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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	acadia19_392
id	acadia19_392
authors	Steinfeld, Kyle
year	2019
title	GAN Loci
doi	https://doi.org/10.52842/conf.acadia.2019.392
source	ACADIA 19:UBIQUITY AND AUTONOMY [Proceedings of the 39th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-59179-7] (The University of Texas at Austin School of Architecture, Austin, Texas 21-26 October, 2019) pp. 392-403
summary	This project applies techniques in machine learning, specifically generative adversarial networks (or GANs), to produce synthetic images intended to capture the predominant visual properties of urban places. We propose that imaging cities in this manner represents the first computational approach to documenting the Genius Loci of a city (Norberg-Schulz, 1980), which is understood to include those forms, textures, colors, and qualities of light that exemplify a particular urban location and that set it apart from similar places. Presented here are methods for the collection of urban image data, for the necessary processing and formatting of this data, and for the training of two known computational statistical models (StyleGAN (Karras et al., 2018) and Pix2Pix (Isola et al., 2016)) that identify visual patterns distinct to a given site and that reproduce these patterns to generate new images. These methods have been applied to image nine distinct urban contexts across six cities in the US and Europe, the results of which are presented here. While the product of this work is not a tool for the design of cities or building forms, but rather a method for the synthetic imaging of existing places, we nevertheless seek to situate the work in terms of computer-assisted design (CAD). In this regard, the project is demonstrative of a new approach to CAD tools. In contrast with existing tools that seek to capture the explicit intention of their user (Aish, Glynn, Sheil 2017), in applying computational statistical methods to the production of images that speak to the implicit qualities that constitute a place, this project demonstrates the unique advantages offered by such methods in capturing and expressing the tacit.
series	ACADIA
type	normal paper
email
last changed	2022/06/07 07:56

_id	acadia17_620
id	acadia17_620
authors	Tsigkari, Martha; Olsson, Jens; Malm, Henrik; Psarras, Stamatios; Aish, Francis
year	2017
title	The Computational Challenges of a Mega Space Frame: Shaping the Envelope of New Mexico City Airport
doi	https://doi.org/10.52842/conf.acadia.2017.620
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. 620- 629
summary	The modeling of the envelope and space frame for the new Mexico City Airport was a massive computational task, demanding the development of numerous new methods, tools and processes to deal with its complexity and scale. The shape of the envelope was created through form finding, leading to an all-encompassing lightweight shell with internal spans reaching 130 m. This paper will discuss the challenges faced and the methods used to develop a visually continuous and smooth space-frame model and envelope, while simultaneously complying with very strict spatial and programmatic constraints and structural optimisation criteria. It will further explain how dynamic relaxation was complemented with bespoke mechanisms for mesh manipulation, interfacing and mesh smoothing to fine-tune the final form.
keywords	design methods; information processing; simulation & optimization; generative system; form finding
series	ACADIA
email
last changed	2022/06/07 07:57

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