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	ijac201917103
id	ijac201917103
authors	Bejarano, Andres; and Christoph Hoffmann
year	2019
title	A generalized framework for designing topological interlocking configurations
source	International Journal of Architectural Computing vol. 17 - no. 1, 53-73
summary	A topological interlocking configuration is an arrangement of pieces shaped in such a way that the motion of any piece is blocked by its neighbors. A variety of interlocking configurations have been proposed for convex pieces that are arranged in a planar space. Published algorithms for creating a topological interlocking configuration start from a tessellation of the plane (e.g. squares colored as a checkerboard). For each square S of one color, a plane P through each edge E is considered, tilted by a given angle ? against the tessellated plane. This induces a face F supported by P and limited by other such planes nearby. Note that E is interior to the face. By adjacency, the squares of the other color have similarly delimiting faces. This algorithm generates a topological interlocking configuration of tetrahedra or antiprisms. When checked for correctness (i.e. for no overlap), it rests on the tessellation to be of squares. If the tessellation consists of rectangles, then the algorithm fails. If the tessellation is irregular, then the tilting angle is not uniform for each edge and must be determined, in the worst case, by trial and error. In this article, we propose a method for generating topological interlocking configurations in one single iteration over the tessellation or mesh using a height value and a center point type for each tile as parameters. The required angles are a function of the given height and selected center; therefore, angle choices are not required as an initial input. The configurations generated using our method are compared against the configurations generated using the angle-choice approach. The results show that the proposed method maintains the alignment of the pieces and preserves the co-planarity of the equatorial sections of the pieces. Furthermore, the proposed method opens a path of geometric analysis for topological interlocking configurations based on non-planar tessellations.
keywords	Topological interlocking, surface tessellation, irregular geometry, parametric design, convex assembly
series	journal
email
last changed	2019/08/07 14:04

_id	acadia19_554
id	acadia19_554
authors	Farzaneh, Ali; Weinstock, Michael
year	2019
title	Mathematical Modeling of Cities as Complex Systems
doi	https://doi.org/10.52842/conf.acadia.2019.554
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. 554-563
summary	Within the domain of computational modelling for cities, the study of complex systems has stimulated a body of research (through mathematical and scientific modelling) that has given greater insight into the characteristic of cities. These characteristics share principles in their hierarchical organisation and formation over time with that of complex living systems. The central focus of the research lies in two parts: the first is the understanding of cities as complex systems that share principles with complex living systems; the second is the computational modelling of cities as complex systems. This paper presents a computational model capable of generating urban tissues of differentiated spatial and morphological patterns that emerge over time. The generative process is driven by simultaneous interaction and exchanges between block and network systems.
series	ACADIA
type	normal paper
email
last changed	2022/06/07 07:55

_id	caadria2019_298
id	caadria2019_298
authors	Karoji, Gen, Hotta, Kensuke, Hotta, Akito and Ikeda, Yasushi
year	2019
title	Pedestrian Dynamic Behaviour Modeling - An application to commercial environment using RNN framework
doi	https://doi.org/10.52842/conf.caadria.2019.1.281
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 1, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 281-290
summary	The research of developing and improving pedestrian simulation model is essential in the process of analysing, evaluating and generating the architectural spaces that can not only satisfy circulation design condition but also promote sales by attracting customers. In terms of programming the simulation for commercial environment, current study attempts to use shortest-path algorithm generally and these results suggested that the model can reproduce approximate real trajectory within given environment. However, these studies also mentioned about necessity of considering shopper internal state and visual field. In this paper, in order to further incorporate the dynamic internal state (memory) into simulation model, we propose using iterative algorithm based on recurrent neural network (RNN) framework which allow it to exhibit temporal dynamic behaviour for a time sequence. Finally, we demonstrate the effectiveness of these algorithms we introduce and assess the combination of multiple algorithms and calibration of probability by comparing with trajectories of the experiment.
keywords	Pedestrian simulation; Algorithm; RNN; Commercial environment
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	caadria2019_143
id	caadria2019_143
authors	Kato, Yuri and Matsukawa, Shohei
year	2019
title	Development of Generating System for Architectural Color Icons Using Google Map Platform and Tensorflow-Segmentation
doi	https://doi.org/10.52842/conf.caadria.2019.2.081
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 2, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 81-90
summary	In this research, the goal is to develop a generating system for architectural color icons using Google Map Platform and Tensorflow-Segmentation. There has been no case of developing a system that allows users to visualize the color tendency of buildings as architectural color icons for each building element from images of various regions. It is considered meaningful to be able to create criteria for decision making in architecture and the urban design by developing a system to clarify the current state of the architectural colors. It will contribute a rise in the consciousness of landscape conservation and be essential for the design of architectures and public objects. This paper includes the explanation of development method, use experiments, and consideration of five problems among architectural color icons creation. It is assumed that the accuracy of the present system will be better as the technology improves.
keywords	Google street view; machine learning; image segmentation; color palette; color analysis
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	ecaadesigradi2019_339
id	ecaadesigradi2019_339
authors	Kinugawa, Hina and Takizawa, Atsushi
year	2019
title	Deep Learning Model for Predicting Preference of Space by Estimating the Depth Information of Space using Omnidirectional Images
doi	https://doi.org/10.52842/conf.ecaade.2019.2.061
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 2, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 61-68
summary	In this study, we developed a method for generating omnidirectional depth images from corresponding omnidirectional RGB images of streetscapes by learning each pair of omnidirectional RGB and depth images created by computer graphics using pix2pix. Then, the models trained with different series of images shot under different site and weather conditions were applied to Google street view images to generate depth images. The validity of the generated depth images was then evaluated visually. In addition, we conducted experiments to evaluate Google street view images using multiple participants. We constructed a model that estimates the evaluation value of these images with and without the depth images using the learning-to-rank method with deep convolutional neural network. The results demonstrate the extent to which the generalization performance of the streetscape evaluation model changes depending on the presence or absence of depth images.
keywords	Omnidirectional image; depth image; Unity; Google street view; pix2pix; RankNet
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:52

_id	caadria2019_449
id	caadria2019_449
authors	Lin, Yuqiong, Yao, Jiawei, Huang, Chenyu and Yuan, Philip F.
year	2019
title	The Future of Environmental Performance Architectural Design Based on Human-Computer Interaction - Prediction Generation Based on Physical Wind Tunnel and Neural Network Algorithms
doi	https://doi.org/10.52842/conf.caadria.2019.2.633
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 2, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 633-642
summary	As the medium of the environment, a building's environment performance-based generative design cannot be separated from intelligent data processing. Sustainable building design should seek an optimized form of environmental performance through a complete set of intelligent induction, autonomous analysis and feedback systems. This paper analyzed the trends in architectural design development in the era of algorithms and data and the status quo of building generative design based on environmental performance, as well as highlighting the importance of physical experiments. Furthermore, a design method for self-generating environmental performance of urban high-rise buildings by applying artificial intelligence neural network algorithms to a customized physical wind tunnel is proposed, which mainly includes a morphology parameter control and environmental data acquisition system, code translation of environmental evaluation rules and architecture of a neural network algorithm model. The design-oriented intelligent prediction can be generated directly from the target environmental requirements to the architectural forms.
keywords	Physical wind tunnel; neural network algorithms; dynamic model; environmental performance; building morphology self-generation
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	sigradi2023_416
id	sigradi2023_416
authors	Machado Fagundes, Cristian Vinicius, Miotto Bruscato, Léia, Paiva Ponzio, Angelica and Chornobai, Sara Regiane
year	2023
title	Parametric environment for internalization and classification of models generated by the Shap-E tool
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. 1689–1698
summary	Computing has been increasingly employed in design environments, primarily to perform calculations and logical decisions faster than humans could, enabling tasks that would be impossible or too time-consuming to execute manually. Various studies highlight the use of digital tools and technologies in diverse methods, such as parametric modeling and evolutionary algorithms, for exploring and optimizing alternatives in architecture, design, and engineering (Martino, 2015; Fagundes, 2019). Currently, there is a growing emergence of intelligent models that increasingly integrate computers into the design process. Demonstrating great potential for initial ideation, artificial intelligence (AI) models like Shap-E (Nichol et al., 2023) by OpenAI stand out. Although this model falls short of state-of-the-art sample quality, it is among the most efficient orders of magnitude for generating three-dimensional models through AI interfaces, offering practical balance for certain use cases. Thus, aiming to explore this gap, the presented study proposes an innovative design agency framework by employing Shap-E connected with parametric modeling in the design process. The generation tool has shown promising results; through generations of synthetic views conditioned by text captions, its final output is a mesh. However, due to the lack of topological information in models generated by Shap-E, we propose to fill this gap by transferring data to a parametric three-dimensional surface modeling environment. Consequently, this interaction's use aims to enable the transformation of the mesh into quantifiable surfaces, subject to collection and optimization of dimensional data of objects. Moreover, this work seeks to enable the creation of artificial databases through formal categorization of parameterized outputs using the K-means algorithm. For this purpose, the study methodologically orients itself in a four-step exploratory experimental process: (1) creation of models generated by Shap-E in a pressing manner; (2) use of parametric modeling to internalize models into the Grasshopper environment; (3) generation of optimized alternatives using the evolutionary algorithm (Biomorpher); (4) and classification of models using the K-means algorithm. Thus, the presented study proposes, through an environment of internalization and classification of models generated by the Shap-E tool, to contribute to the construction of a new design agency methodology in the decision-making process of design. So far, this research has resulted in the generation and classification of a diverse set of three-dimensional shapes. These shapes are grouped for potential applications in machine learning, in addition to providing insights for the refinement and detailed exploration of forms.
keywords	Shap-E, Parametric Design, Evolutionary Algorithm, Synthetic Database, Artificial Intelligence
series	SIGraDi
email
last changed	2024/03/08 14:09

_id	caadria2019_318
id	caadria2019_318
authors	Martinho, Helena, BelÃ©m, Catarina, LeitÃ£o, AntÃ³nio, Loonen, Roel and Gomes, M. GlÃ³ria
year	2019
title	Algorithmic Design and Performance Analysis of Adaptive FaÃ§ades
doi	https://doi.org/10.52842/conf.caadria.2019.1.685
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 1, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 685-694
summary	Building performance simulation tools have the potential for aiding the decision-making process in early design stages of an architectural project. As traditional simulation tools are based on a static design and adaptive faÃ§ades encompass an envisioned movement of construction elements, there is a lack of supporting tools and workflows that can correctly evaluate the performance of such building envelopes at an early stage. The presented ongoing research focuses on developing efficient parametric performance-based approaches for assessing the energy consumption in buildings with adaptive faÃ§ades, combining generative architectural design and performance analysis in a seamless workflow. To this end, we combine a new algorithmic design research tool with the well-established whole-building simulation engine EnergyPlus. The purpose of linking both tools lies in the possibility of generating and simulating models with adaptive faÃ§ade mechanisms through a single script, evaluating and using the simulation results to adjust the model's parameters and develop optimized control strategies.
keywords	Building performance simulation; Adaptive faÃ§ades; Algorithmic design; Energy analysis
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	acadia19_370
id	acadia19_370
authors	Mohammad, Ali; Beorkrem, Christopher; Ellinger, Jefferson
year	2019
title	Hybrid Elevations using GAN Networks
doi	https://doi.org/10.52842/conf.acadia.2019.370
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. 370-379
summary	This project is an attempt to develop and test a method for generating one-sided hybrid exterior building elevations using designer’s base criteria and design rule sets as inputs in an advanced artificial intelligence network. Architects are using computational design to expedite the iteration process in an efficient manner. Optimization techniques utilizing genetic solvers allow designers to explore broad sets of iterations within a predefined subset. However, with the application of artificial intelligence networks these fields of exploration can be expanded upon to develop ranges of exploration which can explore iterations outside of typical ranges. This paper explores the use of Generative Adversarial Networks (GAN) to explore and demonstrate their possible capabilities to typical design problems. In this instance we are exploring their application in the development of architectural elevations.
series	ACADIA
type	normal paper
email
last changed	2022/06/07 07:58

_id	caadria2020_259
id	caadria2020_259
authors	Rhee, Jinmo, Veloso, Pedro and Krishnamurti, Ramesh
year	2020
title	Integrating building footprint prediction and building massing - an experiment in Pittsburgh
doi	https://doi.org/10.52842/conf.caadria.2020.2.669
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 669-678
summary	We present a novel method for generating building geometry using deep learning techniques based on contextual geometry in urban context and explore its potential to support building massing. For contextual geometry, we opted to investigate the building footprint, a main interface between urban and architectural forms. For training, we collected GIS data of building footprints and geometries of parcels from Pittsburgh and created a large dataset of Diagrammatic Image Dataset (DID). We employed a modified version of a VGG neural network to model the relationship between (c) a diagrammatic image of a building parcel and context without the footprint, and (q) a quadrilateral representing the original footprint. The option for simple geometrical output enables direct integration with custom design workflows because it obviates image processing and increases training speed. After training the neural network with a curated dataset, we explore a generative workflow for building massing that integrates contextual and programmatic data. As trained model can suggest a contextual boundary for a new site, we used Massigner (Rhee and Chung 2019) to recommend massing alternatives based on the subtraction of voids inside the contextual boundary that satisfy design constraints and programmatic requirements. This new method suggests the potential that learning-based method can be an alternative of rule-based design methods to grasp the complex relationships between design elements.
keywords	Deep Learning; Prediction; Building Footprint; Massing; Generative Design
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	caadria2019_640
id	caadria2019_640
authors	Zhang, Ruocheng, Tong, Hanshuang, Huang, Weixin and Zhang, Runzhou
year	2019
title	A Generative Design Method for the Functional Layout of Town Planning based on Multi-Agent System
doi	https://doi.org/10.52842/conf.caadria.2019.2.231
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 2, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 231-240
summary	In recent years, with the development of artificial intelligence and digital architecture, more architects begin to wonder how to generate urban planning and urban design through computational method. For the purpose of generating urban planning digitally using computational algorithms, we design a series of algorithms to develop a system that evaluates initial features of the site such as the strength of sunlight, water, landscape. These parameters related to the function zoning of the town were determined based on the data extracted from case studies. These data were integrated into a Markov chain mathematical model for the sake of analyzing the function of grid points. Finally, an algorithm of a multi-agent system was used to optimize the function that could evaluate the grade of each raster point of the town, which could be used to decide the function of a specific region.
keywords	Generative design, Town planning,Multi-agent system, Data analysis
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	cf2019_013
id	cf2019_013
authors	Boychenko, Kristina
year	2019
title	Agency of Interactive Architecture in socio-technological relationship through Actor-Network Theory
source	Ji-Hyun Lee (Eds.) "Hello, Culture!" [18th International Conference, CAAD Futures 2019, Proceedings / ISBN 978-89-89453-05-5] Daejeon, Korea, p. 102
summary	With fast development of new technologies built environment transitioned from a silent background of activities performed by users to another participant of those activities. Agency of interactive architecture is based on interpretation of input data, like users’ actions, their response to the spatial agency, data from environment or other actors, and changing its performance accordingly. Architectural components, environmental conditions and people are all treated as agents and closely correspond to Actor-Network Theory (ANT). This theory generally aims to reveal the complexities of socio-technological world. ANT incorporates a principle of generalized symmetry, it means that human and nonhuman (artifacts, organization structures, etc.) actors are incorporated into the same conceptual framework and assigned equal level of agency. By analysis of the agency of Interactive Architecture through ANT the paper provides insight on social role of this new emerging type of space and its influence on other participants on socio-technological relationship.
keywords	Interactive architecture, Communication, Agency, Social, ActorNetwork Theory
series	CAAD Futures
email
last changed	2019/07/29 14:08

_id	caadria2019_396
id	caadria2019_396
authors	Cao, Rui, Fukuda, Tomohiro and Yabuki, Nobuyoshi
year	2019
title	Quantifying Visual Environment by Semantic Segmentation Using Deep Learning - A Prototype for Sky View Factor
doi	https://doi.org/10.52842/conf.caadria.2019.2.623
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 2, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 623-632
summary	Sky view factor (SVF) is the ratio of radiation received by a planar surface from the sky to that received from the entire hemispheric radiating environment, in the past 20 years, it was more applied to urban-climatic areas such as urban air temperature analysis. With the urbanization and the development of cities, SVF has been paid more and more attention on as the important parameter in urban construction and city planning area because of increasing building coverage ratio to promote urban forms and help creating a more comfortable and sustainable urban residential building environment to citizens. Therefore, efficient, low cost, high precision, easy to operate, rapid building-wide SVF estimation method is necessary. In the field of image processing, semantic segmentation based on deep learning have attracted considerable research attention. This study presents a new method to estimate the SVF of residential environment by constructing a deep learning network for segmenting the sky areas from 360-degree camera images. As the result of this research, an easy-to-operate estimation system for SVF based on high efficiency sky label mask images database was developed.
keywords	Visual environment; Sky view factor; Semantic segmentation; Deep learning; Landscape simulation
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	cf2019_017
id	cf2019_017
authors	Cardoso Llach, Daniel and Javier Argota Sánchez-Vaquerizo
year	2019
title	An Ecology of Conflicts Using Network Analytics to Explore the Data of Building Design
source	Ji-Hyun Lee (Eds.) "Hello, Culture!" [18th International Conference, CAAD Futures 2019, Proceedings / ISBN 978-89-89453-05-5] Daejeon, Korea, p. 131
summary	The scale and socio-technical complexity of contemporary architectural production poses challenges to researchers and practitioners interested in their description and analysis. This paper discusses the novel use of network analysis techniques to study a dataset comprising thousands of design conflicts reported during design coordination of a large project by a group of architects using BIM software. We discuss in detail three approaches to the use of network analysis techniques on these data, showing their potential to offer topological insights about the phenomenon of contemporary architectural design and construction, which complement other forms of architectural analysis.
keywords	Architecture, Network Analysis, Design Ecology, BIM, Data Visualization
series	CAAD Futures
email
last changed	2019/07/29 14:08

_id	caadria2019_259
id	caadria2019_259
authors	Soltani, Sahar, Gu, Ning, Ochoa Paniagua, Jorge, Sivam, Alpana and McGinley, Tim
year	2019
title	A Computational Approach to Measuring Social Impact of Urban Density through Mixed Methods Using Spatial Analysis
doi	https://doi.org/10.52842/conf.caadria.2019.1.321
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 1, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 321-330
summary	While there is a growing interest in using spatial network analysis methods such as Space Syntax to explore the socio-spatial aspects of the built form, some scholars refer to its main limitation of missing the measurements of buildings' fabric and density. Furthermore, new approaches that attempt to address these shortcomings, such as Urban Network Analysis toolbox, do not provide as comprehensive explorations as what Space Syntax does for the street network. Therefore, this paper proposes that a mixed-method applying both the tools in a complementary way enables a deeper understanding of the socio-spatial design metrics addressing density. Employing both tools on two cases of low and high-density neighbourhoods, the results demonstrate that the combination of these tools can minimise the shortcomings of each method individually, and lead to a more comprehensive understanding of socio-spatial design factors in relation with density.
keywords	Urban Network Analysis ; Social Impact; Space Syntax ; UNA Toolbox; Urban Density
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	cf2019_033
id	cf2019_033
authors	Soltani, Sahar; Ning Gu, Jorge Ochoa Paniagua, Alpana Sivam and Tim McGinley
year	2019
title	Investigating the Social Impacts of Highdensity Neighbourhoods through Spatial Analysis
source	Ji-Hyun Lee (Eds.) "Hello, Culture!" [18th International Conference, CAAD Futures 2019, Proceedings / ISBN 978-89-89453-05-5] Daejeon, Korea, p. 255
summary	Studies argue that higher density areas incur social problems such as lack of safety [1], while other studies provide evidence for the positive impact of high-density urban areas, for instance opportunities for social interactions and equal form of accessibility [2]. This paper argues that design factors can mediate the impacts of density on social aspects. Therefore, this study explores the extent to which design factors can be correlated to the social outcomes of different density areas. To do this, data from an empirical study conducted in the UK, which identified the relationship between density and social sustainability through cases of fifteen neighbourhoods, have been utilised. This paper has conducted further analysis based on these cases using a mixed method with spatial analysis tools. Outcomes show that some of the social results in the UK study such as safety are correlated with spatial factors like normalised angular choice. Moreover, the regression model created from the spatial indices can be used to predict the overall social sustainability index reported by the UK study.
keywords	Urban Density, Social Sustainability, Spatial Analysis, Space Syntax, Urban Network Analysis
series	CAAD Futures
email
last changed	2019/07/29 14:15

_id	ecaadesigradi2019_201
id	ecaadesigradi2019_201
authors	Torreblanca-Díaz, David A., Pati?o, Ever, Valencia-Escobar, Andrés and Urdinola, Diana
year	2019
title	Form-finding methodology as strategy for formative research in industrial design education - Experimental techniques for the early creative phases of the product design process
doi	https://doi.org/10.52842/conf.ecaade.2019.1.045
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 1, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 45-54
summary	The experimental work of Antoni Gaudí and Frei Otto have been the precedents of what is currently called form-finding, a methodology based on rules and physical forces of nature that promotes principles of transformation as a result of the relationship between form, material and structure. This text shows the first results of the research titled as Form-finding methodology as strategy for formative research in industrial design education, with an empirical-analytical approach through action-research based method and using collaborative-participatory tools. As a result of the analysis of different cases in the first stage of the research, a basic methodological proposal is made, this methodological proposal is aimed to find new research possibilities for the identification of morphological characteristics to be used in design projects in the early creative phases (ideation and experimentation); the methodological proposal stages are the following: selection of technique, design of the experimentation, experimentation, analysis and discussion.
keywords	Form-finding; Experimental morphology; Industrial design education; Formative research; Action-research
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:58

_id	ecaadesigradi2019_061
id	ecaadesigradi2019_061
authors	Alkadri, Miktha Farid, De Luca, Francesco, Turrin, Michela and Sariyildiz, Sevil
year	2019
title	Making use of Point Cloud for Generating Subtractive Solar Envelopes
doi	https://doi.org/10.52842/conf.ecaade.2019.1.633
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 1, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 633-640
summary	As a contextual and passive design strategy, solar envelopes play a great role in determining building mass based on desirable sun access during the predefined period. With the rapid evolution of digital tools, the design method of solar envelopes varies in different computational platforms. However, current approaches still lack in covering the detailed complex geometry and relevant information of the surrounding context. This, consequently, affects missing information during contextual analysis and simulation of solar envelopes. This study proposes a subtractive method of solar envelopes by considering the geometrical attribute contained in the point cloud of TLS (terrestrial laser scanner) dataset. Integration of point cloud into the workflow of solar envelopes not only increases the robustness of final geometry of existing solar envelopes but also enhances awareness of architects during contextual analysis due to consideration of surface properties of the existing environment.
keywords	point cloud data; solar envelopes; subtractive method; solar access
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:54

_id	ijac201917106
id	ijac201917106
authors	Brown, Nathan C. and Caitlin T. Mueller
year	2019
title	Design variable analysis and generation for performance-based parametric modeling in architecture
source	International Journal of Architectural Computing vol. 17 - no. 1, 36-52
summary	Many architectural designers recognize the potential of parametric models as a worthwhile approach to performance- driven design. A variety of performance simulations are now possible within computational design environments, and the framework of design space exploration allows users to generate and navigate various possibilities while considering both qualitative and quantitative feedback. At the same time, it can be difficult to formulate a parametric design space in a way that leads to compelling solutions and does not limit flexibility. This article proposes and tests the extension of machine learning and data analysis techniques to early problem setup in order to interrogate, modify, relate, transform, and automatically generate design variables for architectural investigations. Through analysis of two case studies involving structure and daylight, this article demonstrates initial workflows for determining variable importance, finding overall control sliders that relate directly to performance and automatically generating meaningful variables for specific typologies.
keywords	Parametric design, design space formulation, data analysis, design variables, dimensionality reduction
series	journal
email
last changed	2019/08/07 14:04

_id	ijac201917303
id	ijac201917303
authors	Heidari, Parvin and Cigdem Polatoglu
year	2019
title	Pen-and-paper versus digital sketching in architectural design education
source	International Journal of Architectural Computing vol. 17 - no. 3, 284–302
summary	This study aimed to compare and evaluate the digital-based sketching versus conventional pen-and-paper sketching through conducting an experiment via protocol study in educational field. To this aim, the linkography analysis technique was used to obatin the related data from the protocol study. Linkography technique allows analyzing design as a system and is capable of tracing the design ideas and their connections; therefore, it facilitated the purposes of the current study. The results demonstrated that designers had a richer design process and more opportunities for generating ideas in the pen-and-paper sketching versus digital sketching. Furthermore, the designers’ performance in the digital media with two-dimensional sketching software was more satisfactory than the digital session with three-dimensional sketching software. However, digital media encouraged designers to make more integration among the ideas.
keywords	Conceptual design, pen-and-paper sketching, digital sketching, linkography
series	journal
email
last changed	2020/11/02 13:34

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