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	caadria2020_272
id	caadria2020_272
authors	Erhan, Halil, Abuzuraiq, Ahmed M., Zarei, Maryam, AlSalman, Osama, Woodbury, Robert and Dill, John
year	2020
title	What do Design Data say About Your Model? - A Case Study on Reliability and Validity
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 557-567
doi	https://doi.org/10.52842/conf.caadria.2020.1.557
summary	Parametric modeling systems are widely used in architectural design. Their use for designing complex built environments raises important practical challenges when composed by multiple people with diverse interests and using mostly unverified computational modules. Through a case study, we investigate possible concerns identifiable from a real-world collaborative design setting and how such concerns can be revealed through interactive data visualizations of parametric models. We then present our approach for resolving these concerns using a design analytic workflow for examine their reliability and validity. We summarize the lessons learnt from the case study, such as the importance of an abundance of test cases, reproducible design instances, accessing and interacting with data during all phases of design, and seeking high cohesion and decoupling between design geometry and evaluation components. We suggest a systematic integration of design modeling and analytics for enhancing a reliable design decision-making.
keywords	Model Reliability; Model Validity; Parametric Modeling; Design Analytics; Design Visualization
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	caadria2020_188
id	caadria2020_188
authors	Suzuki, Takaharu, Ikeda, Hikaru, Takeuchi, Issei, Matsunaga, Fumiya, Sumitomo, Eri and Ikeda, Yasushi
year	2020
title	Holonavi - A study on User Interface for Assembly Guidance System with Mixed Reality in a Timber Craft of Architecture
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 691-700
doi	https://doi.org/10.52842/conf.caadria.2020.1.691
summary	This paper introduces ideas to use Mixed Reality (MR) technologies in craftsman's work of architecture.One of the backgrounds of this study is emerging technology of Mixed Reality becoming much easier to use recently with new devices such as Microsoft Hololens. Among many possible applications of this technique in architectural work, we particularly choose Japanese traditional timber joinery 'Kumiki' as a model case of complicated architectural work.We found that people need a certain sense of 3D recognition and knowledge about right order of assemble. That is what we can suggest for users with our MR guidance system named 'Holonavi' which can show appropriate information in 3D vision in real time. The aim of our research is to find useful knowledge about effective ways and sufficient information to guide users. As a conclusion, we found that guidance with MR technology gives users to have a recognition more effectively for take of right action when they are moving their viewpoint around the object and when they located in the range of reachable distance to the objects. It is the first achievement for use of 'Holonavi' to let people feel more fun to craft something by their hands aided by computer.
keywords	Craftsmanâ€™s work; Mixed Reality; Digital Construction; Augmented Reality; Hololens
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	caadria2020_431
id	caadria2020_431
authors	Kim, Jong Bum, Balakrishnan, Bimal and Aman, Jayedi
year	2020
title	Environmental Performance-based Community Development - A parametric simulation framework for Smart Growth development in the United States
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 873-882
doi	https://doi.org/10.52842/conf.caadria.2020.1.873
summary	Smart Growth is an urban design movement initiated by Environmental Protection Agency (EPA) in the United States (Smart Growth America, 2019). The regulations of Smart Growth control urban morphologies such as building height, use, position, section configurations, faÃ§ade configurations, and materials, which have an explicit association with energy performances. This research aims to analyze and visualize the impact of Smart Growth developments on environmental performances. This paper presents a parametric modeling and simulation framework for Smart Growth developments that can model the potential community development scenarios, simulate the environmental footprints of each parcel, and visualize the results of modeling and simulation. We implemented and examined the proposed framework through a case study of two Smart Growth regulations: Columbia Unified Development Code (UDC) in Missouri (City of Columbia Missouri, 2017) and Overland Park Downtown Form-based Code (FBC) in Kansas City (City of Overland Park, 2017, 2019). Last, we discuss the implementation results, the limitations of the proposed framework, and the future work. We anticipate that the proposed method can improve stakeholders' understanding of how Smart Growth developments are associated with potential environmental footprints from an expeditious and thorough exploration of what-if scenarios of the multiple development schemes.
keywords	Smart Growth; Building Information Modeling (BIM); Parametric Simulation; Solar Radiation
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	ijac202321102
id	ijac202321102
authors	Özerol, Gizem; Semra Arslan Selçuk
year	2023
title	Machine learning in the discipline of architecture: A review on the research trends between 2014 and 2020
source	International Journal of Architectural Computing 2023, Vol. 21 - no. 1, pp. 23–41
summary	Abstract Through the recent technological developments within the fourth industrial revolution, artificial intelligence (AI) studies have had a huge impact on various disciplines such as social sciences, information communication technologies (ICTs), architecture, engineering, and construction (AEC). Regarding decision-making and forecasting systems in particular, AI and machine learning (ML) technologies have provided an opportunity to improve the mutual relationships between machines and humans. When the connection between ML and architecture is considered, it is possible to claim that there is no parallel acceleration as in other disciplines. In this study, and considering the latest breakthroughs, we focus on revealing what ML and architecture have in common. Our focal point is to reveal common points by classifying and analyzing current literature through describing the potential of ML in architecture. Studies conducted using ML techniques and subsets of AI technologies were used in this paper, and the resulting data were interpreted using the bibliometric analysis method. In order to discuss the state-of-the-art research articles which have been published between 2014 and 2020, main subjects, subsets, and keywords were refined through the search engines. The statistical figures were demonstrated as huge datasets, and the results were clearly delineated through Sankey diagrams. Thanks to bibliometric analyses of the current literature of WOS (Web of Science), CUMINCAD (Cumulative Index about publications in Computer Aided Architectural Design supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD, and CAAD futures), predictable data have been presented allowing recommendations for possible future studies for researchers.
keywords	Artificial intelligence, machine learning, deep learning, architectural research, bibliometric analysis
series	journal
last changed	2024/04/17 14:30

_id	ecaade2022_16
id	ecaade2022_16
authors	Bailey, Grayson, Kammler, Olaf, Weiser, Rene, Fuchkina, Ekaterina and Schneider, Sven
year	2022
title	Performing Immersive Virtual Environment User Studies with VREVAL
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. 437–446
doi	https://doi.org/10.52842/conf.ecaade.2022.2.437
summary	The new construction that is projected to take place between 2020 and 2040 plays a critical role in embodied carbon emissions. The change in material selection is inversely proportional to the budget as the project progresses. Given the fact that early-stage design processes often do not include environmental performance metrics, there is an opportunity to investigate a toolset that enables early-stage design processes to integrate this type of analysis into the preferred workflow of concept designers. The value here is that early-stage environmental feedback can inform the crucial decisions that are made in the beginning, giving a greater chance for a building with better environmental performance in terms of its life cycle. This paper presents the development of a tool called LearnCarbon, as a plugin of Rhino3d, used to educate architects and engineers in the early stages about the environmental impact of their design. It facilitates two neural networks trained with the Embodied Carbon Benchmark Study by Carbon Leadership Forum, which learns the relationship between building geometry, typology, and construction type with the Global Warming potential (GWP) in tons of C02 equivalent (tCO2e). The first one, a regression model, can predict the GWP based on the massing model of a building, along with information about typology and location. The second one, a classification model, predicts the construction type given a massing model and target GWP. LearnCarbon can help improve the building life cycle impact significantly through early predictions of the structure’s material and can be used as a tool for facilitating sustainable discussions between the architect and the client.
keywords	Pre-Occupancy Evaluation, Immersive Virtual Environment, Wayfinding, User Centered Design, Architectural Study Design
series	eCAADe
email
last changed	2024/04/22 07:10

_id	caadria2020_223
id	caadria2020_223
authors	Guo, Qi and Mei, Hongyuan
year	2020
title	Research on Spatial Distribution and Performance Evaluation of Mass Sports Facilities Based on Big Data of Social Media - A Case Study of Harbin
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 537-546
doi	https://doi.org/10.52842/conf.caadria.2020.1.537
summary	The extensive application of Python script provides a new opportunity for the research on spatial distribution of mass sports facilities. The traditional way to obtain geography information of POI is by the crawler of API open platform, which needs accurate search content. Therefore, it is difficult to obtain the geography information of the mass sports facilities, which do not have specific category name. The paper took Harbin City in China as an example, combined the social network address text crawler and map websites crawler, accurately obtained the geographic information of mass sports facilities, and used ArcGIS to realize the visualization of the spatial distribution information. Combined with the information of Harbin population distribution, the paper evaluated the quantity spatial distribution and type spatial distribution of mass sports facilities by Lorentz curve and Global Moran's I, aiming to evaluate the health service performance of existing mass sports facilities and provide reference for the design and planning of sports facilities. The paper draws the conclusion that the distribution of mass sports buildings in Harbin is relatively average with the population distribution and the clustering of sports function types of mass sports buildings is obvious.
keywords	mass sports facilities; spatial distribution; crawler; Lorentz curve; Global Moranâ€™s I
series	CAADRIA
email
last changed	2022/06/07 07:49

_id	ecaade2022_161
id	ecaade2022_161
authors	Kharbanda, Kritika, Papadopoulou, Iliana, Pouliou, Panagiota, Daw, Karim, Belwadi, Anirudh and Loganathan, Hariprasath
year	2022
title	LearnCarbon - A tool for machine learning prediction of global warming potential from abstract designs
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. 601–610
doi	https://doi.org/10.52842/conf.ecaade.2022.2.601
summary	The new construction that is projected to take place between 2020 and 2040 plays a critical role in embodied carbon emissions. The change in material selection is inversely proportional to the budget, as the project progresses. Given the fact that early-stage design processes often do not include environmental performance metrics, there is an opportunity to investigate a toolset that enables early-stage design processes to integrate this type of analysis into the preferred workflow of concept designers. The value here is that early-stage environmental feedback can inform the crucial decisions that are made in the beginning, giving a greater chance for a building with better environmental performance in terms of its life cycle. This paper presents the development of a tool called LearnCarbon, as a plugin of Rhino3d, used to educate architects and engineers in the early stages about the environmental impact of their design. It facilitates two neural networks trained with the Embodied Carbon Benchmark Study by Carbon Leadership Forum, which learn the relationship between building geometry, typology, and structure with the Global Warming potential in tCO2e. The first one, a regression model, is able to predict the GWP based on the massing model of a building, along with information about typology and location. The second one, a classification model, predicts the construction type given a massing model and target GWP. LearnCarbon can help improve the building life cycle impact significantly, through early predictions of the structure’s material, and can be used as a tool for facilitating sustainable discussions between the architect and the client.
keywords	Machine Learning, Carbon Emissions, LCA, Rhino Plug-in
series	eCAADe
email
last changed	2024/04/22 07:10

_id	cdrf2019_309
id	cdrf2019_309
authors	Yuliya Sinke, Sebastian Gatz, Martin Tamke, and Mette Ramsgaard Thomsen
year	2020
title	Machine Learning for Fabrication of Graded Knitted Membranes
source	Proceedings of the 2020 DigitalFUTURES The 2nd International Conference on Computational Design and Robotic Fabrication (CDRF 2020)
doi	https://doi.org/https://doi.org/10.1007/978-981-33-4400-6_29
summary	This paper examines the use of machine learning in creating digitally integrated design-to-fabrication workflows. As computational design allows for new methods of material specification and fabrication, it enables direct functional grading of material at high detail thereby tuning the design performance in response to performance criteria. However, the generation of fabrication data is often cumbersome and relies on in-depth knowledge of the fabrication processes. Parametric models that set up for automatic detailing of incremental changes, unfortunately, do not accommodate the larger topological changes to the material set up. The paper presents the speculative case study KnitVault. Based on earlier research projects Isoropia and Ombre, the study examines the use of machine learning to train models for fabrication data generation in response to desired performance criteria. KnitVault demonstrates and validates methods for shortcutting parametric interfacing and explores how the trained model can be employed in design cases that exceed the topology of the training examples.
series	cdrf
email
last changed	2022/09/29 07:51

_id	acadia20_228
id	acadia20_228
authors	Alawadhi, Mohammad; Yan, Wei
year	2020
title	BIM Hyperreality
source	ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 228-236.
doi	https://doi.org/10.52842/conf.acadia.2020.1.228
summary	Deep learning is expected to offer new opportunities and a new paradigm for the field of architecture. One such opportunity is teaching neural networks to visually understand architectural elements from the built environment. However, the availability of large training datasets is one of the biggest limitations of neural networks. Also, the vast majority of training data for visual recognition tasks is annotated by humans. In order to resolve this bottleneck, we present a concept of a hybrid system—using both building information modeling (BIM) and hyperrealistic (photorealistic) rendering—to synthesize datasets for training a neural network for building object recognition in photos. For generating our training dataset, BIMrAI, we used an existing BIM model and a corresponding photorealistically rendered model of the same building. We created methods for using renderings to train a deep learning model, trained a generative adversarial network (GAN) model using these methods, and tested the output model on real-world photos. For the specific case study presented in this paper, our results show that a neural network trained with synthetic data (i.e., photorealistic renderings and BIM-based semantic labels) can be used to identify building objects from photos without using photos in the training data. Future work can enhance the presented methods using available BIM models and renderings for more generalized mapping and description of photographed built environments.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	ecaade2020_203
id	ecaade2020_203
authors	Safin, Stéphane and Dorta, Tomás
year	2020
title	Unfolding Laypersons Creativity Through Social VR - A case study
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 1, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 355-364
doi	https://doi.org/10.52842/conf.ecaade.2020.1.355
summary	Involving laypersons in collaborative design projects faces the challenge of having an adapted representational ecosystem. There is a lack of adequate representational tools for multidisciplinary actors to graphically and physically vizualize and externalize their ideas. Using VR is a promising way of renewing participatory design, but settings with VR raise the difficulty to express ideas on the model, and to support collaboration since using VR headsets eventually hinder design communication between participants wearing them. In this paper we present the a case study of one workshop involving non-designers as participants, based on collective 3D sketches using a Social VR system (without headsets), in which several users simultaneously and immersively sketch using handheld tablets, operating a 3D model as contextual background. The workshop was supported by a representational ecosystem containing: (1) Traditional freehand sketching on paper and working with pre-cut physical components used as boundary objects to represent a scaled model; and (2) immersive 3D model allowing collective life-sized visualization, 3D sketching and interaction. The paper describers the case study and provide insights about layperson's collaborative design.
keywords	Social VR; Representational ecosystem; Laypersons participation; Co-design
series	eCAADe
email
last changed	2022/06/07 07:56

_id	caadria2020_106
id	caadria2020_106
authors	Tian, Jieren and Yu, Chuanfei
year	2020
title	Dynamic Translation of Real-world Environment Factors and Urban Design Operation in a Game Engine - A Case Study of Central District in Tiebei New Town, Nanjing
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 11-20
doi	https://doi.org/10.52842/conf.caadria.2020.2.011
summary	The building and its urban environment are complex and dynamic data systems. Designers, who make design decisions, need the design tools to simulate the built environment, to estimate the feasibility of the design. However, the static modeling software, widely used nowadays, restricts the linkage relationship between the actual data environment and the simulation model, which lacks the dynamic constraint relationship and the construction of the loop order. Different from traditional modeling and analysis tools, simulation games, with dynamic constraint rules and real-time feedback operations, provide a new way of thinking and a perspective to observe the urban, which makes the simulation game be seen as a simplified analog system, to some extent. Therefore, this paper plan to builds a city model, based on an urban design project of an urban district of Nanjing as an example, by using the Cities: Skylines, a city simulation game with priority of traffic and zoning concept. Based on this dynamic model, the next step will evaluate the original project and carry out further optimization operations in real-time.
keywords	real-time interaction; dynamic process simulation; urban environment; city simulation system; simulated game
series	CAADRIA
email
last changed	2022/06/07 07:58

_id	ecaade2020_185
id	ecaade2020_185
authors	Wurzer, Gabriel, Lorenz, Wolfgang E., Forster, Julia, Bindreiter, Stefan, Lederer, Jakob, Gassner, Andreas, Mitteregger, Mathias, Kotroczo, Erich, Pöllauer, Pia and Fellner, Johann
year	2020
title	M-DAB - Towards re-using material resources of the city
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 1, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 127-132
doi	https://doi.org/10.52842/conf.ecaade.2020.1.127
summary	If we strive for a de-carbonized future, we need to think of buildings within a city as resources that can be re-used rather than being disposed of. Together with considerations on refurbishment options and future building materials, this gives a decision field for stakeholders which depends on the current "building stock" - the set of pre-existing buildings which are characterized e.g. by building period, location and material composition. Changes in that context are hard to argue for since (1.) some depend on statistics, other (2.) on the concrete neighborhood and thus the space in which buildings are embedded, yet again others on (3.) future extrapolations again dealing with both of the aforementioned environments. To date, there exists no tool that can handle this back-and-forth between different abstraction levels and horizons in time; nor is it possible to pursue such an endeavor without a proper framework. Which is why the authors of this paper are aiming to provide one, giving a model of change in the context of re-using material resource of the city, when faced with numerous abstraction levels (spatial or abstract; past, current or future) which have feedback loops between them. The paper focuses on a concrete case study in the city of Vienna, however, chances are high that this will apply to every other building stock throughout the world if enough data is available. As a matter of fact, this approach will ensure that argumentation can happen on multiple levels (spatial, statistical, past, now and future) but keeps its focus on making the building stock of a city a resource for sustainable development.
keywords	material reuse; sustainability; waste reduction; Design and computation of urban and local systems – XS to XL; Health and materials in architecture and cities
series	eCAADe
email
last changed	2022/06/07 07:57

_id	acadia20_426
id	acadia20_426
authors	Zohier, Islam; EL Antably, Ahmed; S. Madani, Ahmed
year	2020
title	An AI Lens on Historic Cairo
source	ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 426-434.
doi	https://doi.org/10.52842/conf.acadia.2020.1.426
summary	Reports show that numerous heritage sites are in danger due to conflicts and heritage mismanagement in many parts of the world. Experts have resorted to digital tools to attempt to conserve and preserve endangered and damaged sites. To that end, in this applied research, we aim to develop a deep learning framework applied to the decaying tangible heritage of Historic Cairo, known as “The City of a Thousand Minarets.” The proposed framework targets Cairo’s historic minaret styles as a test case study for the broader applications of deep learning in digital heritage. It comprises recognition and segmentation tasks, which use a deep learning semantic segmentation model trained on two data sets representing the two most dominant minaret styles in the city, Mamluk (1250–1517 CE) and Ottoman (1517–1952 CE). The proposed framework aims to classify these two types using images. It can help create a multidimensional model from just a photograph of a historic building, which can quickly catalog and document a historic building or element. The study also sheds light on the obstacles preventing the exploration and implementation of deep learning techniques in digital heritage. The research presented in this paper is a work-in-progress of a larger applied research concerned with implementing deep learning techniques in the digital heritage domain.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	artificial_intellicence2019_15
id	artificial_intellicence2019_15
authors	Antoine Picon
year	2020
title	What About Humans? Artificial Intelligence in Architecture
source	Architectural Intelligence Selected Papers from the 1st International Conference on Computational Design and Robotic Fabrication (CDRF 2019)
doi	https://doi.org/https://doi.org/10.1007/978-981-15-6568-7_2
summary	Artificial intelligence is about to reshape the architectural discipline. After discussing the relations between artificial intelligence and the broader question of automation in architecture, this article focuses on the future of the interaction between humans and intelligent machines. The way machines will understand architecture may be very different from the reading of humans. Since the Renaissance, the architectural discipline has defined itself as a conversation between different stakeholders, the designer, but also the clients and the artisans in charge of the realization of projects. How can this conversation be adapted to the rise of intelligent machines? Such a question is not only a matter of design effectiveness. It is inseparable from expressive and artistic issues. Just like the fascination of modernist architecture for industrialization was intimately linked to the quest for a new poetics of the discipline, our contemporary interest for artificial intelligence has to do with questions regarding the creative core of the architectural discipline.
series	Architectural Intelligence
email
last changed	2022/09/29 07:28

_id	acadia20_708
id	acadia20_708
authors	Charbel, Hadin; López Lobato, Déborah
year	2020
title	Between Signal and Noise
source	ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 708-718.
doi	https://doi.org/10.52842/conf.acadia.2020.1.708
summary	Climate change continues to have noticeable and accelerated impacts on various territories. Previously predictable and recognizable patterns used by humans and nonhumans alike are perpetually being altered, turning localized signals into noise and effectively disrupting indigenous modes of life. While the use of certain technologies such as data collection, machine learning, and automation can render these otherwise patternless information streams into intelligible content, they are generally associated as being “territorializing,” as an increase in resolution generally lends itself to control, exploitation, and colonization. Contrarily, indigenous groups with long-lasting relationships that have evolved over time have distinct ways of reading and engaging with their contexts, developing sustainable practices that, while effective, are often overlooked as being compatible with contemporary tools. This paper examines how the use of traditionally territorializing technologies can be paired with indigenous knowledge and protocols in order to operate between signal and noise, rendering perverse changes in the landscape comprehensible while also presenting their applications as a facet for sociopolitical, cultural, and ecological adaptation. A methodology defined as “decoding” and “recoding” presents four distinct case studies in the Arctic, addressing various scales and targets with the aim of disrupting current trends in order to grant and/or retain autonomy through what can be read as a form of preservation via augmented adaptation.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	sigradi2020_312
id	sigradi2020_312
authors	Farrokhsiar, Paniz; Gursoy, Benay
year	2020
title	Robotic Sketching: A Study on Robotic Clay 3D Printing
source	SIGraDi 2020 [Proceedings of the 24th Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Online Conference 18 - 20 November 2020, pp. 312-319
summary	Digital fabrication tools are typically employed to materialize a fixed design. Design limits the choice of material; Natural material behavior may consider as flaws in the fabrication. What if these tools and material behaviors being used as sketching tools to generate new design ideas? In this paper, we present a workflow in which digital fabrication tools, specifically robotic arms, are used as sketching tools. It is called robotic sketching; The goal is to sketch with effects of fabrication settings on emerging behaviors of materials in first steps of design. We exemplify this workflow with a case on robotic clay 3D printing.
keywords	Digital fabrication, Sketching, Additive manufacturing, 3D printing with clay, Robotic
series	SIGraDi
email
last changed	2021/07/16 11:49

_id	ecaade2020_503
id	ecaade2020_503
authors	Jansen, Igor and Pi¹tek, £ukasz
year	2020
title	The Evolutionary-algorithm-based Automation of the Initial Stage of Apartment Building Design
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 105-114
doi	https://doi.org/10.52842/conf.ecaade.2020.2.105
summary	The development of information technologies has resulted in a strong return of interest in the concept of automating the design process. Most of the attempts such as works of Hersey and Freedman, Duarte or the PRISM application are based on shape grammars. Another approach is evolutionary simulations in concept creation augmentation such as works of Dogan, Saratsis and Reinhart or Nahara and Terzidis.This study examines to what extent evolutionary algorithms can be used to automate early stages of residential multi-family building architectural design. To facilitate informed decision-making, a tool capable of analysing a building plot and proposing the best fitting building shape was designed and tested with Polish legal regulations taken into consideration.A script generating, analysing, and evolutionally optimising a 3D model of the apartment building, was developed. All models met the basic legal conditions and were optimised by four criteria - view obstruction, insolation, maximal allowed floor area built and building compactness. The script was later used on selected building plots producing thousands of solutions. The best performing solutions were selected and presented together with their calculated parameters.
keywords	genetic algorithm; evolutionary simulation; residential building; design automation
series	eCAADe
email
last changed	2022/06/07 07:52

_id	ecaade2020_478
id	ecaade2020_478
authors	Han, Yoon J. and Kotnik, Toni
year	2020
title	A Tomographic computation of Spatial Dynamics
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 89-94
doi	https://doi.org/10.52842/conf.ecaade.2020.2.089
summary	Waning of vigorous discourses about the idea of space as essence in architectural design concurred with the emergence of digital architecture. The notion of space was replaced with the underlying notion of form facilitating optimization of performances and form-generation in digital design ever since. Within the context of digital architecture, the current research investigates a formal method to reintroduce spatial aspects, based on dynamics of architectural space in relation to form, into digital design processes. Accordingly, a computational framework is devised employing the idea of space as dynamic field conditions, in order to capture dynamic interrelation of architectural space with architectural form. That is, spatial dynamics are regarded as data embedded in architectural space, that can imply operational aspects of spatial experiences and / or stimulate corporeal engagements with experiential space, as concepts as action potentials and affordances do (Rasmussen 1964). As a result, the research aims to contribute to the body of knowledge that endeavour to systematize architectural sensibilities that are implicit in design processes by externalization utilizing computation.
keywords	spatial dynamics; dynamic field conditions; dynamic displacement
series	eCAADe
email
last changed	2022/06/07 07:50

_id	ecaade2020_222
id	ecaade2020_222
authors	Ikeno, Kazunosuke, Fukuda, Tomohiro and Yabuki, Nobuyoshi
year	2020
title	Automatic Generation of Horizontal Building Mask Images by Using a 3D Model with Aerial Photographs for Deep Learning
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 271-278
doi	https://doi.org/10.52842/conf.ecaade.2020.2.271
summary	Information extracted from aerial photographs is widely used in urban planning and design. An effective method for detecting buildings in aerial photographs is to use deep learning for understanding the current state of a target region. However, the building mask images used to train the deep learning model are manually generated in many cases. To solve this challenge, a method has been proposed for automatically generating mask images by using virtual reality 3D models for deep learning. Because normal virtual models do not have the realism of a photograph, it is difficult to obtain highly accurate detection results in the real world even if the images are used for deep learning training. Therefore, the objective of this research is to propose a method for automatically generating building mask images by using 3D models with textured aerial photographs for deep learning. The model trained on datasets generated by the proposed method could detect buildings in aerial photographs with an accuracy of IoU = 0.622. Work left for the future includes changing the size and type of mask images, training the model, and evaluating the accuracy of the trained model.
keywords	Urban planning and design; Deep learning; Semantic segmentation; Mask image; Training data; Automatic design
series	eCAADe
email
last changed	2022/06/07 07:50

_id	caadria2020_165
id	caadria2020_165
authors	Lorenz, Wolfgang E. and Wurzer, Gabriel
year	2020
title	FLÃ„VIZ in the rezoning process - A Web Application to visualize alternatives of land-use planning
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 813-822
doi	https://doi.org/10.52842/conf.caadria.2020.1.813
summary	The rezoning process primarily deals with proposed changes on land-use and zoning plans. More and more often, the public is asked for its opinion and feedback. However, there are two main obstacles in today's practice: On the one hand land-use and zoning plans, in general, only define the potential of areas and so do proposed draft plans; they usually say nothing about the implementation of land-use in the built space. On the other hand, the untrained majority can hardly grasp the current form of representation as two dimensional plans with accompanying written information. In order to enable a wider public participation (and understanding), the authors present FLÃ„VIZ, a 3D visualization of potentials on land-use and zoning plans.
keywords	Alternative land-use and Zoning plans; Three JS; Visual Representation
series	CAADRIA
email
last changed	2022/06/07 07:59

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