Many computational studies generate an array of solutions for a design problem paired with their structural or daylighting performance. An enormous investment of effort and computational time is required to create these simulation-based datasets. However, the generated data is usually bound to the specific case studies they were created to explore. Can this data be useful for application to other design cases? This study employed a generative algorithm to fill a database with perforated shell structures covering a courtyard. A shell by Heinz Isler was chosen to be mapped onto the generated solution space based on its performance. The study found that this method is effective for predicting daylight performance, while structural performance modifications can be a source of inspiration for designing other structural forms.
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