Advantage
through #science

Future kiteboarding is data driven

Take a #tour

.data
(evolves

#Science to the mix

Learn how #data evolves kiteboarding

Learn how #data evolves kiteboarding

Advantage through #science

Data driven development

Vantage starts developing where conventional kite development methods end. Benchmarking the data driven future of kiteboarding.

Through the utilization of a unique data driven and computational deep learning kite design workflow we aim to outsmart the conventional kite development methods for good. Enabling next-generation kite performance. Fly Vantage, fly the data driven future of kiteboarding.

Conventional development

Today’s 60+ kite brands and 15+ kite designers mostly lean on experimental kite development methods.

Kite design today is based upon trial and error and kite performance gets determined through human interpretation. The traditional design methods are therefore by default prone to human error, causing the industry to face severe challenges in its ability to innovate and increase kite performance.

Data driven development for a common #goal


Achieving new #records

Explore #technology

In-flight #data
sensor grid

In-flight #data capture
sensor grid

Why in-flight data?
To understand the real-world structural behaviour of kites, we collect data by using an array of IMU, GPS and pressure sensors. The acquired data is then being converted into a virtual 3D model which represents the real-world behaviour of a kite deforming in flight.

#Aerodynamic analysis

#Aerodynamic analysis & optimization

Computational Fluid Dynamics
CFD analysis are being applied to optimize aerodynamic efficiency. We run our CFD analysis on dynamic and deforming 3D models. Compared to static models, dynamic models represent real-world behaviour at a much higher accuracy.

#Structural analysis

#Structural analysis & optimization

Structural optimization
Kites by default are unstable and flexible structures. To optimize kite designs we simulate the structual deformation behaviour and gain insights on flight behaviour prior to prototype.

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