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	ijac202321201
id	ijac202321201
authors	Steinfeld, Kyle
year	2023
title	Clever little tricks: A socio-technical history of text-to-image generative models
source	International Journal of Architectural Computing 2023, Vol. 21 - no. 2, 211–241
summary	The emergence of text-to-image generative models (e.g., Midjourney, DALL-E 2, Stable Diffusion) in the summer of 2022 impacted architectural visual culture suddenly, severely, and seemingly out of nowhere. To contextualize this phenomenon, this text offers a socio-technical history of text-to-image generative systems. Three moments in time, or “scenes,” are presented here: the first at the advent of AI in the middle of the last century; the second at the “reawakening” of a specific approach to machine learning at the turn of this century; the third that documents a rapid sequence of innovations, dubbed “clever little tricks,” that occurred across just 18 months. This final scene is the crux, and represents the first formal documentation of the recent history of a specific set of informal innovations. These innovations were produced by non-affiliated researchers and communities of creative contributors, and directly led to the technologies that so compellingly captured the architectural imagination in the summer of 2022. Across these scenes, we examine the technologies, application domains, infrastructures, social contexts, and practices that drive technical research and shape creative practice in this space.
keywords	Machine learning, text-to-image, socio-technical study, generative AI
series	journal
last changed	2024/04/17 14:30

_id	ecaade2022_172
id	ecaade2022_172
authors	Vugreshek, Zvonko
year	2022
title	Discrete Differences between Aggregate Systems for Generative Urban and Architectural Design
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. 29–38
doi	https://doi.org/10.52842/conf.ecaade.2022.2.029
summary	The activation of aggregate systems, procedural generation, and other models of discrete computation result in different organizations and formal outcomes. Some differences seem blurry but are relevant to understand in order to govern the computational design process in the specific domain. They are developing around empiric principles, are based on discrete automation rule sets, and are intertwined in various ways. The paper presents and describes some differences and communalities between each system. Its goal is to support the computational designer, architect or urban planner in the decision-making process and choice of which system could work best in a given context and to solve a specific problem. An introduction into aggregation or automation will serve as a foundation for the research. The discrete systems Cellular Automata, Wave Function Collapse, Graph-Grammar Aggregation will be described. In this paper, the latter is specified as selection-based-aggregation. Diffusion-Limited Aggregation (DLA), which is regarded as an early translation of natural behaviour into scripted nature will serve as a framework. In a next step potential and utilization of these discrete systems in expanding the language of architectural and urban morphology will be experimentally demonstrated and compared. The paper concludes by suggesting a current state of development and potential adaptation of the methods for broader use within the architectural and urban design paradigm of developing methods for the creation of new computational typologies.
keywords	Discrete Aggregation, Cellular Automata, Procedural Generation, Urban Morphology Generation, Wave Function Collapse
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
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
doi	https://doi.org/10.52842/conf.caadria.2022.1.393
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_507
id	caadria2022_507
authors	Bolojan, Daniel, Vermisso, Emmanouil and Yousif, Shermeen
year	2022
title	Is Language All We Need? A Query Into Architectural Semantics Using a Multimodal Generative Workflow
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. 353-362
doi	https://doi.org/10.52842/conf.caadria.2022.1.353
summary	This project examines how interconnected artificial intelligence (AI)-assisted workflows can address the limitations of current language-based models and streamline machine-vision related tasks for architectural design. A precise relationship between text and visual feature representation is problematic and can lead to "ambiguity‚ in the interpretation of the morphological/tectonic complexity of a building. Textual representation of a design concept only addresses spatial complexity in a reductionist way, since the outcome of the design process is co-dependent on multiple interrelated systems, according to systems theory (Alexander 1968). We propose herewith a process of feature disentanglement (using low level features, i.e., composition) within an interconnected generative adversarial networks (GANs) workflow. The insertion of natural language models within the proposed workflow can help mitigate the semantic distance between different domains and guide the encoding of semantic information throughout a domain transfer process.
keywords	Neural Language Models, GAN, Domain Transfer, Design Agency, Semantic Encoding, SDG 9
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	ascaad2022_065
id	ascaad2022_065
authors	David, Joao; Leitao, Antonio
year	2022
title	Getting a Handle on Floor Plan Analysis: Door Classification in Floor Plans and a Survey on Existing Datasets
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. 221-236
summary	Floor plan interpretation and reconstruction is crucial to enable the transformation of drawings to 3D models or different digital formats. It has recently taken advantage of neural-based architectures, especially in the semantic segmentation field. These techniques perform better than traditional methods, but the results depend mainly on the data used to train the networks, which is often crafted for the specific task being performed, making it hard to reuse for different purposes. In this paper, we conduct a literature survey on the existing datasets for floor plan analysis, and we explore how information regarding door placement and orientation can be recovered without having to change the initial data or model. We propose a two-step recognition method based on image segmentation followed by classification of cropped zones to allow data augmentation during training. In the process, we generate a dataset consisting of 35000 annotated door images extracted from an existing dataset.
series	ASCAAD
email
last changed	2024/02/16 13:29

_id	ijac202220216
id	ijac202220216
authors	Keyvanfar, Ali; Arezou Shafaghat; Muhamad SF Rosley
year	2022
title	Performance comparison analysis of 3D reconstruction modeling software in construction site visualization and mapping
source	International Journal of Architectural Computing 2022, Vol. 20 - no. 2, pp. 453–475
summary	Unmanned aerial vehicle (UAV) technology has overcome the limitations of conventional construction management methods using advanced and automated visualization and 3D reconstruction modeling techniques. Although the mapping techniques and reconstruction modeling software can generate real-time and high-resolution descriptive textural, physical, and spatial data, they may fail to develop an accurate and complete 3D model of the construction site. To generate a quality 3D reconstruction model, the construction manager must optimize the trade-offs among three major software-selection factors: functionalities, technical capabilities, and the system hardware specifications. These factors directly affect the robust 3D reconstruction model of the construction site and objects. Accordingly, the purpose of this research was to apply nine well-established 3D reconstruction modeling software tools (DroneDeploy, COLMAP, 3DF+Zephyr, Autodesk Recap, LiMapper, PhotoModeler, 3D Survey, AgiSoft Photoscan, and Pix4D Mapper) and compare their performances and reliabilities in generating complete 3D models. The research was conducted in an eco-home building at the University of Technology, Malaysia. A series of regression analyses were conducted to compare the performances of the selected 3D reconstruction modeling software in alignment and registration, distance computing, geometric measurement, and plugin execution. Regression analysis determined that among the software programs, LiMapper had the strongest positive linear correlation with the ground truth model. Furthermore, the correlation analysis showed a statistically significant p-value for all software, except for 3D Survey. In addition, the research found that Autodesk Recap generated the most-robust and highest-quality dense point clouds. DroneDeploy can create an accurate point cloud and triangulation without using many points as required by COLMAP and LiMapper. It was concluded that most of the software is robustly, positively, and linearly correlated with the corresponding ground truth model. In the future, other factors involving software selection should be studied, such as vendor-related, user-related, and automation factors.
keywords	Construction site visualization, unmanned aerial vehicle, photogrammetry, 3D reconstruction modeling, multi-view-stereopsis, structure-from-motion, ANOVA and regression analysis
series	journal
last changed	2024/04/17 14:29

_id	ascaad2022_121
id	ascaad2022_121
authors	Mohsen, Hiba; Tohme, Mohamad; Nashi, Rawan
year	2022
title	From Passive to Immersive: Metaverse as a Pedagogical Approach in History Class: Presenting a Constant Reminder of Historical Remnants and a Customizable Reality for Future Preferences; Beirut as a Case Study
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. 202-219
summary	It is widely acknowledged that passive, non-immersive strategies of teaching adopted in history classes in Lebanon do not offer the right platform for knowledge retention in students. With that said, virtual reality and the use of Metaverse as a pedagogical approach is prophesied as the most apt to invoke a positive attitude from children towards the topic being studied, and thus, in this case, it increases their awareness of the existing built heritage they live amidst. This research sets out from a recent project implemented by Beirut Arab University, together with three UN agencies. The latter aimed for “developing children emotional attachment to the territory of Beirut Blast through activating their participation in the construction of cognitive maps by playing with spatial maps strategically designed in a game environment”. A thorough assessment of the outcomes of the activities implemented throughout the project, including the executed physical models and game boards that simulate myriad neighborhoods in Beirut, is carried out, followed by an analytical comparison of these outcomes with those from using the proposed innovative digital tools. A pilot study is conducted on Martyr’s square to assess how virtual tools can enhance the sensory experience and perception of the built space, making youth active learners rather than passive. It illustrates how introducing children to educating architecture from a young age not only nurtures their awareness of their local neighborhoods, but also generates responsible citizens. The outcome of this study can be divided over a timeline of past, present, and future. The virtual recreation of old Beirut aims to enhance the virtual learning experience as opposed to that from books and chalkboards. Children are expected to formulate a better understanding of their heritage, become more attached to the remnants of the latter, and set out to customize the reality to their preferences or vision of how a better, sustainable Beirut looks like.
series	ASCAAD
email
last changed	2024/02/16 13:38

_id	sigradi2022_53
id	sigradi2022_53
authors	Stuart-Smith, Robert; Danahy, Patrick
year	2022
title	3D Generative Design for Non-Experts: Multiview Perceptual Similarity with Agent-Based Reinforcement Learning
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. 115–126
summary	Advances in additive manufacturing allow architectural elements to be fabricated with increasingly complex geometrical designs, however, corresponding 3D design software requires substantial knowledge and skill to operate, limiting adoption by non-experts or people with disabilities. Established non-expert approaches typically constrain geometry, topology, or character to a pre-established configuration, rather than aligning to figural and aesthetic characteristics defined by a user. A methodology is proposed that enables a user to develop multi-manifold designs from sketches or images in several 3d camera projections. An agent-based design approach responds to computer vision analysis (CVA) and Deep Reinforcement Learning (RL) to design outcomes with perceptual similarity to user input images evaluated by Structural Similarity Indexing (SSIM). Several CVA and RL ratios were explored in training models and tested on untrained images to evaluate their effectiveness. Results demonstrate a combination of CVA and RL motion behavior can produce meshes with perceptual similarity to image content.
keywords	Generative Design, Machine Learning, Agent-Based Systems, Non-Expert Design
series	SIGraDi
email
last changed	2023/05/16 16:55

_id	ecaade2022_105
id	ecaade2022_105
authors	Trento, Armando, Fioravanti, Antonio, Kieferle, Joachim and Woessner, Uwe
year	2022
title	Bridging Cultural Heritage Ontologies in VR Environment - A framework for querying and reasoning on the Temple of Venus and Rome restoration and documentation
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. 177–186
doi	https://doi.org/10.52842/conf.ecaade.2022.2.177
summary	VR applied to Architectural and Archaeological Heritage has a long history: Digital models in this field are evolving from an aesthetic simulation of reality, or, rather, a representation of the visual perception, to a more complex model: an information aggregation core. The investigation presents a research panel oriented to enhance the digital survey products - point clouds, meshes, 3D models -to be used as an intelligent visual archive assigning structured knowledge contents to artefacts’ geometry. The implemented case regards the Temple of Venus and Rome. Research, in progress, has been developed by the following steps: 1) Subdividing the artefact geometry into sub- regions; 2) Developing the consolidation ontology for a few restoration classes; 3) Assigning (manually) to each artefact subcomponent, namely a mesh sub-region, a “smart label” including a link to its consolidation ontology instance. The aim is to combine the potential of VR visualization with ontology reasoning systems.
keywords	VR, Archaeological Heritage, Knowledge-based Design Systems, Restoration Ontologies
series	eCAADe
email
last changed	2024/04/22 07:10

_id	cdrf2022_223
id	cdrf2022_223
authors	Zhiyi Dou, Waishan Qiu, Wenjing Li, Dan Luo
year	2022
title	Evaluation Process of Urban Spatial Quality and Utility Trade-Off for Post-COVID Working Preferences
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_19
summary	The formation of cities, and the relocation of workers to densely populated areas reflect a spatial equilibrium, in which the higher real consumption levels of urban areas are offset by lower non-monetary amenities [1]. However, as the society progress toward a post-COVID stage, the prevailing decentralized delivery systems and location-based services, the growing trend of working from home, with citizens’ shifting preference of de-appreciating densities and gathering, have not only changed the possible spatial distribution of opportunities, resources, consumption and amenities, but also transformed people’s preference regarding desirable urban spatial qualities, value of amenities, and working opportunities [2, 3]. This research presents a systematic method to evaluate the perceived trade-off between urban spatial qualities and urban utilities such as amenities, transportation, and monetary opportunities by urban residence in the post-COVID society. The outcome of the research will become a valid tool to drive and evaluate urban design strategies based on the potential self-organization of work-life patterns and social profiles in the designated neighbourhood. To evaluate the subjective perception of the urban residence, the study started with a comparative survey by asking residence to compare two randomly selected urban contexts in a data base of 398 contexts sampled across Hong Kong and state their living preference under the presumption of following scenarios: 1. working from home; 2. working in city centre offices. Core information influencing the spatial equilibrium are provided in the comparable urban context such as street views, housing price, housing space, travel time to city centre, adjacency to public transport and amenities, etc. Each context is given a preference score calculated with Microsoft TrueSkill Bayesian ranking algorithm [4] based on the comparison survey of two scenarios. The 398 contexts are further analysed via GIS and image processing, to be deconstructed into numerical values describing main features for each of the context that influence urban design strategies such as composition of spatial features, amenity allocation, adjacency to city centre and public transportations. Machine learning models are trained with the numerical values of urban features as input and two preference scores for the two working scenarios as the output. The correlation heat maps are used to identify main urban features and its p-value that influence residence’s preference under two working scenarios in post–COVID era. The same model could also be applied to inform the direction of urban design strategies to construct a sustainable community for each type of working population and validate the design strategies via predicting its competitiveness in attracting residence and developing target industries.
series	cdrf
email
last changed	2024/05/29 14:02

_id	sigradi2022_41
id	sigradi2022_41
authors	Ballestero, Maximiliano Esteban; Ramírez, Lucila Inés; Tosello, María Elena; Jereb, Marcelo Fabián
year	2022
title	BitaLab. Data visualization interface and guidance in technological skills for designers in Visual Communication.
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. 595–606
summary	The objective of the project is to facilitate the perception of the distance between the technological skills built during the academic journey of the students in Visual Communication Design, and the skills demanded by the labor market. For this research, the Vision in Product (ViP) methodology was used, transferring the results to a possible 2027 scenario. We defined seven professional technological profiles which will help students in their professional insertion, and their adaption to the fast changes in the labor area. Our collaborative and interactive interface was designed to display the data obtained in the survey and the design profiles that will be most in demand in the future. The differential value of our research lies in the possibility of showing the obtained results in a collaborative interface.
keywords	Data Visualization, User Experience, Interface Design, Graphic Design, Future Strategic Design
series	SIGraDi
email
last changed	2023/05/16 16:56

_id	caadria2022_267
id	caadria2022_267
authors	Toohey, Gabrielle, Nguyen, Tommy Bao Nghi, Vilppola, Ritva, Qiu, Waishan, Li, Wenjing and Luo, Dan
year	2022
title	Data-Driven Evaluation of Streets to Plan for Bicycle Friendly Environments: A Case Study of Brisbane Suburbs
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. 243-252
doi	https://doi.org/10.52842/conf.caadria.2022.1.243
summary	Empirical cycling data from across the world illustrates the many barriers that car-dependent cities face when implementing cycling programs and infrastructure. Most studies focus on physical criteria, while perception criteria are less addressed. The correlations between the two are still largely unknown. This paper introduces a methodology that utilises computer vision analysis techniques to evaluate 15,383 Google Street View Images (SVI) of Brisbane City against both physical and perception cycling criteria. The study seeks to better understand correlations between the quality of a street environment and an urban area's 'bicycle-friendliness'. PSPNet Image Segmentation is utilised against SVIs to determine the percentage of an image corresponding with objects and the environment related to specific cycling factors. For physical criteria, these images are then further analysed by Masked RCNN processes. For perception criteria, subjective ranking of the images is undertaken using Machine Learning (ML) techniques to score images based on survey data. The methodology effectively allows for current findings in cycling research to be further utilised in combination via computer visioning (CV) and ML applications to measure different physical elements and urban design qualities that correspond with bicycle-friendliness. Such findings can assist targeted design strategies for cities to encourage the use of safer and more sustainable modes of transport.
keywords	Bicycle-friendly, Quality Streetscapes, Active Living, Visual Assessment, Computer Visioning, Machine Learning, SDG 3, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	ecaade2022_125
id	ecaade2022_125
authors	Chen, Emily, Lu, Glenn, Barnik, Lyric and Correa, David
year	2022
title	Fast and Reversible Bistable Hygroscopic Actuators for Architectural Applications Based on Plant Movement Strategies
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. 261–270
doi	https://doi.org/10.52842/conf.ecaade.2022.1.261
summary	Plant movement is of great inspiration for the development of actuators in architectural applications. Since plants lack muscles, they have developed unique hygroscopic mechanisms that use specialized tissue to generate movement in response to stimuli such as touch, light, temperature, or gravity. Most research in architecture has been focused on the stress-induced bending that can be achieved with a bilayer structure – particularly using wood composites and bi-metals. The speed of these mechanisms is mostly limited by the rules of bilayers, as described by Timoshenko, and the speed of moisture/heat diffusion. This paper presents methods to use bistable mechanisms, and their elastic instability, to enable rapid movements of “snap-through” buckling that can greatly improve the speed of transformation. The research covers biomimetic studies on the Mimosa pudica, Oxalis triangularis, and the Maranta leuconeura to develop hygroscopic mechanisms whose kinematic actuation can be amplified through the integration of a bi- stable system. The presented mechanisms make it possible to significantly increase the speed of response of the hygroscopically driven mechanism while maintaining the ability to operate over several reversible cycles. Calibration of the mechanism to specific relative humidity conditions is presented together with some initial prototypes with the potential for manual override strategies. It is the aim of this combined approach that the actuation mechanisms are better able to match users’ expectations of fast shape-change actuation in relation to environmental changes.
keywords	Stimulus-Responsive, Biomimetics, Hygroscopic, Elastic Instability, Actuators
series	eCAADe
email
last changed	2024/04/22 07:10

_id	acadia22pr_178
id	acadia22pr_178
authors	Newell, Catie; Belanger, Zackery; McGee, Wes
year	2022
title	Long Range: Shaping Glass for Acoustic and Optic Performance
source	ACADIA 2022: Hybrids and Haecceities [Projects Catalog of the 42nd Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-7-4]. University of Pennsylvania Stuart Weitzman School of Design. 27-29 October 2022. edited by M. Akbarzadeh, D. Aviv, H. Jamelle, and R. Stuart-Smith. 178-183.
summary	Long Range is a surface shaped to expose the intrinsic acoustic properties of glass, exhibited as gradients of acoustic behavior. Moving from flat panels at one end to deeply slumped and perforated components at the other, the glass reveals its acoustic properties, ranging from reflection, diffusion, absorption, and transmission. The intention is to merge optical and acoustical performance intrinsically into a surface, and offer an alternative to acoustic treatment by calibrating material geometry and sound.
series	ACADIA
type	project
email
last changed	2024/02/06 14:06

_id	acadia22_546
id	acadia22_546
authors	Nguyen, John; Cop, Philipp; Hoban, Nicholas; Peters, Brady; Kesik, Ted
year	2022
title	Resonant Hexagon Diffuser
source	ACADIA 2022: Hybrids and Haecceities [Proceedings of the 42nd Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-8-1]. University of Pennsylvania Stuart Weitzman School of Design. 27-29 October 2022. edited by M. Akbarzadeh, D. Aviv, H. Jamelle, and R. Stuart-Smith. 546-557.
summary	The surge in mass timber buildings being constructed introduces unique acoustical challenges as mass timber is more permissible for sound to travel across floors, ceilings, and walls, especially for lower frequencies. In order to address these acoustical challenges, the absorption qualities of Helmholtz resonators and surface diffusion of scattering surfaces are leveraged by combining the two systems in an integrated structure using the tectonics of mass timber construction. This paper investigates the potential of Helmholtz resonators to be used in combination with sound scattering surfaces to achieve optimal performance in cross laminated timber (CLT) panels through the use of a hexagonal pattern as the underlying design strategy.
series	ACADIA
type	paper
email
last changed	2024/02/06 14:04

_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
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
doi	https://doi.org/10.52842/conf.ecaade.2022.1.215
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	acadia22_000
id	acadia22_000
authors	Akbarzadeh, Masoud; Aviv, Dorit; Jamelle, Hina; Stuart-Smith, Robert
year	2022
title	ACADIA 2022: Hybrids and Haecceities [Proceedings]
source	ACADIA 2022: Hybrids and Haecceities [Proceedings of the 42nd Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-8-1]. University of Pennsylvania Stuart Weitzman School of Design. 27-29 October 2022. edited by M. Akbarzadeh, D. Aviv, H. Jamelle, and R. Stuart-Smith. 839p.
summary	Hybrids & Haecceities seeks novel approaches to design and research that dissolve binary conditions and inherent hierarchies in order to embrace new modes of practice. Haecceities describe the qualities or properties of objects that define them as unique. Concurrently, Hybrids are entities with characteristics enhanced by the process of combining two or more elements with different properties. In concert, these terms offer a provocation toward more inclusive and specific forms of computational design. Hybrids & Haecceities aligns with a fundamental shift away from abstract generalized models of production toward greater degrees of customization at unprecedented scales, made possible by the Fourth Industrial Revolution. With greater reliance on cyber-physical systems, this shift supports more diverse and considered forms of embodiment and participation in the built environment. Conversely, the design and construction industries have profound global effects with significant political, economic, and environmental impacts. The urgent need to decarbonize buildings, and at the same time, provide equitable infrastructure to communities at risk, places responsibility on the design disciplines to form new collaborations in the effort to address today’s social and ecological crises.
series	ACADIA
type	proceedings
email
last changed	2024/02/06 14:00

_id	acadia22_001
id	acadia22_001
authors	Akbarzadeh, Masoud; Aviv, Dorit; Jamelle, Hina; Stuart-Smith, Robert
year	2022
title	ACADIA 2022: Hybrids and Haecceities [Projects Catalog]
source	ACADIA 2022: Hybrids and Haecceities [Projects Catalog of the 42nd Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-7-4]. University of Pennsylvania Stuart Weitzman School of Design. 27-29 October 2022. edited by M. Akbarzadeh, D. Aviv, H. Jamelle, and R. Stuart-Smith. 240p.
summary	Hybrids & Haecceities seeks novel approaches to design and research that dissolve binary conditions and inherent hierarchies in order to embrace new modes of practice. Haecceities describe the qualities or properties of objects that define them as unique. Concurrently, Hybrids are entities with characteristics enhanced by the process of combining two or more elements with different properties. In concert, these terms offer a provocation toward more inclusive and specific forms of computational design. Hybrids & Haecceities aligns with a fundamental shift away from abstract generalized models of production toward greater degrees of customization at unprecedented scales, made possible by the Fourth Industrial Revolution. With greater reliance on cyber-physical systems, this shift supports more diverse and considered forms of embodiment and participation in the built environment. Conversely, the design and construction industries have profound global effects with significant political, economic, and environmental impacts. The urgent need to decarbonize buildings, and at the same time, provide equitable infrastructure to communities at risk, places responsibility on the design disciplines to form new collaborations in the effort to address today’s social and ecological crises.
series	ACADIA
type	projects catalog
email
last changed	2024/02/06 14:00

_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
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
doi	https://doi.org/10.52842/conf.caadria.2022.1.525
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_47
id	caadria2022_47
authors	An, Yudi
year	2022
title	Impact of Covid-19 on Associations between Land Use and Bike-Sharing Usage
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. 605-614
doi	https://doi.org/10.52842/conf.caadria.2022.1.605
summary	Bike-sharing as a human-centred, zero-emission, sustainable, alternative, and easily accessible transport mode has been implemented globally and consistently contributing to communities and the environment by alleviating consumption of natural sources, traffic congestion, and air pollution, which is considered a solution for future cities. The appearance of Covid-19 significantly impacts public transportation modes, including the bike-sharing system. The intention of this study was to investigate the spatiotemporal impact of the Covid-19 pandemic on associations between urban factors and bike-sharing usage in Los Angeles, United States, by analysing a sizeable actual trip dataset and employing geographically weighted regression (GWR) models. GWR was conducted for examining the varying spatial association between bike infrastructure, public transport, and urban land use factors, and bike-sharing trip volume. The results indicated that bike-sharing usage significantly decreased during the pandemic and essential service as restaurant was found consistently and positively associated with bike-sharing use. GWR provided clear spatial patterns of bike usage based on urban land use and big user databases. The outcomes of this study could inspire policymakers and shared mobility operators to support these safe, sustainable transport alters (such as rebalancing bike stations), help city resilience, and shape a sustainable future of mobility in the post-Covid-19 era.
keywords	Bike-Sharing, Covid-19, Land Use, Geographically Weighted Regression, Big Data, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

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