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	architectural_intelligence2022_6
id	architectural_intelligence2022_6
authors	Achim Menges, Fabian Kannenberg & Christoph Zechmeister
year	2022
title	Computational co-design of fibrous architecture
doi	https://doi.org/https://doi.org/10.1007/s44223-022-00004-x
source	Architectural Intelligence Journal
summary	Fibrous architecture constitutes an alternative approach to conventional building systems and established construction methods. It shows the potential to converge architectural concerns such as spatial expression and structural elegance, with urgently required resource effectiveness and material efficiency, in a genuinely computational approach. Fundamental characteristics of fibre composite are shared with fibre structures in the natural world, enabling the transfer of design principles and providing a vast repertoire of inspiration. Robotic fabrication based on coreless filament winding, a technique to deposit resin impregnated fibre filaments with only minimal formwork, as well as integrative computational design methods are imperative to the development of complex fibrous building systems. Two projects, the BUGA Fibre Pavilion as an example for long-span structures, and Maison Fibre as an example of multi-storey architecture, showcase the application of those techniques in an architectural context and highlight areas of further research opportunities. The highly interrelated aesthetic, structural and fabrication characteristics of fibre nets are difficult to understand and go beyond a designer’s comprehension and intuition. An AI powered, self-learning agent system aims to extend and thoroughly explore the design space of fibre structures to unlock the full design potential coreless filament winding offers. In order to ensure feedback between all relevant design and performance criteria and enable interdisciplinary convergence, these novel design methods are embedded in a larger co-design framework. It formalizes the interaction of involved interdisciplinary domains and allows for interactive collaboration based on a central data model, serving as a base for design optimisation and exploration. To further advance research on fibre composites in architecture, bio-based materials are considered, continuing the journey of discovery of fibrous architecture to fundamentally rethinking design and construction towards a novel, computational material culture in architecture.
series	Architectural Intelligence
email
last changed	2025/01/09 15:00

_id	ijac202220106
id	ijac202220106
authors	Förster, Nick; Ivan Bratoev, Jakob Fellner, Gerhard Schubert, Frank Petzold
year	2022
title	Collaborating with the crowd
source	International Journal of Architectural Computing 2022, Vol. 20 - no. 1, pp. 76–95
summary	Microscopic agent-based simulations promise the meaningful inclusion of crowd dynamics in planning processes. However, such complex urban issues depend on a multiplicity of criteria. Thus, an isolated model cannot represent the walk of pedestrians meaningfully in planning contexts. This paper reframes crowd simulation as collaborative experimentation and embeds it directly in the design process. Beyond the simulation algorithm, this perspective draws attention to user interactions, interfaces, and visualizations as crucial simulation elements. Through a prototype, we combine an agent-based pedestrian simulation with a hybrid physical–digital interface. Based on this configuration, we explore requirements of the early design stages and accordingly discuss concepts for interaction, simulation, and visualization. The prototype blends user inputs with intuitive design interactions, adapts the simulation process to qualitative and dynamic negotiations, and presents results immediately in the discussed context. Thus, it aligns crowd simulation with contingent collaborations and reveals its potential in the early design stages.
keywords	Urban design, architectural design, design decision support, pedestrian simulation, human–computer interaction, collaborative design, early design stages
series	journal
last changed	2024/04/17 14:29

_id	sigradi2022_194
id	sigradi2022_194
authors	Leitao de Souza, Thiago; Vereza, Carolina; Boner, Gabriel; Reis, Hugo; Apostolo Salvador, Lucas; Milhm, Julio
year	2022
title	Game Engines in the Historical City: the Panorama of Rio de Janeiro by Victor Meirelles and Henri Langerock
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. 663–674
summary	This essay is part of an ongoing research entitled “The 360? immersive: investigation, representation and digital immersion of Rio de Janeiro city during 19th and 20th centuries”, developed in Universidade Federal do Rio de Janeiro / Programa de Pós-Graduçao em Urbanismo, Brazil, which presents, analyses and discuss in a theoretical-conceptual approach The Panorama of Rio de Janeiro, by Victor Meirelles and Henri Langerock by the Unity Game Engine. To achieve this 360? immersion experience a methodological path was developed: restitution of the Panorama and its visualization in real time; the transition from the Lumion model to the Unity Game Engine; resizing the model scale; the immersive experience beyond the observation platform: the faux-terrain experienced; viewer movement, scenes, scripts, and navigation menus.
keywords	Panorama, Virtual Reality, City History, 360° Immersive Experience, Rio de Janeiro Panorama, Game Engines
series	SIGraDi
email
last changed	2023/05/16 16:56

_id	caadria2022_204
id	caadria2022_204
authors	Narahara, Taro
year	2022
title	Kurashiki Viewer: Qualitative Evaluations of Architectural Spaces inside Virtual Reality
doi	https://doi.org/10.52842/conf.caadria.2022.1.011
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 11-18
summary	This paper discusses how virtual reality (VR) environments can be employed as a data collection tool beyond visualization and representation tools through a simple experiment in a VR space and speculates about its potential applications. Using a VR model that runs on a web browser based on an existing historic town in Japan called Kurashiki, the experiment asked 30 recruited participants to freely walk around and leave ratings on a 5-point scale on any buildings or objects appealing to them. The proposed system in this paper can display points of interest of multiple participants using heatmaps superimposed on a map that can help users visually understand statistical preferences among them. The project's goal is to provide a quantitative means for qualitative values of architectural and urban spaces, making such data more shareable. We intended to show that such a platform could help multiple stakeholders reach better consensuses and possibly collect training datasets for machine learning models that could extract features related to the attractiveness in architecture and urban spaces.
keywords	Virtual reality, subjective evaluation, crowdsourcing, SDG 10, SDG 11.
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	ecaade2022_202
id	ecaade2022_202
authors	Acican, Oyku and Luyten, Laurens
year	2022
title	Experiential Learning of Structural Systems - Comparison of design-based and experiment-based pedagogies
doi	https://doi.org/10.52842/conf.ecaade.2022.2.535
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. 535–544
summary	This research aims to compare two experiential learning methods’ effectiveness for (1) a deeper understanding of structural behaviour, and (2) skills to design architectural forms that are structurally informed. A course was planned to investigate the effect of the type and order of the two teaching units: (1) guided experiments on a parametric design model, and (2) parametric design of a tower and custom experiments using Grasshopper and Karamba. Results indicate that the group that started with the experiments learned to ask the relevant questions by experimenting with the appropriate parameters that helped them to find the structural principles and apply them during their design phase. The group that started with the design were lost in the structural concepts and in identifying the meaningful parameters to test for. However, after the experiment was completed, this group could make a knowledge transfer. Acquisition of structures knowledge may require the experience of multiple situations while the application of this knowledge may involve selecting the relevant structural experience with the architectural form-finding process. In the future, a proposed experiential learning method will be compared with an instructive learning approach of structural systems for architecture students.
keywords	Structures Education, Experiential Learning, Parametric Structural Analysis, Comparative Pedagogy
series	eCAADe
email
last changed	2024/04/22 07:10

_id	ecaade2022_234
id	ecaade2022_234
authors	Afsar, Secil, Estévez, Alberto T., Abdallah, Yomna K., Turhan, Gozde Damla, Ozel, Berfin and Doyuran, Aslihan
year	2022
title	Activating Co-Creation Methodologies of 3D Printing with Biocomposites Developed from Local Organic Wastes
doi	https://doi.org/10.52842/conf.ecaade.2022.1.215
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. 215–224
summary	Compared to the take-make-waste-oriented linear economy model, the circular model has been studied since the 1980s. Due to consumption-oriented lifestyles along with having a tendency of considering waste materials as trash, studies on sustainable materials management (SMM) have remained at a theoretical level or created temporary and limited impacts. To ensure SMM supports The European Green Deal, there is a necessity of developing top-down and bottom-up strategies simultaneously, which can be metaphorized as digging a tunnel from two different directions to meet in the middle of a mountain. In parallel with the New European Bauhaus concept, this research aims to create a case study for boosting bottom-up and data-driven methodologies to produce short-loop products made of bio-based biocomposite materials from local food & organic wastes. The Architecture departments of two universities from different countries collaborated to practice these design democratization methodologies using data transfer paths. The 3D printable models, firmware code, and detailed explanation of working with a customized 3D printer paste extruder were shared using online tools. Accordingly, the bio-based biocomposite recipe from eggshell, xanthan gum, and citric acid, which can be provided from local shops, food & organic wastes, was investigated concurrently to enhance its printability feature for generating interior design elements such as a vase or vertical gardening unit. While sharing each step from open-source platforms with adding snapshots and videos allows further development between two universities, it also makes room for other researchers/makers/designers to replicate the process/product. By combining modern manufacturing and traditional crafting methods with materials produced with DIY techniques from local resources, and using global data transfer platforms to transfer data instead of products themselves, this research seeks to unlock the value of co-creative design practices for SMM.
keywords	Sustainable Materials Management, Co-Creation, Food Waste, 3D Printing, New European Bauhaus
series	eCAADe
email
last changed	2024/04/22 07:10

_id	caadria2022_277
id	caadria2022_277
authors	Akbar, Zuardin, Wood, Dylan, Kiesewetter, Laura, Menges, Achim and Wortmann, Thomas
year	2022
title	A Data-Driven Workflow for Modelling Self-Shaping Wood Bilayer, Utilizing Natural Material Variations with Machine Vision and Machine Learning
doi	https://doi.org/10.52842/conf.caadria.2022.1.393
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 393-402
summary	This paper develops a workflow to train machine learning (ML) models with a small dataset from physical samples to predict the curvatures of self-shaping wood bilayers based on local variations in the grain. In contrast to state-of-the-art predictive models, specifically 1.) a 2D Timoshenko model and 2.) a 3D numerical model with a rheological model, our method accounts for natural and unavoidable material variations. In this paper, we only focus on local grain variations as the main driver for curvatures in small-scale material samples. We extracted a feature matrix from grain images of active and passive layers as a Grey Level Co-Occurrence Matrix and used it as the input for our ML models. We also analysed the impact of grain variations on the feature matrix. We trained and tested several tree-based regression models with different features. The models achieved very accurate predictions for curvatures in each sample (R;0.9) and extend the range of parameters that is incalculable by a Timoshenko model. This research contributes to the material-efficient design of weather-responsive shape-changing wood structures by further leveraging the use of natural material features and explainable data-driven modelling and extends the topic in ML for material behaviour-driven design among the CAADRIA community.
keywords	data-driven model, machine learning, material programming, smart material, timber structure, SDG 12
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_33
id	caadria2022_33
authors	Alva, Pradeep, Mosteiro-Romero, Martin, Miller, Clayton and Stouffs, Rudi
year	2022
title	Digital Twin-Based Resilience Evaluation of District-Scale Archetypes
doi	https://doi.org/10.52842/conf.caadria.2022.1.525
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 525-534
summary	District-scale energy demand models can be powerful tools for understanding interactions in complex urban areas and optimising energy systems in new developments. The process of coupling characteristics of urban environments with simulation software to achieve accurate results is nascent. We developed a digital twin through a web map application for a 170ha district-scale university campus as a pilot. The impact on the built environment is simulated with pandemic (COVID-19) and climate change scenarios. The former can be observed through varying occupancy rates and average cooling loads in the buildings during the lockdown period. The digital twin dashboard was built with visualisations of the 3D campus, real-time data from sensors, energy demand simulation results from the City Energy Analyst (CEA) tool, and occupancy rates from WiFi data. The ongoing work focuses on formulating a resilience assessment metric to measure the robustness of buildings to these disruptions. This district-scale digital twin demonstration can help in facilities management and planning applications. The results show that the digital twin approach can support decarbonising initiatives for cities.
keywords	Digital twin, City Information Modelling, Planning Support System, energy demand model, SGD 11, SGD 13
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_167
id	caadria2022_167
authors	Aman, Jayedi, Matisziw, Timothy C, Kim, Jong Bum and Luo, Dan
year	2022
title	Sensing the City: Leveraging Geotagged Social Media Posts and Street View Imagery to Model Urban Streetscapes Using Deep Neural Networks
doi	https://doi.org/10.52842/conf.caadria.2022.1.595
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 595-604
summary	Understanding the relationships between individuals and the urban streetscape is an essential component of sustainable city planning. However, analysis of these relationships involves accounting for a complex mix of human behaviour, perception, as well as geospatial context. In this context, a comprehensive framework for predicting preferred streetscape characteristics utilizing deep learning and geospatial techniques is proposed. Geotagged social media posts and street view imagery are employed to account for individual sentiment and geospatial context. Natural Language Processing (NLP) and computer vision (CV) are then used to infer sentiment and model the visual environment within which individuals make posts to social media. An application of the developed framework is provided using Instagram posts and Google Street View imagery of the urban environment. A spatial analysis is conducted to assess the extent to which urban attributes correlate with the sentiment of social media postings. The results shed light on sustainable streetscape planning by focusing on the relationship between users and the built environment in a complex urban setting. Finally, limitations of the developed methodology as well as future directions are discussed.
keywords	Urban sustainability, data mining, pedestrian sentiments, transportation behavior, street level imagery, transformers, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	cdrf2022_304
id	cdrf2022_304
authors	Anni Dai
year	2022
title	Co-creation: Space Reconfiguration by Architect and Agent Simulation Based Machine Learning
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_27
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
summary	This research is a manifestation of architectural co-creation between agent simulation based machine learning and an architect’s tacit knowledge. Instead of applying machine learning brains to agents, the author reversed the idea and applied machine learning to buildings. The project used agent simulation as a database, and trained the space to reconfigure itself based on its distance to the nearest agents. To overcome the limitations of machine learning model’s simplified solutions to complicated architectural environments, the author introduced a co-creation method, where an architect uses tacit knowledge to overwatch and have real-time control over the space reconfiguration process. This research combines both the strength of machine learning’s data-processing ability and an architect’s tacit knowledge. Through exploration of emerging technologies such as machine learning and agent simulation, the author highlights limitations in design automation. By combining an architect’s tacit knowledge with a new generation design method of agent simulation based machine learning, the author hopes to explore a new way for architects to co-create with machines.
series	cdrf
email
last changed	2024/05/29 14:02

_id	caadria2022_336
id	caadria2022_336
authors	Araujo, Goncalo, Santos, Luis, Leitao, Antonioand Gomes, Ricardo
year	2022
title	AD-Based Surrogate Models for Simulation and Optimization of Large Urban Areas
doi	https://doi.org/10.52842/conf.caadria.2022.2.689
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 689-698
summary	Urban Building Energy Model (UBEM) approaches help analyze the energy performance of urban areas and predict the impact of different retrofit strategies. However, UBEM approaches require a high level of expertise and entail time-consuming simulations. These limitations hinder their successful application in designing and planning urban areas and supporting the city policy-making sector. Hence, it is necessary to investigate alternatives that are easy-to-use, automated, and fast. Surrogate models have been recently used to address UBEM limitations; however, they are case-specific and only work properly within specific parameter boundaries. We propose a new surrogate modeling approach to predict the energy performance of urban areas by integrating Algorithmic Design, UBEM, and Machine Learning. Our approach can automatically model and simulate thousands of building archetypes and create a broad surrogate model capable of quickly predicting annual energy profiles of large urban areas. We evaluated our approach by applying it to a case study located in Lisbon, Portugal, where we compare its use in model-based optimization routines against conventional UBEM approaches. Results show that our approach delivers predictions with acceptable accuracy at a much faster rate.
keywords	urban building energy modelling, algorithmic design, machine learning in Architecture, optimization of urban areas, SDG 7, SDG 12, SDG 13
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	ascaad2022_120
id	ascaad2022_120
authors	Bacinoglu, Saadet Zeynep; Cavus, Ozlem
year	2022
title	Gamifying Origami: Rule-based Improvisation for Design Exploration
source	Hybrid Spaces of the Metaverse - Architecture in the Age of the Metaverse: Opportunities and Potentials [10th ASCAAD Conference Proceedings] Debbieh (Lebanon) [Virtual Conference] 12-13 October 2022, pp. 595-608
summary	Origami, which originated as a folding paper game in Japan, has turned into a source of learning and inspiration for design and engineering studies. Complex two-dimensional patterns of origami sustain visual rules of space transformation. So, this paper proposes to gamify origami to get users more involved in the design space exploration process. For the gamification of origami, the study alters the origami patterns in a 3D modular composition with rules, scoring, and rounds in a design context. Gamifying origami becomes a tool for a learning experience for first-year architecture students in the early design phases. Accordingly, this paper presents a gaming experience model based on origami for the foundation studios. This model consists of three main stages: start, rounds, and finish. The teaching of the model is the mereological relationship providing continuity concerning improvisations with visual rules. The reward is the model complexity, such as folding numbers, and regular or modified folding. The penalty is losing scores if the continuity is not maintained. The presented experience model is performed twice in the foundation studios. The former is for understanding how much preliminary knowledge is required for the first-year students to grasp and complete the game. The second is for testing the experience. The results of the study prove the role of visual reflection-on/in action by creating pauses during the origami design and the importance of sustaining the visual inference with transformations between individuals to experience form to formation, complexity, unity, and creativity in origami design. This study would contribute to the literature on experimental methods for design pedagogy.
series	ASCAAD
email
last changed	2024/02/16 13:38

_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	sigradi2022_54
id	sigradi2022_54
authors	Balci, Ozan; Alaçam, Sema
year	2022
title	Zone-sensitive RIZOBots in Action: Examining the Behavior of Mobile Robots In a Heterogeneous Environment
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. 397–408
summary	This study proposes a framework for the use of mobile robots namely RIZOBots in form studies in the early phases of design. The proposed framework was tested in two experiments. An agent-based model was utilized for the movement of mobile robots, a drawing task was defined as the task. In particular, rule sets for agent-agent and agent-environment interaction were used. Light-sensitivity rules were utilized to achieve agent-environment interaction, apart from obstacle detection. This study focuses on the effects of two different zone-related states on the behavior of RIZOBot which is a configurable differential-drive wheeled robot developed by authors using off-the-shelf products and 3D printed body parts. Two zone types with very basic features are used to define environmental conditions. The traces left on the canvas, the irregularities in the movement of the robots, and the robot-environment interaction will be evaluated in the study. The results and analysis of the two selected experiments are presented and the potential of the proposed framework is discussed.
keywords	Robotics, Swarm robotics, Swarm behaviour, Mobile agents, Zone-sensitivity
series	SIGraDi
email
last changed	2023/05/16 16:56

_id	ecaade2022_292
id	ecaade2022_292
authors	Baudoux, Gaelle, Calixte, Xaviera and Leclercq, Pierre
year	2022
title	Transition between Architectural Ideation and BIM - Towards a new method through semantic building modeling
doi	https://doi.org/10.52842/conf.ecaade.2022.2.357
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. 357–366
summary	Faced with the challenges of the actors' coordination regarding the increasing building complexity, the new digital collective approaches of advanced design raise the problem of the transition between collaborative ideation (first creative moments of deployment of ideas) and the following phases of digital production (including the formalisation of building specifications in BIM models). In response, we aim to develop a digitally instrumented method for moving from conventional architectural graphic documents to the 3D digital models characteristic of BIM. We propose here a detailed formalisation of the ideation-BIM transition problem and a method for managing building information to improve this transition.
keywords	Building Information Modeling, Architectural Ideation, Digital Representation, Media Architecture, Semantic Model
series	eCAADe
email
last changed	2024/04/22 07:10

_id	sigradi2022_104
id	sigradi2022_104
authors	Bielski, Jessica; Eisenstadt, Viktor; Langenhan, Christoph; Petzold, Frank
year	2022
title	Lost in architectural designing - Possible cognitive biases of architects during the early design phases
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. 557–568
summary	In order to meet the housing demands of the future, architects need to work faster and more efficiently while improving architectural quality. The metis projects aim to create an intelligent design assistant supporting architects during the early design stages through suggesting further design steps for spatial layouting, based on the best practice of reference buildings. By enhancing suggestions with explainability, the system offers insight to improve Human-System-Interaction (HSI), bridging the ‘black box’ problem. The explanations aim to either support the reasoning process or mitigate possible biases of architects, which can be rooted in the heuristic ‘System 1’, as well as the analytical ‘System 2’, drawing from the ‘dual process model’. Within this paper, we propose our approach to clarify the four main heuristic biases and the logical errors of architects, when using reference buildings, and their respective representation during the architectural design decision-making process.
keywords	Decision Making, Biases, Explainability, XAI, Human System Interaction
series	SIGraDi
email
last changed	2023/05/16 16:56

_id	ijac202220204
id	ijac202220204
authors	BuHamdan, Samer; Aladdin Alwisy; Thomas Danel; Ahmed Bouferguene; Zoubeir Lafhaj
year	2022
title	The use of reinforced learning to support multidisciplinary design in the AEC industry: Assessing the utilization of Markov Decision Process
source	International Journal of Architectural Computing 2022, Vol. 20 - no. 2, pp. 216–237
summary	While the design practice in the architecture, engineering, and construction (AEC) industry continues to be acreative activity, approaching the design problem from a perspective of the decision-making science hasremarkable potentials that manifest in the delivery of high-performing sustainable structures. These possiblegains can be attributed to the myriad of decision-making tools and technologies that can be implemented toassist design efforts, such as artificial intelligence (AI) that combines computational power and data wisdom.Such combination comes to extreme importance amid the mounting pressure on the AEC industry players todeliver economic, environmentally friendly, and socially considerate structures. Despite the promisingpotentials, the utilization of AI, particularly reinforced learning (RL), to support multidisciplinary designendeavours in the AEC industry is still in its infancy. Thus, the present research discusses developing andapplying a Markov Decision Process (MDP) model, an RL application, to assist the preliminary multidisciplinary design efforts in the AEC industry. The experimental work shows that MDP models can expediteidentifying viable design alternatives within the solutions space in multidisciplinary design while maximizingthe likelihood of finding the optimal design
keywords	Design evaluation, multidisciplinary design, reinforced learning, Markov Decision Process, social impact,architecture, engineering, and construction industry
series	journal
last changed	2024/04/17 14:29

_id	caadria2022_68
id	caadria2022_68
authors	Carta, Silvio, Turchi, Tommaso and Pintacuda, Luigi
year	2022
title	Measuring Resilient Communities: an Analytical and Predictive Tool
doi	https://doi.org/10.52842/conf.caadria.2022.1.615
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 615-624
summary	This work presents the initial results of an analytical tool designed to quantitatively assess the level of resilience of urban areas. We use Deep Neural Networks to extract features of resilience from a trained model that classifies urban areas using a pre-assigned value range of resilience. The model returns the resilience value for any urban area, indicating the distance between the centre of the selected area and relevant typologies, including green areas, buildings, natural elements and infrastructures. Our tool also indicates the urban morphological characteristics that have a larger impact on the resilience score. In this way we can learn why a neighbourhood is successful (or not) and how to improve its level of resilience. The model employs Convolutional Neural Networks (CNNs) with Keras on Tensorflow for the computation. The outputs are loaded onto a Node.JS environment and bootstrapped with React.js to generate the online demo.
keywords	sustainable cities and communities, resilient communities, CNN, urban morphology, SDG 11, SDG 13
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	ijac202220212
id	ijac202220212
authors	Castriotto, Caio; Felipe Tavares; Gabriela Celani; Olga Popovic Larsen; Xan Browne
year	2022
title	Clamp links: A novel type of reciprocal frame connection
source	International Journal of Architectural Computing 2022, Vol. 20 - no. 2, pp. 378–399
summary	Reciprocal frames (RFs) are complex structural systems based on mutual support between elements. One of the main challenges for these structures is achieving geometrical complexity with ease for assembly. This paper describes the development of a new type of connection for RF that uses a single bolt to fix a whole fan. The method used was the Research Through Design, using algorithmic modelling and virtual and physical prototyping. After the exploration of different alternatives, the connection selected was structurally evaluated with a 3D solid finite element analysis (FEM) software and a 2D bar parametric model. Finally, a fullscale pavilion was built as a proof-of-concept. A total of 47 connections were fabricated using four 3D-printed templates combined with a hand router. The construction allowed us to draw conclusions on the connection design and the assembly method, and the process as a whole can contribute to the development of new structural links and production methods.
keywords	Reciprocal frames, connections, computational design, simulations, digital fabrication
series	journal
last changed	2024/04/17 14:29

_id	sigradi2022_210
id	sigradi2022_210
authors	Cavalcante, Teane; Cardoso, Daniel; Alexandrino, Joao Victor; Fiuza, Rebeca; de Sousa, Eugenio
year	2022
title	City information modeling (CIM) applied to urban planning: the urban indicator of reachness
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. 297–308
summary	This work is part of an extension and investigation project dedicated to studying solutions related to urban, social and economic innovation with the purpose of developing a Health Innovation District (HID). Purposing to define the HID’s intervention area, a group of urban indicators was developed and categorized in four layers: reachness, integrability, use diversity and social validation. This article will explain the first layer: reachness. To achieve this, it aims to appropriate a generic framework that incorporates 1) a Relational Database Management System (PostgreSQL), 2) a Geographic Information System (QGIS) and 3) a CAD software associated to an algorithmic modelator (Rhinoceros3D + Grasshopper3D), associated to computer solutions to assess if the shortest way possible between the residential lots and the points of interest has an adequate distance.
keywords	City Information Model, Urban Planning, Urban Indicators, Parametric Analysis
series	SIGraDi
email
last changed	2023/05/16 16:55

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