⚠ Work in progress; We apologize for any errors on the web pages.

The whole project started as an off-spin of Martin’s projects during his PhD studies at the (university in city)This new algorithm for the propagation of uncertainties was based on a fundamentally new approach to meta-modeling (https://en.wikipedia.org/wiki/Metamodeling), which was later targeted to engineering problems. It turned out that the developed code was very efficient and very robust. Moreover, the technique provided some new insight into the problem and helped to inform a deeper understanding of the problem. It’s first application was the uncertainty propagation for re-entry of orbital debris, where it has shown the importance of statistical propagation. Results clearly showed that a common assumption of ‘Plus-minus’ around the result is completely wrong as you can see in the picture below.

The statistics have a profound influence on the expected result and sometimes it can create some famous quotes such as ‘Houston, we have a problem’. Well, engineers were probably not very happy about this infamous space catastrophe.Moreover, the result was something unexpected even for the team who was working on the re-entry case. We tested the result with an experiment by throwing small balls into the air and observing their impact locations. It turns out that the results of the experiment were very similar to our algorithm, which proved that our algorithm worked very well.

The second case was the re-entry of GOCE and its flight parameters . Here again the algorithm showed its strengths and some interesting ‘wow’ moments about the re-entry. However, it showed a very important aspect of the algorithm, that it can work very efficiently for virtually any problem. Hence, it was decided to transform the algorithm into something industry can use to improve their products.

In the first year, the algorithm started to change to suit industrial needs. It was a very turbulent time, but after many hours of programming, testing and developing, an improved version of the algorithm was created. This new algorithm was used for the collapse of the car box-beam, which was done in cooperation with MECAS ESI in Pilsen. Again, the algorithm proved its robustness and showed that it is working very well even for such complex cases. More importantly, we came up with some interesting ideas on how to provide engineers with even deeper insight. This case impressed Skoda Auto and we started to cooperate on passive safety of cars.

After the first year and with a successful application of our code in industry, we were accepted into ESA Incubator in Prague 
(http://www.esa-bic.cz). Empowered with new ideas, experienced with industrial problems and full of enthusiasm, we started to develop a new industry target platform. After two years of successful incubation, we can proudly say that we developed a tool, which can tackle even the most difficult cases with an efficiency never seen before. Moreover, apart from standard analysis, our tool provides unique insight, which is only available due to our unique approach. Our tool already helps engineers to develop a product, which is more reliable, efficient and ahead of it’s competition.

Today, industry and academia are using our tool, but we will not stop there. We have plenty of new ideas on how to improve our code in its efficiency and even more ideas on how to provide engineers additional insight to produce a better product – so stay tuned.