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	acadia20_84
id	acadia20_84
authors	Kirova, Nikol; Markopoulou, Areti
year	2020
title	Pedestrian Flow: Monitoring and Prediction
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. 84-93.
doi	https://doi.org/10.52842/conf.acadia.2020.1.084
summary	The worldwide lockdowns during the first wave of the COVID-19 pandemic had an immense effect on the public space. The events brought up an opportunity to redesign mobility plans, streets, and sidewalks, making cities more resilient and adaptable. This paper builds on previous research of the authors that focused on the development of a graphene-based sensing material system applied to a smart pavement and utilized to obtain pedestrian spatiotemporal data. The necessary steps for gradual integration of the material system within the urban fabric are introduced as milestones toward predictive modeling and dynamic mobility reconfiguration. Based on the capacity of the smart pavement, the current research presents how data acquired through an agent-based pedestrian simulation is used to gain insight into mobility patterns. A range of maps representing pedestrian density, flow, and distancing are generated to visualize the simulated behavioral patterns. The methodology is used to identify areas with high density and, thus, high risk of transmitting airborne diseases. The insights gained are used to identify streets where additional space for pedestrians is needed to allow safe use of the public space. It is proposed that this is done by creating a dynamic mobility plan where temporal pedestrianization takes place at certain times of the day with minimal disruption of road traffic. Although this paper focuses mainly on the agent-based pedestrian simulation, the method can be used with real-time data acquired by the sensing material system for informed decision-making following otherwise-unpredictable pedestrian behavior. Finally, the simulated data is used within a predictive modeling framework to identify further steps for each agent; this is used as a proof-of-concept through which more insights can be gained with additional exploration.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	ecaade2024_409
id	ecaade2024_409
authors	Zarzycki, Andrzej
year	2024
title	BIM-Driven Curriculum for Integrated Design Studios: Maintaining data interoperability and design flexibility
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. 27–36
doi	https://doi.org/10.52842/conf.ecaade.2024.2.027
summary	This paper presents a curricular model for an integrated design studio focused on BIM-driven processes, satisfying the NAAB 2020's student performance criteria SC.5 and SC6. These criteria emphasize quantifiable, evidence-based design thinking by requiring the provision of "measurable environmental impacts" and "measurable outcomes of building performance." The studio, serving as a capstone project, integrates accessible design, user and regulatory requirements into building assemblies, structural and environmental systems, and life safety, underscoring the importance of measurable building performance outcomes. The adoption of computational design tools, particularly Building Information Modeling (BIM), facilitates engagement in environmental and user-focused simulations and ensures data interoperability throughout the design and post-occupancy phases. Utilizing a comprehensive set of tools, including life-cycle assessment (LCA) and energy modeling, the curriculum advances beyond simple simulations to support decision-making and multi-objective optimizations. This approach enables a new form of design thinking that incorporates a broader set of variables and considerations, encouraging students to meet various environmental impact and performance benchmarks, including LEED v.5 Certification points and Architecture 2030 energy standards. The integration of scenario simulation tools empowers students to autonomously advance their projects within a framework of constraints, marking a pedagogical shift towards faculty acting as learning facilitators and promoting student autonomy in design evaluation.
keywords	building information modeling, BIM, building performance simulations, design education
series	eCAADe
email
last changed	2024/11/17 22:05

_id	caadria2020_306
id	caadria2020_306
authors	Akizuki, Yuta, Bernhard, Mathias, Kakooee, Reza, Kladeftira, Marirena and Dillenburger, Benjamin
year	2020
title	Generative Modelling with Design Constraints - Reinforcement Learning for Object Generation
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. 445-454
doi	https://doi.org/10.52842/conf.caadria.2020.1.445
summary	Generative design has been explored to produce unprecedented geometries, nevertheless design constraints are, in most cases, second-graded in the computational process. In this paper, reinforcement learning is deployed in order to explore the potential of generative design satisfying design objectives. The aim is to overcome the three issues identified in the state of the art: topological inconsistency, less variations in style and unpredictability in design. The goal of this paper is to develop a machine learning framework, which works as an intellectual design interpreter capable of codifying an input geometry to form a new geometry. Experiments demonstrate that the proposed method can generate a family of tables of unique aesthetics, satisfying topological consistency under given constraints.
keywords	generative design; computational design; data-driven design; reinforcement learning; machine learning
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	acadia20_456
id	acadia20_456
authors	Alali, Jiries; Negar Kalantar, Dr.; Borhani, Alireza
year	2020
title	Casting on a Dump
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. 456-463.
doi	https://doi.org/10.52842/conf.acadia.2020.1.456
summary	“Casting on a dump” focuses on finding accessible, low-tech fabrication methodologies that allow for the construction of parametrically designed nonstandard modular cast panels. Such an approach adopts a computational design framework using a single low-tech and low-energy fabrication device to create nonrepetitive volumetric panels cast in situ. The design input for these panels is derived from design preferences and environmental control data. The technique expands upon easy to fabricate and cast methods, targeting less-developed logistical settings worldwide, and thus responding to imminent needs related to climate, available resources, and the economy.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	ecaade2020_146
id	ecaade2020_146
authors	Andriasyan, Mesrop, Zanelli, Alessandra, Yeghikyan, Gevorg, Asher, Rob and Haeusler, Hank
year	2020
title	Algorithmic Planning and Assessment of Emergency Settlements and Refugee Camps
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. 115-124
doi	https://doi.org/10.52842/conf.ecaade.2020.2.115
summary	The planning quality of refugee camps profoundly affects the people living there. Because of the short time span allotted to planners due to the state of emergency, camps are often poorly planned or not planned at all. This paper proposes tools and methods developed through computational modelling algorithms that can enhance the design procedure and provide instant feedback about the plan performance to the planner. The developed planning framework allows defining the planning guidelines which will be tested for compliance. The paper also shows case studies of analysing an existing refugee camp.
keywords	Refugee camp; shelter; generative design; UNHCR; humanitarian architecture
series	eCAADe
email
last changed	2022/06/07 07:54

_id	acadia20_350
id	acadia20_350
authors	Atanasova, Lidia; Mitterberger, Daniela; Sandy, Timothy; Gramazio, Fabio; Kohler, Matthias; Dörfler, Kathrin
year	2020
title	Prototype As Artefact
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. 350-359.
doi	https://doi.org/10.52842/conf.acadia.2020.1.350
summary	In digital design-to-fabrication workflows in architecture, in which digitally controlled machines perform complex fabrication tasks, all design decisions are typically made before production. In such processes, the formal definition of the final shape is explicitly inscribed into the design model by means of corresponding step-by-step machine instructions. The increasing use of augmented reality (AR) technologies for digital fabrication workflows, in which people are instructed to carry out complex fabrication tasks via AR interfaces, creates an opportunity to question and adjust the level of detail and the nature of such explicit formal definitions. People’s cognitive abilities could be leveraged to integrate explicit machine intelligence with implicit human knowledge and creativity, and thus to open up digital fabrication to intuitive and spontaneous design decisions during the building process. To address this question, this paper introduces open-ended Prototype-as-Artefact fabrication workflows that examine the possibilities of designing and creative choices while building in a human-robot collaborative setting. It describes the collaborative assembly of a complex timber structure with alternating building actions by two people and a collaborative robot, interfacing via a mobile device with object tracking and AR visualization functions. The spatial timber assembly being constructed follows a predefined grammar but is not planned at the beginning of the process; it is instead designed during fabrication. Prototype-as-Artefact thus serves as a case study to probe the potential of both intuitive and rational aspects of building and to create new collaborative work processes between humans and machines.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_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	ijac202018302
id	ijac202018302
authors	Brath Jensen, Mads; Isak Worre Foged and Hans Jørgen Andersen
year	2020
title	A framework for interactive human–robot design exploration
source	International Journal of Architectural Computing vol. 18 - no. 3, 235-253
summary	This study seeks to identify key aspects for increased integration of interactive robotics within the creative design process. Through its character as foundational research, the study aims to contribute to the advancement of new explorative design methods to support architects in their exploration of fabrication and assembly of an integrated performance-driven architecture. The article describes and investigates a proposed design framework for supporting an interactive human–robot design process. The proposed framework is examined through a 3-week architectural studio, with university master students exploring the design of a brick construction with the support of an interactive robotic platform. Evaluation of the proposed framework was done by triangulation of the authors’ qualitative user observations, quantitative logging of the students’ individual design processes, and through questionnaires completed after finishing the studies. The result suggests that interactive human–robot fabrication is a relevant mode of design with positive effect on the process of creative design exploration.
keywords	Design methods, robotic design processes, interactive robotics, computational design, design exploration, creativity
series	other
type	normal paper
email
last changed	2020/11/02 13:39

_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_307
id	ecaade2020_307
authors	Caetano, Ines and Leitao, António
year	2020
title	When the Geometry Informs the Algorithm - A hybrid visual/textual programming framework for facade design
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. 371-380
doi	https://doi.org/10.52842/conf.ecaade.2020.2.371
summary	Facade design is becoming increasingly complex, forcing architects to more frequently resort to analysis and optimization processes. However, these processes are time-consuming and require the coordination of multiple tools. Algorithmic Design (AD) has the potential to overcome these limitations through the use of algorithms implemented in Textual Programming Languages (TPLs) or Visual Programming Languages (VPLs). VPLs are more used in architecture due to their smoother learning curve and user-friendliness, but TPLs are better suited than VPLs for handling complex AD problems. To make TPLs more appealing to architects, we incorporated VPLs' features in the textual paradigm, namely, Visual Input Mechanisms (VIMs). In this paper, we propose an extension to an existing AD framework for the design exploration, analysis, and optimization of facades to support a TPL-based approach that handles VIMs.
keywords	Algorithmic Design; Facade Design; Textual Languages; Visual Input
series	eCAADe
email
last changed	2022/06/07 07:54

_id	sigradi2020_149
id	sigradi2020_149
authors	Canestrino, Giuseppe; Laura, Greco; Spada, Francesco; Lucente, Roberta
year	2020
title	Generating architectural plan with evolutionary multiobjective optimization algorithms: a benchmark case with an existent construction system
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. 149-156
summary	In architectural design, evolutionary multiobjective optimization algorithms (EMOA) have found use in numerous practical applications in which qualitative and quantitative aspects can be transformed into fitness functions to be optimized. This paper shows that they can be used in an architectural plan design process that starts from a more traditional approach. The benchmark case uses a novel construction system, called Ac.Ca. Building, with a vast architectural and technological database, arleady validated, to generate architectural plan for a residential towerbuilding with a parametric approach and EMOA. The proposed framework differs from past research because uses spatial units with high level of architectural and tecnological definition.
keywords	Architectural design, Parametric architecture, Performance-driven design, architectural layout, evolutionary multiobjective optimization
series	SIGraDi
email
last changed	2021/07/16 11:48

_id	cdrf2019_17
id	cdrf2019_17
authors	Chuan Liu, Jiaqi Shen, Yue Ren, and Hao Zheng
year	2020
title	Pipes of AI – Machine Learning Assisted 3D Modeling Design
source	Proceedings of the 2020 DigitalFUTURES The 2nd International Conference on Computational Design and Robotic Fabrication (CDRF 2020)
doi	https://doi.org/https://doi.org/10.1007/978-981-33-4400-6_2
summary	Style transfer is a design technique that is based on Artificial Intelligence and Machine Learning, which is an innovative way to generate new images with the intervention of style images. The output image will carry the characteristic of style image and maintain the content of the input image. However, the design technique is employed in generating 2D images, which has a limited range in practical use. Thus, the goal of the project is to utilize style transfer as a toolset for architectural design and find out the possibility for a 3D modeling design. To implement style transfer into the research, floor plans of different heights are selected from a given design boundary and set as the content images, while a framework of a truss structure is set as the style image. Transferred images are obtained after processing the style transfer neural network, then the geometric images are translated into floor plans for new structure design. After the selection of the tilt angle and the degree of density, vertical components that connecting two adjacent layers are generated to be the pillars of the structure. At this stage, 2D style transferred images are successfully transformed into 3D geometries, which can be applied to the architectural design processes. Generally speaking, style transfer is an intelligent design tool that provides architects with a variety of choices of idea-generating. It has the potential to inspire architects at an early stage of design with not only 2D but also 3D format.
series	cdrf
email
last changed	2022/09/29 07:51

_id	acadia20_638
id	acadia20_638
authors	Claypool, Mollie; Jimenez Garcia, Manuel; Retsin, Gilles; Jaschke, Clara; Saey, Kevin
year	2020
title	Discrete Automation
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. 638-647.
doi	https://doi.org/10.52842/conf.acadia.2020.1.638
summary	Globally, the built environment is inequitable. And while construction automation is often heralded as the solution to labor shortages and the housing crisis, such methods tend to focus on technology, neglecting the wider socioeconomic contexts. Automated Architecture (AUAR), a spinoff of AUAR Labs at The Bartlett School of Architecture, UCL, asserts that a values-centered, decentralized approach to automation centered around local communities can begin to address this material hegemony. The paper introduces and discusses AUAR’s platform-based framework, Discrete Automation, which subverts the status quo of automation that excludes those who are already disadvantaged into an inclusive network capable of providing solutions to both the automation gap and the assembly problem. Through both the wider context of existing modular housing platforms and issues of the current use of automated technologies in architectural production, Discrete Automation is discussed through the example of Block Type A, a discrete timber building system, which in conjunction with its combinatorial app constitutes the base of a community-led housing platform developed by AUAR. Built case studies are introduced alongside a discussion of the applied methodologies and an outlook on the platform’s potential for scalability in an equitable, sustainable manner.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	ecaade2020_314
id	ecaade2020_314
authors	Das, Avishek, Worre Foged, Isak and Jensen, Mads Brath
year	2020
title	Designing with a Robot - Interactive methods for brick wall design using computer vision
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. 605-612
doi	https://doi.org/10.52842/conf.ecaade.2020.2.605
summary	The deterministic and linear nature of robotic processes in architectural construction often allows no or very little adjustments during the fabrication process. If any need for modification arise the process is usually interrupted, changes are accommodated, and the process is resumed or restarted. The rigidity in this fabrication process leaves little room for creative intervention and human activities and robotic process are often considered as two segregated processes.The paper will present and discuss the methodological and design challenges of interactive robotic fabrication of brickwork with an industrial robotic arm, a webcam and bricks with varying color tones. Emphasis will be on the integration of external computer vision libraries within Rhino Grasshopper to augment the interactive robotic process. The paper will describe and demonstrate a framework comprising (1) robotic pick and place, material selection and evaluation using computer vision, (2) interactive robotic actuation and (3) the role of human input during a probabilistic fabrication-based design process.
keywords	interactive robotic fabrication; human robot collaboration; computer vision; masonry; machine learning
series	eCAADe
email
last changed	2022/06/07 07:56

_id	ecaade2020_037
id	ecaade2020_037
authors	Dortheimer, Jonathan, Neuman, Eran and Milo, Tova
year	2020
title	A Novel Crowdsourcing-based Approach for Collaborative Architectural Design
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. 155-164
doi	https://doi.org/10.52842/conf.ecaade.2020.2.155
summary	This paper provides an overview of "Architasker", a large-scale crowdsourcing approach, platform, and method that enables a collaborative professional architectural design process in collaboration with a community of stakeholders. The platform includes communicating complex architectural project requirements; solution space exploration using different micro-tasks like sketching, 2D and 3D CAD; design selection; and design review as an evolutionary process. The architectural crowdsourcing model underlying the platform is contextualized in the state-of-the-art research on creative crowdsourcing methods and is supported by relevant evidence from empirical experiments. Experimental results validate the effectiveness of the method to generate architectural artifacts by harnessing the skills, talents, and experience of architects and the opinions and values of the stakeholders.
keywords	Crowdsourcing; Participatory Design; Human Computation; Creative Crowdsourcing; Co-Design; Collective Intelligence
series	eCAADe
email
last changed	2022/06/07 07:55

_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	acadia20_406
id	acadia20_406
authors	Duong, Eric; Vercoe, Garrett; Baharlou, Ehsan
year	2020
title	Engelbart
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. 406-415.
doi	https://doi.org/10.52842/conf.acadia.2020.1.406
summary	The internet has long been viewed as a cyberspace of free and collective information, allowing for an increase in the diversity of ideas and viewpoints available to the general public. However, critics argue that the emergence of personalization algorithms on social media and other internet platforms instead reduces information diversity by forming “filter bubbles"" of viewpoints similar to the user’s own. The adoption of these personalization algorithms is due in part to advancements in natural language processing, which allow for textual analysis at unprecedented scales. This paper aims to utilize natural language processing and architectural spatial principles to present social media from a collective viewpoint rather than a personalized one. To accomplish this, the paper introduces Engelbart, a data-driven agent-based system, where real-time Twitter conversations are visualized within a two-dimensional environment. This environment is interacted with by the artificial intelligence (AI) agent, Engelbart, which summarizes crowdsourced thoughts and feelings about current trending topics. The functionality of this web application comes from the natural language processing of thousands of tweets per minute throughout several layers of operations, including sentiment analysis and word embeddings. Presented as an understandable interface, it incorporates the values of cybernetics, cyberspace, agent-based modeling, and data ethics to show the potential for social media to become a more transparent space for collective discussion.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	caadria2020_402
id	caadria2020_402
authors	Ezzat, Mohammed
year	2020
title	A Framework for a Comprehensive Conceptualization of Urban Constructs - SpatialNet and SpatialFeaturesNet for computer-aided creative urban design
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. 111-120
doi	https://doi.org/10.52842/conf.caadria.2020.2.111
summary	Analogy is thought to be foundational for designing and for design creativity. Nonetheless, practicing analogical reasoning needs a knowledge-base. The paper proposes a framework for constructing a knowledge-base of urban constructs that builds on an ontology of urbanism. The framework is composed of two modules that are responsible for representing either the concepts or the features of any urban constructs' materialization. The concepts are represented as a knowledge graph (KG) named SpatialNet, while the physical features are represented by a deep neural network (DNN) called SpatialFeaturesNet. For structuring SpatialNet, as a KG that comprehensively conceptualizes spatial qualities, deep learning applied to natural language processing (NLP) is employed. The comprehensive concepts of SpatialNet are firstly discovered using semantic analyses of nine English lingual corpora and then structured using the urban ontology. The goal of the framework is to map the spatial features to the plethora of their matching concepts. The granularity Ã nd the coherence of the proposed framework is expected to sustain or substitute other known analogical, knowledge-based, inspirational design approaches such as case-based reasoning (CBR) and its analogical application on architectural design (CBD).
keywords	Domain-specific knowledge graph of urban qualities; Deep neural network for structuring KG; Natural language processing and comprehensive understanding of urban constructs; Urban cognition and design creativity; Case-based reasoning (CBR) and case-based design (CBD)
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	acadia20_320
id	acadia20_320
authors	Fang, Zhihao; Wu, Yuning; Hassonjee, Ammar; Bidgoli, Ardavan; Cardoso-Llach PhD, Daniel
year	2020
title	Towards a Distributed, Robotically Assisted Construction Framework
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. 320-329.
doi	https://doi.org/10.52842/conf.acadia.2020.1.320
summary	In this paper we document progress towards an architectural framework for adaptive and distributed robotically assisted construction. Drawing from state-of-the-art reinforcement learning techniques, our framework allows for a variable number of robots to adaptively execute simple construction tasks. The paper describes the framework, demonstrates its potential through simulations of pick-and-place and spray-coating construction tasks conducted by a fleet of drones, and outlines a proof-of-concept experiment. With these elements the paper contributes to current research in architectural and construction robotics, particularly to efforts towards more adaptive and hybrid human-machine construction ecosystems. The code is available at: https://github.com/c0deLab/RAiC
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	acadia20_594
id	acadia20_594
authors	Farahbakhsh, Mehdi; Kalantar, Negar; Rybkowski, Zofia
year	2020
title	Impact of Robotic 3D Printing Process Parameters on Bond Strength
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. 594-603.
doi	https://doi.org/10.52842/conf.acadia.2020.1.594
summary	Additive manufacturing (AM), also known as 3D printing, offers advantages over traditional construction technologies, increasing material efficiency, fabrication precision, and speed. However, many AM projects in academia and industrial institutions do not comply with building codes. Consequently, they are not considered safe structures for public utilization and have languished as exhibition prototypes. While three discrete scales—micro, mezzo, and macro—are investigated for AM with paste in this paper, structural integrity has been tackled on the mezzo scale to investigate the impact of process parameters on the bond strength between layers in an AM process. Real-world material deposition in a robotic-assisted AM process is subject to environmental factors such as temperature, humidity, the load of upper layers, the pressure of the nozzle on printed layers, etc. Those factors add a secondary geometric characteristic to the printed objects that was missing in the initial digital model. This paper introduces a heuristic workflow for investigating the impacts of three selective process parameters on the bond strength between layers of paste in the robotic-assisted AM of large-scale structures. The workflow includes a method for adding the secondary geometrical characteristic to the initial 3D model by employing X-ray computerized tomography (CT) scanning, digital image processing, and 3D reconstruction. Ultimately, the proposed workflow offers a pattern library that can be used by an architect or artificial intelligence (AI) algorithms in automated AM processes to create robust architectural forms.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

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