Cumincad : CUMINCAD Papers : Search Results

CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

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_id	caadria2022_33
id	caadria2022_33
authors	Alva, Pradeep, Mosteiro-Romero, Martin, Miller, Clayton and Stouffs, Rudi
year	2022
title	Digital Twin-Based Resilience Evaluation of District-Scale Archetypes
doi	https://doi.org/10.52842/conf.caadria.2022.1.525
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. 525-534
summary	District-scale energy demand models can be powerful tools for understanding interactions in complex urban areas and optimising energy systems in new developments. The process of coupling characteristics of urban environments with simulation software to achieve accurate results is nascent. We developed a digital twin through a web map application for a 170ha district-scale university campus as a pilot. The impact on the built environment is simulated with pandemic (COVID-19) and climate change scenarios. The former can be observed through varying occupancy rates and average cooling loads in the buildings during the lockdown period. The digital twin dashboard was built with visualisations of the 3D campus, real-time data from sensors, energy demand simulation results from the City Energy Analyst (CEA) tool, and occupancy rates from WiFi data. The ongoing work focuses on formulating a resilience assessment metric to measure the robustness of buildings to these disruptions. This district-scale digital twin demonstration can help in facilities management and planning applications. The results show that the digital twin approach can support decarbonising initiatives for cities.
keywords	Digital twin, City Information Modelling, Planning Support System, energy demand model, SGD 11, SGD 13
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_102
id	caadria2022_102
authors	Gardner, Nicole, Haeusler, Matthias Hank, Yu, Daniel, Barton, Jack, Dunn, Kate and Huang, Tracy
year	2022
title	Revisiting Shoei Yoh: Developing a Workflow for a Browser-Based 3D Model Environment to Create an Immersive Digital Archive
doi	https://doi.org/10.52842/conf.caadria.2022.1.687
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. 687-696
summary	The digitisation of architecturally significant buildings and sites creates opportunities to innovate methods of analysis, interpretation, representation, and audience engagement. To illustrate this potential, but also examine the attendant challenges, this paper outlines a research project that has digitised archival assets and living buildings designed by the Japanese architect Shoei Yoh to create an immersive 3D Spatial Archive. It focuses particularly on the creation of a browser-based 3D environment using WebGL technology that connects to and displays a repository of digitised archival assets. This includes the use of 3D scan data of Yoh's Naiju Community Centre project to accurately model the 3D immersive environment and a Grasshopper / Rhino into the glTF. File format (graphics library Transmission Format) workflow to render Naiju‚s complex geometry and detailed outdoor scenery. The paper demonstrates how using the .glTF File, which is an open format specifically for transmitting processed and pre-calculated 3D models, can improve the processing efficiency of web-browser based 3D environments. Improving the stability and processing speed of 3D browser-based environments is significant to enhancing how audiences can connect with and experience culturally significant sites remotely. The digital recreation and repurposing of Naiju (which is currently unoccupied and in a state of disrepair) as an immersive archival exhibition space operates to simultaneously protect the real building from over visitation, but also raise awareness of its cultural significance to support preservation efforts. In so doing, the paper makes a further contribution to the developing field of digital cultural heritage.
keywords	Digital Cultural Heritage, Browser-based Modelling, glTF File, Architectural Visualisation, Shoei Yoh, SDG 9, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_204
id	caadria2022_204
authors	Narahara, Taro
year	2022
title	Kurashiki Viewer: Qualitative Evaluations of Architectural Spaces inside Virtual Reality
doi	https://doi.org/10.52842/conf.caadria.2022.1.011
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. 11-18
summary	This paper discusses how virtual reality (VR) environments can be employed as a data collection tool beyond visualization and representation tools through a simple experiment in a VR space and speculates about its potential applications. Using a VR model that runs on a web browser based on an existing historic town in Japan called Kurashiki, the experiment asked 30 recruited participants to freely walk around and leave ratings on a 5-point scale on any buildings or objects appealing to them. The proposed system in this paper can display points of interest of multiple participants using heatmaps superimposed on a map that can help users visually understand statistical preferences among them. The project's goal is to provide a quantitative means for qualitative values of architectural and urban spaces, making such data more shareable. We intended to show that such a platform could help multiple stakeholders reach better consensuses and possibly collect training datasets for machine learning models that could extract features related to the attractiveness in architecture and urban spaces.
keywords	Virtual reality, subjective evaluation, crowdsourcing, SDG 10, SDG 11.
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	ijac202220109
id	ijac202220109
authors	Ortner, F. Peter; Jing Zhi Tay
year	2022
title	Resilient by design: Informing pandemic-safe building redesign with computational models of resident congestion
source	International Journal of Architectural Computing 2022, Vol. 20 - no. 1, pp. 129–144
summary	This paper describes a computational design-support tool created in response to safe-distancing measures enforced during the COVID-19 pandemic. The tool was developed for a specific use case: understanding congestion in crowded migrant worker dormitories that experienced high rates of COVID-19 transmission in 2020. Building from agent-based and network-based computational simulations, the tool presents a hybrid method for simulating building resident movements based on known or pre-determined schedules and likely itineraries. This hybrid method affords the design tool a novel approach to simultaneous exploration of spatial and temporal design scenarios. The paper demonstrates the use of the tool on an anonymised case study of a high-density migrant worker dormitory, comparing results from a baseline configuration against design variations that modify dormitory physical configuration and schedule. Comparisons between the design scenarios provide evidence for reflections on pandemic-resilient design and operation strategies for dor- mitories. A conclusions section considers the extent to which the model and case study results are applicable to other dense institutional buildings and describes the paper’s contributions to general understanding of configurational and operational aspects of resilience in the built environment.
keywords	Design for resilience, evidence-based design, design support, agent-based model, schedule-based model, network analysis
series	journal
last changed	2024/04/17 14:29

_id	caadria2022_302
id	caadria2022_302
authors	Raghu, Deepika, Markopoulou, Areti, Marengo, Mathilde, Neri, Iacopo, Chronis, Angelos and De Wolf, Catherine
year	2022
title	Enabling Component Reuse from Existing Buildings through Machine Learning, Using Google Street View to Enhance Building Databases
doi	https://doi.org/10.52842/conf.caadria.2022.2.577
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. 577-586
summary	Intense urbanization has led us to rethink construction and demolition practices on a global scale. There is an opportunity to respond to the climate crisis by moving towards a circular built environment. Such a paradigm shift can be achieved by critically examining the possibility of reusing components from existing buildings. This study investigates approaches and tools needed to analyze the existing building stock and methods to enable component reuse. Ocular observations were conducted in Google Street View to analyze two building-specific characteristics: (1) facade material and (2) reusable components (window, doors, and shutters) found on building facades in two cities: Barcelona and Zurich. Not all products are equally suitable for reuse and require an evaluation metric to understand which components can be reused effectively. Consequently, tailored reuse strategies that are defined by a priority order of waste prevention are put forth. Machine learning shows promising potential to visually collect building-specific characteristics that are relevant for component reuse. The data collected is used to create classification maps that can help define protocols and for urban planning. This research can upscale limited information in countries where available data about the existing building stock is insufficient.
keywords	machine learning, component reuse, Google Street View, material banks, building databases, SDG 11, SDG 12
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	ascaad2022_110
id	ascaad2022_110
authors	Salem, Mona; Moussa, Ramy
year	2022
title	A Hybrid Approach Based on Building Physics and Machine Learning for Thermal Comfort Prediction in Smart Buildings
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. 253-263
summary	One of the most important challenges facing the world is the application of modern technology in order to create smart buildings that achieve sustainable development goals (SDGs). Thermal comfort and reduction of energy consumption in buildings are considered important factors which, in turn, are reflected in creating a healthy environment and improving human productivity. Internet of Things (IoT) provides an ideal solution for collecting real-time data on the factors affecting indoor thermal comfort and energy consumption. However, comfort level is subjective and depends on many factors, which may not be learned by conventional models, an integrated model depending on thermal comfort factors is needed. In this work, a hybrid physics-based model incorporated with machine learning techniques is used for the prediction of thermal comfort inside buildings. XGBoost (eXtreme Gradient Boost) algorithm method was used due to its abilities to handle complex problems. A calculated dataset was extracted from the physics-based model gathered with the environmental variables data such as humidity, moisture, temperature, and air velocity collected from IoT devices. The results show an improvement in the prediction of the thermal comfort approach as compared with the conventional models. The XGBoost algorithm can exhibit an effective solution for eliminating deficiencies of traditional models and can be used when designing smart buildings, simulating, and evaluating the designed buildings, controlling energy consumption, and achieving thermal comfort.
series	ASCAAD
email
last changed	2024/02/16 13:38

_id	caadria2022_227
id	caadria2022_227
authors	Stuart-Smith, Robert and Danahy, Patrick
year	2022
title	Visual Character Analysis within Algorithmic Design: Quantifying Aesthetics Relative to Structural and Geometric Design Criteria
doi	https://doi.org/10.52842/conf.caadria.2022.1.131
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. 131-140
summary	Buildings are responsible for 40% of world C02 emissions and 40% of the world's raw material consumption. Designing buildings with a reduced material volume is essential to securing a post-carbon built environment and supports a more affordable, accessible architecture. Architecture‚s material efficiency is correlated to structural efficiency however, buildings are seldom optimal structures. Architects must resolve several conflicting design criteria that can take precedence over structural concerns, while material-optimization is also impacted from limited means to quantitatively assess aesthetic decisions. Flexible design methods are required that can adapt to diverse constraints and generate filagree material arrangements, currently infeasible to explicitly model. A novel approach to generative topological design is proposed employing a custom multi-agent method that is adaptive to diverse structural conditions and incorporates quantitative analysis of visual formal character. Computer vision methods Gabor filtering, Canny Contouring and others are utilized to evaluate the visual appearance of designs and encode these within quantitative metrics. A matrix of design outcomes for a pavilion are developed to test adaptation to different spatial arrangements. Results are evaluated against visual character, structural, and geometric methods of analysis and demonstrate a limited set of aesthetic design criteria can be correlated with structural and geometric data in a quantitative metric.
keywords	Generative/Algorithmic Design, Computer Vision, Environmental Performance, Multi-Agent Systems, Visual Character Analysis, SDG 10, SDG 11, SDG 9, SDG 12, SDG 13
series	CAADRIA
email
last changed	2022/07/22 07:34

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

_id	cdrf2022_253
id	cdrf2022_253
authors	Chuheng Tan and Ximing Zhong
year	2022
title	A Rapid Wind Velocity Prediction Method in Built Environment Based on CycleGAN Model
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_22
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
summary	Although the wind microclimate and wind environment play important roles in urban prediction, the time-consuming and complicated setup and process of wind simulation are widely regarded as challenges. There are several methods to use deep learning (DL) models for wind speed prediction by labeling pairs of wind simulation dataset samples. However, many wind simulation experiments are needed to obtain paired datasets, which is still time-consuming and cumbersome. Compared with previous studies, we propose a method to train a DL model without labelling paired data, which is based on Cycle Generative Adversarial Network (cycleGAN). To verify our hypothesis, we evaluate the results and process of the pix2pix model (requires paired datasets) and cycleGAN (does not requires paired datasets), and explore the difference of results between these two DL models and professional CFD software. The result shows that cycleGAN can perform as well as pix2pix in accuracy, indicating that some random city plans image samples and random wind simulation samples can train surrogate models as accurate as labelled DL methods. Although the DL method has similar results to the professional CFD method, the details of the wind flow results still need improvement. This study can help designers and policymakers to make informed decisions to choose Dl methods for real-time wind speed prediction for early-stage design exploration.
series	cdrf
email
last changed	2024/05/29 14:02

_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_154
id	ecaade2022_154
authors	Ferretti, Maddalena, Di Leo, Benedetta, Quattrini, Ramona and Vasic, Iva
year	2022
title	Creativity and Digital Transition in Central Apennine - Innovative design methods and digital technologies as interactive tools to enable heritage regeneration and community engagement
doi	https://doi.org/10.52842/conf.ecaade.2022.2.187
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. 187–196
summary	This contribution proposes strategies of reactivation of the central Apennine of Marche Region in Italy through creative design methods and virtual technologies. The research activities are connected to two related PhD projects: one focusing on architectural and urban design, the other one on heritage digitalization and new technologies and to other research activities of our interdisciplinary team. Cagli, a small town of 8.000 inhabitants, is currently undergoing socio-economic transformations that need to be addressed strategically with a cultural and spatial perspective. The research explores regenerative solutions and local development strategies to enhance the city and its cultural landscape. Participatory processes aided by digital tools and innovative design methods are tested in Cagli’s living lab. The final output of the overall research is a “Reactive Map” combining a trans-scalar and multidisciplinary territorial analysis with visions to identify “potential spaces”. The map is a design tool to define a shared strategy of enhancement of the city and its heritage. With this paper we present one of the methodological steps of the research, a WEB-APP built upon a point clouds database and assessed through a preliminary user test. The highly descriptive 3D environment is able to collect analysis and to be enriched in a participatory way during planned activities of co-thinking. The 3D environment, improved with interviews, plans, historical pictures and other media contents, is also paired with a virtual tour to offer a different representation of the “potential spaces”. The fully boosting 3D digital technology thus represents a viable and effective solution to involve citizens and an innovative and interdisciplinary tool for knowledge advancement in the fields of architectural and urban design and heritage regeneration.
keywords	Tangible and Intangible Heritage, Co-Thinking, Trans-Scalar Approach, Narrative, Point Clouds Exploitation, Interactive Annotation, Virtual Reality
series	eCAADe
email
last changed	2024/04/22 07:10

_id	ecaade2022_133
id	ecaade2022_133
authors	Grisiute, Ayda, Silvennoinen, Heidi, Li, Shiying, Chadzynski, Arkadiusz, von Richthofen, Aurel and Herthogs, Pieter
year	2022
title	Unlocking Urban Simulation Data with a Semantic City Planning System - Ontologically representing and integrating MATSim output data in a knowledge graph
doi	https://doi.org/10.52842/conf.ecaade.2022.2.257
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. 257–266
summary	Simulation models generate an abundance of rich raw data that remains difficult to access for non-experts. However, such data could be unlocked and utilised with a Semantic City Planning System that improves data accessibility and transparency. This paper describes a process of ontologically representing mobility simulation output data using Semantic Web technologies and storing it in a dynamic geospatial knowledge graph. Our work presents two benefits: 1) formally representing simulation output data increases the accessibility and transparency of urban simulation models, and 2) access to under-utilised rich data unlocks novel cross-domain knowledge explorations and research possibilities. We demonstrate these benefits by means of cross-domain queries related to typical city planning questions.
keywords	Semantic Web Technology, Mobility, Urban Planning, Ontology, MATSim, Knowledge Graph
series	eCAADe
email
last changed	2024/04/22 07:10

_id	architectural_intelligence2022_5
id	architectural_intelligence2022_5
authors	Jiading Zhong, Jianlin Liu, Yongling Zhao, Jianlei Niu & Jan Carmeliet
year	2022
title	Recent advances in modeling turbulent wind flow at pedestrian-level in the built environment
doi	https://doi.org/https://doi.org/10.1007/s44223-022-00008-7
source	Architectural Intelligence Journal
summary	Pressing problems in urban ventilation and thermal comfort affecting pedestrians related to current urban development and densification are increasingly dealt with from the perspective of climate change adaptation strategies. In recent research efforts, the prime objective is to accurately assess pedestrian-level wind (PLW) environments by using different simulation approaches that have reasonable computational time. This review aims to provide insights into the most recent PLW studies that use both established and data-driven simulation approaches during the last 5 years, covering 215 articles using computational fluid dynamics (CFD) and typical data-driven models. We observe that steady-state Reynolds-averaged Navier-Stokes (SRANS) simulations are still the most dominantly used approach. Due to the model uncertainty embedded in the SRANS approach, a sensitivity test is recommended as a remedial measure for using SRANS. Another noted thriving trend is conducting unsteady-state simulations using high-efficiency methods. Specifically, both the massively parallelized large-eddy simulation (LES) and hybrid LES-RANS offer high computational efficiency and accuracy. While data-driven models are in general believed to be more computationally efficient in predicting PLW dynamics, they in fact still call for substantial computational resources and efforts if the time for development, training and validation of a data-driven model is taken into account. The synthesized understanding of these modeling approaches is expected to facilitate the choosing of proper simulation approaches for PLW environment studies, to ultimately serving urban planning and building designs with respect to pedestrian comfort and urban ventilation assessment.
series	Architectural Intelligence
email
last changed	2025/01/09 15:00

_id	architectural_intelligence2022_17
id	architectural_intelligence2022_17
authors	Zihuan Zhang, Zao Li & Zhe Guo
year	2022
title	EEG-based spatial elements optimisation design method
doi	https://doi.org/https://doi.org/10.1007/s44223-022-00017-6
source	Architectural Intelligence Journal
summary	In the field of digital design, a recent hot topic is the study of the interaction between spatial environment design and human factors. Electroencephalogram (EEG) and eye tracking can be used as quantitative analysis methods for architectural space evaluation; however, conclusions from existing studies on improving the quality of spatial environments based on human factors tend to remain qualitative. In order to realise the quantitative optimisation design of spatial elements from human physiological data, this research used the digital space optimisation method and perceptual evaluation research. In this way, it established an optimisation method for built space elements in real-time using human psychological indicators. Firstly, this method used the specific indicators of the Meditation value and Attention value in the human EEG signal, taking the ThinkGear AM (TGAM) module as the optimisation objective, the architectural space colour and the window size as the optimisation object, and the multi-objective genetic algorithm as the optimisation tool. Secondly, this research combined virtual reality scenarios and parametric linkage models to realise this optimisation method to establish a tool platform and workflow. Thirdly, this study took the optimisation of a typical living space as an example and recruited 50 volunteers to participate in an optimisation experiment. The results indicated that with the iterative optimisation of the multi-objective genetic algorithm, the specific EEG index decreases significantly and the standard deviation of the in-dex fluctuates and decreases during the iterative process, which further indicates that the optimisation method established in this study with the specific EEG index as the optimisation objective is effective and feasible. In addition, this study laid the foundation for more EEG indicators and more complex spatial element opti-misation research in the future.
series	Architectural Intelligence
email
last changed	2025/01/09 15:00

_id	ecaade2022_168
id	ecaade2022_168
authors	Abdulmawla, Abdulmalik, Schneider, Sven, Koenig, Reinhard, Bielik, Martin and Fuchkina, Ekaterina
year	2022
title	Parametric Urban Data Structuring and Spatial Query - Advanced data mapping and selection methods for parametric modelling environments
doi	https://doi.org/10.52842/conf.ecaade.2022.2.277
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. 277–286
summary	This paper presents a method for organising urban data inside the CAD environment into a hierarchical structure, which promotes the ease of transferring information between all available urban elements, from streets to buildings passing by the plots and blocks. This is done using parametric methods that map the urban data using the available CAD and GIS records. Finally, the paper presents a couple of example scenarios where such methods are most needed and how much they could facilitate more detailed and complex data to be accessed, compared, and analysed.
keywords	Urban Query, Urban Geometry, Spatial Mapping
series	eCAADe
email
last changed	2024/04/22 07:10

_id	acadia22_001
id	acadia22_001
authors	Akbarzadeh, Masoud; Aviv, Dorit; Jamelle, Hina; Stuart-Smith, Robert
year	2022
title	ACADIA 2022: Hybrids and Haecceities [Projects Catalog]
source	ACADIA 2022: Hybrids and Haecceities [Projects Catalog of the 42nd Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-7-4]. University of Pennsylvania Stuart Weitzman School of Design. 27-29 October 2022. edited by M. Akbarzadeh, D. Aviv, H. Jamelle, and R. Stuart-Smith. 240p.
summary	Hybrids & Haecceities seeks novel approaches to design and research that dissolve binary conditions and inherent hierarchies in order to embrace new modes of practice. Haecceities describe the qualities or properties of objects that define them as unique. Concurrently, Hybrids are entities with characteristics enhanced by the process of combining two or more elements with different properties. In concert, these terms offer a provocation toward more inclusive and specific forms of computational design. Hybrids & Haecceities aligns with a fundamental shift away from abstract generalized models of production toward greater degrees of customization at unprecedented scales, made possible by the Fourth Industrial Revolution. With greater reliance on cyber-physical systems, this shift supports more diverse and considered forms of embodiment and participation in the built environment. Conversely, the design and construction industries have profound global effects with significant political, economic, and environmental impacts. The urgent need to decarbonize buildings, and at the same time, provide equitable infrastructure to communities at risk, places responsibility on the design disciplines to form new collaborations in the effort to address today’s social and ecological crises.
series	ACADIA
type	projects catalog
email
last changed	2024/02/06 14:00

_id	acadia22_000
id	acadia22_000
authors	Akbarzadeh, Masoud; Aviv, Dorit; Jamelle, Hina; Stuart-Smith, Robert
year	2022
title	ACADIA 2022: Hybrids and Haecceities [Proceedings]
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. 839p.
summary	Hybrids & Haecceities seeks novel approaches to design and research that dissolve binary conditions and inherent hierarchies in order to embrace new modes of practice. Haecceities describe the qualities or properties of objects that define them as unique. Concurrently, Hybrids are entities with characteristics enhanced by the process of combining two or more elements with different properties. In concert, these terms offer a provocation toward more inclusive and specific forms of computational design. Hybrids & Haecceities aligns with a fundamental shift away from abstract generalized models of production toward greater degrees of customization at unprecedented scales, made possible by the Fourth Industrial Revolution. With greater reliance on cyber-physical systems, this shift supports more diverse and considered forms of embodiment and participation in the built environment. Conversely, the design and construction industries have profound global effects with significant political, economic, and environmental impacts. The urgent need to decarbonize buildings, and at the same time, provide equitable infrastructure to communities at risk, places responsibility on the design disciplines to form new collaborations in the effort to address today’s social and ecological crises.
series	ACADIA
type	proceedings
email
last changed	2024/02/06 14:00

_id	cdrf2022_304
id	cdrf2022_304
authors	Anni Dai
year	2022
title	Co-creation: Space Reconfiguration by Architect and Agent Simulation Based Machine Learning
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_27
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
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	ascaad2022_086
id	ascaad2022_086
authors	Chehab, Aya; Nakhal, Bilal
year	2022
title	Exploring Virtual Reality as an Approach to Resurrect Destroyed Historical Buildings: An Approach to Revive the Destroyed "Egg Building" through VR
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. 609-631
summary	An important part of a city, that gives it a sense of community and character, is its history. One way of acknowledging this heritage is by preserving historic building and structures. Old buildings are witnesses to the aesthetic and cultural history of a city, helping to give people a sense of place and connection to the past. Unfortunately, despite their importance within the city, historical buildings are most of the time subject to demolition and to be replaced- leaving behind stories told and untold of what use to be. The paper, therefore, aims to explore the capability of the metaverse, using virtual reality touring, to revive the memory of historical buildings that are subject to fade. Where preserving historical buildings can not only act as a symbol of grandeur but is also vital for reviving the community’s collective memory. The case study focused upon in the research paper shows a first step in the development of an immersive virtual tour for the significant building of “The Egg” or “Beirut City Center” in Downtown- which is a building that witnessed a series of unfortunate events that lead to destruction, erasure, and demolition of the building. Therefore, examining the recovery and revival of this unique historic site in an unconventional way which is in the metaverse, specifically the Virtual Reality (VR). The paper assumes that virtual reality, as the main metaverse approach, would help people ‘remember’ and ‘mentally revive’ the destroyed historical buildings that once acted as the building blocks in the impacted city. To prove this hypothesis, two different methodologies will be used, by theorical analysis and literature review, such as analyzing the main keyword, and analyzing datum from previous works. The second method will rely on the physical methodology, where virtual 3D Models will be built in a computer software, Autodesk Revit, then imported within a VR experience for an enhanced experience within the historical site to preserve the historic buildings and revive the collective memory within the community, enabling people to view how these historic sites once were and how they have now become.
series	ASCAAD
email
last changed	2024/02/16 13:29

_id	ecaade2022_170
id	ecaade2022_170
authors	Colonneau, Téva, Chenafi, Sabrina and Mastrorilli, Antonella
year	2022
title	Digital Intervention Methodologies and Robotic Manufacturing for the Conservation and the Restoration of 20th-Century Concrete Architecture Damaged by Material Loss
doi	https://doi.org/10.52842/conf.ecaade.2022.2.197
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. 197–206
summary	This article deals with the characterisation of robotic manufacturing systems and digital interventions adapted for the conservation and the restoration of 20th-century concrete buildings. By exploiting the potential for analysis and implementation of robotic manufacturing technologies used in the field of heritage science, two associated non- invasive, non-destructive and integrated intervention solutions are presented here, using two research approaches. Through the use of digital recording tools, digital modelling / simulation and additive manufacturing techniques, the first approach develops a direct repair process by adding material with the help of aerial robots. The second focuses on printing recyclable plastic mouldings in order to reproduce partially degraded or completely destroyed architectural details. The results of these two diverse and complementary researches, as well as their experimental approaches applied to conservation and restoration practices, aim to test the proposed robotic manufacturing- based method, regarding the criteria of transferability and methodological feasibility.
keywords	20th-Century Concrete Built Heritage, Conservation and Restoration Practices, Digital Modelling, Robotic Manufacturing, Democratisation
series	eCAADe
email
last changed	2024/04/22 07:10

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