Conclusion

During this internship, I discovered a great tool: the Pulse Physiology engine. Even though some results weren’t those expected, most of the results were in agreement with the scientific literature. This human simulator could be used as a source term in a modeled room and provide interesting information that can be linked to my colleagues' internships: Mariam studied Indoor Air Quality (IAQ) modelling and its application to COVID-19 transmission, Steve studied the zero-equation turbulence model, and Jimmy studied the modelling of the environmental impact on people in buildings.

The ultimate goal of this internship would have been to spread the amount of coronavirus particles from our simulated patient into a room. Based on Zechariah Lau, Ian M. Griffiths, Aaron English, and Katerina Kaouri’s article on "Predicting the Spatially Varying Infection Risk in Indoor Spaces Using an Efficient Airborne Transmission Model", the choice of an advection-diffusion-reaction equation for the spread of the virus is reasonable.

The Feel++ software can be used to do so, and in particular the Coefficient Form PDEs toolbox, in the Feel++ in Python interface.

I would like to conclude this report by thanking Cemosis for having me as in intern, and in particular Mr J. Aghili for our weekly meetings and his availability to answer my questions.