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	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	caadria2022_145
id	caadria2022_145
authors	Duering, Serjoscha, Fink, Theresa, Chronis, Angelos and Konig, Reinhard
year	2022
title	Environmental Performance Assessment - The Optimisation of High-Rises in Vienna
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. 545-554
doi	https://doi.org/10.52842/conf.caadria.2022.1.545
summary	Our cities are facing different kinds of challenges - in parallel to the urban transformation and densification, climate targets and objectives of decision-makers are on the daily agenda of planning. Therefore, the planning of new neighbourhoods and buildings in high-density areas is complex in many ways. It requires intelligent processes that automate specific aspects of planning and thus enable impact-oriented planning in the early phases. The impacts on environment, economy and society have to be considered for a sustainable planning result in order to make responsible decisions. The objective of this paper is to explore pathways towards a framework for the environmental performance assessment and the optimisation of high-rise buildings with a particular focus on processing large amounts of data in order to derive actionable insights. A development area in the urban centre of Vienna serves as case study to exemplify the potential of automated model generation and applying ML algorithm to accelerate simulation time and extend the design space of possible solutions. As a result, the generated designs are screened on the basis of their performance using a Design Space Exploration approach. The potential for optimisation is evaluated in terms of their environmental impact on the immediate environment.
keywords	simulation, prediction and evaluation, machine learning, computational modelling, digital design, high-rises, SGD 11, SDG 13
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	ijac202220106
id	ijac202220106
authors	Förster, Nick; Ivan Bratoev, Jakob Fellner, Gerhard Schubert, Frank Petzold
year	2022
title	Collaborating with the crowd
source	International Journal of Architectural Computing 2022, Vol. 20 - no. 1, pp. 76–95
summary	Microscopic agent-based simulations promise the meaningful inclusion of crowd dynamics in planning processes. However, such complex urban issues depend on a multiplicity of criteria. Thus, an isolated model cannot represent the walk of pedestrians meaningfully in planning contexts. This paper reframes crowd simulation as collaborative experimentation and embeds it directly in the design process. Beyond the simulation algorithm, this perspective draws attention to user interactions, interfaces, and visualizations as crucial simulation elements. Through a prototype, we combine an agent-based pedestrian simulation with a hybrid physical–digital interface. Based on this configuration, we explore requirements of the early design stages and accordingly discuss concepts for interaction, simulation, and visualization. The prototype blends user inputs with intuitive design interactions, adapts the simulation process to qualitative and dynamic negotiations, and presents results immediately in the discussed context. Thus, it aligns crowd simulation with contingent collaborations and reveals its potential in the early design stages.
keywords	Urban design, architectural design, design decision support, pedestrian simulation, human–computer interaction, collaborative design, early design stages
series	journal
last changed	2024/04/17 14:29

_id	ecaade2022_197
id	ecaade2022_197
authors	Giglio, Andrea, Gorbet, Rob and Beesley, Philip
year	2022
title	Hybrid Soundscape: Human and non-human sounds interactions for a collective installation
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. 441–447
doi	https://doi.org/10.52842/conf.ecaade.2022.1.441
summary	The paper describes a site-specific architectural soundscape installation created during a workshop in August 2021 at the Domaine de Boisbuchet in France. Far from urban noise, participants were attuned to natural, artificial, and human sound spheres, placing them in dialog and interweaving them through emulation, voice recording, and electro-acoustic devices including piezoceramic sensors, small motors, speakers, and embedded electronics. This expository paper includes qualitative descriptions of the spatial sound compositions, the technology that supported them, and the performance into which they were integrated. The results of this event were described by participants as trance-like, with phasing of multiple periodically organized emergent sound phenomena creating a deeply immersive distributed environment. In describing in detail, the tools, processes, outcomes and implications of the workshop, this paper offers an example of a design approach and model that can contribute immersive distributed architectural soundscape design through human and non-human sound interaction.
keywords	Spatial Sound, Hybrid Soundscape, Acoustic Responsive Devices, Human-Nonhuman Sound Interaction, Collective Installation
series	eCAADe
email
last changed	2024/04/22 07:10

_id	ecaade2022_392
id	ecaade2022_392
authors	Karimian-Aliabadi, Hamed, Adelzadeh, Amin and Robeller, Christopher
year	2022
title	A Computational Workflow for Design-to-Assembly of Shingle Covering Systems for Multi-Curved Surface Structures
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. 659–666
doi	https://doi.org/10.52842/conf.ecaade.2022.1.659
summary	Shingle covering of multi-curved surfaces is usually a manual process with no precise plan for the arrangement and assembly of shingle elements. Such processes lack the computational capacity of algorithmic methods for modeling, analysis, and optimization of shingle systems within a seamless digital workflow. As a solution, this paper presents an algorithmic procedure for the design and assembly of shingle covering systems for multi-curved surface structures. The proposed algorithm evaluates the reference surface curvatures to generate an efficient layout of shingles of identical size. The proposed model generates the arrangement of shingles based on given input parameters including the shingle dimensions and overlapping domains. For a precise and quick on-site assembly the corresponding nailing strips are also automatically generated on which the shingles could be installed. The applications and limitations of the proposed algorithm are discussed through a detailed analysis of various case studies.
keywords	Shingle Covering, Algorithmic Design, Concave Surface, Multi-Curvature Surface, Overlapping Domain, Curvature Dependent Spacing, Timber Strips
series	eCAADe
email
last changed	2024/04/22 07:10

_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	caadria2022_279
id	caadria2022_279
authors	Kim, Dongyun, Guida, George and Garcia del Castillo y Lopez, Jose Luis
year	2022
title	PlacemakingAI : Participatory Urban Design with Generative Adversarial Networks
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. 485-494
doi	https://doi.org/10.52842/conf.caadria.2022.2.485
summary	Machine Learning (ML) is increasingly present within the architectural discipline, expanding the current possibilities of procedural computer-aided design processes. Practical 2D design applications used within concept design stages are however limited by the thresholds of entry, output image fidelity, and designer agency. This research proposes to challenge these limitations within the context of urban planning and make the design processes accessible and collaborative for all urban stakeholders. We present PlacemakingAI, a design tool made to envision sustainable urban spaces. By converging supervised and unsupervised Generative Adversarial Networks (GANs) with a real-time user interface, the decision-making process of planning future urban spaces can be facilitated. Several metrics of walkability can be extracted from curated Google Street View (GSV) datasets when overlayed on existing street images. The contribution of this framework is a shift away from traditional design and visualization processes, towards a model where multiple design solutions can be rapidly visualized as synthetic images and iteratively manipulated by users. In this paper, we discuss the convergence of both a generative image methodology and this real-time urban prototyping and visualization tool, ultimately fostering engagement within the urban design process for citizens, designers, and stakeholders alike.
keywords	Machine Learning, Generative Adversarial Networks, user interface, real-time, walkability, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	ecaade2022_217
id	ecaade2022_217
authors	Panagiotidou, Vasiliki and Koerner, Andreas
year	2022
title	From Intricate to Coarse and Back - A voxel-based workflow to approximate high-res geometries for digital environmental simulations
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. 491–500
doi	https://doi.org/10.52842/conf.ecaade.2022.1.491
summary	Digital environmental simulations can present a computational bottleneck concerning the complexity of geometry. Therefore, a series of workarounds, ranging from cloud-based solutions to machine learning simulations as surrogate simulations are conventionally applied in practice. Concurrently, contemporary advances in procedural modelling in architecture result in design concepts with high polygon counts. This leads to an ever- increasing resolution discrepancy between design and analysis models. Responding to this problem, this research presents a step-by-step approximation workflow for handling and transferring high-resolution geometries between procedural modelling and environmental simulation software. The workflow is intended to allow designers to quickly assess a design’s interaction with environmental parameters such as airflow and solar radiation and further articulate them. A controllable voxelization procedure is applied to approximate the original geometry and therefore reduce the resolution. Controllable in this context refers to the user’s ability to locally adjust the voxel resolution to fit design needs. After export and simulation, 3d results are imported back into the design environment. The colour properties are re-mapped onto the original high- resolution geometry following a weighted proximity technique. The developed data transfer pipeline allows designers to integrate environmental analysis during initial design steps, which is essential for accessibility in the design profession. This can help to environmentally inform generative designs as well as to make simulation workflows more accessible when working with a wider range of geometries. In this, it reduces the perceived discrepancy between the concept and simulation model. This eases the use and allows a wider audience of users to develop co-creation processes between computation, architecture, and environment.
keywords	Simulation, Accessibility, Computation, Environmental Data, Workflow
series	eCAADe
email
last changed	2024/04/22 07:10

_id	ecaade2022_448
id	ecaade2022_448
authors	Papanikolaou, Kyratsoula-Tereza, Liapi, Katherine and Sibetheros, Ioannis
year	2022
title	Environmental Impact Assessment and Visualization of Rain-Water Best Management Practices for Urban Blocks - An "architect-friendly" simulation model
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. 75–82
doi	https://doi.org/10.52842/conf.ecaade.2022.2.075
summary	In order to implement stormwater best management practices (BMPs) in urban blocks in Greece and other cities with warm and dry climates, such as green roofs, porous pavements etc., it is crucial that architects are able to assess their environmental impact during the design process in an efficient and simple way, without the requirement of an in depth understanding of the complex hydrological processes. To achieve the above, an “architect-friendly” computer-based model, under development by the authors, is presented. The model can be used as a decision support tool by allowing an assessment of the efficacy of non-conventional, water-sensitive, stormwater management strategies in an urban environment, measured by the stormwater runoff mitigation and temperature decrease. Wind flow simulation data from an external CFD model can be integrated into the proposed model, in order to visualize wind flow patterns in selected urban blocks. The user is able to select different stormwater BMPs from a BMP library and apply them on the 3D urban block model, in order to achieve an improved “water sensitive” state. The ENVI-MET plugin for Rhino is used for simulating temperature decrease and the SCS Curve Number method for determining stormwater runoff reduction, caused by each BMP application. The visualization of the results in the graphical interface of the Grasshopper programming environment facilitates the study of the environmental impact of stormwater BMPs in urban blocks and the comparison of different stormwater management scenarios. Several urban blocks in Athens will be used as case studies to test the proposed model and assess the efficiency of the visualization process.
keywords	Stormwater Best Management Practices, Urban Blocks, Runoff Mitigation, Temperature Reduction, Decision Support Tool, Environmental Impact Visualization
series	eCAADe
email
last changed	2024/04/22 07:10

_id	caadria2022_184
id	caadria2022_184
authors	Sateei, Shahin, Roup, Mattias and Johansson, Mikael
year	2022
title	Collaborative Design Review Sessions in Virtual Reality: Multi-Scale and Multi-User
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. 29-38
doi	https://doi.org/10.52842/conf.caadria.2022.1.029
summary	The use of Virtual Reality (VR) for design reviews in projects is becoming more common in construction. However, the use of VR in these processes has been limited to been used more as a complementary reviewing tool alongside information medias such as 2D drawings and 3D models. Furthermore, immersive VR has been argued to have limitations when it comes to orientation and understanding and reasoning about functional links between physical layouts in a facility. This paper presents a case study of a VR system used during design reviews that support end-users to switch between different representations and scale i.e., miniature model/bird-eye view, and a 1:1 scale experience of the facility. The data gathered, consisted of recorded observation of the VR based design review process and study what type of discussion and design errors that was found during two VR-workshops connected to a new elementary school. The result shows, that by supporting switching between miniature model and 1:1 scale VR experience facilitated spatial orientation and understanding and collaboration across disciplines in the project. The study also show how collaborative immersive VR can be used as an efficient communication-tool during the design process in a real-world project.
keywords	Virtual Reality, VR, Immersive virtual environments, Collaboration, Levels of detail, SDG 4, SDG 9, SDG 11, SDG 12
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	ecaade2022_158
id	ecaade2022_158
authors	Zhao, Xingjian, Wang, Tsung-Hsien and Peng, Chengzhi
year	2022
title	Automatic Room Type Classification using Machine Learning for Two-Dimensional Residential Building Plans
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. 593–600
doi	https://doi.org/10.52842/conf.ecaade.2022.2.593
summary	Building plan semantic retrieval is of interest in every stage of construction and facility management processes. A conceptual design model with a space layout can be used for the early building evaluation, such as functional spatial validation, circulation and security checking, cost estimation, and preliminary energy consumption simulation. With the development of information technology, existing machine learning methods applied to semantic segmentation of building plan images have successfully identified building elements such as doors, windows, and walls. However, for the higher level of room type/function recognition, the prediction accuracy is low when building plans do not contain sufficient details such as furniture. In this paper, we present a workflow and a predictive model for residential room type classification. Given a building plan image, the building elements are first identified, followed by room feature extraction by connectivity and morphological characterization using a rule-based algorithm. The Multi-Layer Perceptron (MLP) is trained with the feature set and then predicts the room type of test samples. We collected 1,586 residential room samples from 165 building layout plans and categorized rooms into nine types. Finally, our current model can achieve a classification accuracy of 0.82.
keywords	Floor Plan Semantic Retrieval, Room Type Classification, Machine Learning
series	eCAADe
email
last changed	2024/04/22 07:10

_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
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
doi	https://doi.org/10.52842/conf.ecaade.2022.1.215
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
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
doi	https://doi.org/10.52842/conf.caadria.2022.1.393
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	cdrf2022_293
id	cdrf2022_293
authors	Amal Algamdey, Aleksander Mastalski, Angelos Chronis, Amar Gurung, Felipe Romero Vargas, German Bodenbender, and Lea Khairallah
year	2022
title	AI Urban Voids: A Data-Driven Approach to Urban Activation
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_26
summary	With the development of digital technologies, big urban data is now readily available online. This opens the opportunity to utilize new data and create new relationships within multiple urban features for cities. Moreover, new computational design techniques open a new portal for architects and designers to reinterpret this urban data and provide much better-informed design decisions. The “AI Urban Voids'' project is defined as a data-driven approach to analyze and predict the strategic location for urban uses in the addition of amenities within the city. The location of these urban amenities is evaluated based on predictions and scores followed by a series of urban analyses and simulations using K-Means clustering. Furthermore, these results are then visualized in a web-based platform; likewise, the aim is to create a tool that will work on a feedback loop system that constantly updates the information. This paper explains the use of different datasets from Five cities including Melbourne, Sydney, Berlin, Warsaw, and Sao Paulo. Python, Osmx libraries and K-means clustering open the way to manipulate large data sets by introducing a collection of computational processes that can override traditional urban analysis.
series	cdrf
email
last changed	2024/05/29 14:02

_id	cdrf2022_304
id	cdrf2022_304
authors	Anni Dai
year	2022
title	Co-creation: Space Reconfiguration by Architect and Agent Simulation Based Machine Learning
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_27
summary	This research is a manifestation of architectural co-creation between agent simulation based machine learning and an architect’s tacit knowledge. Instead of applying machine learning brains to agents, the author reversed the idea and applied machine learning to buildings. The project used agent simulation as a database, and trained the space to reconfigure itself based on its distance to the nearest agents. To overcome the limitations of machine learning model’s simplified solutions to complicated architectural environments, the author introduced a co-creation method, where an architect uses tacit knowledge to overwatch and have real-time control over the space reconfiguration process. This research combines both the strength of machine learning’s data-processing ability and an architect’s tacit knowledge. Through exploration of emerging technologies such as machine learning and agent simulation, the author highlights limitations in design automation. By combining an architect’s tacit knowledge with a new generation design method of agent simulation based machine learning, the author hopes to explore a new way for architects to co-create with machines.
series	cdrf
email
last changed	2024/05/29 14:02

_id	ecaade2022_360
id	ecaade2022_360
authors	Azambuja Varela, Pedro, Lacroix, Igor, Güzelci, Orkan Zeynel and Sousa, José Pedro
year	2022
title	Democratizing Stereotomic Construction through AR Technologies - A reusable mold methodology to the production of customized voussoirs using HoloLens
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. 225–232
doi	https://doi.org/10.52842/conf.ecaade.2022.1.225
summary	Mass customizing of building components allows new conditions to explore aesthetic and sustainability in architecture. However, such possibilities tend to require the use of expensive and heavy digital fabrication machinery, which is seldomly available in most regions on the planet. In this context, this paper presents a research in progress that explores Augmented Reality (AR) to support craft production of customized stereotomic components. As a portable technology, the work examines the potential of AR to materialize design solutions that are geometrically complex and variable. Considering the current research on augmented fabrication processes, this work contributes to producing variable building components for stereotomic construction with a focus on earth-based materials. Extending the findings of a recently completed PhD thesis, the work replaces the use of a robot with the HoloLens glasses and Fologram application to produce low- cost and reusable molds. This augmented fabrication setup allows the human control of the production of variable molds, ready for casting and assembly of stereotomic components. This work addresses several of the NEB and UN SDGs goals.
keywords	Stereotomy, Augmented Reality, Augmented Fabrication, Customized Production, New European Bauhuas
series	eCAADe
email
last changed	2024/04/22 07:10

_id	ascaad2022_120
id	ascaad2022_120
authors	Bacinoglu, Saadet Zeynep; Cavus, Ozlem
year	2022
title	Gamifying Origami: Rule-based Improvisation for Design Exploration
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. 595-608
summary	Origami, which originated as a folding paper game in Japan, has turned into a source of learning and inspiration for design and engineering studies. Complex two-dimensional patterns of origami sustain visual rules of space transformation. So, this paper proposes to gamify origami to get users more involved in the design space exploration process. For the gamification of origami, the study alters the origami patterns in a 3D modular composition with rules, scoring, and rounds in a design context. Gamifying origami becomes a tool for a learning experience for first-year architecture students in the early design phases. Accordingly, this paper presents a gaming experience model based on origami for the foundation studios. This model consists of three main stages: start, rounds, and finish. The teaching of the model is the mereological relationship providing continuity concerning improvisations with visual rules. The reward is the model complexity, such as folding numbers, and regular or modified folding. The penalty is losing scores if the continuity is not maintained. The presented experience model is performed twice in the foundation studios. The former is for understanding how much preliminary knowledge is required for the first-year students to grasp and complete the game. The second is for testing the experience. The results of the study prove the role of visual reflection-on/in action by creating pauses during the origami design and the importance of sustaining the visual inference with transformations between individuals to experience form to formation, complexity, unity, and creativity in origami design. This study would contribute to the literature on experimental methods for design pedagogy.
series	ASCAAD
email
last changed	2024/02/16 13:38

_id	sigradi2022_54
id	sigradi2022_54
authors	Balci, Ozan; Alaçam, Sema
year	2022
title	Zone-sensitive RIZOBots in Action: Examining the Behavior of Mobile Robots In a Heterogeneous Environment
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. 397–408
summary	This study proposes a framework for the use of mobile robots namely RIZOBots in form studies in the early phases of design. The proposed framework was tested in two experiments. An agent-based model was utilized for the movement of mobile robots, a drawing task was defined as the task. In particular, rule sets for agent-agent and agent-environment interaction were used. Light-sensitivity rules were utilized to achieve agent-environment interaction, apart from obstacle detection. This study focuses on the effects of two different zone-related states on the behavior of RIZOBot which is a configurable differential-drive wheeled robot developed by authors using off-the-shelf products and 3D printed body parts. Two zone types with very basic features are used to define environmental conditions. The traces left on the canvas, the irregularities in the movement of the robots, and the robot-environment interaction will be evaluated in the study. The results and analysis of the two selected experiments are presented and the potential of the proposed framework is discussed.
keywords	Robotics, Swarm robotics, Swarm behaviour, Mobile agents, Zone-sensitivity
series	SIGraDi
email
last changed	2023/05/16 16:56

_id	sigradi2022_211
id	sigradi2022_211
authors	Baltazar, Ana Paula; Bartholo, Beatriz; Moritani, Gustavo Jun; Paiva, Luísa; Cabral Filho, José
year	2022
title	Technological appropriations for socio-spatial transformation in Sao Gonçalo do Baçao
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. 847–856
summary	Based on a university teaching-research-extension experience in Sao Gonçalo do Baçao (Minas Gerais, Brazil), this article discusses the use of digital technology as a way to expand the virtual, understood as an event in latent state, as a process of problematization and not of problem solving. Three digital interfaces developed with the common goal of encouraging questioning and the exercise of autonomy from different approaches and themes are presented. The interfaces seek to articulate the Flusserian idea of 'responsibility', regarded as the act of responding to others in a way that promotes an opening for people to continue the design process dialogically. In short, the interfaces indicate possibilities provided by digital technologies and exemplify ways in which they might drive processes towards social-spatial transformation.
keywords	Interactions, Technological appropriations, Sintegrity, Socio-spatial transformation, Sao Gonçalo do Baçao
series	SIGraDi
email
last changed	2023/05/16 16:57

_id	ecaade2022_218
id	ecaade2022_218
authors	Bank, Mathias, Sandor, Viktoria, Schinegger, Kristina and Rutzinger, Stefan
year	2022
title	Learning Spatiality - A GAN method for designing architectural models through labelled sections
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. 611–619
doi	https://doi.org/10.52842/conf.ecaade.2022.2.611
summary	Digital design processes are increasingly being explored through the use of 2D generative adversarial networks (GAN), due to their capability for assembling latent spaces from existing data. These infinite spaces of synthetic data have the potential to enhance architectural design processes by mapping adjacencies across multidimensional properties, giving new impulses for design. The paper outlines a teaching method that applies 2D GANs to explore spatial characteristics with architectural students based on a training data set of 3D models of material-labelled houses. To introduce a common interface between human and neural networks, the method uses vertical slices through the models as the primary medium for communication. The approach is tested in the framework of a design course.
keywords	AI, Architectural Design, Materiality, GAN, 3D, Form Finding
series	eCAADe
email
last changed	2024/04/22 07:10

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