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	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	ecaade2018_176
id	ecaade2018_176
authors	Fisher-Gewirtzman, Dafna and Polak, Nir
year	2018
title	Integrating Crowdsourcing & Gamification in an Automatic Architectural Synthesis Process
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. 439-444
doi	https://doi.org/10.52842/conf.ecaade.2018.1.439
summary	This work covers the methodological approach that is used to gather information from the wisdom of crowd, to be utilized in a machine learning process for the automatic generation of minimal apartment units. The flexibility in the synthesis process enables the generation of apartment units that seem to be random and some are unsuitable for dwelling. Thus, the synthesis process is required to classify units based on their suitability. The classification is deduced from opinions of human participants on previously generated units. As the definition of "suitability" may be subjective, this work offers a crowdsourcing method in order to reach a large number of participants, that as a whole would allow to produce an objective classification. Gaming elements have been adopted to make the crowdsourcing process more intuitive and inviting for external participants.
keywords	crowdsourcing and gamification; urban density; optimization; automated architecture synthesis; minimum apartments; visual openness
series	eCAADe
email
last changed	2022/06/07 07:51

_id	caadria2018_314
id	caadria2018_314
authors	Kim, Jin Sung, Song, Jae Yeol and Lee, Jin Kook
year	2018
title	Approach to the Extraction of Design Features of Interior Design Elements Using Image Recognition Technique
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. 287-296
doi	https://doi.org/10.52842/conf.caadria.2018.2.287
summary	This paper aims to propose deep learning-based approach to the auto-recognition of their design features of interior design elements using given digital images. The recently image recognition technique using convolutional neural networks has shown great success in the various field of research and industry. The open-source frameworks and pre-trained image recognition models supporting image recognition task enable us to easily retrain the models to apply them on any domain. This paper describes how to apply such techniques on interior design process and depicts some demonstration results in that approaches. Furniture that is one of the most common interior design elements has sub-feature including implicit design features, such as style, shape, function as well as explicit properties, such as component, materials, and size. This paper shows to retrain the model to extract some of the features for efficiently managing and utilizing such design information. The target element is chair and the target design features are limited to functional features, materials, seating capacity and design style. Total 3933 chair images dataset and 6 retrained image recognition models were utilized for retraining. Through the combination of those multiple models, inference demonstration also has been described.
keywords	Deep learning; Image recognition; Interior design elements; Design feature; Chair
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.
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
doi	https://doi.org/10.52842/conf.ecaade.2018.2.085
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	acadia18_166
id	acadia18_166
authors	Kvochick, Tyler
year	2018
title	Sneaky Spatial Segmentation. Reading Architectural Drawings with Deep Neural Networks and Without Labeling Data
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. 166-175
doi	https://doi.org/10.52842/conf.acadia.2018.166
summary	Currently, it is nearly impossible for an artificial neural network to generalize a task from very few examples. Humans, however, excel at this. For instance, it is not necessary for a designer to see thousands or millions of unique examples of how to place a given drawing symbol in a way that meets the economic, aesthetic, and performative goals of the project. In fact, the goals can be (and usually are) communicated abstractly in natural language. Machine learning (ML) models, however, do need numerous examples. The methods that we explore here are an attempt to circumvent this in order to make ML models more immediately useful. In this work, we present progress on the application of contemporary ML techniques to the design process in the architecture, engineering, and construction (AEC) industry. We introduce a technique to partially circumvent the data hungriness of neural networks, which is a significant impediment to their application outside of the ML research community. We also show results on the applicability of this technique to real-world drawings and present research that addresses how some fundamental attributes of drawings as images affect the way they are interpreted in deep neural networks. Our primary contribution is a technique to train a neural network to segment real-world architectural drawings after using only generated pseudodrawings.
keywords	full paper, representation + perception, computation, ai & machine learning
series	ACADIA
type	paper
email
last changed	2022/06/07 07:51

_id	ecaade2018_w12
id	ecaade2018_w12
authors	Rahbar, Morteza
year	2018
title	Application of Artificial Intelligence in Architectural Generative Design
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
doi	https://doi.org/10.52842/conf.ecaade.2018.1.071
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

_id	caadria2018_154
id	caadria2018_154
authors	Scotto, Fabio, Lloret Fritschi, Ena, Gramazio, Fabio, Kohler, Matthias and Flatt, Robert J.
year	2018
title	Adaptive Control System for Smart Dynamic Casting - Defining Fabrication-Informed Design Tools and Process Parameters in Digital Fabrication Processes
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. 255-264
doi	https://doi.org/10.52842/conf.caadria.2018.1.255
summary	This paper describes the process control system and the fabrication-informed design tool developed for Smart Dynamic Casting (SDC) - the innovative technique that merges the process of slipforming with robotic fabrication technologies to enable greater geometrical freedom in the production of architectural components made of concrete. The paper focuses on the process parameters that characterizes the production workflow and it outlines the system-specific geometry rationalization algorithm developed for the definition of feasible geometries. Furthermore, the paper introduces the first application of the SDC design tool within the architectural context of the DFAB HOUSE, a building project realized entirely by robotic and digital technologies.
keywords	Digital fabrication; Smart Dynamic Casting; Control System; Design tool
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	caadria2018_303
id	caadria2018_303
authors	Song, Jae Yeol, Kim, Jin Sung, Kim, Hayan, Choi, Jungsik and Lee, Jin Kook
year	2018
title	Approach to Capturing Design Requirements from the Existing Architectural Documents Using Natural Language Processing Technique
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. 247-254
doi	https://doi.org/10.52842/conf.caadria.2018.2.247
summary	This paper describes an approach to utilizing natural language processing (NLP) to capture design requirements from the natural language-based architectural documents. In various design stage of the architectural process, there are several different kinds of documents describing requirements for buildings. Capturing the design requirements from those documents is based on extracting information of objects, their properties, and relations. Until recently, interpreting and extracting that information from documents are almost done by a manual process. To intelligently automate the conventional process, the computer has to understand the semantics of natural languages. In this regards, this paper suggests an approach to utilizing NLP for semantic analysis which enables the computer to understand the semantics of the given text data. The proposed approach has following steps: 1) extract noun words which mostly represent objects and property data in Korean Building Act; 2) analyze the semantic relations between words, using NLP and deep learning; 3) Based on domain database, translate the noun words in objects and properties data and find out their relations.
keywords	NLP (Natural Language Processing); Deep learning; Design requirements; Korean Building Act; Semantic analysis
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	acadia18_186
id	acadia18_186
authors	Yin, Hao; Guo, Zhe; Zhao, Yao; Yuan, Philip F.
year	2018
title	Behavior Visualization System Based on UWB Positioning Technology
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. 186-195
doi	https://doi.org/10.52842/conf.acadia.2018.186
summary	This paper takes behavioral performance as a starting point and uses ultra-wideband (UWB) positioning technology and visualization methods to accurately collect and present in-place behavioral data so as to explore the behavioral characteristics of space users. In this process, we learned the observation, quantification, and presentation of behavioral data from the evolution of behavioral research. Secondly, after a comparative analysis of four types of indoor positioning technologies, we selected UWB-positioning technology and the JavaScript programming language as the development tools for a behavior visualization system. Next, we independently developed the behavior visualization system, which required a deep understanding of the working principle of UWB technology and the visualization method of the JavaScript programming language. Finally, the system was applied to an actual space, collecting and presenting users’ behavioral characteristics and habits in order to verify the applicability of the system in the field of behavioral research.
keywords	full paper, design tools, ai + machine learning, big data, behavioral performance + simulation
series	ACADIA
type	paper
email
last changed	2022/06/07 07:57

_id	sigradi2018_1619
id	sigradi2018_1619
authors	Agirbas, Asli
year	2018
title	Creating Non-standard Spaces via 3D Modeling and Simulation: A Case Study
source	SIGraDi 2018 [Proceedings of the 22nd Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Brazil, São Carlos 7 - 9 November 2018, pp. 1051-1058
summary	Especially in the film industry, architectural spaces away from Euclidean geometry are brought to foreground. The best environment in which such spaces can be designed, is undoubtedly the 3D modeling environment. In this study, an experimental study was carried out on the creation of alternative spaces with undergraduate architectural students. Via using 3D modeling and various simulation techniques in the Maya software, students created spaces, which were away from the traditional architectural spaces. Thus, in addition to learning the 3D modeling software, architectural students learned to use animation and simulation as a part of design, not just as a presentation tool, and opening up new horizons for non-standard spaces was provided.
keywords	3D Modeling; Simulation; Animation; CAAD; Maya; Non-standard spaces
series	SIGRADI
email
last changed	2021/03/28 19:58

_id	acadia18_216
id	acadia18_216
authors	Ahrens, Chandler; Chamberlain, Roger; Mitchell, Scott; Barnstorff, Adam
year	2018
title	Catoptric Surface
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. 216-225
doi	https://doi.org/10.52842/conf.acadia.2018.216
summary	The Catoptric Surface research project explores methods of reflecting daylight through a building envelope to form an image-based pattern of light on the interior environment. This research investigates the generation of atmospheric effects from daylighting projected onto architectural surfaces within a built environment in an attempt to amplify or reduce spatial perception. The mapping of variable organizations of light onto existing or new surfaces creates a condition where the perception of space does not rely on form alone. This condition creates a visual effect of a formless atmosphere and affects the way people use the space. Often the desired quantity and quality of daylight varies due to factors such as physiological differences due to age or the types of tasks people perform (Lechner 2009). Yet the dominant mode of thought toward the use of daylighting tends to promote a homogeneous environment, in that the resulting lighting level is the same throughout a space. This research project questions the desire for uniform lighting levels in favor of variegated and heterogeneous conditions. The main objective of this research is the production of a unique facade system that is capable of dynamically redirecting daylight to key locations deep within a building. Mirrors in a vertical array are individually adjusted via stepper motors in order to reflect more or less intense daylight into the interior space according to sun position and an image-based map. The image-based approach provides a way to specifically target lighting conditions, atmospheric effects, and the perception of space.
keywords	full paper, non-production robotics, representation + perception, performance + simulation, building technologies
series	ACADIA
type	paper
email
last changed	2022/06/07 07:54

_id	ijac201816103
id	ijac201816103
authors	Alani, Mostafa W.
year	2018
title	Algorithmic investigation of the actual and virtual design space of historic hexagonal-based Islamic patterns
source	International Journal of Architectural Computing vol. 16 - no. 1, 34-57
summary	This research challenges the long-standing paradigm that considers compositional analysis to be the key to researching historical Islamic geometric patterns. Adopting a mathematical description shows that the historical focus on existing forms has left the relevant structural similarities between historical Islamic geometric patterns understudied. The research focused on the hexagonal-based Islamic geometric patterns and found that historical designs correlate to each other beyond just the formal dimension and that deep, morphological connections exist in the structures of historical singularities. Using historical evidence, this article identifies these connections and presents a categorization system that groups designs together based on their “morphogenetic” characteristics.
keywords	Islamic geometric patterns, morphology, computations, digital design, algorithmic thinking
series	journal
email
last changed	2019/08/07 14:03

_id	caadria2018_029
id	caadria2018_029
authors	Ayoub, Mohammed
year	2018
title	Adaptive Façades:An Evaluation of Cellular Automata Controlled Dynamic Shading System Using New Hourly-Based Metrics
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. 83-92
doi	https://doi.org/10.52842/conf.caadria.2018.2.083
summary	This research explores utilizing Cellular Automata patterns as climate-adaptive dynamic shading systems to mitigate the undesirable impacts by excessive solar penetration in cooling-dominant climates. The methodological procedure is realized through two main phases. The first evaluates all 256 Elementary Cellular Automata possible rules to elect the ones with good visual and random patterns, to ensure an equitable distribution of the natural daylight in internal spaces. Based on the newly developed hourly-based metrics, simulations are conducted in the second phase to evaluate the Cellular Automata controlled dynamic shadings performance, and formalize the adaptive façade variation logic that maximizes daylighting and minimizes energy demand.
keywords	Adaptive Façade; Dynamic Shading; Cellular Automata; Hourly-Based Metric; Performance Evaluation
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	caadria2018_033
id	caadria2018_033
authors	Bai, Nan and Huang, Weixin
year	2018
title	Quantitative Analysis on Architects Using Culturomics - Pattern Study of Prizker Winners Based on Google N-gram Data
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. 257-266
doi	https://doi.org/10.52842/conf.caadria.2018.2.257
summary	Quantitative studies using the corpus Google Ngram, namely Culturomics, have been analyzing the implicit patterns of culture changes. Being the top-standard prize in the field of Architecture since 1979, the Pritzker Prize has been increasingly diversified in the recent years. This study intends to reveal the implicit pattern of Pritzker Winners using the method of Culturomics, based on the corpus of Google Ngram to reveal the relationship of the sign of their fame and the fact of prize-winning. 48 architects including 32 awarded and 16 promising are analyzed in the printed corpus of English language between 1900 and 2008. Multiple regression models and multiple imputation methods are used during the data processing. Self-Organizing Map is used to define clusters among the awarded and promising architects. Six main clusters are detected, forming a 3×2 network of fame patterns. Most promising architects can be told from the clustering, according to their similarity to the more typical prize winners. The method of Culturomics could expand the sight of architecture study, giving more possibilities to reveal the implicit patterns of the existing empirical world.
keywords	Culturomics; Google Ngram; Pritzker Prize; Fame Pattern; Self-Organizing Map
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	acadia18_176
id	acadia18_176
authors	Bidgoli, Ardavan; Veloso,Pedro
year	2018
title	DeepCloud. The Application of a Data-driven, Generative Model in Design
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. 176-185
doi	https://doi.org/10.52842/conf.acadia.2018.176
summary	Generative systems have a significant potential to synthesize innovative design alternatives. Still, most of the common systems that have been adopted in design require the designer to explicitly define the specifications of the procedures and in some cases the design space. In contrast, a generative system could potentially learn both aspects through processing a database of existing solutions without the supervision of the designer. To explore this possibility, we review recent advancements of generative models in machine learning and current applications of learning techniques in design. Then, we describe the development of a data-driven generative system titled DeepCloud. It combines an autoencoder architecture for point clouds with a web-based interface and analog input devices to provide an intuitive experience for data-driven generation of design alternatives. We delineate the implementation of two prototypes of DeepCloud, their contributions, and potentials for generative design.
keywords	full paper, design tools software computing + gaming, ai & machine learning, generative design, autoencoders
series	ACADIA
type	paper
email
last changed	2022/06/07 07:52

_id	caadria2018_125
id	caadria2018_125
authors	Bungbrakearti, Narissa, Cooper-Wooley, Ben, Odolphi, Jorke, Doherty, Ben, Fabbri, Alessandra, Gardner, Nicole and Haeusler, M. Hank
year	2018
title	HOLOSYNC - A Comparative Study on Mixed Reality and Contemporary Communication Methods in a Building Design Context
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. 401-410
doi	https://doi.org/10.52842/conf.caadria.2018.1.401
summary	The integration of technology into the design process has enabled us to communicate through various modes of virtuality, while more traditional face-to-face collaborations are becoming less frequent, specifically for large scale companies. Both modes of communication have benefits and disadvantages - virtual communication enables us to connect over large distances, however can often lead to miscommunication, while face-to-face communication builds stronger relationship, however may be problematic for geographically dispersed teams. Mixed Reality is argued to be a hybrid of face-to-face and virtual communication, and is yet to be integrated into the building design process. Despite its current limitations, such as field of view, Mixed Reality is an effective tool that generates high levels of nonverbal and verbal communication, and encourages a high and equal level of participation in comparison to virtual and face-to-face communication. Being a powerful communication tool for complex visualisations, it would be best implemented in the later stages of the building design process where teams can present designs to clients or where multiple designers can collaborate over final details.
keywords	Mixed Reality; Communication; Hololens; Collaboration; Virtual
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	caadria2018_278
id	caadria2018_278
authors	Caetano, In?s, Ilunga, Guilherme, Belém, Catarina, Aguiar, Rita, Feist, Sofia, Bastos, Francisco and Leit?o, António
year	2018
title	Case Studies on the Integration of Algorithmic Design Processes in Traditional Design Workflows
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. 111-120
doi	https://doi.org/10.52842/conf.caadria.2018.1.111
summary	Algorithmic design processes have enormous potential for architecture. Even though some large design offices have already incorporated such processes in their workflow, so far, these have not been seriously considered by the large majority of traditional small-scale studios. Nevertheless, as the integration of algorithmic techniques inside architectural studios does not require mastering programming skills, but rather taking advantage of a collaborative design process, small design studios are therefore able of using such strategies within their workflow. This paper discusses a series of challenges presented by one of these studios, where we had to integrate algorithmic design processes with the studio's traditional workflow.
keywords	Collaborative design; Algorithmic design; Design strategies; Design workflow processes
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	sigradi2018_1329
id	sigradi2018_1329
authors	Campos Fialho, Beatriz; A. Costa, Heliara; Logsdon, Louise; Minto Fabrício, Márcio
year	2018
title	CAD and BIM tools in Teaching of Graphic Representation for Engineering
source	SIGraDi 2018 [Proceedings of the 22nd Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Brazil, São Carlos 7 - 9 November 2018, pp. 961-968
summary	BIM technology has represented an advance and a break of the design process’ paradigm, impacting both academia and construction market. Reporting a didactic experience in the Civil Engineering graduation, this article aims to understand the teaching and learning process of graphic representation, by using CAD and BIM tools. The research included Literature Review and Empirical Study, whose data collection was based on the application of questionnaires, practical exercises and theoretical test with the students. As a contribution, we highline the complementary nature of the tools and the potentialities of BIM for teaching graphic representation.
keywords	Graphic Representation; CAD System Education; CAE System Education. BIM
series	SIGRADI
email
last changed	2021/03/28 19:58

_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
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
doi	https://doi.org/10.52842/conf.ecaade.2018.2.669
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	acadia18_386
id	acadia18_386
authors	Chen, Canhui; Burry, Jane
year	2018
title	(Re)calibrating Construction Simplicity and Design Complexity
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. 386-393
doi	https://doi.org/10.52842/conf.acadia.2018.386
summary	Construction simplicity is crucial to cost control, however design complexity is often necessary in order to meet particular spatial performance criteria. This paper presents a case study of a semi-enclosed meeting pod that has a brief that must contend with the seemingly contradictory conditions of the necessary geometric complexities imperative to improved acoustic performance and cost control in construction. A series of deep oculi are introduced as architectural elements to link the pod interior to the outside environment. Their reveals also introduce sound reflection and scattering, which contribute to the main acoustic goal of improved speech privacy. Represented as a three-dimensional funnel like shape, the reveal to each opening is unique in size, depth and angle. Traditionally, the manufacturing of such bespoke architectural elements in many cases resulted in lengthy and costly manufacturing processes. This paper investigates how the complex oculi shape variations can be manufactured using one universal mold. A workflow using mathematical and computational operations, a standardized fabrication approach and customization through tooling results in a high precision digital process to create particular calculated geometries, recalibrated at each stage to account for the paradoxical inexactitudes and inevitable tolerances.
keywords	work in progress,tolerance, developable surface, form finding, construction simplicity, material behavior
series	ACADIA
type	paper
email
last changed	2022/06/07 07:55

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