can fit your shopping bags in the boot and you can, you know, like a truck has to be boxy to fit boxes. 00:33:53.208 --> 00:33:55.665 So there's only so much you can do in terms of changing the shape. 00:33:55.665 --> 00:33:58.790 But still, I think I think still we're going to see subtle changes. 00:33:58.790 --> 00:34:01.540 And I think, yeah, that would be quite interesting to see. 00:34:02.750 --> 00:34:04.458 Good, good. 00:34:04.458 --> 00:34:05.875 Last question for you. 00:34:05.875 --> 00:34:07.208 Nothing to do with racing. 00:34:07.208 --> 00:34:10.458 Well maybe it has to do with racing, but I, I would doubt it for a second. 00:34:10.458 --> 00:34:14.041 But what's what's the next car you're going to buy and why. 00:34:14.208 --> 00:34:18.833 And maybe it is a race car, I don't know, I, you know, I'm a very boring person for that one. 00:34:18.833 --> 00:34:23.833 I know, high performance engineering, but my cars have always been very practical. 00:34:23.875 --> 00:34:33.375 I currently drive a Ford Transit van because I have a family, and I have, my lifestyle is about going company and carry on with bikes and my board in it. 00:34:33.500 --> 00:34:35.750 So I drive what I need. 00:34:35.750 --> 00:34:38.875 I just bought this van, and I'm very happy, so I'm not planning to change. 00:34:38.875 --> 00:34:45.833 But I think one thing I told my friends is that once you have a van, you are not not having your van again, because I can carry it on my holidays. 00:34:46.666 --> 00:34:48.833 So my, my next car will be a run again, I think. 00:34:48.833 --> 00:34:49.583 Very good. 00:34:49.583 --> 00:34:53.625 Well, it's like my family, you know, we we never wanted to buy a minivan. 00:34:53.666 --> 00:34:55.375 Once we had a minivan, we have to family. 00:34:55.375 --> 00:34:58.250 We never wanted to give it up because we realized how great it is, you know? 00:34:58.250 --> 00:35:00.416 But I was the black sheep in Formula one. 00:35:00.416 --> 00:35:01.250 you know, I used to go. 00:35:01.250 --> 00:35:06.125 I come in the car park and all these people with this sports car that I'll come with the Toyota Yaris and park there. 00:35:08.666 --> 00:35:10.041 As. Nothing wrong with that. 00:35:10.041 --> 00:35:11.166 Very good. 00:35:11.166 --> 00:35:12.708 Thank you so much for your time. 00:35:12.708 --> 00:35:24.166 And really highlighting an area of, of the mobility space that I, and I think many of our listeners may know where near ev as much inside or a perspective to as in many other spaces of mobility. 00:35:24.541 --> 00:35:26.041 Again, particularly here racing. 00:35:26.041 --> 00:35:32.625 So thank you so much for educating us and and giving us some great insights and things to ponder about.