ADVANTAGE
THROUGH
#SCIENCE

Enabling next-gen performance

Vantage starts where conventional kite development methods end. By utilizing a data driven, deeplearning kite development method we enable next-gen performance.

01 IN-FLIGHT
DATA CAPTURE

To understand the real-world environment and usage patterns of kites, we collect data by using an array of IMU, GPS and pressure sensors. The collected data is being converted into a realistic 3D model which is required to run accurate CFD and kite deformation simulations.

02 DEFORMATION
SIMULATION

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

03 FLUID DYNAMIC
ANALYSIS

Computational Fluid Dynamic 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.

04 PERFORMANCE
VALIDATION

Once a prototype takes flight we again capture in-flight data. The data collected is used within a deeplearning simulation framework which offsets the realworld performance against the simulation results and therefor allows us to validate and substantiate the true perfomance.

ADVANTAGE
THROUGH
#SCIENCE

Vantage starts where conventional kite development methods end. By utilizing a data driven, deeplearning kite development method we enable next-gen performance.

01 IN-FLIGHT
DATA CAPTURE

To understand the real-world environment and usage patterns of kites, we collect data by using an array of IMU, GPS and pressure sensors. The collected data is being converted into a realistic 3D model which is required to run accurate CFD and kite deformation simulations.

02 DEFORMATION
SIMULATION

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

03
FLUID DYNAMIC
ANALYSIS

Computational Fluid Dynamic 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.

04 PERFORMANCE
VALIDATION

Once a prototype takes flight we again capture in-flight data. The data collected is used within a deeplearning simulation framework which offsets the realworld performance against the simulation results and therefor allows us to validate and substantiate the true perfomance.