Real time dynamic simulation of indoor environment

Understanding and forecasting airflow in enclosed/indoor environments is of great interest due to its close relationship to occupant’s safety, thermal comfort, and energy efficiency. Optimally placed air conditioning could increase comfort of inhabitants. In hospitals, airflow can distribute germs and can pose a significant health hazard. Indoor airflow patterns can be very complex and computer simulations are an invaluable tool for understanding their characteristics which is critical for improvement of indoor air quality (IAQ). But the complex and dynamic nature of the problem makes it challenging to run them accurately in real-time.

This project will combine novel hardware with modern numerical methods to enable real-time simulations of flows for assessment and possible control of IAQ & comfort in an internal micro-climate subject to a time varying external variables. An existing implementation of the Lattice-Boltzmann method (LBM) for graphical processing units (GPU) will be augmented by a parallel-in-time integration algorithm.

The project offers opportunities for both fundamental algorithmic developments, software development as well as working on an important application of computational engineering. The student will be trained in the physics and modelling of fluid flows, in programming GPUs using C++ and CUDA and in modern numerical algorithms.