TY - JOUR
T1 - Masonry screen walls
T2 - a digital framework for design generation and environmental performance optimization
AU - Vazquez, Elena
AU - Duarte, Jose
AU - Poerschke, Ute
N1 - Publisher Copyright:
© 2020 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2021
Y1 - 2021
N2 - Masonry screen walls are architectural elements made from bricks that create different patterns to provide shade and natural ventilation to buildings. This paper presents a digital framework for the design of masonry screen walls, whose performance as environmental control elements is optimized while complying with vernacular construction rules. The framework employs shape grammars for creating a generative design system based on existing construction rules. This design system is then translated into a parametric model and connected to a simulation engine that calculates daylight metrics and cooling energy loads. A genetic algorithm is then used to find a family of optimized solutions, with visual feedback being provided to facilitate the understanding of trade-offs between such solutions. The proposed framework is tested with a case study, in which design solutions are generated by manipulating selected design variables to find optimal design solutions in terms of environmental performance.
AB - Masonry screen walls are architectural elements made from bricks that create different patterns to provide shade and natural ventilation to buildings. This paper presents a digital framework for the design of masonry screen walls, whose performance as environmental control elements is optimized while complying with vernacular construction rules. The framework employs shape grammars for creating a generative design system based on existing construction rules. This design system is then translated into a parametric model and connected to a simulation engine that calculates daylight metrics and cooling energy loads. A genetic algorithm is then used to find a family of optimized solutions, with visual feedback being provided to facilitate the understanding of trade-offs between such solutions. The proposed framework is tested with a case study, in which design solutions are generated by manipulating selected design variables to find optimal design solutions in terms of environmental performance.
UR - http://www.scopus.com/inward/record.url?scp=85083552451&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85083552451&partnerID=8YFLogxK
U2 - 10.1080/00038628.2020.1749552
DO - 10.1080/00038628.2020.1749552
M3 - Article
AN - SCOPUS:85083552451
SN - 0003-8628
VL - 64
SP - 262
EP - 274
JO - Architectural Science Review
JF - Architectural Science Review
IS - 3
ER -