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_507
id	caadria2022_507
authors	Bolojan, Daniel, Vermisso, Emmanouil and Yousif, Shermeen
year	2022
title	Is Language All We Need? A Query Into Architectural Semantics Using a Multimodal Generative Workflow
doi	https://doi.org/10.52842/conf.caadria.2022.1.353
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 353-362
summary	This project examines how interconnected artificial intelligence (AI)-assisted workflows can address the limitations of current language-based models and streamline machine-vision related tasks for architectural design. A precise relationship between text and visual feature representation is problematic and can lead to "ambiguity‚ in the interpretation of the morphological/tectonic complexity of a building. Textual representation of a design concept only addresses spatial complexity in a reductionist way, since the outcome of the design process is co-dependent on multiple interrelated systems, according to systems theory (Alexander 1968). We propose herewith a process of feature disentanglement (using low level features, i.e., composition) within an interconnected generative adversarial networks (GANs) workflow. The insertion of natural language models within the proposed workflow can help mitigate the semantic distance between different domains and guide the encoding of semantic information throughout a domain transfer process.
keywords	Neural Language Models, GAN, Domain Transfer, Design Agency, Semantic Encoding, SDG 9
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	ecaade2022_221
id	ecaade2022_221
authors	Delikanli, Burak and Gül, Leman Figen
year	2022
title	Towards to the Hyperautomation - An integrated framework for Construction 4.0: a case of Hookbot as a distributed reconfigurable robotic assembly system
doi	https://doi.org/10.52842/conf.ecaade.2022.2.389
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. 389–398
summary	Almost every technological and industrial concept changes the built environment around us and our understanding of the architectural practice. Recently, Hyperautomation, an all-encompassing digital transformation with the help of advanced techniques, has been presented as a game-changing concept that can affect any industry. Despite this promising concept, the Architecture, Engineering, and Construction (AEC) industry seems far behind the latest technological breakthroughs and automation of processes compared to other industries. Therefore, this study provides a better understanding of adopting the novel Hyperautomation paradigm in the AEC industry by focusing on Industry 4.0. In this context, the first section introduces the Construction 4.0 concept, its counterpart in the AEC industry, briefly mentions fundamental approaches and indicates the need for a framework. The second section introduces an integrated framework throughout the entire building life-cycle for design and construction processes and exemplifies the stages in an autonomous system and their interrelationships. The third section presents a hypothetical case, a distributed reconfigurable robotic assembly system, and the assembler ‘HookBot’ to understand the relationships in an autonomous system better. The last section discusses the place of the Hyperautomation paradigm in architecture.
keywords	Autonomy, Autonomous Systems, Construction 4.0, Assembly Robotics
series	eCAADe
email
last changed	2024/04/22 07:10

_id	caadria2022_277
id	caadria2022_277
authors	Akbar, Zuardin, Wood, Dylan, Kiesewetter, Laura, Menges, Achim and Wortmann, Thomas
year	2022
title	A Data-Driven Workflow for Modelling Self-Shaping Wood Bilayer, Utilizing Natural Material Variations with Machine Vision and Machine Learning
doi	https://doi.org/10.52842/conf.caadria.2022.1.393
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 393-402
summary	This paper develops a workflow to train machine learning (ML) models with a small dataset from physical samples to predict the curvatures of self-shaping wood bilayers based on local variations in the grain. In contrast to state-of-the-art predictive models, specifically 1.) a 2D Timoshenko model and 2.) a 3D numerical model with a rheological model, our method accounts for natural and unavoidable material variations. In this paper, we only focus on local grain variations as the main driver for curvatures in small-scale material samples. We extracted a feature matrix from grain images of active and passive layers as a Grey Level Co-Occurrence Matrix and used it as the input for our ML models. We also analysed the impact of grain variations on the feature matrix. We trained and tested several tree-based regression models with different features. The models achieved very accurate predictions for curvatures in each sample (R;0.9) and extend the range of parameters that is incalculable by a Timoshenko model. This research contributes to the material-efficient design of weather-responsive shape-changing wood structures by further leveraging the use of natural material features and explainable data-driven modelling and extends the topic in ML for material behaviour-driven design among the CAADRIA community.
keywords	data-driven model, machine learning, material programming, smart material, timber structure, SDG 12
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	ecaade2022_270
id	ecaade2022_270
authors	Akcay Kavakoglu, Aysegul, Almac, Bihter, Eser, Begum and Alacam, Sema
year	2022
title	AI Driven Creativity in Early Design Education - A pedagogical approach in the age of Industry 5.0
doi	https://doi.org/10.52842/conf.ecaade.2022.1.133
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. 133–142
summary	This study presents a pedagogical experiment on the integration of AI into the project studio in the early stages of design education. The motivation of the study is to support creative encounters in design studios by promoting student-design representation, student-student, and student-artificial intelligence (AI) interaction. In the scope of this study, a short-term studio project is used as a case study to examine these creative encounters. The experiment covers five stages that enable a recursive analysis-synthesis action. The stages include (i) precedent analysis of a given set of building façades images, (ii) feature extraction, (iii) composing new façade representations through employing previously generated features, (iv) training an AI by the use of styleGAN2-ADA with the outcomes of stage 3, (v) Use of synthetically generated façade images as a design driver. The pedagogical experiment is evaluated through the lenses of novelty, style, surprisingness, and complexity concepts. The challenges and potentials are introduced, as well as elaborations on the future directions of the interplay between AI-oriented making and first-year student making.
keywords	Artificial Intelligence, Computational Creativity, Design Education, StyleGAN2-ADA
series	eCAADe
email
last changed	2024/04/22 07:10

_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_47
id	caadria2022_47
authors	An, Yudi
year	2022
title	Impact of Covid-19 on Associations between Land Use and Bike-Sharing Usage
doi	https://doi.org/10.52842/conf.caadria.2022.1.605
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. 605-614
summary	Bike-sharing as a human-centred, zero-emission, sustainable, alternative, and easily accessible transport mode has been implemented globally and consistently contributing to communities and the environment by alleviating consumption of natural sources, traffic congestion, and air pollution, which is considered a solution for future cities. The appearance of Covid-19 significantly impacts public transportation modes, including the bike-sharing system. The intention of this study was to investigate the spatiotemporal impact of the Covid-19 pandemic on associations between urban factors and bike-sharing usage in Los Angeles, United States, by analysing a sizeable actual trip dataset and employing geographically weighted regression (GWR) models. GWR was conducted for examining the varying spatial association between bike infrastructure, public transport, and urban land use factors, and bike-sharing trip volume. The results indicated that bike-sharing usage significantly decreased during the pandemic and essential service as restaurant was found consistently and positively associated with bike-sharing use. GWR provided clear spatial patterns of bike usage based on urban land use and big user databases. The outcomes of this study could inspire policymakers and shared mobility operators to support these safe, sustainable transport alters (such as rebalancing bike stations), help city resilience, and shape a sustainable future of mobility in the post-Covid-19 era.
keywords	Bike-Sharing, Covid-19, Land Use, Geographically Weighted Regression, Big Data, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	cdrf2022_150
id	cdrf2022_150
authors	Ana Zimbarg
year	2022
title	Mapping Plant Microclimates on Building Envelope Using Environmental Analysis Tools
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_13
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
summary	Can we build our cities not only for humans but also for all living systems? How can we consider other species occupants of the built environment? Planning cities as an element of the natural domain can reshape our relationship with nature and help redefine sustainability in architecture. Although current design strategies of reducing energy use does not rectify past/continuing im-balances in the natural environment. Landscape architect John Tillman Lyle expanded the regenerative design concept based on a range of ecological concepts. The environment's complexity, and the urge to use resources smartly, encouraged him to think about architecture and the environment as a whole system. John Lyle's regenerative design strategies scaffold a conceptual framework of treating the building as part of the landscape. Environmental tools such as Ladybug can map out the different conditions surrounding the building's envelope. This information can assist in selecting and populating a building façade with suitable plant species. The framework presents the building as a feature in the landscape, creating microclimatic conditions for various plant habitats. This conceptual workflow has the potential to become a tool to include regenerative principles in the urban context.
series	cdrf
email
last changed	2024/05/29 14:02

_id	caadria2022_336
id	caadria2022_336
authors	Araujo, Goncalo, Santos, Luis, Leitao, Antonioand Gomes, Ricardo
year	2022
title	AD-Based Surrogate Models for Simulation and Optimization of Large Urban Areas
doi	https://doi.org/10.52842/conf.caadria.2022.2.689
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. 689-698
summary	Urban Building Energy Model (UBEM) approaches help analyze the energy performance of urban areas and predict the impact of different retrofit strategies. However, UBEM approaches require a high level of expertise and entail time-consuming simulations. These limitations hinder their successful application in designing and planning urban areas and supporting the city policy-making sector. Hence, it is necessary to investigate alternatives that are easy-to-use, automated, and fast. Surrogate models have been recently used to address UBEM limitations; however, they are case-specific and only work properly within specific parameter boundaries. We propose a new surrogate modeling approach to predict the energy performance of urban areas by integrating Algorithmic Design, UBEM, and Machine Learning. Our approach can automatically model and simulate thousands of building archetypes and create a broad surrogate model capable of quickly predicting annual energy profiles of large urban areas. We evaluated our approach by applying it to a case study located in Lisbon, Portugal, where we compare its use in model-based optimization routines against conventional UBEM approaches. Results show that our approach delivers predictions with acceptable accuracy at a much faster rate.
keywords	urban building energy modelling, algorithmic design, machine learning in Architecture, optimization of urban areas, SDG 7, SDG 12, SDG 13
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	ecaade2022_85
id	ecaade2022_85
authors	Ataman, Cem, Herthogs, Pieter, Tuncer, Bige and Perrault, Simon
year	2022
title	Multi-Criteria Decision Making in Digital Participation - A framework to evaluate participation in urban design processes
doi	https://doi.org/10.52842/conf.ecaade.2022.1.401
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. 401–410
summary	Data-driven urban design processes consist of iterative actions of many stakeholders, which require digital participatory approaches for collecting data from a high number of participants to make informed decisions. It is important to evaluate such processes to justify the necessary costs and efforts while continuously improving digital participation. Nevertheless, such evaluation remains a challenge due to the involvement of different stakeholders including participants, designers, and policymakers in decision-making processes, and the lack of a systematic method to generalize participation outputs that are mostly situated and context based. By addressing this challenge, this paper introduces a Multi-Criteria Decision Analysis (MCDA) based framework to measure the effectiveness and quality of digital participation systematically and quantitatively. To achieve such evaluation, we conducted a digital participation experiment and investigated such processes with the help of participants, designers, and policymakers from Singapore and Hamburg. By formulating this framework, we aim to reveal perspectives of different stakeholders towards digital participation and enable the evaluation and comparison of digital participation processes based on the introduced digital participation criteria.
keywords	Data-Driven Urban Design, Digital Participation, Stakeholder Involvement, Multi-Criteria Decision Analysis (MCDA), Participation Quantification
series	eCAADe
email
last changed	2024/04/22 07:10

_id	ecaade2022_251
id	ecaade2022_251
authors	Awan, Abeeha, Lombardi, Davide, Ruffino, Paolo and Agkathidis, Asterios
year	2022
title	Efficacy of Gamification on Introductory Architectural Education: a literature review
doi	https://doi.org/10.52842/conf.ecaade.2022.2.553
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. 553–564
summary	Due to their recent popularity and success in fields such as engineering and business, gamification and by extension game design principles demonstrate the ability to teach complex, multi-disciplinary skills in an engaging, entertaining, and effective way. Architectural education especially introductory architectural education is a foundational and fundamental part of a budding architecture student’s career and oftentimes requires the understanding of dynamic systems, spatial reasoning, and experiential learning. The paper posits that gamification and game design principles can utilize certain components such as augmented reality, narrative design, and fun in order to create tools, gamify existing curriculum, and increase retention, engagement, and mastery of the difficult high-tech skillsets required of introductory architects. The paper focuses on reviewing and systematically analyzing research on gamification in education. In particular, it focuses on systematically reviewing and analyzing data from multiple relevant case studies chosen based on the application of technology such as augmented reality, the integration of game design, and the feasibility of gamification in educational environments. This data is examined based on feasibility, accessibility, and effects on information retention and the findings are outlined in a comparative table of methods, tools, and technologies organized based on their suitability. Ultimately, the paper aims to establish a framework for gamifying introductory modules in architectural education and hopes to create a future architectural augmented reality game meant to utilize gamification to help new architectural students.
keywords	Gamification, Game Design, Architectural Education, Educational Games, Retention, Learning
series	eCAADe
email
last changed	2024/04/22 07:10

_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
doi	https://doi.org/10.52842/conf.ecaade.2022.2.437
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
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	ecaade2022_312
id	ecaade2022_312
authors	Bhagat, Puja and Gursoy, Benay
year	2022
title	Stretch – 3D Print – Release: Formal descriptions of shape-change in 3D printed shapes on stretched fabrics
doi	https://doi.org/10.52842/conf.ecaade.2022.1.301
source	Pak, B, Wurzer, G and Stouffs, R (eds.), Co-creating the Future: Inclusion in and through Design - Proceedings of the 40th Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2022) - Volume 1, Ghent, 13-16 September 2022, pp. 301–310
summary	Researchers have previously explored 3D printing 2D shapes on stretched fabrics using plastic filaments. When released, the 3D printed plastic constrains the fabric to take a 3D form. By leveraging the material properties and resultant tension between the rigid plastic and pliable fabric, it is possible to create 3D forms which would otherwise be difficult to construct with traditional fabrication techniques. Multiple factors are in play in this shape-change. Therefore, it is often difficult to anticipate the 3D form that will emerge when the stretched fabric is released. In this paper, we present our systematic bottom-up explorations on the effects of various parameters on shape-change and formalize our findings as rules. These rules help to visualize the interrelations between (abstract) shapes designed for 3D printing, (material) shapes 3D printed on stretched fabric, and (material) shapes that emerge when the fabric is released. The rules also help to explore design possibilities with this technique in a more controlled, communicable, and repeatable way. We also present a series of vaulted forms that we generated using these rules and by stretching - 3D printing - releasing the fabric.
keywords	Material Computing, Shape-change, Adaptive Architecture, Digital Fabrication, 3D Printing on Textiles
series	eCAADe
email
last changed	2024/04/22 07:10

_id	ecaade2022_249
id	ecaade2022_249
authors	Carrasco Hortal, Jose, Hernandez Carretero, Sergi, Abellan Alarcon, Antonio and Bermejo Pascual, Jorge
year	2022
title	Algae, Gobiidae Fish and Insects that inspire Coastal Custodian Entities - Digital models for a real-virtual space using TouchDesigner
doi	https://doi.org/10.52842/conf.ecaade.2022.1.361
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. 361–370
summary	At the beginning of the twenty-first century, a discipline at the intersection of digital art and science explores how natural and artificial species are affected, coexist, and feed back to humans based on multi-scalar hybrid models. They embody types of surveillance entities or non-human custodians, and serve as inspiration for another generation of designs produced ten years later, the case studies that are presented here. This paper explains the design and parametric fundamentals of a digital architecture installation at the University of Alicante (Spain 2021) using CNC models and the TouchDesigner programming environment. The installation contains a clan of technological-virtual hybrid species, non-human custodians, which: (a) strengthen the Proposal’s discourse on the recognition of legal identity of the Mar Menor lagoon (Southeast Spain); (b) incorporate reactive designs; (c) help raise awareness of the effect of human actions on the lagoon’s ecology and nearby streams. The viewpoint is not anthropocentric, because it adopts the perspective of the foraging fish species or the oxygen-seeking algae species, among others, in order to reveal the deterioration processes. In most cases, the result is a sort of synaesthetic conversation that interweaves light, sound, movement and data.
keywords	Human-Machine Interaction, TouchDesigner, Non-Human Custodian, Responsive Interface, Ethnography of Things
series	eCAADe
email
last changed	2024/04/22 07:10

_id	caadria2022_522
id	caadria2022_522
authors	Cheng, Sifan, Leung, Carson Ka Shut and van Ameijde, Jeroen
year	2022
title	Evaluating the Accessibility of Amenities toward Walkable Neighourhoods: an Integrated Method for Testing Alternatives in a Generative Urban Design Process
doi	https://doi.org/10.52842/conf.caadria.2022.1.495
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. 495-504
summary	Studies have shown that walkable communities reduce traffic-related pollution and the risk of chronic illnesses, promote economic growth and prosperity, and stimulate community participation and the growth of social capital. To assess the walkability of urban areas, various methodologies have been developed around shortest-distance calculations between various points of interest (POIs), yet their outcomes do not guide potential urban design improvements. The absence of appropriate measurements and procedures that may give quantitative and actionable feedback to support design decision-making is one of the primary issues in building walkable neighborhoods. The work presented in this paper revolves around a new workflow, that employed Urbano, a mobility simulation and assessment tool, and integrated it within a generative design process to allowing for the quantitative evaluation on amenity accessibility for several alternative design scenarios for a case study site in Mong Kok, Hong Kong. The results show how this data-driven urban design process benefits from generative techniques to produce solutions with improved contextual connectivity, energy-efficient urban form, and good quality public spaces that contribute to the walkability of neighbourhoods.
keywords	Generative Urban Design, Walkability, Urbano, SDG 3, 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_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

_id	caadria2022_325
id	caadria2022_325
authors	Cui, Qinyu, Zhang, Shuyu and Huang, Yiting
year	2022
title	Retail Commercial Space Clustering Based on Post-carbon Era Context: A Case Study of Shanghai
doi	https://doi.org/10.52842/conf.caadria.2022.1.515
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. 515-524
summary	In the post-carbon era, it has become a development and research trend on adjusting commercial locations to help achieve resource conservation by using big data. This paper uses multi-source urban data and machine learning to make reasonable evaluations and adjustments to commercial district planning. Many relevant factors are affecting urban commercial agglomeration, but how to select the appropriate ones among the many factors is a problem to be considered and studied, while there may be spatial differences in the strength of each influencing factor on commercial agglomeration. Therefore, this paper takes Shanghai, a city with a high economic and commercial development level in China, as an example and identifies the influencing factors through a literature review. Next, this paper uses the machine learning BORUTA algorithm of features selection to screen the influencing factors. It then uses multi-scale geographically weighted regression model (MGWR) to analyse the spatial heterogeneity of factors affecting retail spatial agglomeration. Finally, based on the background of the changing transportation modes and the unchanged social activities in the post-carbon era, the future spatial planning pattern of retail commercial space is discussed to provide particular suggestions for the future location adjustment of urban commerce.
keywords	Business District Hierarchy, Agglomeration Effect, Spatial Variability, Multi-scale Geographically Weighted Regression Model, Machine Learning, Big Data Analysis, SDG 8, SDG 12
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	cdrf2022_3
id	cdrf2022_3
authors	Deli Liu and Keqi Wang
year	2022
title	Spatial Analysis of Villages in Jilin Province Based on Space Syntax and Machine Learning
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_1
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
summary	The development of machine learning technology gives architects and urban planners a new tool that can be used for research and design. The topic of this paper is to analyze the rural space of Jilin Province with the machine learning algorithms and space syntax theory, and to obtain the inherent formation and development laws of rural spatial forms, which can be used as a reference and evaluation system for subsequent rural development, and also can emphasize the locality and continuity of rural development. First, based on geographic information data, researching the connection between the distribution of villages and geographic data at a macro level and to classify them. Then, from each category, selecting one township and use all villages in its area as samples for the more specific study. Spatial features of individual village are extracted based on space syntax theory, and representative spatial features which can as feature values for cluster analysis are selected through comparative analysis. Then classify villages from high-dimensional data and explore their type characteristics. Finally, we hope the result of this study can help provide useful theoretical references for rural construction and nature conservation in the future.
series	cdrf
email
last changed	2024/05/29 14:02

_id	acadia23_v3_195
id	acadia23_v3_195
authors	Gandia, Augusto; Iverson, Aileen
year	2023
title	Hybrid Making: Physical Explorations with Computational Matter
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 3: Proceedings of the 43rd Annual Conference for the Association for Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9891764-1-0]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 24-32.
summary	This publication introduces hybrid making as the subject of a workshop conducted at the ACADIA Conference 2023 (See Fig. 1). We contextualize hybrid making in today’s design digitalization marked by the opening of Artificial Intelligence (AI), wherein AI is seen as an accelerant in the ongoing digital evolution. In design-related practice and research, digital design is increasingly dominant (See Fig. 2); as shown in a quick survey of ACADIA 2022 wherein 10 out of 14 workshops focused on topics related to digitalization. Given this context, the subject of our workshop, hybrid making, highlights that which is excluded in purely digital processes, namely a richness of designing associated with the qualities of materials and fabrication (See Fig. 3). Hybrid making seeks to influence digital evolution with aspects of analogue processes such as the integration of constraints related to actual physical materials and their context. The task of hybrid making, therefore, is to introduce actual constraints into digital ones (See Fig. 4).
series	ACADIA
type	workshop
email
last changed	2024/04/17 14:00

_id	caadria2022_458
id	caadria2022_458
authors	Gong, Pixin, Huang, Xiaoran, Huang, Chenyu and White, Marcus
year	2022
title	Machine Learning-Based Walkability Modeling in Urban Life Circle
doi	https://doi.org/10.52842/conf.caadria.2022.1.645
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. 645-654
summary	With China's fast urbanization, the study of the walkability of residents' life circles has become critical to improve people's quality of life. Traditional walkability calculations are based on Lawrence Frank's theory. However, the weighted calculation method cannot be adapted to ever-changing and complicated scenarios as the scope and topic of research transforming. This study investigated walkability at the community level by combining machine learning techniques with multi-source data. Feature indicators affecting walkability were estimated from multi-source data. Machine learning was used to refine the weighting calculation under the previous indicator framework. We compared the performance of 20 regression models from 6 different machine learning algorithms for estimating the walkability of 14578 communities in downtown Shanghai. It is concluded that the Bagged Tree Model (R2=0.86, RMSE=0.36862) achieves the best performance, which is used to revise the initial walkability index values. The workflow proposed in this paper allows for rapid application of expert empirical consensus to comprehensive urban design and detailed urban governance in the future.
keywords	Life Circle, Walkability Indicator, Multi-source Data, Machine Learning, Refined Urban Design, SDG 3, SDG 10, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

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