Abstract—Residential buildings are responsible for a significant percentage of energy use and a huge amount of this energy is used for heating and cooling. Efficient natural ventilation is known as method to reduce the cooling energy use. Almost all of the building in modern cities can only use single-sided natural ventilation and façade design is known as an effective factor in wind driven single-sided ventilation of modern buildings. This research aims to develop a methodology to optimize façade design options in order to gain enough single-sided natural ventilation for a residential block. By means of wind-driven single-sided ventilation we are going to gain our three performance objectives which are thermal comfort and indoor air quality for the occupants and minimizing cooling energy consumption. To achieve this, an integration of genetic algorithm (GA), artificial neural network (ANN) and computational fluid dynamics (CFD) is proposed.
Index Terms—Façade, genetic algorithm, optimization, ventilation.
Samin Marzban and Lan Din are with the Faculty of Built Environment, University of New South Wales, Sydney, Australia (e-mail: s.marzban@unsw.edu.au).
Victoria Timchenko is with the School of Mechanical and Manufacturing Engineering at the University of New South Wales, Australia (e-mail: v.timchenko@unsw.edu.au).
Matthias Irger is with the Australian School of Architecture and Design, University of New South Wales, Australia (e-mail: m.irger@unsw.edu.au).
Cite: S. Marzban, L. Ding, V. Timchenko, and M. Irger, "Façade Optimization in a Wind-Driven Ventilated Residential Building Targeting Thermal Comfort, IAQ and Energy Consumption," International Journal of Environmental Science and Development vol. 7, no. 5, pp. 379-384, 2016.
