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Architectural Design Exploration Using Generative Design: Framework Development and Case Study of a Residential Block

Auteur(s):

Médium: article de revue
Langue(s): anglais
Publié dans: Buildings, , n. 11, v. 10
Page(s): 201
DOI: 10.3390/buildings10110201
Abstrait:

The use of generative design has been suggested to be a novel approach that allows designers to take advantage of computers’ computational capabilities in the exploration of design alternatives. However, the field is still sparsely explored. Therefore, this study aimed to investigate the potential use of generative design in an architectural design context. A framework was iteratively developed alongside a prototype, which was eventually demonstrated in a case study to evaluate its applicability. The development of a residential block in the northern parts of Sweden served as the case. The findings of this study further highlight the potential of generative design and its promise in an architectural context. Compared to previous studies, the presented framework is open to other generative algorithms than mainly genetic algorithms and other evaluation models than, for instance, energy performance models. The paper also presents a general technical view on the functionality of the generative design system, as well as elaborating on how to explore the solution space in a top-down fashion. This paper moves the field of generative design further by presenting a generic framework for architectural design exploration. Future research needs to focus on detailing how generative design should be applied and when in the design process.

Copyright: © 2020 by the authors; licensee MDPI, Basel, Switzerland.
License:

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

  • Informations
    sur cette fiche
  • Reference-ID
    10475542
  • Publié(e) le:
    13.11.2020
  • Modifié(e) le:
    02.06.2021
 
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