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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	acadia20_208
id	acadia20_208
authors	Zheng, Hao; Wang, Xinyu; Qi, Zehua; Sun, Shixuan; Akbarzadeh, Masoud
year	2020
title	Generating and Optimizing a Funicular Arch Floor Structure
doi	https://doi.org/10.52842/conf.acadia.2020.2.208
source	ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 208-217.
summary	In this paper, we propose a geometry-based generative design method to generate and optimize a floor structure with funicular building members. This method challenges the antiquated column system, which has been used for more than a century. By inputting the floor plan with the positions of columns, designers can generate a variety of funicular supporting structures, expanding the choice of floor structure designs beyond simply columns and beams and encouraging the creation of architectural spaces with more diverse design elements. We further apply machine learning techniques (artificial neural networks) to evaluate and optimize the structural performance and constructability of the funicular structure, thus finding the optimal solutions within the almost infinite solution space. To achieve this, a machine learning model is trained and used as a fast evaluator to help the evolutionary algorithm find the optimal designs. This interdisciplinary method combines computer science and structural design, providing flexible design choices for generating floor structures.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	caadria2020_146
id	caadria2020_146
authors	Lertsithichai, Surapong
year	2020
title	Fantastic Facades and How to Build Them
doi	https://doi.org/10.52842/conf.caadria.2020.1.355
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 355-364
summary	As part of an ongoing investigation in augmented architecture, the exploration of an architectural facade as a crucial element of architecture is a challenging design experiment. We believe that new architectural facades when seamlessly integrated with augmented architecture, enhanced with multiple functionalities, interactivity and performative qualities can extend a building's use beyond its typical function and limited lifespan. Augmented facades or "Fantastic Facades," can be seen as a separate entity from the internal spaces inside the building but at the same time, can also be seen as an integral part of the building as a whole that connects users, spaces, functions and interactivity between inside and outside. An option design studio for 4th year architecture students was offered to conduct this investigation for a duration of one semester. During the process of form generations, students experimented with various 2D and 3D techniques including biomimicry and generative designs, biomechanics or animal movement patterns, leaf stomata patterns, porous bubble patterns, and origami fold patterns. Eventually, five facade designs were carried on towards the final step of incorporating performative interactions and contextual programs to the facade requirements of an existing building or structure in Bangkok.
keywords	Facade Design; Augmented Architecture; Form Generation; Surface System; Performative Interactions
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	sigradi2020_60
id	sigradi2020_60
authors	Asmar, Karen El; Sareen, Harpreet
year	2020
title	Machinic Interpolations: A GAN Pipeline for Integrating Lateral Thinking in Computational Tools of Architecture
source	SIGraDi 2020 [Proceedings of the 24th Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Online Conference 18 - 20 November 2020, pp. 60-66
summary	In this paper, we discuss a new tool pipeline that aims to re-integrate lateral thinking strategies in computational tools of architecture. We present a 4-step AI-driven pipeline, based on Generative Adversarial Networks (GANs), that draws from the ability to access the latent space of a machine and use this space as a digital design environment. We demonstrate examples of navigating in this space using vector arithmetic and interpolations as a method to generate a series of images that are then translated to 3D voxel structures. Through a gallery of forms, we show how this series of techniques could result in unexpected spaces and outputs beyond what could be produced by human capability alone.
keywords	Latent space, GANs, Lateral thinking, Computational tools, Artificial intelligence
series	SIGraDi
email
last changed	2021/07/16 11:48

_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	acadia20_74
id	acadia20_74
authors	Bucklin, Oliver; Born, Larissa; Körner, Axel; Suzuki, Seiichi; Vasey, Lauren; T. Gresser, Götz; Knippers, Jan; Menges,
year	2020
title	Embedded Sensing and Control
doi	https://doi.org/10.52842/conf.acadia.2020.1.074
source	ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 74-83.
summary	This paper investigates an interactive and adaptive control system for kinetic architectural applications with a distributed sensing and actuation network to control modular fiber-reinforced composite components. The aim of the project was to control the actuation of a foldable lightweight structure to generate programmatic changes. A server parses input commands and geometric feedback from embedded sensors and online data to drive physical actuation and generate a digital twin for real-time monitoring. Physical components are origami-like folding plates of glass and carbon-fiber-reinforced plastic, developed in parallel research. Accelerometer data is analyzed to determine component geometry. A component controller drives actuators to maintain or move towards desired positions. Touch sensors embedded within the material allow direct control, and an online user interface provides high-level kinematic goals to the system. A hierarchical control system parses various inputs and determines actuation based on safety protocols and prioritization algorithms. Development includes hardware and software to enable modular expansion. This research demonstrates strategies for embedded networks in interactive kinematic structures and opens the door for deeper investigations such as artificial intelligence in control algorithms, material computation, as well as real-time modeling and simulation of structural systems.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	ecaade2022_161
id	ecaade2022_161
authors	Kharbanda, Kritika, Papadopoulou, Iliana, Pouliou, Panagiota, Daw, Karim, Belwadi, Anirudh and Loganathan, Hariprasath
year	2022
title	LearnCarbon - A tool for machine learning prediction of global warming potential from abstract designs
doi	https://doi.org/10.52842/conf.ecaade.2022.2.601
source	Pak, B, Wurzer, G and Stouffs, R (eds.), Co-creating the Future: Inclusion in and through Design - Proceedings of the 40th Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2022) - Volume 2, Ghent, 13-16 September 2022, pp. 601–610
summary	The new construction that is projected to take place between 2020 and 2040 plays a critical role in embodied carbon emissions. The change in material selection is inversely proportional to the budget, as the project progresses. Given the fact that early-stage design processes often do not include environmental performance metrics, there is an opportunity to investigate a toolset that enables early-stage design processes to integrate this type of analysis into the preferred workflow of concept designers. The value here is that early-stage environmental feedback can inform the crucial decisions that are made in the beginning, giving a greater chance for a building with better environmental performance in terms of its life cycle. This paper presents the development of a tool called LearnCarbon, as a plugin of Rhino3d, used to educate architects and engineers in the early stages about the environmental impact of their design. It facilitates two neural networks trained with the Embodied Carbon Benchmark Study by Carbon Leadership Forum, which learn the relationship between building geometry, typology, and structure with the Global Warming potential in tCO2e. The first one, a regression model, is able to predict the GWP based on the massing model of a building, along with information about typology and location. The second one, a classification model, predicts the construction type given a massing model and target GWP. LearnCarbon can help improve the building life cycle impact significantly, through early predictions of the structure’s material, and can be used as a tool for facilitating sustainable discussions between the architect and the client.
keywords	Machine Learning, Carbon Emissions, LCA, Rhino Plug-in
series	eCAADe
email
last changed	2024/04/22 07:10

_id	ecaade2020_246
id	ecaade2020_246
authors	Kozikoglu, Nilüfer, Çebi, Pelin Dursun, Yazar, Tugrul, Balaban, Büºra, Üneºi, Ogulcan and Erden, Melike Sena
year	2020
title	Dynamic Architectural Canvas - Designing a relational mapping based architectural design tool
doi	https://doi.org/10.52842/conf.ecaade.2020.1.229
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 1, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 229-238
summary	Configuration of spatial set-up is a major act in the architectural design process. Configuration implies a set of relationships among the spatial elements that can be represented as a network pattern. This kind of spatial network is significant for architectural design as it reveals social implications by mapping interactions between users, indicating functional and latent routes and spatial proximities. This paper concentrates on network thinking in architecture and presents the development of a new software plugin and compares the plugin to similar software studies that allow coding spatial networks and exploring their potentials. The experimental study is also tested by student workshops, explains the motives for the plug-in currently prototyped as a Grasshopper definition and how-it-works.
keywords	Space syntax; Network thinking; Scenario based Design; Evidence based architectural design
series	eCAADe
email
last changed	2022/06/07 07:51

_id	ecaade2020_283
id	ecaade2020_283
authors	Sebestyen, Adam and Tyc, Jakub
year	2020
title	Machine Learning Methods in Energy Simulations for Architects and Designers - The implementation of supervised machine learning in the context of the computational design process
doi	https://doi.org/10.52842/conf.ecaade.2020.1.613
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 1, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 613-622
summary	Application of Machine Learning (ML) in the field of architecture is a worthwhile topic to discuss in the context of digital architecture. Authors propose to extend this discussion, presenting an integrated ML pipeline built with the state-of-the-art data science tools. To investigate the affordances of such pipelines, an ML model being able to predict the environmental metrics of a generalized facade system is created. This approach is valid for arbitrary facades, as long as the proposed design could be discretized in the form analogous to the data generated for the ML model training. The presented experiment evaluates the precision of the sunlight hours and radiation values predictions, aiming at the application in the early design phases. Conducted investigation builds up on the knowledge embedded in the Grasshopper and Ladybug toolsets. Potential application of Convolutional Neural Networks and categorical datasets for classifications tasks to increase the precision of the ML models have been identified. Possibility to extend the approach beyond the workspace of Rhino and Grasshopper is suggested. Further research outlook, investigating the data pattern recognition capabilities in relation to the three-dimensional forms discretized as multidimensional arrays, is stated.
keywords	Machine Learning; Environmental Analysis; Parametric Design; Supervised Learning
series	eCAADe
email
last changed	2022/06/07 08:00

_id	acadia20_238
id	acadia20_238
authors	Zhang, Hang
year	2020
title	Text-to-Form
doi	https://doi.org/10.52842/conf.acadia.2020.1.238
source	ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 238-247.
summary	Traditionally, architects express their thoughts on the design of 3D architectural forms via perspective renderings and standardized 2D drawings. However, as architectural design is always multidimensional and intricate, it is difficult to make others understand the design intention, concrete form, and even spatial layout through simple language descriptions. Benefiting from the fast development of machine learning, especially natural language processing and convolutional neural networks, this paper proposes a Linguistics-based Architectural Form Generative Model (LAFGM) that could be trained to make 3D architectural form predictions based simply on language input. Several related works exist that focus on learning text-to-image generation, while others have taken a further step by generating simple shapes from the descriptions. However, the text parsing and output of these works still remain either at the 2D stage or confined to a single geometry. On the basis of these works, this paper used both Stanford Scene Graph Parser (Sebastian et al. 2015) and graph convolutional networks (Kipf and Welling 2016) to compile the analytic semantic structure for the input texts, then generated the 3D architectural form expressed by the language descriptions, which is also aided by several optimization algorithms. To a certain extent, the training results approached the 3D form intended in the textual description, not only indicating the tremendous potential of LAFGM from linguistic input to 3D architectural form, but also innovating design expression and communication regarding 3D spatial information.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	caadria2020_045
id	caadria2020_045
authors	Zheng, Hao and Ren, Yue
year	2020
title	Machine Learning Neural Networks Construction and Analysis in Vectorized Design Drawings
doi	https://doi.org/10.52842/conf.caadria.2020.2.707
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 707-716
summary	Machine Learning, a recently prevalent research domain in data prediction and analysis, has been widely used in a variety of fields. In the design field, especially for architectural design, a machine learning method to learn and generate design data as pixelized images has been developed in previous researches. However, proceeding pixelized image data will cause the problems of precision loss and calculation waste, since the geometric architectural design data is efficiently stored and presented as vectorized CAD files. Thus, in this article, the author developed a specific machine learning neural network to learn and predict design drawings as vectorized data, speeding up the learning and predicting process, while improving the accuracy. First, two necessary geometric tests have been successfully done, which shows the central concept of neural network construct. Then, a design rule prediction model was built to demonstrate the methods to optimize the neural network and data structure. Lastly, a generation model based on human-made design data was constructed, which can be used to predict and generate the bedroom furniture positions by inputting the boundary data of the room, door, and window.
keywords	Machine Learning; Artificial Intelligence; Generative Design; Geometric Design
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	caadria2020_090
id	caadria2020_090
authors	Crolla, Kristof and Goepel, Garvin
year	2020
title	Designing with Uncertainty - Objectile vibrancy in the TOROO bamboo pavilion
doi	https://doi.org/10.52842/conf.caadria.2020.2.507
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 507-516
summary	This paper challenges digital preoccupations with precision and control and questions the status of tolerance, allowance and error in post-digital, human-centred architectural production. It uses the participatory action research design-and-build project TOROO, a light-weight bending-active bamboo shell structure, built in Hsinchu, Taiwan, in June 2019, as a demonstrator project to discuss how protean digital design diagrams, named 'vibrant objectiles,' are capable of productively absorbing serendipity throughout project crystallisation processes, increasing designer agency in challenging construction contexts with high degrees of unpredictability. The demonstrator project is then used to discuss future research directions that were exposed by the project. Finally, the applicability of working with 'vibrant objectiles' is discussed beyond its local project use. Common characteristics and requirements are extracted, highlighting project setup preconditions for which the scope covered by the architect needs to be both broadened and relaxed to allow for feedback from design implementation phases.
keywords	Post-digital; Bamboo; Bending-active shell structures; Uncertainty; Objectile
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	sigradi2020_975
id	sigradi2020_975
authors	Mangrich, Camila Poeta; Almeida, Renato Luiz Martins de; Harthmann, Gabriela Peglow; Kos, José Ripper
year	2020
title	Urban Mobility and Database Allied to Environmental Regeneration of a University Campus
source	SIGraDi 2020 [Proceedings of the 24th Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Online Conference 18 - 20 November 2020, pp. 975-982
summary	This study departs from the data exploration of the people dynamics within a university campus to foster solutions of sustainable mobility and environmental regeneration. The research has dealt with a critical challenge of guaranteeing the privacy of individuals' registration data, following the recommendations listed in the foreseen General Data Protection Law. While ensuring anonymity, the work aims to assess the contribution of databases as infrastructures that can convey relevant knowledge beyond scientific research and to guide public management to the trends advocated for the future of universities.
keywords	University campus, Mobility, Database visualization, Sustainability
series	SIGraDi
email
last changed	2021/07/16 11:53

_id	ijac202018204
id	ijac202018204
authors	Nathansohn, Nof; Molly Mason, David Allen White, Hugh Timothy Ebdy, Yaara Yacoby, Hila Sharabi, and Lawrence Sass
year	2020
title	Design for disassembly: Using temporary fabrication for land politics in the Negev
source	International Journal of Architectural Computing vol. 18 - no. 2, 155-173
summary	Political conflicts have increasingly displaced people from their homes, necessitating various forms of temporary structures and housing. However, these shelters are often one-size-fits-all and do not take into account the individual requirements, family structures, or cultural needs of these communities. This article explores how digital fabrication can be used to empower disenfranchised communities to act as their own architects. Because the police demolish the structures in Al Araqib every 3 weeks, the residents have to rebuild their structures, and appropriate architecture as a resistance tool, and not only as a housing solution. This circumstance allows us to develop a structure designed primarily for the condition of rapid disassembly that can additionally be produced with a low-tech setup of a mobile computer numerical control router. Through this case study with the Bedouin village Al Araqib in the Negev Desert, we introduce the term community-specific design, present our methodology for designing and fabricating a temporary structure in collaboration with the community, and outline the logistics for a future mobile infrastructure. Beyond aiding the Bedouin’s fight for justice, our intention as designers, acutely aware of the power of technology and architecture, is to harness both physical and digital tools in an effort to create innovative systems that can be leveraged by unrecognized populations struggling for cultural survival.
keywords	Digital fabrication, temporary structur
series	journal
email
last changed	2020/11/02 13:34

_id	acadia20_574
id	acadia20_574
authors	Nguyen, John; Peters, Brady
year	2020
title	Computational Fluid Dynamics in Building Design Practice
doi	https://doi.org/10.52842/conf.acadia.2020.1.574
source	ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 574-583.
summary	This paper provides a state-of-the-art of computational fluid dynamics (CFD) in the building industry. Two methods were used to find this new knowledge: a series of interviews with leading architecture, engineering, and software professionals; and a series of tests in which CFD software was evaluated using comparable criteria. The paper reports findings in technology, workflows, projects, current unmet needs, and future directions. In buildings, airflow is fundamental for heating and cooling, as well as occupant comfort and productivity. Despite its importance, the design of airflow systems is outside the realm of much of architectural design practice; but with advances in digital tools, it is now possible for architects to integrate air flow into their building design workflows (Peters and Peters 2018). As Chen (2009) states, “In order to regulate the indoor air parameters, it is essential to have suitable tools to predict ventilation performance in buildings.” By enabling scientific data to be conveyed in a visual process that provides useful analytical information to designers (Hartog and Koutamanis 2000), computer performance simulations have opened up new territories for design “by introducing environments in which we can manipulate and observe” (Kaijima et al. 2013). Beyond comfort and productivity, in recent months it has emerged that air flow may also be a matter of life and death. With the current global pandemic of SARS-CoV-2, it is indoor environments where infections most often happen (Qian et al. 2020). To design architecture in a post-COVID-19 environment will require an in-depth understanding of how air flows through space.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	acadia20_220p
id	acadia20_220p
authors	Rieger, Uwe; Liu, Yinan
year	2020
title	LightWing II
source	ACADIA 2020: Distributed Proximities / Volume II: Projects [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95253-6]. Online and Global. 24-30 October 2020. edited by M. Yablonina, A. Marcus, S. Doyle, M. del Campo, V. Ago, B. Slocum. 220-225
summary	LightWing II is an immersive XR installation that explores hybrid design strategies equally addressing physical and digital design parameters. The interactive project links a kinetic structure with dynamic digital information in the form of 3D projected imagery and spatial sound. A key component of the project was the development of a new rendering principle that allows the accurate projection of stereoscopic images on a moving target screen. Using simple red/cyan cardboard glasses, the system expands the applications of contemporary AR headsets beyond an isolated viewing towards a communal multi-viewer event. LightWing`s construction consists of thin flexible carbon fibre rods used to tension an almost invisible mesh screen. The structure is asymmetrically balanced on a single pin joint and monitored by an IMU. A light touch sets the delicate wing-like object into a rotational oscillation. As a ‘hands-on’ experience, LightWing II creates a mysterious sensation of tactile data and enables the user to navigate through holographic narratives assembled in four scenes, including the interaction with swarms of three winged creatures, being immersed in a silky bubble, and a journey through a velvet wormhole. The user interface is dissolved through the direct linkage between the physical construction and the dynamic digital content. The project was developed at the arc/sec Lab at the University of Auckland. The Lab explores user responsive constructions where dynamic properties of the virtual world influence the material world and vice versa. The Lab’s vision is to re-connect the intangible computer world to the multisensory qualities of architecture and urban spaces. With a focus on intuitive forms of user interaction, the arc/sec Lab uses large-scale prototypes and installations as the driving method for both the development and the demonstration of new cyber-physical design principles.
series	ACADIA
type	project
email
last changed	2021/10/26 08:08

_id	ecaade2024_222
id	ecaade2024_222
authors	Bindreiter, Stefan; Sisman, Yosun; Forster, Julia
year	2024
title	Visualise Energy Saving Potentials in Settlement Development: By linking transport and energy simulation models for municipal planning
doi	https://doi.org/10.52842/conf.ecaade.2024.2.079
source	Kontovourkis, O, Phocas, MC and Wurzer, G (eds.), Data-Driven Intelligence - Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2024), Nicosia, 11-13 September 2024, Volume 2, pp. 79–88
summary	To achieve Sustainable Development Goals, in addition to the switch to sustainable energy sources and energy-efficient buildings, transport offers a major lever for reducing energy consumption and greenhouse gases. The increasing demand for emission-free mobility (e.g. through electromobility) but also heat pumps has a direct impact on the electricity consumption of buildings and settlements. It is still difficult to simulate the effects and interactions of different measures as sector coupling concepts require comprehensible tools for ex ante evaluation of planning measures at the community level and the linking of domain-specific models (energy, transport). Using the municipality of Bruck an der Leitha (Austria) as an example, a digital twin based on an open data model (Bednar et al., 2020) is created for the development of methods, which can be used to simulate measures to improve the settlement structure within the municipality. Forecast models for mobility (Schmaus, 2019; Ritz, 2019) and the building stock are developed or applied and linked via the open data model to be able to run through development scenarios and variants. The forecasting and visualisation options created in the project form the basis for the ex-ante evaluation of measures and policies on the way to a Positive-Energy-District. By identifying and collecting missing data, data gaps are filled for the simulation of precise models in the specific study area. A digital, interactive 3D model is created to examine the forecast results and the different scenarios.
keywords	visualisation, decision support, sector coupling, holistic spatial energy models for municipal planning, (energy) saving potentials in settlement development
series	eCAADe
email
last changed	2024/11/17 22:05

_id	sigradi2022_298
id	sigradi2022_298
authors	Perry, Isha N.; Xue, Zhouyi; Huang, Hui-Ling; Crispe, Nikita; Vegas, Gonzalo; Swarts, Matthew; Gomez Z., Paula
year	2022
title	Human Behavior Simulations to Determine Best Strategies for Reducing COVID-19 Risk in Schools
source	Herrera, PC, Dreifuss-Serrano, C, Gómez, P, Arris-Calderon, LF, Critical Appropriations - Proceedings of the XXVI Conference of the Iberoamerican Society of Digital Graphics (SIGraDi 2022), Universidad Peruana de Ciencias Aplicadas, Lima, 7-11 November 2022 , pp. 39–50
summary	The dynamics of COVID-19 spread have been studied from an epidemiological perspective, at city, country, and global scales (Rabajante, 2020, Ma, 2020, and Giuliani et al., 2020), although after two years of the pandemic we know that viruses spread mostly through built environments. This study is part of the Spatiotemporal Modeling of COVID-19 spread in buildings research (Gomez, Hadi, and Kemenova et al., 2020 and 2021), which proposes a multidimensional model that integrates spatial configurations, temporal use of spaces, and virus characteristics into one multidimensional model. This paper presents a specific branch of this model that analyzes the behavioral parameters, such as vaccination, masking, and mRNA booster rates, and compares them to reducing room occupancy. We focused on human behavior, specifically human interactions within six feet. We utilized the multipurpose simulation software, AnyLogic, to quantify individual exposure to the virus, in the high school building by Perkins and Will. The results show how the most effective solution, reducing the occupancy rates or redesigning layouts, being the most impractical one, is as effective as 80% of the population getting a third boost.
keywords	Spatiotemporal Modeling, Behavior Analytics, COVID-19 Spread, Agent-Based Simulation, COVID-19 Prevention
series	SIGraDi
email
last changed	2023/05/16 16:55

_id	sigradi2020_549
id	sigradi2020_549
authors	Rodríguez-Velásquez, Maribel
year	2020
title	Socio-technical interactions in the relationship between social movements and internet: a review of the state of the art and the theoretical framework
source	SIGraDi 2020 [Proceedings of the 24th Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Online Conference 18 - 20 November 2020, pp. 549-554
summary	The paper recognizes the relationship between social movements and internet how new practices of resistance through technological appropriation (Castells, 2012). This social interaction mediated by technology, understood as socio-technical interaction, establish new dynamics between human-technology-human and other heterogeneous actants (Latour, 2008), such as power and counter-power institutions that also connect to the socio-technical network. Therefore, the studies about digital interaction of the instrumental line are expanded, towards an understanding of socio-technical interactions, from the dynamics of design/use interconnected with cultural, political and economic contexts (Scolari, 2004, 2019), because the technology must satisfy social needs.
keywords	Socio-technical interaction, Social movements, Internet, Human-Computer Interaction, Socio- technical network
series	SIGraDi
email
last changed	2021/07/16 11:52

_id	acadia20_228
id	acadia20_228
authors	Alawadhi, Mohammad; Yan, Wei
year	2020
title	BIM Hyperreality
doi	https://doi.org/10.52842/conf.acadia.2020.1.228
source	ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 228-236.
summary	Deep learning is expected to offer new opportunities and a new paradigm for the field of architecture. One such opportunity is teaching neural networks to visually understand architectural elements from the built environment. However, the availability of large training datasets is one of the biggest limitations of neural networks. Also, the vast majority of training data for visual recognition tasks is annotated by humans. In order to resolve this bottleneck, we present a concept of a hybrid system—using both building information modeling (BIM) and hyperrealistic (photorealistic) rendering—to synthesize datasets for training a neural network for building object recognition in photos. For generating our training dataset, BIMrAI, we used an existing BIM model and a corresponding photorealistically rendered model of the same building. We created methods for using renderings to train a deep learning model, trained a generative adversarial network (GAN) model using these methods, and tested the output model on real-world photos. For the specific case study presented in this paper, our results show that a neural network trained with synthetic data (i.e., photorealistic renderings and BIM-based semantic labels) can be used to identify building objects from photos without using photos in the training data. Future work can enhance the presented methods using available BIM models and renderings for more generalized mapping and description of photographed built environments.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	acadia23_v1_136
id	acadia23_v1_136
authors	Alima, Natalia
year	2023
title	InterspeciesForms
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 1: Projects Catalog of the 43rd Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-8-1]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 136-143.
summary	The hybridization of architectural, biological and robotic agencies Situated in the field of architectural biodesign, InterspeciesForms explores a closer relationship between the fungus Pleurotus ostreatus and the designer in the creation of form. The intention of hybridizing mycelia’s agency of growth with architectural design intention is to generate novel, non-indexical crossbred designed outcomes that evolve preconceived notions of architectural form. Mycelium are threadlike fibrous root systems made up of hyphae, that form the vegetative part of a fungus (Jones 2020). Known as the hackers of the wood wide web (Simard 1997) mycelia form complex symbiotic relationships with other species that inhabit our earth. Michael Lim states “Fungi redefine resourcefulness, collaboration, resilience and symbiosis” (Lim 2022, p. 14). When wandering around the forest to connect with other species or searching for food, fungi form elaborate and entangled networks by spreading their hyphal tips. Shown in Figure 1, this living labyrinth results in the aesthetic formation of an intricate web. Due to the organisms ability to determine the most effective direction of growth, communicate with its surrounding ecosystem, and connect with other species, fungi are indeed an intelligent species with a unique aesthetic that must not be ignored. In drawing on these concepts, I refer to the organism’s ability to search for, tangle, and digest its surroundings as ‘mycelia agency of growth’. It is this specific behavioral characteristic that is the focus of this research, with which I, as the architect, set out to co-create and hybridize with.
series	ACADIA
type	project
email
last changed	2024/04/17 13:58

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