Spray Segmentation

Under gas turbine conditions, the aerodynamic forces exhibit a driving influence on atomization performance of liquid fuels and we strive to advance the fundamental understanding of the involved processes. To this end,  quantitative diagnostic and data analysis is indispensible. Here we advance state-of-the-art AI detection models to analyse the experimental data, segregate ligaments and droplets to delineate the spray process from primary atomization to turbulent dispersion and provide a quantitative description of the process. The developed knowledge base facilitates a comprehensive injection system optimization in order to realise excellent atomization. In turn, this features prompt evaporation and mixture formation that is key to reduce non-CO2 (NOX and particulates) emissions of related combustion system.

The developed models are later validated with external methods to check the accuracy of the models. It is also ensured that the models are capable of predicting over a wide range of cases, thus ensuring better generalisation.

If you are interested in our project, have further questions, or would like to support us through student work, internships, or thesis projects, we would be delighted to hear from you via email or phone. Contact details can be found below.