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	ecaade2018_172
id	ecaade2018_172
authors	Al-Douri, Firas
year	2018
title	The Employment of Digital Simulation in the Planning Departments in US Cities - How does it affect design and decision-making processes?
doi	https://doi.org/10.52842/conf.ecaade.2018.2.539
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. 539-548
summary	The increased interactivity of digital simulation tools has offered a wide range of opportunities that may provoke a paradigmatic shift in urban design practice. Yet, research results did not provide any clear evidence that such shift seems to exist. Further studies are required to examine the methods and impact of their usage on decision-making and design outcome. To that goal, this research uses the single-case study design that has been pursued in three phases: literature review, online survey, and semi-structured interviews. The results have shown inadequacies, inconsistency, and ineffectiveness of usage of the tools that are most appropriate to the design activities of each phase and thus a limited impact on critical areas of the decision-making. The impact of the tools' usage is found to be correlated with not only the extent of their usage, but also with a variety of procedural and substantive factors such as the plan methodology, extent of tool's usage, choice of the appropriate tool, and planners' skills and capabilities in using those tools.
keywords	Urban Simulation ; Urban Design Practice
series	eCAADe
email
last changed	2022/06/07 07:54

_id	acadia18_118
id	acadia18_118
authors	Kalantari, Saleh; Contreras-Vidal, Jose Luis; Smith, Joshua Stanton; Cruz-Garza, Jesus; Banner, Pamela
year	2018
title	Evaluating Educational Settings through Biometric Data and Virtual Response Testing
doi	https://doi.org/10.52842/conf.acadia.2018.118
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. 118-125
summary	The physical design of the learning environment has been shown to contribute significantly to student performance and educational outcomes. However, the existing literature on this topic relies primarily on generalized observations rather than on rigorous empirical testing. Broad trends in environmental impacts have been noted, but there is a lack of detailed evidence about how specific design variables can affect learning performance. The goal of this study was to apply a new approach in examining classroom design innovations. We developed a protocol to evaluate the effectiveness of classroom designs by measuring the physical responses of study participants as they interacted with different designs using a virtual reality platform. Our hypothesis was that virtual “test runs” can help designers to identify potential problems and successes in their work prior to its being physically constructed. The results of our initial pilot study indicated that this approach could yield important results about human responses to classroom design, and that the virtual environment seemed to be a reliable testing substitute when compared against real classroom environments. In addition to leading toward practical conclusions about specific classroom design variables, this project provides a new kind of research method and toolset to test the potential human impacts of a wide variety of architectural innovations.
keywords	work in progress, signal processing, eeg, virtual reality, big data, learning performance
series	ACADIA
type	paper
email
last changed	2022/06/07 07:52

_id	acadia18_196
id	acadia18_196
authors	Zhang, Yan; Grignard; Aubuchon, Alexander; Lyons, Keven; Larson, Kent
year	2018
title	Machine Learning for Real-time Urban Metrics and Design Recommendations
doi	https://doi.org/10.52842/conf.acadia.2018.196
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. 196-205
summary	Cities are growing, becoming more complex, and changing rapidly. Currently, community engagement for urban decision-making is often ineffective, uninformed, and only occurs in projects’ later stages. To facilitate a more collaborative and evidence-based urban decision- making process for both experts and non-experts, real-time feedback and optimized suggestions are essential. However, most of the current tools for urban planning are neither capable of performing complex simulations in real time nor of providing guidance for better urban performance. CityMatrix was introduced to address these challenges. Machine learning techniques were applied to achieve real-time prediction of multiple urban simulations, and thousands of city configurations were simulated. The simulation results were used to train a convolutional neural network (CNN) to predict the traffic and solar performance of unseen city configurations. The prediction with the CNN is thousands of times faster than the original simulations and maintains a high-quality representation of the results. This machine learning approach was applied as a versatile, quick, accurate, and computationally efficient method not only for real-time feedback, but also for optimized design recommendations. Users involved in the evaluation of this project had a better understanding of the embodied trade-offs of the city and achieved their goals in an efficient manner.
keywords	full paper, optimization, collaboration, urban design & analysis, ai & machine learning
series	ACADIA
type	paper
email
last changed	2022/06/07 07:57

_id	acadia18_136
id	acadia18_136
authors	Austern, Guy; Capeluto, Isaac Guedi; Grobman, Yasha Jacob
year	2018
title	Fabrication-Aware Design of Concrete Façade Panels. A Computational Method For Evaluating the Fabrication of Large- Scale Molds in Complex Geometries
doi	https://doi.org/10.52842/conf.acadia.2018.136
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. 136-145
summary	This paper presents a design methodology for concrete façade panels that takes into consideration constraints related to digital fabrication machinery. A computational method for the real-time evaluation of industrial mold-making techniques, such as milling and hot wire cutting, was developed. The method rapidly evaluates the feasibility, material use, and machining time of complex geometry molds for architectural façade elements. Calculation speed is achieved by mathematically approximating CAM-machining operations. As results are obtained in nearly real time, the method can be easily incorporated into the architectural design process during its initial stages, when changes to the design are more effective. In the paper, we describe the algorithms of the computational evaluation method. We also show how it can be used to introduce fabrication considerations into the design process by using it to rationalize several types of panels. Additionally, we demonstrate how the method can be used in complex, large-scale architectural projects to save machining time and materials by evaluating and altering the paneling subdivision.
keywords	full paper, fabrication & robotics, digital fabrication, performance + simulation, geometry
series	ACADIA
type	paper
email
last changed	2022/06/07 07:54

_id	sigradi2018_1671
id	sigradi2018_1671
authors	Brito, Michele; de Sá, Ana Isabel; Borges, Jéssica; Rena, Natacha
year	2018
title	IndAtlas - Technopolitic platform for urban investigation
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. 1305-1312
summary	This article presents the project of the urban research platform IndAtlas, currently in early development stage by UFMG’s Research Group Indisciplinar. Through the association of crowdsourcing tools, a spatial database and the production of visualizations of different types, it is intended to create a Web platform for collecting, analyzing and depicting information about processes of production and transformation of urban space. It is proposed that the phenomena (themes) investigated in the platform are approached mainly from four axes: 1) spatial / territorial; 2) temporal; 3) social; 4) communicational. To do this, we try to combine online collaborative maps with the production of dynamic timelines and visualizations of networks of social actors (graphs), connected with social networks and Wiki pages. The article will address the development of Indisciplinar’s working method, which guided the proposal of the platform, as well as the functional and technical aspects to be observed for its implementation, the proposed architecture and the importance of interoperability for the project. Finally, the inquiries derived from the first test experiment of an IndAtlas test prototype will be presented. The experiment took place in a workshop belonging to the Cidade Eletrônika 2018 Festival – an arts and technology event. The workshop was offered in January of the same year, and it proposed a collaborative cartography of the Santa Tereza neighborhood, in Belo Horizonte / MG – a traditional neighborhood of great importance for historical heritage, currently subject to great real estate pressure and the focus of a series of territorial disputes.
keywords	IndAtlas, Crowdsourcing, Urban Technopolitics,, Digital Cartographies,, Spatial Data.
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
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	ecaade2018_187
id	ecaade2018_187
authors	Chatzivasileiadi, Aikaterini, Hosney Lila, Anas M., Lannon, Simon and Jabi, Wassim
year	2018
title	The Effect of Reducing Geometry Complexity on Energy Simulation Results
doi	https://doi.org/10.52842/conf.ecaade.2018.2.559
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. 559-568
summary	Accuracy and time are metrics inherently associated with the design process and the energy performance simulation of buildings. The accurate representation of the building is an essential requirement for energy analysis, which comes with the expense of time; however, this is in contrast with the need to minimise the simulation time in order to make it compatible with design times. This is a particularly interesting aspect in the case of complex geometries, which are often simplified for use in building energy performance simulation. The effects of this simplification on the accuracy of simulation results are not usually reported. This paper explored these effects through a systematic analysis of several test cases. The results indicate that the use of orthogonal prisms as simplified surrogates for buildings with complex shapes presents a worst-case scenario that should be avoided where possible. A significant reduction of geometry complexity by at least 50% can also be achieved with negligible effects on simulation results, while minimising the time requirements. Accuracy, however, deteriorates rapidly below a critical threshold.
keywords	Building performance simulation; Energy analysis; Geometry simplification
series	eCAADe
email
last changed	2022/06/07 07:55

_id	ecaade2018_255
id	ecaade2018_255
authors	Danesh, Foroozan, Baghi, Ali and Kalantari, Saleh
year	2018
title	Programmable Paper Cutting - A Method to Digitally Fabricate Transformable, Complex Structural Geometry
doi	https://doi.org/10.52842/conf.ecaade.2018.2.489
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. 489-498
summary	This paper presents a computational approach to generating architectural forms for large spanning structures based on a "paper-cutting" technique. Using this approach, a flat sheet is cut and scored in such a way that a small application of force prompts it to expand into a three-dimensional structure. Our computational system can be used to estimate optimal cutting patterns and to predict the resulting structural characteristics, thereby providing greater rigor to what has previously been an ad-hoc and experimental design approach. To develop the model, we analyzed paper-cutting techniques, extracted the relevant formative parameters, and created a simulation using finite element analysis. We then used a data-mining approach through 400 simulations and applied a regression analysis to create a prediction model. Given a small number of input variables from the designer, this model can rapidly and precisely predict the transformation volume of a paper-cutting pattern. Additional structural characteristics will be modelled in future work. The use of this tool makes paper-cut design approaches more practical by changing a non-systematic, labor-intensive design process into a more precise and efficient one.
keywords	Paper-cut?; Transformable geometry; Design method; Model prediction; Data mining; Regression analysis
series	eCAADe
email
last changed	2022/06/07 07:55

_id	acadia23_v1_34
id	acadia23_v1_34
authors	Gascon Alvarez, Eduardo; Curth, Alexander (Sandy); Feickert, Kiley; Martinez Schulte, Dinorah; Mueller, Caitlin; Ismail, Mohamed
year	2023
title	Algorithmic Design for Low-Carbon, Low-Cost Housing Construction in Mexico
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 1: Projects Catalog of the 43rd Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-8-1]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 34-38.
summary	Mexico is one of the most urbanized countries in the Global South, and simultaneously faces a rapidly increasing population and a deluge of inadequate housing (URBANET 2019). In 2016, it was estimated that 40 percent of all private residences in Mexico were considered inadequate by UN-Habitat (UN-Habitat 2018). As informal housing constitutes over half of all Mexican housing construction, the most vulnerable groups of the population are particularly impacted. Therefore, there is a serious need to innovate in the area of low-cost building construction for housing in Mexico. This research explores how shape-optimized concrete and earth construction could help provide adequate housing without jeopardizing the country’s commitment to sustainability.
series	ACADIA
type	project
email
last changed	2024/04/17 13:58

_id	ijac201816102
id	ijac201816102
authors	Harmon, Brendan A.; Anna Petrasova, Vaclav Petras, Helena Mitasova and Ross Meentemeyer
year	2018
title	Tangible topographic modeling for landscape architects
source	International Journal of Architectural Computing vol. 16 - no. 1, 4-21
summary	We present Tangible Landscape—a technology for rapidly and intuitively designing landscapes informed by geospatial modeling, analysis, and simulation. It is a tangible interface powered by a geographic information system that gives three- dimensional spatial data an interactive, physical form so that users can naturally sense and shape it. Tangible Landscape couples a physical and a digital model of a landscape through a real-time cycle of physical manipulation, three-dimensional scanning, spatial computation, and projected feedback. Natural three-dimensional sketching and real-time analytical feedback should aid landscape architects in the design of high performance landscapes that account for physical and ecological processes. We conducted a series of studies to assess the effectiveness of tangible modeling for landscape architects. Landscape architecture students, academics, and professionals were given a series of fundamental landscape design tasks—topographic modeling, cut-and-fill analysis, and water flow modeling. We assessed their performance using qualitative and quantitative methods including interviews, raster statistics, morphometric analyses, and geospatial simulation. With tangible modeling, participants built more accurate models that better represented morphological features than they did with either digital or analog hand modeling. When tangibly modeling, they worked in a rapid, iterative process informed by real-time geospatial analytics and simulations. With the aid of real-time simulations, they were able to quickly understand and then manipulate how complex topography controls the flow of water.
keywords	Human–computer interaction, tangible interfaces, tangible interaction, landscape architecture, performance, geospatial modeling, topographic modeling, hydrological modeling
series	journal
email
last changed	2019/08/07 14:03

_id	acadia23_v3_169
id	acadia23_v3_169
authors	Kanngieser, AM
year	2023
title	Ethics and Ecocidal Listening: Oceanic Refractions as an Artistic Case Study
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 3: Proceedings of the 43rd Annual Conference for the Association for Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9891764-1-0]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 24-32.
summary	In 2018 I was invited to visit the archipelago of Kiribati, located in the Pacific Ocean around 1000 miles from Hawaii. A big ocean state, Kiribati holds a land mass of around 315 sq. miles and an oceanic economic zone of 1,328,890 sq. mi. Tarawa, the most inhabited of the islands peaks at around 3 m above sea level. I went to Kiribati in part to meet with Dr Teweiariki Teaero, a renowned scholar, poet and educator who had directed the Oceania Center at the University of the South Pacific in Fiji for many years before returning to his homeland where at the time he had been planning on running for government. Teweiariki spoke with me at length about the status of Kiribati as one of the already most critically affected frontline nations. I asked him what was a lesson for non-Pacific Islanders to learn about understanding everyday life there. He said to me “Two ears, one mouth, don’t talk too much. Learn to listen more. Not only to hear, but to be able to develop another thing and that is to be able to interpret. These things are different, they occur at different levels. The hearing and the interpretation of the sound…it’s very much part of our world” (Teaero 2018).
series	ACADIA
type	keynote
email
last changed	2024/04/17 14:00

_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
doi	https://doi.org/10.52842/conf.caadria.2018.2.287
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
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	caadria2018_018
id	caadria2018_018
authors	Lin, Yuming and Huang, Weixin
year	2018
title	Social Behavior Analysis in Innovation Incubator Based on Wi-Fi Data - A Case Study on Yan Jing Lane Community
doi	https://doi.org/10.52842/conf.caadria.2018.2.197
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. 197-206
summary	Innovation incubator is an emerging kind of office space which focuses on promoting social interaction in the space. From the perspective of environmental behavior, the complex relationship between a particular space form and the social interactions is well worth exploring. Based on Wi-Fi positioning data, this paper examined the spatial and temporal behavior in innovation incubators. Using the interdisciplinary social networks analysis, this paper further analyzed the social interactions in this space, mining out social structures such as gathering and community, and analyzing the relationship between these structures and spaces. The result shows that human behavior in innovation incubators has some interesting characteristics, and the social structures are closely linked with the functional area of innovation incubator. This paper provides a new perspective and introduces interdisciplinary approaches to study the social behaviors in a particular space form, which has great potential in future research.
keywords	environmental behavior study; social behavior analysis; innovation incubator; Wi-Fi IPS; social network
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	sigradi2018_1451
id	sigradi2018_1451
authors	Massara Rocha, Bruno; Simão de Lima, Camilo
year	2018
title	Open Design: Principles, Interfaces and Values Analysis
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. 1241-1249
summary	This article discuss in which terms design, distribution and production processes have changed after the great technological revolution in a post-industrial era in order to become more democratic and easily shared. After a brief analysis of the economic impact brought by this digital revolution, the article presents newly design values and production environments that emerged from it. We focus in the Open Design movement to show how its process introduce new ways to create and produce architecture. The main idea is to enlighten and explain how Open Design enhances innovation and foster a new democratic practice based on freedom, collaboration and experimentation.
keywords	Shared project; Open design; Maker movement; Digital fabrication; Cognitive capitalism
series	SIGRADI
email
last changed	2021/03/28 19:58

_id	acadia18_434
id	acadia18_434
authors	Meibodi, Mania Aghaei ; Jipa, Andrei; Giesecke, Rena; Shammas, Demetris; Bernhard, Mathias; Leschok, Matthias; Graser, Konrad; Dillenburger, Benjamin
year	2018
title	Smart Slab. Computational design and digital fabrication of a lightweight concrete slab
doi	https://doi.org/10.52842/conf.acadia.2018.434
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. 434-443
summary	This paper presents a computational design approach and novel digital fabrication method for an optimized lightweight concrete slab using a 3D-printed formwork. Smart Slab is the first concrete slab fabricated with a 3D-printed formwork. It is a lightweight concrete slab, displaying three-dimensional geometric differentiation on multiple scales. The optimization of slab systems can have a large impact on buildings: more compact slabs allow for more usable space within the same building volume, refined structural concepts allow for material reduction, and integrated prefabrication can reduce complexity on the construction site. Among the main challenges is that optimized slab geometries are difficult to fabricate in a conventional way because non-standard formworks are very costly. Novel digital fabrication methods such as additive manufacturing of concrete can provide a solution, but until now the material properties and the surface quality only allow for limited applications. The fabrication approach presented here therefore combines the geometric freedom of 3D binderjet printing of formworks with the structural performance of fiber reinforced concrete. Using 3D printing to fabricate sand formwork for concrete, enables the prefabrication of custom concrete slab elements with complex geometric features with great precision. In addition, space for building systems such as sprinklers and Lighting could be integrated in a compact way. The design of the slab is based on a holistic computational model which allows fast design optimization and adaptation, the integration of the planning of the building systems, and the coordination of the multiple fabrication processes involved with an export of all fabrication data. This paper describes the context, design drivers, and digital design process behind the Smart Slab, and then discusses the digital fabrication system used to produce it, focusing on the 3D-printed formwork. It shows that 3D printing is already an attractive alternative for custom formwork solutions, especially when strategically combined with other CNC fabrication methods. Note that smart slab is under construction and images of finished elements can be integrated within couple of weeks.
keywords	full paper, digital fabrication, computation, generative design, hybrid practices
series	ACADIA
type	paper
email
last changed	2022/06/07 07:58

_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_194
id	ecaade2018_194
authors	Paixao, Jose, Fend, Florian and Hirschberg, Urs
year	2018
title	Break It Till You Make It - A design studio for problem-finding
doi	https://doi.org/10.52842/conf.ecaade.2018.1.753
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. 753-762
summary	In a context where architectural education is undergoing great transformations due to the impact of digital technology, the authors present a design studio model that rather than teaching how to operate the tool en vogue focuses on the formulation of questions. Traditional pedagogic practices have privileged answers in knowledge production, but an alternative is proposed. A methodology was devised in which problem-finding is moved forward by an iterative process of experimental making. This was tested in Winter 2017 with results showing a diversity in questions raised, but also the premature discontinuation of several paths of inquiry. Only one completed all 6 planned iterations and benefited from the final, in which the building of a 1:1 prototype informed its research focus. The conclusions highlight the contribution of this model in preparing future practitioners with an attitude of inquiry and drive to experiment that will resist obsoleteness from rapid technological developments.
keywords	Architectural Education; Design Studio; Problem-Based Learning; Material Systems; Digital Fabrication; Wood Construction
series	eCAADe
email
last changed	2022/06/07 08:00

_id	acadia18_56
id	acadia18_56
authors	Suzuki, Seiichi; Knippers, Jan
year	2018
title	Digital Vernacular Design. Form-finding at the edge of realities
doi	https://doi.org/10.52842/conf.acadia.2018.056
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. 56-65
summary	Introducing design innovation within structural systems normally requires the development of novel design strategies for exploring different solutions in which optimized shapes can be derived from material behaviors and force principles. This condition is particularly important for bending- and form-active structures where intricate geometrical arrangements can be produced by combining simple discrete components. The use of real-time physics-based simulations as design tools has rapidly become popular for addressing these problems. However, all numerical methods tend to lack the interactive and playful characteristics that are intrinsic in traditional analogue methods. Because of this, the intuitive and creative characteristics of digital design processes are limited, and therefore a gap between analogue and digital design practices is progressively created. In this paper, we present a design approach we call "digital vernacular," which involves the combination of interactive and playful characteristics of empirical and experimental methods within numerical models. This approach originates from the technical framework of topology-driven form-finding, which addresses the activation of topologic spaces during real-time physics-based simulations. The presented study is placed within a larger body of research regarding simulation-based design and aims to bridge the gap between analogue and digital design practices. Two computational frameworks based on particle-based methods and a set of research projects are presented to illustrate our design approach.
keywords	work in progress, design methods and information processing, form finding, physics, representation
series	ACADIA
type	paper
email
last changed	2022/06/07 07:56

_id	caadria2018_000
id	caadria2018_000
authors	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.)
year	2018
title	CAADRIA 2018: Learning, Prototyping and Adapting, Volume 1
doi	https://doi.org/10.52842/conf.caadria.2018.1
source	Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 1, Tsinghua University, Beijing, China, 17-19 May 2018, 578 p.
summary	Rapidly evolving technologies are increasingly shaping our societies as well as our understanding of the discipline of architecture. Computational developments in fields such as machine learning and data mining enable the creation of learning networks that involve architects alongside algorithms in developing new understanding. Such networks are increasingly able to observe current social conditions, plan, decide, act on changing scenarios, learn from the consequences of their actions, and recognize patterns out of complex activity networks. While digital technologies have already enabled architecture to transcend static physical boxes, new challenges of the present and visions for the future continue to call for both innovative responses integrating emerging technologies into experimental architectural practice and their critical reflection. In this process, the capability of adapting to complex social and environmental challenges through learning, prototyping and verifying solution proposals in the context of rapidly shifting realities has become a core challenge to the architecture discipline. Supported by advancing technologies, architects and researchers are creating new frameworks for digital workflows that engage with new challenges in a variety of ways. Learning networks that recognize patterns from massive data, rapid prototyping systems that flexibly iterate innovative physical solutions, and adaptive design methods all contribute to a flexible and networked digital architecture that is able to learn from both past and present to evolve towards a promising vision of the future.
series	CAADRIA
last changed	2022/06/07 07:49

_id	caadria2018_001
id	caadria2018_001
authors	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.)
year	2018
title	CAADRIA 2018: Learning, Prototyping and Adapting, Volume 2
doi	https://doi.org/10.52842/conf.caadria.2018.2
source	Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, 610 p.
summary	Rapidly evolving technologies are increasingly shaping our societies as well as our understanding of the discipline of architecture. Computational developments in fields such as machine learning and data mining enable the creation of learning networks that involve architects alongside algorithms in developing new understanding. Such networks are increasingly able to observe current social conditions, plan, decide, act on changing scenarios, learn from the consequences of their actions, and recognize patterns out of complex activity networks. While digital technologies have already enabled architecture to transcend static physical boxes, new challenges of the present and visions for the future continue to call for both innovative responses integrating emerging technologies into experimental architectural practice and their critical reflection. In this process, the capability of adapting to complex social and environmental challenges through learning, prototyping and verifying solution proposals in the context of rapidly shifting realities has become a core challenge to the architecture discipline. Supported by advancing technologies, architects and researchers are creating new frameworks for digital workflows that engage with new challenges in a variety of ways. Learning networks that recognize patterns from massive data, rapid prototyping systems that flexibly iterate innovative physical solutions, and adaptive design methods all contribute to a flexible and networked digital architecture that is able to learn from both past and present to evolve towards a promising vision of the future.
series	CAADRIA
last changed	2022/06/07 07:49

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