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	caadria2022_208
id	caadria2022_208
authors	Bielski, Jessica, Langenhan, Christoph, Ziegler, Christoph, Eisenstadt, Viktor, Petzold, Frank, Dengel, Andreas and Althoff, Klaus-Dieter
year	2022
title	The What, Why, What-If and How-To for Designing Architecture, Explainability for Auto-Completion of Computer-Aided Architectural Design of Floor Plan Layouting During the Early Design Stages
doi	https://doi.org/10.52842/conf.caadria.2022.2.435
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 435-444
summary	In the next thirty years, the world's population is expected to increase to ten billion people, posing major challenges for the construction industry. To meet the growing demands for residential housing in the future, architects need to work faster, more efficiently, and more sustainably, while increasing architectural quality. The hypothetical intelligent design assistant WHITE BRIDGE, based on the methods of the 'metis' projects, suggests further design steps to support the architectural design decision-making processes of the early design phases. This facilitates faster and better decisions early in the process for a more responsible resource consumption, better mental well-being, and ultimately economic growth. Through a case study we investigate if additional information supports the understanding of these suggestions to reduce the cognitive workload of architectural design decisions on the backdrop of their respective representation. The paper contributes an approach for visualising explanations of an intelligent design assistant, their integration into paper prototypes for case studies, and a workflow for data collection and analysis. The results suggest that the cognitive horizon of the architects is broadened by the explanations, while the visualisation methods significantly influence the usefulness and use of the conveyed information within the explanations.
keywords	Explainability, Artificial intelligence, XAI, SDG 3, SDG 8, SDG 12
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	ijac202220101
id	ijac202220101
authors	Bao, Ding Wen; Xin Yan, Yi Min Xie
year	2022
title	Encoding topological optimisation logical structure rules into multi-agent system for architectural design and robotic fabrication
source	International Journal of Architectural Computing 2022, Vol. 20 - no. 1, pp. 7–17
summary	Natural phenomena have been explored as a source of architectural and structural design inspiration with different approaches undertaken within architecture and engineering. The research proposes a connection between two dichotomous principles: architectural complexity and structural efficiency through a hybrid of natural phenomena, topology optimisation and generative design. Both Bi-directional Evolutionary Structural Optimisation (BESO) and multi-agent algorithms are emerging technologies developed into new approaches that transform architectural and structural design, respectively, from the logic of topology optimisation and swarm intelligence. This research aims to explore a structural behaviour feedback loop in designing intricate functional forms through encoding BESO logical structure rules into the multi-agent algorithm. This research intends to study and evaluate the application of topology optimisation and multi-agent system in form-finding and later robotic fabrication through a series of prototypes. It reveals a supposition that the structural behaviour-based design method matches the beauty and function of natural appearance and structure. Thus, a new exploration of architectural design and fabrication strategy is introduced, which benefits the collab- oration among architects, engineers and manufacturers. There is the potential to seek the ornamental complexities in architectural forms and the most efficient use of material based on structural performance in the process of generating complex geometry of the building and its various elements.
keywords	Swarm intelligence, multi-agent, bi-directional evolutionary structural optimisation (BESO), intricate architectural form, efficient structure
series	journal
last changed	2024/04/17 14:29

_id	caadria2022_507
id	caadria2022_507
authors	Bolojan, Daniel, Vermisso, Emmanouil and Yousif, Shermeen
year	2022
title	Is Language All We Need? A Query Into Architectural Semantics Using a Multimodal Generative Workflow
doi	https://doi.org/10.52842/conf.caadria.2022.1.353
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 353-362
summary	This project examines how interconnected artificial intelligence (AI)-assisted workflows can address the limitations of current language-based models and streamline machine-vision related tasks for architectural design. A precise relationship between text and visual feature representation is problematic and can lead to "ambiguity‚ in the interpretation of the morphological/tectonic complexity of a building. Textual representation of a design concept only addresses spatial complexity in a reductionist way, since the outcome of the design process is co-dependent on multiple interrelated systems, according to systems theory (Alexander 1968). We propose herewith a process of feature disentanglement (using low level features, i.e., composition) within an interconnected generative adversarial networks (GANs) workflow. The insertion of natural language models within the proposed workflow can help mitigate the semantic distance between different domains and guide the encoding of semantic information throughout a domain transfer process.
keywords	Neural Language Models, GAN, Domain Transfer, Design Agency, Semantic Encoding, SDG 9
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	ecaade2022_136
id	ecaade2022_136
authors	Hong, Soon-min, Kim, Dong-wuk, Gu, Hyeong-mo and Choo, Seung-yeon
year	2022
title	Establishment of Database for Automated Building Codes Compliance Checking in the Pre-Design Phase
doi	https://doi.org/10.52842/conf.ecaade.2022.2.329
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 2, Ghent, 13-16 September 2022, pp. 329–338
summary	The ICT’s development has led to the introduction of work automation technology into the AEC industry, and many governments around the world have attempted to increase work efficiency by introducing the automation technology for building legality review into the building administrative system. Prior to this, it is essential to develop a database of which natural language-based building codes should be modified in code. Thus, this study addresses a method to convent building acts in the form of natural language into computer-readable one through formalization and encoding and to establish database with the aim of developing the automation technology for legality review for setting size used in pre-design phase. The method suggested is verified through the developed authoring tool.
keywords	Automated Checking, Building Codes Compliance, Mass Generation
series	eCAADe
email
last changed	2024/04/22 07:10

_id	acadia22_628
id	acadia22_628
authors	Sung, Woongki; Nagakura, Takehiko; Tsai, Daniel
year	2022
title	Design Contextualism by AI
source	ACADIA 2022: Hybrids and Haecceities [Proceedings of the 42nd Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-8-1]. University of Pennsylvania Stuart Weitzman School of Design. 27-29 October 2022. edited by M. Akbarzadeh, D. Aviv, H. Jamelle, and R. Stuart-Smith. 628-637.
summary	This paper presents a data- driven method for encoding and representing the statistical information of an architectural site layout in the form of a Bayesian network. Given a set of simplified satellite photos and maps, the site layout model is formulated that consists of variables of interest. Structured learning is performed to find an optimal Bayesian network structure that best fits the dataset and is then trained to calculate its parameters.
series	ACADIA
type	paper
email
last changed	2024/02/06 14:04

_id	cdrf2022_371
id	cdrf2022_371
authors	Viktória Sándor, Mathias Bank, Kristina Schinegger, and Stefan Rutzinger
year	2022
title	Collapsing Complexities: Encoding Multidimensional Architecture Models into Images
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_32
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
summary	The paper details a 3D to 2D encoding method, which can store complex digital 3D models of architecture within a single image. The proposed encoding works in combination with a point cloud notation and a sequential slicing operation where each slice of points is stored as a single row of pixels in the UV space of a 1024?×?1024 image. The performance of the notation system is compared between a StyleGan2 and existing image editing methods and evaluated through the production of new 3D models of houses with material attributes. The uncovered findings maintain the relatively high level of detail stored through the encoding while allowing for innovative ways of form-finding—producing new and unseen 3d models of architectural houses.
series	cdrf
email
last changed	2024/05/29 14:03

_id	caadria2022_435
id	caadria2022_435
authors	Stieler, David, Schwinn, Tobias and Menges, Achim
year	2022
title	Additive Formwork in Precast Construction - Agent-based Methods for Fabrication-aware Modularization of Concrete Building Elements
doi	https://doi.org/10.52842/conf.caadria.2022.2.081
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 81-90
summary	This paper presents the geometric foundations for an agent-based modeling (ABM) approach to modularize concrete building elements for prefabrication via additive formwork. The method presented extends the functionality of existing planning tools for concrete prefabrication to addresses the manufacturing characteristics of additive formwork production using fused deposition modeling (FDM), and negotiates these with the structural requirements of its underlying building geometry. First, a method to classify building components according to fabrication methods using a probabilistic feature-based Naive Bayes classifier is presented. This classification allows to automatically assign the most suitable production method to every individual building element within a given building model. Following this class0864108000ification, elements identified for the production using additive formwork are modularized in an automated, agent-based process. The modularization process utilizing a voxel-representation of the initial building element geometry is described in detail. An agent-based method to simulate multiple modularization variants is presented and the integration of feedback from iterative negotiation processes between fabrication expenditures and structural behaviour outlined. The approach presented fosters material-saving construction and production processes in planning and therefore directly addresses crucial issues of the agenda for global Sustainable Development Goals (SDGs).
keywords	agent-based modeling, modularization, prefabrication, ABM, volumetric modeling, additive formwork, SDG 9, SDG 12
series	CAADRIA
email
last changed	2022/07/22 07:34

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