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

PDF papers
References

Hits 1 to 20 of 619

Reformat results as: short short into frame detailed detailed into frame

_id	caadria2019_109
id	caadria2019_109
authors	Kim, Jinsung, Song, Jaeyeol and Lee, Jin-Kook
year	2019
title	Approach to Auto-recognition of Design Elements for the Intelligent Management of Interior Pictures
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 2, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 785-794
doi	https://doi.org/10.52842/conf.caadria.2019.2.785
summary	This paper explores automated recognition of elements in interior design pictures for an intelligent design reference management system. Precedent design references have a significant role to help architects, designer and even clients in general architecture design process. Pictures are one of the representation that could exactly show a kind of design idea and knowledge. Due to the velocity, variety and volume of reference pictures data with growth of references platform, it is hard and time-consuming to handle the data with current manual way. To solve this problem , this paper depicts a deep learning-based approach to figuring out design elements and recognizing the design feature of them on the interior pictures using faster-RCNN and CNN algorithms. The targets are the residential furniture such as a table and a seating. Through proposed application, input pictures can automatically have tagging data as follows; seating1(type: sofa, seating capacity: two-seaters, design style: classic)
keywords	Interior design picture; Design element; Design feature; Automated recognition; Design Reference management
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	ijac201917106
id	ijac201917106
authors	Brown, Nathan C. and Caitlin T. Mueller
year	2019
title	Design variable analysis and generation for performance-based parametric modeling in architecture
source	International Journal of Architectural Computing vol. 17 - no. 1, 36-52
summary	Many architectural designers recognize the potential of parametric models as a worthwhile approach to performance- driven design. A variety of performance simulations are now possible within computational design environments, and the framework of design space exploration allows users to generate and navigate various possibilities while considering both qualitative and quantitative feedback. At the same time, it can be difficult to formulate a parametric design space in a way that leads to compelling solutions and does not limit flexibility. This article proposes and tests the extension of machine learning and data analysis techniques to early problem setup in order to interrogate, modify, relate, transform, and automatically generate design variables for architectural investigations. Through analysis of two case studies involving structure and daylight, this article demonstrates initial workflows for determining variable importance, finding overall control sliders that relate directly to performance and automatically generating meaningful variables for specific typologies.
keywords	Parametric design, design space formulation, data analysis, design variables, dimensionality reduction
series	journal
email
last changed	2019/08/07 14:04

_id	caadria2019_396
id	caadria2019_396
authors	Cao, Rui, Fukuda, Tomohiro and Yabuki, Nobuyoshi
year	2019
title	Quantifying Visual Environment by Semantic Segmentation Using Deep Learning - A Prototype for Sky View Factor
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 2, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 623-632
doi	https://doi.org/10.52842/conf.caadria.2019.2.623
summary	Sky view factor (SVF) is the ratio of radiation received by a planar surface from the sky to that received from the entire hemispheric radiating environment, in the past 20 years, it was more applied to urban-climatic areas such as urban air temperature analysis. With the urbanization and the development of cities, SVF has been paid more and more attention on as the important parameter in urban construction and city planning area because of increasing building coverage ratio to promote urban forms and help creating a more comfortable and sustainable urban residential building environment to citizens. Therefore, efficient, low cost, high precision, easy to operate, rapid building-wide SVF estimation method is necessary. In the field of image processing, semantic segmentation based on deep learning have attracted considerable research attention. This study presents a new method to estimate the SVF of residential environment by constructing a deep learning network for segmenting the sky areas from 360-degree camera images. As the result of this research, an easy-to-operate estimation system for SVF based on high efficiency sky label mask images database was developed.
keywords	Visual environment; Sky view factor; Semantic segmentation; Deep learning; Landscape simulation
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	caadria2020_093
id	caadria2020_093
authors	Cerovsek, Tomo and Martens, Bob
year	2020
title	The Evolution of CAADRIA Conferences - A Bibliometric Approach
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 325-334
doi	https://doi.org/10.52842/conf.caadria.2020.1.325
summary	This paper presents an analysis of the output, impact, use and content of 1,860 papers that were published in the CAADRIA conference proceedings over the last 20+ years (from 1996 to 2019). The applied methodology is a blend of bibliometrics, webometrics and clustering with text mining. The bibliometric analysis leads to quantitative and qualitative results on three levels: (1) author, (2) article and (3) association. The most productive authors authored over 50 papers, and the top 20% authors have over 80 % of all citations generated by CAADRIA proceedings. The overall impact of CAADRIA may be characterised by nearly 2,000 known citations and by the h-index that is 17. The webometrics based on CumInCAD.org reveals that the CAADRIA papers served over 200 k users, which is a considerable visibility for scientific CAAD output. The keywords most frequently used by authors were digital fabrication, BIM and parametric, generative, computational design. Notably, 90% of the papers' descriptors are 2-grams. This study may be useful to researchers, educators and publishers interested in CAAD.
keywords	bibliometrics; open source; text clustering; n-gram
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	caadria2019_117
id	caadria2019_117
authors	Deniz Kiraz, Leyla and Kocaturk, Tuba
year	2019
title	Integrating User-Behaviour as Performance Criteria in Conceptual Parametric Design
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 1, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 215-224
doi	https://doi.org/10.52842/conf.caadria.2019.1.215
summary	Prediction of user behaviour has always been problematic in architectural design. Several methods have already been developed and explored to model human behaviour in architecture. However, the majority of these methods are implemented during post-design evaluation where the insights obtained can only be implemented in a limited capacity. There is an apparent gap and opportunity, in current research and practice, to embed behaviour simulations directly into the conceptual design process. The proposed paper (research) aims to fill this gap. This paper will report on the results of a recently completed research exploring the integration process of Agent Based Modelling into the conceptual design process, using a parametric design approach. The research resulted in the development of a methodological framework for the integration of behavioural parameters into the explorative stages of the early design process. This paper also offers a categorisation and critical evaluation of existing Agent Based Modelling applications in current research and practice, which leads to the formulation of possible pathways for future implementation.
keywords	Performance Based Design; Generative Design; Behaviour Modelling; Agent Based Modelling; Parametric Design
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	acadia19_130
id	acadia19_130
authors	Devadass, Pradeep; Heimig, Tobias; Stumm, Sven; Kerber, Ethan; Cokcan, Sigrid Brell
year	2019
title	Robotic Constraints Informed Design Process
source	ACADIA 19:UBIQUITY AND AUTONOMY [Proceedings of the 39th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-59179-7] (The University of Texas at Austin School of Architecture, Austin, Texas 21-26 October, 2019) pp. 130-139
doi	https://doi.org/10.52842/conf.acadia.2019.130
summary	Promising results in efficiently producing highly complex non-standard designs have been accomplished by integrating robotic fabrication with parametric design. However, the project workflow is hampered due to the disconnect between designer and robotic fabricator. The design is most often developed by the designer independently from fabrication process constraints. This results in fabrication difficulties or even non manufacturable components. In this paper we explore the various constraints in robotic fabrication and assembly processes, analyze their influence on design, and propose a methodology which bridges the gap between parametric design and robotic production. Within our research we investigate the workspace constraints of robots, end effectors, and workpieces used for the fabrication of an experimental architectural project: “The Twisted Arch.” This research utilizes machine learning approaches to parameterize, quantify, and analyze each constraint while optimizing how those parameters impact the design output. The research aims to offer a better planning to production process by providing continuous feedback to the designer during early stages of the design process. This leads to a well-informed “manufacturable” design.
keywords	Robotic Fabrication and Assembly, Mobile Robotics, Machine Learning, Parametric Design, Constraint Based Design.
series	ACADIA
type	normal paper
email
last changed	2022/06/07 07:55

_id	ecaadesigradi2019_648
id	ecaadesigradi2019_648
authors	Eisenstadt, Viktor, Langenhan, Christoph and Althoff, Klaus-Dieter
year	2019
title	Generation of Floor Plan Variations with Convolutional Neural Networks and Case-based Reasoning - An approach for transformative adaptation of room configurations within a framework for support of early conceptual design phases
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 2, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 79-84
doi	https://doi.org/10.52842/conf.ecaade.2019.2.079
summary	We present an approach for computer-aided generation of different variations of floor plans during the early phases of conceptual design in architecture. The early design phases are mostly characterized by the processes of inspiration gaining and search for contextual help in order to improve the building design at hand. The generation method described in this work uses the novel as well as established artificial intelligence methods, namely, generative adversarial nets and case-based reasoning, for creation of possible evolutions of the current design based on the most similar previous designs. The main goal of this approach is to provide the designer with information on how the current floor plan can evolve over time in order to influence the direction of the design process. The work described in this paper is part of the methodology FLEA (Find, Learn, Explain, Adapt) whose task is to provide a holistic structure for support of the early conceptual phases in architecture. The approach is implemented as the adaptation component of the framework MetisCBR that is based on FLEA.
keywords	room configuration; adaptation; case-based reasoning; convolutional neural networks; conceptual design
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:55

_id	acadia19_16
id	acadia19_16
authors	Hosmer, Tyson; Tigas, Panagiotis
year	2019
title	Deep Reinforcement Learning for Autonomous Robotic Tensegrity (ART)
source	ACADIA 19:UBIQUITY AND AUTONOMY [Proceedings of the 39th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-59179-7] (The University of Texas at Austin School of Architecture, Austin, Texas 21-26 October, 2019) pp. 16-29
doi	https://doi.org/10.52842/conf.acadia.2019.016
summary	The research presented in this paper is part of a larger body of emerging research into embedding autonomy in the built environment. We develop a framework for designing and implementing effective autonomous architecture defined by three key properties: situated and embodied agency, facilitated variation, and intelligence.We present a novel application of Deep Reinforcement Learning to learn adaptable behaviours related to autonomous mobility, self-structuring, self-balancing, and spatial reconfiguration. Architectural robotic prototypes are physically developed with principles of embodied agency and facilitated variation. Physical properties and degrees of freedom are applied as constraints in a simulated physics-based environment where our simulation models are trained to achieve multiple objectives in changing environments. This holistic and generalizable approach to aligning deep reinforcement learning with physically reconfigurable robotic assembly systems takes into account both computational design and physical fabrication. Autonomous Robotic Tensegrity (ART) is presented as an extended case study project for developing our methodology. Our computational design system is developed in Unity3D with simulated multi-physics and deep reinforcement learning using Unity’s ML-agents framework. Topological rules of tensegrity are applied to develop assemblies with actuated tensile members. Single units and assemblies are trained for a series of policies using reinforcement learning in single-agent and multi-agent setups. Physical robotic prototypes are built and actuated to test simulated results.
series	ACADIA
type	normal paper
email
last changed	2022/06/07 07:50

_id	ecaadesigradi2019_346
id	ecaadesigradi2019_346
authors	Kaftan, Martin, Sautter, Sebastian and Kubicek, Bernhard
year	2019
title	Integrating BIPV during Early Stages of Building Design
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 2, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 139-144
doi	https://doi.org/10.52842/conf.ecaade.2019.2.139
summary	In the quest to achieve the ambitious climate and clean energy targets the broad implementation of Integrated Photovoltaics (BIPV) is one of the keys. Photovoltaic (PV) modules can be installed above or on current roofing or traditional wall structures. In addition, BIPV devices substitute the skin of the exterior construction frame, i.e. the weather screen, thus simultaneously acting as both a climate screen and an energy producing source. However, while the integral planning strategy to building projects promotes the effective execution of BIPV, the limitation lies in the absence of both instruments and easy-to-use planning aid guidelines, particularly by non-PV experts in the early design stage. This study presents computational methods that help to quickly analyze the BIPV potential for a given building project and to suggest the optimal economical amount and location of the panels based on the building's energy demand profile.
keywords	building integrated photovoltaic (BIPV); integral planning; design rules; simplified models; machine learning
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:52

_id	cf2019_004
id	cf2019_004
authors	Kim, Jinsung; Jaeyeol Song and Jin-Kook Lee
year	2019
title	Recognizing and Classifying Unknown Object in BIM using 2D CNN
source	Ji-Hyun Lee (Eds.) "Hello, Culture!" [18th International Conference, CAAD Futures 2019, Proceedings / ISBN 978-89-89453-05-5] Daejeon, Korea, p. 23
summary	This paper aims to propose an approach to automated classifying building element instance in BIM using deep learning-based 3D object classification algorithm. Recently, studies related to checking or validating engine of BIM object for ensuring data integrity of BIM instances are getting attention. As a part of this research, this paper train recognition models that are targeted at basic building element and interior element using 3D object recognition technique that uses images of objects as inputs. Object recognition is executed in two stages; 1) class of object (e.g. wall, window, seating furniture, toilet fixture and etc.), 2) sub-type of specific classes (e.g. Toilet or Urinal). Using the trained models, BIM plug-in prototype is developed and the performance of this AI-based approach with test BIM model is checked. We expect this recognition approach to help ensure the integrity of BIM data and contribute to the practical use of BIM.
keywords	3D object classification, Building element, Building information modeling, Data integrity, Interior element
series	CAAD Futures
email
last changed	2019/07/29 14:08

_id	acadia19_664
id	acadia19_664
authors	Koshelyuk, Daniil; Talaei, Ardeshir; Garivani, Soroush; Markopoulou, Areti; Chronis, Angelo; Leon, David Andres; Krenmuller, Raimund
year	2019
title	Alive
source	ACADIA 19:UBIQUITY AND AUTONOMY [Proceedings of the 39th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-59179-7] (The University of Texas at Austin School of Architecture, Austin, Texas 21-26 October, 2019) pp. 664-673
doi	https://doi.org/10.52842/conf.acadia.2019.664
summary	In the context of data-driven culture, built space still maintains low responsiveness and adaptability. Part of this reality lies in the low resolution of live information we have about the behavior and condition of surfaces and materials. This research addresses this issue by exploring the development of a deformation-sensing composite membrane material system following a bottom-up approach and combining various technologies toward solving related technical issues—exploring conductivity properties of graphene and maximizing utilization within an architecture-related proof-of-concept scenario and a workflow including design, fabrication, and application methodology. Introduced simulation of intended deformation helps optimize the pattern of graphene nanoplatelets (GNP) to maximize membrane sensitivity to a specific deformation type while minimizing material usage. Research explores various substrate materials and graphene incorporation methods with initial geometric exploration. Finally, research introduces data collection and machine learning techniques to train recognition of certain types of deformation (single point touch) on resistance changes. The final prototype demonstrates stable and symmetric readings of resistance in a static state and, after training, exhibits an 88% prediction accuracy of membrane shape on a labeled sample data-set through a pre-trained neural network. The proposed framework consisting of a simulation based, graphene-capturing fabrication method on stretchable surfaces, and includes initial exploration in neural network training shape detection, which combined, demonstrate an advanced approach to embedding intelligence.
series	ACADIA
type	normal paper
email
last changed	2022/06/07 07:51

_id	ecaadesigradi2019_173
id	ecaadesigradi2019_173
authors	Matthias, Kulcke and Martens, Bob
year	2019
title	Digital Empowerment for the "Experimental Bureau" - Work Based Learning in Architectural Education
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 1, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 117-126
doi	https://doi.org/10.52842/conf.ecaade.2019.1.117
summary	This paper describes the concept of the "Experimental Bureau" as a didactic environment aiming to deal with real-life design tasks within the framework of architectural education. Its main focus lies on the specific opportunities for digital empowerment of students who learn about the design process - sometimes even in the role of contractors - in real-life oriented project work. Thus the following questions come under scrutiny and discussion from an angle of work based learning: What kind of design problems are tackled in a meaningful way by students through the utilization of a digital strategy? What kind of software (or software mix) is chosen and what problems are addressed by the choice and handling of these digital tools? These questions are answered in a different way applying the format of the Experimental Bureau, driven by its real-life projects and client communication, in comparison to largely artificial tasks confined to the academic realm.
keywords	design education; real-life case study; stakeholder communication; real-world experience; didactic approach
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:58

_id	ecaadesigradi2019_456
id	ecaadesigradi2019_456
authors	Pereira, In?s, Belém, Catarina and Leit?o, António
year	2019
title	Optimizing Exhibition Spaces - A Multi-Objective Approach
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 3, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 53-62
doi	https://doi.org/10.52842/conf.ecaade.2019.3.053
summary	Nowadays, there is a widespread awareness towards environmental issues. This is already visible in architecture by the increasing number of analysis tools that evaluate different performance criteria. However, the application of these tools is usually restricted to the final design stages, conditioning the implementation of design changes. Performance-Based Design (PBD) is an approach that addresses this limitation. Through PBD, architects integrate analysis tools since early design stages to make informed decisions regarding the performance of their designs. Since the success of PBD highly depends on the number of evaluations that can be performed, these approaches usually end up benefiting from Parametric Models (PMs), which facilitate the generation of a wide range of design variations, by simply changing the values of the parameters. Furthermore, in order to more efficiently achieve a PBD approach, architects can take advantage of the combination between PMs, analysis tools, and optimization processes. In this paper, we explore this combination to optimize an exhibition space regarding its daylight performance and the material cost of the new elements intended for that space.
keywords	Environmental Design; Algorithmic Design and Analysis; Performance-Based Design; Multi-Objective Optimization; Daylight Optimization
series	eCAADeSIGraDi
email
last changed	2022/06/07 08:00

_id	acadia19_352
id	acadia19_352
authors	Poustinchi, Ebrahim
year	2019
title	Robotically Augmented Imaging (RAI Alpha)
source	ACADIA 19:UBIQUITY AND AUTONOMY [Proceedings of the 39th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-59179-7] (The University of Texas at Austin School of Architecture, Austin, Texas 21-26 October, 2019) pp. 352-359
doi	https://doi.org/10.52842/conf.acadia.2019.352
summary	This paper presents a project-based research study in the design studio context, highlighting the use of robotic technology as a “perspective-machine” to create custom spatial readings/experiences through predetermined and controlled static/dynamic views. The early studies of this method—in this paper referred to as Robotically Augmented Imaging (RAI Alpha), enables architects, designers, and students to micro direct the “spatial experience” and atmospheric effects of the project through visual story-telling and in multiscale set-ups ranging from architectural to product and object scale. Demonstrating the contemporary opportunities of imaging and perspective—as an architectural tool to investigate/define the space—RAI Alpha studies the potentials of robotically controlled/manipulated views as a possible new medium for interacting with form, space, architecture, atmosphere, and performance in a scale-free seamless experience and as both a design tool and a product.
series	ACADIA
type	normal paper
email
last changed	2022/06/07 08:00

_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
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
doi	https://doi.org/10.52842/conf.ecaade.2023.2.327
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	ecaadesigradi2019_201
id	ecaadesigradi2019_201
authors	Torreblanca-Díaz, David A., Pati?o, Ever, Valencia-Escobar, Andrés and Urdinola, Diana
year	2019
title	Form-finding methodology as strategy for formative research in industrial design education - Experimental techniques for the early creative phases of the product design process
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 1, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 45-54
doi	https://doi.org/10.52842/conf.ecaade.2019.1.045
summary	The experimental work of Antoni Gaudí and Frei Otto have been the precedents of what is currently called form-finding, a methodology based on rules and physical forces of nature that promotes principles of transformation as a result of the relationship between form, material and structure. This text shows the first results of the research titled as Form-finding methodology as strategy for formative research in industrial design education, with an empirical-analytical approach through action-research based method and using collaborative-participatory tools. As a result of the analysis of different cases in the first stage of the research, a basic methodological proposal is made, this methodological proposal is aimed to find new research possibilities for the identification of morphological characteristics to be used in design projects in the early creative phases (ideation and experimentation); the methodological proposal stages are the following: selection of technique, design of the experimentation, experimentation, analysis and discussion.
keywords	Form-finding; Experimental morphology; Industrial design education; Formative research; Action-research
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:58

_id	acadia19_642
id	acadia19_642
authors	Chua, Pamela Dychengbeng; Hui, Lee Fu
year	2019
title	Compliant Laminar Assemblies
source	ACADIA 19:UBIQUITY AND AUTONOMY [Proceedings of the 39th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-59179-7] (The University of Texas at Austin School of Architecture, Austin, Texas 21-26 October, 2019) pp. 642-653
doi	https://doi.org/10.52842/conf.acadia.2019.642
summary	This paper presents an innovative approach to the design and fabrication of three-dimensional objects from single-piece flat sheets, inspired by the origami technique of twist-closing. While in origami twist-closing is merely used to stabilize a cylindrical or spherical structure, ensuring it maintains its shape, this research investigates the potential of twist-closing as a multi-functional mechanism that also activates and controls the transformation of a planar surface into a predesigned three-dimensional form. This exploration is directed towards an intended application to stiff and brittle sheet materials that are difficult to shape through other processes. The methods we have developed draw mainly upon principles of lattice kirigami and laminar reciprocal structures. These are reflected in a workflow that integrates digital form-generation and fabrication-rationalization techniques to reference and apply these principles at every stage. Significant capabilities of the developed methodology include: (1) achievement of pseudo-double-curvature with brittle, stiff sheet materials; (2) stabilization in a 3D end-state as a frameless self-contained single-element laminar reciprocal structure—essentially a compliant mechanism; and (3) an ability to pre-encode 3D assembly constraints in a 2D cutout pattern, which guides a moldless fabrication process. The paper reviews the precedent geometric techniques and principles that comprise this method of 3D surface fabrication and describes a sample deployment of the method as applied to the design of laminar modules made of high-pressure laminate (HPL).
series	ACADIA
type	normal paper
email
last changed	2022/06/07 07:54

_id	ecaade2023_138
id	ecaade2023_138
authors	Crolla, Kristof and Wong, Nichol
year	2023
title	Catenary Wooden Roof Structures: Precedent knowledge for future algorithmic design and construction optimisation
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 1, Graz, 20-22 September 2023, pp. 611–620
doi	https://doi.org/10.52842/conf.ecaade.2023.1.611
summary	The timber industry is expanding, including construction wood product applications such as glue-laminated wood products (R. Sikkema et al., 2023). To boost further utilisation of engineered wood products in architecture, further development and optimisation of related tectonic systems is required. Integration of digital design technologies in this endeavour presents opportunities for a more performative and spatially diverse architecture production, even in construction contexts typified by limited means and/or resources. This paper reports on historic precedent case study research that informs an ongoing larger study focussing on novel algorithmic methods for the design and production of lightweight, large-span, catenary glulam roof structures. Given their structural operation in full tension, catenary-based roof structures substantially reduce material needs when compared with those relying on straight beams (Wong and Crolla, 2019). Yet, the manufacture of their non-standard geometries typically requires costly bespoke hardware setups, having resulted in recent projects trending away from the more spatially engaging geometric experiments of the second half of the 20th century. The study hypothesis that the evolutionary design optimisation of this tectonic system has the potential to re-open and expand its practically available design solution space. This paper covers the review of a range of built projects employing catenary glulam roof system, starting from seminal historic precedents like the Festival Hall for the Swiss National Exhibition EXPO 1964 (A. Lozeron, Swiss, 1964) and the Wilkhahn Pavilions (Frei Otto, Germany, 1987), to contemporary examples, including the Grandview Heights Aquatic Centre (HCMA Architecture + Design, Canada, 2016). It analysis their structural concept, geometric and spatial complexity, fabrication and assembly protocols, applied construction detailing solutions, and more, with as aim to identify methods, tools, techniques, and construction details that can be taken forward in future research aimed at minimising construction complexity. Findings from this precedent study form the basis for the evolutionary-algorithmic design and construction method development that is part of the larger study. By expanding the tectonic system’s practically applicable architecture design solution space and facilitating architects’ access to a low-tech producible, spatially versatile, lightweight, eco-friendly, wooden roof structure typology, this study contributes to environmentally sustainable building.
keywords	Precedent Studies, Light-weight architecture, Timber shell, Catenary, Algorithmic Optimisation, Glue-laminated timber
series	eCAADe
email
last changed	2023/12/10 10:49

_id	acadia20_142p
id	acadia20_142p
authors	Kilian, Axel
year	2020
title	The Flexing Room
source	ACADIA 2020: Distributed Proximities / Volume II: Projects [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95253-6]. Online and Global. 24-30 October 2020. edited by M. Yablonina, A. Marcus, S. Doyle, M. del Campo, V. Ago, B. Slocum. 142-147
summary	Robotics has been largely confined to the object category with fewer examples at the scale of buildings. Robotic buildings present unique challenges in communicating intent to the enclosed user. Precedent work in architectural robotics explored the performative dimension, the playful and interactive qualities, and the cognitive challenges of AI systems interacting with people in architecture. The Flexing Room robotic skeleton was installed at MIT at its full designed height for the first time and tested for two weeks in the summer of 2019. The approximately 13-foot-tall structure is comprised of 36 pneumatic actuators and an active bend fiberglass structure. The full height allowed for a wide range of postures the structure could take. Acoustic monitoring through Piezo pickup mics was added that allowed for basic rhythmic responses of the structure to people tapping or otherwise triggering the vibration sensors. Data streams were collected synchronously from Kinect skeleton tracking, piezo pickup mics, camera streams, and posture data. The emphasis in this test period was first to establish reliable hardware operations at full scale and second to record correlated data streams of the sensors installed in the structure together with the actuation triggers and the human poses of the inhabitant. The full-scale installation of hardware was successful and proved the feasibility of the structural and actuation approach previously tested on a one-level setup. The range of postures was increased and more transparent for the occupant. The perception of the structure as space was also improved as the system reached regular ceiling height and formed a clearer architectural scale enclosure. The ambition of communicating through architectural postures has not been achieved yet, but promising directions emerged from the test and data collection
series	ACADIA
type	project
email
last changed	2021/10/26 08:03

_id	acadia19_72
id	acadia19_72
authors	Pertigkiozoglou, Eliza
year	2019
title	Pattern Mapping
source	ACADIA 19:UBIQUITY AND AUTONOMY [Proceedings of the 39th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-59179-7] (The University of Texas at Austin School of Architecture, Austin, Texas 21-26 October, 2019) pp. 72-80
doi	https://doi.org/10.52842/conf.acadia.2019.072
summary	Current computer-aided-design tools tend to focus on technical descriptions of objects and processes, while disregarding the agency of the designer in the creative process. This research shifts the focus to explore how computational tools could embrace the designer’s perception and trigger design exploration. In this direction, Pattern Mapping is presented as a prototypical software for the designing, making, and learning of a geometric material system: free-form surfaces created by the deformation of thin aluminum with auxetic-pattern slits. Along with the development of the software, the paper reports on a new methodology towards visual exploration in computational tools. Texture mapping—a computer-graphics algorithm—is utilized to bridge intuitive visualizations of form and materiality with geometric analysis. Informed by recent studies on design creativity, visual perception, and a precedent of an artist’s workflow, the proposed software facilitates learning through multiple modes of representations and drawing-like operations. Ultimately, Pattern Mapping is a provocation for the fusion of computational analysis with perception, drawing, and making.
keywords
series	ACADIA
type	normal paper
email
last changed	2022/06/07 08:00

For more results click below: