Ben has successfully completed a BSc in Physical Geography at Lancaster University, an MSc in Climate Change at University of East Anglia and has recently completed the MRes in Energy Demand Studies as part of the LoLo programme at Loughborough University. Prior to joining LoLo Ben spent two years working in the water industry as computer modeller at WRC in Swindon. His MRes dissertation topic was centred around predicting ventilation effectiveness values for a range of mechanical and natural ventilation strategies. This project used CFD techniques to model the different ventilation systems and predict the ventilation effectiveness values. Ben will continue to investigate ventilation effectiveness and other performance metrics for natural ventilation in his PhD. With the use of CFD and other modelling techniques.
For his PhD the thesis title is “Multi-Criteria Optimization of Building Design for Natural Ventilation”. This project will investigate different methods that can be used to optimize a building’s façade against a range of design criteria. The design criteria being studied will cover both Indoor Air Quality (IAQ) and Thermal Comfort (TC) parameters. This project will endeavour to use an Evolutionary Algorithm (EA) and an Artificial Neural Network (ANN) to optimize the building’s façade. The ANN will act as a surrogate model to replace the use of time intensive modelling techniques such as Computational Fluid Dynamics (CFD). The ANN will be trained through the use of either CFD or Fast Fluid Dynamics (FFD). A key outcome of this project is to design a methodology that allows for building optimization against IAQ and TC metrics to be conducted efficiently. Through the efficient use of the ANN and FFD, this methodology could be more acceptable for industrial use where time is a key factor in the early design phase of a building.