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 633

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

_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
doi	https://doi.org/10.52842/conf.acadia.2018.176
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
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_w12
id	ecaade2018_w12
authors	Rahbar, Morteza
year	2018
title	Application of Artificial Intelligence in Architectural Generative Design
doi	https://doi.org/10.52842/conf.ecaade.2018.1.071
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 71-72
summary	In this workshop, data-driven models will be discussed and how they could change the way architects think, design and analyse. Both supervised and unsupervised learning models will be discussed and different projects will be referred as examples. Deep learning models are the third part of the workshop and more specifically, Generative Adversarial Networks will be mentioned in more detail. The GAN's open a new field of generative models in design which is based on data-driven process and we will go into detail with GANs, their branches and how we could test a sample architecture generative problem with GANs.
keywords	Artificial Intelligence; Machine Learning; Generative Design; Knowledge based Design; GAN
series	eCAADe
email
last changed	2022/06/07 08:00

_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	acadia18_276
id	acadia18_276
authors	Bilotti, Jeremy; Norman, Bennett; Rosenwasser, David; Leo Liu, Jingyang; Sabin, Jenny
year	2018
title	Robosense 2.0. Robotic sensing and architectural ceramic fabrication
doi	https://doi.org/10.52842/conf.acadia.2018.276
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. 276-285
summary	Robosense 2.0: Robotic Sensing and Architectural Ceramic Fabrication demonstrates a generative design process based on collaboration between designers, robotic tools, advanced software, and nuanced material behavior. The project employs fabrication tools which are typically used in highly precise and predetermined applications, but uniquely thematizes the unpredictable aspects of these processes as applied to architectural component design. By integrating responsive sensing systems, this paper demonstrates real-time feedback loops which consider the spontaneous agency and intuition of the architect (or craftsperson) rather than the execution of static or predetermined designs. This paper includes new developments in robotics software for architectural design applications, ceramic-deposition 3D printing, sensing systems, materially-driven pattern design, and techniques with roots in the arts and crafts. Considering the increasing accessibility and advancement of 3D printing and robotic technologies, this project seeks to challenge the erasure of materiality: when mistakes or accidents caused by inconsistencies in natural material are avoided or intentionally hidden. Instead, the incorporation of material and user-input data yields designs which are imbued with more nuanced traces of making. This paper suggests the potential for architects and craftspeople to maintain a more direct and active relationship with the production of their designs.
keywords	full paper, fabrication & robotics, robotic production, digital fabrication, digital craft
series	ACADIA
type	paper
email
last changed	2022/06/07 07:54

_id	ecaade2018_227
id	ecaade2018_227
authors	Chatzitsakyris, Panagiotis
year	2018
title	EventMode - A new computational design tool for integrating human activity data within the architectural design workflow
doi	https://doi.org/10.52842/conf.ecaade.2018.1.649
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. 649-656
summary	Architectural designers are currently depending on a multitude of elaborate computational tools in order to explore, manipulate and visualize the geometric form of their building projects. However, if architecture can be perceived as the manipulation of geometric form in direct relation to human activities and events that take place inside it, then it is evident that such design parameters are not sufficiently represented in the currently available modeling software. Would it be possible to introduce the human activity element in the aforementioned computational tools in a way that informs the design process and improves the final building product? This paper attempts to answer this question by introducing a new experimental design tool that enables the creation of parametric human activity envelopes within three-dimensional digital models. The novel approach is that this tool enables the parametric interaction of these components with the actual building geometry and generates novel visual and data representations of the 3D model. The goal is to improve the decision-making process of architects as well as their clients by enabling them to evaluate and iterate their designs based not only on the building's form but also on the human spatial events that take place inside it. A prototype implementation demonstrates the tool's practical application through three design examples.
series	eCAADe
email
last changed	2022/06/07 07:55

_id	caadria2021_089
id	caadria2021_089
authors	Cristie, Verina, Ibrahim, Nazim and Joyce, Sam Conrad
year	2021
title	Capturing and Evaluating Parametric Design Exploration in a Collaborative Environment - A study case of versioning for parametric design
doi	https://doi.org/10.52842/conf.caadria.2021.2.131
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 2, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 131-140
summary	Although parametric modelling and digital design tools have become ubiquitous in digital design, there is a limited understanding of how designers apply them in their design processes (Yu et al., 2014). This paper looks at the use of GHShot versioning tool developed by the authors (Cristie & Joyce, 2018; 2019) used to capture and track changes and progression of parametric models to understand early-stage design exploration and collaboration empirically. We introduce both development history graph-based metrics (macro-process) and parametric model and geometry change metric (micro-process) as frameworks to explore and understand the captured progression data. These metrics, applied to data collected from three cohorts of classroom collaborative design exercises, exhibited students' distinct modification patterns such as major and complex creation processes or minor parameter explorations. Finally, with the metrics' applicability as an objective language to describe the (collaborative) design process, we recommend using versioning for more data-driven insight into parametric design exploration processes.
keywords	Design exploration; parametric design; history recording; version control; collaborative design
series	CAADRIA
email
last changed	2022/06/07 07:56

_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
doi	https://doi.org/10.52842/conf.ecaade.2018.2.131
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
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	sigradi2018_1879
id	sigradi2018_1879
authors	Danesh Zand, Foroozan; Baghi, Ali; Kalantari, Saleh
year	2018
title	Digitally Fabricating Expandable Steel Structures Using Kirigami Patterns
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. 724-731
summary	This article presents a computational approach to generating architectural forms for large spanning structures based on a “paper-cutting” technique. In this traditional artform, 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. To make these types of expandable structures feasible at an architectural scale, four challenges had to be met during the research. The first was to map the kinetic properties of a paper-cut model, investigating formative parameters such as the width and frequency of cuts to determine how they affect the resulting structure. The second challenge was to computationally simulate the paper-cut structure in an accurate fashion. We accomplished this task using finite element analysis in the Ansys software platform. The third challenge was to create a prediction model that could precisely forecast the characteristics of a paper-cutting pattern. We made significant strides in this demanding task by using a data-mining approach and regression analysis through 400 simulations of various cutting patterns. The final challenge was to verify the efficiency and accuracy of our prediction model, which we accomplished through a series of physical prototypes. Our resulting computational paper-cutting 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.
keywords	Transformable Paper-cut; Design method; Prediction Model; Regression analysis; Physical prototype
series	SIGRADI
email
last changed	2021/03/28 19:58

_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	ijac201816205
id	ijac201816205
authors	Faircloth,Billie; Ryan Welch, Martin Tamke, Paul Nicholas, Phil Ayres, Yulia Sinke, Brandon Cuffy and Mette Ramsgaard Thomsen
year	2018
title	Multiscale modeling frameworks for architecture: Designing the unseen and invisible with phase change materials
source	International Journal of Architectural Computing vol. 16 - no. 2, 104-122
summary	Multiscale design and analysis models promise a robust, multimethod, multidisciplinary approach, but at present have limited application during the architectural design process. To explore the use of multiscale models in architecture, we develop a calibrated modeling and simulation platform for the design and analysis of a prototypical envelope made of phase change materials. The model is mechanistic in nature, incorporates material-scale and precinct scale-attributes, and supports the design of two- and three-dimensional phase change material geometries informed by heat transfer phenomena. Phase change material behavior, in solid and liquid states, dominates the visual and numerical evaluation of the multiscale model. Model calibration is demonstrated using real-time data gathered from the prototype. Model extensibility is demonstrated when it is used by designers to predict the behavior of alternate envelope options. Given the challenges of modeling phase change material behavior in this multiscale model, an additional multiple linear regression model is applied to data collected from the physical prototype in order to demonstrate an alternate method for predicting the melting and solidification of phase change materials.
keywords	Multiscale modeling, mechanistic modeling, heat transfer modeling, phase change materials, model validation
series	journal
email
last changed	2019/08/07 14:03

_id	ecaaderis2018_116
id	ecaaderis2018_116
authors	Giannopoulou, Effimia, Montás Laracuente, Nelson Bernardo and Baquero, Pablo
year	2018
title	Qualitative Study on two Kinetic System Simulations - Experiments Based on Shape Memory Material and Stepper Motors
source	Odysseas Kontovourkis (ed.), Sustainable Computational Workflows [6th eCAADe Regional International Workshop Proceedings / ISBN 9789491207143], Department of Architecture, University of Cyprus, Nicosia, Cyprus, 24-25 May 2018, pp. 95-102
keywords	This investigation intends to compare two computational design experiments operating on two kinetic architecture (Zuk and Clark 1970) design application domains: Shape-memory material (SMM) activated grids and stepper-actuated (SA) responsive skins. In the first one, the goal was to build a standard way of simulating SMM, which can be used as actuators in the construction of kinetic structures and in the second, to simulate and construct a responsive skin according to human interaction using kinect and stepper motors. In both experiments, a similar generative workflow was employed, combining insights from materials and mechanical systems. The objective is to investigate kinetic performance, kinetic design methodology, simulation implementation and applications within the two separate design domains. The general hypothesis is that both experiments become design workflows in themselves as real-time, dynamic modeling systems. A qualitatively study of both sets of cases, is taking in count general, simulation and application aspects, using evaluation criteria including workflow, material quantity, data capture and mechanical properties.
series	eCAADe
email
last changed	2018/05/29 14:33

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

_id	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	ecaade2018_394
id	ecaade2018_394
authors	Rubinowicz, Pawe³
year	2018
title	Application of Available Digital Resources for City Visualisation and Urban Analysis
doi	https://doi.org/10.52842/conf.ecaade.2018.2.595
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. 595-602
summary	The article presents two methods for generating 3D city models. The methods are based on LiDAR and GIS-2D data. The first one enables to create automatically simplified city models that include buildings in the LoD1 standard (excluding roof geometry). The second one provides for generating precise 3D city models including all components of the city space, such as buildings, tall green, city infrastructure. This involves direct transformation of DSM (Digital Surface Model) data as mesh-3D. The analyses presented are based on data available in Poland (in particular GIS). The results of the study can be easily applied for analysing other cities in Europe and elsewhere in the world. The article presents possibilities of using such models to urban analyses. The methods and figures included in the article have been developed using C++ software developed by the author.
keywords	airborne LiDAR scanning; Digital Surface Model; BDOT 10k; city visualization; digital urban analysis; urban design
series	eCAADe
email
last changed	2022/06/07 07:56

_id	ecaade2018_170
id	ecaade2018_170
authors	Shahsavari, Fatemeh, Koosha, Rasool, Vahid, Milad R., Yan, Wei and Clayton, Mark
year	2018
title	Towards the Application of Uncertainty Analysis in Architectural Design Decision-Making - A Probabilistic Model and Applications
doi	https://doi.org/10.52842/conf.ecaade.2018.1.295
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. 295-304
summary	To this day, proper handling of uncertainties -including unknown variables in primary stages of a design, an actual climate data, occupants' behavior, and degradation of material properties over the time- remains as a primary challenge in an architectural design decision-making process. For many years, conventional methods based on the architects' intuition have been used as a standard approach dealing with uncertainties and estimating the resulting errors. However, with buildings reaching great complexity in both their design and material selections, conventional approaches come short to account for ever-existing but unpredictable uncertainties and prove incapable of meeting the growing demand for precise and reliable predictions. This study aims to develop a probability-based framework and associated prototypes to employ uncertainty analysis and sensitivity analysis in architectural design decision-making. The current research explores an advanced physical model for thermal energy exchange characteristics of a hypothetical building and uses it as a test case to demonstrate the proposed probability-based analysis framework. The proposed framework provides a means to employ uncertainty and sensitivity analysis to improve reliability and effectiveness in a buildings design decision-making process.
keywords	Probability-based design decision; uncertainty analysis; sensitivity analysis; building energy consumption model
series	eCAADe
email
last changed	2022/06/07 07:57

_id	sigradi2024_104
id	sigradi2024_104
authors	Spiegelhalter, Thomas
year	2024
title	Integrating AI-SynBio-Digital Twin Futures in Coastal Urban Resilience
source	Herrera, Pablo C., Gómez, Paula, Estevez, Alberto T., Torreblanca-Díaz, David A. Biodigital Intelligent Systems - Proceedings of the XXVIII Conference of the Iberoamerican Society of Digital Graphics (SIGraDi 2024) - ISBN 978-9915-9635-2-5, iBAG-UIC Barcelona, Spain, 13-15 November 2024, pp. 2361–2372
summary	Our research at the Generative AI-SynBio Infrastructures Design Studio, supported by the National Science Foundation (NSF US), Intelligent Europe, and the EU Belmont/Horizon 2020 programs, proposes a pioneering investigation into applying bio-digital intelligent systems in design. Over six years of research, we have targeted low-lying coastal regions, creating bio-inspired code-driven growth and adaptation scenarios with an open-access integrated decision support system app for scenarios from 2018 to 2100. This research interlaces advanced tools and methodologies, including Generative AI, Machine Learning, and Generative Adversarial Networks, merged with natural and synthetic biology data ecosystems. This amalgamation fosters evolutionary growth design algorithms and techniques pivotal for developing resilient, adaptive, and carbon-positive urban landscapes, specifically addressing challenges like sea-level rise, soil subsidence, hurricane-driven storm surges, and heatwaves in low-lying areas of Miami, Fort Myers-Sanibel Island, USA, and Genoa, Italy.
keywords	Bio-Digital Intelligent Systems, Infrastructural Resilience, Generative Adversarial Networks, Synthetic Biology, Evolutionary Algorithms
series	SIGraDi
email
last changed	2025/07/21 11:50

_id	ecaade2018_274
id	ecaade2018_274
authors	Stojanovski, Todor
year	2018
title	City Information Modelling (CIM) and Urban Design - Morphological Structure, Design Elements and Programming Classes in CIM
doi	https://doi.org/10.52842/conf.ecaade.2018.1.507
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. 507-516
summary	In architecture, there was an evolution from Computer-Aided Design (CAD) to Building Information Modelling (BIM), but in urban planning and design, where the Geographic Information Systems (GIS) are often used, there is no such analogy. This paper reviews research in typo-morphology, a branch of urban morphology, procedural modelling of buildings and cities and 3D city modelling and visualizations. It present a generic morphological structure of urban elements and discusses them as programming classes in City Information Modelling (CIM) and the application of CIM in urban design practice. Urban design can be understood as art of juxtaposing and arranging urban design elements such as streets, sidewalks, buildings, building façades, landscaping, etc. Designing implies experimentation and play for design elements within design worlds. CIM should integrate procedural modelling, urban morphological research with toolboxes of design elements and rules of combinations. CIM should serve as digital design worlds where urban designers can play with design elements, model and analyse urban scenarios with generative procedures, rules and typological processes.
keywords	City Information Modelling (CIM); urban morphology; morphological structure; urban design; design element; programming classes
series	eCAADe
email
last changed	2022/06/07 07:56

_id	caadria2018_332
id	caadria2018_332
authors	van Ameijde, Jeroen and Song, Yutao
year	2018
title	Data-Driven Urban Porosity - Incorporating Parameters of Public Space into a Generative Urban Design Process
doi	https://doi.org/10.52842/conf.caadria.2018.1.173
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. 173-182
summary	This paper presents an urban design project for a new city district, using generative design processes in architecture and urbanism developed over several years within academic research and practice work. The paper discusses the opportunities and challenges found when using a data-driven urban design methodology in relation to the complex logistical, social and economical networks of new urban centers.
keywords	Design Methods and Information Processing; Generative System; Simulation & Optimization; Urban Planning and Design; Public Space Design
series	CAADRIA
email
last changed	2022/06/07 07:58

_id	ecaade2018_232
id	ecaade2018_232
authors	Al Bondakji, Louna, Chatzi, Anna-Maria, Heidari Tabar, Minoo, Wesseler, Lisa-Marie and Werner, Liss C.
year	2018
title	VR-visualization of High-dimensional Urban Data
doi	https://doi.org/10.52842/conf.ecaade.2018.2.773
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. 773-780
summary	The project aims to investigate the possibility of VR in a combination of visualizing high-dimensional urban data. Our study proposes a data-based tool for urban planners, architects, and researchers to 3D visualize and experience an urban quarter. Users have a possibility to choose a specific part of a city according to urban data input like "buildings, streets, and landscapes". This data-based tool is based on an algorithm to translate data from Shapefiles (.sh) in a form of a virtual cube model. The tool can be scaled and hence applied globally. The goal of the study is to improve understanding of the connection and analysis of high-dimensional urban data beyond a two-dimensional static graph or three-dimensional image. Professionals may find an optimized condition between urban data through abstract simulation. By implementing this tool in the early design process, researchers have an opportunity to develop a new vision for extending and optimizing urban materials.
keywords	Abstract Urban Data Visualization; Virtual Reality; Geographical Information System
series	eCAADe
email
last changed	2022/06/07 07:54

_id	sigradi2023_39
id	sigradi2023_39
authors	Borges, Marina, Karantino, Lucas and Gorges, Diego
year	2023
title	Walkability: Digital Parametric Process for Analyzing and Evaluating Walkability Criteria in Peripheral Central Regions of Belo Horizonte
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. 397–408
summary	According to one of the Sustainable Development Goals (UN, 2018), it is important for cities to be inclusive, safe, resilient, and sustainable. Therefore, it is necessary to value pedestrians and consequently active mobility, giving priority to the concepts of the Transportation Oriented Development (TOD) methodology. Although the Master Plan (BELO HORIZONTE, 2019) proposes that areas located in regional centralities are enhancing active mobility, can residents actually benefit from these resources at a walkable distance to access basic services? Thus, the aim of this research is to utilize digital technologies to visualize, analyze, and assess pedestrians' access conditions to commerce and basic services, identifying areas lacking infrastructure. The goal is for the model to serve as a reference for the development of public policies. To achieve this, metadata was used for parametric modeling to study walkability in the peripheral region of the city of Belo Horizonte.
keywords	Walkability, Urban Data Analysis, Urban Design, Parametric Urbanism, Algorithmic Logic
series	SIGraDi
email
last changed	2024/03/08 14:07

For more results click below: