2023-10-27 –, track 1
In this lightning talk, I will show videos of analysed experimental data obtained in a wind tunnel at a flow speed of Mach 7, i.e. seven times the speed of sound, using Python. I will discuss how Python helps us discover the science behind creating reusable rockets that could one day allow us to fly from London to Tokyo in two hours.
Traditionally, large datasets from wind tunnel experiments have been processed and visualised using MATLAB. However, there is a need of an open-source alternative to make such tools accessible to a wider community, particularly to young scientists and engineers. In this lightning talk, large experimental datasets obtained in a wind tunnel at a flow speed of Mach 7, i.e. seven times the speed of sound, are analysed and visualised using Python. The central topic of this talk will be transpiration cooling — a method where the rocket ‘sweats' an gas to keep itself cool. The steps of data processing, analysis, and visualisation are discussed. The wind tunnel experiments involve the use of Pressure-sensitive paint (PSP) in conjunction with a high-speed camera, a technique that allows for the determination of oxygen partial pressure on a surface in the flow. An area of interrogation of 140 mm x 37 mm is coated with PSP and tested with upstream injection of air, nitrogen, and helium. A relative concentration, ranging from 0% to 100%, is constructed in a pixel-by-pixel fashion from the high-speed videos. The video data are treated with a stabilisation algorithm to remove the jitter that stems from the tunnel’s movement during the experiments. The data are then sent through several signal processing loops to reduce the noise. The frames are time-averaged over approximately 30 ms and the final quantity of relative concentration of the gas, e.g nitrogen or helium, is obtained and visualised in static plots and videos. The aim of this lightning talk is to demonstrate that Python and its libraries are capable of producing scientific quality visualisation of aerodynamics or wind tunnel data and persuade researchers, teachers, and students in this field to utilise this open-source resource. In 5 minutes, I will showcase how Python is being used to discover the science needed to build reusable rockets.
Dr Ifti joined the High-Speed Aerodynamics and Propulsion Lab at the University of Maryland, USA, in April 2022. Originally from Mymensingh, Bangladesh, he earned his DPhil in Engineering Science (Hypersonics) from the University of Oxford, United Kingdom. For the scientific contributions in his doctoral thesis entitle, “Transpiration Cooling of a Hypersonic Vehicle,” he won the 2022 UK Doctoral Researcher Award (2nd Prize, Engineering), in a UK-wide academic competition that is awarded annually to junior researchers with promise to be amongst the world class academics of the future. Dr Ifti holds bachelor’s and master’s degrees in Aerospace Engineering from the University of Stuttgart, Germany.