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 caadria2020_395
id caadria2020_395
authors Loo, Stella Yi Ning, Jayashankar, Dhileep Kumar, Gupta, Sachin and Tracy, Kenneth
year 2020
title Hygro-Compliant: Responsive Architecture with Passively Actuated Compliant Mechanisms
doi https://doi.org/10.52842/conf.caadria.2020.1.223
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. 223-232
summary Research investigating water-driven passive actuation demonstrates the potential to transform how buildings interact with their environment while avoiding the complications of conventionally powered actuation. Previous experiments evidence the possibilities of bi-layer materials (Reichert, Menges, and Correa 2015; Correa et al. 2015) and mechanical assemblies with discretely connected actuating members (Gupta et al. 2019). By leveraging changes in weather to power actuated building components these projects explore the use of smart biomaterials and responsive building systems. Though promising the implementation of these technologies requires deep engagement into material synthesis and fabrication. This paper presents the design and prototyping of a rain responsive façade system using chitosan hygroscopic films as actuators counterbalanced by programmed compliant mechanisms. Building on previous work into chitosan film assemblies this research focuses on the development of compliant mechanisms as a means of controlling movement without over-complicated rotating parts.
keywords Passive Actuation; Responsive Architecture; Bio-polymers; 4D Structures; Compliant Mechanism
series CAADRIA
email
last changed 2022/06/07 07:52

_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 acadia21_340
id acadia21_340
authors Zhang, Yu; Tatarintseva, Liz; Clewlow, Tom; Clark, Ed; Botsford, Gianni; Shea, Kristina
year 2021
title Mortarless Compressed Earth Block Dwellings
doi https://doi.org/10.52842/conf.acadia.2021.340
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. 340-345.
summary This project develops a template design and an adaptive fabrication process for sustainable Compressed Earth Block (CEB) dwellings for low-income countries. Most existing projects (Wilton et al. 2019; WASP 2021) on sustainable dwellings involve high-tech equipment or skilled workers on-site. This project integrates digital technologies into the design and fabrication processes to reduce these requirements and make the design compatible with conventional construction methods that are actively adopted in low-income countries using minimum infrastructure, skilled labor, and investment.
series ACADIA
type project
email
last changed 2023/10/22 12:06

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