Environmental Emulation

Machine Learning

Emulation is a technique used to make concept exploration more productive.

A Neural Network has been ‘trained’ to ‘guess’ what the environmental outcomes would be at a particular point on the ground.

Emulation can be used for extended controlled airspace – highlighting and mitigating the impact on commercial use of airspace.

  • Hawkrose has developed tools that support the rapid environmental evaluation and optimisation of airspace systems. The tools rely on neural networks that are trained, from validated environmental modeller outputs, to predict the noise and air quality outcome of any point as a function of airspace geometry and localised flight demand. The rapid evaluation of environmental outcomes, coupled with Reinforcement Learning, enables Hawkrose applications to ‘find’ high performing Airspace Systems based on a few operational parameters and a target function.

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