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	caadria2020_107
id	caadria2020_107
authors	Meng, Leo Lin, Graham, Jeremy and Haeusler, M. Hank
year	2020
title	t-SNE: A Dimensionality Reduction Tool for Design Data Visualisation
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. 629-638
doi	https://doi.org/10.52842/conf.caadria.2020.2.629
summary	One can argue that data is the 'new oil'. Yet more important than the sheer quantity of data is the question, in the context of architecture and design, how data is represented in design, as this is becoming a more relevant question to the architecture profession. We argue that data, in particular n-dimensional, is often hidden even in BIM models. Hence we propose a new way of understanding the space by (1) generate and integrate space analytics data using space syntax method as well as space usage data and (2) visualise the data using t-Distributed Stochastic Neighbour Embedding (t-SNE), an unsupervised learning and dimensionality reduction tool to help intuitively display high dimensions of data. This approach may help to discover the 'hidden layers' of the building information that may be otherwise omitted. This investigation, its proposed hypothesis, methodology, implications, significance and evaluation are presented in the paper.
keywords	Data-Driven Design; t-SNE; Machine Learning; Space Syntax
series	CAADRIA
email
last changed	2022/06/07 07:58

_id	ascaad2021_142
id	ascaad2021_142
authors	Bakir, Ramy; Sara Alsaadani, Sherif Abdelmohsen
year	2021
title	Student Experiences of Online Design Education Post COVID-19: A Mixed Methods Study
source	Abdelmohsen, S, El-Khouly, T, Mallasi, Z and Bennadji, A (eds.), Architecture in the Age of Disruptive Technologies: Transformations and Challenges [9th ASCAAD Conference Proceedings ISBN 978-1-907349-20-1] Cairo (Egypt) [Virtual Conference] 2-4 March 2021, pp. 142-155
summary	This paper presents findings of a survey conducted to assess students’ experiences within the online instruction stage of their architectural education during the lockdown period caused by the COVID-19 pandemic between March and June 2020. The study was conducted in two departments of architecture in both Cairo branches of the Arab Academy for Science, Technology & Maritime Transport (AASTMT), Egypt, with special focus on courses involving a CAAD component. The objective of this exploratory study was to understand students’ learning experiences within the online period, and to investigate challenges facing architectural education. A mixed methods study was used, where a questionnaire-based survey was developed to gather qualitative and quantitative data based on the opinions of a sample of students from both departments. Findings focus on the qualitative component to describe students’ experiences, with quantitative data used for triangulation purposes. Results underline students’ positive learning experiences and challenges faced. Insights regarding digital tool preferences were also revealed. Findings are not only significant in understanding an important event that caused remote architectural education in Egypt but may also serve as an important stepping-stone towards the future of design education in light of newly-introduced disruptive online learning technologies made necessary in response to lockdowns worldwide
series	ASCAAD
email
last changed	2021/08/09 13:13

_id	ecaade2020_190
id	ecaade2020_190
authors	Dounas, Theodoros, Jabi, Wassim and Lombardi, Davide
year	2020
title	Smart Contracts for Decentralised Building Information Modelling
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 565-574
doi	https://doi.org/10.52842/conf.ecaade.2020.2.565
summary	The paper presents a model for decentralizing building information modelling, through implementing its infrastructure using the decentralized web. We discuss the shortcomings of BIM in terms of its infrastructure, with a focus on tracing identities of design authorship in this collective design tool. In parallel we examine the issues with BIM in the cloud and propose a decentralized infrastructure based on the Ethereum blockchain and the Interplanetary filesystem (IPFS). A series of computing nodes, that act as nodes on the Ethereum Blockchain, host disk storage with which they participate in a larger storage pool on the Interplanetary Filesystem. This storage is made available through an API is used by architects and designers creating and editing a building information model that resides on the IPFS decentralised storage. Through this infrastructure central servers are eliminated, and BIM libraries and models can be shared with others in an immutable and transparent manner. As such Architecture practices are able to exploit their intellectual property in novel ways, by making it public on the internet. The infrastructure also allows the decentralised creation of a resilient global pool of data that allows the participation of computation agents in the creation and simulation of BIM models.
keywords	Blockchain; decentralisation; immutability; resilience; Building Information Modelling
series	eCAADe
email
last changed	2022/06/07 07:55

_id	caadria2020_443
id	caadria2020_443
authors	Abuzuraiq, Ahmed M. and Erhan, Halil
year	2020
title	The Many Faces of Similarity - A Visual Analytics Approach for Design Space Simplification
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 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 485-494
doi	https://doi.org/10.52842/conf.caadria.2020.1.485
summary	Generative design methods may involve a complex design space with an overwhelming number of alternatives with their form and design performance data. Existing research addresses this complexity by introducing various techniques for simplification through clustering and dimensionality reduction. In this study, we further analyze the relevant literature on design space simplification and exploration to identify their potentials and gaps. We find that the potentials include: alleviating the choice overload problem, opening up new venues for interrelating design forms and data, creating visual overviews of the design space and introducing ways of creating form-driven queries. Building on that, we present the first prototype of a design analytics dashboard that combines coordinated and interactive visualizations of design forms and performance data along with the result of simplifying the design space through hierarchical clustering.
keywords	Visual Analytics; Design Exploration; Dimensionality Reduction; Clustering; Similarity-based Exploration
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	ecaade2020_185
id	ecaade2020_185
authors	Wurzer, Gabriel, Lorenz, Wolfgang E., Forster, Julia, Bindreiter, Stefan, Lederer, Jakob, Gassner, Andreas, Mitteregger, Mathias, Kotroczo, Erich, Pöllauer, Pia and Fellner, Johann
year	2020
title	M-DAB - Towards re-using material resources of the city
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 1, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 127-132
doi	https://doi.org/10.52842/conf.ecaade.2020.1.127
summary	If we strive for a de-carbonized future, we need to think of buildings within a city as resources that can be re-used rather than being disposed of. Together with considerations on refurbishment options and future building materials, this gives a decision field for stakeholders which depends on the current "building stock" - the set of pre-existing buildings which are characterized e.g. by building period, location and material composition. Changes in that context are hard to argue for since (1.) some depend on statistics, other (2.) on the concrete neighborhood and thus the space in which buildings are embedded, yet again others on (3.) future extrapolations again dealing with both of the aforementioned environments. To date, there exists no tool that can handle this back-and-forth between different abstraction levels and horizons in time; nor is it possible to pursue such an endeavor without a proper framework. Which is why the authors of this paper are aiming to provide one, giving a model of change in the context of re-using material resource of the city, when faced with numerous abstraction levels (spatial or abstract; past, current or future) which have feedback loops between them. The paper focuses on a concrete case study in the city of Vienna, however, chances are high that this will apply to every other building stock throughout the world if enough data is available. As a matter of fact, this approach will ensure that argumentation can happen on multiple levels (spatial, statistical, past, now and future) but keeps its focus on making the building stock of a city a resource for sustainable development.
keywords	material reuse; sustainability; waste reduction; Design and computation of urban and local systems – XS to XL; Health and materials in architecture and cities
series	eCAADe
email
last changed	2022/06/07 07:57

_id	acadia20_120
id	acadia20_120
authors	Barsan-Pipu, Claudiu; Sleiman, Nathalie; Moldovan, Theodor
year	2020
title	Affective Computing for Generating Virtual Procedural Environments Using Game Technologies
source	ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 120-129.
doi	https://doi.org/10.52842/conf.acadia.2020.2.120
summary	Architects have long sought to create spaces that can relate to or even induce specific emotional conditions in their users, such as states of relaxation or engagement. Dynamic or calming qualities were given to these spaces by controlling form, perspective, lighting, color, and materiality. The actual impact of these complex design decisions has been challenging to assess, from both quantitative and qualitative standpoints, because neural empathic responses, defined in this paper by feature indexes (FIs) and mind indexes (MIs), are highly subjective experiences. Recent advances in the fields of virtual procedural environments (VPEs) and virtual reality (VR), supported by powerful game engine (GE) technologies, provide computational designers with a new set of design instruments that, when combined with brain-computing interfacing (BCI) and eye-tracking (E-T) hardware, can be used to assess complex empathic reactions. As the COVID-19 health crisis showed, virtual social interaction becomes increasingly relevant, and the social catalytic potential of VPEs can open new design possibilities. The research presented in this paper introduces the cyber-physical design of such an affective computing system. It focuses on how relevant empathic data can be acquired in real time by exposing subjects within a dynamic VR-based VPE and assessing their emotional responses while controlling the actual generative parameters via a live feedback loop. A combination of VR, BCI, and E-T solutions integrated within a GE is proposed and discussed. By using a VPE inside a BCI system that can be accurately correlated with E-T, this paper proposes to identify potential morphological and lighting factors that either alone or combined can have an empathic effect expressed by the relevant responses of the MIs.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	acadia20_74
id	acadia20_74
authors	Bucklin, Oliver; Born, Larissa; Körner, Axel; Suzuki, Seiichi; Vasey, Lauren; T. Gresser, Götz; Knippers, Jan; Menges,
year	2020
title	Embedded Sensing and Control
source	ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 74-83.
doi	https://doi.org/10.52842/conf.acadia.2020.1.074
summary	This paper investigates an interactive and adaptive control system for kinetic architectural applications with a distributed sensing and actuation network to control modular fiber-reinforced composite components. The aim of the project was to control the actuation of a foldable lightweight structure to generate programmatic changes. A server parses input commands and geometric feedback from embedded sensors and online data to drive physical actuation and generate a digital twin for real-time monitoring. Physical components are origami-like folding plates of glass and carbon-fiber-reinforced plastic, developed in parallel research. Accelerometer data is analyzed to determine component geometry. A component controller drives actuators to maintain or move towards desired positions. Touch sensors embedded within the material allow direct control, and an online user interface provides high-level kinematic goals to the system. A hierarchical control system parses various inputs and determines actuation based on safety protocols and prioritization algorithms. Development includes hardware and software to enable modular expansion. This research demonstrates strategies for embedded networks in interactive kinematic structures and opens the door for deeper investigations such as artificial intelligence in control algorithms, material computation, as well as real-time modeling and simulation of structural systems.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	ecaade2020_298
id	ecaade2020_298
authors	Zhang, Ye, Zhang, Kun, Chen, KaiDi and Xu, Zhen
year	2020
title	Source Material Oriented Computational Design and Robotic Construction
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 443-452
doi	https://doi.org/10.52842/conf.ecaade.2020.2.443
summary	The disconnection between architectural form and materiality has become an important issue in recent years. Architectural form is mainly decided by the designer, while material data, for example, the natural shape of source materials, is often treated as an afterthought which doesn't factor in decision-making directly. This study proposes a new, real-time scanning-modeling system for obtaining material information, and incorporating the data into a continuous digital chain of computational design and robotic construction. After collecting and visualizing the data, the calculation portion of the chain processes the selection of source materials and generates architectural geometry based on both human-designed rules and various shapes of materials. Finally, at the action end of the chain, an industry robot is used to fabricate the design. End-effector is designed for tightly gripping the irregular source materials. Scripts is written in Grasshopper for positioning the components and assemble them into configurations. This study also shows a pavilion developing with the continuous digital chain
keywords	scanning-modeling system; source material information; computational design; robotic construction
series	eCAADe
email
last changed	2022/06/07 07:57

_id	ecaade2020_193
id	ecaade2020_193
authors	Alymani, Abdulrahman, Jabi, Wassim and Corcoran, Padraig
year	2020
title	Machine Learning Methods for Clustering Architectural Precedents - Classifying the relationship between building and ground
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 1, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 643-652
doi	https://doi.org/10.52842/conf.ecaade.2020.1.643
summary	Every time an object is built, it creates a relationship with the ground. Architects have a full responsibility to design the building by taking the ground into consideration. In the field of architecture, using data mining to identify any unusual patterns or emergent architectural trends is a nascent area that has yet to be fully explored. Clustering techniques are an essential tool in this process for organising large datasets. In this paper, we propose a novel proof-of-concept workflow that enables a machine learning computer system to cluster aspects of an architect's building design style with respect to how the buildings in question relate to the ground. The experimental workflow in this paper consists of two stages. In the first stage, we use a database system to collect, organise and store several significant architectural precedents. The second stage examines the most well-known unsupervised learning algorithm clustering techniques which are: K-Means, K-Modes and Gaussian Mixture Models. Our experiments demonstrated that the K-means clustering algorithm method achieves a level of accuracy that is higher than other clustering methods. This research points to the potential of AI in helping designers identify the typological and topological characteristics of architectural solutions and place them within the most relevant architectural canons
keywords	Machine Learning; Building and Ground Relationship; Clustering Algorithms; K-means cluster Algorithms
series	eCAADe
email
last changed	2022/06/07 07:54

_id	acadia20_208p
id	acadia20_208p
authors	Bernier-Lavigne, Samuel
year	2020
title	Object-Field
source	ACADIA 2020: Distributed Proximities / Volume II: Projects [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95253-6]. Online and Global. 24-30 October 2020. edited by M. Yablonina, A. Marcus, S. Doyle, M. del Campo, V. Ago, B. Slocum. 208-213
summary	This project aims to continue the correlative study between two fundamental entities of digital architecture: the object and the field. Following periods of experimentations on the ""field"" (materialization of flows of data through animation), the ""field of objects"" (parametricism), the ""object"" (OOO), we investigate the last possible interaction remaining: the ""object-field,"" by merging the formal characteristics of the object with the structural flow of its internal field. This investigation is achieved by exploring the high-resolution features of 3d printing in the design of autonomous architectural objects expressing materiality through topological optimization. The objects are generated by an iterative process of volumetric reduction, resulting in an ensemble of monoliths. Four of them are selected and analyzed through topological optimization in order to extract their internal fields. Next, a series of high-resolution algorithmic systems translate the structural information into 3d printed materiality. Of the four object-fields, one materializes, close to identical, the result of the optimization, giving the keystone to understanding the others. The second one expresses the structural flow through a 1mm voxel system, informed by the optimization, having the effect of stiffening the structure where it is needed and thus generating a new topography on the object. The last two explore the blur that this high-resolution can paradoxically create, with complete integration of the optimal structure in a transparent monolith. This is achieved by a vertex displacement algorithm, and the dissolution of the formal data of the monolith and the structural flows, through the mereological assembly of simple linear elements. For each object-field, a series of drawings was developed using specific algorithmic procedures derived from the peculiarities of their complex geometry. The drawings aim to catalyze coherence throughout the project, where similarities, hitherto kept apart by the multiple materialities, begin to dialogue.
series	ACADIA
type	project
email
last changed	2021/10/26 08:08

_id	ecaade2024_222
id	ecaade2024_222
authors	Bindreiter, Stefan; Sisman, Yosun; Forster, Julia
year	2024
title	Visualise Energy Saving Potentials in Settlement Development: By linking transport and energy simulation models for municipal planning
source	Kontovourkis, O, Phocas, MC and Wurzer, G (eds.), Data-Driven Intelligence - Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2024), Nicosia, 11-13 September 2024, Volume 2, pp. 79–88
doi	https://doi.org/10.52842/conf.ecaade.2024.2.079
summary	To achieve Sustainable Development Goals, in addition to the switch to sustainable energy sources and energy-efficient buildings, transport offers a major lever for reducing energy consumption and greenhouse gases. The increasing demand for emission-free mobility (e.g. through electromobility) but also heat pumps has a direct impact on the electricity consumption of buildings and settlements. It is still difficult to simulate the effects and interactions of different measures as sector coupling concepts require comprehensible tools for ex ante evaluation of planning measures at the community level and the linking of domain-specific models (energy, transport). Using the municipality of Bruck an der Leitha (Austria) as an example, a digital twin based on an open data model (Bednar et al., 2020) is created for the development of methods, which can be used to simulate measures to improve the settlement structure within the municipality. Forecast models for mobility (Schmaus, 2019; Ritz, 2019) and the building stock are developed or applied and linked via the open data model to be able to run through development scenarios and variants. The forecasting and visualisation options created in the project form the basis for the ex-ante evaluation of measures and policies on the way to a Positive-Energy-District. By identifying and collecting missing data, data gaps are filled for the simulation of precise models in the specific study area. A digital, interactive 3D model is created to examine the forecast results and the different scenarios.
keywords	visualisation, decision support, sector coupling, holistic spatial energy models for municipal planning, (energy) saving potentials in settlement development
series	eCAADe
email
last changed	2024/11/17 22:05

_id	acadia20_226p
id	acadia20_226p
authors	Borhani, Alireza; Kalantar, Negar
year	2020
title	Interlocking Shell
source	ACADIA 2020: Distributed Proximities / Volume II: Projects [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95253-6]. Online and Global. 24-30 October 2020. edited by M. Yablonina, A. Marcus, S. Doyle, M. del Campo, V. Ago, B. Slocum. 226-231
summary	With a specific focus on robotic stereotomy, two full-scale vault structures were designed to explore the potential of self-standing building structures made from interlocking components; these structures were fabricated with a track-mounted industrial-scale robot (ABB 4600). To respond to the economic affordances of robotic subtractive cutting, all uniquely shaped structural modules came from one block of material (48"" x96"" x36""). Through the discretization of curvilinear tessellated vault surfaces into a limited number of uniquely shaped modules with embedded form-fitting connectors, the project exhibited the potential for programming a robot to cut ruled surfaces to produce freeform shells of any kind. Representing nearly zero-waste construction, the developed technology can potentially be used for self-supporting emergency shelters and field medical clinics, facilitating easy shipping and speedy assembly. Without using any scaffolding, a few people can erect and dismantle an entire mortar-free structure at the construction site. The disassembled structure occupies minimal space in storage, and the structure’s pieces can be transported to the site in stacks. Robot milling is a common technique for removing material to transform a block into a sculptural shape. Unlike milling techniques that produce significant waste, we used a hotwire that sliced through a Geofoam block to create almost no waste pieces. Since the front side of every module was concurrent with the backside of the next one, such a decision allowed to operate just one cut per front side of each module. In this case, by having three cuts, two neighboring modules were fabricated. The form of the structure and its modules emerged from the constraints of the fabrication technique, aiming to establish a feedback loop between geometry, material, simulation, and tool. By cross-referencing geometric data across Grasshopper, a customized tessellation script was made to breakdown a vault into its modular ruled surface constructs.
series	ACADIA
type	project
email
last changed	2021/10/26 08:08

_id	ecaade2020_047
id	ecaade2020_047
authors	Brown, Lachlan, Yip, Michael, Gardner, Nicole, Haeusler, M. Hank, Khean, Nariddh, Zavoleas, Yannis and Ramos, Cristina
year	2020
title	Drawing Recognition - Integrating Machine Learning Systems into Architectural Design Workflows
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 289-298
doi	https://doi.org/10.52842/conf.ecaade.2020.2.289
summary	Machine Learning (ML) has valuable applications that are yet to be proliferated in the AEC industry. Yet, ML offers arguably significant new ways to produce and assist design. However, ML tools are too often out of the reach of designers, severely limiting opportunities to improve the methods by which designers design. To address this and to optimise the practices of designers, the research aims to create a ML tool that can be integrated into architectural design workflows. Thus, this research investigates how ML can be used to universally move BIM data across various design platforms through the development of a convolutional neural network (CNN) for the recognition and labelling of rooms within floor plan images of multi-residential apartments. The effects of this computation and thinking shift will have meaningful impacts on future practices enveloping all major aspects of our built environment from designing, to construction to management.
keywords	machine learning; convolutional neural networks; labelling and classification; design recognition
series	eCAADe
email
last changed	2022/06/07 07:54

_id	caadria2020_012
id	caadria2020_012
authors	Chatzi, Anna-Maria and Wesseler, Lisa-Marie
year	2020
title	OGOS+ - A Tool to Visualize Densification potential
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 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 773-782
doi	https://doi.org/10.52842/conf.caadria.2020.1.773
summary	OGOS+ is a GIS data-based tool, which would offer urban planners, architects, and researchers visualisations of potential building mass in the form of 3D models. It compares the height of existing buildings to the maximum permitted height by German zoning law and calculates the potential building mass. To ensure minimum building footprints it only calculates the densification potential on top of existing buildings. It summarises information of the building potential for future utilisation. The goal is an increase of urban density achieved with micro interventions.
keywords	Urban densification; City Information Modeling and GIS; Big Data and Analytics in Architecture
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	caadria2020_276
id	caadria2020_276
authors	Chuang, I-Ting
year	2020
title	Sensing the Diversity of Social Hubs through Social Media
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. 61-70
doi	https://doi.org/10.52842/conf.caadria.2020.2.061
summary	As we continue to discover the potential of social media data as an insightful source for academic research, the majority of previous work tends to focus on the density of socio-spatial relations as the foundation for understanding urban phenomena. This paper extended those approaches by introducing the concepts of diversity and inclusiveness through an investigation of the 'differences' within the networks of relations that are inherent to social media data. The author constructs a diversity measure based on the variety of home locations of social media user visitors to each geographical location in the city. This home location, in its turn, is derived from each user's digital spatio-temporal footprint. This proposed method demonstrates that through the visualization of this diversity measure, 'social hubs' (which are frequently visited by different groups of people) were able to be located that would otherwise be overlooked in conventional data analyses that focus only on density. As such, this research expands the usefulness of social media as a practical tool to help understand urban processes by making the concept of diversity - a key consideration in many planning and design contexts - measurable and mappable.
keywords	Social Media Data; Home Location Detection; Diversity Analysis
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	caadria2020_423
id	caadria2020_423
authors	Erhan, Halil, Zarei, Maryam, Abuzuraiq, Ahmed M., Haas, Alyssa, Alsalman, Osama and Woodbury, Robert
year	2020
title	FlowUI: Combining Directly-Interactive Design Modeling with Design Analytics
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 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 475-484
doi	https://doi.org/10.52842/conf.caadria.2020.1.475
summary	In a systems building experiment, we explored how directly manipulating non-parametric geometries can be used together with a real-time parametric performance analytics for informed design decision-making in the early phases of design. This combination gives rise to a design process where considerations that would traditionally take place in the late phases of design can become part of the early phases. The paper presents FlowUI, a prototype tool for performance-driven design that is developed in a collaboration with our industry partner as part of our design analytics research program. The tool works with and responds to changes in the design modeling environment, processes the design data and presents the results in design (data) analytics interfaces. We discuss the system's design intent and its overall architecture, followed by a set of suggestions on the comparative analysis of design solutions and design reports generation as integral parts of design exploration tasks.
keywords	Non-Parametric Modeling; Performance-Driven Design; Design Analytics; Information Visualization
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	caadria2020_100
id	caadria2020_100
authors	Hershcovich, Cheli, van Hout, RENÃ‰, Rinsky, Vladislav, Laufer, Michael and Grobman, Yasha J.
year	2020
title	Insulating with Geometry - Employing Cellular Geometry to Increase the Thermal Performance of Building Facades
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 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 507-516
doi	https://doi.org/10.52842/conf.caadria.2020.1.507
summary	This paper presents the current stage of a study examining the potential of complex geometry concrete tiles to improve thermal performance in building envelopes. This stage focused on developing tile geometries and testing them using physical and digital CFD (Computational Fluid Dynamics) simulations. Tiles were developed taking two approaches: (i) developing variation from basic geometries (triangle, square, circle and trapezoid) and (ii) learning from natural envelopes. Following successful validation of experimental and numerical data, the designed tiles were tested using a digital simulation (Star-CCM+). The results show that for the examined configuration (flow perpendicular to the surface), a significant reduction of heat transfer rate occurs in most of the tested tiles. Furthermore, geometries that achieved the same thermal performance as the base-line flat tile saved up to 38 percent of the material.
keywords	Complex Geometry; Microclimate; CFD
series	CAADRIA
email
last changed	2022/06/07 07:50

_id	caadria2020_088
id	caadria2020_088
authors	Kado, Keita, Furusho, Genki, Nakamura, Yusuke and Hirasawa, Gakuhito
year	2020
title	rocess Path Derivation Method for Multi-Tool Processing Machines Using Deep-Learning-Based Three Dimensional Shape Recognition
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. 609-618
doi	https://doi.org/10.52842/conf.caadria.2020.2.609
summary	When multi-axis processing machines are employed for high-mix, low-volume production, they are operated using a dedicated computer-aided design/ computer-aided manufacturing (CAD/CAM) process that derives an operating path concurrently with detailed modeling. This type of work requires dedicated software that occasionally results in complicated front-loading and data management issues. We proposed a three-dimensional (3D) shape recognition method based on deep learning that creates an operational path from 3D part geometry entered by a CAM application to derive a path for processing machinery such as a circular saw, drill, or end mill. The methodology was tested using 11 joint types and five processing patterns. The results show that the proposed method has several practical applications, as it addresses wooden object creation and may also have other applications.
keywords	Three-dimensional Shape Recognition; Deep Learning; Digital Fabrication; Multi-axis Processing Machine
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	ijac202018106
id	ijac202018106
authors	Koronaki, Antiopi; Paul Shepherd and Mark Evernden
year	2020
title	Rationalization of freeform space-frame structures: Reducing variability in the joints
source	International Journal of Architectural Computing vol. 18 - no. 1, 84-99
summary	In recent years, the application of space-frame structures on large-scale freeform designs has significantly increased due to their lightweight configuration and the freedom of design they offer. However, this has introduced a level of complexity into their construction, as doubly curved designs require non-uniform configurations. This article proposes a novel computational workflow that reduces the construction complexity of freeform space-frame structures, by minimizing variability in their joints. Space-frame joints are evaluated according to their geometry and clustered for production in compliance with the tolerance requirements of the selected fabrication process. This provides a direct insight into the level of customization required and the associated construction complexity. A subsequent geometry optimization of the space-frame’s depth minimizes the number of different joint groups required. The variables of the optimization are defined in relation to the structure’s curvature, providing a direct link between the structure’s geometry and the optimization process. Through the application of a control surface, the dimensionality of the design space is drastically reduced, rendering this method applicable to large-scale projects. A case study of an existing structure of complex geometry is presented, and this method achieves a significant reduction in the construction complexity in a robust and computationally efficient way.
keywords	Geometry optimization, space-frame structures, joint, fabrication process, construction, cost, clustering, control surface
series	journal
email
last changed	2020/11/02 13:34

_id	sigradi2020_534
id	sigradi2020_534
authors	Mariano, Pedro Oscar Pizzetti; Fonseca, Raphaela Walger da; Pereira, Fernando Oscar Ruttkay; Pereira, Alice Theresinha Cybis
year	2020
title	Autonomous parametric process for daylight simulation applied to the proposal of a daylighting of buildings performance tool
source	SIGraDi 2020 [Proceedings of the 24th Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Online Conference 18 - 20 November 2020, pp. 534-540
summary	The openings features definition, considering the obstructions influence caused by the urban environment, are extremely relevant for the daylit buildings design. The complexity of the daylight phenomenon and the need to estimate its performance spread the use of parametric simulation and simulation programs. Thus, this article aims to create a parametric process, derived from a digital process, capable of simulating and registering the performance of daytime construction in different urban scenarios in an automated way. This process made it possible to generate a series of data capable of producing tools for understanding the phenomenon of natural daylight.
keywords	Parametric process, Simulation, Daylighting, Building performance
series	SIGraDi
email
last changed	2021/07/16 11:52

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