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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	ecaade2022_367
id	ecaade2022_367
authors	Doumpioti, Christina and Huang, Jeffrey
year	2022
title	Field Condition - Environmental sensibility of spatial configurations with the use of machine intelligence
source	Pak, B, Wurzer, G and Stouffs, R (eds.), Co-creating the Future: Inclusion in and through Design - Proceedings of the 40th Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2022) - Volume 2, Ghent, 13-16 September 2022, pp. 67–74
doi	https://doi.org/10.52842/conf.ecaade.2022.2.067
summary	Within computational environmental design (CED), different Machine Learning (ML) models are gaining ground. They aim for time efficiency by automating simulation and speeding up environmental performance feedback. This study suggests an approach that enhances not the optimization but the generative aspect of environmentally driven ML processes in architectural design. We follow Stan Allen's (2009) idea of 'field conditions' as a bottom-up phenomenon according to which form and space emerge from local invisible and dynamic connections. By employing parametric modeling, environmental analysis data, and conditional Generative Adversarial Networks [cGAN] we introduce a generative approach in design that reverses the typical design process of going from formal interpretation to analysis and encourages the emergence of spatial configurations with embedded environmental intelligence. We call it Intensive-driven Environmental Design Computation [IEDC], and we employ it in a case study on a residential building typology encountered in the Mediterranean. The paper describes the process, emphasizing dataset preparation as the stage where the logic of field conditions is established. The proposed research differentiates from cGAN models that offer automatic environmental performance predictions to one that spatial predictions stem from dynamic fields.
keywords	Field Architecture, Environmental Design, Generative Design, Machine Learning, Residential Typologies
series	eCAADe
email
last changed	2024/04/22 07:10

_id	ecaade2022_302
id	ecaade2022_302
authors	Lu, Xin, Meng, Zeyuan, Rodriguez, Alvaro Lopez and Pantic, Igor
year	2022
title	Reusable Augmented Concrete Casting System - Accessible method for formwork manufacturing through holographic guidance
source	Pak, B, Wurzer, G and Stouffs, R (eds.), Co-creating the Future: Inclusion in and through Design - Proceedings of the 40th Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2022) - Volume 1, Ghent, 13-16 September 2022, pp. 371–380
doi	https://doi.org/10.52842/conf.ecaade.2022.1.371
summary	Reinforced concrete has been one of the essential materials for modern architecture for the last hundred years. Its use is entirely global, having been adopted by all cultures and styles since its invention in the late 19th century. Although its value is excellent due to its low cost, durability and adaptability, its environmental impact is significant, being, in fact, one of the most polluting industries in the world (Babor et al. 2009). This experimental project will research a more sustainable use of concrete, exploring a new form of reusable concrete formwork that will ideally reduce the CO2 footprint by removing wood waste in the casting process and replacing it with adaptable metal components. The modular part-based system for the concrete casting also attempts to simplify one of the current complexities for concrete construction, the Skilled-Labour shortage. (Yusoff et al. 2021). To mitigate this problem, the project also proposes using an Augmented Assembly logic for the casting parts to guide the ensemble and dismantle the formwork through an optimised algorithmic logic. The use of Augmented Reality as a replacement for traditional paper instructions will facilitate access to more workers to this construction art and potentially improve access to optimised use of concrete in developing communities with restricted building technological resources.
keywords	Mixed Reality, Distributed Manufacturing, Augmented Manufacturing, Sustainability, Computational Design, Concrete Casting
series	eCAADe
email
last changed	2024/04/22 07:10

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