Influence of façade details on early design decisions regarding daylight performance of neighborhoods

Neighborhood form and building facade design are key drivers of indoor daylight performance. Architectural design at the neighborhood scale starts with massing scheme proposals and other design specifications including façade design are typically enriched sequentially in subsequent design stages. In this study, we simulate multiple pairs of early design massing schemes and compare their daylight performance at sequentially increasing façade level of detail (fLOD). We found the design-decision between two schemes to be more robust at high window-wall ratios (WWR) as the difference in the estimated daylight performance of two massing schemes was amplified at high WWR. At medium and low WWR, the performance difference between the massing schemes, and the resulting design-decision depended on the façade design choices such as the distribution of openings across different orientations and balcony design. Also, at high stringency in decision criteria (i.e. requirement of higher margin of difference in performance), higher fLODs were found to improve the accuracy of decision.

[1]  Émilie Nault.  Solar potential in early neighborhood design , 2016 .

[2]  Kevin Van Den Wymelenberg,et al.  Patterns of occupant interaction with window blinds: A literature review , 2012 .

[3]  Jlm Jan Hensen,et al.  Uncertainty analysis in building performance simulation for design support , 2011 .

[4]  Marilyne Andersen,et al.  Robustness Assessment Methodology for the Evaluation of Building Performance with A View to Climate Uncertainties , 2015, Building Simulation Conference Proceedings.

[5]  Christoph F. Reinhart,et al.  A rules of thumb-based design sequence for diffuse daylight , 2010 .

[6]  Lisa Heschong,et al.  Approved Method: IES Spatial Daylight Autonomy (sDA) and Annual Sunlight Exposure (ASE) , 2012 .

[7]  John Mardaljevic,et al.  Influence of input reflectance values on climate-based daylight metrics using sensitivity analysis , 2018 .

[8]  P. Michalatos,et al.  URBAN DAYLIGHT SIMULATION 1 CALCULATING THE DAYLIT AREA OF URBAN DESIGNS 2 3 , 2013 .

[9]  K. Steemers,et al.  Urban Form, Density and Solar Potential , 2006 .

[10]  Eduardo Fernández,et al.  EXPLORING METRICS ON THE EVALUATION OF THE BIOCLIMATIC POTENTIAL AT EARLY STAGES OF URBAN PROJECT , 2015 .

[11]  N. F. F. Ebecken,et al.  On extending F-measure and G-mean metrics to multi-class problems , 2005, Data Mining VI.

[12]  M. Nikolopoulou,et al.  Urban geometry and solar availability on façades and ground of real urban forms: using London as a case study , 2016 .

[13]  Michael D. Lepech,et al.  A multi-objective feedback approach for evaluating sequential conceptual building design decisions , 2014 .

[14]  C. Ratti,et al.  Energy consumption and urban texture , 2005 .

[15]  D. Robinson.  Urban morphology and indicators of radiation availability , 2006 .

[16]  Christoph F. Reinhart,et al.  Validation of dynamic RADIANCE-based daylight simulations for a test office with external blinds , 2001 .

[17]  Randolph Kirchain,et al.  Sequential early-design guidance for residential single-family buildings using a probabilistic metamodel of energy consumption , 2017 .

[18]  Peter Andreas Sattrup,et al.  Building typologies in northern European cities: daylight, solar access, and building energy use , 2013 .