Cumincad : CUMINCAD Papers : Search Results

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	cdrf2019_159
id	cdrf2019_159
authors	Hang Zhang and Ye Huang
year	2020
title	Machine Learning Aided 2D-3D Architectural Form Finding at High Resolution
doi	https://doi.org/https://doi.org/10.1007/978-981-33-4400-6_15
source	Proceedings of the 2020 DigitalFUTURES The 2nd International Conference on Computational Design and Robotic Fabrication (CDRF 2020)
summary	In the past few years, more architects and engineers start thinking about the application of machine learning algorithms in the architectural design field such as building facades generation or floor plans generation, etc. However, due to the relatively slow development of 3D machine learning algorithms, 3D architecture form exploration through machine learning is still a difficult issue for architects. As a result, most of these applications are confined to the level of 2D. Based on the state-of-the-art 2D image generation algorithm, also the method of spatial sequence rules, this article proposes a brand-new strategy of encoding, decoding, and form generation between 2D drawings and 3D models, which we name 2D-3D Form Encoding WorkFlow. This method could provide some innovative design possibilities that generate the latent 3D forms between several different architectural styles. Benefited from the 2D network advantages and the image amplification network nested outside the benchmark network, we have significantly expanded the resolution of training results when compared with the existing form-finding algorithm and related achievements in recent years
series	cdrf
email
last changed	2022/09/29 07:51

_id	caadria2020_178
id	caadria2020_178
authors	Luo, Yue, Liang, Manchen, Gao, Letong, Zhang, Yuchun, Wang, Chenxi, Su, Xia and Huang, Weixin
year	2020
title	Investigating Site Survey Process with Protocol Analysis and an Extended FBS Framework
doi	https://doi.org/10.52842/conf.caadria.2020.2.547
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 547-556
summary	In this paper, we try to investigate architectural site survey process by conducting experiment and quantitative analysis. 17 student volunteers were asked to practice site survey for a fixed design objective. With site survey process recorded along with sketching and utterance, we adopt protocol analysis and FBS ontology, which are widely used and discussed in design process research, as the basis of our analysis. Since site survey is a preliminary stage of architectural design, it differs from actual design process in many aspects. In this case, we extended the original FBS framework by adding two extra activities- Objective Processor and Subjective Processor- to better describe site survey process.
keywords	Site Survey; Protocol Analysis; FBS Ontology; Architecture Education
series	CAADRIA
email
last changed	2022/06/07 07:51

_id	sigradi2022_298
id	sigradi2022_298
authors	Perry, Isha N.; Xue, Zhouyi; Huang, Hui-Ling; Crispe, Nikita; Vegas, Gonzalo; Swarts, Matthew; Gomez Z., Paula
year	2022
title	Human Behavior Simulations to Determine Best Strategies for Reducing COVID-19 Risk in Schools
source	Herrera, PC, Dreifuss-Serrano, C, Gómez, P, Arris-Calderon, LF, Critical Appropriations - Proceedings of the XXVI Conference of the Iberoamerican Society of Digital Graphics (SIGraDi 2022), Universidad Peruana de Ciencias Aplicadas, Lima, 7-11 November 2022 , pp. 39–50
summary	The dynamics of COVID-19 spread have been studied from an epidemiological perspective, at city, country, and global scales (Rabajante, 2020, Ma, 2020, and Giuliani et al., 2020), although after two years of the pandemic we know that viruses spread mostly through built environments. This study is part of the Spatiotemporal Modeling of COVID-19 spread in buildings research (Gomez, Hadi, and Kemenova et al., 2020 and 2021), which proposes a multidimensional model that integrates spatial configurations, temporal use of spaces, and virus characteristics into one multidimensional model. This paper presents a specific branch of this model that analyzes the behavioral parameters, such as vaccination, masking, and mRNA booster rates, and compares them to reducing room occupancy. We focused on human behavior, specifically human interactions within six feet. We utilized the multipurpose simulation software, AnyLogic, to quantify individual exposure to the virus, in the high school building by Perkins and Will. The results show how the most effective solution, reducing the occupancy rates or redesigning layouts, being the most impractical one, is as effective as 80% of the population getting a third boost.
keywords	Spatiotemporal Modeling, Behavior Analytics, COVID-19 Spread, Agent-Based Simulation, COVID-19 Prevention
series	SIGraDi
email
last changed	2023/05/16 16:55

_id	caadria2020_346
id	caadria2020_346
authors	Ortner, Frederick Peter and Huang, Jeffrey
year	2020
title	Modeling UAM Scenarios for Urban Design
doi	https://doi.org/10.52842/conf.caadria.2020.2.071
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 71-80
summary	Recent developments in unmanned aerial vehicles (UAVs), including drone delivery services and air taxis, are revolutionizing urban transport, leading to a new field of research referred to as Urban Air Mobility (UAM). While several contemporary efforts to computationally model future scenarios for UAM exist, in this paper we argue that these models tend to be narrowly conceived as air-space design and management tools and provide little information on ground-level impacts. This paper describes an ongoing effort to create UAM modelling tools useful specifically to urban designers as part of a push toward integration of urban airspace design with ground-level master-planning. Current functions permit designers to visualize drone-fleet origin-corridor-destination routes, generate a strategic model of UAM noise, and compare tradeoffs between UAM system efficiency and noise.
keywords	urban air mobility (UAM); urban design; data-driven design; simulation; parametric design
series	CAADRIA
email
last changed	2022/06/07 08:00

_id	sigradi2020_377
id	sigradi2020_377
authors	Xu, Weishun; Huang, Zixun
year	2020
title	Robotic Fabrication of Sustainable Hybrid Formwork with Clay and Foam for Concrete Casting
source	SIGraDi 2020 [Proceedings of the 24th Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Online Conference 18 - 20 November 2020, pp. 377-383
summary	This paper presents a hybrid formwork fabrication method utilizing additive manufacturing with clay on top of curved foam surfaces robotically fabricated with hot wire. The primary focus of this study is to develop a relatively efficient and highly sustainable formwork manufacturing method capable of producing geometrically complex modular concrete building components. The method leverages fluidity and recyclability of clay to produce uniquely shaped, free-form parts of the mold, and reduces overall production time by using foam for shared mold support/enclosure. A Calibration and tool path generating method based on computational modeling to integrate the two systems are also subsequently developed.
keywords	Robotic fabrication, Hybrid formwork, Mass customization, Clay printing, Foam cutting
series	SIGraDi
email
last changed	2021/07/16 11:49

_id	cdrf2019_208
id	cdrf2019_208
authors	Zhijia Chen, Weixin Huang, and Ziniu Luo
year	2020
title	embedGAN: A Method to Embed Images in GAN Latent Space
doi	https://doi.org/https://doi.org/10.1007/978-981-33-4400-6_20
source	Proceedings of the 2020 DigitalFUTURES The 2nd International Conference on Computational Design and Robotic Fabrication (CDRF 2020)
summary	GAN is an efficient generative model. By performing a latent walk in GAN, the generation result can be adjusted. However, the latent walk cannot start from a selected image. The embedGAN is proposed to embed selected images into GAN and remain the generation effect. It contains an embedded network and a generative network. Application cases of residential interior design are given in the article. With advantages of a low computing cost and short training time, embedGAN shows its potential. The embedGAN algorithm framework can be applied to various GANs.
series	cdrf
email
last changed	2022/09/29 07:51

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