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 437

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

_id	acadia18_156
id	acadia18_156
authors	Huang, Weixin; Zheng, Hao
year	2018
title	Architectural Drawings Recognition and Generation through Machine Learning
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
doi	https://doi.org/10.52842/conf.acadia.2018.156
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	ijac201816304
id	ijac201816304
authors	Miao, Yufan; Reinhard Koenig, Katja Knecht, Kateryna Konieva, Peter Buš and Mei-Chih Chang
year	2018
title	Computational urban design prototyping: Interactive planning synthesis methods—a case study in Cape Town
source	International Journal of Architectural Computing vol. 16 - no. 3, 212-226
summary	This article is motivated by the fact that in Cape Town, South Africa, approximately 7.5 million people live in informal settlements and focuses on potential upgrading strategies for such sites. To this end, we developed a computational method for rapid urban design prototyping. The corresponding planning tool generates urban layouts including street network, blocks, parcels and buildings based on an urban designer’s specific requirements. It can be used to scale and replicate a developed urban planning concept to fit different sites. To facilitate the layout generation process computationally, we developed a new data structure to represent street networks, land parcellation, and the relationship between the two. We also introduced a nested parcellation strategy to reduce the number of irregular shapes generated due to algorithmic limitations. Network analysis methods are applied to control the distribution of buildings in the communities so that preferred neighborhood relationships can be considered in the design process. Finally, we demonstrate how to compare designs based on various urban analysis measures and discuss the limitations that arise when we apply our method in practice, especially when dealing with more complex urban design scenarios.
keywords	Procedural modeling, spatial synthesis, generative design, urban planning
series	journal
email
last changed	2019/08/07 14:03

_id	ecaade2018_303
id	ecaade2018_303
authors	Werner, Liss C.
year	2018
title	Biological Computation of Physarum - From DLA to spatial adaptive Voronoi
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. 531-536
doi	https://doi.org/10.52842/conf.ecaade.2018.2.531
summary	Physarum polycephalum, also called slime mold or myxamoeba, has started attracting the attention of those architects, urban designers, and scholars, who work in experimental trans- and flexi-disciplines between architecture, computer sciences, biology, art, cognitive sciences or soft matter; disciplines that build on cybernetic principles. Slime mold is regarded as a bio-computer with intelligence embedded in its physical mechanisms. In its plasmodium stage, the single cell organism shows geometric, morphological and cognitive principles potentially relevant for future complexity in human-machines-networks (HMN) in architecture and urban design. The parametric bio-blob presents itself as a geometrically regulated graph structure-morphologically adaptive, logistically smart. It indicates cognitive goal-driven navigation and the ability to externally memorize (like ants). Physarum communicates with its environment. The paper introduces physarum polycephalum in the context of 'digital architecture' as a biological computer for self-organizing 2D- to 4D-geometry generation.
keywords	generative geometry; bio-computation; Voronoi
series	eCAADe
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	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	acadia19_392
id	acadia19_392
authors	Steinfeld, Kyle
year	2019
title	GAN Loci
source	ACADIA 19:UBIQUITY AND AUTONOMY [Proceedings of the 39th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-59179-7] (The University of Texas at Austin School of Architecture, Austin, Texas 21-26 October, 2019) pp. 392-403
doi	https://doi.org/10.52842/conf.acadia.2019.392
summary	This project applies techniques in machine learning, specifically generative adversarial networks (or GANs), to produce synthetic images intended to capture the predominant visual properties of urban places. We propose that imaging cities in this manner represents the first computational approach to documenting the Genius Loci of a city (Norberg-Schulz, 1980), which is understood to include those forms, textures, colors, and qualities of light that exemplify a particular urban location and that set it apart from similar places. Presented here are methods for the collection of urban image data, for the necessary processing and formatting of this data, and for the training of two known computational statistical models (StyleGAN (Karras et al., 2018) and Pix2Pix (Isola et al., 2016)) that identify visual patterns distinct to a given site and that reproduce these patterns to generate new images. These methods have been applied to image nine distinct urban contexts across six cities in the US and Europe, the results of which are presented here. While the product of this work is not a tool for the design of cities or building forms, but rather a method for the synthetic imaging of existing places, we nevertheless seek to situate the work in terms of computer-assisted design (CAD). In this regard, the project is demonstrative of a new approach to CAD tools. In contrast with existing tools that seek to capture the explicit intention of their user (Aish, Glynn, Sheil 2017), in applying computational statistical methods to the production of images that speak to the implicit qualities that constitute a place, this project demonstrates the unique advantages offered by such methods in capturing and expressing the tacit.
series	ACADIA
type	normal paper
email
last changed	2022/06/07 07:56

_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	ecaade2018_399
id	ecaade2018_399
authors	Cutellic, Pierre
year	2018
title	UCHRON - An Event-Based Generative Design Software Implementing Fast Discriminative Cognitive Responses from Visual ERP BCI
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. 131-138
doi	https://doi.org/10.52842/conf.ecaade.2018.2.131
summary	This research aims at investigating BCI technologies in the broad scope of CAAD applications exploiting early visual cognition in computational design. More precisely, this paper will describe the investigation of key BCI and ML components for the implementation and development of a software supporting this research : Uchron. It will be organised as follows. Firstly, it will introduce the pursued interest and contribution that visual-ERP EEG based BCI application for Generative Design may provide through a synthetic review of precedents and BCI technology. Secondly, selected BCI components will be described and a methodology will be presented to provide an appropriate framework for a CAAD software approach. This section main focus is on the processing component of the BCI. It distinguishes two key aspects of discrimination and generation in its design and proposes a new model based on GAN for modulated adversarial design. Emphasis will be made on the explicit use of inference loops integrating fast human cognitive responses and its individual capitalisation through time in order to reflect towards the generation of design and architectural features.
keywords	Human Computer Interaction; Neurodesign; Generative Design; Design Computing and Cognition; Machine Learning
series	eCAADe
email
last changed	2022/06/07 07:56

_id	caadria2018_083
id	caadria2018_083
authors	Luo, Dan, Wang, Jinsong and Xu, Weiguo
year	2018
title	Robotic Automatic Generation of Performance Model for Non-Uniform Linear Material via Deep Learning
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. 39-48
doi	https://doi.org/10.52842/conf.caadria.2018.1.039
summary	In the following research, a systematic approach is developed to generate an experiment-based performance model that computes and customizes properties of non-uniform linear materials to accommodate the form of designated curve under bending and natural force. In this case, the test subject is an elastomer strip of non-uniform sections. A novel solution is provided to obtain sufficient training data required for deep learning with an automatic material testing mechanism combining robotic arm automation and image recognition. The collected training data are fed into a deep combination of neural networks to generate a material performance model. Unlike most traditional performance models that are only able to simulate the final form from the properties and initial conditions of the given materials, the trained neural network offers a two-way performance model that is also able to compute appropriate material properties of non-uniform materials from target curves. This network achieves complex forms with minimal and effective programmed materials with complicated nonlinear properties and behaving under natural forces.
keywords	Material performance model; Deep Learning; Robotic automation; Material computation; Neural network
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	ijac201816101
id	ijac201816101
authors	Nisztu, Maciejk and Pawe³ B. Myszkowsk
year	2018
title	Usability of contemporary tools for the computational design of architectural objects: Review, features evaluation and reflection
source	International Journal of Architectural Computing vol. 16 - no. 1, 58-84
summary	This article is an overview focused on functionality and usability of selected contemporary approaches for the computational floor plan generation of architectural objects. This article describes current solutions for generative architectural design and focuses on their usability from the point of view of architectural design practice. Recent research papers and prototypes, as well as the most important tools (selected computer-aided design and BIM software) for generative design from the architectural perspective, are described. The functionalities and level of usability of present-day software and prototypes are described. In addition, the descriptive review of the research prototypes architectural design outcomes is present. Furthermore, the survey among active architects regarding the usage of computational tools in the professional practice and possible guidelines for the development of such tools are present. This article summarises with the conclusion about the current state of generative floor plan design tools, the lack of fully functional and developed commercial tools of this type on the market and future directions for the development of generative floor plans tools.
keywords	Architectural design, case studies, computer-aided architectural design, optimisation in computer-aided architectural design, computer-aided architectural design applications
series	journal
email
last changed	2019/08/07 14:03

_id	caadria2018_197
id	caadria2018_197
authors	Rogers, Jessie, Schnabel, Marc Aurel and Lo, Tian Tian
year	2018
title	Digital Culture - An Interconnective Design Methodology Ecosystem
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. 493-502
doi	https://doi.org/10.52842/conf.caadria.2018.1.493
summary	Transitioning away from traditional design methodology, for example, paper sketching, CAAD works, and 'flat screen' rendering, this paper proposes a new methodological ecosystem of which tests its validity within a studio-based case study. The focus will prove whether dynamic implementation and interconnectivity of evolving design tools can create richness and complexity of a design outcome through arbitrary phases of a generative design methodology ecosystem. Processes tested include combinations of agent simulations, artistic image processing analysis, site photogrammetry, 3D immersive sketching both abstract and to site-scale, parametric design generation, and virtual reality style presentations. Enhancing the process of design with evolving techniques in a generative way which dynamically interconnects will stimulate a digital culture of design generation that includes new aspects of interest and introduces innovative opportunities within all corners of the architectural realm. Methodology components within this ecosystem of interaction prove that the architecture cannot be as rich and complex without the utilisation of all strengths within each unique design tool.
keywords	Methodology Ecosystem; Simulation; Immersive; Virtual Reality; Photogrammetry
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	ecaade2018_158
id	ecaade2018_158
authors	Zhou, Jing, Klumpner, Hubert and Brillembourg, Afredo
year	2018
title	The Dynamic Geometric Network Model for Representing Verticalized Urban Environment and its Generation
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. 525-530
doi	https://doi.org/10.52842/conf.ecaade.2018.1.525
summary	Against the background of urbanization and the fast growth of population in big cities, there will be more and more high-rises emerged in the future. In some big cities, the various layers of public transpiration networks such as metro systems also played an essential role in the urban life. In the verticalized urban environment, the complexity of the multi-layers space system connected by various horizontal and vertical connections have been beyond people's cognition. The boundaries between private space and public space, outdoor-space and indoor-space have already blurred. The graph theory based urban spatial analysis approaches are adopted in urban studies to tackle with the urban complexity issues. However, at present, most of the methods proposed are specializing in open urban spaces, and they cannot describe the three-dimensional completely and accurately. Therefore, in this paper, a new graph theory based representation method, the Dynamic Geometric Network Model, which adapted to the verticalized urban environment will be proposed. And the approach of how to automatically generate such a representation model according to the urban layout will also be introduced.
keywords	Graph Model Representation; Graph Model Generation; Verticalized Urban Environment
series	eCAADe
email
last changed	2022/06/07 07:57

_id	ecaade2018_323
id	ecaade2018_323
authors	Newton, David
year	2018
title	Multi-Objective Qualitative Optimization (MOQO) in Architectural 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. 187-196
doi	https://doi.org/10.52842/conf.ecaade.2018.1.187
summary	Architectural design problems are often multi-objective in nature, involving both qualitative and quantitative objectives. Previous research has focused exclusively on the development of multi-objective optimization algorithms that work with multiple quantitative objectives. No previous research has looked at the topic of multi-objective qualitative optimization (MOQO), in which multiple qualitative objectives are optimized simultaneously. This research addresses MOQO through the development of a unique multi-objective optimization algorithm for the conceptual design phase that uses three-dimensional convolutional neural networks (3D CNNs) to measure user-defined qualities in architectural massing models.
keywords	multi-objective optimization; generative design; multi-objective qualitative optimization; algorithmic design
series	eCAADe
email
last changed	2022/06/07 07:58

_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	ecaade2018_403
id	ecaade2018_403
authors	Coraglia, Ugo Maria, Wurzer, Gabriel and Fioravanti, Antonio
year	2018
title	ORe – A simulation model for Organising Refurbishments
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. 605-610
doi	https://doi.org/10.52842/conf.ecaade.2018.2.605
summary	The problem of interferences due to the refurbishing activities of a complex building, carried out in parallel with the daily activities that characterize it, is not to be underestimated, especially when talking about a hospital structure. Consequently, the benefits that would be obtained by reducing the presence of construction activities result important in terms of safety and health of users, above all hospital patients. Setting the best solution of Gantt in the early stages of planning can be a winning strategy, as well as being able to recognize the safest and fastest path (e.g. predicting which is the fastest way to reach the rooms taken into consideration by the refurbishment). At the same time, being able to check which activities are most penalized by the presence of the construction site and to set which are essential for the survival of the activities that characterize the environment to be refurbished, e.g. the hospital ward, is a valid support tool for the healthcare staff. The proposed tool aims, on the one hand, to help designers by proposing the best possible Gantt solutions in relation to the management of daily activities that can not be suspended and on the other hand to support healthcare staff in the organization of these latter.
keywords	Refurbishment; Complex building; Construction site; Space syntax; Bubble diagram; Gantt
series	eCAADe
email
last changed	2022/06/07 07:56

_id	ecaade2018_210
id	ecaade2018_210
authors	Ezzat, Mohammed
year	2018
title	A Computational Tool for Mapping the Users' Urban Cognition - A Framework and a Representation for the Evolutionary Optimization of the Fuzzy Binary Relation between the Urban Conceptions of "Us" and "Others"
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. 667-676
doi	https://doi.org/10.52842/conf.ecaade.2018.1.667
summary	The paper proposes a computational tool for simulating the users' urban cognitive systems, or more specifically the long-term memory associated with the knowledge of urbanism and its related urban visual features. The tool builds on our comprehensive theory of Urbanism, which presents a monolithic, structured, comprehensive, professional conception of Urbanism based on which any relativistic users' urban conceptions could be predicted as a restructuring of the professional conception. These versatile relativistic conceptions would emerge based on a nurturing environment, which is a conception of the empirical/anthropological collected data of the intended users' reflections against their preferred constructed urban environments. Once the users' conceptions of Urbanism are formulated, which is the first phase of the simulation, the users' impressions against any examined urban constructs are attainable, which is the second phase of the simulation. The two phases, the framework, would be monolithically represented by a proposed novel cellular graph. The proposed computational tool is thought of as a robust technique for the computational incorporation of the users' urban identity, and some of its constituents could be considered as a needed common platform of communication for a successful Human-Computer interaction in the field of urban analysis/design.
keywords	a comprehensive model of Urbanism; a default professional conception of Urbanism; the relativistic users' conceptions of Urbanism ; recognized extracted urban features ; the users' urban identity; A comprehensive theory for space syntax:
series	eCAADe
email
last changed	2022/06/07 07:55

_id	sigradi2023_243
id	sigradi2023_243
authors	O. Oporto, Italo, Martínez Arias, Andrea and Villouta Gutierrez, Daniela
year	2023
title	Iluminación y configuración espacial: Una metodología de análisis íntegra: El caso del Servicio de Psiquiatría Guillermo Grant Benavente en Concepción, Chile.”
source	García Amen, F, Goni Fitipaldo, A L and Armagno Gentile, Á (eds.), Accelerated Landscapes - Proceedings of the XXVII International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2023), Punta del Este, Maldonado, Uruguay, 29 November - 1 December 2023, pp. 385–396
summary	Our everyday environment plays a significant role in shaping our social and emotional interactions. It has been empirically evidenced that natural daylight mitigates depression, insomnia, and other disorders (Weber, 2022). This resonates with the fact that individuals with disrupted circadian rhythms are more susceptible to mental health perturbations (Menculini et al., 2018). The current investigation delves into the correlation between luminosity and spatial configuration within the Guillermo Grantt Benavente Psychiatry Service in Concepción, Chile. The contention is that proficient spatial connectivity and exposure to natural daylight can potentially enhance therapeutic dimensions. The overarching objective is to comprehend this nexus for formulating an architectural design methodology. Specific objectives encompass: 1. Defining the communal spaces under scrutiny; 2. Analyzing luminosity and spatial attributes. The methodological approach encompasses a hybrid framework encompassing interviews, spatial analysis, and illuminance measurements. An intricate interrelationship among preferred spaces, illuminance, and spatial characteristics is anticipated.
keywords	Environment, Lighting, Space Syntax, Mental health, Psychiatric residence
series	SIGraDi
email
last changed	2024/03/08 14:07

_id	sigradi2018_1681
id	sigradi2018_1681
authors	Paglis, Julia; Brandão, Guilherme; Lima, Fernando; Serdoura, Francisco
year	2018
title	Urban Analysis and Space Syntax Theory: study and mapping of the city of Juiz de Fora, Brazil
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. 602-608
summary	This paper is a result of a research that uses the Space Syntax Theory for analysis of the city of Juiz de Fora, Brazil. After elaborating the axial map, based on data collection available by the City Hall, some analysis of the city were made using the syntactic measures: Integration HH, Mean Depth and Total Depth. The focus of the analysis was on the central area of the city, called "Central Triangle". As a result, the analyzes make it possible to identify that the initial urban center remains as the point of convergence of several urban areas of the city, consolidating itself as an area with great potential.
keywords	Space Syntax; Urban analysis; Central area; Juiz de Fora
series	SIGRADI
email
last changed	2021/03/28 19:59

_id	ecaade2018_398
id	ecaade2018_398
authors	Papavasiliou, Mattheos
year	2018
title	The Didactic Aspect of Ars Combinatoria in Architectural Design - Employing syntactic ("space syntax") formulations to communicate architectural design to students of Architecture.
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. 525-530
doi	https://doi.org/10.52842/conf.ecaade.2018.2.525
summary	This paper presents educative aspects of visualization techniques based on an idea by B. Hillier to illustrate architectural forms with the space syntax theory. It explores and renders the technique of transformation and implementation of syntactic analysis in order to convey to students of Architecture spatial concepts and to differentiate spatial arrangements that present understandably similarities and differences. The technique is applied to plans of well-known examples from the history of Architecture and illustrates to a sufficient extent the theoretical interpretations taught in the architectural design studio.
keywords	architectural configuration; design strategy; design analysis; shape evaluation
series	eCAADe
email
last changed	2022/06/07 08:00

_id	sigradi2018_1642
id	sigradi2018_1642
authors	Pereira Bezerra de Melo Junior, Silvio; Canuto da Silva, Robson
year	2018
title	Aplicability of 2D and 3D isovists and visibility graph analysis for evaluating urban vulnerability to crime: the case of Boa Viagem, in Recife
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. 308-315
summary	This work aims to investigate the applicability of 2D and 3D isovists, as well as Visibility Graph Analysis (VGA), for evaluating urban vulnerability to crime. The methodology is based on correlations between number of crime occurrences and measurements of 2D and 3D isovists, and mean values of visual integration (VGA). The 2D isovists were produced through DeCoding Spaces Toolbox for Grasshopper and the 3D isovists were generated by using algorithms within Rhinoceros and Grasshopper. VGA maps were elaborated within DepthmapX. For this study, were selected nine street segments of Boa Viagem, located in Recife-PE, a neighbourhood which is known for high rates of robberies. Although the number of samples is reduced, the results suggest that criminals prefer much more visually integrated spaces with low occlusivity and fewer spatial cavities.
keywords	Criminality; isovist; parametric; urban space; space syntax
series	SIGRADI
email
last changed	2021/03/28 19:59

For more results click below: