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	ecaade2021_151
id	ecaade2021_151
authors	Zolghadrasli, Niloofar, Hadighi, Mahyar and Costa, Eduardo
year	2021
title	Computational Generation of Hybrid Façades for a Focal Context - The case of Naser-Khosrow Street in Tehran
source	Stojakovic, V and Tepavcevic, B (eds.), Towards a new, configurable architecture - Proceedings of the 39th eCAADe Conference - Volume 2, University of Novi Sad, Novi Sad, Serbia, 8-10 September 2021, pp. 333-340
doi	https://doi.org/10.52842/conf.ecaade.2021.2.333
summary	The purpose of this paper is to use shape grammar methodology to generate contextualized urban façades within the focal context of Naser-Khosrow Street in Iran's capital city of Tehran. The history of Naser-Khosrow Street, which is considered a significant historic urban space, begins in the Safavid period (1735-1501). Yet, the urban history and historical significance of this street have been neglected in recent years. Evidence of a sense of turmoil and incompatibility between the modern and traditional architectural façades featured on the street is easily observed. Against this background, this paper offers façade models generated based on the computational methodology developed by Hadighi and Duarte (2019, 2020) to determine and capture the hybrid expression of European modernist and American traditional styles. In this spirit, the systematic methodology of shape grammar is expanded to the focal urban area of Naser-Khosrow Street to generate new façade layouts referencing the characteristic features of some of the iconic buildings located there.
keywords	Shape Grammar, Naser -Khosrow Street, Façade Design, Generating Hybridity
series	eCAADe
email
last changed	2022/06/07 07:57

_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	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
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
doi	https://doi.org/10.52842/conf.caadria.2019.1.281
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	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
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
doi	https://doi.org/10.52842/conf.ecaade.2019.2.061
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	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
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
doi	https://doi.org/10.52842/conf.caadria.2020.2.669
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	ecaadesigradi2019_409
id	ecaadesigradi2019_409
authors	Ulkucu, Yigitcan and Alacam, Sema
year	2019
title	A Decision Support Framework for FLP in the Context of Industrial Facilities by the Use of BIM
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. 269-278
doi	https://doi.org/10.52842/conf.ecaade.2019.2.269
summary	In today's industrial production environment, an effective solution to the FLP (Facility Layout Problem) plays a significant role in deciding whether a facility will hold a competitive advantage against others by its improved workflow. This advantage comes from an efficient placement of facilities, which mostly contributes to the overall business performance. In addition to that, regarding the need to answer the demands of the dynamic market, facilities need to adapt their processes and adapt their production line as quickly as possible. Therefore, a continuous search for a solution to the FLP is present. Although there are many space allocation programs available both as academic and commercial products, present approaches' availability in the BIM environment is not common yet. This paper introduces a decision support system framework which uses Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) to generate the most appropriate solution in Revit Dynamo environment both in the earlier phases of design and through the life-cycle of the facility. The proposed framework will specifically be responsible for generating solutions for equipment location in serial production facilities. As NSGA-II is a Multi-Objective Evolutionary Algorithm (MOEA), a second optimization criterion is defined as the optimization of the foreman's locations distributed on the shop floor. A Dynamo package named Refinery will hold the optimization and evaluation procedures.
keywords	Facility Layout Problems; NSGA-II; Automated Space Layout
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:57

_id	cf2019_009
id	cf2019_009
authors	Veloso, Pedro; Jinmo Rhee and Ramesh Krishnamurti
year	2019
title	Multi-agent space planning: a literature review (2008-2017)
source	Ji-Hyun Lee (Eds.) "Hello, Culture!" [18th International Conference, CAAD Futures 2019, Proceedings / ISBN 978-89-89453-05-5] Daejeon, Korea, pp. 52-74
summary	In this paper we review the research on multi-agent space planning (MASP) during the period of 2008-2017. By MASP, we refer to space planning (SP) methods based on online mobile agents that map local perceptions to actions in the environment, generating spatial representation. We group two precedents and sixteen recent MASP prototypes into three categories: (1) agents as moving spatial units, (2) agents that occupy a space, and (3) agents that partition a space. In order to compare the prototypes, we identify the occurrence of features in terms of representation, objectives, and control procedures. Upon analysis of occurrences and correlations of features in the types, we present gaps and challenges for future MASP research. We point to the limits of current systems to solve spatial conflicts and to incorporate architectural knowledge. Finally, we suggest that behavioral learning offers a promising path for robust and autonomous MASP systems in the architectural domain.
keywords	Space planning; Agent-based modeling; Multi-agent systems; Generative systems
series	CAAD Futures
email
last changed	2019/07/29 14:08

_id	acadia19_664
id	acadia19_664
authors	Koshelyuk, Daniil; Talaei, Ardeshir; Garivani, Soroush; Markopoulou, Areti; Chronis, Angelo; Leon, David Andres; Krenmuller, Raimund
year	2019
title	Alive
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. 664-673
doi	https://doi.org/10.52842/conf.acadia.2019.664
summary	In the context of data-driven culture, built space still maintains low responsiveness and adaptability. Part of this reality lies in the low resolution of live information we have about the behavior and condition of surfaces and materials. This research addresses this issue by exploring the development of a deformation-sensing composite membrane material system following a bottom-up approach and combining various technologies toward solving related technical issues—exploring conductivity properties of graphene and maximizing utilization within an architecture-related proof-of-concept scenario and a workflow including design, fabrication, and application methodology. Introduced simulation of intended deformation helps optimize the pattern of graphene nanoplatelets (GNP) to maximize membrane sensitivity to a specific deformation type while minimizing material usage. Research explores various substrate materials and graphene incorporation methods with initial geometric exploration. Finally, research introduces data collection and machine learning techniques to train recognition of certain types of deformation (single point touch) on resistance changes. The final prototype demonstrates stable and symmetric readings of resistance in a static state and, after training, exhibits an 88% prediction accuracy of membrane shape on a labeled sample data-set through a pre-trained neural network. The proposed framework consisting of a simulation based, graphene-capturing fabrication method on stretchable surfaces, and includes initial exploration in neural network training shape detection, which combined, demonstrate an advanced approach to embedding intelligence.
series	ACADIA
type	normal paper
email
last changed	2022/06/07 07:51

_id	caadria2019_134
id	caadria2019_134
authors	Li, Yunqin, Zhang, Jiaxin and Yu, Chuanfei
year	2019
title	Intelligent Multi-Objective Optimization Method for Complex Building Layout based on Pedestrian Flow Organization - A case study of People's Court building in Anhui, China
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. 271-280
doi	https://doi.org/10.52842/conf.caadria.2019.1.271
summary	The pedestrian flow of the building influences and determines the layout of the building's plan. For buildings with complex flow such as courts, airports, and stations, mixed flow line and low traffic efficiency are prone to be problems. However, the optimization of the layout of complex flow buildings usually relies on the architect's experience to judge and trials to improve. To overcome these problems, we attempt to establish a parametric model of buildings' plan (taking a typical court building as an example) with information about the different pedestrian flow and functional groups. Based on the Rhino and Grasshopper platform, we take the minimum of different pedestrian flow path length and the maximum of total spatial integration value and the minimum of total spatial entropy value as the starting point, combines pathfinding algorithm, Space Syntax and multi-objective genetic algorithm to optimize space allocation. The result shows that, compared with the original scheme, the intelligent optimised scheme can reduce the spatial waste caused by improper flow organisation, effectively improve space transportation capacity and spatial organization efficiency.
keywords	Intelligent optimisation; space allocation; multi-objective optimization algorithm; Space Syntax; pathfinding algorithm
series	CAADRIA
email
last changed	2022/06/07 07:51

_id	caadria2021_231
id	caadria2021_231
authors	Wong, Kwan Ki Calvin and van Ameijde, Jeroen
year	2021
title	In-Between Spaces: Data-driven Analysis and Generative Design for Public Housing Estate Layouts
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. 397-406
doi	https://doi.org/10.52842/conf.caadria.2021.2.397
summary	As Hong Kong constructs increasingly high-density, high-rise public housing estates to increase land use efficiency, public in-between spaces are more constrained, which impacts the quality of social relations, movements and daily practices of residents (Shelton et al. 2011; Tang et al. 2019). Current planning practices are focused on the achievement of quantitative performance measures, rather than qualitative design considerations that support residents experiences and community interaction. This paper presents a new methodology that combines urban analysis and generative design for the regeneration of social housing estates, based on the spatial and social qualities of their in-between spaces.
keywords	Social Housing; Public Open Space; Generative Design; Urban Planning
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	caadria2019_426
id	caadria2019_426
authors	Lee, Jisun and Lee, Hyunsoo
year	2019
title	Agent-driven Accessibility and Visibility Analysis in Nursing Units
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. 351-360
doi	https://doi.org/10.52842/conf.caadria.2019.1.351
summary	This study investigates the nursing unit design for care quality and efficient operation, evaluating visibility and walking distance of nurses in the different form of layout. Sufficient visibility from nurses' station to patient rooms and corridors can increase nurses' care abilities to understand the needs and movements of patients. The workload and time caused by nurse's walking can be diverted to patient care. Isovist analysis and agent-based simulation are experimented to investigate the effects of spatial layout on visibility and nurses' accessibility to patients. In the isovist analysis, the nurses' station facing patient rooms were more effective in nurse-to-patient visibility. In the nurse's walking trail analysis, uneven walking distance of each nurse appeared due to the asymmetric patient room layout centering the nurses' station and heavy room allocation plan. Understanding the potential impacts of design parameters enables designers to predict possible behaviors in each design alternative and to make effective and efficient design decisions for the occupants. This study underlines the role of the physical environment in the delivery of patient care and nurse's well-being. It presents an evaluation framework integrating syntactic analysis and agent-based simulation to predict the effect of the spatial layouts on the hospital activities.
keywords	Nursing unit design; Isovists; Agent-based modeling; Accessibility; Visibility
series	CAADRIA
email
last changed	2022/06/07 07:52

_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
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
doi	https://doi.org/10.52842/conf.ecaade.2019.1.633
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	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
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
doi	https://doi.org/10.52842/conf.caadria.2019.2.633
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	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
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
doi	https://doi.org/10.52842/conf.caadria.2019.1.685
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	ecaadesigradi2019_233
id	ecaadesigradi2019_233
authors	Noronha Pinto de Oliveira e Sousa, Marcela, Duarte, Jose and Celani, Gabriela
year	2019
title	Urban Street Retrofitting - An Application Study on Bottom-Up Design
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 3, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 287-296
doi	https://doi.org/10.52842/conf.ecaade.2019.3.287
summary	Urban streets will have to be retrofitted to improve walkability and to provide space for a diversity of transport modes. This paper introduces a framework which combines space syntax and shape grammars in a design support method for generating scenarios for urban street retrofitting. A procedure to hierarchize streets and select priority locations for urban street retrofitting is presented. Four different angular choice analyses with decreasing radii are used to derive the hierarchical structure of target urban areas with the aim of triggering shape grammar rules and generating bottom-up intervention designs. The same measure using a local radius to represent walking modal is then used to determine which streets should be retrofitted to improve pedestrian safety and walkability for the largest number of people. An application study using this procedure is presented and results are compared to street hierarchies from two different sources. This study is the first step towards automating the generation of design scenarios for urban street retrofitting.
keywords	Space Syntax; Street Hierarchy; Parametric Urbanism; Scenario Modeling; Travel Behavior
series	eCAADeSIGraDi
email
last changed	2022/06/07 08:00

_id	ecaadesigradi2019_355
id	ecaadesigradi2019_355
authors	Poustinchi, Ebrahim
year	2019
title	Oriole Beta - A Parametric Solution for Robotic Motion Design Using Animation
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. 227-234
doi	https://doi.org/10.52842/conf.ecaade.2019.2.227
summary	This paper presents a project-based research study using the beta version of Oriole-a custom-made animation-based plug-in for grasshopper 3D visual programming environment, to develop robotic motion/controlling solutions. Oriole, as a parametric tool, makes it possible for designers/users to "design"-instead of generating, the motions of the robot based on the notion of keyframing and time-based animation. Through the use of Oriole, users can simulate-and ultimately develop robotic motions/performances in more intuitive ways. This unique feature enables users with minor or no programming background to create robotic solutions using Oriole as a software/plugin Bridge.Using Rhinoceros 3D as a digital modeling platform in conjunction with Grasshopper 3D and its robotic simulation platforms, Oriole can develop controlling strategies for different industrial robots such as KUKA, ABB, and Universal Robots. Oriole enables designers to create a precise interaction between the robot, its spatial "performance" and the physical environment, through animation and keyframing to "design" robotic interactions and movements as frames of animation instead of segments of a curve "path."
keywords	Robotics; Software Development; Animation; Parametric Design; Design
series	eCAADeSIGraDi
email
last changed	2022/06/07 08:00

_id	ecaadesigradi2019_112
id	ecaadesigradi2019_112
authors	Rahimian, Mina, Nuno Beir?o, José, Pinto Duarte, José and Domenica Iulo, Lisa
year	2019
title	A Grammar-Based Generative Urban Design Tool Considering Topographic Constraints - The Case for American Urban Planning
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 3, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 267-276
doi	https://doi.org/10.52842/conf.ecaade.2019.3.267
summary	This paper explains the development of a generative urban design tool based on shape grammars. The novelty of this tool lies in considering the topographic constraints of the site and generating various alternatives of urban design scenarios accordingly. For the purposes of this research, San Diego has been chosen as an example of a steep city with varied topography that, in consequence, has created distinct urban typologies within the city. With the use of shape grammars, the rules and patterns forming the urban structure of each typology have been decodified. The extracted urban shape grammar is then used as the basis for a generative design tool producing various urban design scenarios considering the limitations and potential of the site's topology. This paper describes the extracted urban shape grammars and how that informs the development of the presented generative urban design tool.
keywords	Generative Design; Urban Shape Grammars; Topography; American Urban Planning
series	eCAADeSIGraDi
email
last changed	2022/06/07 08:00

_id	cf2019_029
id	cf2019_029
authors	Rogers, Jessie; Marc Aurel Schnabel and Tane Moleta
year	2019
title	Digital Design Ecology to Generate a Speculative Virtual Environment Reimagining New Relativity Laws
source	Ji-Hyun Lee (Eds.) "Hello, Culture!" [18th International Conference, CAAD Futures 2019, Proceedings / ISBN 978-89-89453-05-5] Daejeon, Korea, p. 234
summary	This paper presents the trilogy of virtual classifications, the speculative environment, the virtual inhabitant and the virtual built-form. These combine, generating a new realm of design within immersive architectural space, all to be designed relative to each other, this paper focuses on the speculative environment portion. This challenged computational design and representation through atmospheric filters, visible environment boundaries, materiality and audio experience. The speculative environment was generated manipulating the physical laws of the physical world, applied within the virtual space. The outcome provided a new spatial experience of architectural dynamics enhanced by detailed spatial qualities. Design concepts within this paper suggest at what immersive virtual reality can evolve into. Following an interconnective design methodology framework allowed a high level of complexity and richness to shine through the research case study throughout the process and final dissemination stages.
keywords	Virtual Reality, Relativity, Methodology, Immersive, Speculative
series	CAAD Futures
email
last changed	2019/07/29 14:15

_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
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
doi	https://doi.org/10.52842/conf.caadria.2019.2.231
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
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last changed	2022/06/07 07:57

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