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	caadria2019_329
id	caadria2019_329
authors	Zhao, Yao, Zhu, Weiran and Yuan, Philip F.
year	2019
title	From Acoustic Data Perception to Visualization Design
doi	https://doi.org/10.52842/conf.caadria.2019.1.393
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 1, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 393-402
summary	This research project is based on the research results from the "Acoustic Visualization Group" of Digital FUTURES Summer Workshop in Shanghai, 2018. In this workshop, students use sound data acquisition sound collection equipment to collect sound information in the space and transform it into digital data. After analyzing the data, they present it as a visible form and design the sound interaction device based on the results. This study combines the media art and digital technology to transform the invisible acoustics digital information into a tangibly visible experiencing space and to mix the virtual acoustics space, realistic light- and- shadow space and the three-dimension material space in multi-dimensions through the digital programming and generative art design. Acoustic visualization interaction design is a comprehensive attempt which mixed with several research fields such as architecture device design, digital media technology, human-computer interaction and architecture environment science.
keywords	Acoustic Visualization; Digital FUTURES; Interaction Device
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	caadria2017_062
id	caadria2017_062
authors	Ji, Seung Yeul, Kim, Mi Kyoung and Jun, Han Jong
year	2017
title	Campus Space Management Using a Mobile BIM-based Augmented Reality System
doi	https://doi.org/10.52842/conf.caadria.2017.105
source	P. Janssen, P. Loh, A. Raonic, M. A. Schnabel (eds.), Protocols, Flows, and Glitches - Proceedings of the 22nd CAADRIA Conference, Xi'an Jiaotong-Liverpool University, Suzhou, China, 5-8 April 2017, pp. 105-114
summary	In South Korea, the changing paradigm of family composition toward single-person households and nuclear families has caused the decrease in number of students, which has led to the need for change in the qualitative, rather than quantitative, management of spaces and facilities on university campuses. In particular, since 2005, the merging of universities have accelerated, which has brought up the need for a system that facilitates the management of integrated university systems. Accordingly, universities now require efficient system operation based on three-dimensional and data visualization, unlike the document-based management of facilities and spaces in the past. Users lack a sense of responsibility for public facilities, causing difficulties such as energy waste and frequent movement, as well as damage and theft of goods. This study aims to form an AR-based interface using the ANPR algorithm, a computer vision technique, and the position-based data of the GPS. It also aims to build a campus space management system to overcome the limitations of current systems and to effectively and systematically manage integrated building data. In addition, for module test verification, the prototype is applied to actual campus spaces, and additional demands for campus space management in the AR application are identified and organized.
keywords	augmented reality; Campus space management; BIM; CAFM (computer-aided facilities management); user experience (UX)
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	caadria2024_43
id	caadria2024_43
authors	Ji, Seung Yeul, Kim, Mi Kyoung and Jun, Han Jong
year	2024
title	Real-Time User Experience and Emotional State Tracking in Indoor Architectural Spaces Using ChatGPT API and EEG
doi	https://doi.org/10.52842/conf.caadria.2024.3.489
source	Nicole Gardner, Christiane M. Herr, Likai Wang, Hirano Toshiki, Sumbul Ahmad Khan (eds.), ACCELERATED DESIGN - Proceedings of the 29th CAADRIA Conference, Singapore, 20-26 April 2024, Volume 3, pp. 489–498
summary	Technological advances have revolutionized our perception of human interactions in architectural spaces. In this study, EEG for brainwave analysis, LiDAR for spatial scanning, and ESP32 UWB for position detection were integrated into Unity3D and analyzed using the ChatGPT API. Our goal was to enhance the human experience by visualizing real-time positions, emotions, and reactions in architectural environments. The project started with 3D scanning to create a digital twin model in Unity3D, which was transformed into a virtual space with a 5x5 grid to capture EEG data. The data was analyzed using the Wolfram Mathematica API and a ranking algorithm, complemented by the ChatGPT API, fine-tuned with the SEED dataset for comprehensive emotion recognition. The core feature of the system was heat maps for visualizing emotional responses, using Unity3D's dynamic particle system for a more immersive and three-dimensional representation. This advanced approach provides architects and designers with deeper insight into user-centered space design. In summary, our integrated system demonstrates significant potential for understanding and enhancing the user experience in architectural spaces by providing insight into the impact of design elements on emotional states. It's a step forward in intelligent building and urban design that focuses on human well-being and satisfaction.
keywords	EEG, ChatGPT API, Wolfram Mathematica API, LiDAR Scanners, ESP32 UWB, Unity3D
series	CAADRIA
email
last changed	2024/11/17 22:05

_id	architectural_intelligence2024_3
id	architectural_intelligence2024_3
authors	Zhe Guo, Zihuan Zhang, Zao Li, Yi Hu, Yuandi Qian, Nengming Cheng & Philip F. Yuan
year	2024
title	Brain-computer interface based generative design framework: an empirical multi-domain application exploration based on human-factors and form-generation interactive mechanisms
doi	https://doi.org/https://doi.org/10.1007/s44223-024-00047-2
source	Architectural Intelligence Journal
summary	Human experience in an architectural space is defined as the state of mind that is reflected on their physiological, emotional, and cognitive statuses. Ergonomic data, as an objective manifestation of quantifiable signals generated by the human body during specific spatial perception processes, serves as a vital foundation for spatial evaluation and guidance for optimization. Electroencephalogram (EEG) signals, as quantifiable sensory indicators directly arising from the interaction between individuals and external stimuli, hold substantial potential as a data-driven force and as a means of optimization assessment in the study of generative design. Although existing research has effectively established a unidirectional relationship between EEG and spatial-environment assessment, there is still a notable deficiency in addressing the creation of a two-way, mutually informative feedback mechanism. This study investigates the applicability of EEG signals as a data-driven basis for generative design across universal methods. It delves into various scales and scenarios of digital design, from the microscopic to the macroscopic, encompassing planar and volumetric visual elements, the design of architectural spatial environmental characteristics, and urban space design grounded in human perceptual sightlines. The research examines the viability and appropriateness of an interactive generative design method based on form generation, predicated on human-factor physiological data exemplified by EEG signals. This paper initially conducts a methodological and tool-based examination of current research in ergonomics-driven design and the use of EEG for design assessment, thereby discussing the objective feasibility of employing EEG in interactive generative design. Subsequently, the study establishes an integrated data flow system encompassing multiple hardware and software components to form a comprehensive workflow. Following this setup, empirical studies based on this method are conducted at different scales of application, yielding corresponding form-generative outcomes. Finally, this paper substantiates the rationality and feasibility of this framework in multi environment design domains.
series	Architectural Intelligence
email
last changed	2025/01/09 15:03

_id	ddss2006-pb-271
id	DDSS2006-PB-271
authors	Ji-Hyun Lee and Huai-Wei Liu
year	2006
title	The Art of Communication: a Collaborative Decision-Making System among Different Industrial Design Stakeholders - The case of the company ASUS
source	Van Leeuwen, J.P. and H.J.P. Timmermans (eds.) 2006, Progress in Design & Decision Support Systems in Architecture and Urban Planning, Eindhoven: Eindhoven University of Technology, ISBN-10: 90-386-1756-9, ISBN-13: 978-90-386-1756-5, p. 271-288
summary	Collaboration benefits the process of complex design. However, there are many communication problems among different stakeholders in the domain of industrial design, because the situation of communication and decision-makings for stakeholders is so complicated. To deal with the complexity requires both a web-based collaborative system to communicate and share information immediately, and a multi-agent system (MAS) integrated with KW architecture to possess different levels of competence at performing a particular task. The goal of our system is to integrate a variety of representational methods of transferring knowledge and to communicate among different stakeholders using a single platform. To demonstrate our proposed concepts, we focus on a prototype system for notebook design for the company ASUS, a leading notebook manufacturer based in Taiwan.
keywords	Web-based collaborative system, Computer-supported cooperative work, Decision-making, Multi-agent system, Knowledge warehouse
series	DDSS
last changed	2006/08/29 12:55

_id	caadria2023_137
id	caadria2023_137
authors	Jia, Muxin and Narahara, Taro
year	2023
title	Spatial Analytics of Housing Prices With User-Generated POI Data, a Case Study in Shenzhen
doi	https://doi.org/10.52842/conf.caadria.2023.1.635
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. 635–644
summary	Housing is among the most pressing issues in China. Researchers are eager to identify housing property's internal and geographic factors influencing residential property prices. However, few studies have examined the relationship between social media users' point of interest (POI) data and house prices using big data. This paper presents a machine learning model for regression analysis to reveal the relationship between housing prices and check-in POI density in Futian District, Shenzhen. The results show that our proposed price prediction model using additional features based on POI data proved to provide higher prediction accuracy. Our results indicate that incorporating POI features based on current feeds from location-based social networks can provide more up-to-date estimates of housing market price trends.
keywords	Check-in POI, Kernel density estimation, Hedonic pricing method, SVR model
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	caadria2024_263
id	caadria2024_263
authors	Jia, Muxin, Zhang, Kaiheng and Narahara, Taro
year	2024
title	Characterizing Residential Building Patterns in High-Density Cities Using Graph Convolutional Neural Networks
doi	https://doi.org/10.52842/conf.caadria.2024.2.039
source	Nicole Gardner, Christiane M. Herr, Likai Wang, Hirano Toshiki, Sumbul Ahmad Khan (eds.), ACCELERATED DESIGN - Proceedings of the 29th CAADRIA Conference, Singapore, 20-26 April 2024, Volume 2, pp. 39–48
summary	In urban morphology studies, accurately classifying residential building patterns is crucial for informed zoning and urban design guidelines. While machine learning, particularly neural networks, has been widely applied to urban form taxonomy, most studies focus on grid-like data from street-view images or satellite imagery. Our paper provides a novel framework for graph classification by extracting features of clustering buildings at different scales and training a spectral-based GCN model on graph-structured data. Furthermore, from the perspective of urban designers, we put forward corresponding design strategies for different building patterns through data visualization and scenario analysis. The findings indicate that GCN has a good performance and generalization ability in identifying residential building patterns, and this framework can aid urban designers or planners in decision-making for diverse urban environments in Asia.
keywords	Urban morphology, Machine learning, Building pattern classification, Graph convolutional neural networks.
series	CAADRIA
email
last changed	2024/11/17 22:05

_id	cdrf2021_380
id	cdrf2021_380
authors	Jiabei Ye and Xiaoxi Guo
year	2021
title	Mass Customization: The Implication on Development of Aluminum Joint
doi	https://doi.org/https://doi.org/10.1007/978-981-16-5983-6_35
source	Proceedings of the 2021 DigitalFUTURES The 3rd International Conference on Computational Design and Robotic Fabrication (CDRF 2021)
summary	In the manufacturing process, the production of standardized prefabricated components is highly efficient, which can benefit the demand for mass production of standardized architecture after World War II. However, overstandardized architecture sometimes cannot satisfy the demand for uniqueness in an architecture project. At this time, bespoke components began to be used to solve the over-simplification of aesthetics of architecture. Besides, with the help of digital fabrication, bespoke components could achieve mass customization in architecture. The research designs two joints: prefabricated aluminum joints and bespoke aluminum joints, which aims to develop bespoke joints to aluminum components with ornamental characteristics and become a part of architecture with practical function and ornamental function. Furthermore, in the process of generating bespoke joints, improve the deficiency when conducting lost-foam casting.
series	cdrf
last changed	2022/09/29 07:53

_id	caadria2019_045
id	caadria2019_045
authors	Zheng, Hao, Darweesh, Barrak, Lee, Heewon and Yang, Li
year	2019
title	Caterpillar - A Gcode translator in Grasshopper
doi	https://doi.org/10.52842/conf.caadria.2019.2.253
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 2, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 253-262
summary	Additive manufacturing has widely been spread in the digital fabrication and design fields, allowing designers to rapidly manufacture complex geometry. In the additive process of Fused Deposition Modelling (FDM), machine movements are provided in the form of Gcode - A language of spatial coordinates controlling the position of the 3D printing extruder. Slicing software use closed mesh models to create Gcode from planar contours of the imported mesh, which raises limitations in the geometry types accepted by slicing software as well as machine control freedom. This paper presents a framework that makes full use of three degrees of freedom of Computer Numerically Controlled (CNC) machines through the generation of Gcode in the Rhino and Grasshopper environment. Eliminating the need for slicing software, Gcode files are generated through user-defined toolpaths that allow for higher levels of control over the CNC machine and a wider range of possibilities for non-conventional 3D printing applications. Here, we present Caterpillar, a Grasshopper plug-in providing architects and designers with high degrees of customizability for additive manufacturing. Core codes are revealed, application examples of printing with user-defined toolpaths are shown.
keywords	3D Printing; Gcode; Grasshopper; Modelling; Simulation
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	architectural_intelligence2023_22
id	architectural_intelligence2023_22
authors	Jiaming Ma, Hongjia Lu, Ting-Uei Lee, Yuanpeng Liu, Ding Wen Bao & Yi Min Xie
year	2023
title	Topology optimization of shell structures in architectural design
doi	https://doi.org/https://doi.org/10.1007/s44223-023-00042-z
source	Architectural Intelligence Journal
summary	Free-form architectural design has gained significant interest in modern architectural practice. Due to their visually appealing nature and inherent structural efficiency, free-form shells have become increasingly popular in architectural applications. Recently, topology optimization has been extended to shell structures, aiming to generate shell designs with ultimate structural efficiency. However, despite the huge potential of topology optimization to facilitate new design for shells, its architectural applications remain limited due to complexity and lack of clear procedures. This paper presents four design strategies for optimizing free-form shells targeting architectural applications. First, we propose a topology-optimized ribbed shell system to generate free-form rib layouts possessing improved structure performance. A reusable and recyclable formwork system is developed for their effective and sustainable fabrication. Second, we demonstrate that topology optimization can be combined with funicular form-finding techniques to generate a rich variety of elegant designs, offering new design possibilities. Third, we offer cost-effective design solutions using modular components for free-form shells by combining surface planarization and periodic constraint. Finally, we integrate topology optimization with user-defined patterns on free-form shells to facilitate aesthetic expression, exemplified by the Voronoi pattern. The presented strategies can facilitate the usage of topology optimization in shell designs to achieve high-performance and innovative solutions for architectural applications.
series	Architectural Intelligence
email
last changed	2025/01/09 15:03

_id	caadria2023_50
id	caadria2023_50
authors	Jiang, Mingrui and Cai, Chenyi
year	2023
title	Communication With Detroit: Machine Learning in Open Source Community Housing Design
doi	https://doi.org/10.52842/conf.caadria.2023.1.049
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. 49–58
summary	Traditional pre-design investigation includes conceptual studies, site analysis, and programming processes to analyze the site and design for users. Instead, designers and architects should consider users' ideas and their actual usage of space, which are recorded and reflected on the social media platform. To introduce more citizens' voices in the design and learn more about people's expression of Detroit city and its housing, we propose to involve the machine learning analysis in the earlier stage of the housing project using users' reflections from social media to support the conceptual design. This paper introduces a novel design framework that deals with the lacking public programs in Detroit using an online data clustering platform and demonstrates a conceptual open-source community housing design according to related findings. This framework incorporates data collection from the Twitter platform, implementation of clustering for user-oriented programs, and design applications based on the findings. Our research demonstrates an efficient and flexible approach to the open-source community housing project.
keywords	Machine learning, Decision making, Social Media, User-oriented design, Open source community
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	acadia22_300
id	acadia22_300
authors	Zheng, Hao; Akbarzadeh, Masoud
year	2022
title	A Web-based Interactive Structural Pattern Generation Tool with Graphic Statics and Machine Learning of Dragonfly Wings
source	ACADIA 2022: Hybrids and Haecceities [Proceedings of the 42nd Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-8-1]. University of Pennsylvania Stuart Weitzman School of Design. 27-29 October 2022. edited by M. Akbarzadeh, D. Aviv, H. Jamelle, and R. Stuart-Smith. 300-309.
summary	The dragonfly wing is among the many natural structures that have intrigued many researchers to study its geometry and performance as a bioinspired design. In previous research, we developed a workflow to use Graphic Statics to analyze the dragonfly wing structure and machine learning models to generate the topology and geometry of a dragonfly wing structure. However, the current workflow involves multiple geometric algorithms and the implementation of complex machine learning models, making it is difficult for designers to follow and use. Therefore, in this paper, we introduce a web-based tool that implements the workflow.
series	ACADIA
type	paper
email
last changed	2024/02/06 14:00

_id	caadria2023_398
id	caadria2023_398
authors	Jiang, Wanzhu and Wang, Jiaqi
year	2023
title	Stylized Space Synthesis: Exploring the Stylized Generative Design Method of Architecture Based on Wave Function Collapse Algorithm
doi	https://doi.org/10.52842/conf.caadria.2023.1.311
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. 311–320
summary	It has been a frequent task and challenge for architects to translate and transfer a specific style so that the design works can fit into a particular built environment or a unique period. The wave function collapse algorithm is an image generator inspired by constraint solving, which generates numerous images with similar styles by analyzing the potential connections of discrete segments in instances. This paper explores the application of the wave function collapse algorithm in the generation of stylized architecture. By deconstructing architectural style templates into predefined spatial tiles and connection rules, this research models style expression as a constraint-solving process, establishing a stylized spatial synthesis algorithm with discrete design logic to generate self-similar aggregations, shaping architecture as a unique semantic system. Based on the generative experiments of cultural architecture in the traditional Chinese style, this method was tested in two stages. While demonstrating a complete workflow, it has been fully verified for the feasibility, creativity and adaptability in stylized synthesis problems.
keywords	Stylized Synthesis, Discrete Aggregation, Wave Function Collapse, Spatial Module, Constraint Solving, Generative Design
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	acadia20_208
id	acadia20_208
authors	Zheng, Hao; Wang, Xinyu; Qi, Zehua; Sun, Shixuan; Akbarzadeh, Masoud
year	2020
title	Generating and Optimizing a Funicular Arch Floor Structure
doi	https://doi.org/10.52842/conf.acadia.2020.2.208
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. 208-217.
summary	In this paper, we propose a geometry-based generative design method to generate and optimize a floor structure with funicular building members. This method challenges the antiquated column system, which has been used for more than a century. By inputting the floor plan with the positions of columns, designers can generate a variety of funicular supporting structures, expanding the choice of floor structure designs beyond simply columns and beams and encouraging the creation of architectural spaces with more diverse design elements. We further apply machine learning techniques (artificial neural networks) to evaluate and optimize the structural performance and constructability of the funicular structure, thus finding the optimal solutions within the almost infinite solution space. To achieve this, a machine learning model is trained and used as a fast evaluator to help the evolutionary algorithm find the optimal designs. This interdisciplinary method combines computer science and structural design, providing flexible design choices for generating floor structures.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	sigradi2022_15
id	sigradi2022_15
authors	Jiang, Wanzhu; Wang, Jiaqi
year	2022
title	Autonomous Collective Housing Platform: Digitization, Fluidization and Materialization of Ownership
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. 15–26
summary	New social phenomena like digital nomads urge an upgrade in housing ownership. This research proposes an autonomous housing platform that shapes residential communities into adaptive and reconfigurable systems, framing a cycle of digitalization, fluidization and materialization of housing ownership. Specifically, the interactive interface carries the flexible ownership model that uses virtual space voxels as digital currency; the artificial intelligence algorithm drives the multilateral ownership negotiation and circulation, and modular robots complete the mapping from ownership status to real spaces. Taking project TESSERACT as a case study, we verified the feasibility of this method and presented expected co-living scenarios: the spaces and ownership are constantly adjusted according to demands and are always in the closest interaction with users. By exploring the ownership evolution, this research guides an integrated and inclusive housing system paradigm, triggering critical evaluation of traditional models and providing new ideas for solving housing problems in the post-digital era.
keywords	Agent-Based Systems, Digital Platform, Housing Ownership, Space Planning Algorithm, Discrete Material System
series	SIGraDi
email
last changed	2023/05/16 16:55

_id	acadia22pr_76
id	acadia22pr_76
authors	Jiang, Wanzhu; Wang, Jiaqi; Hosmer, Tyson; He, Ziming
year	2022
title	TESSERACT?Integrated Reconfigurable Autonomous Architecture System
source	ACADIA 2022: Hybrids and Haecceities [Projects Catalog of the 42nd Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-7-4]. University of Pennsylvania Stuart Weitzman School of Design. 27-29 October 2022. edited by M. Akbarzadeh, D. Aviv, H. Jamelle, and R. Stuart-Smith. 76-81.
summary	TESSERACT is an autonomous architecture developed through a voxel-based robotic material system that continuously reshapes communities through a socio-economic model with shifting fractional ownership. This incentivizes users to trade and share portions of physical space in real-time.
series	ACADIA
type	project
email
last changed	2024/02/06 14:04

_id	ecaade2024_5
id	ecaade2024_5
authors	Zheng, Yuchen; Chen, Lingchuan; Meng, Xiangduo; Lo, Tian Tian
year	2024
title	Exploring Virtual Reality's Role in Assessing Public Spaces for Children: An embodied design approach
doi	https://doi.org/10.52842/conf.ecaade.2024.2.149
source	Kontovourkis, O, Phocas, MC and Wurzer, G (eds.), Data-Driven Intelligence - Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2024), Nicosia, 11-13 September 2024, Volume 2, pp. 149–158
summary	This study introduces a pioneering methodology that leverages Virtual Reality (VR) technology to facilitate architects in the evaluation and enhancement of public spaces' accessibility for children. By integrating immersive VR experiences, architects are empowered to embody a child's perspective within simulated environments, thereby promoting empathetic design practices and identifying existing accessibility barriers. The primary aim of this paper is to investigate the utility of immersive VR environments in enabling architects to comprehend and address the navigational challenges that children encounter in public spaces, which are traditionally designed with adult users as the focal point. An outcome of this study is the development of a VR design tool, followed by both qualitative and quantitative analysis based on its application by 25 architecture students and professionals. The findings underscore the tool's effectiveness in facilitating an empathetic design approach towards creating more accessible environments for young users. Moreover, the study proposes a novel architectural design workflow wherein architects can import initial design models into VR for further refinements aimed at enhancing accessibility for children. Ultimately, this paper positions VR as a transformative instrument for architects, advocating for its adoption as a useful method in the design and evaluation of public spaces with a keen focus on improving accessibility for children. Additionally, this research scrutinizes the current limitations of VR technology in architectural practices and proposes a series of recommendations for future research to refine and broaden its application.
keywords	Virtual Reality, Children's Accessible Space, Embodied Experience, Empathy in Design, Inclusive Public Spaces
series	eCAADe
email
last changed	2024/11/17 22:05

_id	ecaade2024_155
id	ecaade2024_155
authors	Jiang, Xincheng; Gao, Tianyi; Zhang, Chi; Yuan, Philip F.
year	2024
title	Mortise and Tenon Beam-to-Beam Joints Solver for Discrete Timber Structures: A structural performance-driven tool based on finite element analysis
doi	https://doi.org/10.52842/conf.ecaade.2024.1.157
source	Kontovourkis, O, Phocas, MC and Wurzer, G (eds.), Data-Driven Intelligence - Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2024), Nicosia, 11-13 September 2024, Volume 1, pp. 157–166
summary	Timber, as a building material with carbon sequestration ability, has significant potential in promoting sustainable development goals. Advancements in parametric design and robotic fabrication are revitalizing traditional timber craftsmanship, leading to a new era of non-standardized design a mass customization. Modern timber structure construction faces key challenges, including analyzing traditional mortise and tenon joints' structural performance and seamlessly integrating parametric designs into robotic workflows. Achieving effective modeling for these joints requires a specialized, intelligent toolkit that spans the entire design-to-fabrication process, tailored for robotic fabrication. The study focuses on the "Mortise and Tenon Beam-to-Beam" technique, combining traditional methods with advanced technology through the FUROBOT-based "Mortise and Tenon Beam-to-Beam Joints Solver." This innovative toolkit, applied in designing and constructing a timber pavilion, enables large-scale, flexible customization in timber structures. The research begins with a detailed description of the generation of parametric joints. Following this, to enhance joint performance, finite element analysis is conducted in Abaqus, focusing on the anisotropic nature of wood joints. This analysis feedback is used in conjunction with the solver to compare multiple solutions and obtain the best high-performance joint solution. Subsequently, robot tool path generation and trajectory optimization are undertaken, considering the constructability of the wood. In the practical application phase, a timber pavilion spanning 682 square meters and standing 6 meters tall, constructed from 603 glued wood components, was erected. The empirical demonstration of the "Mortise and Tenon Beam-to-Beam Joints Solver" process verified its effectiveness and efficiency in enabling architects to design high-performance joints and implement robotic fabrication workflows. The total processing time for the 603 glued timber components was 30 days, marking a 1/3 reduction in time compared to traditional timber structure workflows. This achievement underscores the toolkit's role as a driving force in advancing non-standardized design and promoting large-scale, flexible customization in timber structure construction.
keywords	Mortise-and-Tenon Joints, Timber Structures, Parametric Joint Solver, Finite Element Analysis, Robotic Fabrication
series	eCAADe
email
last changed	2024/11/17 22:05

_id	ddss2006-pb-169
id	DDSS2006-PB-169
authors	Zhenjiang Shen, Mitsuhiko Kawakami, and Ping Chen
year	2006
title	Study on a Decision Support System for Large-Scale Shopping Centre Location Planning Using a Multi-Agent System
source	Van Leeuwen, J.P. and H.J.P. Timmermans (eds.) 2006, Progress in Design & Decision Support Systems in Architecture and Urban Planning, Eindhoven: Eindhoven University of Technology, ISBN-10: 90-386-1756-9, ISBN-13: 978-90-386-1756-5, p. 169-184
summary	Multi-agent system as a bottom-up approach has been shown powerful in better understanding processes of urban development and growth. Most of them are approaching from economic theory and social behaviours but urban planning. This paper proposes an alternative approach to urban simulation that combines urban planning with agents' behaviour in multi-agent modelling thus to make scenarios analysis more reasonable particularly for decision based on urban land use plan. This paper discusses the approach as a computer simulative solution of a new large-scale shopping centre location for most regional cities in Japan where commercial heart of inner city is facing decline. We postulate that policy decision makers can get better understanding of the policies' impact on inner city commercial environment under different scenarios through computer experimentation.
keywords	Inner city decline, Planning regulations, Planning policy, Agent
series	DDSS
last changed	2006/08/29 12:55

_id	cdrf2022_263
id	cdrf2022_263
authors	Jiaqi Wang and Wanzhu Jiang
year	2022
title	Demand-Driven Distributed Adaptive Space Planning Based on Reinforcement Learning
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_23
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
summary	In the second digital turn, the architecture driven by big data logic is gradually shifting from a traditional static entity to an intellective living organism. This paper explores a space planning algorithm that applies reinforcement learning to the multi-agent system to achieve condition adaptability. This algorithm contains an inclusive environment and programmable agents that represent independent spaces. Through reinforcement learning, personalized space needs are quantified as the agent’s Space Schema, which can provide adaptive behavior strategies to adjust volumetric room boundaries. The spatial organization emerges in multi-agent competition, guided by the Negotiation Schema, realizing the dynamic equilibrium of spatial relations and the stable maximization of collective interests. Through real-time interaction and distributed decision-making, this bottom-up method defines a new architectural paradigm that continuously changes based on demands with its high degree of variability, adaptability and evolvability.
series	cdrf
email
last changed	2024/05/29 14:02

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