How much Python is used in creating the next generation rockets? In this poster, I will demonstrate this using an example of supersonic combustion. Supersonic combustion occurs rapidly, requiring high-speed cameras to capture the details of the combustion physics. Each take produces large datasets that need to be analysed to visualise this complex physics. In this poster, I will discuss how Python is used to perform this analysis. I will show analysed videos/images of supersonic combustion using hydrogen as a fuel conducted in a wind tunnel. These images will show combustion data in terms of density gradients in the flow, known as 'Schlieren.' I will show how large datasets from wind tunnel experiments can be carefully analysed using Python to obtain quantitative information on the combustion physics. The audience will be able to see that such complex problems can be tackled with Python. I will conclude with how we are using Python in educating the next generation of rocket scientists!
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