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 369

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

_id	ecaade2018_164
id	ecaade2018_164
authors	Chang, Mei-Chih, Buš, Peter, Tartar, Ayça, Chirkin, Artem and Schmitt, Gerhard
year	2018
title	Big-Data Informed Citizen Participatory Urban Identity Design
doi	https://doi.org/10.52842/conf.ecaade.2018.2.669
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 2, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 669-678
summary	The identity of an urban environment is important because it contributes to self-identity, a sense of community, and a sense of place. However, under present-day conditions, the identities of expanding cities are rapidly deteriorating and vanishing, especially in the case of Asian cities. Therefore, cities need to build their urban identity, which includes the past and points to the future. At the same time, cities need to add new features to improve their livability, sustainability, and resilience. In this paper, using data mining technologies for various types of geo-referenced big data and combine them with the space syntax analysis for observing and learning about the socioeconomic behavior and the quality of space. The observed and learned features are identified as the urban identity. The numeric features obtained from data mining are transformed into catalogued levels for designers to understand, which will allow them to propose proper designs that will complement or improve the local traditional features. A workshop in Taiwan, which focuses on a traditional area, demonstrates the result of the proposed methodology and how to transform a traditional area into a livable area. At the same time, we introduce a website platform, Quick Urban Analysis Kit (qua-kit), as a tool for citizens to participate in designs. After the workshop, citizens can view, comment, and vote on different design proposals to provide city authorities and stakeholders with their ideas in a more convenient and responsive way. Therefore, the citizens may deliver their opinions, knowledge, and suggestions for improvements to the investigated neighborhood from their own design perspective.
keywords	Urban identity; unsupervised machine learning; Principal Component Analysis (PCA); citizen participated design; space syntax
series	eCAADe
email
last changed	2022/06/07 07:56

_id	caadria2018_316
id	caadria2018_316
authors	Yan, Chao, Zhang, Yunyu, Yuan, Philip F. and Yao, Jiawei
year	2018
title	Virtual Motion - Shifting Perspective as an Instrument for Geometrical Construction
doi	https://doi.org/10.52842/conf.caadria.2018.2.471
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 471-480
summary	From the invention of projection to the emergence of digital technology, there's a clear correspondences among the transformations of visual representation paradigm in art, the developments of design instrument in architecture, and the human perception of time/space. Base on the examination of this particular historical trajectory, this paper focuses the working mechanism of shifting perspective as an alternative design instrument to explore the possibility of embedding time and motion into static form in digital age. Firstly, the paper reviews how the shifting perspective was introduced to represent space in modern western painting and photography. Then based on the research on shifting perspective, the paper develops a design tool, which would be able to translate motion into the particular geometrical feature of a generated 3D object. In the end, the paper brings further discussions about the formal and spatial effects brought by this new tool, and its potential to incorporate the perceptive image of human being into design process.
keywords	Shape Study; Projective Geometry; Shifting Perspective; Motion; Time Dimension
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	ijac201816406
id	ijac201816406
authors	As, Imdat; Siddharth Pal and Prithwish Basu
year	2018
title	Artificial intelligence in architecture: Generating conceptual design via deep learning
source	International Journal of Architectural Computing vol. 16 - no. 4, 306-327
summary	Artificial intelligence, and in particular machine learning, is a fast-emerging field. Research on artificial intelligence focuses mainly on image-, text- and voice-based applications, leading to breakthrough developments in self-driving cars, voice recognition algorithms and recommendation systems. In this article, we present the research of an alternative graph- based machine learning system that deals with three-dimensional space, which is more structured and combinatorial than images, text or voice. Specifically, we present a function-driven deep learning approach to generate conceptual design. We trained and used deep neural networks to evaluate existing designs encoded as graphs, extract significant building blocks as subgraphs and merge them into new compositions. Finally, we explored the application of generative adversarial networks to generate entirely new and unique designs.
keywords	Architectural design, conceptual design, deep learning, artificial intelligence, generative design
series	journal
email
last changed	2019/08/07 14:04

_id	ecaadesigradi2019_425
id	ecaadesigradi2019_425
authors	Betti, Giovanni, Aziz, Saqib and Ron, Gili
year	2019
title	Pop Up Factory : Collaborative Design in Mixed Rality - Interactive live installation for the makeCity festival, 2018 Berlin
doi	https://doi.org/10.52842/conf.ecaade.2019.3.115
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. 115-124
summary	This paper examines a novel, integrated and collaborative approach to design and fabrication, enabled through Mixed Reality. In a bespoke fabrication process, the design is controlled and altered by users in holographic space, through a custom, multi-modal interface. Users input is live-streamed and channeled to 3D modelling environment,on-demand robotic fabrication and AR-guided assembly. The Holographic Interface is aimed at promoting man-machine collaboration. A bespoke pipeline translates hand gestures and audio into CAD and numeric fabrication. This enables non-professional participants engage with a plethora of novel technology. The feasibility of Mixed Reality for architectural workflow was tested through an interactive installation for the makeCity Berlin 2018 festival. Participants experienced with on-demand design, fabrication an AR-guided assembly. This article will discuss the technical measures taken as well as the potential in using Holographic Interfaces for collaborative design and on-site fabrication.Please write your abstract here by clicking this paragraph.
keywords	Holographic Interface; Augmented Reality; Multimodal Interface; Collaborative Design; Robotic Fabrication; On-Site Fabrication
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:52

_id	ecaade2018_268
id	ecaade2018_268
authors	Cheang, Jeremy Jenn Ren and Loh, Paul
year	2018
title	FOAM - Custom Single Task Construction Robot
doi	https://doi.org/10.52842/conf.ecaade.2018.1.157
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 157-164
summary	This paper discusses the design and fabrication of a novel in-situ fabrication system for building cladding envelope. The construction industry has utilised automation in onsite construction for many decades. This research examines how through the automation process, different construction techniques can be combined to generate a new system that is both performance and design lead. Through abstracting generative effects through the design process, the results are feedback into the fabrication process to construct a more meaningful dialogue between form, material and fabrication procedure. Using electronic prototyping, the researchers tested the system through large-scale prototypes. The paper concludes by discussing the interaction between material and design. We examine how this is evident in the machine workflow. The article addresses the theme of the conference through examining a revision of tool in design that embodied research knowledge for a more sustainable environment.
keywords	Digital Fabrication, Design workflow, Automation
series	eCAADe
email
last changed	2022/06/07 07:55

_id	caadria2018_056
id	caadria2018_056
authors	Chirkin, Artem, Pishniy, Maxim and Sender, Arina
year	2018
title	Generilized Visibility-Based Design Evaluation Using GPU
doi	https://doi.org/10.52842/conf.caadria.2018.2.483
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 483-492
summary	Visibility plays an important role in perception and use of an urban design, and thus often becomes a target of design analysis. This work presents a fast method of evaluating various visibility-based design characteristics, such as isovists or insolation exploiting the GPU rendering pipeline and compute shaders. The proposed method employs a two-stage algorithm on each point of interest. First, it projects the visible space around a vantage point onto an equirectangular map. Second, it folds the map using a flexibly defined function into a single value that is associated with the vantage point. Being executed on a grid of points in a 3D scene, it can be visualized as a heat map or utilized by another algorithm for further design analysis. The developed system provides nearly real-time analysis tools for an early-stage design process to a broad audience via web services.
keywords	design analysis; design evaluation; GPU; isovist; insolation
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	ecaade2018_301
id	ecaade2018_301
authors	Cocho-Bermejo, Ana, Birgonul, Zeynep and Navarro-Mateu, Diego
year	2018
title	Adaptive & Morphogenetic City Research Laboratory
doi	https://doi.org/10.52842/conf.ecaade.2018.2.659
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 2, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 659-668
summary	"Smart City" business model is guiding the development of future metropolises. Software industry sales to town halls for city management services efficiency improvement are, these days, a very pro?table business. Being the model decided by the industry, it can develop into a dangerous situation in which the basis of the new city design methodologies is decided by agents outside academia expertise. Drawing on complex science, social physics, urban economics, transportation theory, regional science and urban geography, the Lab is dedicated to the systematic analysis of, and theoretical speculation on, the recently coined "Science of Cities" discipline. On the research agenda there are questions arising from the synthesis of architecture, urban design, computer science and sociology. Collaboration with citizens through inclusion and empowerment, and, relationships "City-Data-Planner-Citizen" and "Citizen-Design-Science", configure Lab's methodology provoking a dynamic responsive process of design that is yet missing on the path towards the real responsive city.
keywords	Smart City; Morphogenetic Urban Design; Internet of Things; Building Information Modelling; Evolutionary Algorithms; Machine Learning & Artificial Intelligence
series	eCAADe
email
last changed	2022/06/07 07:56

_id	acadia18_206
id	acadia18_206
authors	Farahi, Behnaz
year	2018
title	HEART OF THE MATTER: Affective Computing in Fashion and Architecture
doi	https://doi.org/10.52842/conf.acadia.2018.206
source	ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 206-215
summary	What if material interfaces could physically adapt to the user’s emotional state in order to develop a new affective interaction? By using emotional computing technologies to track facial expressions, material interfaces can help to regulate emotions. They can serve either as a tool for intelligence augmentation or as a means of leveraging an empathic relationship by developing an affective loop with the user. This paper explores how color- and shape-changing operations can be used as interactive design tools to convey emotional information, and is illustrated by two projects, one at the intimate scale of fashion and one at a more architectural scale. By engaging with design, art, psychology, and computer and material science, this paper envisions a world where material systems can detect the emotional responses of a user and reconfigure themselves in order to enter into a feedback loop with the user’s affective state and influence social interaction.
keywords	full paper, materials & adaptive systems, materials/adaptive systems, computation.
series	ACADIA
type	paper
email
last changed	2022/06/07 07:55

_id	caadria2018_052
id	caadria2018_052
authors	Fung, Enrica and Crolla, Kristof
year	2018
title	Choreographed Architecture - Body-Spatial Exploration
doi	https://doi.org/10.52842/conf.caadria.2018.1.101
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 1, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 101-110
summary	This paper presents a design-methodological case study that looks into the practical expansion of conventional conceptual architectural design media by incorporating contemporary technology of motion capture. It discusses challenges of integrating dance movement as a real-time input parameter for architectural design that aims at translating body motion into space. The paper consists of four parts, beginning with a historic background overview of scientists, physiologists, artists, choreographers, and architects who have attempted capturing body motion and turning the motion into space. The second part of the paper discusses the iterative development of the 'Dance Machine' as a methodological tool for the integration of motion capture into conceptual architectural design. Thirdly, the paper discusses tested design applications of the 'Dance Machine' by looking at two sited applications. Finally, the overall methodology is critically assessed and discussed in the light of continuous development of creative applications of motion capturing technology. The paper concludes by highlighting the architectural potential found in specific qualities of dance and by advocating for a broader palette of tools, techniques, and input methods for the conceptual design of architecture.
keywords	Choreographed architecture; Motion capture; Conceptual design media; Space design; Human body
series	CAADRIA
email
last changed	2022/06/07 07:50

_id	acadia18_156
id	acadia18_156
authors	Huang, Weixin; Zheng, Hao
year	2018
title	Architectural Drawings Recognition and Generation through Machine Learning
doi	https://doi.org/10.52842/conf.acadia.2018.156
source	ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 156-165
summary	With the development of information technology, the ideas of programming and mass calculation were introduced into the design field, resulting in the growth of computer- aided design. With the idea of designing by data, we began to manipulate data directly, and interpret data through design works. Machine Learning as a decision making tool has been widely used in many fields. It can be used to analyze large amounts of data and predict future changes. Generative Adversarial Network (GAN) is a model framework in machine learning. It’s specially designed to learn and generate output data with similar or identical characteristics. Pix2pixHD is a modified version of GAN that learns image data in pairs and generates new images based on the input. The author applied pix2pixHD in recognizing and generating architectural drawings, marking rooms with different colors and then generating apartment plans through two convolutional neural networks. Next, in order to understand how these networks work, the author analyzed their framework, and provided an explanation of the three working principles of the networks, convolution layer, residual network layer and deconvolution layer. Lastly, in order to visualize the networks in architectural drawings, the author derived data from different layer and different training epochs, and visualized the findings as gray scale images. It was found that the features of the architectural plan drawings have been gradually learned and stored as parameters in the networks. As the networks get deeper and the training epoch increases, the features in the graph become more concise and clearer. This phenomenon may be inspiring in understanding the designing behavior of humans.
keywords	full paper, design study, generative design, ai + machine learning, ai & machine learning
series	ACADIA
type	paper
email
last changed	2022/06/07 07:49

_id	caadria2018_044
id	caadria2018_044
authors	Inoue, Kazuya, Fukuda, Tomohiro, Cao, Rui and Yabuki, Nobuyoshi
year	2018
title	Tracking Robustness and Green View Index Estimation of Augmented and Diminished Reality for Environmental Design - PhotoAR+DR2017 project
doi	https://doi.org/10.52842/conf.caadria.2018.1.339
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 1, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 339-348
summary	To assess an environmental design, augmented and diminished reality (AR/DR) have a potential to build a consensus more smoothly through the landscape simulation of new design visualization of the items to be assessed, such as the green view index. However, the current system is still considered to be impractical because it does not provide complete user experience. Thus, we aim to improve the robustness of the AR/DR system and to integrate the estimation of the green view index into the AR/DR system on a game engine. Further, we achieve an improved stable tracking by eliminating the outliers of the tracking reference points using the random sample consensus (RANSAC) method and by defining the tracking reference points over an extensive area of the AR/DR display. Additionally, two modules were implemented, among which one module is used to solve the occlusion problem while the other is used to estimate the green view index. The novel integrated AR/DR system with all modules was developed on the game engine. A mock design project was developed in an outdoor environment for simulation purposes, thereby verifying the applicability of the developed system.
keywords	Environmental Design; Augmented Reality (AR); Diminished Reality (DR); Green View Index; Segmentation
series	CAADRIA
email
last changed	2022/06/07 07:50

_id	caadria2018_343
id	caadria2018_343
authors	Kalantar, Negar and Borhani, Alireza
year	2018
title	Informing Deformable Formworks - Parameterizing Deformation Behavior of a Non-Stretchable Membrane via Kerfing
doi	https://doi.org/10.52842/conf.caadria.2018.2.339
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 339-348
summary	The process for constructing freeform buildings composed of many non-repetitive shapes and waste-free formwork systems remains relatively unexplored. This research reviews a method for fabricating complex double-curved shapes without utilizing single-use formworks. This work answers questions regarding the manufacturing of these shapes in an environmentally-friendly and economic fashion. The proposed method, called a "transformative formwork," could replace state-of-the-art CNC-milled molds and is potentially suitable for large-scale construction. The transformative formwork uses a stretchable membrane or "interpolation layer" that can be manipulated into any curved surface by using vertical bars capable of being rearranged into different heights. Here, to accurately generate most of the smooth, double-curved surfaces, laser kerfing is used for bending interpolation layer into almost any complex shape. A parametric model simplifies local or global changes to the density of the kerfing patterns, modifying the deformation behavior of the layer. Several kerfed interpolation layers produced for four transformative formworks showed that the application of this method.
keywords	Transformative Formwork, Interpolation Layer, Relief-cut Patterns, Positive & Negative Gaussian Curvatures, Interlocking Archimedean Spiral-Patterns, Kerfing
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	acadia18_376
id	acadia18_376
authors	Kalantari, Saleh; Becker, Aaron T.; Ike, Rhema
year	2018
title	Designing for Digital Assembly with a Construction Team of Mobile Robots
doi	https://doi.org/10.52842/conf.acadia.2018.376
source	ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 376-385
summary	Advances in construction automation have primarily focused on creating heavy machines to accomplish repetitive tasks. While this approach is valuable in an assembly-line context, it does not always translate well for the diverse terrain and dynamic nature of construction sites. As a result, the use of automation in the architectural assembly has lagged far behind other industries. To address the challenges of construction-site assembly, this project suggests an alternative technique that uses a fl eet of smaller robots working in parallel. The proposed method, which is inspired by the construction techniques of insect colonies, has several advantages over the use of larger machines. It allows for much greater on-site fl exibility and portability. It is also easy to scale the operation, by adding or removing additional units as needed. The use of multiple small robots provides operational redundancy that can adapt to the loss of any particular machine. These advantages make the technology particularly suitable for construction in hazardous or inaccessible areas. The use of assembly robots also opens new horizons for design creativity, allowing architects to explore new ideas that would be unwieldy and expensive to construct using traditional techniques. In our tests, we used a team of small mobile robots to fold 2D laser-cut stock into 3D curved structures, and then assemble these units into larger interlocked forms.
keywords	full paper, automated assembly, digital fabrication, collective behavior, robot, swarm network
series	ACADIA
type	paper
email
last changed	2022/06/07 07:52

_id	ecaade2018_169
id	ecaade2018_169
authors	Kasahara, Maki, Matsushita, Kiwa and Mizutani, Akihiro
year	2018
title	Learning from Generative Design System in the 60's - Case Study of Agricultural City Project by Kisho Kurokawa
doi	https://doi.org/10.52842/conf.ecaade.2018.2.095
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 2, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 95-102
summary	The concept of generative design in Architecture and Urbanism can be found in the 60's before the wide availability of computer technology. This paper decodes one of the urban projects by Metabolist in 1960, which was intended to be a generative system applicable to other sites and evolves over time. Through our analysis, we de-code the formulation process, and verified our hypothesis by re-coding into the program using the software, Rhinoceros and Grasshopper. We found that the determinate factors rule more at the macro level of the project, but the parameters are set by taking the local conditions into account. At the micro level, the system leaves more freedom to accommodate various needs, reflecting the philosophy of the Metabolists. The investigation on this historical predecessor can provide useful insights for parameter settings in future generative system design.
keywords	Generative Design; Grasshopper; Kisho Kurokawa
series	eCAADe
email
last changed	2022/06/07 07:52

_id	ecaade2018_111
id	ecaade2018_111
authors	Khean, Nariddh, Fabbri, Alessandra and Haeusler, M. Hank
year	2018
title	Learning Machine Learning as an Architect, How to? - Presenting and evaluating a Grasshopper based platform to teach architecture students machine learning
doi	https://doi.org/10.52842/conf.ecaade.2018.1.095
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 95-102
summary	Machine learning algorithms have become widely embedded in many aspects of modern society. They have come to enhance systems, such as individualised marketing, social media services, and search engines. However, contrasting its growing ubiquity, the architectural industry has been comparatively resistant in its adoption; objectively one of the slowest industries to integrate with machine learning. Machine learning expertise can be separate from professionals in other fields; however, this separation can be a major hinderance in architecture, where interaction between the designer and the design facilitates the production of favourable outcomes. To bridge this knowledge gap, this research suggests that the solution lies with architectural education. Through the development of a novel educative framework, the research aims to teach architecture students how to implement machine learning. Exploration of student-centred pedagogical strategies was used to inform the conceptualisation of the educative module, which was subsequently implemented into an undergraduate computational design studio, and finally evaluated on its ability to effectively teach designers machine learning. The developed educative module represents a step towards greater technological adoption in the architecture industry.
keywords	Artificial Intelligence; Machine Learning; Neural Networks; Student-Centred Learning; Educative Framework
series	eCAADe
email
last changed	2022/06/07 07:52

_id	caadria2018_126
id	caadria2018_126
authors	Khean, Nariddh, Kim, Lucas, Martinez, Jorge, Doherty, Ben, Fabbri, Alessandra, Gardner, Nicole and Haeusler, M. Hank
year	2018
title	The Introspection of Deep Neural Networks - Towards Illuminating the Black Box - Training Architects Machine Learning via Grasshopper Definitions
doi	https://doi.org/10.52842/conf.caadria.2018.2.237
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 237-246
summary	Machine learning is yet to make a significant impact in the field of architecture and design. However, with the combination of artificial neural networks, a biologically inspired machine learning paradigm, and deep learning, a hierarchical subsystem of machine learning, the predictive capabilities of machine learning processes could prove a valuable tool for designers. Yet, the inherent knowledge gap between the fields of architecture and computer science has meant the complexity of machine learning, and thus its potential value and applications in the design of the built environment remain little understood. To bridge this knowledge gap, this paper describes the development of a learning tool directed at architects and designers to better understand the inner workings of machine learning. Within the parametric modelling environment of Grasshopper, this research develops a framework to express the mathematic and programmatic operations of neural networks in a visual scripting language. This offers a way to segment and parametrise each neural network operation into a basic expression. Unpacking the complexities of machine learning in an intermediary software environment such as Grasshopper intends to foster the broader adoption of artificial intelligence in architecture.
keywords	machine learning; neural network; action research; supervised learning; education
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	ecaade2018_315
id	ecaade2018_315
authors	Koehler, Daniel, Abo Saleh, Sheghaf, Li, Hua, Ye, Chuwei, Zhou, Yaonaijia and Navasaityte, Rasa
year	2018
title	Mereologies - Combinatorial Design and the Description of Urban Form.
doi	https://doi.org/10.52842/conf.ecaade.2018.2.085
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 2, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 85-94
summary	This paper discusses the ability to apply machine learning to the combinatorial design-assembly at the scale of a building to urban form. Connecting the historical lines of discrete automata in computer science and formal studies in architecture this research contributes to the field of additive material assemblies, aggregative architecture and their possible upscaling to urban design. The following case studies are a preparation to apply deep-learning on the computational descriptions of urban form. Departing from the game Go as a testbed for the development of deep-learning applications, an equivalent platform can be designed for architectural assembly. By this, the form of a building is defined via the overlap between separate building parts. Building on part-relations, this research uses mereology as a term for a set of recursive assembly strategies, integrated into the design aspects of the building parts. The models developed by research by design are formally described and tested under a digital simulation environment. The shown case study shows the process of how to transform geometrical elements to architectural parts based merely on their compositional aspects either in horizontal or three-dimensional arrangements.
keywords	Urban Form; Discrete Automata ; Combinatorics; Part-Relations; Mereology; Aggregative Architecture
series	eCAADe
email
last changed	2022/06/07 07:51

_id	ecaade2018_234
id	ecaade2018_234
authors	Loh, Paul, Leggett, David and Prohasky, Daniel
year	2018
title	CNC Adjustable Mould to Eliminate Waste in Concrete Casting
doi	https://doi.org/10.52842/conf.ecaade.2018.1.735
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 735-742
summary	Fabricating complex curvature in concrete panel typically required unique one-off formwork which is usually computer numerically controlled (CNC) milled, generating enormous waste as a by-product. What if, we can produce complex curvature in concrete with minimal or no immediate construction waste? This paper presents a novel machine designed by a team of architects and engineer to eliminate waste in concrete casting. Using a hyperbolic paraboloid geometric model, the machine produces variable shape using a single mould design reducing waste and cost to the casting process. The paper discussed the design framework of the system and its fabrication workflow. The outcome is digitally scanned and verified to satisfy industry standard. The paper concludes by reviewing the application of the system and highlighting the need for future research into digital fabrication and design that is less wasteful and waste conscious to better the process of constructing our built environment.
keywords	Digital fabrication; Concrete casting; Adjustable mould
series	eCAADe
email
last changed	2022/06/07 07:59

_id	acadia20_574
id	acadia20_574
authors	Nguyen, John; Peters, Brady
year	2020
title	Computational Fluid Dynamics in Building Design Practice
doi	https://doi.org/10.52842/conf.acadia.2020.1.574
source	ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 574-583.
summary	This paper provides a state-of-the-art of computational fluid dynamics (CFD) in the building industry. Two methods were used to find this new knowledge: a series of interviews with leading architecture, engineering, and software professionals; and a series of tests in which CFD software was evaluated using comparable criteria. The paper reports findings in technology, workflows, projects, current unmet needs, and future directions. In buildings, airflow is fundamental for heating and cooling, as well as occupant comfort and productivity. Despite its importance, the design of airflow systems is outside the realm of much of architectural design practice; but with advances in digital tools, it is now possible for architects to integrate air flow into their building design workflows (Peters and Peters 2018). As Chen (2009) states, “In order to regulate the indoor air parameters, it is essential to have suitable tools to predict ventilation performance in buildings.” By enabling scientific data to be conveyed in a visual process that provides useful analytical information to designers (Hartog and Koutamanis 2000), computer performance simulations have opened up new territories for design “by introducing environments in which we can manipulate and observe” (Kaijima et al. 2013). Beyond comfort and productivity, in recent months it has emerged that air flow may also be a matter of life and death. With the current global pandemic of SARS-CoV-2, it is indoor environments where infections most often happen (Qian et al. 2020). To design architecture in a post-COVID-19 environment will require an in-depth understanding of how air flows through space.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	ecaade2018_w12
id	ecaade2018_w12
authors	Rahbar, Morteza
year	2018
title	Application of Artificial Intelligence in Architectural Generative Design
doi	https://doi.org/10.52842/conf.ecaade.2018.1.071
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 71-72
summary	In this workshop, data-driven models will be discussed and how they could change the way architects think, design and analyse. Both supervised and unsupervised learning models will be discussed and different projects will be referred as examples. Deep learning models are the third part of the workshop and more specifically, Generative Adversarial Networks will be mentioned in more detail. The GAN's open a new field of generative models in design which is based on data-driven process and we will go into detail with GANs, their branches and how we could test a sample architecture generative problem with GANs.
keywords	Artificial Intelligence; Machine Learning; Generative Design; Knowledge based Design; GAN
series	eCAADe
email
last changed	2022/06/07 08:00

For more results click below: