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	artificial_intellicence2019_147
id	artificial_intellicence2019_147
authors	Ding Wen Bao, Xin Yan, Roland Snooks, and Yi Min Xie
year	2020
title	Bioinspired Generative Architectural Design Form-Finding and Advanced Robotic Fabrication Based on Structural Performance
doi	https://doi.org/https://doi.org/10.1007/978-981-15-6568-7_10
source	Architectural Intelligence Selected Papers from the 1st International Conference on Computational Design and Robotic Fabrication (CDRF 2024)
summary	Due to the potential to generate forms with high efficiency and elegant geometry, topology optimization is widely used in architectural and structural designs. This paper presents a working flow of form-finding and robotic fabrication based BESO (Bi-directional Evolutionary Structure Optimization) optimization method. In case there are some other functional requirements or condition limitations, some useful modifications are also implemented in the process. With this kind of working flow, it is convenient to foreknow or control the structural optimization direction before the optimization process. Furthermore, some fabrication details of the optimized model will be discussed because there are also many notable technical points between computational optimization and robotic fabrication.
series	Architectural Intelligence
email
last changed	2022/09/29 07:28

_id	ecaade2020_138
id	ecaade2020_138
authors	Patel, Sayjel Vijay, Tchakerian, Raffi, Lemos Morais, Renata, Zhang, Jie and Cropper, Simon
year	2020
title	The Emoting City - Designing feeling and artificial empathy in mediated environments
doi	https://doi.org/10.52842/conf.ecaade.2020.2.261
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 261-270
summary	This paper presents a theoretical blueprint for implementing artificial empathy into the built environment. Transdisciplinary design principles have oriented the creation of a new model for autonomous environments integrating psychology, architecture, digital media, affective computing and interactive UX design. 'The Emoting City', an interactive installation presented at the 2019 Shenzhen Bi-City Biennale of Urbanism/Architecture, is presented as a first step to explore how to engage AI-driven sensing by integrating human perception, cognition and behaviour in a real-world scenario. The approach described encompasses two main elements: embedded cyberception and responsive surfaces. Its human-AI interface enables new modes of blended interaction that are conducive to self-empathy and insight. It brings forth a new proposition for the development of sensing systems that go beyond social robotics into the field of artificial empathy. The installation innovates in the design of seamless affective computing that combines 'alloplastic' and 'autoplastic' architectures. We believe that our research signals the emergence of a potential revolution in responsive environments, offering a glimpse into the possibility of designing intelligent spaces with the ability to sense, inform and respond to human emotional states in ways that promote personal, cultural and social evolution.
keywords	Artificial Intelligence; Responsive Architecture; Affective Computation; Human-AI Interfaces; Artificial Empathy
series	eCAADe
email
last changed	2022/06/07 07:59

_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	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	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	acadia20_198p
id	acadia20_198p
authors	Birkeland, Jennifer; Scelsa, Jonathan A.
year	2020
title	Live L’oeil – Through the Looking Ceiling
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. 198-201
summary	Following the proliferation of linear perspective during the Renaissance, the hegemony of the vantage point was often problematically used to signify the patron’s dominance. During the mannerist era, we witnessed the creation of elaborate rooms, painted in architectural linear perspective establishing the illusionary space of faraway lands - a measure of optic imperialism wherein the conquests of the west played out in the domestic decoration of the elite later provided to the public as a societal spectacle in the form of the panorama. Within these architectural illusions, or Quadratura as they were named in Italy, lies the most notable and justifiable critique of design by vantage point, the question ‘which vantage point is privileged?’ History not surprisingly reveals that the typical vantage point was most problematically centered at one and three-quarter meters above the ground – coincident with five centimeters below the average height of a human European male. The design of architectural form through view or spatial image has arguably perpetuated this act of optic bias. This project addresses this problematic practice of design by vantage point by utilizing motion sensors to liberate the virtual space of a canonic example of quadrature from its confines within a singular vantage point. The authors digitally modeled the projective space of Andrea Pozzo’s vision for the Church of Sant’Ignazio di Loyola in Rome, scaled and fit to a gallery space outfitted with a canvas to inform a ceiling plane. Anamorphic images of the virtual heavenly space, as seen through the canvas ceiling picture plane, were created from the digital model and encoded to the individual moments in the room. Individuals who moved through the gallery were followed by the illusion of the heavenly space, creating a live l’oeil distortion.
series	ACADIA
type	project
email
last changed	2021/10/26 08:08

_id	acadia20_584
id	acadia20_584
authors	Brás, Catarina; Castelo-Branco, Renata; Menezes Leitao, António
year	2020
title	Parametric Model Manipulation in Virtual Reality
doi	https://doi.org/10.52842/conf.acadia.2020.1.584
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. 584-593.
summary	Algorithmic design (AD) uses algorithms to describe architectural designs, producing results that are visual by nature and greatly benefit from immersive visualization. Having this in mind, several approaches have been developed that allow architects to access and change their AD programs in virtual reality (VR). However, programming in VR introduces a new level of complexity that hinders creative exploration. Solutions based in visual programming offer limited parameter manipulation and do not scale well, particularly when used in a remote collaboration environment, while those based in textual programming struggle to find adequate interaction mechanisms to efficiently modify existing programs in VR. This research proposes to ease the programming task for architects who wish to develop and experiment with collaborative textual-based AD in VR, by bringing together the user-friendly features of visual programming and the flexibility and scalability of textual programming. We introduce an interface for the most common parametric changes that automatically generates the corresponding code in the AD program, and a hybrid programming solution that allows participants in an immersive collaborative design experience to combine textual programming with this new visual alternative for the parametric manipulation of the design. The proposed workflow aims to foster remote collaborative work in architecture studios, offering professionals of different backgrounds the opportunity to parametrically interact with textual-based AD projects while immersed in them.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	caadria2020_446
id	caadria2020_446
authors	Cho, Dahngyu, Kim, Jinsung, Shin, Eunseo, Choi, Jungsik and Lee, Jin-Kook
year	2020
title	Recognizing Architectural Objects in Floor-plan Drawings Using Deep-learning Style-transfer Algorithms
doi	https://doi.org/10.52842/conf.caadria.2020.2.717
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. 717-725
summary	This paper describes an approach of recognizing floor plans by assorting essential objects of the plan using deep-learning based style transfer algorithms. Previously, the recognition of floor plans in the design and remodeling phase was labor-intensive, requiring expert-dependent and manual interpretation. For a computer to take in the imaged architectural plan information, the symbols in the plan must be understood. However, the computer has difficulty in extracting information directly from the preexisting plans due to the different conditions of the plans. The goal is to change the preexisting plans to an integrated format to improve the readability by transferring their style into a comprehensible way using Conditional Generative Adversarial Networks (cGAN). About 100-floor plans were used for the dataset which was previously constructed by the Ministry of Land, Infrastructure, and Transport of Korea. The proposed approach has such two steps: (1) to define the important objects contained in the floor plan which needs to be extracted and (2) to use the defined objects as training input data for the cGAN style transfer model. In this paper, wall, door, and window objects were selected as the target for extraction. The preexisting floor plans would be segmented into each part, altered into a consistent format which would then contribute to automatically extracting information for further utilization.
keywords	Architectural objects; floor plan recognition; deep-learning; style-transfer
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	caadria2020_316
id	caadria2020_316
authors	Czynska, Klara
year	2020
title	Computational Methods for Examining Reciprocal Relations between the Viewshed of Planned Facilities and Historical Dominants - Their integration within the cultural landscape
doi	https://doi.org/10.52842/conf.caadria.2020.1.853
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. 853-862
summary	The article presents a methodology for the assessment of the impact of new buildings on the cultural landscape, in particular the exposure of historical landmarks. While using digital analysis and a 3D city model, the methodology examines reciprocal visual relations between historical and planned buildings. The following methods have been used: a) Visual Impact Size (VIS) which enables to determine a visual impact area and the degree of architectural facility domination in space; b) comparative analysis (cumulative viewshed) which enables to determine areas where viewsheds of new investment and historical buildings overlap; c) simulation of selected views from the level of human eyesight. The proposed landscape examination methodology has been presented using the case study of Katowice, Poland. The goal was to determine reciprocal relations between historical landmarks of the Silesia Museum and tall buildings planned in the vicinity. The study used a Digital Surface Model (DSM), a 3D city model. All simulations have been performed using software developed by the author (C++).
keywords	cumulative viewshed; digital cityscape analysis; historical dominants; visual impact; VIS method
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	ecaade2020_037
id	ecaade2020_037
authors	Dortheimer, Jonathan, Neuman, Eran and Milo, Tova
year	2020
title	A Novel Crowdsourcing-based Approach for Collaborative Architectural Design
doi	https://doi.org/10.52842/conf.ecaade.2020.2.155
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 155-164
summary	This paper provides an overview of "Architasker", a large-scale crowdsourcing approach, platform, and method that enables a collaborative professional architectural design process in collaboration with a community of stakeholders. The platform includes communicating complex architectural project requirements; solution space exploration using different micro-tasks like sketching, 2D and 3D CAD; design selection; and design review as an evolutionary process. The architectural crowdsourcing model underlying the platform is contextualized in the state-of-the-art research on creative crowdsourcing methods and is supported by relevant evidence from empirical experiments. Experimental results validate the effectiveness of the method to generate architectural artifacts by harnessing the skills, talents, and experience of architects and the opinions and values of the stakeholders.
keywords	Crowdsourcing; Participatory Design; Human Computation; Creative Crowdsourcing; Co-Design; Collective Intelligence
series	eCAADe
email
last changed	2022/06/07 07:55

_id	caadria2020_272
id	caadria2020_272
authors	Erhan, Halil, Abuzuraiq, Ahmed M., Zarei, Maryam, AlSalman, Osama, Woodbury, Robert and Dill, John
year	2020
title	What do Design Data say About Your Model? - A Case Study on Reliability and Validity
doi	https://doi.org/10.52842/conf.caadria.2020.1.557
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. 557-567
summary	Parametric modeling systems are widely used in architectural design. Their use for designing complex built environments raises important practical challenges when composed by multiple people with diverse interests and using mostly unverified computational modules. Through a case study, we investigate possible concerns identifiable from a real-world collaborative design setting and how such concerns can be revealed through interactive data visualizations of parametric models. We then present our approach for resolving these concerns using a design analytic workflow for examine their reliability and validity. We summarize the lessons learnt from the case study, such as the importance of an abundance of test cases, reproducible design instances, accessing and interacting with data during all phases of design, and seeking high cohesion and decoupling between design geometry and evaluation components. We suggest a systematic integration of design modeling and analytics for enhancing a reliable design decision-making.
keywords	Model Reliability; Model Validity; Parametric Modeling; Design Analytics; Design Visualization
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	acadia20_594
id	acadia20_594
authors	Farahbakhsh, Mehdi; Kalantar, Negar; Rybkowski, Zofia
year	2020
title	Impact of Robotic 3D Printing Process Parameters on Bond Strength
doi	https://doi.org/10.52842/conf.acadia.2020.1.594
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. 594-603.
summary	Additive manufacturing (AM), also known as 3D printing, offers advantages over traditional construction technologies, increasing material efficiency, fabrication precision, and speed. However, many AM projects in academia and industrial institutions do not comply with building codes. Consequently, they are not considered safe structures for public utilization and have languished as exhibition prototypes. While three discrete scales—micro, mezzo, and macro—are investigated for AM with paste in this paper, structural integrity has been tackled on the mezzo scale to investigate the impact of process parameters on the bond strength between layers in an AM process. Real-world material deposition in a robotic-assisted AM process is subject to environmental factors such as temperature, humidity, the load of upper layers, the pressure of the nozzle on printed layers, etc. Those factors add a secondary geometric characteristic to the printed objects that was missing in the initial digital model. This paper introduces a heuristic workflow for investigating the impacts of three selective process parameters on the bond strength between layers of paste in the robotic-assisted AM of large-scale structures. The workflow includes a method for adding the secondary geometrical characteristic to the initial 3D model by employing X-ray computerized tomography (CT) scanning, digital image processing, and 3D reconstruction. Ultimately, the proposed workflow offers a pattern library that can be used by an architect or artificial intelligence (AI) algorithms in automated AM processes to create robust architectural forms.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	caadria2020_342
id	caadria2020_342
authors	Han, Yoojin and Lee, Hyunsoo
year	2020
title	A Deep Learning Approach for Brand Store Image and Positioning - Auto-generation of Brand Positioning Maps Using Image Classification
doi	https://doi.org/10.52842/conf.caadria.2020.2.689
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. 689-696
summary	This paper presents a deep learning approach to measuring brand store image and generating positioning maps. The rise of signature brand stores can be explained in terms of brand identity. Store design and architecture have been highlighted as effective communicators of brand identity and position but, in terms of spatial environment, have been studied solely using qualitative approaches. This study adopted a deep learning-based image classification model as an alternative methodology for measuring brand image and positioning, which are conventionally considered highly subjective. The results demonstrate that a consistent, coherent, and strong brand identity can be trained and recognized using deep learning technology. A brand positioning map can also be created based on predicted scores derived by deep learning. This paper also suggests wider uses for this approach to branding and architectural design.
keywords	Deep Learning; Image Classification; Brand Identity; Brand Positioning Map; Brand Store Design
series	CAADRIA
email
last changed	2022/06/07 07:50

_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	ijac202018103
id	ijac202018103
authors	Kimm, Geoff
year	2020
title	Actual and experiential shadow origin tagging: A 2.5D algorithm for efficient precinct-scale modelling
source	International Journal of Architectural Computing vol. 18 - no. 1, 41-52
summary	This article describes a novel algorithm for built environment 2.5D digital model shadow generation that allows identities of shadowing sources to be efficiently precalculated. For any point on the ground, all sources of shadowing can be identified and are classified as actual or experiential obstructions to sunlight. The article justifies a 2.5D raster approach in the context of modelling of architectural and urban environments that has in recent times shifted from 2D to 3D, and describes in detail the algorithm which builds on precedents for 2.5D raster calculation of shadows. The algorithm is efficient and is applicable at even precinct scale in low-end computing environments. The simplicity of this new technique, and its independence of GPU coding, facilitates its easy use in research, prototyping and civic engagement contexts. Two research software applications are presented with technical details to demonstrate the algorithm’s use for participatory built environment simulation and generative modelling applications. The algorithm and its shadow origin tagging can be applied to many digital workflows in architectural and urban design, including those using big data, artificial intelligence or community participative processes.
keywords	2.5D raster, actual and experiential shadow origins, generative techniques, participatory built environment simulation, reactive scripting for design
series	journal
email
last changed	2020/11/02 13:34

_id	sigradi2020_384
id	sigradi2020_384
authors	Martínez Otalora, Jose David; Bolshakova, Marina; Rojas Celis, Anyela Piedad; Almonacid Lara, Fabián Humberto
year	2020
title	MELNIKOV HOUSE A BIOCLIMATIC ANALYSIS
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. 384-391
summary	The aim of this article is to recognize the methods of environmental control used by the master of the "constructivist" movement Konstantin Melnikov in a Melnikov's house, a creation whose architectural value has been highlighted on several occasions, it also seeks to demonstrate through modern climate software simulation and analysis tools that in the early 20th century Melnikov consciously used environmental control methods, which makes the afore-mentioned construction a historical example of bioclimatic architecture meant for Russian climate. In order to assess this topic a digital model has been built and different energy simulations were carried out using software such as Climate Consultant, Design Builder and ArchiCAD.
keywords	Melnikov house, Energy efficiency, Temperature comfort, B. Giovani‘s strategy
series	SIGraDi
email
last changed	2021/07/16 11:49

_id	cdrf2019_290
id	cdrf2019_290
authors	Mary Spyropoulos and Alisa Andrasek
year	2020
title	Material Disruption
doi	https://doi.org/https://doi.org/10.1007/978-981-33-4400-6_27
source	Proceedings of the 2020 DigitalFUTURES The 2nd International Conference on Computational Design and Robotic Fabrication (CDRF 2020)
summary	This paper examines the role of computational simulation of material processes with robotics fabrication, with the intent of examining its implications for architectural design and construction. Simulation techniques have been adopted in the automotive industry amongst others, advancing their design and manufacturing outputs. At present, architecture is yet to explore the full potential of this technology and their techniques. The need for simulation is evident in exploring the behaviours of materials and their relative properties. Currently, there is a distinct disconnect between the virtual model and its fabricated counterpart. Through research in simulation, we can begin to understand and clearly visualize the relationship between material behaviours and properties that can lead to a closer correlation between the digital design and its fabricated outcome. As the first phase of investigation, the material of clay is used due to its volatile qualities embedded within the material behaviour. The input geometry is constrained to rudimentary extruded forms in order to not obscure the behaviour of the material, but rather allow for it to drive the machine-making process.
series	cdrf
email
last changed	2022/09/29 07:51

_id	caadria2020_081
id	caadria2020_081
authors	Mclennan, Sam, Schnabel, Marc Aurel, Moleta, Tane and Brown, Andre
year	2020
title	Extracting and Communicating Underlying Pseudo-Formalised Procedural Rules in Heritage Architecture - The Case of New Zealand's 19th Century Timber Churches
doi	https://doi.org/10.52842/conf.caadria.2020.2.163
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. 163-172
summary	The research employs procedural modelling to investigate the characteristic rules present within a loosely defined architectural style. The 19th-century timber neo-Gothic churches built in the city of Wellington, New Zealand are examples of a particular interpretation of the Gothic Revival style. Although they all share common aspects, no prescribed rules are regulating how these churches were designed. This research explores a methodology for creating a procedural 'Timber Gothic Church Generator' that is generated from an understanding and interpretation of the design of the buildings examined. Once developed the procedural generator can be used to extrapolate, and produce other church designs as well as create hybrid designs. These outputs can be further refined through the creation of parametric rules. A key result of this methodology is to explicate better otherwise ambiguous design philosophies that are shared between the similar buildings. It shows how a design can be reverse-engineered and converted into procedural logic. The research establishes the process and logic to enable the creation of further rules to be explored.
keywords	Digital Forensics; Digital Heritage; Gothic Architecture; Houdini; Procedural Modelling
series	CAADRIA
email
last changed	2022/06/07 07:58

_id	ecaade2020_334
id	ecaade2020_334
authors	Ntzoufras, Sotirios, Oungrinis, Konstantinos-Alketas, Liapi, Marianthi and Papamanolis, Antonios
year	2020
title	Robotic Swarms in Architectural Design - A communication platform bridging design analysis and robotic construction
doi	https://doi.org/10.52842/conf.ecaade.2020.2.453
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 453-462
summary	The research work fueling this paper examines ?ptimal approaches for bridging design analysis and robotic spatial construction. In this context, the paper presents the development of a unified platform for managing a swarm of robotic fabrication agents. The goal is the development of a streamlined methodology that guides the conversion of a design model into construction data code that can be assigned to the robotic swarm for fabrication.The work focuses on bridging architectural design platforms and distributed automation processes, on the one hand, and on the other, it targets the development of a functional management tool for adjusting and optimizing fabrication. A crucial parameter considered is the monitoring and assessment of all stages of the proposed process. This involves a constant exchange of information between the various actors, such as the swarm agents, the construction data and the designer - user. As a result, the construction process is treated as a constant reassessment and re-adjustment of the design parameters rather than the linear result of the original set of construction data. Therefore, the proposed system cannot be described as reactive, but acts responsively in a ``sensible'' manner.
keywords	Swarm Robotics; Adaptive Fabrication; Robotic Construction Communication Platform; Sensible System
series	eCAADe
email
last changed	2022/06/07 08:00

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

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