| id |
ecaade2023_389 |
| authors |
Szentesi-Nejur, Szende, de Luca, Francesco, Nejur, Andrei and Madelat, Payam |
| year |
2023 |
| title |
Early Design Clustering Method Considering Equitable Daylight Distribution in The Adaptive Re-Use of Heritage Buildings |
| doi |
https://doi.org/10.52842/conf.ecaade.2023.2.105
|
| source |
Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 105–114 |
| summary |
The re-use of existing buildings is gaining importance worldwide in the context of the carbon reduction efforts. In the case of Québec City there is a large number of heritage buildings that are currently unused. There are ongoing projects to breathe new life in these buildings, mainly by converting them in residential units. At the same time there is a growing preoccupation in Québec province towards energy efficiency and proper daylighting in both new and existing buildings. This is reflected in the emergence of new regulations concerning new buildings. In relation to existing buildings there are no regulations, but optimal daylight is a desired feature that can contribute significantly to the quality and attractiveness of newly designed spaces in the existing premises. In the case of heritage buildings, the additional conceptual challenge is to create properly daylit spaces while maintaining the character defining elements of the building, including facades and openings. Therefore, a digital workflow was developed to be integrated in the earliest schematic phase of design to ensure an equitable distribution of existing daylight in the newly created spatial units of heritage buildings. The method is based on an adapted constrained K-means clustering algorithm that works on daylight simulation data. |
| keywords |
adaptive re-use, heritage buildings, daylight optimization, clustering method, early design digital tools |
| series |
eCAADe |
| email |
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| full text |
 file.pdf (1,902,018 bytes) |
| references |
Content-type: text/plain
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| last changed |
2023/12/10 10:49 |
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