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	ecaade2023_377
id	ecaade2023_377
authors	Zhang, Qiyan, Li, Biao, Li, Hongjian and Tang, Peng
year	2023
title	Towards Integration and Hybridization in Urban Generation: An extendable urban generative system for better natural ventilation
doi	https://doi.org/10.52842/conf.ecaade.2023.2.379
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 379–388
summary	The integration of environmental context and morphological design reflects the complexity and synthesis in the urban and architectural design process. Especially considering sustainability, synthesizing climate impact at the early design stage is a more effective way to achieve improved environmental performance. This paper presents an extendable urban generation framework that can integrate multiple environmental information through the field model and interactively generate urban massing with optimized outdoor natural ventilation. The application and implementation of the framework are shown with a case study of a multi-objective optimization model that integrates wind field and frontal area index (FAI). The proposed system supports expansion to the different urban scales and other design applications, inspiring the promising paths of the more hybrid, integrated, and extendable digital framework and the potential of performance-based design optimization toward a sustainable urban future.
keywords	Generative methods, Wind environment evaluation, Performance-driven design, Urban massing generation, Field model
series	eCAADe
email
last changed	2023/12/10 10:49

_id	acadia23_v2_384
id	acadia23_v2_384
authors	Vakhshouri, Pouria; Luo, Jingyu; Su, Shuoxuan; Tang, Haohan; Wang, Bentian; Faircloth, Billie; King, Nathan; Stuart-Smith, Robert
year	2023
title	Ceramic Forest: Robotic Die-Extrusion Variable Forming for Architectural Ceramics
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 2: Proceedings of the 43rd Annual Conference for the Association for Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9891764-0-3]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 384-395.
summary	Extrusion is a well-established industrial production technique for making ceramic clay parts in high-volume, mass-production lines, using an auger to push the clay out from a reservoir through a die profile onto a conveyor belt. While the method enables elaborately profiled extrusions, the extrusion and die allow for no degree of variability across the production of several parts. Ceramic Forest explores how robotic fabrication and clay extrusion techniques can be integrated into a variable production process by mounting an extrusion die and extrusion system on an industrial robot end-of-arm tool. Experiments exploring fabrication parameters including the clay body water content, die geometry, air pressure, and a robot's motion trajectory were conducted, and demonstrated the merits of the approach. The fabrication method is also demonstrated through the production of a series of geometrically distinctive parts that are utilized in a full-scale, assembled, façade screen prototype. A computational design method was also developed for an architectural façade screen that generates design outcomes that align with the research’s established fabrication constraints. Together, these developments demonstrate an approach to die-formed ceramic extrusion and an aligned computational design tool for its use on architectural façade screens.
series	ACADIA
type	paper
email
last changed	2024/12/20 09:12

_id	caadria2023_253
id	caadria2023_253
authors	Li, Jinze and Tang, Peng
year	2023
title	Multisource Analysis of Big Data on Street Vitality Using GIS Mapping and Deep Learning: A Case Study of Ding Shu, China
doi	https://doi.org/10.52842/conf.caadria.2023.1.565
source	Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 565–574
summary	Urban vitality is the driving force behind sustainable urban development. As the most frequently used public space in cities, the enhancement of street vitality is of great significance for improving human-centred habitats. Based on multi-source big data, this study uses spatial and statistical analysis methods to explore the impact factors of street vitality. Through the quantitative evaluation of these factors, we propose corresponding strategies to enhance the vitality of the street. Firstly, the spatial elements of streets are extracted using deep learning algorithm based on the acquired street view images. Further, the impact factors of street vitality are demonstrated using statistical methods by combining multi-source data. We established an evaluation system based on the impact factors of street vitality, which can quantify and predict street vitality. In this way, we can propose vitality enhancement strategy for the street with lower vitality in a targeted approach. The feasibility of the process is demonstrated by using Ding Shu as an example. This study provides a basic framework for a people-centred approach to enhance street vitality based on big data. It also contributes to causal inference in urban problems.
keywords	Multi-source data, street vitality, deep learning, spatial analysis, statistical analysis, causal inference, people-centred city
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	caadria2023_358
id	caadria2023_358
authors	Song, Zhehao, Tang, Peng and Song, Yacheng
year	2023
title	Digital Application of Typo-morphology in the Conservation and Renewal of Historic Areas
doi	https://doi.org/10.52842/conf.caadria.2023.1.545
source	Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 545–554
summary	The conservation and renewal of historic areas are facing many complex and scattered problems, which are not suitable to be completed by a unified method. Designers tried to use the typo-morphology to analyse the morphology of each micro unit to carry out targeted conservation and renewal actions. However, any adjustment of spatial structure may affect the morphological characteristics of the whole block and each micro unit, designers need an efficient method to control the dynamic changes of the block in real-time. Based on the hierarchical structure of typo-morphology, a digital model of the historic areas was built. This model can be perfected as a morphological analysis tool and analyse the block's spatial morphological evolution during its conservation and renewal process. In the renewal design work of Hehuatang historical and cultural block in Nanjing, this method helps designers test each strategy's rationality and find a more scientific scheme to guide the further detailed design. The involvement of digital methods enables typo-morphology to assist design work more accurately and promote the working mode to gradually change from "experience-based artificial induction" to "data-based pattern extraction".
keywords	historic area, conservation and renewal, typo-morphology, hierarchical structure, digital model
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	caadria2023_359
id	caadria2023_359
authors	Wang, Xiao, Tang, Peng and Cai, Chenyi
year	2023
title	Traditional Chinese Village Morphological Feature Extraction and Cluster Analysis Based on Multi-source Data and Machine Learning
doi	https://doi.org/10.52842/conf.caadria.2023.1.179
source	Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 179–188
summary	This study of traditional village morphology provides a possible entry point for understanding the growth patterns of settlements for sustainable development. This study proposes a hybrid data-driven approach to support quantitative morphological descriptions and to further morphology-related studies using open-source map data and deep learning approaches. We construct a dataset of 6819 traditional villages on the Chinese official list with geometrical, geographic and related no-material information. The images containing village buildings combined with roads or other environments are represented in binary to explore the integrated influence of these elements. The neural network is implemented to quantify the morphological features into feature vectors. After dimension reduction, cluster analysis is conducted by calculating the distance between the feature vectors to reveal five main types of Chinese traditional village patterns. The proposed method considers their overall spatial form and other factors such as size, transportation, graphical structure, and density. At the same time, it explores a framework using machine learning in the conservation and renewal work. And it also shows the possibility of data-driven methods for design and decision making.
keywords	Cluster analysis, traditional village, morphology, multi-source data, machine learning, rural development
series	CAADRIA
email
last changed	2023/06/15 23:14

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