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	acadia23_v2_560
id	acadia23_v2_560
authors	Saldana Ochoa, Karla; Huang, Lee-Su; Guo, Zifeng; Bokhari, Adil
year	2023
title	Playing Dimensions: Images / Models / Maps: Conceptualizing Architecture with Big Data and Artificial Intelligence
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 2: Proceedings of the 43rd Annual Conference for the Association for Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9891764-0-3]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 560-568.
summary	This article presents a novel architecture design workflow that explores the intersection of Big Data, Artificial Intelligence (AI), and storytelling by scraping, encoding, and mapping data, which can then be implemented through Virtual Reality (VR) and Augmented Reality (AR) technologies. In contrast to conventional approaches that consider AI solely as an optimization tool, this workflow embraces AI as an instrument for critical thinking and idea generation. Rather than creating new AI models, this workflow encourages architects to experiment with existing ones as part of their practice. The workflow revolves around the concept of ""Canonical architecture,"" where data-driven techniques serve to traverse dimensions and representations, encompassing text, images, and 3D objects. The data utilized consists of information specific to the project, gathered from social media posts, including both images and text, which provide insights into user needs and site charac- teristics. Additionally, roughly 9,000 3D models of architectural details extracted from 38 different architectural projects were used. The primary objective is to assist architects in developing a workflow that does not suggest starting from scratch or a tabula rasa, but to work with already hyper-connected objects, be it text, images, 3D models, et cetera. These conceptualizations can then be enacted in game engines and/or experimented with in AR/ VR platforms, while keeping their connections alive. Through this process, the framework aims to develop a sensibility of working with large amounts of data without losing focus, and letting the electric grounds of the internet help us in articulating projects.
series	ACADIA
type	paper
email
last changed	2024/12/20 09:13

_id	sigradi2023_416
id	sigradi2023_416
authors	Machado Fagundes, Cristian Vinicius, Miotto Bruscato, Léia, Paiva Ponzio, Angelica and Chornobai, Sara Regiane
year	2023
title	Parametric environment for internalization and classification of models generated by the Shap-E tool
source	García Amen, F, Goni Fitipaldo, A L and Armagno Gentile, Á (eds.), Accelerated Landscapes - Proceedings of the XXVII International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2023), Punta del Este, Maldonado, Uruguay, 29 November - 1 December 2023, pp. 1689–1698
summary	Computing has been increasingly employed in design environments, primarily to perform calculations and logical decisions faster than humans could, enabling tasks that would be impossible or too time-consuming to execute manually. Various studies highlight the use of digital tools and technologies in diverse methods, such as parametric modeling and evolutionary algorithms, for exploring and optimizing alternatives in architecture, design, and engineering (Martino, 2015; Fagundes, 2019). Currently, there is a growing emergence of intelligent models that increasingly integrate computers into the design process. Demonstrating great potential for initial ideation, artificial intelligence (AI) models like Shap-E (Nichol et al., 2023) by OpenAI stand out. Although this model falls short of state-of-the-art sample quality, it is among the most efficient orders of magnitude for generating three-dimensional models through AI interfaces, offering practical balance for certain use cases. Thus, aiming to explore this gap, the presented study proposes an innovative design agency framework by employing Shap-E connected with parametric modeling in the design process. The generation tool has shown promising results; through generations of synthetic views conditioned by text captions, its final output is a mesh. However, due to the lack of topological information in models generated by Shap-E, we propose to fill this gap by transferring data to a parametric three-dimensional surface modeling environment. Consequently, this interaction's use aims to enable the transformation of the mesh into quantifiable surfaces, subject to collection and optimization of dimensional data of objects. Moreover, this work seeks to enable the creation of artificial databases through formal categorization of parameterized outputs using the K-means algorithm. For this purpose, the study methodologically orients itself in a four-step exploratory experimental process: (1) creation of models generated by Shap-E in a pressing manner; (2) use of parametric modeling to internalize models into the Grasshopper environment; (3) generation of optimized alternatives using the evolutionary algorithm (Biomorpher); (4) and classification of models using the K-means algorithm. Thus, the presented study proposes, through an environment of internalization and classification of models generated by the Shap-E tool, to contribute to the construction of a new design agency methodology in the decision-making process of design. So far, this research has resulted in the generation and classification of a diverse set of three-dimensional shapes. These shapes are grouped for potential applications in machine learning, in addition to providing insights for the refinement and detailed exploration of forms.
keywords	Shap-E, Parametric Design, Evolutionary Algorithm, Synthetic Database, Artificial Intelligence
series	SIGraDi
email
last changed	2024/03/08 14:09

_id	cdrf2023_315
id	cdrf2023_315
authors	Wenjing Li, Xinhui Xu, Mehdi Makvandi, Zhuoyang Sun, Philip F. Yuan
year	2023
title	The Use of Normative Energy Calculation for Natural Ventilation Performance-Driven Urban Block Morphology Generation
doi	https://doi.org/https://doi.org/10.1007/978-981-99-8405-3_27
source	Proceedings of the 2023 DigitalFUTURES The 5st International Conference on Computational Design and Robotic Fabrication (CDRF 2023)
summary	Exploring the three-state coupling relationship between “urban block morphology, carbon emissions, and human comfort” is necessary when making preliminary design decisions. Currently, morphology generative design is subject to interactions between the level of model definition and simulation duration. Self-intelligent and intelligent generative design workflows using evolutionary algorithms are now becoming an effective solution to this problem. This paper incorporates a dedicated controllable ventilation model based on a normative performance calculator and proposes it in the morphology feedback generation execution of the automated design process. The aim is to develop this automated design method from ambient environment driving only to outside-interior coupling natural potential ventilation influencing morphology generation, with the aim of providing technical support for carbon emission performance-oriented and indoor human comfort-oriented design of urban blocks.
series	cdrf
email
last changed	2024/05/29 14:04

_id	ascaad2023_071
id	ascaad2023_071
authors	Gabr, Rana
year	2023
title	Exploring the Integration of Mid-Journey AI for Architectural Post-Occupancy Evaluation - Prioritizing Experiential Assessment: Case Study of the Egyptian Museum and National Museum of Egyptian Civilization
source	C+++: Computation, Culture, and Context – Proceedings of the 11th International Conference of the Arab Society for Computation in Architecture, Art and Design (ASCAAD), University of Petra, Amman, Jordan [Hybrid Conference] 7-9 November 2023, pp. 518-550.
summary	The post-occupancy evaluation (POE) process, traditionally reliant on subjective user feedback and observations, has evolved in response to global concerns like climate change and sustainability. This shift towards greater objectivity and quantification reflects an increased focus on precise measurement of environmental and performance metrics. Consequently, architectural assessment is now more quantitatively oriented, moving away from a predominantly experiential emphasis. This research investigates the integration of the emerging AI tool Mid-journey into the POE process, specifically targeting the evaluation of experiential aspects in architectural design. It proposes that AI tools can be instrumental for architects and evaluators by translating user feedback into visual representations and conceptual insights. The study aims to initiate a discourse on the role of text-to-image models in assessing user experiences, potentially becoming integral to the design and concept generation process. The research combines quantitative methods like surveys and AI-driven experiments with qualitative approaches such as observations and interviews to offer enhancement proposals for Egyptian museums, comparing traditional POE solutions and frameworks with new proposed framework that incorporates AI-generated alternatives. This study emphasizes the dual role of museums as artifact custodians and platforms for public education about ancient cultures. It highlights the imperative to transform Egyptian national museums into immersive learning environments, rather than mere storage spaces. The aspiration is to create museums that securely display and preserve artifacts while fostering educational engagement in preserving our shared history.
series	ASCAAD
email
last changed	2024/02/13 14:40

_id	sigradi2023_114
id	sigradi2023_114
authors	Huang, Sheng-Yang, Wang, Yuankai and Jiang, Qingrui
year	2023
title	(In)Visible Cities: Exploring generative artificial intelligence'screativity through the analysis of a conscious journey in latent space
source	García Amen, F, Goni Fitipaldo, A L and Armagno Gentile, Á (eds.), Accelerated Landscapes - Proceedings of the XXVII International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2023), Punta del Este, Maldonado, Uruguay, 29 November - 1 December 2023, pp. 717–728
summary	The rise of generative AI has redefined architectural design by introducing latent space, challenging traditional methods. This paper aims to explore, structure, and analyse latent journeys, drawing from analytical design discourses. We construct journeys towards 'Isaura' from 'Invisible Cities' by Italo Calvino, bridging literature and visual narratives, utilising the text-image generating software, Midjourney. The objective is to identify spatial configurations that align with the designer's interpretation of the text, ensuring the accuracy of visual elements. Structured as a Markov (stochastic) process, the experiment encompasses four primary stages to offer a rational explanation for the journey and the role of each segment. Findings emphasise the potential of latent space in augmenting architectural design and underscore the necessity for analytical tools to avert the reduction of design to trivial formalism. The study's outcome suggests that understanding and leveraging the traits of latent space can nurture a more meaningful engagement with AI-driven design, presenting a novel approach to architectural creativity.
keywords	Latent Space, Generative Artificial Intelligence, Text-to-image Generation, Architectural Creativity, Spatial Analysis
series	SIGraDi
email
last changed	2024/03/08 14:07

_id	ecaade2023_205
id	ecaade2023_205
authors	Meeran, Ahmed and Joyce, Sam
year	2023
title	Rethinking Airport Spatial Analysis and Design: A GAN based data driven approach using latent space exploration on aerial imagery for adaptive airport planning
doi	https://doi.org/10.52842/conf.ecaade.2023.2.501
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 501–510
summary	Airports require long term planning, balancing estimations of future demand against available airfield land and site constraints. This is becoming more critical with climate change and the transition to sustainable aviation fuelling infrastructure. This paper demonstrates a novel procedure using Satellite Imagery and Generative Learning to aid in the comparative analysis and early-stage airfield design. Our workflow uses a GAN trained on 2000 images of airports transforming them into a high-dimensional latent space capturing the typologies’ large-scale features. Using a process of projection and dimensional-reduction methods we can locate real-world airport images in the generative latent space and vice-versa. With this capability we can perform comparative “neighbour” analysis at scale based on spatial similarity of features like airfield configuration, and surrounding context. Using this low-dimensional 3D ‘airport designs space’ with meaningful markers provided by existing airports allows for ‘what if’ modelling, such as visualizing an airport on a site without one, modifying an existing airport towards another target airport, or exploring changes in terrain, such as due to climate change or urban development. We present this method a new way to undertake case study, site identification and analysis, as well as undertake speculative design powered by typology informed ML generation, which can be applied to any typologies which could use aerial images to categorize them.
keywords	Airport Development, Machine Learning, GAN, High Dimensional Analysis, Parametric Space Exploration, tSNE, Latent Space Exploration, Data Driven Planning
series	eCAADe
email
last changed	2023/12/10 10:49

_id	ijac202321205
id	ijac202321205
authors	Zhuang, Xinwei; Ju, Yi; Yang, Allen; Caldas, Luisa
year	2023
title	Synthesis and generation for 3D architecture volume with generative modeling
source	International Journal of Architectural Computing 2023, Vol. 21 - no. 2, 297–314
summary	Generative design in architecture has long been studied, yet most algorithms are parameter-based and require explicit rules, and the design solutions are heavily experience-based. In the absence of a real understanding of the generation process of designing architecture and consensus evaluation matrices, empirical knowledge may be difficult to apply to similar projects or deliver to the next generation. We propose a workflow in the early design phase to synthesize and generate building morphology with artificial neural networks. Using 3D building models from the financial district of New York City as a case study, this research shows that neural networks can capture the implicit features and styles of the input dataset and create a population of design solutions that are coherent with the styles. We constructed our database using two different data representation formats, voxel matrix and signed distance function, to investigate the effect of shape representations on the performance of the generation of building shapes. A generative adversarial neural network and an auto decoder were used to generate the volume. Our study establishes the use of implicit learning to inform the design solution. Results show that both networks can grasp the implicit building forms and generate them with a similar style to the input data, between which the auto decoder with signed distance function representation provides the highest resolution results.
keywords	data-driven design, 3D deep learning, architecture morphology representation, auto decoder, generative adversarial neural network
series	journal
last changed	2024/04/17 14:30

_id	ecaade2023_436
id	ecaade2023_436
authors	Bank Stigsen, Mathias, Moisi, Alexandra, Rasoulzadeh, Shervin, Schinegger, Kristina and Rutzinger, Stefan
year	2023
title	AI Diffusion as Design Vocabulary - Investigating the use of AI image generation in early architectural design and education
doi	https://doi.org/10.52842/conf.ecaade.2023.2.587
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 587–596
summary	This paper investigates the potential of Text-to-Image AI in assisting the ideation phase in architectural design and education. The study proposes a structured workflow and tests it with first-year architecture students. It aims to create a comprehensive design vocabulary by using AI-generated images as primary design references and incorporating them into a modelling workflow. The paper implements a process combining specific vocabulary extraction, image generation, 2D to 3D translation, and spatial composition within a six weeklong design course. The findings suggest that such a process can enhance the ideation phase by generating new and diverse design inspirations, improve spatial understanding through the exploration of various design elements, and provide students with a targeted visual vocabulary that helps define design intention and streamlines the modelling process.
keywords	Artificial Intelligence, Text-to-Image, Midjourney, Architectural design, Design ideation, 2D to 3D
series	eCAADe
email
last changed	2023/12/10 10:49

_id	ecaade2023_48
id	ecaade2023_48
authors	Doumpioti, Christina and Huang, Jeffrey
year	2023
title	Text to Image to Data
doi	https://doi.org/10.52842/conf.ecaade.2023.2.541
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 541–548
summary	Recent advancements in text-to-image technology have transformed the landscape of computational creativity by enabling the generation of conceptual images. By implementing innovative standards for image generation, we can now shift our focus from the constraints of notational design communication to more purposeful reflection, opening up new design possibilities for future architectures informed by contemporary ideas, concepts, and concerns. In light of the pressing climatic crisis, this paper specifically explores the relationship between text-to-image generation and the integration of environmental sensibility, aiming to explore how digital information (bits) can translate into physical reality (atoms). Our case study focuses on specific residential building typology and its façade morphology to analyse the environmental responsiveness of the design. We propose a workflow that merges creative and analytic processes, through different stages, including diffusion-generated conceptual images, 2D to 3D through depth-mapping and point-cloud meshing, semantic segmentation analysis and sunlight simulation. The paper describes the methods and their combination into a coherent workflow, outlines encountered setbacks, and suggests stages for further improvement.
keywords	Computational Creativity, Text-to-Image, Simulation, Environmental Responsiveness, Machine Intelligence
series	eCAADe
email
last changed	2023/12/10 10:49

_id	caadria2023_446
id	caadria2023_446
authors	Guida, George
year	2023
title	Multimodal Architecture: Applications of Language in a Machine Learning Aided Design Process
doi	https://doi.org/10.52842/conf.caadria.2023.2.561
source	Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 561–570
summary	Recent advances in Natural Language Processing (NLP) and Diffusion Models (DMs) are leading to a significant change in the way architecture is conceived. With capabilities that surpass those of current generative models, it is now possible to produce an unlimited number of high-quality images (Dhariwal and Nichol 2021). This opens up new opportunities for using synthetic images and marks a new phase in the creation of multimodal 3D forms, central to architectural concept design stages. Presented here are three methodologies of generation of meaningful 2D and 3D designs, merging text-to-image diffusion models Stable Diffusion, and DALL-E 2 with computational methods. These allow designers to intuitively navigate through a multimodal feedback loop of information originating from language and aided by artificial intelligence tools. This paper contributes to our understanding of machine-augmented design processes and the importance of intuitive user interfaces (UI) in enabling new dialogues between humans and machines. Through the creation of a prototype of an accessible UI, this exchange of information can empower designers, build trust in these tools, and increase control over the design process.
keywords	Machine Learning, Diffusion Models, Concept Design, Semantics, User Interface, Design Agency
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	acadia23_v2_420
id	acadia23_v2_420
authors	Guida, George; Escobar, Daniel; Navarro, Carlos
year	2023
title	3D Neural Synthesis: Gaining Control with Neural Radiance Fields
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 2: Proceedings of the 43rd Annual Conference for the Association for Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9891764-0-3]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 420-428.
summary	This research introduces a novel, 3D machine-learning, aided design approach for early design stages. Integrating language within a multimodal framework grants designers greater control and agency in generating 3D forms. The proposed method leverages Stable Diffusion and Runway's Gen1 through the generation of 3D Neural Radiance Fields (NeRFs), surpassing the limitations of 2D image-based outcomes in aiding the design process. This paper presents a flexible machine-learning workflow taught to students in a conference workshop, and outlines the multimodal methods used - between text, image, video, and NeRFs. The resultant NeRF design outcomes are contextualized within a Unity agent-based, virtual environment for architectural simulation, and are expe- rienced with real-time VFX augmentations. This hybridized design process ultimately highlights the importance of feedback loops and control within machine-learning, aided-design processes.
series	ACADIA
type	paper
email
last changed	2024/12/20 09:12

_id	acadia23_v2_582
id	acadia23_v2_582
authors	Wu, Kaicong; Li, Chenming; Su, Wenjun
year	2023
title	The Chair Game Experiment: Transforming Multiplayer Design Processes with Text-to-Image Generation and 2D-to-3D Modelling
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 2: Proceedings of the 43rd Annual Conference for the Association for Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9891764-0-3]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 582-595.
summary	The urgency for an inclusive architectural design process in conceptualizing the built environment stems from the need to establish effective communication between under- represented groups and design professionals. However, various challenges hinder the development of an inclusive design process that accommodates diverse stakeholders. Individual designers or selective design teams are frequently limited by their own visions, causing them to potentially overlook alternative solutions. Moreover, stakeholders who lack professional training might struggle to articulate their expectations. The emergence of generative AI (artificial intelligence) technologies has significantly reduced the tech- nical barriers in design, and has empowered non-professionals to vividly express their ideas regarding forms and spaces. This has presented a valuable opportunity to better understand the perspectives of underrepresented groups through visual representations. Therefore, this research aims to explore the impact of image generation on the democ- ratization of the design process. Using chair design as a testing ground, we propose an evolutionary computing framework that simulates interactions among designers and participants empowered by emerging AI technologies. To investigate the potential impact of image generation, we have implemented a multiplayer design game to allow computing agents to compete in exploring 3D chair forms. Through this approach, we aim to gain insights into how image generation influences design decisions, whether it generates more diversified solutions, and what values could be introduced into the built environment.
series	ACADIA
type	paper
email
last changed	2024/12/20 09:13

_id	sigradi2023_435
id	sigradi2023_435
authors	Conceiçao, Sandro, Diehl, Natália and Bruscato, Leia
year	2023
title	ChatGPT for Briefing Creation
source	García Amen, F, Goni Fitipaldo, A L and Armagno Gentile, Á (eds.), Accelerated Landscapes - Proceedings of the XXVII International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2023), Punta del Este, Maldonado, Uruguay, 29 November - 1 December 2023, pp. 819–830
summary	This study aims to investigate the stages involved in document creation during the architecture and design project phases, through the integration of the Briefing with the assistance of ChatGPT-3.5, with the purpose of assessing the relevance, correspondence, and coherence of data generated by Artificial Intelligence (AI). The research involved the use of two distinct prompts: one featuring a more generic nature, and the other defined by a higher level of detail. It was found that the generic prompt yielded innovative options – not foreseen in the reference sources –, however with lower correspondence. The detailed request was limited to the predefined structure, resulting in greater correspondence and partial consistency with the parameters established in the reference literature. It was possible to conclude that, while AI automates the briefing stages, the input and critical analysis of the generated text require substantial subject knowledge for consistent results.
keywords	Artificial Intelligence, ChatGPT, Briefing, Architecture Programme, Design Process.
series	SIGraDi
email
last changed	2024/03/08 14:07

_id	caadria2023_304
id	caadria2023_304
authors	Lin, Bing-Xuan and Hou, June-Hao
year	2023
title	Design of Bistable Deployable Scissor Structures Consisting of Translational Units Based on Flat Retraction Logic
doi	https://doi.org/10.52842/conf.caadria.2023.2.541
source	Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 541–550
summary	The subject of this research is the study of the retraction change mode of deployable scissor grids based on the Hoberman mechanism. The retraction logic of this type of flat mechanism can be changed mainly by moving the pivot point of the rod and using bistable deployable scissor structures consisting of translational units. Therefore, the mechanism can remain flat while it retracts, and the irregular translational units allow for a greater variety of surface variations in the shape of the mechanism. Through the study of the scissor system, a simplified mathematical model is used to explore the geometric potential, and a formula for complete flat retraction is derived. Following the input of defined data using digital tools, the remaining translational scissor units that conform to the retraction logic are generated. Then, irregular linkage mechanisms are created that can retract from 3D to 2D, with the opening mode not being limited to the radial sphere or other mean geometries. These results provide a unique retraction mode for deployable scissor grids, thus facilitating the collection and transportation of such mechanisms in practical applications.
keywords	flat retraction logic, geometric design, translational units, pivot point, bistable deployable scissor structures
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	sigradi2023_480
id	sigradi2023_480
authors	Schaffer, Maria Luz, Sturba, Yamile Anabella, De Angeli, Maria Agustina, Chiarella, Mauro, Salinas Arriagada, Alexis and Banda-Pérez, Pablo
year	2023
title	Additive Architecture: Emergency habitat, from transience to permanence.
source	García Amen, F, Goni Fitipaldo, A L and Armagno Gentile, Á (eds.), Accelerated Landscapes - Proceedings of the XXVII International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2023), Punta del Este, Maldonado, Uruguay, 29 November - 1 December 2023, pp. 1433–1442
summary	The present work addresses the subject of Additive Architecture by means of the ideation of sets of habitable emergency enclosures, materialised with mixed technologies for the Litoral Centro xxx region. The case of application, emergency housing, poses a "complex existential phenomenon" in Latin America, where the temporary inevitably becomes permanent, preserving its identity and initial precariousness for a long time. Assuming the challenge of transforming temporary housing as a permanent habitat, parametric definitions are designed that synthesise the current material restrictions of 3D printing technologies in South America (know-how of leading researchers), a technical solution is developed with mixed technologies and growth variables of contingency settlements are explored as emerging landscapes of current techno-diversity and their projection as future technopolitics.
keywords	Additive architecture, Emergency housing, 3D-printing, Parametric design
series	SIGraDi
email
last changed	2024/03/08 14:08

_id	caadria2023_57
id	caadria2023_57
authors	Alva, Pradeep, Mosteiro-Romero, Martin, Pei, Wanyu, Bartolini, Andrea, Yuan, Chao and Stouffs, Rudi
year	2023
title	Bottom-Up Approach for Creating an Urban Digital Twin Platform and Use Cases
doi	https://doi.org/10.52842/conf.caadria.2023.1.605
source	Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 605–614
summary	Smart city initiatives have been a driving force for city-level dataset collection and the development of data-driven applications that benefit effective city management. There is a need to demonstrate use cases for effective city management using the available dataset. Urban Digital Twin (UDT) is a 3D city model that can integrate multi-disciplines and improve systems operability on a digital platform. However, UDTs are developed within organisations, and there is only limited availability of authoritative open 3D datasets to explore the potential of UDT concepts. This paper reports a methodology for creating a UDT platform for visualising and querying city energy data. We demonstrate a bottom-up approach to constructing an integrated 3D city dataset and create a query system for rapid access and navigation of the 3D city dataset through a visualisation platform using Cesium Ion. Various use cases are explored based on the dataset, such as building material stock management, energy demand simulation, electric vehicles (EV) demand and flexibility, and estimation of greenhouse gas (GHG) emissions. These use cases can help decision-makers and stakeholders involved in city planning and management. Furthermore, it provides a guideline for developers willing to create UDT applications for smart city initiatives.
keywords	Energy modelling, City dataset, Urban analytics, Building Stock Management, Decarbonisation
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	sigradi2023_46
id	sigradi2023_46
authors	Barashkov, Julia
year	2023
title	Customising Urban Joy: Urban Planning Mechanisms for the Mass - Customisation of Cities, through the Quantifiable Nature of Joy Using Geo-tagged Social Media Data
source	García Amen, F, Goni Fitipaldo, A L and Armagno Gentile, Á (eds.), Accelerated Landscapes - Proceedings of the XXVII International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2023), Punta del Este, Maldonado, Uruguay, 29 November - 1 December 2023, pp. 31–42
summary	The paper examines citizen participation in a digitally-driven society and the disparity between desired and existing cities. It emphasises the need to transform cities into adaptable environments that respond to the needs of residents. Traditional top-down urban planning often fails to match the flexible nature of digitised urban residents. To address this, an agent-based model is employed, evaluating urban environments based on individual sentiment derived from social media API. The study case of Wittenberge, Germany, showcases the methodology, including the creation of a 3D digital twin using open data sources and generating agents with unique personalities from social media keywords. These agents' "life satisfaction score" reflects their ability to fulfil daily needs and preferences within a 20-minute walking radius.
keywords	Data-based urban design, Citizen participation, Agent-based modelling, Social media sentiment analysis, Co-creation in cities
series	SIGraDi
email
last changed	2024/03/08 14:06

_id	ecaade2023_92
id	ecaade2023_92
authors	Buš, Peter, Russell, Peter, Curry, Terrence and Wu, Chaoyun
year	2023
title	A Parametric Tolerance Model for Numerically Controlled Digital Fabrication: Adaptation of kit-of-parts components for a pre-manufactured WikiHouse scenario
doi	https://doi.org/10.52842/conf.ecaade.2023.1.551
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 1, Graz, 20-22 September 2023, pp. 551–558
summary	Numerically controlled digital fabrication (NC) encompasses precise toolpaths generated according to the predefined geometry, material characteristics, type of machining processes, and processing tools. This includes a definition of tolerances, necessary for a successful and smooth assembly process when dealing with component-driven assembly after the components were fabricated. However, the prototyping and assembly practice often encounters a variety of issues in real fabrication and assembly scenarios: humidity of the environment, specific material properties, such as the ability of the stock material to change its dimensions according to the unexpected environmental conditions, unexpected different dimensions of the stock material delivered from a factory or a producer, variety of fabrication producers with different machine types, or unique conditions of a production machine. Therefore, there is a need to adapt the geometry of components to different humidity scenarios and combinations of stock material properties or specific machine or production-related processes, which influence the dimensions, and the tolerances embedded into the process of toolpath generation. To address these, we introduce an adaptive parametric model. This has been created as an open-source and open-access algorithm within the Grasshopper environment to easily modify the dimensions of tolerances according to specific and unexpected conditions. The paper also elaborates on and discusses the limitations of such an approach and the scalability and extendibility of the proposed tolerance engine.
keywords	tolerance model, digital manufacturing, intelligent kit-of-parts assemblies
series	eCAADe
email
last changed	2023/12/10 10:49

_id	acadia23_v2_408
id	acadia23_v2_408
authors	C Kim, Frederick; Johanes, Mikhael; Huang, Jeffrey
year	2023
title	Flow2Form: A Flow-Driven Computational Framework for Early Stage Architectural Design
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 2: Proceedings of the 43rd Annual Conference for the Association for Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9891764-0-3]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 408-418.
summary	Flows have been a persistent theme as a rational and formal basis for architecture. This paper introduces a flow-based design framework for architecture using parametric modeling and machine learning analysis. It explores the integration of flows’ rational and figurative aspects into the early stages of the design process. The research employs para- metric tools and machine learning algorithms to represent and analyze flows, focusing on the artisanal and craft processes aiming for circular proto-typology as a transfor- mative architecture. The framework involves three stages: 3D flow modeling, machine learning analysis of formal and topological properties, and process-based programming and optimization. The results include volumetric representations of 16 artisanal flows and the classification of nodes based on their formal and topological characteristics. The framework enables the exploration of flow-driven architectural design, and bridges the gap between human interpretation and computational design. The research contributes to understanding flows to form in architecture, and the potential of machine learning in shaping architectural space.
series	ACADIA
type	paper
email
last changed	2024/12/20 09:12

_id	caadria2023_305
id	caadria2023_305
authors	Deshpande, Rutvik, Vijay Patel, Sayjel, Weijenberg, Camiel, Nisztuk, Maciej, Corcuera, Miriam, Luo, Jianxi and Zhu, Qihao
year	2023
title	Generative Pre-Trained Transformers for 15-Minute City Design
doi	https://doi.org/10.52842/conf.caadria.2023.1.595
source	Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 595–604
summary	Cities globally are adopting “The 15-Minute City” as an urban response to various crises, including the Covid-19 Pandemic and climate change. However, the challenge of linking location-specific requirements with potential design solutions hinders its effective implementation. To bridge this gap, this paper introduces a novel urban 15 Minute City concept generation tool that applies an artificial intelligence (AI) method called a pre-trained language model (PLM). The PLM model was fine-tuned with structured examples based on 15-Minute City principles. Using a PLM, the tool maps 15-Minute City concepts to a location and project specific prompt, automatically generating neighbourhood design concepts in the form of natural language.
keywords	15-Minute City, neighbourhood design, data-driven design, urban design, natural language generation, Generative Pre-trained Transformer
series	CAADRIA
email
last changed	2023/06/15 23:14

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