Multi-Objective Optimization

Indoor inhalation exposure can be minimized through mechanical ventilation. On the other hand, building and mechanical ventilation design remain as the main sources of energy consumption. The present study focuses on the optimization of a displacement-ventilated room by applying computational fluid dynamics, virtual manikins and a genetic algorithm in order to minimize airborne viral density while reducing the energy consumption level. 

The need for zero carbon buildings is changing the trial-and-error process that Architectural design has traditionally employed towards a system that allows wider analysis capacity at the conceptual stage. By visualizing design as a “Black Box” where the composition variable B can be cleared from knowing the stimuli S and the desired response R; optimal solutions arise to the surface.

Previous work involving literature review, simulation tool analysis and interviews with world leading building performance consulting engineers and designers has shown that building performance simulation (BPS) is mostly limited to code compliance checking of the final building design whilst it could provide useful information and guidelines throughout the entire design process [Hopfe et al., 2005/ 2006].