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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Reformat results as: short short into frame detailed detailed into frame

_id	ecaade2022_312
id	ecaade2022_312
authors	Bhagat, Puja and Gursoy, Benay
year	2022
title	Stretch – 3D Print – Release: Formal descriptions of shape-change in 3D printed shapes on stretched fabrics
doi	https://doi.org/10.52842/conf.ecaade.2022.1.301
source	Pak, B, Wurzer, G and Stouffs, R (eds.), Co-creating the Future: Inclusion in and through Design - Proceedings of the 40th Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2022) - Volume 1, Ghent, 13-16 September 2022, pp. 301–310
summary	Researchers have previously explored 3D printing 2D shapes on stretched fabrics using plastic filaments. When released, the 3D printed plastic constrains the fabric to take a 3D form. By leveraging the material properties and resultant tension between the rigid plastic and pliable fabric, it is possible to create 3D forms which would otherwise be difficult to construct with traditional fabrication techniques. Multiple factors are in play in this shape-change. Therefore, it is often difficult to anticipate the 3D form that will emerge when the stretched fabric is released. In this paper, we present our systematic bottom-up explorations on the effects of various parameters on shape-change and formalize our findings as rules. These rules help to visualize the interrelations between (abstract) shapes designed for 3D printing, (material) shapes 3D printed on stretched fabric, and (material) shapes that emerge when the fabric is released. The rules also help to explore design possibilities with this technique in a more controlled, communicable, and repeatable way. We also present a series of vaulted forms that we generated using these rules and by stretching - 3D printing - releasing the fabric.
keywords	Material Computing, Shape-change, Adaptive Architecture, Digital Fabrication, 3D Printing on Textiles
series	eCAADe
email
last changed	2024/04/22 07:10

_id	ijac202220212
id	ijac202220212
authors	Castriotto, Caio; Felipe Tavares; Gabriela Celani; Olga Popovic Larsen; Xan Browne
year	2022
title	Clamp links: A novel type of reciprocal frame connection
source	International Journal of Architectural Computing 2022, Vol. 20 - no. 2, pp. 378–399
summary	Reciprocal frames (RFs) are complex structural systems based on mutual support between elements. One of the main challenges for these structures is achieving geometrical complexity with ease for assembly. This paper describes the development of a new type of connection for RF that uses a single bolt to fix a whole fan. The method used was the Research Through Design, using algorithmic modelling and virtual and physical prototyping. After the exploration of different alternatives, the connection selected was structurally evaluated with a 3D solid finite element analysis (FEM) software and a 2D bar parametric model. Finally, a fullscale pavilion was built as a proof-of-concept. A total of 47 connections were fabricated using four 3D-printed templates combined with a hand router. The construction allowed us to draw conclusions on the connection design and the assembly method, and the process as a whole can contribute to the development of new structural links and production methods.
keywords	Reciprocal frames, connections, computational design, simulations, digital fabrication
series	journal
last changed	2024/04/17 14:29

_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	ecaade2022_175
id	ecaade2022_175
authors	Di Carlo, Raffaele, Mittal, Divyae and Vesely, Ondrej
year	2022
title	Generating 3D Building Volumes for a Given Urban Context using Pix2Pix GAN
doi	https://doi.org/10.52842/conf.ecaade.2022.2.287
source	Pak, B, Wurzer, G and Stouffs, R (eds.), Co-creating the Future: Inclusion in and through Design - Proceedings of the 40th Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2022) - Volume 2, Ghent, 13-16 September 2022, pp. 287–295
summary	Our ability to delegate the most intellectually demanding tasks to machines improves with each passing day. Even in the fields of architecture and design, which were previously thought to be exclusive domain of human creativity and flare, we are moving the first steps towards developing models that can capture the patterns, invisible to the naked eye, embedded in the creative process. These patterns reflect ideas and traditions, imprinted in the collective mind over the course of history, that can be improved upon or serve as a cautionary tale for the new generation of designers in their work of designing an equitable, more inclusive future. Generative Adversarial Networks (GANs) give us the opportunity to turn style and design into learnable features that can be used to automatically generate blueprints and layouts. In this study, we attempt to apply this technology to urban design and to the task of generating a building footprint and volume that fits within the surrounding built environment. We do so by developing a Pix2Pix model composed of a ResNet-6 generator and a Patch discriminator, applying it to satellite views of neighborhoods from across the Netherlands, and then turning the resulting 2D generated building footprint into a reusable 3D model. The model is trained using the national cadastral data and TU Delft 3D BAG dataset. The results show that it is possible to predict a building shape compatible in style and height with the surroundings. Although the model can be used for different applications, we use it as an evaluation tool to compare the design alternatives fitting the desired contextual patterns.
keywords	Generative Adversarial Networks, Urban Design, Pix2Pix, Raster Vectorization, 3D Rendering
series	eCAADe
email
last changed	2024/04/22 07:10

_id	ecaade2022_278
id	ecaade2022_278
authors	Gopalakrishnan, Srilalitha, Srikanth, Anjanaa, Hablani, Chirag and Schroepfer, Thomas
year	2022
title	Measuring Impacts of Vertically Integrated Pedestrian Network Configurations on Urban Space Use in Dense Built Environments
doi	https://doi.org/10.52842/conf.ecaade.2022.2.307
source	Pak, B, Wurzer, G and Stouffs, R (eds.), Co-creating the Future: Inclusion in and through Design - Proceedings of the 40th Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2022) - Volume 2, Ghent, 13-16 September 2022, pp. 307–316
summary	Integrated mixed-use developments are increasingly taking the form of vertical extensions of urban spaces on the ground. The spatial networks within the evolving vertical neighbourhoods, their relationships with the larger urban fabric, and the user interactions within these complex multi-layered urban built environments are numerous and varied. This paper presents an analytical framework to map and analyse the pedestrian connectivity within the vertically integrated urban open space network and its interactions with the ground level urban fabric using a Network Science-based approach. The research uses Kampung Admiralty, a first-of-its-kind building site scale 'vertical city' prototype in Singapore, as a case study. A 3d pedestrian network link model mapping the pedestrian connectivity within the development is generated and analysed to understand the flows and accessibility to the vertically distributed urban open spaces. This 3d pedestrian link model is further combined with the 2d urban walking network at the ground level to generate an integrated neighbourhood-level walkability analysis. Analysing the two-dimensional connectivity at the ground level and comparing the influence of linking the three-dimensional vertical connectivity to the ground network generates valuable design insights into the spatial performance of vertically integrated developments in their immediate urban context.
keywords	Network Science, sDNA, Urban Pedestrian Network, Vertical Urban Environments, Vertical Connectivity
series	eCAADe
email
last changed	2024/04/22 07:10

_id	caadria2022_361
id	caadria2022_361
authors	Lok, Leslie and Bae, Jiyoon
year	2022
title	Timber De-Standardized 2.0 : Mixed Reality Visualizations and User Interface for Processing Irregular Timber
doi	https://doi.org/10.52842/conf.caadria.2022.2.121
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. 121-130
summary	Timber De-Standardized 2.0†is a mixed reality (MR) user interface (UI) that utilizes timber waste produced by manufacturing dimensional lumber, suggesting an expanded notion for "material usability‚ in timber construction. The expanded notion of designing with discarded logs not only requires new tools and technologies for cataloguing, structuring, and fabricating. It also relies on new methods and platforms for the visualization and design of these structures. As a†MR†UI,†Timber De-Standardized†enables professionals and non-professionals alike to seamlessly design with irregular logs and to create viable structural systems using an intuitive†MR†environment. In order to develop a†MR†environment with this level of competency, the research aims to finesse the visualization techniques in the immersive full-scale†3D†environment and to minimize the use of alternative 2D UI(s). The research methodology†focuses on†(1) cataloguing and extracting basic properties of various tree logs, (2)†refining mesh visualization for better user interaction, and†(3)†developing†the†MR†UI to increase user design agency with custom menu lists and operations.†This methodology will extend the usability of†MR†UI protocols to a broader audience while democratizing design and enabling the user as co-creator.
keywords	Irregular Tree Logs, Wood Construction, Augmented and Mixed Realities, Mixed Reality User Interface, Co-Creative Design, Digital representation and visualization, SDG 9, SDG 12, SDG 13
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_405
id	caadria2022_405
authors	Onishi, Ryo, Fukuda, Tomohiro and Yabuki, Nobuyoshi
year	2022
title	A Remote Sharing Method of 3D Physical Objects Using Instance-Segmented Real-Time 3D Point Cloud for Design Meeting
doi	https://doi.org/10.52842/conf.caadria.2022.2.395
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. 395-404
summary	In the field of architecture and urban design, physical models are used in design meetings. Furthermore, teleconferencing via the internet has begun to be widely used in society due to COVID-19 and in preparation for disasters. Although conventional web conferencing can share only 2D information through screens, it is expected that interactive screen sharing of physical objects will enable smoother remote conferencing. A system that can manipulate point clouds in clusters by dividing real-time point clouds captured from 3D real objects by distance has been reported as a way to share physical objects. However, because the point clouds are divided by distance between the two clusters when the point clouds get closer than some threshold, they become treated as a single object. In this study, we aim to develop a system that uses instance segmentation to divide point clouds by region rather than by distance between objects. This system is expected to contribute to the realisation of better architectural and urban design processes without any misunderstandings among the parties involved and to the reduction of unnecessary energy consumption due to travel for face-to-face meetings.
keywords	remote meeting, fast point cloud, instance segmentation, three-dimensional remote sharing, mixed reality, SDG 11, SDG 13
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_177
id	caadria2022_177
authors	Pan, Yongjie and Zhang, Tong
year	2022
title	Outdoor Thermal Environment Assessment of Existing Residential Areas Supported by UAV Thermal Infrared and 3D Reconstruction Technology
doi	https://doi.org/10.52842/conf.caadria.2022.2.729
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. 729-738
summary	The underlying surface temperature is an effective evaluation index to study the urban micro-scale thermal environment. For surface temperature acquisition, the thermal infrared camera mounted on a unmanned aerial vehicle (UAV) can reduce field work intensity, improve data collection efficiency, and ensure high accuracy at low cost. In order to convert the 2D thermal image into a more intuitive 3D thermal model, the UAV-based thermal infrared 3D reconstruction is adopted. The key element of thermal infrared 3D model reconstruction lies in the processing of thermal infrared images with low resolution and different temperature scales. In order to improve the quality of the final thermal 3D model, this paper proposes the reconstruction of the detailed 3D mesh using visible images (higher resolution), and map then mapping thermal textures onto the mesh using thermal images (low resolution). In addition, absolute temperature values are extracted from thermal images with different temperature ranges to ensure consistence between color and temperature values in the reconstructed thermal 3D model. The thermal 3D model generated for an existing residential area in Nanjing successfully displays the temperature distribution of the underlying surface and provides a valuable basis for outdoor thermal environment assessment.
keywords	Thermal image, UAV, 3D reconstruction, Residential outdoor space, Underlying surface temperature, SDG 3, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	cdrf2022_359
id	cdrf2022_359
authors	Qiaoming Deng, Xiaofeng Li, and Yubo Liu
year	2022
title	Using Pix2Pix to Achieve the Spatial Refinement and Transformation of Taihu Stone
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_31
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
summary	Under the impact of globalization, the transformation of traditional architectural space is particularly important for the development of local architecture. As an important spatial component of traditional gardens, Taihu stone has the image characteristics of “thin, wrinkled, leaky and transparent”. The “transparency” and “ leaky” of Taihu stone reflect the connectivity and irregularity of the holes of Taihu stone, which are in line with the ideas of flowing space and transparency in contemporary architectural design. However, there are relatively few theoretical studies on the spatial analysis and design transformation of Taihu stone. The Pix2Pix model extracts the 3D spatial variation pattern by learning the variation pattern between two adjacent slices of Taihu stone. The trained Pix2Pix model can generate a series of continuous spatial sections with the spatial variation pattern of Taihu stone. Finally, the 2D sections are transformed into 3D building volumes to complete the spatial translation of Taihu stone in contemporary architectural design. In addition, this paper also provides a new idea for machine learning to master the continuous 3D spatial change pattern.
series	cdrf
email
last changed	2024/05/29 14:03

_id	ascaad2022_018
id	ascaad2022_018
authors	Song, Yang; Agkathidis, Asterios; Koeck, Richard
year	2022
title	Augmented Masonry Design: A Design Method using Augmented Reality (AR) for Customized Bricklaying Design Algorithms
source	Hybrid Spaces of the Metaverse - Architecture in the Age of the Metaverse: Opportunities and Potentials [10th ASCAAD Conference Proceedings] Debbieh (Lebanon) [Virtual Conference] 12-13 October 2022, pp. 703-712
summary	The Augmented Masonry Design project presents experimental research about developing and applying Augmented Reality (AR) technology for customized design algorithms, exploring a real-time, interactive, and spatial-free design method for the early architectural design stage. We aim to resolve the current 2D-based design limitations and provide architects with a 3D-4D immersive perception in AR for a practical and easy-to-use design method. Furthermore, with reference to the Covid-19 pandemic, we propose that this method could break through site accessibility and constraints by breaking the barriers of physical space. Towards this aim, we apply the Augmented Masonry Design into two prototypes: a) user interface (UI) immersive design, in which interactive inputs will communicate with design algorithms in AR through the inputs from the screen-based UI on mobile devices (e.g., smartphones and tablets); b) intuitive interaction immersive design, in which interactive inputs will be translated to design algorithms directly in AR through hand gestures on head-mounted devices (HMD) (e.g., Microsoft HoloLens). Our Findings highlight the advantages of immersive design in the initial stage of architectural drafts, which gives designers better spatial understanding and design creativity, as well as the challenges arising from the limitations of current AR devices and the lack of real physical simulation in the design system.
series	ASCAAD
email
last changed	2024/02/16 13:24

_id	caadria2022_507
id	caadria2022_507
authors	Bolojan, Daniel, Vermisso, Emmanouil and Yousif, Shermeen
year	2022
title	Is Language All We Need? A Query Into Architectural Semantics Using a Multimodal Generative Workflow
doi	https://doi.org/10.52842/conf.caadria.2022.1.353
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. 353-362
summary	This project examines how interconnected artificial intelligence (AI)-assisted workflows can address the limitations of current language-based models and streamline machine-vision related tasks for architectural design. A precise relationship between text and visual feature representation is problematic and can lead to "ambiguity‚ in the interpretation of the morphological/tectonic complexity of a building. Textual representation of a design concept only addresses spatial complexity in a reductionist way, since the outcome of the design process is co-dependent on multiple interrelated systems, according to systems theory (Alexander 1968). We propose herewith a process of feature disentanglement (using low level features, i.e., composition) within an interconnected generative adversarial networks (GANs) workflow. The insertion of natural language models within the proposed workflow can help mitigate the semantic distance between different domains and guide the encoding of semantic information throughout a domain transfer process.
keywords	Neural Language Models, GAN, Domain Transfer, Design Agency, Semantic Encoding, SDG 9
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	ijac202220310
id	ijac202220310
authors	Castro Henriques, Goncalo; Pedro Maciel Xavier; Victor de Luca Silva; Luca Rédua Bispo; Joao Victor Fraga
year	2022
title	Computation for Architecture, hybrid visual and textual language: Research developments and considerations about the implementation of structural imperative and object-oriented paradigms
source	International Journal of Architectural Computing 2022, Vol. 20 - no. 3, pp. 673–687
summary	In the fourth industrial revolution, programming promises to be a fundamental subject like mathematics, science, languages or the arts. Architects design more than buildings developing innovative methods and they are among the pioneers in visual programming development. However, after more than 10 years of visual programming in architecture, despite the fast-learning curve, visual programming presents considerable limitations to solve complex problems. To overcome limitations, the authors propose to associate the advantages of visual and textual languages in Python. The article addresses an ongoing research study to implement Computational Methods in Architectural Education. The authors began by describing the general goal of this project, and of this article in particular. This article focuses on the implementation of two disciplines ‘Computation for Architecture in Python’ I and II. The first discipline uses programming based on the construction of functions in the imperative language, implemented in the text editor, in visual programming, using Grasshopper methods. The second discipline, which is under development, intends to teach object-oriented programming. The results of the first discipline are encouraging; despite reported difficulties in programming fundamentals, such as lists, loops and recursion. The development of the second discipline, in object-oriented programming, deals with the concepts of classes and objects, and more abstract principles such abstraction, inheritance, polymorphism or encapsulation. This paradigm allows building robust programs, but requires a more in-depth syntax. The article reports this ongoing research on this new paradigm of object-oriented language, expanding the application of a hybrid visual-textual language in Architecture
keywords	computation, textual programming, visual programming, imperative programming, object oriented programming
series	journal
last changed	2024/04/17 14:30

_id	caadria2024_186
id	caadria2024_186
authors	Huang, Jingfei and Tu, Han
year	2024
title	Inconsistent Affective Reaction: Sentiment of Perception and Opinion in Urban Environments
doi	https://doi.org/10.52842/conf.caadria.2024.2.395
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. 395–404
summary	The ascension of social media platforms has transformed our understanding of urban environments, giving rise to nuanced variations in sentiment reaction embedded within human perception and opinion, and challenging existing multidimensional sentiment analysis approaches in urban studies. This study presents novel methodologies for identifying and elucidating sentiment inconsistency, constructing a dataset encompassing 140,750 Baidu and Tencent Street view images to measure perceptions, and 984,024 Weibo social media text posts to measure opinions. A reaction index is developed, integrating object detection and natural language processing techniques to classify sentiment in Beijing Second Ring for 2016 and 2022. Classified sentiment reaction is analysed and visualized using regression analysis, image segmentation, and word frequency based on land-use distribution to discern underlying factors. The perception affective reaction trend map reveals a shift toward more evenly distributed positive sentiment, while the opinion affective reaction trend map shows more extreme changes. Our mismatch map indicates significant disparities between the sentiments of human perception and opinion of urban areas over the years. Changes in sentiment reactions have significant relationships with elements such as dense buildings and pedestrian presence. Our inconsistent maps present perception and opinion sentiments before and after the pandemic and offer potential explanations and directions for environmental management, in formulating strategies for urban renewal.
keywords	Urban Sentiment, Affective Reaction, Social Media, Machine Learning, Urban Data, Image Segmentation.
series	CAADRIA
email
last changed	2024/11/17 22:05

_id	cdrf2022_199
id	cdrf2022_199
authors	Jingming Li
year	2022
title	Using Text Understanding to Create Formatted Semantic Web from BIM
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_17
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
summary	The application of BIM in the building life cycle needs to be continuous. The information collected and accumulated in the early stages should flow to the subsequent phases. However, BIM applications currently focus on collision inspection, compliance inspection, and engineering calculation, few models can be successively used in the following stages. Remodeling is required in the operation and maintenance period, resulting in waste. Meanwhile, some of the information accumulated by BIM might be frequently used in the operation and maintenance stage, while some data are relatively rarely used. The semantic web can help manage building information at all stages. But the generation of a semantic web is mostly manually completed. It is necessary to standardize the repeated semantic description in the model and convert BIM into a standard semantic model for information indexing, reducing the resource consumption of model loading and optimizing the efficiency of the operation and maintenance system. When the existing research transforms from BIM to the semantic web, there will be a lack of information and descriptions of the ownership relationship between entities due to the limitation of formats. To realize the standard transformation from BIM to the semantic web, this work proposes a method of using Natural Language Processing (NLP) to understand the text and infer the relationship between entities according to the knowledge map. First, the entities are extracted from BIM, such as air conditioning unit, electric lamp, fan, etc., if the name of the extracted entity is irregular, the names are translated with the help of NLP and Ontology (such as brick or haystack) to obtain the standard definition. By comparing the complete knowledge graph (such as the knowledge graph of the air conditioning system), the relationships can be deduced, and then a standardized semantic model can be generated.
series	cdrf
email
last changed	2024/05/29 14:02

_id	ijac202321201
id	ijac202321201
authors	Steinfeld, Kyle
year	2023
title	Clever little tricks: A socio-technical history of text-to-image generative models
source	International Journal of Architectural Computing 2023, Vol. 21 - no. 2, 211–241
summary	The emergence of text-to-image generative models (e.g., Midjourney, DALL-E 2, Stable Diffusion) in the summer of 2022 impacted architectural visual culture suddenly, severely, and seemingly out of nowhere. To contextualize this phenomenon, this text offers a socio-technical history of text-to-image generative systems. Three moments in time, or “scenes,” are presented here: the first at the advent of AI in the middle of the last century; the second at the “reawakening” of a specific approach to machine learning at the turn of this century; the third that documents a rapid sequence of innovations, dubbed “clever little tricks,” that occurred across just 18 months. This final scene is the crux, and represents the first formal documentation of the recent history of a specific set of informal innovations. These innovations were produced by non-affiliated researchers and communities of creative contributors, and directly led to the technologies that so compellingly captured the architectural imagination in the summer of 2022. Across these scenes, we examine the technologies, application domains, infrastructures, social contexts, and practices that drive technical research and shape creative practice in this space.
keywords	Machine learning, text-to-image, socio-technical study, generative AI
series	journal
last changed	2024/04/17 14:30

_id	sigradi2022_258
id	sigradi2022_258
authors	Taºdelen, Hanife Sümeyye; Gül, Leman Figen
year	2022
title	The analysis of architectural discourse in the context of computational public opinion: Data mining of Google map reviews
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. 101–112
summary	New media platforms and mapping tools are created by digital communities, and their representations influence public opinion. Crowdsourcing platforms such as Twitter, Instagram, Google search engines and Maps have no such limitations or boundaries as in the physical space, these platforms are creating new virtual public places. To assess and forecast the accessibility and aesthetic issues of urban spaces in Istanbul, text and image data from Google Maps were employed. In this study, we searched at the reviews of certain public/semi-public places by using text mining and image analytics tools. Recently designed or renovated 11 public buildings and open places were chosen. The main findings of this exploratory study are that; 1) the level of being public can be understood from the crowdsourcing, 2) image analytics of crowdsourced visual data can assist to identify the aesthetic quality, and 3) the accessibility capacity of public spaces can be identified.
keywords	Data Analytics, Public Spaces, Architectural Criticism, Collaborative Map, Accessibility-Aesthetic issues
series	SIGraDi
email
last changed	2023/05/16 16:55

_id	ecaade2022_234
id	ecaade2022_234
authors	Afsar, Secil, Estévez, Alberto T., Abdallah, Yomna K., Turhan, Gozde Damla, Ozel, Berfin and Doyuran, Aslihan
year	2022
title	Activating Co-Creation Methodologies of 3D Printing with Biocomposites Developed from Local Organic Wastes
doi	https://doi.org/10.52842/conf.ecaade.2022.1.215
source	Pak, B, Wurzer, G and Stouffs, R (eds.), Co-creating the Future: Inclusion in and through Design - Proceedings of the 40th Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2022) - Volume 1, Ghent, 13-16 September 2022, pp. 215–224
summary	Compared to the take-make-waste-oriented linear economy model, the circular model has been studied since the 1980s. Due to consumption-oriented lifestyles along with having a tendency of considering waste materials as trash, studies on sustainable materials management (SMM) have remained at a theoretical level or created temporary and limited impacts. To ensure SMM supports The European Green Deal, there is a necessity of developing top-down and bottom-up strategies simultaneously, which can be metaphorized as digging a tunnel from two different directions to meet in the middle of a mountain. In parallel with the New European Bauhaus concept, this research aims to create a case study for boosting bottom-up and data-driven methodologies to produce short-loop products made of bio-based biocomposite materials from local food & organic wastes. The Architecture departments of two universities from different countries collaborated to practice these design democratization methodologies using data transfer paths. The 3D printable models, firmware code, and detailed explanation of working with a customized 3D printer paste extruder were shared using online tools. Accordingly, the bio-based biocomposite recipe from eggshell, xanthan gum, and citric acid, which can be provided from local shops, food & organic wastes, was investigated concurrently to enhance its printability feature for generating interior design elements such as a vase or vertical gardening unit. While sharing each step from open-source platforms with adding snapshots and videos allows further development between two universities, it also makes room for other researchers/makers/designers to replicate the process/product. By combining modern manufacturing and traditional crafting methods with materials produced with DIY techniques from local resources, and using global data transfer platforms to transfer data instead of products themselves, this research seeks to unlock the value of co-creative design practices for SMM.
keywords	Sustainable Materials Management, Co-Creation, Food Waste, 3D Printing, New European Bauhaus
series	eCAADe
email
last changed	2024/04/22 07:10

_id	caadria2022_277
id	caadria2022_277
authors	Akbar, Zuardin, Wood, Dylan, Kiesewetter, Laura, Menges, Achim and Wortmann, Thomas
year	2022
title	A Data-Driven Workflow for Modelling Self-Shaping Wood Bilayer, Utilizing Natural Material Variations with Machine Vision and Machine Learning
doi	https://doi.org/10.52842/conf.caadria.2022.1.393
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. 393-402
summary	This paper develops a workflow to train machine learning (ML) models with a small dataset from physical samples to predict the curvatures of self-shaping wood bilayers based on local variations in the grain. In contrast to state-of-the-art predictive models, specifically 1.) a 2D Timoshenko model and 2.) a 3D numerical model with a rheological model, our method accounts for natural and unavoidable material variations. In this paper, we only focus on local grain variations as the main driver for curvatures in small-scale material samples. We extracted a feature matrix from grain images of active and passive layers as a Grey Level Co-Occurrence Matrix and used it as the input for our ML models. We also analysed the impact of grain variations on the feature matrix. We trained and tested several tree-based regression models with different features. The models achieved very accurate predictions for curvatures in each sample (R;0.9) and extend the range of parameters that is incalculable by a Timoshenko model. This research contributes to the material-efficient design of weather-responsive shape-changing wood structures by further leveraging the use of natural material features and explainable data-driven modelling and extends the topic in ML for material behaviour-driven design among the CAADRIA community.
keywords	data-driven model, machine learning, material programming, smart material, timber structure, SDG 12
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	ascaad2022_014
id	ascaad2022_014
authors	Alani, Mostafa; Alacam, Sema
year	2022
title	Beyond Flat Surfaces: Parametric Derivations of Historical Islamic Geometric Designs
source	Hybrid Spaces of the Metaverse - Architecture in the Age of the Metaverse: Opportunities and Potentials [10th ASCAAD Conference Proceedings] Debbieh (Lebanon) [Virtual Conference] 12-13 October 2022, pp. 451-462
summary	This paper sets out to identify a guiding methodology and define algorithms to extend the existence of Islamic geometric designs beyond flat surfaces. The paper discusses two computational approaches to deriving various non-flat geometric compositions: Euclidean Point Extrusion and Curved Surface Fitting. The paper examines historical precedents, conducts an in-depth analysis of patterns employed to generate those elements, then establishes a computational process to explore the potential of translating 2D Islamic Geometric Designs into 3D non-flat surfaces.
series	ASCAAD
email
last changed	2024/02/16 13:24

_id	acadia22_58
id	acadia22_58
authors	Anton, Ana; Skevaki, Eleni; Bischof, Patrick; Reiter, Lex; Dillenburger, Benjamin
year	2022
title	Column-Slab Interfaces for 3D Concrete Printing
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. 58-67.
summary	3D Concrete Printing (3DCP) currently dominates the scene of digital fabrication with concrete. 3DCP can be utilized on-site or in prefabrication setups. While prefabrication with 3DCP allows for more complex construction elements, it also requires the design for connections and assembly. In the context of prefabrication using 3DCP, this paper illustrates the state of research in the design, construction, and assembly of 3D printed components. It proposes segmentation and fabrication strategies to produce horizontal and vertical structural members of a column-slab building system following the typology of mushroom slabs.
series	ACADIA
type	paper
email
last changed	2024/02/06 14:00

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