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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Hits 1 to 9 of 9

_id caadria2020_047
id caadria2020_047
authors Lee, Han Jie, Lin, Zhuoli, Zhang, Ji and Janssen, Patrick
year 2020
title Irradiance Mappinig for Large Scale City Models
doi https://doi.org/10.52842/conf.caadria.2020.1.803
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 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 803-812
summary This paper reports on the development of a geocomputational simulation workflow for the irradiance mapping of large scale city models. A fully automated workflow is presented, for importing CityGML city models, generating the simulation input models, executing the simulations, and aggregating the results. In order to speed up the overall processing time, the workflow uses parallel processing across multiple computers and multiple cores. Two case studies are presented, for Singapore and for Rotterdam.
keywords Integrated irradiance simulation; Solar potential assessment ; Large scale urban 3D model; Houdini; Radiance
series CAADRIA
email
last changed 2022/06/07 07:51

_id ecaade2020_143
id ecaade2020_143
authors Ilyas, Sobia, Wang, Xinyue, Li, Wenting, Zhang, Zhuoqun, Wang, Tsung-Hsien and Peng, Chengzhi
year 2020
title Towards an Interactionist Model of Cognizant Architecture - A sentient maze built with swarm intelligence
doi https://doi.org/10.52842/conf.ecaade.2020.2.201
source Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 201-208
summary Cognizant Architecture is a term used to define sentient and smart structures broadly. In this paper, an 'Interactionist' model of cognizant architecture is proposed as a method of investigating the development process by inverting the conventional concept of maze design. The proposed 'Cognizant Maze' aims to achieve user-architecture micro-interactions through delighting the users, presenting a physical activity equally attractive to kids and adults alike, and activating mind-enticing visual effects. Like many previous innovations, nature is what inspires us in the maze-making process. In modelling the cognizant maze, we develop the concept and workflow of prototyping a form of swarm intelligence. We are particularly interested in exploring how simulated behaviours of swarm intelligence can be manifested in a maze environment for micro-interactions to take place. Combining parametric modelling and Arduino-based physical computing, our current interactive prototyping shows how the maze and its users can 'think, act and play' with each other, hence achieving an interactionist model of cognizant architecture. We reflect that the lessons learned from the Cognizant Maze experiment may lead to further development of cognizant architecture as a propagation of swarm intelligence through multi-layered micro-interactions.
keywords swarm intelligence; maze design; Micro-interactions; interactive prototyping; cognizant architecture
series eCAADe
email
last changed 2022/06/07 07:50

_id ecaade2020_235
id ecaade2020_235
authors Li, Bin, Guo, Weihong, schnabel, Marc Aurel and Zhang, Ziqi
year 2020
title Virtual Simulation of New Residential Buildings in Lingnan Using Vernacular Wisdom
doi https://doi.org/10.52842/conf.ecaade.2020.1.269
source Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 1, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 269-278
summary Every new idea has some sort of precedent or echoes from the past. It is the same for the new residential buildings in Lingnan, China. In Lingnan, the vernacular knowledge of building design has been established over thousands of years. Whether it is suitable for use today should be verified. In this research, virtual simulations are employed to arrive at an overall conclusion. Virtual simulations based on PHOENICS, ENVI_MET, CadnaA, and Ecotect software were separately used for analysing the case of new residential buildings located in Lingnan. The study analysed the wind, thermal, acoustic, and light environments, which are four aspects of these new residential buildings. According to the results of our research, the paper discussed ways to amend and improve the new residential buildings that sit within the overall spirit of the vernacular knowledge of Lingnan; thus, it helps to put the traditional knowledge into the current context. The vernacular knowledge from XS to XL scale contexts, such as Feng-shui, was verified as being suitable for use in Lingnan today.
keywords Virtual simulation; Vernacular wisdom; Residential building; Lingnan; Feng-shui
series eCAADe
email
last changed 2022/06/07 07:52

_id ecaade2020_113
id ecaade2020_113
authors Li, Yunqin, Yabuki, Nobuyoshi, Fukuda, Tomohiro and Zhang, Jiaxin
year 2020
title A big data evaluation of urban street walkability using deep learning and environmental sensors - a case study around Osaka University Suita campus
doi https://doi.org/10.52842/conf.ecaade.2020.2.319
source Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 319-328
summary Although it is widely known that the walkability of urban street plays a vital role in promoting street quality and public health, there is still no consensus on how to measure it quantitatively and comprehensively. Recent emerging deep learning and sensor network has revealed the possibility to overcome the previous limit, thus bringing forward a research paradigm shift. Taking this advantage, this study explores a new approach for urban street walkability measurement. In the experimental study, we capture Street View Picture, traffic flow data, and environmental sensor data covering streets within Osaka University and conduct both physical and perceived walkability evaluation. The result indicates that the street walkability of the campus is significantly higher than that of municipal, and the streets close to large service facilities have better walkability, while others receive lower scores. The difference between physical and perceived walkability indicates the feasibility and limitation of the auto-calculation method.
keywords walkability; WalkScore; deep learning; Street view picture; environmental sensor
series eCAADe
email
last changed 2022/06/07 07:51

_id ecaade2020_138
id ecaade2020_138
authors Patel, Sayjel Vijay, Tchakerian, Raffi, Lemos Morais, Renata, Zhang, Jie and Cropper, Simon
year 2020
title The Emoting City - Designing feeling and artificial empathy in mediated environments
doi https://doi.org/10.52842/conf.ecaade.2020.2.261
source Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 261-270
summary This paper presents a theoretical blueprint for implementing artificial empathy into the built environment. Transdisciplinary design principles have oriented the creation of a new model for autonomous environments integrating psychology, architecture, digital media, affective computing and interactive UX design. 'The Emoting City', an interactive installation presented at the 2019 Shenzhen Bi-City Biennale of Urbanism/Architecture, is presented as a first step to explore how to engage AI-driven sensing by integrating human perception, cognition and behaviour in a real-world scenario. The approach described encompasses two main elements: embedded cyberception and responsive surfaces. Its human-AI interface enables new modes of blended interaction that are conducive to self-empathy and insight. It brings forth a new proposition for the development of sensing systems that go beyond social robotics into the field of artificial empathy. The installation innovates in the design of seamless affective computing that combines 'alloplastic' and 'autoplastic' architectures. We believe that our research signals the emergence of a potential revolution in responsive environments, offering a glimpse into the possibility of designing intelligent spaces with the ability to sense, inform and respond to human emotional states in ways that promote personal, cultural and social evolution.
keywords Artificial Intelligence; Responsive Architecture; Affective Computation; Human-AI Interfaces; Artificial Empathy
series eCAADe
email
last changed 2022/06/07 07:59

_id ecaade2020_310
id ecaade2020_310
authors Schulz, Daniel, Degkwitz, Till, Luft, Jonas, Zhang, Yuxiang, Stradtmann, Nicola and Noennig, Jörg Rainer
year 2020
title Cockpit Social Infrastructure - Developing a planning support system in Hamburg
doi https://doi.org/10.52842/conf.ecaade.2020.2.341
source Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 341-350
summary In a complex urban scenario with a growing number of stakeholders and high dynamic developments, decision makers rely heavily on public data to make informed decisions. Often though, the available data is heterogeneous and stems from incomplete or inconsistent sources. The planning process, especially the definition of planning goals/needs, is often delayed due to time-consuming data procurement and assessment. This paper describes the development of the Cockpit Social Infrastructure (CoSI), a GIS-based planning support system that serves as an easy-access interface between Hamburgs Urban Data Platform GIS data infrastructure and the municipal planners for social infrastructure, bridging the gap between disciplines and facilitating communication and decision-making between stakeholders. CoSI takes full advantage of the UDP infrastructure and aims to introduce a city-wide tool for planners to conduct holistic, evidence-based planning, grounded in the latest and regularly updated statistical data. The paper outlines the project genesis and underlying technical and administrative structures.
keywords Planning Support System; GIS; Social Infrastructure; Urban Data
series eCAADe
email
last changed 2022/06/07 07:57

_id ecaade2020_258
id ecaade2020_258
authors Zhang, Ran, Waibel, Christoph and Wortmann, Thomas
year 2020
title Aerodynamic Shape Optimization for High-Rise Conceptual Design - Integrating and validating parametric design, (fast) fluid dynamics, structural analysis and optimization
doi https://doi.org/10.52842/conf.ecaade.2020.1.037
source Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 1, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 37-45
summary Using an integrated workflow with parametric design, Computational Fluid Dynamic (CFD) and Fast Fluid Dynamic (FFD) simulations, structural analysis and optimization, this paper evaluates the relative suitability of CFD and FFD simulations for Aerodynamic Shape Optimization (ASO). Specifically, it applies RBFOpt, a model-based optimization algorithm, to the ASO of a supertall high-rise. The paper evaluates the accuracy of the CFD and FDD simulations relative to a slower, more exact CFD simulation, and the performance of the model-based optimization algorithm relative to CMA-ES, an evolutionary algorithm. We conclude that FFD is useful for relative comparisons, such as for optimization, but less accurate than CFD in terms of absolute quantities. Although results tend to be similar, CMA-ES performs less well than RBFOpt for both large and small numbers of simulations, and for both CFD and FFD. RBFOpt with FFD emerges as the most suitable method for conceptual design, as it is much faster and only slightly less effective than RBFOpt with CFD.
keywords Aerodynamic Shape Optimization; Computational Fluid Dynamics (CFD); Fast Fluid Dynamics (FFD); Model-based Optimization; High-rise Conceptual Design
series eCAADe
email
last changed 2022/06/07 07:57

_id ecaade2020_298
id ecaade2020_298
authors Zhang, Ye, Zhang, Kun, Chen, KaiDi and Xu, Zhen
year 2020
title Source Material Oriented Computational Design and Robotic Construction
doi https://doi.org/10.52842/conf.ecaade.2020.2.443
source Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 443-452
summary The disconnection between architectural form and materiality has become an important issue in recent years. Architectural form is mainly decided by the designer, while material data, for example, the natural shape of source materials, is often treated as an afterthought which doesn't factor in decision-making directly. This study proposes a new, real-time scanning-modeling system for obtaining material information, and incorporating the data into a continuous digital chain of computational design and robotic construction. After collecting and visualizing the data, the calculation portion of the chain processes the selection of source materials and generates architectural geometry based on both human-designed rules and various shapes of materials. Finally, at the action end of the chain, an industry robot is used to fabricate the design. End-effector is designed for tightly gripping the irregular source materials. Scripts is written in Grasshopper for positioning the components and assemble them into configurations. This study also shows a pavilion developing with the continuous digital chain
keywords scanning-modeling system; source material information; computational design; robotic construction
series eCAADe
email
last changed 2022/06/07 07:57

_id acadia20_238
id acadia20_238
authors Zhang, Hang
year 2020
title Text-to-Form
doi https://doi.org/10.52842/conf.acadia.2020.1.238
source ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 238-247.
summary Traditionally, architects express their thoughts on the design of 3D architectural forms via perspective renderings and standardized 2D drawings. However, as architectural design is always multidimensional and intricate, it is difficult to make others understand the design intention, concrete form, and even spatial layout through simple language descriptions. Benefiting from the fast development of machine learning, especially natural language processing and convolutional neural networks, this paper proposes a Linguistics-based Architectural Form Generative Model (LAFGM) that could be trained to make 3D architectural form predictions based simply on language input. Several related works exist that focus on learning text-to-image generation, while others have taken a further step by generating simple shapes from the descriptions. However, the text parsing and output of these works still remain either at the 2D stage or confined to a single geometry. On the basis of these works, this paper used both Stanford Scene Graph Parser (Sebastian et al. 2015) and graph convolutional networks (Kipf and Welling 2016) to compile the analytic semantic structure for the input texts, then generated the 3D architectural form expressed by the language descriptions, which is also aided by several optimization algorithms. To a certain extent, the training results approached the 3D form intended in the textual description, not only indicating the tremendous potential of LAFGM from linguistic input to 3D architectural form, but also innovating design expression and communication regarding 3D spatial information.
series ACADIA
type paper
email
last changed 2023/10/22 12:06

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