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CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

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_id	sigradi2021_189
id	sigradi2021_189
authors	Paiva Ponzio, Angelica, Giudoux Gonzaga, Mario, Pires de Castro Aguiar Vale, Marina, Bruscato, Underléa Miotto and Mog, William
year	2021
title	Parametric Design Learning Strategies in the Context of Architectural Design Remote Teaching
source	Gomez, P and Braida, F (eds.), Designing Possibilities - Proceedings of the XXV International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2021), Online, 8 - 12 November 2021, pp. 1077–1088
summary	This article aims to demonstrate how a theoretical-didactic model and its respective teaching strategies for algorithmic-parametric logic can act as potential elements of innovation in the architectural design process. Based on the theories of parametric design thinking by Oxman (2017) and the studies by Woodbury (2010) and Romcy (2017), such strategies are based on the principle that algorithmic logic can be understood, in certain circumstances, as a procedural framework and not just an instrumental one. It will also be discussed how the situation of remote learning in the face of the COVID-19 crisis brought about the use of virtual teaching tools as an increment of the learning process.
keywords	Architectural teaching, computational design, parametric design thinking, design process, algorithmic design
series	SIGraDi
email
last changed	2022/05/23 12:11

_id	acadia17_28
id	acadia17_28
authors	Aguiar, Rita; Cardoso, Carmo; Leit?o,António
year	2017
title	Algorithmic Design and Analysis Fusing Disciplines
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 28-37
doi	https://doi.org/10.52842/conf.acadia.2017.028
summary	In the past, there has been a rapid evolution in computational tools to represent and analyze architectural designs. Analysis tools can be used in all stages of the design process, but they are often only used in the final stages, where it might be too late to impact the design. This is due to the considerable time and effort typically needed to produce the analytical models required by the analysis tools. A possible solution would be to convert the digital architectural models into analytical ones, but unfortunately, this often results in errors and frequently the analytical models need to be built almost from scratch. These issues discourage architects from doing a performance-oriented exploration of their designs in the early stages of a project. To overcome these issues, we propose Algorithmic Design and Analysis, a method for analysis that is based on adapting and extending an algorithmic-based design representation so that the modeling operations can generate the elements of the analytical model containing solely the information required by the analysis tool. Using this method, the same algorithm that produces the digital architectural model can also automatically generate analytical models for different types of analysis. Using the proposed method, there is no information loss and architects do not need additional work to perform the analysis. This encourages architects to explore several design alternatives while taking into account the design’s performance. Moreover, when architects know the set of design variations they wish to analyze beforehand, they can easily automate the analysis process.
keywords	design methods; information processing; simulation & optimization; BIM; generative system
series	ACADIA
email
last changed	2022/06/07 07:54

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