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	caadria2022_32
id	caadria2022_32
authors	Lin, Han-Ting and Hou, June-Hao
year	2022
title	Exploring the Topological System of Dougong
doi	https://doi.org/10.52842/conf.caadria.2022.1.667
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 667-676
summary	The large-span wooden construction project uses a sophisticated tenon joinery system to overcome the limitation on the size of the material. However, making a clear layout and knowledge transfer is an important issue under the complex structure. This research takes "Dougong‚ as an example to sort out the possible knowledge graph of Dougong. Through the geometric feature classification and the relationship between the joints, we found that the structural relationship of traditional Dougong is like the branch system of the L-system. But it has the characteristic of horizontal connections that make Dougong restrain one another more firmly. Besides a graphical representation of the complex joinery system, it can quickly visualize and adjust the type changes and therefore provide another network related to the building model. Besides computational geometry to traditional wood structure analysis and automation, we also explored two new types of Dougong from a perspective of the traditional wooden structure. So, in this research, we developed automatic digital tools for Dougong and propose new applications of Space Syntax, attempting to break through the existing limitations of Dougong.
keywords	Dougong joint, Knowledge Graph Visualization, Parametric design, Space Syntax, SDG 4, SDG 9, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_474
id	caadria2022_474
authors	Wang, Xiang, Zhou, Ziqi, Lv, Xueyuan, Yuan, Philip F. and Chen, Lei
year	2022
title	DfD-based Design, Assembly, High-Accuracy Real-time Monitoring and Levelling Calibration for Large-scale Prefabricate Structure with Multiple Measuring Systems
doi	https://doi.org/10.52842/conf.caadria.2022.2.517
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 517-526
summary	This article introduces a novel monitoring method for the construction of high-precision prefabricated structures based on multiple sensors and measurement technologies. The proposed method introduces the optical motion capture system and combines it with traditional construction measurement technology to achieve real-time dynamic monitoring of more than hundreds of points within a large construction area more than 1810m. Tolerance fitting algorithms and the correction methods are developed and testified to provide a global tolerance with ±1mm. Meanwhile a real-time visualization interface is developed to provide the feedback and analysis of the tolerance for each structure components. As demonstrator, such monitoring system is applied in the real construction of a DfD (Design for Disassembly)-based prefabricated steel structure in the "Water Cube‚ (Chinese National Aquatics Centre) in Beijing. With the demand to control the flatness tolerance within 6mm (within a 2550m area), a large area monitoring system was applied in the project and finally reduced the construction time within 20 days.
keywords	Design for Disassembly, Real-time Monitoring, Precise Levelling Calibration, Motion-capture System, Error Fitting Algorithm, SDG 9
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_130
id	caadria2022_130
authors	Yu, Junah and Min, Deedee
year	2022
title	PL-System: Visual Representation of Pattern Language using L-System
doi	https://doi.org/10.52842/conf.caadria.2022.1.201
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 201-210
summary	Pattern Language provides simple and conveniently formatted solutions to complex design problems ranging from urban planning to interior design for community-led inclusive designs. Despite the intention, the concept has been more widely adopted by computer science professionals. One possible reason is the lack of visualization, making it difficult to be used interactively by the non-professionals. To overcome the issue, we aim to integrate the patterns from Pattern Language into the L-system to visualize the paper architecture into geometric forms. Specifically, we implement Pattern L-System (PL-System), which generates diagrammatic floor plans using design rules based on the pattern languages. We first made analogical comparisons of the concepts and grammar structure between Pattern Language and the L-system. Next, we defined a geometric interpreter for drawing diagrammatic floor plans using turtle graphics, which consist of geometrical rules for putting shapes together. Then, we selected three patterns and reinterpreted them for visualization using strings of turtle graphics letters that determine the turtle‚s movements for the geometric representation of walls, columns, and doors. From this research process, we learned that Modular L-system opens up the possibility for the visualization of the patterns in Pattern Language.
keywords	Pattern Language, L-System, Diagrammatic Floor Plan, Turtle Graphics, Geometric Forms, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_270
id	caadria2022_270
authors	Chen, Guoyi, Choi, Seungcheol, Makki, Mohammed and Mathers, Jordan
year	2022
title	Parasite City: Retaining the Industrial District of Alexandria, Sydney as an Integral Part of Urban Regeneration
doi	https://doi.org/10.52842/conf.caadria.2022.1.161
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 161-170
summary	Industrial lands are the most vulnerable urban typologies in areas undergoing urban regeneration. They are considered less adaptive to integrated residential typologies, and their legacies are threatened under fast gentrification. The goal of this paper is to explore a sustainable strategy to address the conflict between urban sprawl and industrial conservation in Alexandria, Sydney. Through the application of a sequential evolutionary simulation, the presented research proposes a potential mixed-use scheme to rejuvenate the existing industrial district of Alexandria in an integrative manner without necessitating its destruction. This paper provides a prototype of urban regeneration, optimised by a multi-objective evolutionary algorithm, that demonstrates the necessity of industrial integration in the pursuit of true mixed use urban typologies.
keywords	GeGentrification, Mixed-use, Urban Development, Sequential eGentrification, Mixed-use, Urban Development, Sequential evolutionary simulation, SDG 9, SDG 10, SDG 11, SDG 12
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_258
id	caadria2022_258
authors	Chen, Hao, Fukuda, Tomohiro and Yabuki, Nobuyoshi
year	2022
title	Developing an Augmented Reality System with Real-Time Reflection for Landscape Design Visualization, Using Real-Time Ray Tracing Technique
doi	https://doi.org/10.52842/conf.caadria.2022.1.089
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 89-98
summary	In landscape design, visualization of a new design on the site with clients can greatly improve communication efficiency and reduce communication costs. The use of augmented reality (AR) allows the projection of design models into the real environment, but the relationship between the models and the physical environment, such as reflections, which are often thoughtfully considered in waterfront landscape design, is difficult to express in existing AR systems. The aim of this study is to accurately render and express the reflections of virtual models in the physical environment in an AR system. Different from traditional rasterized rendering, this study used physically correct ray-tracing algorithms for reflection rendering calculations. Using a smartphone and a computer, we first constructed a basic AR system using a game engine and then performed ray-tracing computations using a shader kernel in the game engine. Finally, we combined the rendering results of reflections with the video stream from a smartphone camera to achieve the reflection effect of a virtual model in a physical environment. Both designers and clients could review the design with a realistic reflection on an actual water surface and discuss design decisions through this system.
keywords	Augmented reality (AR), reflection, landscape design, interactive visualization, real-time rendering, planar reflection, real-time ray tracing, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_42
id	caadria2022_42
authors	Chen, Jielin and Stouffs, Rudi
year	2022
title	Robust Attributed Adjacency Graph Extraction Using Floor Plan Images
doi	https://doi.org/10.52842/conf.caadria.2022.2.385
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 385-394
summary	Architectural design solutions are intrinsically structured information with a broad range of interdependent scopes. Compared to conventional 2D Euclidean data such as orthographic drawings and perspectives, non-Euclidean data (e.g., attributed adjacency graphs) can be more effective and accurate for representing 3D architectural design information, which can be useful for numerous design tasks such as spatial analysis and reasoning, and practical applications such as floor plan parsing and generation. Thus, getting access to a matching attributed adjacency graph dataset of architectural design becomes a necessity. However, the task of conveniently acquiring attributed adjacency graphs from existing architectural design solutions still remains an open challenge. To this end, this project leverages state-of-the-art image segmentation techniques using an ensemble learning scheme and proposes an end-to-end framework to efficiently extract attributed adjacency graphs from floor plan images with diverse styles and varied levels of complexity, aiming at addressing generalization issues of existing approaches. The proposed graph extraction framework can be used as an innovative tool for advancing design research infrastructure, with which we construct a large-scale attributed adjacency graph dataset of architectural design using floor plan images retrieved in bulk. We have open sourced our code and dataset.
keywords	attributed adjacency graph, floor plan segmentation, ensemble learning, architectural dataset, SDG 9
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_194
id	caadria2022_194
authors	Cheung, Ling Kit, Xu, Zhitao, Chen, Pei and Makki, Mohammed
year	2022
title	An Alternative Model for Urban Renewal: A Generative Approach to the (Re)-Development of Xian Village
doi	https://doi.org/10.52842/conf.caadria.2022.1.181
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 181-190
summary	The impact of urban renewal, specifically in countries experiencing rapid urbanisation due to population growth, has resulted in the erasure of urban culture and heritage in favour of repetitive homogeneity that has been synonymous with 20th century modernist planning models. One such region experiencing this rapid urban renewal is the Guangzhou region in southern China. The presented experiments examine Xian Village in Guangzhou, a culturally rich urban tissue currently experiencing redevelopment, and proposes an alternative model for urban renewal, employing a bottom-up approach to urban growth through the use of a multi-objective evolutionary model; presenting a model that integrates historic and existing urban characteristics adapted to future development plans.
keywords	China, Guangzhou, Xian Village, Village in the City, Urban Renewal, Cultural and Heritage Preservation, Multi-Objective Evolutionary Algorithm (MOEA), SDG 10, SDG 11, SDG 13
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_220
id	caadria2022_220
authors	Hsiao, Chi-Fu, Lee, Ching-Han, Chen, Chun-Yen, Fang, Yu-Cyuan and Chang, Teng-Wen
year	2022
title	Training a Vision-Based Autonomous Robot From Material Bending Analysis to Deformation Variables Predictions With an XR Approach
doi	https://doi.org/10.52842/conf.caadria.2022.2.201
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 201-210
summary	This paper proposes a "Human Aided Hand-Eye System (HAHES)" to aid the autonomous robot for "Digital Twin Model (DTM)" sampling and correction. HAHES combining the eye-to hand and eye-in hand relationship to build an online DTM datasets. Users can download data and inspect DTM by "Human Wearable XR Device (HWD)", then continuous updating DTM by back testing the probing depth, and the overlap between physics and virtual. This paper focus on flexible linear material as experiment subject, then compares several data augmentation approaches: from 2D OpenCV homogeneous transformation, autonomous robot arm nodes depth probes, to overlap judgement by HWD. Then we train an additive regression model with back-testing DTM datasets and use the gradient boosting algorithm to inference an approximate 3D coordinate datasets with 2D OpenCV datasets to shorten the elapsed time. After all, this paper proposes a flexible mechanism to train a vision-based autonomous robot by combing different hand-eye relationship, HWD posture, and DTM in a recursive workflow for further researchers.
keywords	Digital Twin Model, Hand-Eye Relationship, Human Wearable XR Device, Homogeneous Transformation, Gradient Boosting, SDG 4, SDG 9
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_48
id	caadria2022_48
authors	Jeong, Joowon, Chen, Qinchuan, Kim, Nayeon and Lee, Hyunsoo
year	2022
title	Virtual Reality Collaborative Platform for E-learning: Analysis of Student Engagement and Perceptions
doi	https://doi.org/10.52842/conf.caadria.2022.1.019
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 19-28
summary	In this paper, we discuss the potential of using virtual reality collaborative platforms for e-learning to improve the quality of online education. First, we explore the characteristics of existing online platforms that can be used for e-learning. Second, we present a method for creating a Virtual Reality Collaborative Environment (VRCE) for e-learning using an online platform, namely FrameVR. Third, an experiment is conducted to investigate participants' behavioural and emotional engagement when using Zoom and the VRCE for online learning. Valid survey data from twenty-two participants are analysed. Then, participants are interviewed about their perceptions of using a VRCE for e-learning. The results of the experiment confirm that using a VRCE can increase student engagement, especially emotional engagement compared to Zoom. However, the findings also suggest that there is still room for improvement in the use of VRCE for e-learning. Therefore, further suggestions are made on the drawbacks of VRCE to improve the user experience. This paper provides insight into incorporating VRCE to enhance the e-learning experience and contribute to the development of online education.
keywords	Virtual Reality Collaborative Environment, E-Learning, FrameVR, Online Education, SDG 4
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_193
id	caadria2022_193
authors	Tsai, Tsung-Han, Chen, Ting-Chia, Huang, Ching-Wen, Lu, Yen-Cheng and Wang, Shih-Yuan
year	2022
title	S.n.o.w_Sintering TPU via Nichrome Wire
doi	https://doi.org/10.52842/conf.caadria.2022.2.243
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 243-252
summary	This paper introduces and investigates NiChrome wire sintering, a novel fabrication technique in the field of additive manufacturing. With a combination of differentiated material states and material properties, this research generates forms with different sintering strategies through computation and fabrication systems. Rather than creating objects through selectively depositing melted material in a predetermined path, layer-by-layer, this rapid prototyping methodology generates 2D or 3D spatial wireframes by weaving NiChrome wire and sintering thermoplastic polyurethane (TPU) onto it by utilizing the instantaneous high temperature of NiChrome wire after electrification. A series of experiments is presented utilizing a proportional integral derivative (PID) temperature control system in cooperation with thermal camera equipment to ensure consistent results under the same conditions. In addition, the project focuses not only on developing NiChrome wire sintering systems but also on the applicabilities of this technique by fabricating wireframe surfaces under different situations.
keywords	Nichrome Wire Sintering, Rapid Prototyping, Elastic Material, Digital Fabrication, SDG 12
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_46
id	caadria2022_46
authors	Wang, Likai, Janssen, Patrick and Chen, Kian Wee
year	2022
title	Evolutionary Design of Residential Precincts, A Skeletal Modeling Approach for Generating Building Layout Configurations
doi	https://doi.org/10.52842/conf.caadria.2022.1.415
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 415-424
summary	This paper presents a ‚skeletal‚ parametric schema to generate residential building layout configurations for performance-based design optimization. The schema generates residential building layout configurations using a set of ‚skeletal‚ lines that are created based on various design elements and coincident with factors such as walkways, spacing, and setback requirements. As such, the schema is able to generate diverse and legitimate design alternatives. With the proposed parametric schema, a case-study optimization is carried out for a Singapore Housing Development Board (HDB) project. The case study considers a set of performance criteria and produces results with higher practical referential value. The case study demonstrates that the optimization with the parametric schema can improve the overall quality of the design and provide designers with various design options.
keywords	parametric modeling, building layout, performance-based design, algorithmic design, design optimization, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_291
id	caadria2022_291
authors	Zhang, Qiyan, Li, Biao, Mo, Yichen, Chen, Yulong and Tang, Peng
year	2022
title	A Web-based Interactive Tool for Urban Fabric Generation: A Case Study of Chinese Rural Context
doi	https://doi.org/10.52842/conf.caadria.2022.1.625
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 625-634
summary	The design of rural fabric is significant for making sustainable communities and requires innovative design models and prospective work paths. This paper presents an interactive tool based on the web to generate block fabric that responds to the Chinese rural context, consisting of streets, plots, and buildings. The tool is built upon the Browser/Server (B/S) architecture, allowing users to access the generation system via the web simply and to have interactive control over the generation process in a user-friendly way. The underlying tensor field and rule-based system are adopted in the backend to model the fabric subject to multiple factors, with rules extracted from the rural design prototype. The system aims to integrate the procedural model with practical design constraints in the rural context, such as patterns, natural boundaries, elevations, planning structure, and existing streets. The proposed framework supports extensions to different urban or suburban areas, inspiring the promising paths of remote cooperation and generative design for sustainable cities and communities.
keywords	Generative Design, Web-based Tool, Urban Fabric, Rural Context, Procedural Modeling, Tensor Field, SDG 11
series	CAADRIA
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last changed	2022/07/22 07:34

_id	caadria2022_297
id	caadria2022_297
authors	Zhou, Margaret Z., Chen, Shi Yu and Garcia del Castillo y Lopez, Jose Luis
year	2022
title	Elemental Motion in Spatial Interaction (EMSI): A Framework for Understanding Space through Movement and Computer Vision
doi	https://doi.org/10.52842/conf.caadria.2022.1.505
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 505-514
summary	Spatial analysis and evaluation are becoming increasingly common as new technologies enable users, designers, and researchers to study spatial motion patterns without relying on manual notations for observations. While ideas related to motion and space have been studied in other fields such as industrial engineering, choreography, and computer science, the understanding of efficiency and quality in architectural spaces through motion has not been widely explored. This research applies techniques in computer vision to analyse human body motion in architectural spaces as a measure of experience and engagement. A taxonomy framework is proposed to categorize human motion components relevant to spatial interactions, for analysis through computer vision. A technical case study developed upon a machine-learning-aided model is used to test a selection of the proposed framework within domestic kitchen environments. This contribution adds further perspective to wider research explorations in the quality, inclusivity, engagement, and efficiency of architectural spaces through computer-aided tools.
keywords	Pose Estimation, Spatial Evaluation, Architectural Usability, Motion Studies, Computer Vision, SDG 3, SDG 9
series	CAADRIA
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last changed	2022/07/22 07:34

_id	caadria2022_486
id	caadria2022_486
authors	Zhou, Xinyi, Chen, Yao, Chen, Fukai, Li, Kan, Lo, Tian Tian, Xiang, Rufeng and Liu, Liquan
year	2022
title	Remembering Urban Village: Using CloudXR Technology as an Enhanced Alternative to Better Disseminate Heritage
doi	https://doi.org/10.52842/conf.caadria.2022.1.757
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 757-766
summary	Urban villages are strictly related to urban growth. It reflects the era characteristics and memory in urban growth, which has significant value in heritage and sustainable cities (SDG 11). Due to the continuous development of urbanization and the shortage of urban land, many urban villages will be replaced by more valuable functions. Therefore, better preserving the digitalization of urban villages and making more people understand the value of urban villages is particularly important. However, the existing technology still has shortcomings in disseminating digital heritage. For urban villages, usually a large-scale and complex environment, the hardware requirements will be very high for high-precision visualization. Most existing solutions use large hardware devices, such as the virtual sand table. Unlike hand-held devices, such devices are expensive and not portable, limiting better dissemination of such heritage. Due to the hardware limitation of hand-held devices, neither the display resolution nor the interaction effect is satisfying. Therefore, this paper proposes a new workflow by NVIDIA CloudXR streaming technology to achieve high-precision visualization and a rich interactive experience on hand-held devices. Such heritage can be promoted and cities can be more sustainable.
keywords	CloudXR technology, urban village, digital heritage, preservation, dissemination, portable devices, SDG 11
series	CAADRIA
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last changed	2022/07/22 07:34

_id	caadria2022_114
id	caadria2022_114
authors	Dong, Zhiyong, Lin, Jinru, Wang, Siqi, Xu, Yijia, Xu, Jiaqi and Liu, Xiao
year	2022
title	Where Will Romance Occur, A New Prediction Method of Urban Love Map through Deep Learning
doi	https://doi.org/10.52842/conf.caadria.2022.1.213
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 213-222
summary	Romance awakens fond memories of the city. Finding out the relationship between romantic scene and urban morphology, and providing a prediction, can potentially facilitate the better urban design and urban life. Taking the Yangtze River Delta region of China as an example, this study aims to predict the distribution of romantic locations using deep learning based on multi-source data. Specifically, we use web crawlers to extract romance-related messages and geographic locations from social media platforms, and visualize them as romance heatmap. The urban environment and building features associated with romantic information are identified by Pearson correlation analysis and annotated in the city map. Then, both city labelled maps and romance heatmaps are fed into a Generative Adversarial Networks (GAN) as the training dataset to achieve final romance distribution predictions across regions for other cities. The ideal prediction results highlight the ability of deep learning techniques to quantify experience-based decision-making strategies that can be used in further research on urban design.
keywords	Romance Heatmap, Generative Adversarial Networks, Deep Learning, Big Data Analysis, Correlation Analysis, SDG 11
series	CAADRIA
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last changed	2022/07/22 07:34

_id	caadria2022_195
id	caadria2022_195
authors	Li, Shuyang, Sun, Chengyu and Lin, Yinshan
year	2022
title	A Method of VR Enhanced POE for Wayfinding Efficiency in Mega Terminals of Airport
doi	https://doi.org/10.52842/conf.caadria.2022.1.079
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 79-88
summary	The airport is one of the most essential infrastructures of cities. An important issue of the airport design is that passengers must be able to find their way efficiently. Although the designers adopt the post-evaluation after the operation, it takes a long time to conduct the on-site wayfinding experiment, and the number of participants of the experiment is also limited. Moreover, conventional post-occupancy evaluation suffers from security control and quarantine inspection that can not be carried out in the field. We proposed a VR enhanced POE approach that carries out an online wayfinding experiment to obtain numerous and detailed data, which significantly improves the efficiency of the post-occupancy evaluation project, and is validated by an affordable small-scale on-site experiment. Meanwhile, the cause for low wayfinding efficiencies, such as the symmetric space, the ambiguous direction and the redundant information on signboards are found and corresponding optimization suggestions are presented. The following signage system optimization project conducted in the terminal is welcomed by the passengers according to monthly questionnaires.
keywords	Transportation Building, Post-Occupancy Evaluation, Digital Twins, Signage System Design, Wayfinding, Virtual Reality, Eye-Tracking, SDG 9.
series	CAADRIA
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last changed	2022/07/22 07:34

_id	caadria2022_120
id	caadria2022_120
authors	Lin, Yuxin
year	2022
title	Rhetoric, Writing, and Anexact Architecture: The Experiment of Natural Language Processing (NLP) and Computer Vision (CV) in Architectural Design
doi	https://doi.org/10.52842/conf.caadria.2022.1.343
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 343-352
summary	This paper presents a novel language-driven and artificial intelligence-based architectural design method. This new method demonstrates the ability of neural networks to integrate the language of form through written texts and has the potential to interpret the texts into sustainable architecture under the topic of the coexistence between technologies and humans. The research merges natural language processing, computer vision, and human-machine interaction into a machine learning-to-design workflow. This article encompasses the following topics: 1) an experiment of rethinking writing in architecture through anexact form as rhetoric; 2) an integrative machine learning design method incorporating Generative Pre-trained Transformer 2 model and Attentional Generative Adversarial Networks for sustainable architectural production with unique spatial feeling; 3) a human-machine interaction framework for model generation and detailed design. The whole process is from inexact to exact, then finally anexact, and the key result is a proof-of-concept project: Anexact Building, a mixed-use building that promotes sustainability and multifunctionality under the theme of post-carbon. This paper is of value to the discipline since it applies current and up-to-date digital tools research into a practical project.
keywords	Rhetoric and writing, Natural Language Processing, Computer Vision, GPT-2, AttnGAN, Human-computer Interaction, Architectural Design, Post-carbon, SDG3, SDG11
series	CAADRIA
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last changed	2022/07/22 07:34

_id	caadria2022_57
id	caadria2022_57
authors	Wang, Hanmo, Goel, Abhimanyu and Lin, Alexander
year	2022
title	Optimization of Partition Wall Infilled Pattern for Minimizing Carbon Footprint: A Method That Integrates Parametric Design Tool With FEA Analysis Engine
doi	https://doi.org/10.52842/conf.caadria.2022.2.365
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 365-374
summary	The term "biomimicry‚ has been discussed and studied for a long time in the research field. A triply minimal surface geometry called gyroid was found to have the potential to present lightweight but solid structures and possess good thermal insulation properties, thus possibly minimizing the carbon footprints during both building construction and operation stages. Therefore, this paper will deliver research on the physical properties of the gyroid structure at different scales and explore the feasibility of scaling microstructure onto a partition wall system, which seeks opportunities to set up an efficient connection between parametric modelling and finite element engine. The integration work allows evaluating the performance of the gyroid structure with various variables as the wall infillings, which supplies the critical information and assist the engineers in figuring out the ideal design candidates at a given condition. This workflow requires a parametric approach including Rhino and Grasshopper, a finite element analysis tool ANSYS APDL (ANSYS Parametric Design Language), and Excel to save the essential data for further use. This project studies the suitable scales of the selected gyroid structure and the technical details on the interoperability between the parametrical system and the structure analysis engine for performance-based optimization. The expected outcome is to provide a tool that assists designers in optimizing the building components at the early stage and finally enrich the methods of computer-aided design.
keywords	Low-carbon Solution, Bio-inspired Solution, Design Simulation, FEA Method, Design Optimization, SDG 12, SDG 13
series	CAADRIA
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last changed	2022/07/22 07:34

_id	caadria2022_264
id	caadria2022_264
authors	Zhang, Garry Hangge, Meng, Leo Lin, Gardner, Nicole, Yu, Daniel and Haeusler, Matthias Hank
year	2022
title	Transit Oriented Development Assistive Interface (TODAI): A Machine Learning Powered Computational Urban Design Tool for TOD
doi	https://doi.org/10.52842/conf.caadria.2022.1.253
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 253-262
summary	Transit-oriented Development(TOD) is widely regarded as a sustainable development paradigm for its sensible space planning and promotion of public transit access. Research in providing decision support tools of TOD may contribute to the Sustainable Development Goals, especially towards sustainable cities and communities (SDG goal 11).While the existing Geographic Information System(GIS) approach may well inform TOD planning, computational design, simulation, and visualisation techniques can further enhance this process. The research aims to provide a data-driven, computational-aided planning support system (PSS) to enhance the TOD decision-making process. The research adopts an action research methodology, which iteratively designs experiments and inquires through situating the research question in real-world practice. A work-in-progress prototype is provided - Transit-Oriented Development Assistive Interface (TODAI), along with an experiment in a newly proposed metro station in Sydney, Australia. TODAI provides real-time visualisation of urban forms and analytical data indicators reflecting key considerations relevant to TOD performance. A regressive machine learning model (XGBoost) is used to make predictions of analytical indicators, promptly producing outcomes that may otherwise require a costly computational operation.
keywords	TransUrban Planning, Transit-Oriented Development, Planning Support System, Machine Learning, SDG 11it-Oriented Development, Urban Planning, Machine Learning, Computational Design, SDG11, Sustainable Cities and Communities
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_360
id	caadria2022_360
authors	McMeel, Dermott and Petrovic, Emina K.
year	2022
title	Architecture Value Change in Response to the Anthropocene: The Contribution of Digital Innovation
doi	https://doi.org/10.52842/conf.caadria.2022.2.415
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 415-424
summary	The confluence of different interests‚the Anthropocene, productivity, sustainability, economics‚calls for a need to re-think how the professions evaluate the built environment. There is a myriad of different strands of work under this umbrella which‚broadly‚point to a shift in the value framework for those people and professions who have agency in, and are responsible for, the creation of the built environment. This paper has two objectives. First, by drawing from the writing of architectural theorist Juhani Pallasmaa it teases out themes useful to conceptualise the value change. The goal is to delineate particular views around the creation of and our relation to the built environment. Second, it presents three projects: (1) tracking chemical composition of construction materials, (2) an app that encourages e-commerce in building multi-species environments, and (3) a concept for an economy in construction waste leveraging possibilities presented by blockchain technology. The aim is to shed light on how the emerging blockchain technology might alter values and organisational systems of the built environment in response to the Anthropocene and climate crisis.
keywords	Design, Anthropocene, Value Change, Blockchain, System Design, SDG 9, SDG 11, SDG 12
series	CAADRIA
email
last changed	2022/07/22 07:34

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