Greetings everyone!
Today is a very exciting day!
Today we mark the beginning of the UN-BIASED project, funded by the EU through the Horizon TMA MSCA framework.
The project’s name is an acronym for UNcertainty quantification and modelling Bias Inhibition by means of an Agnostic Synergistic Exploitation of multi-fidelity Data.
Quite a lengthy title, isn’t it?
But no worries, understanding the project’s goals is easier done than said!
Let’s see what UN-BIASED is all about in short.
It all started with realising that the Scientific Modelling method currently implemented by Scientists is a heavily hypotheses-driven process.
As such, it is strongly biased by the subjective thinking of the human mind which ultimately introduces accuracy limits in the mathematical model that we use to describe the reality surrounding us.
The UN-BIASED project aims at solving this issue by developing an objective procedure for modelling complex physical phenomena.
In other words, by unbiasing the modelling process from the Modeller’s beliefs concerning a particular phenomenon.
So lets the data speak!
The key tool for achieving such an ambitious goal is indeed Data Science, which opens the path to an unbiased approach to our learning experience. By closely integrating Data Science methodology within the current standard modelling processes, we believe that it is possible to improve our understanding of reality and achieve a more accurate description of complex physical phenomena.
And then what?
Our target application is tilt-rotors and multi-rotor machines which have the unique capability of combining vertical take-off and landing with a high cruise speed, comfort, and range.
This capability is awesome and essential to electric Urban Air Mobility, search and rescue, emergency medical services, air-taxi, and service to isolated areas.
Despite the large amount of resources pledged by the industry, we still lack a clear and full understanding of the complex aerodynamics characterising these machines…
…and this is the perfect playground for UN-BIASED!
Wanna go more technical?
Have a look at the UN-BIASED manifesto!
