AirShaper

Can software tell you how to improve #aerodynamics ? AirShaper surely can! ▶️ Design Advice is based on "adjoint" simulations - a technique will tell you how to morph a surface (inward or outward) to reduce drag, or increase lift. It's an extremely powerful technique to provide designers with insights as to how they can improve their design. It very often leads to surprise gains & shapes you wouldn't think of! And, importantly, it dramatically cuts the time-to-market! See for yourself: https://lnkd.in/e9x6j8WW Would you use this tool?

Starting from the basics - What is #aerodynamic drag? Video by Wouter Remmerie 🏁 of AirShaper #cfd #simulation

No #AI - Just straight to the point without training! Check how this algorithm can morph 3D models to lower #aerodynamic drag ▶️ We like #AI and see a bright future for it. But in many cases the adjoint shape optimization technique is much more efficient to come up with an improved design. After running a normal #aerodynamic #cfd #simulation, an adjoint simulation is performed. This method will calculate how a surface should be morphed to reduce drag (or increase lift, if you like). Then, it will implement these suggestions by morphing the CFD mesh. And then the cycle repeats: - Run an aerodynamic simulation to map the new flow field - Run an adjoint simulation to know where to morph the surface - Morph the geometry After just 5-10 iterations, you'll end up with an improved version of your own 3D model. Benefits versus AI: - No training required - Actual simulations, not predictions (yes, simulations are also predictions, but you know what I mean :) ). - No constraints in terms of going beyond the limits of the data set. All new shapes are properly analyzed using a full CFD run - Much cheaper if you factor in the cost of training Downsides versus AI: - Not real time - Always starts from your existing design, doesn't come up with crazy wild new ideas - More expensive per run (if you ignore the training) Check out the online results here: https://lnkd.in/eSxr6K6H What are your thoughts?

This car hit 447.8 km/h already by cutting drag by 28%! Check how Adriano Raeli did this using AirShaper 👇 The donor car for this project was the #lamborghini Huracán and the goal was (and still is) to reach 300 mph. Boosting the engine's power can help a lot, but it's not enough. You also need to improve the #aerodynamics - and in this case, we slashed the drag coefficient by a staggering 28%! It took countless #cfd #simulations and many special tricks. But the results were there - on the first test, the car already hit 447.8 km/h! Curious to learn how? Then check out the video or check sample projects at app.airshaper.com!

Excited to share our podcast with TELO Trucks 🚗 Learn how to reduce drag, the evolution of AirShaper, and the vital link between aerodynamics & efficiency ▶️ https://lnkd.in/esQ_egPV #aerodynamics #simulations #cfd Thanks a lot Jason Marks Forrest North Lee Anna Mariglia for hosting AirShaper!

Can the creators of the fastest drone (480 km/h) do it again? Check how they're using AirShaper to break the RC car record! https://lnkd.in/gRCWcGzQ #aerodynamics #cfd #simulations

Discover how we optimized electric vehicle design and decreased 3% in emissions from electricity consumption 👉 https://lnkd.in/eYYqnqNE WBCSD – World Business Council for Sustainable Development Solar Impulse Foundation Aptera Motors #theclimatedrive #pioneerwards #climateaction #aerodynamics #cfd #simulation

A massive thanks to all of our subscribers!!! Awesome work Nikola Majksner and Wouter Remmerie 🏁

You can now find AirShaper & many more engineering companies on Engineering Maps 👉 https://lnkd.in/e6vMD2mf Good luck Michael Rüd-Momeni!

Upcoming webinar on #cfd #simulation! From CFD theory to record breaking Lamborghini's - register below! Join Sandeep Mouvanal, Ph.D and Wouter Remmerie 🏁 on Nov 25th!