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	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	cf2019_052
id	cf2019_052
authors	Abdelmohsen, Sherif ;Passaint Massoud, Rana El-Dabaa, Aly Ibrahim and Tasbeh Mokbel
year	2019
title	The Effect of Hygroscopic Design Parameters on the Programmability of Laminated Wood Composites for Adaptive Façades
source	Ji-Hyun Lee (Eds.) "Hello, Culture!" [18th International Conference, CAAD Futures 2019, Proceedings / ISBN 978-89-89453-05-5] Daejeon, Korea, p. 435
summary	Typical adaptive façades respond to external conditions to enhance indoor spaces based on complex mechanical actuators and programmable functions. Hygroscopic embedded properties of wood, as low-cost low-tech programmable material, have been utilized to induce passive motion mechanisms. Wood as anisotropic material allows for different passive programmable motion configurations that relies on several hygroscopic design parameters. This paper explores the effect of these parameters on programmability of laminated wood composites through physical experiments in controlled humidity environment. The paper studies variety of laminated configurations involving different grain orientations, and their effect on maximum angle of deflection and its durability. Angle of deflection is measured using image analysis software that is used for continuous tracking of deflection in relation to time. Durability is studied as the number of complete programmable cycles that wood could withstand before reaching point of failure. Results revealed that samples with highest deflection angle have least programmability durability.
keywords	Wood, hygroscopic design, lamination, deflection, durability, adaptive façades
series	CAAD Futures
email
last changed	2019/07/29 14:18

_id	ecaade2021_203
id	ecaade2021_203
authors	Arora, Hardik, Bielski, Jessica, Eisenstadt, Viktor, Langenhan, Christoph, Ziegler, Christoph, Althoff, Klaus-Dieter and Dengel, Andreas
year	2021
title	Consistency Checker - An automatic constraint-based evaluator for housing spatial configurations
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. 351-358
doi	https://doi.org/10.52842/conf.ecaade.2021.2.351
summary	The gradual rise of artificial intelligence (AI) and its increasing visibility among many research disciplines affected Computer-Aided Architectural Design (CAAD). Architectural deep learning (DL) approaches are being developed and published on a regular basis, such as retrieval (Sharma et al. 2017) or design style manipulation (Newton 2019; Silvestre et al. 2016). However, there seems to be no method to evaluate highly constrained spatial configurations for specific architectural domains (such as housing or office buildings) based on basic architectural principles and everyday practices. This paper introduces an automatic constraint-based consistency checker to evaluate the coherency of semantic spatial configurations of housing construction using a small set of design principles to evaluate our DL approaches. The consistency checker informs about the overall performance of a spatial configuration followed by whether it is open/closed and the constraints it didn't satisfy. This paper deals with the relation of spaces processed as mathematically formalized graphs contrary to existing model checking software like Solibri.
keywords	model checking, building information modeling, deep learning, data quality
series	eCAADe
email
last changed	2022/06/07 07:54

_id	ecaadesigradi2019_340
id	ecaadesigradi2019_340
authors	Azambuja Varela, Pedro and Sousa, José Pedro
year	2019
title	Digital Expansion of Stereotomy - A semantic classification
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. 387-396
doi	https://doi.org/10.52842/conf.ecaade.2019.1.387
summary	This paper presents a critical analysis and reflection on stereotomy with the purpose of updating its theoretical discourse. Having risen to the apex of architecture technological possibilities in the 17th century, stereotomic construction lost its importance in favour of iron, steel and other materials and construction techniques brought by the Industrial Revolution. More recently, much owing to the possibilities offered by digital technologies, a resurgence of interest in the subject has spawned various researches which bring stereotomy back to the architectural discourse. Although technological applications and design innovations in service of stereotomy have developed in multiple interesting paths, there is a lack of a common theory on the subject which is capable of relating these multiple apparently diverging stereotomic approaches between each other and, maybe even more importantly, to the classical practice which sparked the development this discipline. The research presented in this paper shows how the digital tools were instrumental in bringing this tradition to architecture contemporaneity and how a current stereotomy is largely supported by these technologies, while keeping strong relations to its classic origin.
keywords	stereotomy; classification; history; digital
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:54

_id	caadria2019_332
id	caadria2019_332
authors	Dwivedi, Urvashi, Porcellini, Valentin, Hong, Sukjoo, Chang, Zhuming and Lee, Ji-Hyun
year	2019
title	Computing Spatial Features to Allocate Collision-free Motion-paths for Tele-presence Avatars
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. 245-254
doi	https://doi.org/10.52842/conf.caadria.2019.1.245
summary	Recently, indoor-intelligent services like "Tele-presence" have made quite an advancement. Therefore, to completely 1) understand the diverse indoor environment, 2) efficiently calculate similarity for semantic spaces and 3) for defining an efficient path movement for an augmented reality-based Avatar; we propose spatial features computation, graphical representation and Topology-based graph-similarity measure for complex domains to overcome the limited visibility of an Avatar. Thus, collision with the surrounding objects in a given indoor-space can be avoided. This study begins by securing spatial features of objects, e.g., furniture, doorways, etc., of an indoor environment from an FBSMAP (Function-Behaviour-Structure Map). Then, we establish a method for defining similarity for locations and paths.
keywords	Tele-presence Avatar; Activity space; Topology; Spatial similarity; Similarity measure; Cell; Field of view.
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	cf2019_005
id	cf2019_005
authors	Eisenstadt, Viktor; Klaus-Dieter Althoff and Christoph Langenhan
year	2019
title	Supporting Architectural Design Process with FLEA A Distributed AI Methodology for Retrieval, Suggestion, Adaptation, and Explanation of Room Conﬁgurations
source	Ji-Hyun Lee (Eds.) "Hello, Culture!" [18th International Conference, CAAD Futures 2019, Proceedings / ISBN 978-89-89453-05-5] Daejeon, Korea, p. 24
summary	The artiﬁcial intelligence methods, such as case-based reasoning and artiﬁcial neural networks were already applied to the task of architectural design support in a multitude of speciﬁc approaches and tools. However, modern AI trends, such as Explainable AI (XAI), and additional features, such as providing contextual suggestions for the next step of the design process, were rarely considered an integral part of these approaches or simply not available. In this paper, we present an application of a distributed AI-based methodology FLEA (Find, Learn, Explain, Adapt) to the task of room conﬁguration during the early conceptual phases of architectural design. The implementation of the methodology in the framework MetisCBR applies CBR-based methods for retrieval of similar ﬂoor plans to suggest possibly inspirational designs and to explain the returned results with speciﬁc explanation patterns. Furthermore, it makes use of a farm of recurrent neural networks to suggest contextually suitable next conﬁguration steps and to present design variations that show how the designs may evolve in the future. The ﬂexibility of FLEA allows for variational use of its components in order to activate the currently required modules only. The methodology was initialized during the basic research project Metis (funded by German Research Foundation) during which the architectural semantic search patterns and a family of corresponding ﬂoor plan representations were developed. FLEA uses these patterns and representations as the base for its semantic search, explanation, next step suggestion, and adaptation components. The methodology implementation was iteratively tested during quantitative evaluations and user studies with multiple ﬂoor plan datasets.
keywords	Room con?guration, Distributed AI, Case-based reasoning, Neural networks, Explainable AI
series	CAAD Futures
type	normal paper
email
last changed	2019/07/29 14:11

_id	ecaadesigradi2019_117
id	ecaadesigradi2019_117
authors	Kido, Daiki, Fukuda, Tomohiro and Yabuki, Nobuyoshi
year	2019
title	Development of a Semantic Segmentation System for Dynamic Occlusion Handling in Mixed Reality for Landscape Simulation
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. 641-648
doi	https://doi.org/10.52842/conf.ecaade.2019.1.641
summary	The use of mixed reality (MR) for landscape simulation has attracted attention recently. MR can produce a realistic landscape simulation by merging a three-dimensional computer graphic (3DCG) model of a new building on a real space. One challenge with MR that remains to be tackled is occlusion. Properly handling occlusion is important for the understanding of the spatial relationship between physical and virtual objects. When the occlusion targets move or the target's shape changes, depth-based methods using a special camera have been applied for dynamic occlusion handling. However, these methods have a limitation of the distance to obtain depth information and are unsuitable for outdoor landscape simulation. This study focuses on a dynamic occlusion handling method for MR-based landscape simulation. We developed a real-time semantic segmentation system to perform dynamic occlusion handling. We designed this system for use in mobile devices with client-server communication for real-time semantic segmentation processing in mobile devices. Additionally, we used a normal monocular camera for practice use.
keywords	Mixed Reality; Dynamic occlusion handling; Semantic segmentation; Deep learning; Landscape simulation
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:52

_id	caadria2019_027
id	caadria2019_027
authors	Nandavar, Anirudh, Petzold, Frank, Schubert, Gerhard and Youssef, Elie
year	2019
title	Opening BIM in a New Dimension - A simple, OpenBIM standards based Virtual reality collaboration technique for BIM
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. 595-604
doi	https://doi.org/10.52842/conf.caadria.2019.1.595
summary	This work explores the possibility of leveraging the OpenBIM standards to create an interactive Virtual Reality (VR) tool for collaboration in the BIM ecosystem, independent of any vendor-specific software. The highlight of the work is integration of BCF issue mark-ups and a mechanism to add doors and windows from VR with correct semantic relationships to an IFC model. We also lay foundation for a networked, multi-user environment using the same approach.
keywords	IFC; VR; BIM; Interactive; OpenBIM
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	caadria2019_413
id	caadria2019_413
authors	Ahrens, Chandler, Chamberlain, Roger, Mitchell, Scott, Barnstorff, Adam and Gelbard, Joshua
year	2019
title	Controlling Daylight Reflectance with Cyber-physical Systems
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. 433-442
doi	https://doi.org/10.52842/conf.caadria.2019.1.433
summary	Cyber-physical systems increasingly inform and alter the perception of atmospheric conditions within interior environments. The Catoptric Surface research project uses computation and robotics to precisely control the location of reflected daylight through a building envelope to form an image-based pattern of light on the building interior's surfaces. In an attempt to amplify or reduce spatial perception, the daylighting reflected onto architectural surfaces within a built environment generates atmospheric effects. The modification of light patterns mapped onto existing or new surfaces enables the perception of space to not rely on form alone. The mapping of a new pattern that is independent of architectural surfaces creates a visual effect of a formless atmosphere and holds the potential to affect the way people interact with the space. People need different amounts and quality of daylight depending on physiological differences due to age or the types of tasks they perform. This research argues for an informed luminous and atmospheric environment that is relative both to the user and more conceptual architectural aspirations of spatial perception controlled by a cyber-physical robotic faÃ§ade system.
keywords	Contextual; Computation
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	ecaadesigradi2019_605
id	ecaadesigradi2019_605
authors	Andrade Zandavali, Bárbara and Jiménez García, Manuel
year	2019
title	Automated Brick Pattern Generator for Robotic Assembly using Machine Learning and Images
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. 217-226
doi	https://doi.org/10.52842/conf.ecaade.2019.3.217
summary	Brickwork is the oldest construction method still in use. Digital technologies, in turn, enabled new methods of representation and automation for bricklaying. While automation explored different approaches, representation was limited to declarative methods, as parametric filling algorithms. Alternatively, this work proposes a framework for automated brickwork using a machine learning model based on image-to-image translation (Conditional Generative Adversarial Networks). The framework consists of creating a dataset, training a model for each bond, and converting the output images into vectorial data for robotic assembly. Criteria such as: reaching wall boundary accuracy, avoidance of unsupported bricks, and brick's position accuracy were individually evaluated for each bond. The results demonstrate that the proposed framework fulfils boundary filling and respects overall bonding structural rules. Size accuracy demonstrated inferior performance for the scale tested. The association of this method with 'self-calibrating' robots could overcome this problem and be easily implemented for on-site.
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:54

_id	lasg_whitepapers_2019_089
id	lasg_whitepapers_2019_089
authors	Byrne, Daragh; and Dana Cupkova
year	2019
title	Towards Psychosomatic Architecture; Attuning Reactive Architectural Materials through Biofeedback
source	Living Architecture Systems Group White Papers 2019 [ISBN 978-1-988366-18-0] Riverside Architectural Press: Toronto, Canada 2019. pp.089 - 100
summary	The built environment is known to affect human health and wellbeing. Yet, architecture does not respond to our bodies or our minds. It tends to be static, ignoring the human occupant, their mood, behaviors, and emotions. There is evidence that this monotony of average space is harmful to human health. Additionally, differences in gender, race and cultural conditions vary the perception of and preferences for temperature and color. To improve the psychosomatic relationship with architectural spaces, there arises the necessity for it to have a greater range of spatial reactivity and better support for personalized thermoregulation and aesthetics. This paper proposes an architecture that operates like a mood-ring, one that creates rich feedback between architecture and occupant towards individualized reactivity and expression. [Sentient Concrete] ([Image 1]) is a prototype of a thermochromically treated concrete panel that is thermally actuated by embedded electromechanical systems and can dynamically produce localized thermally reactive responses. It serves as a test case for outlining further research agendas and possible design frameworks for psychosomatic architecture.
keywords	living architecture systems group, organicism, intelligent systems, design methods, engineering and art, new media art, interactive art, dissipative systems, technology, cognition, responsiveness, biomaterials, artificial natures, 4DSOUND, materials, virtual projections,
email
last changed	2019/07/29 14:02

_id	ecaadesigradi2019_339
id	ecaadesigradi2019_339
authors	Kinugawa, Hina and Takizawa, Atsushi
year	2019
title	Deep Learning Model for Predicting Preference of Space by Estimating the Depth Information of Space using Omnidirectional Images
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. 61-68
doi	https://doi.org/10.52842/conf.ecaade.2019.2.061
summary	In this study, we developed a method for generating omnidirectional depth images from corresponding omnidirectional RGB images of streetscapes by learning each pair of omnidirectional RGB and depth images created by computer graphics using pix2pix. Then, the models trained with different series of images shot under different site and weather conditions were applied to Google street view images to generate depth images. The validity of the generated depth images was then evaluated visually. In addition, we conducted experiments to evaluate Google street view images using multiple participants. We constructed a model that estimates the evaluation value of these images with and without the depth images using the learning-to-rank method with deep convolutional neural network. The results demonstrate the extent to which the generalization performance of the streetscape evaluation model changes depending on the presence or absence of depth images.
keywords	Omnidirectional image; depth image; Unity; Google street view; pix2pix; RankNet
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:52

_id	ijac201917104
id	ijac201917104
authors	Matthews, Linda and Gavin Perin
year	2019
title	Exploiting ambiguity: The diffraction artefact and the architectural surface
source	International Journal of Architectural Computing vol. 17 - no. 1, 103-115
summary	In the contemporary ‘envisioned’ environment, Internet webcams, low- and high-altitude unmanned aerial vehicles and satellites are the new vantage points from which to construct the image of the city. Armed with hi-resolution digital optical technologies, these vantage points effectively constitute a ubiquitous visioning apparatus serving either the politics of promotion or surveillance. Given the political dimensions of this apparatus, it is important to note that this digital imaging of public urban space refers to the human visual system model. In order to mimic human vision, a set of algorithm patterns are used to direct numerous ‘soft’ and ‘hard’ technologies. Mimicry thus has a cost because this insistence on the human visual system model necessitates multiple transformative moments in the production and transmission pipeline. If each transformative moment opens a potential vulnerability within the visioning apparatus, then every glitch testifies to the artificiality of the image. Moreover, every glitch potentially interrupts the political narratives be communicated in contemporary image production and transmission. Paradoxically, the current use of scripting to create glitch-like images has reimagined glitches as a discrete aesthetic category. This article counters this aestheticisation by asserting glitching as a disruption in communication. The argument will rely on scaled tests produced by one of the authors who show how duplicating the digital algorithmic patterns used within the digital imaging pipeline on any exterior building surface glitches the visual data captured within that image. Referencing image-based techniques drawn from the Baroque and contemporary modes of camouflage, it will be argued that the visual aberrations created by these algorithm-based patterned facades can modify strategically the ‘emission signature’ of selected parts of the urban fabric. In this way, the glitch becomes a way to intercede in the digital portrayal of city.
keywords	Surveillance, algorithms, diffraction, pattern, disruptive, optics
series	journal
email
last changed	2019/08/07 14:04

_id	caadria2019_126
id	caadria2019_126
authors	Ng, Jennifer Mei Yee, Khean, Nariddh, Madden, David, Fabbri, Alessandra, Gardner, Nicole, Haeusler, M. Hank and Zavoleas, Yannis
year	2019
title	Optimising Image Classification - Implementation of Convolutional Neural Network Algorithms to Distinguish Between Plans and Sections within the Architectural, Engineering and Construction (AEC) Industry
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. 795-804
doi	https://doi.org/10.52842/conf.caadria.2019.2.795
summary	Modern communication between built environment professionals are governed by the effective exchange of digital models, blueprints and technical drawings. However, the increasing quantity of such digital files, in conjunction with inconsistent filing systems, increases the potential for human-error upon their look-up and retrieval. Further, current methods are manual, thus slow and resource intensive. Evidently, the architectural, engineering and construction (AEC) industry lacks an automated classification system capable of systematically identifying and categorising different drawings. To intercede, we aim to investigate artificially intelligent solutions capable of automatically identifying and retrieving a wide set of AEC files from a company's resource library. We present a convolutional neural network (CNN) model capable of processing large sets of technical drawings - such as sections, plans and elevations - and recognise their individual patterns and features, ultimately minimising laboriousness.
keywords	Convolutional Neural Network; Artificial Intelligence; Machine Learning; Classification; Filing architectural drawings.
series	CAADRIA
email
last changed	2022/06/07 07:58

_id	caadria2020_259
id	caadria2020_259
authors	Rhee, Jinmo, Veloso, Pedro and Krishnamurti, Ramesh
year	2020
title	Integrating building footprint prediction and building massing - an experiment in Pittsburgh
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 669-678
doi	https://doi.org/10.52842/conf.caadria.2020.2.669
summary	We present a novel method for generating building geometry using deep learning techniques based on contextual geometry in urban context and explore its potential to support building massing. For contextual geometry, we opted to investigate the building footprint, a main interface between urban and architectural forms. For training, we collected GIS data of building footprints and geometries of parcels from Pittsburgh and created a large dataset of Diagrammatic Image Dataset (DID). We employed a modified version of a VGG neural network to model the relationship between (c) a diagrammatic image of a building parcel and context without the footprint, and (q) a quadrilateral representing the original footprint. The option for simple geometrical output enables direct integration with custom design workflows because it obviates image processing and increases training speed. After training the neural network with a curated dataset, we explore a generative workflow for building massing that integrates contextual and programmatic data. As trained model can suggest a contextual boundary for a new site, we used Massigner (Rhee and Chung 2019) to recommend massing alternatives based on the subtraction of voids inside the contextual boundary that satisfy design constraints and programmatic requirements. This new method suggests the potential that learning-based method can be an alternative of rule-based design methods to grasp the complex relationships between design elements.
keywords	Deep Learning; Prediction; Building Footprint; Massing; Generative Design
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	ecaadesigradi2019_630
id	ecaadesigradi2019_630
authors	Saad, Carla
year	2019
title	If Only Wood Could Speak... - Explorations in digital fabrication processes based on timber grain and patterns
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. 227-234
doi	https://doi.org/10.52842/conf.ecaade.2019.3.227
summary	This paper presents an exploration following wood patterns applied to traditional woodworking techniques such as steam bending and carving. It builds on a digital fabrication process where the patterns that are unique to each wood strip and which constitutes their structural geometry are also used within fabrication processes and applied machinery such as the zund machine. The experiments were done in two series where the earlier set focuses on routing along the wood patterns of thin wood strips and steam bending the different pieces. The second set experimented with carving thick wood strips on passes generated from the extracted patterns. An automated technique based in computer vision and specifically OpenCV was developed using different filters in order to extract the patterns and transfer the results into CAD software where the lines where further manipulated for variable exploration. The results of this study led to a better understanding of wood patterns from a geometrical perspective thus enriching the aesthetic composition of a design while being authentic to the unique nature of each piece of wood.
keywords	Timber; pattern recognition; grain; image; carving ; digital fabrication
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:56

_id	acadia19_392
id	acadia19_392
authors	Steinfeld, Kyle
year	2019
title	GAN Loci
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. 392-403
doi	https://doi.org/10.52842/conf.acadia.2019.392
summary	This project applies techniques in machine learning, specifically generative adversarial networks (or GANs), to produce synthetic images intended to capture the predominant visual properties of urban places. We propose that imaging cities in this manner represents the first computational approach to documenting the Genius Loci of a city (Norberg-Schulz, 1980), which is understood to include those forms, textures, colors, and qualities of light that exemplify a particular urban location and that set it apart from similar places. Presented here are methods for the collection of urban image data, for the necessary processing and formatting of this data, and for the training of two known computational statistical models (StyleGAN (Karras et al., 2018) and Pix2Pix (Isola et al., 2016)) that identify visual patterns distinct to a given site and that reproduce these patterns to generate new images. These methods have been applied to image nine distinct urban contexts across six cities in the US and Europe, the results of which are presented here. While the product of this work is not a tool for the design of cities or building forms, but rather a method for the synthetic imaging of existing places, we nevertheless seek to situate the work in terms of computer-assisted design (CAD). In this regard, the project is demonstrative of a new approach to CAD tools. In contrast with existing tools that seek to capture the explicit intention of their user (Aish, Glynn, Sheil 2017), in applying computational statistical methods to the production of images that speak to the implicit qualities that constitute a place, this project demonstrates the unique advantages offered by such methods in capturing and expressing the tacit.
series	ACADIA
type	normal paper
email
last changed	2022/06/07 07:56

_id	acadia19_564
id	acadia19_564
authors	Chai, Hua; Marino, Dario; So, ChunPong; Yuan, Philip F.
year	2019
title	Design for Mass-Customization
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. 564-572
doi	https://doi.org/10.52842/conf.acadia.2019.564
summary	Tradition wood tectonics, like interlocking joints, have regained focus against the background of digital design and fabrication technologies. While research on interlocking joints is quite focused on joint geometries, especially for timber plates, there has been less attention on the design and mass customization of interlocking joints for linear timber elements. In this context, this research addresses the challenges of mass customization of interlocking joints for linear elements through the design and realization of a 9-meterhigh timber structure with fully interlocking joints, without the use of any nails or glue. A customized code generation program was developed for the fabrication process, allowing the rapid programming and fabrication for all the 840 elements and 2592 notches. The project demonstrates how innovative structures are allowed through the synthesis of joint geometry, assembly process, and cutting-edge fabrication technology.
series	ACADIA
type	normal paper
email
last changed	2022/06/07 07:55

_id	cf2019_050
id	cf2019_050
authors	Erdine, Elif ; Giulio Gianni, Angel Fernando Lara Moreira, Alvaro Lopez Rodriguez, Yutao Song and Alican Sungur
year	2019
title	Robot-Aided Fabrication of Light-Weight Structures with Sheet Metal Expansion
source	Ji-Hyun Lee (Eds.) "Hello, Culture!" [18th International Conference, CAAD Futures 2019, Proceedings / ISBN 978-89-89453-05-5] Daejeon, Korea, p. 433
summary	This paper presents a novel approach for the creation of metal lightweight self-supporting structures through the employment of metal kerfing and robotic sheet panel expansion. Research objectives focus on the synthesis of material behavior on a local scale and the structural performance on a global scale via advanced computational and robotic methods. There are inherent structural properties to expanded metal sheets which can be employed to achieve an integrated building system without the need for a secondary supporting structure. A computational workflow that integrates Finite Element Analysis, geometrical optimization, and robotic toolpath planning has been developed. This workflow is informed by the parameters of material experimentation on sheet metal kerfing and robotic sheet metal expansion on the local panel scale. The proposed methodology is applied on a range of panels with a custom-built robotic fabrication setup for the design, fabrication, and assembly of a one-to-one scale working prototype.
keywords	Robotic fabrication, Robotic sheet metal expansion, Light-weight structure, Metal kerfing, Metal expansion
series	CAAD Futures
email
last changed	2019/07/29 14:18

_id	caadria2019_054
id	caadria2019_054
authors	Hofmeyer, HÃ¨rm, Claessens, Dennis, Boonstra, Sjonnie and de Vries, Bauke
year	2019
title	Effects of 3D Zoning of Spatial Designs on the Performance of Structure Systems
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. 205-214
doi	https://doi.org/10.52842/conf.caadria.2019.1.205
summary	A particular application for informed building design concerns the intelligent synthesis of a structure system for a conceptual spatial design. As part of this synthesis, the positioning of structural elements is normally related to the surfaces of the spaces that form the spatial design. It is shown that if surfaces of zones are taken instead, with a zone being a group of complete or possibly incomplete spaces, structural performance of the space-based systems may be Pareto dominated by the zone-based systems. This indicates that zones are a useful concept to improve structural performance. Also, the variety of zoned designs for a single spatial design delivers, together with a single structural grammar, many variants for a structure system.
keywords	Zoning; Structural Grammar; Structure System
series	CAADRIA
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last changed	2022/06/07 07:50

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