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	caadria2021_391
id	caadria2021_391
authors	Elshani, Diellza, Koenig, Reinhard, Duering, Serjoscha, Schneider, Sven and Chronis, Angelos
year	2021
title	Measuring Sustainability and Urban Data Operationalization - An integrated computational framework to evaluate and interpret the performance of the urban form.
doi	https://doi.org/10.52842/conf.caadria.2021.2.407
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 2, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 407-416
summary	With rapid urbanization, the necessity for sustainable development has skyrocketed, and sustainable urban development is a must. Recent advances in computing performance of urban layouts in real-time allow for new paradigms of performance-driven design. As beneficial as utilizing multiple layers of urban data may be, it can also create a challenge in interpreting and operationalizing data. This paper presents an integrated computational framework to measure sustainability, operationalize and interpret the urban forms performance data using generative design methods, novel performance simulations, and machine learning predictions. The performance data is clustered into three pillars of sustainability: social, environmental, and economical, and it is followed with the performance space exploration, which assists in extracting knowledge and actionable rules of thumb. A significant advantage of the framework is that it can be used as a discussion table in participatory planning processes since it could be easily adapted to interactive environments.
keywords	generative design; data interpretation ; urban sustainability; performance simulation; machine learning
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	ecaade2021_178
id	ecaade2021_178
authors	Nicholas, Paul, Chiujdea, Ruxandra Stefania, Sonne, Konrad and Scaffidi, Antonio
year	2021
title	Design and Fabrication Methodologies for Repurposing End of Life Metal via Robotic Incremental Sheet Metal Forming
doi	https://doi.org/10.52842/conf.ecaade.2021.2.171
source	Stojakovic, V and Tepavcevic, B (eds.), Towards a new, configurable architecture - Proceedings of the 39th eCAADe Conference - Volume 2, University of Novi Sad, Novi Sad, Serbia, 8-10 September 2021, pp. 171-180
summary	This paper investigates an integrative approach to robotic incremental sheet metal forming (RISF), which connects the registration of variable material properties and geometries to the re-forming of pre-made components beyond their initial formulations. Re-using rather than recycling metals can save the significant energy costs that come with having to melt, purify and re-manufacture products, as well as saving the costs of the new object it replaces. In this paper, we describe a workflow that connects 3d scanning, design automation and fabrication. The method goes beyond state of the art for RISF by challenging the assumption of starting from a flat unused sheet of metal, opening up the potential of RISF for material reuse. Our approach is demonstrated through the fabrication of a series of bench seating elements from oil drum geometries, however is generalisable to other input materials and output geometries. 3d scanning is used to register varying geometric features such as rolled beads, irregularities such as dents and holes, and material properties such as corrosion.
keywords	robotic fabrication; re-use; upcycling; incremental sheet metal forming
series	eCAADe
email
last changed	2022/06/07 07:58

_id	acadia23_v3_71
id	acadia23_v3_71
authors	Vassigh, Shahin; Bogosian, Biayna
year	2023
title	Envisioning an Open Knowledge Network (OKN) for AEC Roboticists
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 3: Proceedings of the 43rd Annual Conference for the Association for Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9891764-1-0]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 24-32.
summary	The construction industry faces numerous challenges related to productivity, sustainability, and meeting global demands (Hatoum and Nassereddine 2020; Carra et al. 2018; Barbosa, Woetzel, and Mischke 2017; Bock 2015; Linner 2013). In response, the automation of design and construction has emerged as a promising solution. In the past three decades, researchers and innovators in the Architecture, Engineering, and Construction (AEC) fields have made significant strides in automating various aspects of building construction, utilizing computational design and robotic fabrication processes (Dubor et al. 2019). However, synthesizing innovation in automation encounters several obstacles. First, there is a lack of an established venue for information sharing, making it difficult to build upon the knowledge of peers. First, the absence of a well-established platform for information sharing hinders the ability to effectively capitalize on the knowledge of peers. Consequently, much of the research remains isolated, impeding the rapid dissemination of knowledge within the field (Mahbub 2015). Second, the absence of a standardized and unified process for automating design and construction leads to the individual development of standards, workflows, and terminologies. This lack of standardization presents a significant obstacle to research and learning within the field. Lastly, insufficient training materials hinder the acquisition of skills necessary to effectively utilize automation. Traditional in-person robotics training is resource-intensive, expensive, and designed for specific platforms (Peterson et al. 2021; Thomas 2013).
series	ACADIA
type	field note
email
last changed	2024/04/17 13:59

_id	ecaade2022_249
id	ecaade2022_249
authors	Carrasco Hortal, Jose, Hernandez Carretero, Sergi, Abellan Alarcon, Antonio and Bermejo Pascual, Jorge
year	2022
title	Algae, Gobiidae Fish and Insects that inspire Coastal Custodian Entities - Digital models for a real-virtual space using TouchDesigner
doi	https://doi.org/10.52842/conf.ecaade.2022.1.361
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. 361–370
summary	At the beginning of the twenty-first century, a discipline at the intersection of digital art and science explores how natural and artificial species are affected, coexist, and feed back to humans based on multi-scalar hybrid models. They embody types of surveillance entities or non-human custodians, and serve as inspiration for another generation of designs produced ten years later, the case studies that are presented here. This paper explains the design and parametric fundamentals of a digital architecture installation at the University of Alicante (Spain 2021) using CNC models and the TouchDesigner programming environment. The installation contains a clan of technological-virtual hybrid species, non-human custodians, which: (a) strengthen the Proposal’s discourse on the recognition of legal identity of the Mar Menor lagoon (Southeast Spain); (b) incorporate reactive designs; (c) help raise awareness of the effect of human actions on the lagoon’s ecology and nearby streams. The viewpoint is not anthropocentric, because it adopts the perspective of the foraging fish species or the oxygen-seeking algae species, among others, in order to reveal the deterioration processes. In most cases, the result is a sort of synaesthetic conversation that interweaves light, sound, movement and data.
keywords	Human-Machine Interaction, TouchDesigner, Non-Human Custodian, Responsive Interface, Ethnography of Things
series	eCAADe
email
last changed	2024/04/22 07:10

_id	caadria2021_220
id	caadria2021_220
authors	MacDonald, Katie and Schumann, Kyle
year	2021
title	Twinned Assemblage - Curating and Distilling Digital Doppelgangers
doi	https://doi.org/10.52842/conf.caadria.2021.1.693
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 1, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 693-702
summary	Recent developments in digital fabrication have made increasingly intelligent use of machine visioning and 3D scanning. These technologies enable ever-higher resolution digital models of physical material, and present opportunities for physical material to gain agency in the design process. Digital design workflows using such technologies require ever-greater computing power as the resolution of digitized models increases, and high-fidelity 3D scanning systems become cost-prohibitive, creating obstacles to widespread use. Twinned assemblage uses consumer-grade photogrammetry software, lowering the cost of equipment required, and presents a series of distillation methods that strategically reduce the fidelity of data digitally describing a physical object. Distillation methods discussed include reducing a mesh to a low-poly geometry, identifying the location and orientation of an object's largest faces, and creating 2D sections, among others. These methods can be designed intentionally to extract or highlight certain qualities in digital models, that in turn inform aggregation strategies generated through computational simulation. This paper presents several examples of such aggregations in a variety of materials, conveying benefits and challenges of the process. Such methods present opportunities for granting agency to physical materials in the design process, and for the democratized use of digitizing technologies.
keywords	Authorship; Digitizing; Material Agency; Digital Design; Democratized Technology
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	caadria2021_218
id	caadria2021_218
authors	Saslawsky, Kevin, Sanford, Tyler, MacDonald, Katie and Schumann, Kyle
year	2021
title	Branching Inventory - Democratized Fabrication of Available Stock
doi	https://doi.org/10.52842/conf.caadria.2021.1.513
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 1, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 513-522
summary	Branching inventory is a construction methodology demonstrated through a full-scale structural prototype that reduces the waste inherent in milling lumber and celebrates natural variation by making complex form the efficient result of irregular material. The processing of wood into standardized components embeds waste and intensive energy consumption into timber construction. This work reimagines the utility of raw materials, using computational feedback to place natural form in dialogue with design intent -- creating a dialogue between technology, material, and designer. A custom workflow synthesizes a network of branches into a specific, structural form, shaped by the thicknesses and curvatures of the stock material as well as design input. Building on work using machine visioning in fabricating non-standard timber by others -- most of which relies on elaborate and cost-prohibitive 3D scanning and robotic fabrication systems -- branching inventory demonstrates a low-fidelity, democratized version of such approaches, using standard wood and metal-working tools and in which the available material stock contributes to design possibilities.
keywords	Digital Design; Digital Fabrication; 3D Scanning; Material Agency; Democratized Technology
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	ecaade2023_259
id	ecaade2023_259
authors	Sonne-Frederiksen, Povl Filip, Larsen, Niels Martin and Buthke, Jan
year	2023
title	Point Cloud Segmentation for Building Reuse - Construction of digital twins in early phase building reuse projects
doi	https://doi.org/10.52842/conf.ecaade.2023.2.327
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 327–336
summary	Point cloud processing has come a long way in the past years. Advances in computer vision (CV) and machine learning (ML) have enabled its automated recognition and processing. However, few of those developments have made it through to the Architecture, Engineering and Construction (AEC) industry. Here, optimizing those workflows can reduce time spent on early-phase projects, which otherwise could be spent on developing innovative design solutions. Simplifying the processing of building point cloud scans makes it more accessible and therefore, usable for design, planning and decision-making. Furthermore, automated processing can also ensure that point clouds are processed consistently and accurately, reducing the potential for human error. This work is part of a larger effort to optimize early-phase design processes to promote the reuse of vacant buildings. It focuses on technical solutions to automate the reconstruction of point clouds into a digital twin as a simplified solid 3D element model. In this paper, various ML approaches, among others KPConv Thomas et al. (2019), ShapeConv Cao et al. (2021) and Mask-RCNN He et al. (2017), are compared in their ability to apply semantic as well as instance segmentation to point clouds. Further it relies on the S3DIS Armeni et al. (2017), NYU v2 Silberman et al. (2012) and Matterport Ramakrishnan et al. (2021) data sets for training. Here, the authors aim to establish a workflow that reduces the effort for users to process their point clouds and obtain object-based models. The findings of this research show that although pure point cloud-based ML models enable a greater degree of flexibility, they incur a high computational cost. We found, that using RGB-D images for classifications and segmentation simplifies the complexity of the ML model but leads to additional requirements for the data set. These can be mitigated in the initial process of capturing the building or by extracting the depth data from the point cloud.
keywords	Point Clouds, Machine Learning, Segmentation, Reuse, Digital Twins
series	eCAADe
email
last changed	2023/12/10 10:49

_id	ijac202119106
id	ijac202119106
authors	Del Campo, Matias; Alexandra Carlson, and Sandra Manninger
year	2021
title	Towards Hallucinating Machines - Designing with Computational Vision
source	International Journal of Architectural Computing 2021, Vol. 19 - no. 1, 88–103
summary	There are particular similarities in how machines learn about the nature of their environment, and how humans learn to process visual stimuli. Machine Learning (ML), more specifically Deep Neural network algorithms rely on expansive image databases and various training methods (supervised, unsupervised) to “make sense” out of the content of an image. Take for example how students of architecture learn to differentiate various architectural styles. Whether this be to differentiate between Gothic, Baroque or Modern Architecture, students are exposed to hundreds, or even thousands of images of the respective styles, while being trained by faculty to be able to differentiate between those styles. A reversal of the process, striving to produce imagery, instead of reading it and understanding its content, allows machine vision techniques to be utilized as a design methodology that profoundly interrogates aspects of agency and authorship in the presence of Artificial Intelligence in architecture design. This notion forms part of a larger conversation on the nature of human ingenuity operating within a posthuman design ecology. The inherent ability of Neural Networks to process large databases opens up the opportunity to sift through the enormous repositories of imagery generated by the architecture discipline through the ages in order to find novel and bespoke solutions to architectural problems. This article strives to demystify the romantic idea of individual artistic design choices in architecture by providing a glimpse under the hood of the inner workings of Neural Network processes, and thus the extent of their ability to inform architectural design.The approach takes cues from the language and methods employed by experts in Deep Learning such as Hallucinations, Dreaming, Style Transfer and Vision. The presented approach is the base for an in-depth exploration of its meaning as a cultural technique within the discipline. Culture in the extent of this article pertains to ideas such as the differentiation between symbolic and material cultures, in which symbols are defined as the common denominator of a specific group of people.1 The understanding and exchange of symbolic values is inherently connected to language and code, which ultimately form the ingrained texture of any form of coded environment, including the coded structure of Neural Networks.A first proof of concept project was devised by the authors in the form of the Robot Garden. What makes the Robot Garden a distinctively novel project is the motion from a purely two dimensional approach to designing with the aid of Neural Networks, to the exploration of 2D to 3D Neural Style Transfer methods in the design process.
keywords	Artificial intelligence, design agency, neural networks, machine learning, machine vision
series	journal
email
last changed	2021/06/03 23:29

_id	caadria2021_118
id	caadria2021_118
authors	Huang, Chien-hua
year	2021
title	Reinforcement Learning for Architectural Design-Build - Opportunity of Machine Learning in a Material-informed Circular Design Strategy
doi	https://doi.org/10.52842/conf.caadria.2021.1.171
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 1, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 171-180
summary	This paper discusses the potentials of reinforcement learning in game engine for design, implementation, and construction of architecture. It inaugurates a new design tool that promotes a material-informed design-build workflow for architectural design and construction industries that achieves a comprehensive circular economy. As a proof of concept, it uses the project Reform Standard, a machine-learning-based searching system that designs new shell structures composed of existing wasted materials, as a demonstration to discuss how reinforcement learning, machine vision and automated searching algorithm in the game engine can promote a material-aware design and converts wastes into construction materials. The demonstrator project sorts and transforms irregular chunks of wasted broken plastics into a new form. Instead of recycling those wastes in an energy-intensive process, the game engine is capable of finding the intricacy and new machine-oriented aesthetics in those otherwise neglected wastes. Furthermore, future research directions such as robotic-aided construction are discussed by exposing the potentials and problems in the demonstrated project. Finally, the future circular strategy is discussed beyond the demonstrated tests and local uses. The standardization of material, legislation and material lifecycle needs to be comprehensively considered and designed by architects and designers during conceptual design phase.
keywords	Reinforcement Learning; ML-Agents; Unity3D; circular design; geometric analysis
series	CAADRIA
email
last changed	2022/06/07 07:50

_id	ecaade2021_158
id	ecaade2021_158
authors	Joyce, Sam Conrad and Nazim, Ibrahim
year	2021
title	Limits to Applied ML in Planning and Architecture - Understanding and defining extents and capabilities
doi	https://doi.org/10.52842/conf.ecaade.2021.1.243
source	Stojakovic, V and Tepavcevic, B (eds.), Towards a new, configurable architecture - Proceedings of the 39th eCAADe Conference - Volume 1, University of Novi Sad, Novi Sad, Serbia, 8-10 September 2021, pp. 243-252
summary	There has been an exponential increase in Machine Learning (ML) research in design. Specifically, with Deep Learning becoming more accessible, frameworks like Generative Adversarial Networks (GANs), which are able to synthesise novel images are being used in the classification and generation of designs in architecture. While much of these explorations successfully demonstrate the 'magic' and potential of these techniques, their limits remain unclear, with only a few, but crucial, discussions on underlying fundamental limits and sensitivities of ML. This is a gap in our understanding of these tools especially within the complex context of planning and architecture. This paper seeks to discuss what limits ML in design as it exists today, by examining the state-of-the-art and mechanics of ML models relevant to design tasks. Aiming to help researchers to focus on productive uses of ML and avoid areas of over-promise.
keywords	Machine Learning; Artificial Intelligence; Creativity
series	eCAADe
email
last changed	2022/06/07 07:52

_id	acadia23_v1_242
id	acadia23_v1_242
authors	Noel, Vernelle A.
year	2023
title	Carnival + AI: Heritage, Immersive virtual spaces, and Machine Learning
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 1: Projects Catalog of the 43rd Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-8-1]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 242-245.
summary	Built on a Situated Computations framework, this project explores preservation, reconfiguration, and presentation of heritage through immersive virtual experiences, and machine learning for new understandings and possibilities (Noel 2020; 2017; Leach and Campo 2022; Leach 2021). Using the Trinidad and Tobago Carnival - hereinafter referred to as Carnival - as a case study, Carnival + AI is a series of immersive experiences in design, culture, and artificial intelligence (AI). These virtual spaces create new digital modes of engaging with cultural heritage and reimagined designs of traditional sculptures in the Carnival (Noel 2021). The project includes three virtual events that draw on real events in the Carnival: (1) the Virtual Gallery, which builds on dancing sculptures in the Carnival and showcases AI-generated designs; (2) Virtual J’ouvert built on J’ouvert in Carnival with AI-generated J’ouvert characters specific; and (3) Virtual Mas which builds on the masquerade.
series	ACADIA
type	project
email
last changed	2024/04/17 13:58

_id	acadia21_142
id	acadia21_142
authors	Quinteros, Cami; Rossi, Gabriella; Shawqy, Hesham; Papdopoulou, Iliana; Leon, David
year	2021
title	Imaginary Vessels
doi	https://doi.org/10.52842/conf.acadia.2021.142
source	ACADIA 2021: Realignments: Toward Critical Computation [Proceedings of the 41st Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-986-08056-7]. Online and Global. 3-6 November 2021. edited by B. Bogosian, K. Dörfler, B. Farahi, J. Garcia del Castillo y López, J. Grant, V. Noel, S. Parascho, and J. Scott. 142-151.
summary	Clay is one of the foundational materials in art and architecture, traced in the development of mud walls and the adobe module, and showcased in utilitarian and ornamental pottery. Wheel throwing is the process of shaping clay mainly into symmetrical objects, a complex craft in which the master potter has the knowledge and skill to manipulate the clay into the final design of various physical objects. This project explores how Machine Learning can be used to translate the richness and complexity of wheel throwing for digital fabrication. In this paper we present a surrogate digital dataset for robotic fabrication and geometric prediction used to train neural networks and provide a bridge between digital fabrication and handcraft. We report on the parametric model which abstracts wheel throwing as the interaction between a rotating mass and a given set of forces, as well as on data wrangling methods, dataset composition considerations, and training methodology. We present two models, one in which geometry is predicted based on a given set of forces, and a second in which forces are predicted based on a given geometry. Lastly, we give a critical assessment of the predictions of both networks and discuss future steps.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	acadia21_76
id	acadia21_76
authors	Smith, Rebecca
year	2021
title	Passive Listening and Evidence Collection
doi	https://doi.org/10.52842/conf.acadia.2021.076
source	ACADIA 2021: Realignments: Toward Critical Computation [Proceedings of the 41st Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-986-08056-7]. Online and Global. 3-6 November 2021. edited by B. Bogosian, K. Dörfler, B. Farahi, J. Garcia del Castillo y López, J. Grant, V. Noel, S. Parascho, and J. Scott. 76-81.
summary	In this paper, I present the commercial, urban-scale gunshot detection system ShotSpotter in contrast with a range of ecological sensing examples which monitor animal vocalizations. Gunshot detection sensors are used to alert law enforcement that a gunshot has occurred and to collect evidence. They are intertwined with processes of criminalization, in which the individual, rather than the collective, is targeted for punishment. Ecological sensors are used as a “passive” practice of information gathering which seeks to understand the health of a given ecosystem through monitoring population demographics, and to document the collective harms of anthropogenic change (Stowell and Sueur 2020). In both examples, the ability of sensing infrastructures to “join up and speed up” (Gabrys 2019, 1) is increasing with the use of machine learning to identify patterns and objects: a new form of expertise through which the differential agendas of these systems are implemented and made visible. I trace the differential agendas of these systems as they manifest through varied components: the spatial distribution of hardware in the existing urban environment and / or landscape; the software and other informational processes that organize and translate the data; the visualization of acoustical sensing data; the commercial factors surrounding the production of material components; and the apps, platforms, and other forms of media through which information is made available to different stakeholders. I take an interpretive and qualitative approach to the analysis of these systems as cultural artifacts (Winner 1980), to demonstrate how the political and social stakes of the technology are embedded throughout them.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	ascaad2021_071
id	ascaad2021_071
authors	Al Maani, Duaa; Saba Alnusairat, Amer Al-Jokhadar
year	2021
title	Transforming Learning for Architecture: Online Design Studio as New Norm for Crises Adaptation Under COVID-19
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. 129-141
summary	For students, studying architecture necessitates a fundamental shift in learning mode and attitude in the transition from school. Beginner students are often surprised by the new mode of learning-by-doing and the new learner identity that they must adopt and adapt to in the design studio. Moreover, due to the COVID-19 pandemic, architecture teaching has moved online. Both instructors and students are experiencing dramatic changes in their modes of teaching and learning due to the sudden move from on-campus design studios to a virtual alternative, with only the bare minimum of resources and relevant experience. This study explored the virtual design studio as a transformative learning model for disaster and resilience context, including the factors that affect foundation students’ perceptions and experiences of the quality of this adaptation. Data obtained from 248 students who took online design studios during the lockdown in 15 universities in Jordan highlight many factors that make the experience of the online design studio more challenging. Despite these challenges, strongly positive aspects of the online studio were evident and widely discussed. A model of hyper-flexible design studio in which students can have a direct contact with their instructors when needed – in addition to online activities, reviews, and written feedback – is highly recommended for the beginner years. This HyFlex model will enrich students’ learning and understanding of the fundamentals of design and ensure that technology solutions deliver significant and sustainable benefits.
series	ASCAAD
email
last changed	2021/08/09 13:13

_id	ascaad2021_021
id	ascaad2021_021
authors	Albassel, Mohamed; Mustafa Waly
year	2021
title	Applying Machine Learning to Enhance the Implementation of Egyptian Fire and Life Safety Code in Mega Projects
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. 7-22
summary	Machine Learning has become a significant research area in architecture; it can be used to retrieve valuable information for available data used to predict future instances. the purpose of this research was to develop an automated workflow to enhance the implementation of The Egyptian fire & life safety (FLS) code in mega projects and reduce the time wasted on the traditional process of rooms’ uses, occupant load, and egress capacity calculations to increase productivity by applying Supervised Machine Learning based on classification techniques through data mining and building datasets from previous projects, and explore the methods of preparation and analyzing data (text cleanup- tokenization- filtering- stemming-labeling). Then, provide an algorithm for classification rules using C# and python in integration with BIM tools such as Revit-Dynamo to calculate cumulative occupant load based on factors which are mentioned in the Egyptian FLS code, determine classification and uses of rooms to validate all data related to FLS. Moreover, calculating the egress capacity of means of egress for not only exit doors but also exit stairs. In addition, the research is to identify a clear understanding about ML and BIM through project case studies and how to build a model with the needed accuracy.
series	ASCAAD
email
last changed	2021/08/09 13:11

_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

_id	acadia21_400
id	acadia21_400
authors	Bruce, Mackenzie; Clune, Gabrielle; Xie, Ruxin; Mozaffari, Salma; Adel, Arash
year	2021
title	Cocoon: 3D Printed Clay Formwork for Concrete Casting
doi	https://doi.org/10.52842/conf.acadia.2021.400
source	ACADIA 2021: Realignments: Toward Critical Computation [Proceedings of the 41st Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-986-08056-7]. Online and Global. 3-6 November 2021. edited by B. Bogosian, K. Dörfler, B. Farahi, J. Garcia del Castillo y López, J. Grant, V. Noel, S. Parascho, and J. Scott. 400-409.
summary	Concrete, a material widely used in the construction industry today for its low cost and considerable strength as a composite building material, allows designers to work with nearly any form imaginable; if the technology to build the formwork is possible. By combining two historic and widely used materials, clay and concrete, our proposed novel process, Cocoon, integrates robotic clay three-dimensional (3D) printing as the primary formwork and incrementally casting concrete into this formwork to fabricate nonstandard concrete elements. The incremental casting and printing process anchors the concrete and clay together, creating a symbiotic and harmonious relationship. The concrete’s fluidity takes shape from the 3D printed clay formwork, allowing the clay to gain structure from the concrete as it cures. As the clay loses moisture, the formwork begins to shrink, crack, and reveal the concrete below. This self-demolding process produces easily removable formwork that can then be recycled by adding water to rehydrate the clay creating a nearly zero-waste formwork. This technique outlines multiple novel design features for complex concrete structures, including extended height limit, integrated void space design, tolerable overhang, and practical solutions for clay deformation caused by the physical stress during the casting process. The novelty of the process created by 3D printing clay formwork using an industrial robotic arm allows for rapid and scalable production of nearly zero-waste customizable formwork. More significant research implications can impact the construction industry, integrating more sustainable ways to build, enabled by digital fabrication technologies.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	sigradi2021_88
id	sigradi2021_88
authors	Evrim, Berfin
year	2021
title	Hybrid Carbon Fiber and Jute Fiber Textile Bone Stool: Integrative Fabrication Method of Weaving and 3D Printing
source	Gomez, P and Braida, F (eds.), Designing Possibilities - Proceedings of the XXV International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2021), Online, 8 - 12 November 2021, pp. 629–641
summary	The structural properties of Fiber Reinforced Polymers (FRP) encourage designers and architects to use textiles as a load-bearing architectural material to create lightweight and strong structures. Manufacturing techniques of FRPs are mostly concentrated on the molding method. This method requires an extra mold fabrication that causes waste of material. This study focuses on integrative weaving and 3D printing fabrication methods, which emphasize the lightweight property of the material. This integrative method avoids excessive material waste during fabrication by using an additive approach. 3D printing on textiles prevents significant deformation in a specific direction of the fabric instead of using any kind of synthetic resin for stiffening the fabric. Additionally, structural behavior simulation allows designers to understand the different loading conditions and maximize the strengths of each textile design by adding more material where it is needed for possible architectural applications.
keywords	Stool Design, Bone Analysis, Textile Load Simulation, Weaving, 3D Printing
series	SIGraDi
email
last changed	2022/05/23 12:11

_id	ecaade2021_115
id	ecaade2021_115
authors	Foged, Isak and Hilmer, Jacob
year	2021
title	Fiber Compositions - Development of wood and textile layered structures as a material strategy for sustainable design
doi	https://doi.org/10.52842/conf.ecaade.2021.2.443
source	Stojakovic, V and Tepavcevic, B (eds.), Towards a new, configurable architecture - Proceedings of the 39th eCAADe Conference - Volume 2, University of Novi Sad, Novi Sad, Serbia, 8-10 September 2021, pp. 443-452
summary	This study examines composite compositions based on fiber-based materials. It focuses on organic textiles of Jute, Hemp, Wool, Flax, and Glass fiber as a synthetic textile, combined with the lightweight wood species Paulownia. By creating novel composites, the study aims to investigate methods and generate design knowledge for material strategies to improve and reduce material waste in the built environment, further enabled by the use of small elements that can be sourced from waste wood and reclaimed wood. Research is conducted as a hybrid material-computational methodology, developing and testing probes, prototypes and a full-scale demonstrator assembly in the form of a wall seating composition. The results find that the proposed method and resulting composites have significant potentials for both expressive and functional characteristics, allowing tectonic articulation to be made, while creating minimum material structures based on assembly of small elements to larger complex curvature building parts.
keywords	Wood; Textile; Composite; Computational Design; Environmental Design
series	eCAADe
email
last changed	2022/06/07 07:51

_id	caadria2023_446
id	caadria2023_446
authors	Guida, George
year	2023
title	Multimodal Architecture: Applications of Language in a Machine Learning Aided Design Process
doi	https://doi.org/10.52842/conf.caadria.2023.2.561
source	Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 561–570
summary	Recent advances in Natural Language Processing (NLP) and Diffusion Models (DMs) are leading to a significant change in the way architecture is conceived. With capabilities that surpass those of current generative models, it is now possible to produce an unlimited number of high-quality images (Dhariwal and Nichol 2021). This opens up new opportunities for using synthetic images and marks a new phase in the creation of multimodal 3D forms, central to architectural concept design stages. Presented here are three methodologies of generation of meaningful 2D and 3D designs, merging text-to-image diffusion models Stable Diffusion, and DALL-E 2 with computational methods. These allow designers to intuitively navigate through a multimodal feedback loop of information originating from language and aided by artificial intelligence tools. This paper contributes to our understanding of machine-augmented design processes and the importance of intuitive user interfaces (UI) in enabling new dialogues between humans and machines. Through the creation of a prototype of an accessible UI, this exchange of information can empower designers, build trust in these tools, and increase control over the design process.
keywords	Machine Learning, Diffusion Models, Concept Design, Semantics, User Interface, Design Agency
series	CAADRIA
email
last changed	2023/06/15 23:14

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