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	caadria2024_202
id	caadria2024_202
authors	Ataman, Cem, Tunçer, Bige and Perrault, Simon
year	2024
title	Digital Participation in Urban Design and Planning: Addressing Data Translation Challenges in Urban Policy- and Decision-Making through Visualization Techniques
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. 201–210
doi	https://doi.org/10.52842/conf.caadria.2024.2.201
summary	Digital technologies and online platforms, such as e-participation and crowdsourcing tools, are revolutionizing citizen engagement in urban design and planning by enabling large-scale, asynchronous, and individual participation processes. This evolution towards more inclusive and representative decision- and policy-making, however, presents a significant challenge: the effective utilization of the vast amounts of textual data generated. This difficulty arises from distilling the most relevant information from the extensive datasets and the lack of suitable methodologies for the visual representation of qualitative data in urban practices. Addressing this, the paper deploys AI-based analysis methods, including Natural Language Processing (NLP), Topic Modeling (TM), and sentiment analysis, to efficiently analyze these datasets and extract relevant information. It then advances into the realm of data representation, proposing innovative approaches for the visual translation of this textual data into multi-layered narratives. These approaches, designed to comply with a comprehensive set of both quantitative and qualitative interpretation criteria, aim to offer deeper insights, thus fostering equitable and inclusive governance. The goal of this research is to harness the power of qualitative textual data derived from online participation platforms to inform and enhance decision- and policy-making processes in urban design and planning, thereby contributing to more informed, inclusive, and effective urban governance.
keywords	Digital Participation, Textual Big Data, Natural Language Processing, Spatial Data Analytics, Data Visualization
series	CAADRIA
email
last changed	2024/11/17 22:05

_id	ecaade2024_114
id	ecaade2024_114
authors	Su, Xinyu; Liu, Zidong; Yang, Mingzhuo; Koehler, Daniel
year	2024
title	ZoeLength: Framework for indoor measurement from a single interior image for the popularization of AI interior design
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. 413–422
doi	https://doi.org/10.52842/conf.ecaade.2024.2.413
summary	Applying Artificial Intelligence Generated Content (AIGC) to interior design makes it possible for anyone to take on the role of a designer. Size is crucial to interior design, and distance measurement has become an essential component allowing to integration of image generation in industrial supply chain processes. This paper explores a new framework for indoor measurement based on a single interior image. Without any reference and camera calibration, our method ZoeLength can estimate the target size by taking a photo with the simplest mobile device. We achieved this by constructing a simplified camera model, incorporating cutting-edge depth estimation technology, ZoeDepth and Depth Anything, and object detection technology, Grounding DINO. To increase the accuracy of measurement, we trained a depth estimation model specifically for indoor scenes using our own collected dataset. Experimental results from multiple aspects demonstrate the reliability and validity of the proposed method and its application value to real-world scenarios.
keywords	AIGC Interior Design, Indoor Measurement, Single-Image Measurement, Depth Estimation, Object Detection
series	eCAADe
email
last changed	2024/11/17 22:05

_id	ecaade2024_298
id	ecaade2024_298
authors	Avellaneda Lopez, Omar Fabrisio; Christodoulou, Marilena; Mendoza, Marisela
year	2024
title	Parametric Design and Geometric Optimization for Deployable Domes Based on the icosahedron frequency with hexagonal modules
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. 411–420
doi	https://doi.org/10.52842/conf.ecaade.2024.1.411
summary	The systems of deployable structures domes with straight bars are directly related to the geometry of solids. They are lightweight, modular, and transformable systems. This research relates to the design of deployable structures with articulated straight bars, with the purpose of being habitable and offering a solution to the light and traditional architecture. In particular, it refers to the design of deployable domes with articulated straight bars, starting from the transformation of the icosahedron using deployable hexagonal modules. With the possibility of changing its scale when increasing its frequency. In addition, has aims at a parametric design method for deployable domes or shells with straight bars of equal articulated dimension, stabilized with a flexible or rigid architectural covering. The process is defined as quick assembly. The optimization method employed is based on transforming the icosahedron and varying its frequencies. The process consists of optimizing deployable hexagonal modules with bars of equal length following geodesic patterns. Using visual programming algorithms using Rhinoceros + Grasshopper, geometric optimization results are achieved with deployable hexagonal modules applied to different dome frequencies. The system offers efficient solutions to temporary shelters, portable greenhouses, scenarios for medium and large-scale events, and everything related to light and transformable architecture.
keywords	Deployable Structures, Geometric Optimization, Parametric Design, Lightweight Structures
series	eCAADe
email
last changed	2024/11/17 22:05

_id	ecaade2024_359
id	ecaade2024_359
authors	Cigáník, Ondøej; Sviták, Daniel; Sýsová, Kateøina; Tsikoliya, Shota; Vaško, Imrich
year	2024
title	Strengthened Shells: Possibilities of conformal printing on curved surfaces in large scale 3D printing
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. 9–16
doi	https://doi.org/10.52842/conf.ecaade.2024.1.009
summary	This paper investigates the potential impact of conformal filament layering on various 3D printed structures with the aim of enhancing or altering their properties. Currently, large scale 3D printed objects predominantly utilize vase-mode style prints, occasionally featuring more intricate internal structures resembling FDM infill patterns, yet typically produced in a single continuous extrusion, resulting in a single perimeter wall thickness. This research seeks to explore the advantages of layering additional material onto the outer perimeter of a print, leveraging the capabilities of 6-axis robots and conformal printing techniques. To empirically assess the efficacy of this technique, an experiment is designed involving the fabrication of a consistent one-layer domed shell on a supportive form, onto which additional layers, oriented differently and featuring various patterns, are subsequently applied. The resultant samples are subjected to tests measuring both their strength and visual attributes, generating data for further analysis and application.
keywords	Additive Manufacturing, Robotic Fabrication, Conformal Printing, Non-planar, Recycled Material, Material Characteristics
series	eCAADe
email
last changed	2024/11/17 22:05

_id	ecaade2024_296
id	ecaade2024_296
authors	Fereos, Pavlos; Bauer, Kilian; Efthimiou, Eftychios-Nicolaos
year	2024
title	Surface Articulation as Structural Leverage in Large Scale 3D Printing
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. 607–616
doi	https://doi.org/10.52842/conf.ecaade.2024.2.607
summary	As large-scale robotic 3D printing continues to gain traction in architecture, design and construction, the necessity to develop fabrication-inherent strategies and guidelines to overcome generic limitations of the method becomes increasingly apparent. To contribute to this process, this paper presents three prototypes that explore the concept of surface articulation through geometry manipulation as structural leverage in large scale robotic 3D printing. Each of the three prototypes addresses a specific architectural task with increasing ambition to incrementally challenge the hypothesis. The three research pieces are a three-meter tall, leaning Column, an ornamental Throne and a two and a half meters tall, cantilevering Lamp-post. While the three prototypes represent only a small series of case studies, they are nonetheless diverse and demonstrate situations of different structural stresses, ranging from tension to compression to bending. In the attempt to counteract these structural stresses, all three prototypes pursue the notion of geometry manipulation in the appearance of surface articulation. While the approach to improve surface rigidity through complexity and folding has been known for a long time, it is inherent to the nature of digital design and fabrication, which could revive surface ornamentation in additive manufacturing. The three objects presented, which together form the Trilogy of Additive Hyper-Ornamental Prototypes, aim to contribute to this process by showcasing initial explorations into surface articulation as structural leverage in large scale 3D printing and the aesthetics inherent to this process in order to inspire further research.
keywords	large scale 3D printing, robotic fabrication, surface ornamentation, material properties, geometry manipulation
series	eCAADe
email
last changed	2024/11/17 22:05

_id	ecaade2024_290
id	ecaade2024_290
authors	Hsieh, Wen-Chun; Sheng, Yu-Ting; Wang, Shih-Yuan
year	2024
title	Exploration of Incremental Sheet Forming for Application in Formwork Techniques
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. 85–94
doi	https://doi.org/10.52842/conf.ecaade.2024.1.085
summary	This research explores the application of Incremental Sheet Forming (ISF) technology in concrete formwork to enhance efficiency and sustainability in construction. Traditional formwork methods suffer from inefficiency and limited customizability, prompting the need for alternatives. In the 1930s, the emergence of pneumatic formwork marked a significant advancement in the construction industry. Subsequently, alternatives such as hanging cable net formwork, CNC milling, and other digital fabrication methods have offered greater flexibility in designing complex geometries. However, challenges persist in scalability and understanding material properties. Despite advancements, the industry still seeks solutions to optimize design and minimize waste in construction formwork techniques. Incremental sheet forming (ISF), a versatile manufacturing technique, enables the rapid production of complex 3D shapes from sheet materials while reducing resource consumption. This research employs a 0.6mm thick aluminum alloy sheet processed with a 6-axis robotic arm, integrating digital design-to-fabrication workflow for precise control. Experiments focus on comparing ISF formwork with other digital fabrication formwork, exploring design control methods, and concluding with concrete casting. Challenges remain in understanding the interaction between concrete properties and the ISF process, especially for large-scale structures. Leveraging ISF in concrete formwork offers the potential to redefine construction practices, balancing design flexibility, sustainability, and customization. This research contributes to advancing construction methods and underscores opportunities for future research in ISF formwork applications.
keywords	Concrete Formwork, Incremental Sheet Forming, Robotic Fabrication
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
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
doi	https://doi.org/10.52842/conf.ecaade.2024.1.157
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	ecaade2024_80
id	ecaade2024_80
authors	Li, Wenpei; Wu, Jiaqian; M. Herr, Christiane; Stouffs, Rudi
year	2024
title	Enhancing Lexicon Based Evaluation of Urban Green Space Characteristics and Perceptions with a Large Language Model
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. 59–68
doi	https://doi.org/10.52842/conf.ecaade.2024.2.059
summary	Evaluating Urban green space Characteristics and Human Perceptions (UCHP) is crucial for landscape design and management due to their impact on public health. Online park reviews provide valuable insights into human-environment interactions, enabling the large-scale evaluation of UCHP. However, existing approaches to classify online park reviews commonly ignore text context, leading to low precision of UCHP quantification and supervised approaches are rarely applied due to huge cost. To improve the precision and effectiveness of UCHP quantification, we propose a novel workflow comprising five stages: custom lexicon creation, design of labels for a Large Language Model (LLM), sentence classification using lexicon and LLM, and performance evaluation using a manually annotated dataset and four metrics: precision, recall, accuracy, and F1 score. To examine the performance of the LLM, we compared the classification of 15 UCHP using LLM, lexicon, and lexicon+LLM. The analysis involved utilizing online park review sentences from Google Map and TripAdvisor using the proposed workflow. The higher precision, accuracy and F1 score demonstrate that combination of lexicon and LLM yields the highest performance, followed by using only lexicon and then solely LLM. This performance evaluation demonstrates the validity of the proposed LLM-aided workflow, providing a practical, reliable, and efficient alternative to the lower performance of unsupervised methods, or costly supervised classification methods. We discuss the limitations of lexicon+LLM and outline new opportunities for LLM application in landscape studies.
keywords	urban green space, characteristics and human perceptions, large language model, evaluation
series	eCAADe
email
last changed	2024/11/17 22:05

_id	ecaade2024_264
id	ecaade2024_264
authors	Meyer, Joost; Garrido, Federico; Martarello, Ana; Hömberg, Christina
year	2024
title	Opportunities for a sustainable future: Testing the biocompatibility of new materials for large scale additive manufacturing
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. 245–254
doi	https://doi.org/10.52842/conf.ecaade.2024.1.245
summary	This paper is about recycling, reuse, composting and degradation of natural 3D-printing materials based on waste from the wood industry. Wood is an abundant organic material used in the construction industry that generates significant waste during its manufacturing process. Liquid Deposition Modelling (LDM) offers a flexible and energy-efficient additive manufacturing method for paste-like materials made from these same waste materials. Due to the inherent properties of its components, the resulting material is sustainable and complies with the principles of the circular economy. The potential impact of this emerging and scarcely investigated technological opportunity on the construction industry could be immense. The sustainable properties can lead to a turning point in the carbon-conscious design in architecture. For this reason, a young team of researchers, supported by architectural students in their Masters, designed experimental set-ups, methods and evaluation criteria focusing on aspects of ecology.
keywords	biogenic materials, additive manufacturing, 3d printed architecture, circularity, liquid deposition modelling, zero waste, up-cycling, wood waste recycling
series	eCAADe
email
last changed	2024/11/17 22:05

_id	ecaade2024_168
id	ecaade2024_168
authors	Meyuhas, Ohad Yaacov; Larianovsky, Pavel; Natanian, Jonathan; Sprecher, Aaron
year	2024
title	Thermal and structural performance of cork-cement composite for Additive Manufacturing (AM)
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. 265–272
doi	https://doi.org/10.52842/conf.ecaade.2024.1.265
summary	This study explores the potential of cork-cement composites for structural and thermal performance in architecture through additive manufacturing (AM) technology. By optimizing the composite for 3D printing, the research demonstrates the unique applicability of this composite for large-scale architectural projects, particularly for building envelope elements. Employing a robotic 3D printing process, masonry blocks were manufactured and evaluated for structural performance and thermal efficiency. The results of this study demonstrate the practicality of using cement-cork composite in AM architectural envelopes. In addition, the results show that 3D-printed cork-cement composite elements outperform traditional masonry blocks. Ultimately, this study paves the way for future 3D printing of architectural elements with functionally graded structural and thermal performance.
keywords	Additive Manufacturing, Architectural Robotics, Thermal Performance, Structural Performance, Cork, Cementitious Material
series	eCAADe
email
last changed	2024/11/17 22:05

_id	ecaade2024_117
id	ecaade2024_117
authors	Su, Xinyu; Luo, Jianhe; Liu, Zidong; Yan, Gaoliang
year	2024
title	Text to Terminal: A framework for generating airport terminal layout with large-scale language-image models
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. 469–478
doi	https://doi.org/10.52842/conf.ecaade.2024.1.469
summary	Large-scale language-image (LLI) models present novel opportunities for architectural design by facilitating its multimodal process via text-image interactions. However, the inherent two-dimensionality of their outputs restricts their utility in architectural practice. Airport terminals, characterized by their flexibility and patterned forms, with most of the design operations occurring at the level of master plan, indicating a promising application area for LLI models. We propose a workflow that, in the early design phase, employs a fine-tuned Stable Diffusion model to generate terminal design solutions from textual descriptions and a site image, followed by a quantitative evaluation from an architectural expert's viewpoint. We created our dataset by collecting satellite images of 295 airport terminals worldwide and annotating them in terms of size and form. Using Terminal 2 of Zhengzhou Xinzheng International Airport as a case study, we scored the original and generated solutions on three airside evaluation metrics, verifying the validity of the proposed method. Our study bridges image generation and expert architectural design assessments, providing valuable insights into the practical application of LLI models in architectural practice and introducing a new method for the intelligent design of large-scale public buildings.
keywords	Multimodal Machine Learning, Diffusion Model, Text-to-Architecture, Airport Terminal Configuration Design, Post-Generation Evaluation
series	eCAADe
email
last changed	2024/11/17 22:05

_id	ecaade2024_54
id	ecaade2024_54
authors	Svatoš-Ražnjeviæ, Hana; Wyller, Maria; Schad, Eva; Menges, Achim
year	2024
title	Jammed Rubble: A building system concept for granular architecture from mixed mineral waste
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. 587–596
doi	https://doi.org/10.52842/conf.ecaade.2024.2.587
summary	The research presented in this paper aims to expand the design and fabrication space for building with mixed mineral construction and demolition waste (rubble) by utilizing granular jamming in combination with lightweight textile containers. Despite the wide availability of rubble and the persistence of destructive demolition processes, there has been relatively little research on its application in architecture. Often considered a low-quality material, rubble, a granular material, has the inherent potential to form structurally stable geometries through confinement. In this paper, we aim to take advantage of this quality and present a rapidly deployable building system and fabrication concept for compression-based vertical building components. The research methods consist of rubble analysis and categorization, and the development of packing, layering and pouring strategies tested through physical prototyping. Although in its early stages, the research demonstrates the potential of bringing unprocessed rubble back into architecture as a low-cost sustainable material resource for large-scale aggregate structures to combat one of the world's largest waste streams.
keywords	Upcycling demolition waste, upcycled rubble, aggregate architecture, jammed structures, granular construction, mixed mineral waste
series	eCAADe
email
last changed	2024/11/17 22:05

_id	ecaade2024_153
id	ecaade2024_153
authors	Tsurunaga, Shinya; Fukuda, Tomohiro; Yabuki, Nobuyoshi
year	2024
title	Enhanced Landscape Visualization of Post-Structure Removal: Integrating 3D reconstruction techniques and diffusion models through machine learning
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. 549–558
doi	https://doi.org/10.52842/conf.ecaade.2024.1.549
summary	In urban redevelopment, demolition of existing buildings often occur and landscape assessment plays an important role in avoiding various environmental issues. Both residents and professionals should be involved to create a virtual three-dimensional (3D) space after demolition, which would enable even non-experts to understand the future landscape. Research efforts aimed at creating virtual 3D spaces by removing unnecessary objects utilize techniques such as neural radiance fields (NeRF). These techniques reconstruct spaces into virtual 3D spaces from RGB images by removing redundant objects. However, a challenge arises from the low-quality images generated from the resultant space. Additionally, methods for reconstructing 3D images face limitations in acquiring images of portions previously obscured by structures slated for demolition. This often leads to numerous artifacts in 3D reconstruction after structure removal, which hinders accurate space construction. This study proposes a system that integrates 3D Gaussian splatting, capable of high-quality 3D reconstruction through machine learning, and image completion processing using a diffusion model. This integration aims to reduce the impact of artifacts in 3D reconstruction after building removal in complex and large-scale urban areas. This will contribute to the intuitive understanding and decision-making of non-experts, such as residents, in future landscape assessments after building removal.
keywords	3D reconstruction, diffusion model, landscape visualization, view synthesis, real-time rendering, 3D Gaussian splatting
series	eCAADe
email
last changed	2024/11/17 22:05

_id	ecaade2024_60
id	ecaade2024_60
authors	Wan, Zijun; Sun, Shuaibing; Meng, Fanjing; Yan, Yu
year	2024
title	How Augment Reality Support Public Participation in the Urban Design Decision-Making: A ten - year literature review
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. 455–464
doi	https://doi.org/10.52842/conf.ecaade.2024.2.455
summary	Emerging applications of AR have demonstrated its powerful visualization capabilities, which is a potential solution to enhance public participation in the urban design process. However, there is still a lack of complete understanding of how AR gets involved in this decision-making process. Therefore, this paper reviews 33 empirical studies relating to the topic through the four steps of “PRISMA”. The results indicate that the quantity and quality of research is increasing yearly. As AR technology progresses, the techniques and research methods used in those studies show a trend toward diversification and customization; this has also led to a shift in the scale of urban design from large and abstract to small and concrete. In terms of content, the topics have gradually changed from “people group” to “technology”, and then to “environment”. Notably, a small number of cases in tangible interaction and multi-user collaboration have emerged from 2020 — areas showing great promise. In terms of user assessments, most studies give positive feedback, but there are currently concerns about problems in poor AR visualizations, privacy risks, and the social inequality caused by technical affordance.
keywords	Augment reality, Urban design and planning, Public participation, Collaborative and participative design, Design decision-making
series	eCAADe
email
last changed	2024/11/17 22:05

_id	caadria2024_514
id	caadria2024_514
authors	Yildiz, Burak, Cuartero, Javier, Mostafavi, Fatemeh and Khademi, Seyran
year	2024
title	BatchPlan: A Large Scale Solution for Floor Plan Extraction
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 1, pp. 201–210
doi	https://doi.org/10.52842/conf.caadria.2024.1.201
summary	The development of Building Information Modelling (BIM) has enabled new opportunities, such as standard data storage and collaborative building design. Moreover, there exist many Life Cycle Assessment (LCA) tools and Building Energy Performance (BEP) simulators that use the Industry Foundation Classes (IFC) exports of BIM platforms as input for further operational analysis. While the extracted IFC files contain numerical and tabular data from the BIM model, the visual data including floor plans and section drawings is often obtained directly from the original 3D software such as REVIT. In this study, we introduce an open-source solution, BatchPlan, for batch processing IFC files of medium- and high-rise building projects, leading to floor plan extraction on a large scale. Furthermore, we have designed a user-friendly graphical interface that allows users to select floors manually. BatchPlan is based on open-source Python packages; thus users can easily edit and adapt it to their specific requirements. The presented solution enables a scalable data generation pipeline for downstream tasks that require extensive quantitative analysis, such as machine learning models to perform material detection, volume estimation, and environmental impact prediction.
keywords	floor plan extraction, Industry Foundation Classes (IFC), Building Information Modelling (BIM), architectural technical drawings, big data
series	CAADRIA
email
last changed	2024/11/17 22:05

_id	ecaade2024_47
id	ecaade2024_47
authors	Alymani, Abdulrahman Ahmed A
year	2024
title	Integrating Artificial Intelligence Rendering Tools in Design: Integrating AI as teaching methods in architectural education
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. 629–638
doi	https://doi.org/10.52842/conf.ecaade.2024.2.629
summary	This paper introduces an innovative teaching approach for architectural design studios, emphasizing the integration of AI-rendering tools to enhance student learning and creativity. The method begins with conventional site analysis, followed by an in-depth study of a micro-home case study to deepen understanding. Students’ progress from traditional 2D plans to conceptual 3D massing, facing challenges in integrating case studies into their designs. To address this, an AI-rendering engine is incorporated, allowing students to add intricate details and apply various case studies directly onto their 3D models. This visual approach aids understanding and application of architectural concepts. The paper discusses how this approach helps students overcome integration challenges and fosters creative exploration. Findings suggest that this method enriches architectural education, offering a new dimension to design studio learning.
keywords	Architectural Pedagogy, AI-Rendering Tools, Architecture Precedents, Architecture Case Study, Design Studios
series	eCAADe
email
last changed	2024/11/17 22:05

_id	caadria2024_498
id	caadria2024_498
authors	Deng, Yingxin and Li, Yang
year	2024
title	Assessing Path Choosing in Mountainous Cities via Pedestrian Network Data and Subway Station Observations: A Case Study of Jiefangbei, Chongqing
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. 355–364
doi	https://doi.org/10.52842/conf.caadria.2024.2.355
summary	In high-density mountainous cities, pedestrian system becomes more challenging due to terrain constraints, which amplifies the difficulty associated with walking. Consequently, many individuals opt "subway + walking" as their primary mode of travel, which is deemed more efficient. This research focuses on a case study in the Jiefangbei area of Chongqing, known for its intricate terrain and dense urban fabric, and assesses people's walking selection around subway stations within 10-minute walking isochrone. It employs space syntax with weighted topographical street network to establish an evaluation system. The evaluation system comprises three primary indicators: road accessibility, walking attractiveness and walking efficiency. It encompasses both the physical and perceptual factors influencing people's walking preferences in the walking system. This research utilizes python to crawl POI points, Arcgis and sDNA to process and visualize data and JS divergence for final similarity analysis. By conducting an in-depth assessment of the walking system around subway stations in mountainous urban areas, this paper attempts to provide strategies aimed at enhancing the walkability in mountainous cities.
keywords	Walkability, Path choosing, Spatial Design Network Analysis, Pedestrian network, Mountainous city, Weighted Network Analysis
series	CAADRIA
email
last changed	2024/11/17 22:05

_id	caadria2024_331
id	caadria2024_331
authors	Gao, Naixiang
year	2024
title	Interactive Mediatised Urbanism: Shaping High Emotional Value Food Consumption Spaces With Human Data on Social Media
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. 415–424
doi	https://doi.org/10.52842/conf.caadria.2024.2.415
summary	Research in the field of shaping urban spaces with emotional values on social media is still lacking. This paper attempts to shape an urban food consumption space with high emotional value through digital interactive media consisting of machine learning and other algorithmic processing of the emotional values contained in images of urban food consumption venues posted by humans on social media for the food consumption process. Images on social media that contain geographic information on the food market with research conditions are used as the data source, which is filtered by algorithms for the emotional value data. The filtered images are put into a machine learning model for training, resulting in a series of spatial images containing high emotional values, which are used as learning objects for the pictures entered by the user community at the input side of the system. The depth information in the output objects is read to transform them into spatial models, and the information from these virtual spatial models that have been learned for higher emotional values is the output of user interactions and the basis for improving the food consumption space.
keywords	social media database, human-urban interactive media, computer visualization, image-to-model, food consumption space, emotional values, machine learning, AR interface
series	CAADRIA
email
last changed	2024/11/17 22:05

_id	caadria2024_198
id	caadria2024_198
authors	Shi, Zewei, Wang, Xiaoxin, Wang, Jinyu, Wang, Yu, Jian, Yixin, Huang, Chenyu and Yao, Jiawei
year	2024
title	A Method for Real-Time Prediction of Indoor Natural Ventilation in Residential Buildings
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 1, pp. 9–18
doi	https://doi.org/10.52842/conf.caadria.2024.1.009
summary	Against the backdrop of energy crises and climate change, performance-oriented architectural design is increasingly gaining attention. Early-stage assessment of natural ventilation performance is crucial for optimizing designs to enhance indoor environmental comfort and reduce building energy consumption. However, traditional numerical simulations are time-consuming, and existing data-driven surrogate models primarily focus on predicting partial indicators in indoor airflow or single-space airflow. Predicting the spatial distribution of airflow is more advantageous for addressing global issues in building layout design. This paper introduces a surrogate model based on Generative Adversarial Networks. We constructed a dataset of floor plans, with 80% of the data generated using parameterized methods and 20% sourced from real-world examples. We developed a 3D encoding method for the floor plans to facilitate machine understanding of spatial depth and structure. Finally, we conducted airflow simulations on the dataset, with the simulated results used to train the Pix2pix model. The results demonstrate that the Pix2pix model can predict indoor airflow distribution with high accuracy, requiring only 0.8 seconds. In the test set, the average values for MAPE, SSIM, and R2 are 2.6113%, 0.9798, and 0.9114, respectively. Our research can improve architectural design, enhance energy efficiency, and enhance residents' comfort, thereby contributing to the creation of healthier indoor environments.
keywords	generative residential buildings, natural indoor ventilation, early design stage, real-time prediction, generative adversarial networks (GAN)
series	CAADRIA
email
last changed	2024/11/17 22:05

_id	caadria2024_360
id	caadria2024_360
authors	Adelzadeh, Amin, Karimian-Aliabadi, Hamed and Robeller, Christopher
year	2024
title	ReciproFrame Timber Gridshell: From CAM Data Interface Modeling to Operating Industrial Joinery Machine for Scaling up Reusable Timber Structures
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. 339–348
doi	https://doi.org/10.52842/conf.caadria.2024.3.339
summary	This research extends the work from our previous study on utilizing digital technologies to turn short solid timber elements into framed timber systems designed for the rapid assembly and disassembly of cost-effective, material-efficient, reusable gridshells. In a former paper, we developed an innovative reciprocally-reinforced topology of trivalent polyhedral frames, termed "ReciproFrame", enabled by the development of a CSV file to leverage the precision and speed of multi-axis robotic arms, which was then utilized in the construction of a small-scale, 7.5-meter research demonstrator. Although the multi-objective analysis confirmed the efficiency of the production method in constructing structurally-efficient catenary cross-sections without the need for any steel nodes—a feat not achievable with previous geodesic domes—we realized that the automated construction of larger structures in future timber industry would require an industrial-class production workflow featuring high-performance units equipped with powerful and efficient machining capacities for varied timber processing. As a solution, this paper presents a 24-hour industrial fabrication workflow, enabled by a self-developed data interface plugin that generates XML-based, industry-standard CAM data for the direct instruction of Hundegger K2 machines. It addresses the operational problems and technical challenges related to interoperability between the data interface programming and the operation of industrial joinery machines. Finally, the paper discusses the possible applications and limitations of the production workflow, while presenting the design-to-assembly process of a medium-scale research demonstrator with a maximum span of 15 meters, made of 768 industrially-fabricated Laminated Veneer Lumber (LVL) beams.
keywords	automated joinery, XML-based CAM data, CAMBIUM, Hundegger K2 joinery machines, P-Hex, ReciproFrame, Laminated Veneer Lumber LVL, reusable timber gridshells
series	CAADRIA
email
last changed	2024/11/17 22:05

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