Step 1 - Generative Design Framework
Step 2 - Generative Design Study
Step 3 - Generative Design Study Results
The optimization results illustrate the tradeoff between:
- winter solar gains,
- summer solar protection,
- and interior daylight availability.
The study produced a range of Pareto-optimal solutions rather than a single dominant solution. This suggests that the façade design problem involves genuinely conflicting environmental objectives, where improvements in one performance criterion often result in a corresponding decline in another.
The Parallel Coordinates Plot demonstrates that solutions with improved winter solar gains and higher interior daylight availability generally also experience increased summer solar exposure. This relationship can be observed in the graph, where solutions performing well in FO1 (interior radiation) and FO2 (winter radiation) tend to perform poorly in FO3 (summer radiation). Conversely, solutions optimised for reduced summer radiation often show lower winter solar gains and reduced interior daylight performance.
The results also suggest a positive relationship between interior daylight availability and winter solar gains, since façade configurations with larger glazing areas generally improve both objectives simultaneously. However, these same solutions often increase summer solar exposure, reinforcing the importance of external shading strategies.
The optimisation, therefore, did not identify a single universally optimal façade configuration. Instead, the study revealed a range of balanced solutions representing different compromises between daylight availability, passive winter solar gains, and summer solar protection.
Simplified radiation-based proxy metrics were intentionally used instead of full thermal or daylight simulations in order to maintain computational efficiency during evolutionary optimisation while still capturing the environmental tradeoffs influencing façade performance.
