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_532
id	acadia23_v2_532
authors	Zhuang, Xinwei; Huang, Zixun; Zeng, Wentao; Caldas, Luisa
year	2023
title	Encoding Urban Ecologies: Automated Building Archetype Generation through Self-Supervised Learning for Energy Modeling
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 532-541.
summary	As the global population and urbanization expand, the building sector has emerged as the predominant energy consumer and carbon emission contributor. The need for inno- vative Urban Building Energy Modeling grows, yet existing building archetypes often fail to capture the unique attributes of local buildings and the nuanced distinctions between different cities, jeopardizing the precision of energy modeling. This paper presents an alternative tool employing self-supervised learning to distill complex geometric data into representative, locale-specific archetypes. This study attempts to foster a new paradigm of interaction with built environments, incorporating local parameters to conduct bespoke energy simulations at the community level. The catered archetypes can augment the precision and applicability of energy consumption modeling at the different scales across diverse building inventories. This tool provides a potential solution that encourages the exploration of emerging local ecologies. By integrating building envelope characteristics and cultural granularity into the building archetype generation process, we seek a future where architecture and urban design are intricately interwoven with the energy sector in shaping our built environments.
series	ACADIA
type	paper
email
last changed	2024/12/20 09:13

_id	ecaade2023_60
id	ecaade2023_60
authors	Mostafavi, Fatemeh and Khademi, Seyran
year	2023
title	Micro-Climate Building Context Visualization
doi	https://doi.org/10.52842/conf.ecaade.2023.2.009
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. 9–18
summary	Residential buildings are responsible for a considerable share of energy consumption and carbon emission. To decarbonize by 2050, as agreed in the Paris Climate Accord, immediate action for lowering the environmental impact of the building sector is needed. Environmental building design is a promising path, particularly during the early-stage design when design decisions are more impactful and long-lasting. One of the initial steps in the building design process is site assessment, during which the building context and environmental factors are to be evaluated. The surrounding environment plays a critical role in the building's energy performance and the thermal, visual, and acoustic comfort of its occupants. We choose quantitative approaches to study the complexity of the environmental design with respect to the building context by analyzing environmental cues embedded in architectural drawings that have been given less attention in previous studies. Nevertheless, disclosing site-specific geolocation data of buildings, more specifically residential type, is often challenging due to privacy issues. Therefore, there is a lack of context-related metadata in the current architectural datasets. Whereas simulation data are more available and provide a wealth of contextual information, however, it is less appealing for architects to interpret design patterns from extensive simulation figures. This research focuses on developing an interpretable visualization of the building’s micro-climate context from environmental simulation data without direct access to the geolocation of the site. The environmental context visualization is created from daylight, view, and noise from 3088 multifamily housing presented in the Swiss Buildings data set, merely based on available simulation data. The presented pipeline in this study facilitates the employment of existing simulation data in the built environment datasets while circumventing the concerns associated with geolocation data exposure. Further, the generated visualizations may be used to develop computer vision models for environmental assessments of building layout design.
keywords	Building Context, Environmental Design, Data Visualization, Big Data, Decarbonizing
series	eCAADe
email
last changed	2023/12/10 10:49

_id	ecaade2023_389
id	ecaade2023_389
authors	Szentesi-Nejur, Szende, de Luca, Francesco, Nejur, Andrei and Madelat, Payam
year	2023
title	Early Design Clustering Method Considering Equitable Daylight Distribution in The Adaptive Re-Use of Heritage Buildings
doi	https://doi.org/10.52842/conf.ecaade.2023.2.105
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. 105–114
summary	The re-use of existing buildings is gaining importance worldwide in the context of the carbon reduction efforts. In the case of Québec City there is a large number of heritage buildings that are currently unused. There are ongoing projects to breathe new life in these buildings, mainly by converting them in residential units. At the same time there is a growing preoccupation in Québec province towards energy efficiency and proper daylighting in both new and existing buildings. This is reflected in the emergence of new regulations concerning new buildings. In relation to existing buildings there are no regulations, but optimal daylight is a desired feature that can contribute significantly to the quality and attractiveness of newly designed spaces in the existing premises. In the case of heritage buildings, the additional conceptual challenge is to create properly daylit spaces while maintaining the character defining elements of the building, including facades and openings. Therefore, a digital workflow was developed to be integrated in the earliest schematic phase of design to ensure an equitable distribution of existing daylight in the newly created spatial units of heritage buildings. The method is based on an adapted constrained K-means clustering algorithm that works on daylight simulation data.
keywords	adaptive re-use, heritage buildings, daylight optimization, clustering method, early design digital tools
series	eCAADe
email
last changed	2023/12/10 10:49

_id	cdrf2023_305
id	cdrf2023_305
authors	Wang Yueyang, Philip F. Yuan
year	2023
title	A Parametric Approach Towards Carbon Net Zero in Agricultural Planning
doi	https://doi.org/https://doi.org/10.1007/978-981-99-8405-3_26
source	Proceedings of the 2023 DigitalFUTURES The 5st International Conference on Computational Design and Robotic Fabrication (CDRF 2023)
summary	This paper presents a new tool called the Space Data Generator, which is a parametric tool for organizing open spaces in rural areas. It can optimize the layout of buildings, solar panels, and agricultural planting spaces. While architects have been exploring ways to achieve net-zero carbon emissions in building design, it is equally important to attain a feasible carbon-neutral goal in rural areas. This is particularly crucial as 40% of the world’s population resides in rural areas, and transitioning towards a more sustainable and efficient economy can bring about not only moral but also economic benefits through proper management [1]. The Space Date Generator offers a powerful spatial planning approach for optimizing and planning agricultural resources on any given land. This innovative tool utilizes a combination of remote sensing to generate precise maps of the land, providing a comprehensive understanding of its terrain and potential agricultural resources. With this information, farmers and land managers can make informed decisions about crop selection, irrigation, and fertilizer application, among other factors. By using the Space Date Generator, they can optimize the use of available resources and maximize crop yields, ultimately increasing profitability and sustainability in agriculture [2]. Overall, the Space Date Generator is a valuable tool for any farmer or land manager looking to make the most of their land and resources. Its ability to provide detailed and accurate data on the land’s potential agricultural resources can help to streamline decision-making processes and ultimately lead to more efficient and sustainable land use practices. 1. The Space data generator uses the collected site coordinate information, geographical status (including stones, lakes, and water patterns), and the planted plants’ price as input. 2. Divide the site into small squares, then configure enough solar panels in the optimal sunlight area of the site to meet the user’s needs, and then plant crops on the remaining land. 3. The Space data generator will analyze the number of calories a household needs each year as a percentage. If there is a surplus, the excess food can be allocated to generate economic outcomes on the market. The land area at hand will be subdivided based on its sun ratio, which is a relatively straightforward process. However, we are also interested in determining the value of excess vegetation that may grow in the allocated space. In this regard, the Space Data Generator can prove to be a valuable tool, not only for this particular scenario but also in other types of agricultural settings such as those involving a mix of livestock and crops. Additionally, it may be possible to use this tool to calculate the optimal harvesting of various plant species at different points in the seasonal cycle. The Space Date Generator has the potential to offer valuable references for optimizing agricultural schemes. However, it must provide users with completely accurate results. Unfortunately, it currently cannot measure crucial factors such as soil type and moisture level, which are essential for agricultural planning. Despite this limitation, the Space Data Generator is a flexible tool that can be modified as research advances, allowing for more inputs to be added to improve its accuracy. Moreover, the Space Data Generator can provide guidance in various other areas based on the specific needs of the user. For instance, it can offer guidelines for traffic and urban design, among other demands. By leveraging this technology, users can access more precise and relevant information, enhancing their decisionmaking capabilities. As such, the Space Data Generator represents a valuable tool for various industries and sectors.
series	cdrf
email
last changed	2024/05/29 14:04

_id	ecaade2023_68
id	ecaade2023_68
authors	Mugita, Yuki, Fukuda, Tomohiro and Yabuki, Nobuyoshi
year	2023
title	Future Landscape Visualization by Generating Images Using a Diffusion Model and Instance Segmentation
doi	https://doi.org/10.52842/conf.ecaade.2023.2.549
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. 549–558
summary	When designing a new landscape, such as when demolishing buildings and building new ones, visual methods are effective in sharing a common image. It is possible to visualize future landscapes by making sketches and models, but this requires a great deal of skill and effort on the part of the creator. One method for visualizing future landscapes without the need for specialized skills or labor is image generation using deep learning, and a method has been proposed of using deep learning to generate landscape images after demolishing current buildings. However, there are two problems: the inability to remove arbitrary buildings and the inability to generate a landscape after reconstruction. Therefore, this study proposes a future landscape visualization method that integrates instance segmentation and a diffusion model. The proposed method can generate both post-removal images of existing buildings and post-reconstruction images based on text input, without the need for specialized technology or labor. Verification results confirmed that the post-removal image was more than 90% accurate when the building was removed and replaced with the sky. And the post-reconstruction image matched the text content with a best accuracy of more than 90%. This research will contribute to the realization of urban planning in which all project stakeholders, both professionals and the public, can directly participate by visualizing their own design proposals for future landscapes.
keywords	landscape visualization, deep learning, diffusion model, instance segmentation, text input, text-to-image model, inpainting
series	eCAADe
email
last changed	2023/12/10 10:49

_id	sigradi2023_259
id	sigradi2023_259
authors	Paiva, Ricardo, Braga, Bruno and Torquato Lima Da Silva, Joao Marcello
year	2023
title	Contemporary Architectures in Ceará [arq.con.ce]: Digital Diagrams
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. 325–336
summary	The production of contemporary architecture in Ceará is part of an economic, political and cultural-ideological context of alignment with global economic flows, constituting a significant collection to be documented and analyzed. The use of BIM as a technology that uses parametric models for inventory, documentation, intervention, management, promotion and analysis of existing projects and buildings allows, in addition to its (re)construction through virtual simulation, the exploration and management of information, becoming an object and source of study. Modeling also enables the construction of digital diagrams that allow the understanding of design processes, as well as interpretation. In this context, the objective of this paper is to analyze the process of constructing digital diagrams through the BIM platform as a strategy for analyzing contemporary architecture in Ceará, taking as a case study institutional buildings for higher education, namely the Advanced Campus of the Federal University of Ceará - UFC in Russas.
keywords	Digital diagram, BIM, 3D modeling, Ceará, Campus Avançado Russas (UFC).
series	SIGraDi
email
last changed	2024/03/08 14:07

_id	architectural_intelligence2023_3
id	architectural_intelligence2023_3
authors	Areti Markopoulou & Oana Taut
year	2023
title	Urban mining. Scoping resources for circular construction
doi	https://doi.org/https://doi.org/10.1007/s44223-023-00021-4
source	Architectural Intelligence Journal
summary	Operating with an abundance mindset – rather than from a place of “scarcity” – is a new paradigm, relevant to the practices of design and construction, which expands the definition of “resources” as well as where resources, both raw and non-raw materials, can be found and “mined”. Within three scales of design and planning, the current research – developed at the Institute for Advanced Architecture of Catalonia (IAAC) – examines the applications of computational technologies and life cycle assessment with the goal of setting up protocols for enhancing processes of urban mining and material reuse in future circular construction. In the material scale (i), selected projects experiment with up-cycled waste for the creation of new engineered composites for construction. In the building scale (ii), robotic technologies and computer vision are used to scan and sort the materials from existing buildings or demolition sites. Finally, in the urban scale (iii), google images, satellite data and ML are used to index the existing material stock in building façades in cities. The research calls for agents involved in design, planning and construction to shift their focus to the anthroposphere as a source of, rather than just a destination for, processed goods. The concept of “urban mining” is revisited to manage the material stock in urban systems and the use of anthropogenic resources in new production cycles. Through a multi-scalar approach, the outcome challenges the foundation of our material practices, presenting the potential to disrupt linear patterns of design and making in the built environment.
series	Architectural Intelligence
email
last changed	2025/01/09 15:00

_id	sigradi2023_209
id	sigradi2023_209
authors	Mateus, Daniel, Henriques, Gonçalo Castro, Nepomuceno, Taiane Melo and Moro, Ana Clara
year	2023
title	Carioca modern façades: improving the performance of existing Brazilian modern buildings through their shading systems, the Bristol case study
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. 461–472
summary	In the 1940s, modern Rio de Janeiro architects developed passive systems to improve buildings performance, without resorting to air conditioning systems. This article continues a research that studies the performance of a set of eight buildings, from the Carioca School, investigating in a prospective sense, how to improve their performance through computational methods. The authors select a new case study from these buildings, the Bristol building, and analyse the building performance, regarding insolation and illuminance, using the software Ladybug and Honeybee. Based on the simulation data, they use combinatorial modelling to change the position of each of the shading type’s modules, of the Bristol west façade to improve performance. Results suggest that is possible to improve the building performance, and the modern buildings legacy, using computational methods to improve and reduce energy consumption, encouraging natural systems and diminishing the need for artificial air conditioning systems.
keywords	Generative design, Shading performance, Insolation and illuminance analysis, Combinatorial modelling, Carioca modern façades
series	SIGraDi
email
last changed	2024/03/08 14:07

_id	acadia23_v2_44
id	acadia23_v2_44
authors	Pei, Wanyu; Stouffs, Rudi
year	2023
title	Parametric Archetype: A Synthetic Digital Method of Buildings Material Stock Representation Based on Distance Measurement
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 44-52.
summary	Building material stock (BMS) is a crucial inventory of secondary resources which contain comprehensive information for analyzing the potential of material reuse and urban harvesting. Due to the complexity of urban building systems and the large number of buildings, obtaining building information one by one is impractical. Existing methods for stock representation mainly start from data collection, and utilize techniques such as clustering, machine learning, computer vision, et cetera, to process and analyze large and complete datasets. However, it is noticed that data on urban buildings, especially for building materials, is very limited or rather inaccessible. Existing methods cannot be applied in data-scarce cities and are also challenging to update over time. Therefore, this study proposes a synthetic approach named parametric archetype for the digital repre- sentation of BMS. This approach combines distance measurement, which is a distance within dimensions describing building features, to match instance buildings dynamically to a parametric archetype with the highest similarity. The weight and types of different building features, which may influence building material (composition and properties) in distance measurement, can be determined by supervised, semi-supervised, or unsuper- vised learning, whether relying on ample available data or domain rules/expert knowledge when data is scarce. This way, the parametric archetype model can use data more effi- ciently to form a synthetic and extensible representation for urban-level BMS (Figure 1). The parametric archetype is anticipated to offer an approach for describing, quantifying, and modeling the real building material stock system incrementally and transparently.
series	ACADIA
type	paper
email
last changed	2024/12/20 09:12

_id	acadia23_v3_201
id	acadia23_v3_201
authors	Boon, Gary
year	2023
title	Towards a Low Carbon Additive Manufacturing
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	In this workshop, the DART laboratory, Sika, and XtreeE collaborated to showcase the potential of 3D printing in reimagining the design-to-fabrication process, with a strong emphasis on rethinking concrete elements and enhancing their performance. More than a decade of digitization of concrete through 3D printing has primarily focused on labor reduction and process automation, often overlooking ways to enhance the quality of the output. The goal of this workshop was to raise awareness on the untapped potential of 3D concrete printing in advancing architectural possibilities and elevating the overall construction landscape.
series	ACADIA
type	workshop
last changed	2024/04/17 14:00

_id	sigradi2023_165
id	sigradi2023_165
authors	Chávez Valdés, Florencia, Delgado Smulders, María Constanza, Karich, Juan Cristóbal and Raspall, Felix
year	2023
title	Design of a Low-cost Extruder for Large Scale Additive Manufacturing with Earth-based Pastes
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. 301–312
summary	This research explores the potential of earth construction as a low-carbon solution for large-scale additive manufacturing in the global south. Existing expensive printing technologies for earth-based structures limit their application in economically challenged regions. To address this, the study proposes and tests a low-cost extruder design using a paint/mortar mixer powertool, a metal hopper, and a 3D printed nozzle. The extruder is mounted on a CNC manipulator for precise control. Printing tests demonstrate the reliability of the design. The findings show that the low-cost extruder is a viable and sustainable option for large-scale printing, significantly reducing construction costs. By promoting the use of earth-based pastes, the research contributes to more environmentally friendly construction practices, aiding in mitigating the construction industry's environmental impact in the long run.
keywords	Additive Manufacturing, Robotics, Earth Construction, Large-scale Additive Manufacturing
series	SIGraDi
email
last changed	2024/03/08 14:06

_id	ecaade2023_258
id	ecaade2023_258
authors	Hong, Soon Min, Kim, Geunjae, Gu, Hyeongmo, Kim, Taehoon and Choo, Seungyeon
year	2023
title	Development of Building Component Combination Algorithms for Generative Design-based DfMA Applications
doi	https://doi.org/10.52842/conf.ecaade.2023.2.207
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. 207–216
summary	The AEC industry faces challenges such as low productivity, high carbon emissions, labor shortages, and construction site accidents. To address these issues, the industry focuses on MMC and DfMA based on BIM. This research paper develops building component combination algorithms for generative design-based applications. Using GD, the proposed method optimises the layout and selection of building components while considering construction costs and a specified budget range. A case study of a five-component building system with four types of components demonstrates the method's ability to generate diverse design alternatives. Designers can efficiently explore and evaluate these alternatives based on economic and design criteria. However, the method has limitations, such as the exclusion of MEP facilities as GD parameters and the focus on optimising the budget as a single goal. Nevertheless, this study lays the foundation for applying DfMA in the early design stage and utilizing GD technology in construction projects.
keywords	DfMA, OSC, Generative Design, Optimisation
series	eCAADe
email
last changed	2023/12/10 10:49

_id	ecaade2023_227
id	ecaade2023_227
authors	Moorhouse, Jon and Freeman, Tim
year	2023
title	Towards a Genome for Zero Carbon Retrofit of UK Housing
doi	https://doi.org/10.52842/conf.ecaade.2023.2.197
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. 197–206
summary	The United Kingdom has some of the worst insulated housing stock in Northern Europe. This is in part due to the age of housing in the UK, with over 90% being built before 1990 [McCrone 2017, Piddington 2020]. Moreover, 85% of current UK housing will still be in use in 2050 by which stage their Government are targeting Net Carbon Zero [Eyre 2019]. Domestic energy use accounts for around 25% of UK carbon emissions. The UK will need to retrofit 20 million dwellings in order to meet this target. If this delivery were evenly spread, it would equate to over 2,000 retrofit completions each day. Government-funded initiatives are stimulating the market, with upwards of 60,000 social housing retrofits planned for 2023, but it is clear that a system must be developed to enable the design and implementation of housing-stock improvement at a large scale.This paper charts the 20-year development of a digital approach to the design for low-carbon domestic retrofit by architects Constructive Thinking Studio Limited and thence documents the emergence of a collaborative approach to retrofit patterns on a National scale. The author has led the Research and Development stream of this practice, developing a Building Information Modelling methodology and integrated Energy Modelling techniques to optimise design for housing retrofit [Georgiadou 2019, Ben 2020], and then inform a growing palette of details and a database of validated solutions [Moorhouse 2013] that can grow and be used to predict options for future projects [D’Angelo 2022]. The data is augmented by monitoring energy and environmental performance, enabling a growing body of knowledge that can be aligned with existing big data to simulate the benefits of nationwide stock improvement. The paper outlines incremental case studies and collaborative methods pivotal in developing this work The proposed outcome of the work is a Retrofit Genome that is available at a national level.
keywords	Retrofit, Housing, Zero-Carbon, BIM, Big Data, Design Genome
series	eCAADe
email
last changed	2023/12/10 10:49

_id	ijac202321308
id	ijac202321308
authors	Xu, Hang; Tsung-Hsien Wang
year	2023
title	A generative computational workflow to develop actionable renovation strategies for renewable built environments: A case study of Sheffield
source	International Journal of Architectural Computing 2023, Vol. 21 - no. 3, 516–535
summary	Urban building energy modelling (UBEM) is a prevalent research method to examine the multi-scale building to urban renovation in mitigating global energy-related carbon emissions. However, only a few studies delineate a complete workflow from generation to application using UBEM. In particular, to facilitate the designing of sustainable built environments, existing research needs to emphasize the integration of multiscale energy performance evaluation within the design development process for architects and urban planners. The key challenges lie in the need for integrated datasets and incompatibility between software tools required for designing, modelling, and evaluation. This paper presents a comprehensive methodological framework to investigate applicable urban decarbonization strategies. A case study of Sheffield in the UK demonstrates the development of an automated and standardized computational workflow. This data-driven workflow aims to evaluate energy demand and supply scenarios at an urban scale to access the potential of decarbonizing built environments. The workflow is designed to be adaptable to various scales of urban regions, given a suitable geographic information system (GIS) dataset.
keywords	Parametric design, urban sustainability, urban building energy modelling, building performance simulation, decarbonization
series	journal
last changed	2024/04/17 14:30

_id	sigradi2023_246
id	sigradi2023_246
authors	YAO, Chaowen and Fricker, Pia
year	2023
title	Building Green Decarbonization for Urban Digital Twin – Estimating Carbon Sequestration of Urban Trees by Allometric Equations using Blend Types of Point Cloud
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. 91–102
summary	The achievement of climate neutrality is a fundamental goal for cities in the next 30 years. In order to achieve this goal, this research focuses on a novel tree carbon sequestration utilizing point clouds. Using a multi-algorithm workflow, tree information is extracted to calculate carbon storage from airborne and mobile laser scanning data, using Helsinki as a test case. The study employs local maximum and seeded region growing algorithms to detect tree locations and crown extents from aerial point clouds. A Python script is generated using the DBSCAN algorithm to extract tree point clouds and trunk diameters. The established allometric equations are utilized to calculate the carbon sequestration of trees. The results are integrated into the digital platform, filling the gap in urban digital twins' carbon storage information. This innovative approach will contribute significantly to urban planning and decision-making for sustainable cities in the face of climate challenges.
keywords	Urban tree, Carbon sequestration, Point cloud applications, Density-based clustering, Urban digital twin.
series	SIGraDi
email
last changed	2024/03/08 14:06

_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_144
id	ecaade2023_144
authors	Irsyad, Naufal Andi, Alkadri, Miktha Farid, De Luca, Francesco, Arif, Muhammad and Heinzelmann, Florian
year	2023
title	Tropical Responsive Envelopes for Urban Heat Island mitigation in tropical countries
doi	https://doi.org/10.52842/conf.ecaade.2023.2.249
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. 249–258
summary	Since tropical countries present wet and dry seasons all year round, the objective of solar envelopes significantly shifts and aims to minimize the penetration of direct sun access to the buildings, due to high temperatures. As a consequence, the air conditioner (AC) frequently becomes a short-term solution to mitigate a building’s temperature, which unfortunately contributes to an annual increase in energy consumption. Accordingly, shading conditions become considerably relevant for urban form generation in tropical contexts, especially to reduce the UHI effect for tropical high-rise building areas. The concept of tropical responsive envelopes is then proposed not only to create shading for adjacent buildings but also to perform self-building protection that refers to self-shading envelopes. This concept specifically deals with solar-radiation reduction in order to achieve appropriate daylight in both the proposed building and the surrounding context. To do so, a solar protection plane and ray tracing analysis are performed based on shading performance criteria. In parallel, solar radiation simulation is applied to identify potential solar collectors on the building surfaces. This provides architects with a comprehensive method of tackling passive solar design strategy for urban equatorial climates
keywords	Solar Envelopes, Shading Envelopes, Self-shading Envelopes, Tropical Responsive Envelopes
series	eCAADe
email
last changed	2023/12/10 10:49

_id	caadria2023_412
id	caadria2023_412
authors	Li, Yuanyuan, Huang, Chenyu and Yao, Jiawei
year	2023
title	Optimising the Control Strategies for Performance-Driven Dynamic Building Facades Using Machine Learning
doi	https://doi.org/10.52842/conf.caadria.2023.1.199
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. 199–208
summary	The balance between energy consumption and indoor environmental comfort is a continuing research topic in building energy efficiency. The dynamic façades (DF) are considered a practical approach to separate the sun and create more shadows for buildings with curtain walls, reducing the HVAC system's energy consumption. However, the design complexity of the DF leads to a time-consuming simulation process, making it difficult to modify the design parameters in the early design stage efficiently. This paper provides optimized control strategies for four dynamic façade prototypes. We use explainable machine learning to explore the relationship between design parameters of DF and indoor performance, including Energy Use Intensity (EUI) and Daylight Glare Probability (DGP). We deployed the trained model in optimizing the rotation angle of DF per hour on a typical day to minimize the EUI and DGP of the target room. The results show that the rotation angle of DF significantly affects the DGP, whereas the room size affects EUI performance more than rotation angles. Optimized control strategies of DF bring a maxim 13.5% EUI decrease and 51.7% reduction of DGP. Our work provides a generalizable design flow for performance-driven dynamic skin design.
keywords	Dynamic façade, Energy consumption, Indoor comfort, computational simulation, Multi-objective optimization, Machine learning
series	CAADRIA
email
last changed	2023/06/15 23:14

_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	ecaade2023_460
id	ecaade2023_460
authors	Papanikolaou, Kyratsoula-Tereza, Liapi, Katherine, Sibetheros, Ioannis and Vlachaki, Evangelia
year	2023
title	A Simulation Model for Stormwater Runoff Management in Urban Blocks
doi	https://doi.org/10.52842/conf.ecaade.2023.2.287
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. 287–296
summary	The shift towards Water Sensitive Urban Design (WSUD) has become a necessity for many cities with warm and dry climates which are still using conventional rainwater management and are adversely affected by extreme rainfall episodes or persistent heatwaves. However, WSUD still remains a complex issue for architects that requires specialized technical knowledge, relevant experience, and interdisciplinary collaboration. The paper presents initial results of an “architect friendly” computer-based model, developed by the authors, that facilitates the assessment of the efficacy of non-conventional, water-sensitive, stormwater management strategies in urban blocks, measured by the stormwater runoff mitigation. The model allows for the design and visualization of stormwater management scenarios on surfaces of selected urban blocks, as well as the quantitative comparison of their impact on runoff reduction. Users can choose from a range of different Best Management Practices (BMPs) from the BMP library of the model, create their own stormwater management scenarios, assess them, and finally choose the most appropriate one with regard to its impact on stormwater runoff. BMPs added in the library include green roofs with different substrate depths and plant types, facades, stormwater harvesting cisterns, raingardens and permeable paving. The Grasshopper programming environment has been used for the development of the model, the integration of as-built climate data and the incorporation of runoff estimation equations based on the Soil Conservation Service Curve Number (SCS-CN) method. The paper compares the results of different stormwater management scenarios that involve several BMP types and geometries, applied on an urban block in Athens, Greece. Based on this case study results, preliminary conclusions are drawn regarding the user-friendliness of the model’s interface and data requirements, as well as the effectiveness of the model’s visualization process.
keywords	Stormwater best management practices, urban blocks, runoff mitigation, decision support tool, environmental impact visualization
series	eCAADe
email
last changed	2023/12/10 10:49

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