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	ecaade2022_16
id	ecaade2022_16
authors	Bailey, Grayson, Kammler, Olaf, Weiser, Rene, Fuchkina, Ekaterina and Schneider, Sven
year	2022
title	Performing Immersive Virtual Environment User Studies with VREVAL
doi	https://doi.org/10.52842/conf.ecaade.2022.2.437
source	Pak, B, Wurzer, G and Stouffs, R (eds.), Co-creating the Future: Inclusion in and through Design - Proceedings of the 40th Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2022) - Volume 2, Ghent, 13-16 September 2022, pp. 437–446
summary	The new construction that is projected to take place between 2020 and 2040 plays a critical role in embodied carbon emissions. The change in material selection is inversely proportional to the budget as the project progresses. Given the fact that early-stage design processes often do not include environmental performance metrics, there is an opportunity to investigate a toolset that enables early-stage design processes to integrate this type of analysis into the preferred workflow of concept designers. The value here is that early-stage environmental feedback can inform the crucial decisions that are made in the beginning, giving a greater chance for a building with better environmental performance in terms of its life cycle. This paper presents the development of a tool called LearnCarbon, as a plugin of Rhino3d, used to educate architects and engineers in the early stages about the environmental impact of their design. It facilitates two neural networks trained with the Embodied Carbon Benchmark Study by Carbon Leadership Forum, which learns the relationship between building geometry, typology, and construction type with the Global Warming potential (GWP) in tons of C02 equivalent (tCO2e). The first one, a regression model, can predict the GWP based on the massing model of a building, along with information about typology and location. The second one, a classification model, predicts the construction type given a massing model and target GWP. LearnCarbon can help improve the building life cycle impact significantly through early predictions of the structure’s material and can be used as a tool for facilitating sustainable discussions between the architect and the client.
keywords	Pre-Occupancy Evaluation, Immersive Virtual Environment, Wayfinding, User Centered Design, Architectural Study Design
series	eCAADe
email
last changed	2024/04/22 07:10

_id	ecaade2022_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	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	ecaade2022_368
id	ecaade2022_368
authors	Das, Avishek, Brunsgaard, Camilla and Madsen, Claus Brondgaard
year	2022
title	Understanding the AR-VR Based Architectural Design Workflow among Selected Danish Architecture Practices
doi	https://doi.org/10.52842/conf.ecaade.2022.1.381
source	Pak, B, Wurzer, G and Stouffs, R (eds.), Co-creating the Future: Inclusion in and through Design - Proceedings of the 40th Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2022) - Volume 1, Ghent, 13-16 September 2022, pp. 381–388
summary	Virtual reality (VR) and augmented reality (AR) have been proposed to be additional architectural design mediums for at least 25 years (Dagit, 1993). Despite rapid technical and technological development, it has not been adopted into architectural design practices as compared to academia and research. Surveys from the American Institute of Architects (AIA) and Royal Institutes of British Architects (RIBA) demonstrate the state of architectural practices; 72% of architects and 65% of architects respectively are not using any kind of virtual, augmented, or mixed reality in their practices(RIBA and Microsoft, 2018; Hampson, 2020). In this paper, the authors investigate the state of practices, issues, challenges, and opportunities of the utilization of virtual, augmented, and mixed realities in six architectural practices in the Danish context. Three of the practices are large architectural practices, one medium-sized practice specializing in institutional, healthcare and cultural architecture, and one firm designing private family houses, kindergartens, daycares and places for people with disability and, one experimental design studio. All these practices have used VR/AR in their projects to various degrees. In recent years Danish architectural practices have been involved in various VR/AR-based exhibitions, demonstrations, and tool developments to promote the usage of the same in design practice. Through a set of qualitative interviews with personnel from key architectural practices, the authors would like to demonstrate the present state of practices. The investigation explores the usage of VR and AR in Danish architecture practices by identifying challenges and opportunities regarding skill levels, architectural typology, use cases, toolchains, and workflow and shows similarities and differences between traditional and VR-based design processes. The main findings show how VR/AR-based visualization helps architects to perceive spatiality and also ushers creativity through immersion and overlays.
keywords	Virtual Reality, Augmented Reality, Architectural Design Practice, Denmark
series	eCAADe
email
last changed	2024/04/22 07:10

_id	ecaade2020_044
id	ecaade2020_044
authors	Dumlu, Burcu Nimet
year	2020
title	Virtual Reality as a Tool for Measuring Spatial Tendencies in Urban Experience
doi	https://doi.org/10.52842/conf.ecaade.2020.1.365
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. 365-374
summary	Virtual reality (VR) enables the controlled acquisition of physical reality into the virtual environment. The virtual built environment stimulates people as physical urban experiences. Room-scale experience allows wandering around the urban space. The purpose of this study is to understand VR as a tool for measuring spatial tendencies of the individual through distance structuring (proxemics) in the virtual environment. According to the concept of proxemics, individuals interact with the built environment and people through personal, social, and public distances. The study provided a virtual space that was designed as a streetscape with a road and buildings along the way both sides. Users were immersed in the VR model for 10 minutes through navigating on the chosen route and recorded in the video. The objective was understanding how the architectural elements are related to proxemics tendencies. This study describes VR as a tool for understanding user tendencies through user spatial behavior.
keywords	Virtual Reality; Virtual Space; Proxemics; HTC Vive
series	eCAADe
email
last changed	2022/06/07 07:52

_id	ecaade2020_503
id	ecaade2020_503
authors	Jansen, Igor and Pi¹tek, £ukasz
year	2020
title	The Evolutionary-algorithm-based Automation of the Initial Stage of Apartment Building Design
doi	https://doi.org/10.52842/conf.ecaade.2020.2.105
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. 105-114
summary	The development of information technologies has resulted in a strong return of interest in the concept of automating the design process. Most of the attempts such as works of Hersey and Freedman, Duarte or the PRISM application are based on shape grammars. Another approach is evolutionary simulations in concept creation augmentation such as works of Dogan, Saratsis and Reinhart or Nahara and Terzidis.This study examines to what extent evolutionary algorithms can be used to automate early stages of residential multi-family building architectural design. To facilitate informed decision-making, a tool capable of analysing a building plot and proposing the best fitting building shape was designed and tested with Polish legal regulations taken into consideration.A script generating, analysing, and evolutionally optimising a 3D model of the apartment building, was developed. All models met the basic legal conditions and were optimised by four criteria - view obstruction, insolation, maximal allowed floor area built and building compactness. The script was later used on selected building plots producing thousands of solutions. The best performing solutions were selected and presented together with their calculated parameters.
keywords	genetic algorithm; evolutionary simulation; residential building; design automation
series	eCAADe
email
last changed	2022/06/07 07:52

_id	ecaade2020_511
id	ecaade2020_511
authors	Maierhofer, Mathias, Ulber, Marie, Mahall, Mona, Serbest, Asli and Menges, Achim
year	2020
title	Designing (for) Change - Towards adaptivity-specific architectural design for situational open Environments
doi	https://doi.org/10.52842/conf.ecaade.2020.2.575
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. 575-584
summary	The introduction of cybernetic principles to the architectural discourse some 50 years ago stimulated a new notion of buildings as dynamic and under-specified systems. Although their traditional conception as static and deterministic objects has remained predominant to this day, concepts for adaptive architecture capable of interacting with their surroundings and occupants have gained renewed attention in recent decades. However, investigations so far have largely concentrated on small-scale applications or individual adaptation strategies. The notion of situational open Environments, as argued in this paper, provides a framework through which adaptivity can be conceived and explored more holistically as well as on an inhabitable scale. Environments reject deterministic design and adaptation solutions and hence call for integrative and interactive design strategies that not only allow for the exploration of particularly adaptable (i.e. underspecified) architectural morphologies, but also for the communication and negotiation during their further development beyond deployment. In respect thereof, this paper discusses the potentials and implications of computational (design) strategies, meaning the agencies of buildings, designers, residents, and surroundings. The presented research originates from the author's involvement in an interdisciplinary research project centered around the development of an adaptive high-rise building that incorporates various adaptation strategies.
keywords	Adaptive Architecture; Architectural Environment; Computational Design; Agent-based Modeling; Architecture Theory; Cybernetics
series	eCAADe
email
last changed	2022/06/07 07:59

_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

_id	caadria2020_035
id	caadria2020_035
authors	Pereira, InÃªs, BelÃ©m, Catarina and LeitÃ£o, AntÃ³nio
year	2020
title	Escaping Evolution - A Study on Multi-Objective Optimization
doi	https://doi.org/10.52842/conf.caadria.2020.1.295
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. 295-304
summary	The architectural field is currently experiencing a paradigm shift towards a more environmentally-aware design process. In this new paradigm, known as Performance-Based Design (PBD), building performance emerges as a guiding principle. Unfortunately, PBD entails several problems, for instance, building design is often associated with the simultaneous assessment of multiple performance criteria, which dramatically increases the complexity of the problem. In this vein, recent works claim that coupling optimization tools with PBD approaches allows for more efficient and optima-oriented strategies. This approach, known as Algorithmic Optimization, is based on the use of an optimization tool combined with a parametric model of a design to iteratively generate more efficient design alternatives. This paper focus on evaluating and comparing different classes of Multi-Objective Optimization (MOO) algorithms, namely, metaheuristics and model-based ones. In addition, in order to try to better understand the algorithms' suitability to different optimization problems, this research analyses two different MOO design problems.
keywords	Performance-Based Design; Algorithmic Optimization; Multi-Objective Optimization
series	CAADRIA
email
last changed	2022/06/07 08:00

_id	caadria2020_091
id	caadria2020_091
authors	Ren, Yue and Zheng, Hao
year	2020
title	The Spire of AI - Voxel-based 3D Neural Style Transfer
doi	https://doi.org/10.52842/conf.caadria.2020.2.619
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. 619-628
summary	In the architecture field, humans have mastered various skills for creating unique spatial experiences with unknown interplays between known contents and styles. Meanwhile, machine learning, as a popular tool for mapping different input factors and generating unpredictable outputs, links the similarity of the machine intelligence with the typical form-finding process. Style Transfer, therefore, is widely used in 2D visuals for mixing styles while inspiring the architecture field with new form-finding possibilities. Researchers have applied the algorithm in generating 2D renderings of buildings, limiting the results in 2D pixels rather than real full volume forms. Therefore, this paper aims to develop a voxel-based form generation methodology to extend the 3D architectural application of Style Transfer. Briefly, through cutting the original 3D model into multiple plans and apply them to the 2D style image, the stylized 2D results generated by Style Transfer are then abstracted and filtered as groups of pixel points in space. By adjusting the feature parameters with user customization and replacing pixel points with basic voxelization units, designers can easily recreate the original 3D geometries into different design styles, which proposes an intelligent way of finding new and inspiring 3D forms.
keywords	Form Finding; Machine Learning; Artificial Intelligence; Style Transfer
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	sigradi2020_412
id	sigradi2020_412
authors	Simeone, Davide; Fioravanti, Antonio; Coraglia, Ugo Maria; Cursi, Stefano
year	2020
title	A simulation model for building use re-thinking after the COVID-19 emergency
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. 412-417
summary	COVID-19 infection is forcing designers and building managers in re-thinking the use and experience of architectural spaces, as well as the interactions within the people in it. To support this difficult task, this research is working on a simulation model, based on agent-based modeling, able to predict the use phenomena of buildings and provided quantitative and qualitative feedback regarding the impact of re-defined use processes to COVID-19 infection risk. The derived platform is particularly designed to support the testing of visiting scenarios in museums and galleries, potentially helping them in their re-opening phases.
keywords	Agent-based modeling and simulation (ABMS), COVID-19, Building use, Behavioral simulation, Unity 3D
series	SIGraDi
email
last changed	2021/07/16 11:49

_id	ecaade2020_030
id	ecaade2020_030
authors	Song, Yang
year	2020
title	BloomShell - Augmented Reality for the assembly and real-time modification of complex curved structure
doi	https://doi.org/10.52842/conf.ecaade.2020.1.345
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. 345-354
summary	Augmented Reality (AR) as a new technical tool has developed rapidly in the last few years and has now the potential of bridging the gap between holographic drawings and the real world. This paper addresses whether AR can guide unskilled labour on complex structure assembly and fabrication process. It contains three experiments developed with AR. The research aims to prove that with intuitive holographic instructions, AR helps to reduce the time spent in comparing 2D drawings to the real site during the assembly process, and therefore offers possibilities to improve the construction efficiency significantly. The research also paves the way for shell structures, considering the latest technology such as AR and AI, and gives emphasis on the communication between computer and human during the fabrication process through the physical model. It is an exploration of how people might change their mind or decisions can be changed in a real-time manner harmoniously using AI through AR.
keywords	Augmented Reality; complex curved structure assembly; real-time modification; holographic instruction; HoloLens; Artificial Intelligence
series	eCAADe
email
last changed	2022/06/07 07:56

_id	ecaade2020_108
id	ecaade2020_108
authors	Steino, Nicolai
year	2020
title	Post-Conflict Reconstruction - Small scale elements of a parametric urban design approach
doi	https://doi.org/10.52842/conf.ecaade.2020.2.069
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. 69-78
summary	Taking the Syrian city of Homs as its point of departure, this paper aims to suggest some first components of a parametric urban design approach to post-conflict reconstruction focused on scenario building. From analyses of social, physical and environmental infrastructures and theoretical positions on environmentally and socially sustainable urban design in the Middle Eastern culture and climate, a framework and some initial tests for a parametric 3D urban model developed in CityEngine are presented. With the intended purpose of providing a tool capable of visualising modifiable urban design scenarios along with relevant associated data, the presented work focuses on the smallest scale of a model encompassing scales from the district level to the level of the urban block, with some relevant architectural features relating to social and environmental qualities.
keywords	parametric urban design; post-conflict reconstruction; scenario building; climate-adaptive design
series	eCAADe
email
last changed	2022/06/07 07:56

_id	ecaade2020_093
id	ecaade2020_093
authors	Veloso, Pedro and Krishnamurti, Ramesh
year	2020
title	An Academy of Spatial Agents - Generating spatial configurations with deep reinforcement learning
doi	https://doi.org/10.52842/conf.ecaade.2020.2.191
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. 191-200
summary	Agent-based models rely on decentralized decision making instantiated in the interactions between agents and the environment. In the context of generative design, agent-based models can enable decentralized geometric modelling, provide partial information about the generative process, and enable fine-grained interaction. However, the existing agent-based models originate from non-architectural problems and it is not straight-forward to adapt them for spatial design. To address this, we introduce a method to create custom spatial agents that can satisfy architectural requirements and support fine-grained interaction using multi-agent deep reinforcement learning (MADRL). We focus on a proof of concept where agents control spatial partitions and interact in an environment (represented as a grid) to satisfy custom goals (shape, area, adjacency, etc.). This approach uses double deep Q-network (DDQN) combined with a dynamic convolutional neural-network (DCNN). We report an experiment where trained agents generalize their knowledge to different settings, consistently explore good spatial configurations, and quickly recover from perturbations in the action selection.
keywords	space planning; agent-based model; interactive generative systems; artificial intelligence; multi-agent deep reinforcement learning
series	eCAADe
email
last changed	2022/06/07 07:58

_id	ecaade2020_185
id	ecaade2020_185
authors	Wurzer, Gabriel, Lorenz, Wolfgang E., Forster, Julia, Bindreiter, Stefan, Lederer, Jakob, Gassner, Andreas, Mitteregger, Mathias, Kotroczo, Erich, Pöllauer, Pia and Fellner, Johann
year	2020
title	M-DAB - Towards re-using material resources of the city
doi	https://doi.org/10.52842/conf.ecaade.2020.1.127
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. 127-132
summary	If we strive for a de-carbonized future, we need to think of buildings within a city as resources that can be re-used rather than being disposed of. Together with considerations on refurbishment options and future building materials, this gives a decision field for stakeholders which depends on the current "building stock" - the set of pre-existing buildings which are characterized e.g. by building period, location and material composition. Changes in that context are hard to argue for since (1.) some depend on statistics, other (2.) on the concrete neighborhood and thus the space in which buildings are embedded, yet again others on (3.) future extrapolations again dealing with both of the aforementioned environments. To date, there exists no tool that can handle this back-and-forth between different abstraction levels and horizons in time; nor is it possible to pursue such an endeavor without a proper framework. Which is why the authors of this paper are aiming to provide one, giving a model of change in the context of re-using material resource of the city, when faced with numerous abstraction levels (spatial or abstract; past, current or future) which have feedback loops between them. The paper focuses on a concrete case study in the city of Vienna, however, chances are high that this will apply to every other building stock throughout the world if enough data is available. As a matter of fact, this approach will ensure that argumentation can happen on multiple levels (spatial, statistical, past, now and future) but keeps its focus on making the building stock of a city a resource for sustainable development.
keywords	material reuse; sustainability; waste reduction; Design and computation of urban and local systems – XS to XL; Health and materials in architecture and cities
series	eCAADe
email
last changed	2022/06/07 07:57

_id	ecaade2020_007
id	ecaade2020_007
authors	Yu, De
year	2020
title	Reprogramming Urban Block by Machine Creativity - How to use neural networks as generative tools to design space
doi	https://doi.org/10.52842/conf.ecaade.2020.1.249
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. 249-258
summary	The democratization of design requires balancing all sorts of factors in space design. However, the traditional way to organize spatial relationships cannot deal with such complex design objectives. Can one find another form of creativity rather the human brain to design space? As Margaret Boden mentioned, "computers and creativity make interesting partners with respect to two different projects." This paper addresses whether machine creativity in the form of neural networks could be considered as a powerful generative tool to reprogram urban block in order to meet multi-users' needs. It tested this theory in a specific block model called Agri-tecture, a new architectural form combing farming with the urban built environment. Specifically, the machine empowered by Generative Adversarial Network designed spatial layouts based on learning the existing cases. Nevertheless, since the machine can hardly avoid errors, architects need to intervene and verify the machine's work. Thus, a synergy between human creativity and machine creativity is called for.
keywords	machine creativity; Generative Adversarial Network; spatial layout; creativity combination; Agri-tecture
series	eCAADe
email
last changed	2022/06/07 07:57

_id	caadria2020_015
id	caadria2020_015
authors	Zheng, Hao, An, Keyao, Wei, Jingxuan and Ren, Yue
year	2020
title	Apartment Floor Plans Generation via Generative Adversarial Networks
doi	https://doi.org/10.52842/conf.caadria.2020.2.599
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. 599-608
summary	When drawing architectural plans, designers should always define every detail, so the images can contain enough information to support design. This process usually costs much time in the early design stage when the design boundary has not been finally determined. Thus the designers spend a lot of time working forward and backward drawing sketches for different site conditions. Meanwhile, Machine Learning, as a decision-making tool, has been widely used in many fields. Generative Adversarial Network (GAN) is a model frame in machine learning, specially designed to learn and generate image data. Therefore, this research aims to apply GAN in creating architectural plan drawings, helping designers automatically generate the predicted details of apartment floor plans with given boundaries. Through the machine learning of image pairs that show the boundary and the details of plan drawings, the learning program will build a model to learn the connections between two given images, and then the evaluation program will generate architectural drawings according to the inputted boundary images. This automatic design tool can help release the heavy load of architects in the early design stage, quickly providing a preview of design solutions for architectural plans.
keywords	Machine Learning; Artificial Intelligence; Architectural Design; Interior Design
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	caadria2020_043
id	caadria2020_043
authors	Bai, Nan, Nourian, Pirouz, Xie, Anping and Pereira Roders, Ana
year	2020
title	Towards a Finer Heritage Management - Evaluating the Tourism Carrying Capacity using an Agent-Based Model
doi	https://doi.org/10.52842/conf.caadria.2020.1.305
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. 305-314
summary	As one of the most important areas in the Palace Museum, Beijing, China, the Hall of Mental Cultivation had suffered from overcrowding of visitors before it was closed in 2016 for conservation. Preparing for the reopening in 2020, the Palace Museum decided to take the chance and initiate finer-grained tourism management in the Hall. This research intends to provide an audio-guided touring program by dynamically evaluating the Tourism Carrying Capacity (TCC) with the highlight spots in the Hall, to operate the touring program spatiotemporally. Framing an optimization problem for the touring program, an agent-based simulator, Thunderhead Pathfinder, originally developed for evacuation in the emergency, is utilized to verify the performance of the touring system. The simulation shows that the proposed touring program could precisely fit all the key requirements to improve the visitors' experience, to guarantee heritage safety, and to ensure more efficient management.
keywords	Tourism Carrying Capacity; Agent-Based Simulation; Operations Research; Heritage Management
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	ascaad2021_142
id	ascaad2021_142
authors	Bakir, Ramy; Sara Alsaadani, Sherif Abdelmohsen
year	2021
title	Student Experiences of Online Design Education Post COVID-19: A Mixed Methods Study
source	Abdelmohsen, S, El-Khouly, T, Mallasi, Z and Bennadji, A (eds.), Architecture in the Age of Disruptive Technologies: Transformations and Challenges [9th ASCAAD Conference Proceedings ISBN 978-1-907349-20-1] Cairo (Egypt) [Virtual Conference] 2-4 March 2021, pp. 142-155
summary	This paper presents findings of a survey conducted to assess students’ experiences within the online instruction stage of their architectural education during the lockdown period caused by the COVID-19 pandemic between March and June 2020. The study was conducted in two departments of architecture in both Cairo branches of the Arab Academy for Science, Technology & Maritime Transport (AASTMT), Egypt, with special focus on courses involving a CAAD component. The objective of this exploratory study was to understand students’ learning experiences within the online period, and to investigate challenges facing architectural education. A mixed methods study was used, where a questionnaire-based survey was developed to gather qualitative and quantitative data based on the opinions of a sample of students from both departments. Findings focus on the qualitative component to describe students’ experiences, with quantitative data used for triangulation purposes. Results underline students’ positive learning experiences and challenges faced. Insights regarding digital tool preferences were also revealed. Findings are not only significant in understanding an important event that caused remote architectural education in Egypt but may also serve as an important stepping-stone towards the future of design education in light of newly-introduced disruptive online learning technologies made necessary in response to lockdowns worldwide
series	ASCAAD
email
last changed	2021/08/09 13:13

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