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	acadia18_216
id	acadia18_216
authors	Ahrens, Chandler; Chamberlain, Roger; Mitchell, Scott; Barnstorff, Adam
year	2018
title	Catoptric Surface
doi	https://doi.org/10.52842/conf.acadia.2018.216
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. 216-225
summary	The Catoptric Surface research project explores methods of reflecting daylight through a building envelope to form an image-based pattern of light on the interior environment. This research investigates the generation of atmospheric effects from daylighting projected onto architectural surfaces within a built environment in an attempt to amplify or reduce spatial perception. The mapping of variable organizations of light onto existing or new surfaces creates a condition where the perception of space does not rely on form alone. This condition creates a visual effect of a formless atmosphere and affects the way people use the space. Often the desired quantity and quality of daylight varies due to factors such as physiological differences due to age or the types of tasks people perform (Lechner 2009). Yet the dominant mode of thought toward the use of daylighting tends to promote a homogeneous environment, in that the resulting lighting level is the same throughout a space. This research project questions the desire for uniform lighting levels in favor of variegated and heterogeneous conditions. The main objective of this research is the production of a unique facade system that is capable of dynamically redirecting daylight to key locations deep within a building. Mirrors in a vertical array are individually adjusted via stepper motors in order to reflect more or less intense daylight into the interior space according to sun position and an image-based map. The image-based approach provides a way to specifically target lighting conditions, atmospheric effects, and the perception of space.
keywords	full paper, non-production robotics, representation + perception, performance + simulation, building technologies
series	ACADIA
type	paper
email
last changed	2022/06/07 07:54

_id	ecaade2018_167
id	ecaade2018_167
authors	Anton, Ana and Abdelmahgoub, Ahmed
year	2018
title	Ceramic Components - Computational Design for Bespoke Robotic 3D Printing on Curved Support
doi	https://doi.org/10.52842/conf.ecaade.2018.2.071
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. 71-78
summary	Additive manufacturing enables the fabrication of affordable customisation of construction elements. This paper presents a computational design method developed for 3D printing of unique interlocking ceramic components, which assemble into segmented columns. The fabrication method is ceramic-paste extrusion, robotically placed on semi-cylindrical molds. Material system and fabrication setup contribute to the development of an integrated generative system which includes overall design, assembly logic and printing tool-path. By contextualizing clay extrusion and identifying challenges in bespoke tool-path generation, this paper discusses detailing opportunities in digital fabrication. Finally, it identifies future directions of research in extrusion-based printing.
keywords	CAAD education; generative design; robotic 3D printing; clay extrusion; curved support
series	eCAADe
email
last changed	2022/06/07 07:54

_id	acadia18_244
id	acadia18_244
authors	Belanger, Zackery; McGee, Wes; Newell, Catie
year	2018
title	Slumped Glass: Auxetics and Acoustics
doi	https://doi.org/10.52842/conf.acadia.2018.244
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. 244-249
summary	This research investigates the effect of curvature, at a variety of scales, on the acoustic properties of glass. Plate glass, which has predictable and uniform acoustically reflective behavior, can be formed into curved surfaces through a combination of parametrically-driven auxetic pattern generation, CNC water-jet cutting, and controlled heat forming. When curved, plate glass becomes “activated” and complex acoustically-diffusive behavior emerges. The parametrically-driven auxetic perforation pattern allows the curvature to be altered and controlled across a formed pane of glass, and a correlation is demonstrated between the level of curvature and the extent of acoustically diffusive behavior. Beyond individual panels, curved panes can be aggregated to extend acoustic influence to the entire interior room condition, and the pace at which acoustic energy is distributed can be controlled. In this work the parameters surrounding the controlled slumping of glass are described, and room-sized formal and acoustic effects are studied using wave-based acoustic simulation techniques. This paper discusses the early stages of work in progress.
keywords	work in progress, materials and adaptive systems, performance and simulation, digital fabrication
series	ACADIA
type	paper
email
last changed	2022/06/07 07:54

_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	acadia18_286
id	acadia18_286
authors	Claire Im, Hyeonji; AlOthman, Sulaiman; García del Castillo, Jose Luis
year	2018
title	Responsive Spatial Print. Clay 3D printing of spatial lattices using real-time model recalibration
doi	https://doi.org/10.52842/conf.acadia.2018.286
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. 286-293
summary	Additive manufacturing processes are typically based on a horizontal discretization of solid geometry and layered deposition of materials, the speed and the rate of which are constant and determined by the stability criteria. New methods are being developed to enable three-dimensional printing of complex self-supporting lattices, expanding the range of possible outcomes in additive manufacturing. However, these processes introduce an increased degree of formal and material uncertainty, which require the development of solutions specific to each medium. This paper describes a development to the 3D printing methodology for clay, incorporating a closed-loop feedback system of material surveying and self-correction to recompute new depositions based on scanned local deviations from the digital model. This Responsive Spatial Print (RSP) method provides several improvements over the Spatial Print Trajectory (SPT) methodology for clay 3D printing of spatial lattices previously developed by the authors. This process compensates for the uncertain material behavior of clay due to its viscosity, malleability, and deflection through constant model recalibration, and it increases the predictability and the possible scale of spatial 3D prints through real-time material-informed toolpath generation. The RSP methodology and early successful results are presented along with new challenges to be addressed due to the increased scale of the possible outcomes.
keywords	work in progress, closed loop system, spatial clay printing, self-supporting lattice, in-situ printking, extrusion rate, material behavior
series	ACADIA
type	paper
email
last changed	2022/06/07 07:52

_id	ecaade2018_399
id	ecaade2018_399
authors	Cutellic, Pierre
year	2018
title	UCHRON - An Event-Based Generative Design Software Implementing Fast Discriminative Cognitive Responses from Visual ERP BCI
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	ecaade2018_438
id	ecaade2018_438
authors	Das, Subhajit
year	2018
title	Interactive Artificial Life Based Systems, Augmenting Design Generation and Evaluation by Embedding Expert Opinion - A Human Machine dialogue for form finding.
doi	https://doi.org/10.52842/conf.ecaade.2018.1.085
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. 85-94
summary	Evolution of natural life and subsequently selection of life forms is an interesting topic that has been explored multiple times. This area of research and its application has high relevance in evolutionary design and automated design generation. Taking inspiration from Charles Darwin's theory, all biological species were formed by the process of evolution based on natural selection of the fittest (Darwin, n.d.) this paper explains exploratory research showcasing semi-automatic design generation. This is realized by an interactive artificial selection tool, where the designer or the end user makes key decisions steering the propagation and breeding of future design artifacts. This paper, describes two prototypes and their use cases, highlighting interaction based optimal design selection. One of the prototypes explains a 2d organic shape creator using a metaball shape approach, while the other discusses a spatial layout generation technique for conceptual design.
keywords	design generation; implicit surfaces; artificial life; decision making; artificial selection; spatial layout generation
series	eCAADe
email
last changed	2022/06/07 07:55

_id	ecaade2018_176
id	ecaade2018_176
authors	Fisher-Gewirtzman, Dafna and Polak, Nir
year	2018
title	Integrating Crowdsourcing & Gamification in an Automatic Architectural Synthesis Process
doi	https://doi.org/10.52842/conf.ecaade.2018.1.439
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. 439-444
summary	This work covers the methodological approach that is used to gather information from the wisdom of crowd, to be utilized in a machine learning process for the automatic generation of minimal apartment units. The flexibility in the synthesis process enables the generation of apartment units that seem to be random and some are unsuitable for dwelling. Thus, the synthesis process is required to classify units based on their suitability. The classification is deduced from opinions of human participants on previously generated units. As the definition of "suitability" may be subjective, this work offers a crowdsourcing method in order to reach a large number of participants, that as a whole would allow to produce an objective classification. Gaming elements have been adopted to make the crowdsourcing process more intuitive and inviting for external participants.
keywords	crowdsourcing and gamification; urban density; optimization; automated architecture synthesis; minimum apartments; visual openness
series	eCAADe
email
last changed	2022/06/07 07:51

_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	caadria2018_210
id	caadria2018_210
authors	Lin, Yuqiong, Zheng, Jingyun, Yao, Jiawei and Yuan, Philip F.
year	2018
title	Research on Physical Wind Tunnel and Dynamic Model Based Building Morphology Generation Method
doi	https://doi.org/10.52842/conf.caadria.2018.2.165
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 165-174
summary	The change of the building morphology directly affects the surrounding environment, while the evaluation of these environment data becomes the main basis for the genetic iterations of the building morphology. Indeed, due to the complexity of the outdoor natural ventilation, multiple factors in the site could be the main reasons for the change of air flow. Thus, the architect is suggested to take the wind environment as the main morphology generation factor in the early stage of the building design. Based on the research results of 2017 DigitalFUTURE Wind Tunnel Visualization Workshop, a novel self-form-finding method in design infancy has been proposed. This method uses Arduino to carry out the dynamic design of the building model, which can not only connect the sensor to monitor the wind environment data, but also contribute the building model to correlate with the wind environment data in real time. The integration of the Arduino platform and the physical wind tunnel can create the possibility of continuous and real-time physical changes, data collection and wind environment simulation, using quantitative environmental factors to control building morphology, and finally achieve the harmony among the building, environment and human.
keywords	Physical wind tunnel; dynamic model; building morphology generation; environmental performance design; wind environment visualization
series	CAADRIA
email
last changed	2022/06/07 07:59

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

_id	ijac201816403
id	ijac201816403
authors	Pantazis, Evangelos and David Gerber
year	2018
title	A framework for generating and evaluating façade designs using a multi-agent system approach
source	International Journal of Architectural Computing vol. 16 - no. 4, 248-270
summary	Digital design paradigms in architecture have been rooted in representational models which are geometry centered and therefore fail to capture building complexity holistically. Due to a lack of computational design methodologies, existing digital design workflows do little in predicting design performance in the early design stage and in most cases analysis and design optimization are done after a design is fixed. This work proposes a new computational design methodology, intended for use in the area of conceptual design of building design. The proposed methodology is implemented into a multi-agent system design toolkit which facilitates the generation of design alternatives using stochastic algorithms and their evaluation using multiple environmental performance metrics. The method allows the user to probabilistically explore the solution space by modeling the design parameters’ architectural design components (i.e. façade panel) into modular programming blocks (agents) which interact in a bottom-up fashion. Different problem requirements (i.e. level of daylight inside a space, openings) described into agents’ behavior allow for the coupling of data from different engineering fields (environmental design, structural design) into the a priori formation of architectural geometry. In the presented design experiment, a façade panel is modeled into an agent-based fashion and the multi-agent system toolkit is used to generate and evolve alternative façade panel configurations based on environmental parameters (daylight, energy consumption). The designer can develop the façade panel geometry, design behaviors, and performance criteria to evaluate the design alternatives. The toolkit relies on modular and functionally specific programming modules (agents), which provide a platform for façade design exploration by combining existing three-dimensional modeling and analysis software.
keywords	Generative design, multi-agent systems, façade design, agent-based modeling, stochastic search
series	journal
email
last changed	2019/08/07 14:04

_id	sigradi2018_1650
id	sigradi2018_1650
authors	Regadas Reis Vianna, Maria Elisa; Castro Henriques, Gonçalo; Martin Passaro, Andrés
year	2018
title	Constructive-geometry:the integration of generation and construction systems in a case-study
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. 316-323
summary	This project reflects about the use of the term constructive geometry, based on the development of a case study. Even if we posses the digital tools and processes to develop a design, it is not so clear how to combine the generation and the necessary tools to materialize it. To find form we rely on algorithmic generation unfolding this term with digital fabrication, to include material and techniques feedback. Constructive geometry looks for an inclusive computational design to integrate generation and fabrication. This process is tested and documented in the development of a studentl graduation project.
keywords	Constructive geometry, digital integration, form generation, digital fabrication
series	SIGRADI
email
last changed	2021/03/28 19:59

_id	caadria2018_170
id	caadria2018_170
authors	Stouffs, Rudi
year	2018
title	Where Associative and Rule-Based Approaches Meet - A Shape Grammar Plug-in for Grasshopper
doi	https://doi.org/10.52842/conf.caadria.2018.2.453
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 453-462
summary	We present a shape grammar plug-in for Grasshopper that allows shapes and shape rules to be defined in a parametric manner, even if the rule matching mechanism does not support parametric rules. The plug-in supports shape emergence and provides support for visually enumerating rule applications. We reflect on the interaction between parametric or associative modelling and rule-based generation within the context of using this plug-in.
keywords	shape grammar; SGI; parametric modelling; Grasshopper; rule-based
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	ecaade2018_112
id	ecaade2018_112
authors	Yu, K. Daniel, Haeusler, M. Hank, Simon, Katrina and Fabbri, Alessandra
year	2018
title	Data Influenced Infrastructure Generation - Combining holistic urban datasets through a digital Slime Mold algorithm for cycle path generation
doi	https://doi.org/10.52842/conf.ecaade.2018.2.647
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. 647-656
summary	Existing infrastructure in cities has become increasingly incapable of operating at its designed efficiency. This demand has been created by the growth in population generating a larger demand and strain on the existing infrastructure. This paper explores how user-generated data could be utilised to create transport infrastructure, more specifically bicycle pathways. Through a series of 'four sprints', a pathway generation system has been adapted from the behaviour of Slime Molds (Physarum Polycephalum), in particular, its ability to define shortest paths on a terrain. The first sprint outlines the design of a Slime Mold algorithm between user-specified points, the second utilises the algorithm for pathway generation in a macro and micro urban scale (acknowledging both the existing infrastructure and cadastral), the third defines weight or effort limits for the pathways in order to suite realistic user-profiles (fitness level of cyclist groups), and the last sprint creates the start and end points for the pathway generation from user-generated data, applying the Slime Mold system to a 'real world' context. Through the four sprints, a design tool has been created that can be used to not only create and analyse cycle pathways, but tweaked for various other forms of tangible transport infrastructure.
keywords	urban planning; agent based modelling; optimisation and decision support; transport planning
series	eCAADe
email
last changed	2022/06/07 07:57

_id	acadia18_196
id	acadia18_196
authors	Zhang, Yan; Grignard; Aubuchon, Alexander; Lyons, Keven; Larson, Kent
year	2018
title	Machine Learning for Real-time Urban Metrics and Design Recommendations
doi	https://doi.org/10.52842/conf.acadia.2018.196
source	ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 196-205
summary	Cities are growing, becoming more complex, and changing rapidly. Currently, community engagement for urban decision-making is often ineffective, uninformed, and only occurs in projects’ later stages. To facilitate a more collaborative and evidence-based urban decision- making process for both experts and non-experts, real-time feedback and optimized suggestions are essential. However, most of the current tools for urban planning are neither capable of performing complex simulations in real time nor of providing guidance for better urban performance. CityMatrix was introduced to address these challenges. Machine learning techniques were applied to achieve real-time prediction of multiple urban simulations, and thousands of city configurations were simulated. The simulation results were used to train a convolutional neural network (CNN) to predict the traffic and solar performance of unseen city configurations. The prediction with the CNN is thousands of times faster than the original simulations and maintains a high-quality representation of the results. This machine learning approach was applied as a versatile, quick, accurate, and computationally efficient method not only for real-time feedback, but also for optimized design recommendations. Users involved in the evaluation of this project had a better understanding of the embodied trade-offs of the city and achieved their goals in an efficient manner.
keywords	full paper, optimization, collaboration, urban design & analysis, ai & machine learning
series	ACADIA
type	paper
email
last changed	2022/06/07 07:57

_id	ecaade2018_138
id	ecaade2018_138
authors	Abdulmawla, Abdulmalik, Schneider, Sven, Bielik, Martin and Koenig, Reinhard
year	2018
title	Integrated Data Analysis for Parametric Design Environment - mineR: a Grasshopper plugin based on R
doi	https://doi.org/10.52842/conf.ecaade.2018.2.319
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. 319-326
summary	In this paper we introduce mineR- a tool that integrates statistical data analysis inside the parametric design environment Grasshopper. We first discuss how the integration of statistical data analysis would improve the parametric modelling workflow. Then we present the statistical programming language R. Thereafter, we show how mineR is built to facilitate the use of R in the context of parametric modelling. Using two example cases, we demonstrate the potential of implementing mineR in the context of urban design and analysis. Finally, we discuss the results and possible further developments.
keywords	Statistical Data Analysis; Parametric Design
series	eCAADe
email
last changed	2022/06/07 07:54

_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	sigradi2018_1867
id	sigradi2018_1867
authors	Alawadhi, Mohammad; Yan, Wei
year	2018
title	Geometry from 3D Photogrammetry for Building Energy Modeling
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. 631-637
summary	Building energy modeling requires skilled labor, and there is a need to make environmental assessments of buildings more efficient and accessible for architects. A building energy model is based on collecting data from the real, physical world and representing them as a digital model. Recent digital photogrammetry tools can reconstruct real-world geometry by transforming photographs into 3D models automatically. However, there is a lack of accessible workflows that utilize this technology for building energy modeling and simulations. This paper presents a novel methodology to generate a building energy model from a photogrammetry-based 3D model using available tools and computer algorithms.
keywords	3D scanning; Building energy modeling; Building energy simulation; Digital photogrammetry; Photo-to-BEM
series	SIGRADI
email
last changed	2021/03/28 19:58

_id	ijac201816203
id	ijac201816203
authors	Anderson, Carl; Carlo Bailey, Andrew Heumann and Daniel Davis
year	2018
title	Augmented space planning: Using procedural generation to automate desk layouts
source	International Journal of Architectural Computing vol. 16 - no. 2, 164-177
summary	We developed a suite of procedural algorithms for space planning in commercial offices. These algorithms were benchmarked against 13,000 actual offices designed by human architects. The algorithm performed as well as an architect on 77% of offices, and achieved a higher capacity in an additional 6%, all while following a set of space standards. If the algorithm used the space standards the same way as an architect (a more relaxed interpretation), the algorithm achieved a 97% match rate, which means that the algorithm completed this design task as well as a designer and in a shorter time. The benchmarking of a layout algorithm against thousands of existing designs is a novel contribution of this article, and we argue that it might be a first step toward a more comprehensive method to automate parts of the office layout process.
keywords	Office design, design augmentation, space planning, automation, office layout, desk layouts
series	journal
email
last changed	2019/08/07 14:03

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