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_415
id	caadria2021_415
authors	Chuang, Cheng-Lin and Chien, Sheng-Fen
year	2021
title	Facilitating Architect-Client Communication in the Pre-design Phase
doi	https://doi.org/10.52842/conf.caadria.2021.2.071
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. 71-80
summary	The process of architects exploring the program with clients often take place through face-to-face oral discussions and visual aids, such as photos and sketches. Our research focuses on two communication mediums: language and sketch. We employ machine learning techniques to assist architects and clients to improve their communication and reduce misunderstandings. We have trained a Naive Bayesian Classifier machine, the language assistant (LA), to classify architectural vocabularies with associations to design requirements. In addition, we have trained a Generative Adversarial Network, the sketch assistant (SA), to generate photo quality images based on architects' sketches. The language assistant and sketch assistant combined can facilitate architect-client communication during the pre-design stage.
keywords	Architect-Client Communication; Pre-design; Architectural Programming; Machine Learning; Schematic Design
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	cdrf2021_275
id	cdrf2021_275
authors	E. Özdemir, L. Kiesewetter, K. Antorveza, T. Cheng, S. Leder, D. Wood, and A. Menges
year	2021
title	Towards Self-shaping Metamaterial Shells: A Computational Design Workflow for Hybrid Additive Manufacturing of Architectural Scale Double-Curved Structures
doi	https://doi.org/https://doi.org/10.1007/978-981-16-5983-6_26
source	Proceedings of the 2021 DigitalFUTURES The 3rd International Conference on Computational Design and Robotic Fabrication (CDRF 2021)
summary	Double curvature enables elegant and material-efficient shell structures, but their construction typically relies on heavy machining, manual labor, and the additional use of material wasted as one-off formwork. Using a material’s intrinsic properties for self-shaping is an energy and resource-efficient solution to this problem. This research presents a fabrication approach for self-shaping double-curved shell structures combining the hygroscopic shape-changing and scalability of wood actuators with the tunability of 3D-printed metamaterial patterning. Using hybrid robotic fabrication, components are additively manufactured flat and self-shape to a pre-programmed configuration through drying. A computational design workflow including a lattice and shell-based finite element model was developed for the design of the metamaterial pattern, actuator layout, and shape prediction. The workflow was tested through physical prototypes at centimeter and meter scales. The results show an architectural scale proof of concept for self-shaping double-curved shell structures as a resource-efficient physical form generation method.
series	cdrf
email
last changed	2022/09/29 07:53

_id	cdrf2021_129
id	cdrf2021_129
authors	Fuyuan Liu, Min Chen, Lizhe Wang, Xiang Wang, and Cheng-Hung Lo
year	2021
title	Custom-Fit and Lightweight Optimization Design of Exoskeletons Using Parametric Conformal Lattice
doi	https://doi.org/https://doi.org/10.1007/978-981-16-5983-6_12
source	Proceedings of the 2021 DigitalFUTURES The 3rd International Conference on Computational Design and Robotic Fabrication (CDRF 2021)
summary	This paper presents an integrated design method for the customization and lightweight design of free-shaped wearable devices, illustrated by a lower limb exoskeleton. The customized design space is derived from the 3D scanning models. Based on the finite element analysis, the structural framework is determined through topology optimization with allowable strength. By means of generative design, the lattice library is constructed to fill the frames under different conformal algorithms. Finally, the proposed method is illustrated by the exoskeleton design case.
series	cdrf
email
last changed	2022/09/29 07:53

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