Multi criteria optimization for High Comfort-Low Impact in Buildings
A tool for designing better buildings is a passive design optimization that uses simple regression equations and is to be employed in the conceptual design stage. The tool helps in identifying which passive building approaches would work for certain climate contexts. Early introduction of sustainable strategies in the design process reduces the changes required to a design at a later stage.
In the past three to four decades a building has evolved from more than being just a shelter, Key elements that define the quality of a space today are thermal comfort, visual comfort, acoustic comfort and indoor air quality. Most modern buildings have highly controlled indoor climates, irrespective of the outdoor climate regime and at the expense of energy consumption. A building’s passive nature or the ability of the building to use the potentials of nature through cooling and heating are integral to the building form and design.
Thus there is a need for optimizing the comfort parameters in the building in tandem because some of the parameters influence more than one of the comfort modes. For example, windows could influence both the thermal heat gain (thermal comfort) and the daylight factor (visual comfort); in this kind of situation we need to work to find a concrete range for the window size and location that satisfies more than one of the building’s interior comforts.
The objective of this project is to come up with a cross-functional optimization of building comfort modes through multi criteria decision making algorithms/ regression equations.
Expected outcomes of this research project include a set of simple regression equations that can be used at preliminary design stages to quantify the various comfort modes. Accuracy and precision of these equations would be cross verified with commercially available simulation tools. Secondly, considering building form as a parameter for the comfort mode optimization, would give a near optimal building form. Finally, a sensitivity analysis of parameters on comfort modes helps in understanding the extent by which each parameter influences the different modes. This will be presented as a graphical tool to visualize the real time change in parameters and corresponding effect on comfort. ©Ramanathan Subramanian