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	caadria2021_354
id	caadria2021_354
authors	Huang, Chenyu, Gong, Pixin, Ding, Rui, Qu, Shuyu and Yang, Xin
year	2021
title	Comprehensive analysis of the vitality of urban central activities zone based on multi-source data - Case studies of Lujiazui and other sub-districts in Shanghai CAZ
doi	https://doi.org/10.52842/conf.caadria.2021.2.549
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 2, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 549-558
summary	With the use of the concept Central Activities Zone in the Shanghai City Master Plan (2017-2035) to replace the traditional concept of Central Business District, core areas such as Shanghai Lujiazui will be given more connotations in the future construction and development. In the context of todays continuous urbanization and high-speed capital flow, how to identify the development status and vitality characteristics is a prerequisite for creating a high-quality Central Activities Zone. Taking Shanghai Lujiazui sub-district etc. as an example, the vitality value of weekday and weekend as well as 19 indexes including density of functional facilities and building morphology is quantified by obtaining multi-source big data. Meanwhile, the correlation between various indexes and the vitality characteristics of the Central Activities Zone are tried to summarize in this paper. Finally, a neural network regression model is built to bridge the design scheme and vitality values to realize the prediction of the vitality of the Central Activities Zone. The data analysis method proposed in this paper is versatile and efficient, and can be well integrated into the urban big data platform and the City Information Modeling, and provides reliable reference suggestions for the real-time evaluation of future urban construction.
keywords	multi-source big data; Central Activities Zone; Vitality; Lujiazui
series	CAADRIA
email
last changed	2022/06/07 07:50

_id	caadria2021_305
id	caadria2021_305
authors	Keshavarzi, Mohammad, Afolabi, Oladapo, Caldas, Luisa, Yang, Allen Y. and Zakhor, Avideh
year	2021
title	GenScan: A Generative Method for Populating Parametric 3D Scan Datasets
doi	https://doi.org/10.52842/conf.caadria.2021.1.091
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 1, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 91-100
summary	The availability of rich 3D datasets corresponding to the geometrical complexity of the built environments is considered an ongoing challenge for 3D deep learning methodologies. To address this challenge, we introduce GenScan, a generative system that populates synthetic 3D scan datasets in a parametric fashion. The system takes an existing captured 3D scan as an input and outputs alternative variations of the building layout including walls, doors, and furniture with corresponding textures. GenScan is fully automated system that can also be manually controlled by a user through an assigned user interface. Our proposed system utilizes a combination of a hybrid deep neural network and a parametrizer module to extract and transform elements of a given 3D scan. GenScan takes advantage of style transfer techniques to generate new textures for the generated scenes. We believe our system would facilitate data augmentation to expand the currently limited 3D geometry datasets commonly used in 3D computer vision, generative design and general 3D deep learning tasks.
keywords	Computational Geometry; Generative Modeling; 3D Manipulation; Texture Synthesis
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	caadria2021_143
id	caadria2021_143
authors	Song, Yang, Koeck, Richard and Luo, Shan
year	2021
title	AR Digi-Component - AR-assisted,real-time,immersive design and robotic fabrication workflow for parametric architectural structures
doi	https://doi.org/10.52842/conf.caadria.2021.2.253
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 2, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 253-262
summary	This research project, entitled AR Digi-Component, tries to digitalize the traditional architectural components and combines Augmented Reality (AR) technologies to explore new possibilities for architectural design and assembly. AR technology and Digitalize components will help to achieve a real-time immersive design and an AR-assisted robotic fabrication process through the augmented environments. As part of the AR Digi-Component project, we created an experimental design prototype in which designers gestures are being identified in AR real-time immersive design process, and a fabrication prototype in which traditional 2D drawings are being replaced by 3D on-site holographic guidance, followed by an assembly process in which robotic operations are being controlled by humans within an AR simulation to enhance the assembly efficiency and safety. In this paper, we are sharing the preliminary research results of such AR-assisted tests, for which we used a UR10 Robotic arm in combination with Microsoft HoloLens as well as in terms of software Rhino, HAL Robotics, FURobot, PX Simulate, and Fologram plugin in Grasshopper, to demonstrate new kind of applications and workflow of AR technology for real-time, immersive design and robotic fabrication.
keywords	Augmented Reality; immersive design; holographic assembly instruction; robotic fabrication; real-time interaction
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	caadria2021_064
id	caadria2021_064
authors	Yang, Chunxia, Liu, Mengxuan, Zhan, Ming, Lyu, Chengzhe and Fan, Zhaoxiang
year	2021
title	Research on the Influence of Microclimate on Recreation Behavior in Urban Waterfront Public Space - Based on Multi-agent Behavior Simulation
doi	https://doi.org/10.52842/conf.caadria.2021.2.417
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 2, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 417-426
summary	Microclimate is one of the important components of the city environment. Previous researches on public space focused on the influence of spatial forms on user behavior, while ignoring the microclimate elements. This makes it difficult to be authentic of further recreational behavior simulation. The study puts forward a new path to study the influence of microclimate on recreational behavior. Taking the waterfront public space as an example, through the combination of field investigation and microclimate simulation, the influence of wind, temperature, and sunshine environment on residents recreational is explored, and the influence will be merged into the recreational behavior simulation. In the process of behavior simulation, the microclimate environment classification evaluation map is used. The study committed to achieve a higher degree of adaption between behavior simulation results and actual conditions. The study introduced microclimate influence factors on the basis of the influence of urban spatial form and service facility elements on behavior activities in the past. Based on that, we optimize the simulation method of urban public space recreational behavior, and improve the accuracy of space diagnosis through showing the impact of microclimate on the behavior of people in the space more objectively and intuitively.
keywords	Behavior simulation; Microclimate; Waterfront public space
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	caadria2021_075
id	caadria2021_075
authors	Yang, Chunxia, Lyu, Chengzhe, Yao, Ziying and Liu, Mengxuan
year	2021
title	Study on the Differences of Day and Night Behavior in Urban Waterfront Public Space Based on Multi-agent Behavior Simulation
doi	https://doi.org/10.52842/conf.caadria.2021.2.559
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 2, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 559-568
summary	In the twenty-four hour city era, how to optimize public spaces based on night behavior demands to promote full-time use has become a significant issue of urban design. Taking Shanghai North Bund as an example, the study collects data through site survey and questionnaire including environment elements, users attribute and behaviors. Next, the study sets up the simulation environment and translate the interaction of space and behavior into model language. Then, by setting up agent particles, running and fitting, the study obtains an ideal model. Finally, through sub-simulation and analysis, the study quantitatively explores the interaction mechanism between the physical environment and behavior from three levels of different spaces, different groups of people and different light conditions. The study finds that the differences of day and night behavior are produced under the combined effect of changes in attractiveness of environmental elements and changes in users demands and preferences. Compared with adults, the behaviors of elderly people and children show more obvious differences between day and night, and are more susceptible to space lighting, ground conditions and operating hours of facilities. Furthermore, the same kind of environment element will further affect users behavior in the night under different light conditions.
keywords	Self-Organization Behavior; Behavior Differences; Day and Night; Multi-Agent Behavior Simulation; Waterfront Public Space
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	caadria2021_056
id	caadria2021_056
authors	Yang, Chunxia, Xu, Chen, Lyu, Chengzhe and Zhan, Ming
year	2021
title	Differences between Behavior Simulation and Space Syntax in the Study of Urban Texture - Considering the Street System and Property Right Plots
doi	https://doi.org/10.52842/conf.caadria.2021.2.367
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 2, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 367-376
summary	The study applies two methods of behavioral simulation and space syntax to study waterfront accessibility from the urban texture levels of street system and property plot, exploring two methods differences, advantages and disadvantages in terms of simulation principle, fitting precision, and calculating results. The North Bund area of Shanghai is selected as the research sample. And the software of AnyLogic and Depthmap which are mostly used in the fields of behavior simulation and space syntax are used. The results are:Behavior simulation can visually reflect the usage condition of specific spaces through micro behavior data such as pedestrian flow, walking time, etc. But it has limitation in precision and stability of calculation, and the model need much time to construct and run if the site is large. Space syntax is more mature in accessibility analysis with high precise indexes such as choice and integration degree. However, the fitting precision between the output and real situation is lower than behavior simulation, and it cant directly evaluate the capacity and service level of the urban space. In general, both behavior simulation and space syntax can be applied to urban space research and have their own advantages and disadvantages, and complementary in between.
keywords	behavior simulation; space syntax; method comparison; urban texture; waterfront
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	acadia21_182
id	acadia21_182
authors	Yang, Qi; Cruz-Garza, Jesus G.; Kalantari, Saleh
year	2021
title	MindSculpt
doi	https://doi.org/10.52842/conf.acadia.2021.182
source	ACADIA 2021: Realignments: Toward Critical Computation [Proceedings of the 41st Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-986-08056-7]. Online and Global. 3-6 November 2021. edited by B. Bogosian, K. Dörfler, B. Farahi, J. Garcia del Castillo y López, J. Grant, V. Noel, S. Parascho, and J. Scott. 182-193.
summary	MindSculpt enables users to generate a wide range of hybrid geometries in Grasshopper in real-time simply by thinking about those geometries. This design tool combines a non-invasive brain–computer interface (BCI) with the parametric design platform Grasshopper, creating an intuitive design workflow that shortens the latency between ideation and implementation compared to traditional computer-aided design tools based on mouse-and-keyboard paradigms. The project arises from transdisciplinary research between neuroscience and architecture, with the goal of building a cyber-human collaborative tool that is capable of leveraging the complex and fluid nature of thinking in the design process. MindSculpt applies a supervised machine-learning approach, based on the support vector machine model (SVM), to identify patterns of brain-waves that occur in EEG data when participants mentally rotate four different solid geometries. The researchers tested MindSculpt with participants who had no prior experience in design, and found that the tool was enjoyable to use and could contribute to design ideation and artistic endeavors.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	caadria2021_080
id	caadria2021_080
authors	Yang, Xuyou and Xu, Weishun
year	2021
title	A Tool for Searching Active Bending Bamboo Strips in Construction via Deep Learning
doi	https://doi.org/10.52842/conf.caadria.2021.1.463
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 1, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 463-472
summary	As an alternative material for construction, the structural use of bamboo in architecture is commonly associated with active bending. However, as natural material, the deformation of unprocessed bamboo strips is affected by the distribution of nodes, whose impact on deformation is difficult to precisely programme for each individual case and thus often causes discrepancies between generic digital simulation and construction. This research proposes a tool for searching active bending bamboo strips via deep leaning based on a multi-task neural network. The tool is able to predict both the number and locations of nodes suggested on bamboo strips according to a target curve as tool input. By approximating the prediction, users can find a strip that is most likely to deform into the desired geometry.
keywords	neural network; active bending; neural architecture search (NAS); bamboo; material behaviour
series	CAADRIA
email
last changed	2022/06/07 07:57

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