Suitability of neighborhood-scale massing models for daylight performance evaluation

Access to daylight in buildings is the combined effect of a building’s own physical attributes along with its surrounding physical context. There is thus growing interest among researchers to extend the use of building performance simulation (BPS) tools for daylight performance evaluation, not just for an individual building, but to the neighborhood scale and beyond. In the design process of neighborhoods, massing models are often utilized and are a pivotal early design-stage work-product. These models are typically simple and delineate broad geometric dimensions of built enclosures. They are thus attractive for fast early design stage assessment using BPS tools and maybe used to determine daylight access potential. However, at this stage, the designer may have limited and imprecise information regarding the building façade, the vital element for daylight intake and distribution in the building interior. In this study, we assess the dependability of simple massing models for comparative indoor daylight assessments of neighborhood forms. Useful Daylight Illuminance (UDI) metric based performance values were calculated for five neighborhood design options using common practice for façade related inputs in early design stage simulation models and then ranked in decreasing order of performance. A virtual progression of the design-process was then carried out to develop multiple plausible façade design solutions for all proposed massing schemes. The main finding of this study is that significant changes can be observed in neighbourhood rankings when increasing the degree of detail in the façade design solutions. While the highest performing designs were found to maintain their ranks, the rankings of other projects shifted considerably when façade related information was supplied. This work informs on the possibility of erroneous design decisions resulting from simplified façade inputs in early design stage models and fosters the growing discussion on appropriate utilization of BPS tools for informing design decisions.