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	ecaade2020_253
id	ecaade2020_253
authors	Buš, Peter
year	2020
title	User-driven Configurable Architectural Assemblies - Towards artificial intelligence-embedded responsive environments
doi	https://doi.org/10.52842/conf.ecaade.2020.2.483
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. 483-490
summary	The paper theoretically elaborates the idea of individual users' customisation activities to create and configure responsive spatial scenarios by means of reconfigurable interactive adaptive assemblies. It reflects Gordon Pask's concept of human and device interaction based on its unpredictable notion speculating a potential to be enhanced by artificial intelligence learning approach of an assembly linked with human activator's participative inputs. Such a link of artificial intelligence, human agency and interactive assembly capable to generate its own spatial configurations by itself and users' stimuli may lead to a new understanding of humans' role in the creation of spatial scenarios. The occupants take the prime role in the evolution of spatial conditions in this respect. The paper aims to position an interaction between the human agents and artificial devices as a participatory and responsive design act to facilitate creative potential of participants as unique individuals without pre-specified or pre-programmed goal set by the designer. Such an approach will pave a way towards true autonomy of responsive built environments, determined by an individual human agent and behaviour of the spatial assemblies to create authentic responsive built forms in a digital and physical space.
keywords	deployable systems; responsive assemblies; embedded intelligence; Learning-to-Design-and-Assembly method; Conversation Theory
series	eCAADe
email
last changed	2022/06/07 07:54

_id	ecaade2020_138
id	ecaade2020_138
authors	Patel, Sayjel Vijay, Tchakerian, Raffi, Lemos Morais, Renata, Zhang, Jie and Cropper, Simon
year	2020
title	The Emoting City - Designing feeling and artificial empathy in mediated environments
doi	https://doi.org/10.52842/conf.ecaade.2020.2.261
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. 261-270
summary	This paper presents a theoretical blueprint for implementing artificial empathy into the built environment. Transdisciplinary design principles have oriented the creation of a new model for autonomous environments integrating psychology, architecture, digital media, affective computing and interactive UX design. 'The Emoting City', an interactive installation presented at the 2019 Shenzhen Bi-City Biennale of Urbanism/Architecture, is presented as a first step to explore how to engage AI-driven sensing by integrating human perception, cognition and behaviour in a real-world scenario. The approach described encompasses two main elements: embedded cyberception and responsive surfaces. Its human-AI interface enables new modes of blended interaction that are conducive to self-empathy and insight. It brings forth a new proposition for the development of sensing systems that go beyond social robotics into the field of artificial empathy. The installation innovates in the design of seamless affective computing that combines 'alloplastic' and 'autoplastic' architectures. We believe that our research signals the emergence of a potential revolution in responsive environments, offering a glimpse into the possibility of designing intelligent spaces with the ability to sense, inform and respond to human emotional states in ways that promote personal, cultural and social evolution.
keywords	Artificial Intelligence; Responsive Architecture; Affective Computation; Human-AI Interfaces; Artificial Empathy
series	eCAADe
email
last changed	2022/06/07 07:59

_id	caadria2020_395
id	caadria2020_395
authors	Loo, Stella Yi Ning, Jayashankar, Dhileep Kumar, Gupta, Sachin and Tracy, Kenneth
year	2020
title	Hygro-Compliant: Responsive Architecture with Passively Actuated Compliant Mechanisms
doi	https://doi.org/10.52842/conf.caadria.2020.1.223
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. 223-232
summary	Research investigating water-driven passive actuation demonstrates the potential to transform how buildings interact with their environment while avoiding the complications of conventionally powered actuation. Previous experiments evidence the possibilities of bi-layer materials (Reichert, Menges, and Correa 2015; Correa et al. 2015) and mechanical assemblies with discretely connected actuating members (Gupta et al. 2019). By leveraging changes in weather to power actuated building components these projects explore the use of smart biomaterials and responsive building systems. Though promising the implementation of these technologies requires deep engagement into material synthesis and fabrication. This paper presents the design and prototyping of a rain responsive faÃ§ade system using chitosan hygroscopic films as actuators counterbalanced by programmed compliant mechanisms. Building on previous work into chitosan film assemblies this research focuses on the development of compliant mechanisms as a means of controlling movement without over-complicated rotating parts.
keywords	Passive Actuation; Responsive Architecture; Bio-polymers; 4D Structures; Compliant Mechanism
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	acadia20_136p
id	acadia20_136p
authors	López Lobato, Déborah; Charbel, Hadin
year	2020
title	Foll(i)cle
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. 136-141
summary	In the early months of 2019, air pollution in Bangkok reached a record high, bringing national and international attention to the air quality in the South East Asian cosmopolitan. Although applications such as real-time pollution maps provide an environmental reading from the exterior, such information reveals the ‘here and now,’ where its record is inevitably lost through the ‘refreshing’ process of the live update and does not take increment and accumulation as factors to consider. The project was conceived around understanding the human body as precisely that medium that resists classification as either an interior or exterior environment that inherently performs as an impressionable record of its surroundings. Can a city’s toxicity be read through its living constituents? Can the living bodies that dwell, navigate, breathe, and process habitable environments be accessed? Can architecture retain a degree of independence while also performing as a beacon for the collective? Along this line of questioning, it was found that human hair can be transformed from a material that is effortlessly and continuously grown, cut, stylized, and discarded, and instead be intercepted and used in the production of public information gathering. Foll(i)cle is a collective being made of discarded human hair. Performing as a parliament for collectivity embedded with a protocol; the hairy pavilion invites the public in and presents them with a device at the center that hosts all the necessary equipment and information for anonymously and voluntarily providing hair samples for heavy metal analysis, the data of which is used in making a publically accessible toxi-cartography. Although humans are the primary subject for this study, the results suggest that extending the methodology to non-humans could prove useful in reading urban toxicity through various life forms.
series	ACADIA
type	project
email
last changed	2021/10/26 08:03

_id	ecaade2020_499
id	ecaade2020_499
authors	Ashour, Ziad and Yan, Wei
year	2020
title	BIM-Powered Augmented Reality for Advancing Human-Building Interaction
doi	https://doi.org/10.52842/conf.ecaade.2020.1.169
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. 169-178
summary	The shift from computer-aided design (CAD) to building information modeling (BIM) has made the adoption of augmented reality (AR) promising in the field of architecture, engineering and construction. Despite the potential of AR in this field, the industry and professionals have still not fully adopted it due to registration and tracking limitations and visual occlusions in dynamic environments. We propose our first prototype (BIMxAR), which utilizes existing buildings' semantically rich BIM models and contextually aligns geometrical and non-geometrical information with the physical buildings. The proposed prototype aims to solve registration and tracking issues in dynamic environments by utilizing tracking and motion sensors already available in many mobile phones and tablets. The experiment results indicate that the system can support BIM and physical building registration in outdoor and part of indoor environments, but cannot maintain accurate alignment indoor when relying only on a device's motion sensors. Therefore, additional computer vision and AI (deep learning) functions need to be integrated into the system to enhance AR model registration in the future.
keywords	Augmented Reality; BIM; BIM-enabled AR; GPS; Human-Building Interactions; Education
series	eCAADe
email
last changed	2022/06/07 07:54

_id	sigradi2020_60
id	sigradi2020_60
authors	Asmar, Karen El; Sareen, Harpreet
year	2020
title	Machinic Interpolations: A GAN Pipeline for Integrating Lateral Thinking in Computational Tools of Architecture
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. 60-66
summary	In this paper, we discuss a new tool pipeline that aims to re-integrate lateral thinking strategies in computational tools of architecture. We present a 4-step AI-driven pipeline, based on Generative Adversarial Networks (GANs), that draws from the ability to access the latent space of a machine and use this space as a digital design environment. We demonstrate examples of navigating in this space using vector arithmetic and interpolations as a method to generate a series of images that are then translated to 3D voxel structures. Through a gallery of forms, we show how this series of techniques could result in unexpected spaces and outputs beyond what could be produced by human capability alone.
keywords	Latent space, GANs, Lateral thinking, Computational tools, Artificial intelligence
series	SIGraDi
email
last changed	2021/07/16 11:48

_id	caadria2020_141
id	caadria2020_141
authors	Dezen-Kempter, Eloisa, Mezencio, Davi Lopes, Miranda, Erica De Matos, De SÃ¡, Danilo Pico and Dias, Ulisses
year	2020
title	Towards a Digital Twin for Heritage Interpretation - from HBIM to AR visualization
doi	https://doi.org/10.52842/conf.caadria.2020.2.183
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. 183-191
summary	Data-driven Building Information Modelling (BIM) technology has brought new tools to efficiently deal with the tension between the real and the virtual environments in the field of Architecture, Engineering, Construction, and Operation (AECO). For historic assets, BIM represents a paradigm shift, enabling better decision-making about preventive maintenance, heritage management, and interpretation. The potential application of the Historic-BIM is creating a digital twin of the asset. This paper deals with the concept of a virtual environment for the consolidation and dissemination of heritage information. Here we show the process of creating interactive virtual environments for the Pampulha Modern Ensemble designed by Oscar Niemeyer in the 1940s, and the workflow to their dissemination in an AR visualization APP. Our results demonstrate the APP feasibility to the Pampulha's building interpretation.
keywords	Augmented Reality (AR); Historic Building Information Modelling (HBIM); Heritage Interpretation; Modern Architecture
series	CAADRIA
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
doi	https://doi.org/10.52842/conf.acadia.2020.1.406
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.
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_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
doi	https://doi.org/10.52842/conf.caadria.2020.1.475
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
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_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
doi	https://doi.org/10.52842/conf.caadria.2020.2.629
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
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	caadria2020_091
id	caadria2020_091
authors	Ren, Yue and Zheng, Hao
year	2020
title	The Spire of AI - Voxel-based 3D Neural Style Transfer
doi	https://doi.org/10.52842/conf.caadria.2020.2.619
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. 619-628
summary	In the architecture field, humans have mastered various skills for creating unique spatial experiences with unknown interplays between known contents and styles. Meanwhile, machine learning, as a popular tool for mapping different input factors and generating unpredictable outputs, links the similarity of the machine intelligence with the typical form-finding process. Style Transfer, therefore, is widely used in 2D visuals for mixing styles while inspiring the architecture field with new form-finding possibilities. Researchers have applied the algorithm in generating 2D renderings of buildings, limiting the results in 2D pixels rather than real full volume forms. Therefore, this paper aims to develop a voxel-based form generation methodology to extend the 3D architectural application of Style Transfer. Briefly, through cutting the original 3D model into multiple plans and apply them to the 2D style image, the stylized 2D results generated by Style Transfer are then abstracted and filtered as groups of pixel points in space. By adjusting the feature parameters with user customization and replacing pixel points with basic voxelization units, designers can easily recreate the original 3D geometries into different design styles, which proposes an intelligent way of finding new and inspiring 3D forms.
keywords	Form Finding; Machine Learning; Artificial Intelligence; Style Transfer
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	caadria2020_154
id	caadria2020_154
authors	Stojanovic, Vladeta, Hagedorn, Benjamin, Trapp, Matthias and DÃ¶llner, JÃ¼rgen
year	2020
title	Ontology-Driven Analytics for Indoor Point Clouds
doi	https://doi.org/10.52842/conf.caadria.2020.2.537
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. 537-546
summary	Automated processing, semantic enrichment and visual analytics methods for point clouds are often use-case specific for a given domain (e.g, for Facility Management (FM) applications). Currently, this means that applicable processing techniques, semantics and visual analytics methods need to be selected, generated or implemented by human domain experts, which is an error-prone, subjective and non-interoperable process. An ontology-driven analytics approach can be used to solve this problem by creating and maintaining a Knowledge Base, and utilizing an ontology for automatically suggesting optimal selection of processing and analytics techniques for point clouds. We present an approach of an ontology-driven analytics concept and system design, which supports smart representation, exploration, and processing of indoor point clouds. We present and provide an overview of high-level concept and architecture for such a system, along with related key technologies and approaches based on previously published case studies. We also describe key requirements for system components, and discuss the feasibility of their implementation within a Service-Oriented Architecture (SOA).
keywords	Knowledge Base; Point Clouds; Semantic Enrichment; Service-Oriented Architecture; Ontology
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	ecaade2020_015
id	ecaade2020_015
authors	Yazici, Sevil
year	2020
title	A machine-learning model driven by geometry, material and structural performance data in architectural design process
doi	https://doi.org/10.52842/conf.ecaade.2020.1.411
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. 411-418
summary	Artificial Intelligence (AI), based on interpretation of data, influences various professions including architectural design today. Although research on integrating conceptual design with Machine Learning (ML) algorithms as a subset of the AI has been investigated previously, there is not a framework towards integration of architectural geometry with material properties and structural performance data towards decision making in the early-design phase. Undertaking performance simulations require significant amount of computation power and time. The aim of this research is to integrate ML algorithms into design process to achieve time efficiency and improve design results. The proposed workflow consists of three stages, including generation of the parametric model; running structural performance simulations to collect the data, and operating the ML algorithms, including Artificial Neural Network (ANN), Non-Linear Regression (NLR) and Gaussian Mixture (GM) for undertaking different tasks. The results underlined that the system generates relatively fast solutions with accuracy. Additionally, ML algorithms can assist generative design processes.
keywords	Machine-learning; performance simulation; data-driven design; early-design phase
series	eCAADe
email
last changed	2022/06/07 07:57

_id	ijac202321102
id	ijac202321102
authors	Özerol, Gizem; Semra Arslan Selçuk
year	2023
title	Machine learning in the discipline of architecture: A review on the research trends between 2014 and 2020
source	International Journal of Architectural Computing 2023, Vol. 21 - no. 1, pp. 23–41
summary	Abstract Through the recent technological developments within the fourth industrial revolution, artificial intelligence (AI) studies have had a huge impact on various disciplines such as social sciences, information communication technologies (ICTs), architecture, engineering, and construction (AEC). Regarding decision-making and forecasting systems in particular, AI and machine learning (ML) technologies have provided an opportunity to improve the mutual relationships between machines and humans. When the connection between ML and architecture is considered, it is possible to claim that there is no parallel acceleration as in other disciplines. In this study, and considering the latest breakthroughs, we focus on revealing what ML and architecture have in common. Our focal point is to reveal common points by classifying and analyzing current literature through describing the potential of ML in architecture. Studies conducted using ML techniques and subsets of AI technologies were used in this paper, and the resulting data were interpreted using the bibliometric analysis method. In order to discuss the state-of-the-art research articles which have been published between 2014 and 2020, main subjects, subsets, and keywords were refined through the search engines. The statistical figures were demonstrated as huge datasets, and the results were clearly delineated through Sankey diagrams. Thanks to bibliometric analyses of the current literature of WOS (Web of Science), CUMINCAD (Cumulative Index about publications in Computer Aided Architectural Design supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD, and CAAD futures), predictable data have been presented allowing recommendations for possible future studies for researchers.
keywords	Artificial intelligence, machine learning, deep learning, architectural research, bibliometric analysis
series	journal
last changed	2024/04/17 14:30

_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	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
doi	https://doi.org/10.52842/conf.acadia.2020.1.074
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.
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	acadia20_688
id	acadia20_688
authors	del Campo, Matias; Carlson, Alexandra; Manninger, Sandra
year	2020
title	3D Graph Convolutional Neural Networks in Architecture Design
doi	https://doi.org/10.52842/conf.acadia.2020.1.688
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. 688-696.
summary	The nature of the architectural design process can be described along the lines of the following representational devices: the plan and the model. Plans can be considered one of the oldest methods to represent spatial and aesthetic information in an abstract, 2D space. However, to be used in the design process of 3D architectural solutions, these representations are inherently limited by the loss of rich information that occurs when compressing the three-dimensional world into a two-dimensional representation. During the first Digital Turn (Carpo 2013), the sheer amount and availability of models increased dramatically, as it became viable to create vast amounts of model variations to explore project alternatives among a much larger range of different physical and creative dimensions. 3D models show how the design object appears in real life, and can include a wider array of object information that is more easily understandable by nonexperts, as exemplified in techniques such as building information modeling and parametric modeling. Therefore, the ground condition of this paper considers that the inherent nature of architectural design and sensibility lies in the negotiation of 3D space coupled with the organization of voids and spatial components resulting in spatial sequences based on programmatic relationships, resulting in an assemblage (DeLanda 2016). These conditions constitute objects representing a material culture (the built environment) embedded in a symbolic and aesthetic culture (DeLanda 2016) that is created by the designer and captures their sensibilities.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	ecaade2020_034
id	ecaade2020_034
authors	Hamilton, William, Butler, Andrew, Gardner, Nicole, Haeusler, M. Hank, Ramos, Cristina and Zavoleas, Yannis
year	2020
title	Keeping up with the Code - Communicating the Decision Making History of Architectural Scripts
doi	https://doi.org/10.52842/conf.ecaade.2020.1.633
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. 633-642
summary	As the architecture industry engages computational methods to automate and optimise design processes, decision-making becomes embedded and hidden within complex code. Even where employees understand the procedure and logic of architectural scripts they may struggle to understand those developed by others and used on different projects. Accordingly, this paper outlines the research and development of a workflow to trace and document the decision-making history (DMH) of architectural scripts. This develops the relational database Huginn to test the feasibility of tracing decision-making history in scripting through a Python Web framework that sends data in a JavaScript Object Notation (JSON) format from Grasshopper. The research outcomes successfully demonstrate a system that can link a series of objects to their 'decision' origins. This contributes to informing the development of theoretically-grounded coding protocols and simultaneously demystifying the complexity of architectural scripting and communicating the significance of data-augmented decision making within contemporary architectural design processes.
keywords	Automation in Architecture; Design Optimisation; Architectural Scripting; Decision Making History; Database; Visual Programming
series	eCAADe
email
last changed	2022/06/07 07:50

_id	ecaade2020_478
id	ecaade2020_478
authors	Han, Yoon J. and Kotnik, Toni
year	2020
title	A Tomographic computation of Spatial Dynamics
doi	https://doi.org/10.52842/conf.ecaade.2020.2.089
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. 89-94
summary	Waning of vigorous discourses about the idea of space as essence in architectural design concurred with the emergence of digital architecture. The notion of space was replaced with the underlying notion of form facilitating optimization of performances and form-generation in digital design ever since. Within the context of digital architecture, the current research investigates a formal method to reintroduce spatial aspects, based on dynamics of architectural space in relation to form, into digital design processes. Accordingly, a computational framework is devised employing the idea of space as dynamic field conditions, in order to capture dynamic interrelation of architectural space with architectural form. That is, spatial dynamics are regarded as data embedded in architectural space, that can imply operational aspects of spatial experiences and / or stimulate corporeal engagements with experiential space, as concepts as action potentials and affordances do (Rasmussen 1964). As a result, the research aims to contribute to the body of knowledge that endeavour to systematize architectural sensibilities that are implicit in design processes by externalization utilizing computation.
keywords	spatial dynamics; dynamic field conditions; dynamic displacement
series	eCAADe
email
last changed	2022/06/07 07:50

_id	acadia20_382
id	acadia20_382
authors	Hosmer, Tyson; Tigas, Panagiotis; Reeves, David; He, Ziming
year	2020
title	Spatial Assembly with Self-Play Reinforcement Learning
doi	https://doi.org/10.52842/conf.acadia.2020.1.382
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. 382-393.
summary	We present a framework to generate intelligent spatial assemblies from sets of digitally encoded spatial parts designed by the architect with embedded principles of prefabrication, assembly awareness, and reconfigurability. The methodology includes a bespoke constraint-solving algorithm for autonomously assembling 3D geometries into larger spatial compositions for the built environment. A series of graph-based analysis methods are applied to each assembly to extract performance metrics related to architectural space-making goals, including structural stability, material density, spatial segmentation, connectivity, and spatial distribution. Together with the constraint-based assembly algorithm and analysis methods, we have integrated a novel application of deep reinforcement (RL) learning for training the models to improve at matching the multiperformance goals established by the user through self-play. RL is applied to improve the selection and sequencing of parts while considering local and global objectives. The user’s design intent is embedded through the design of partial units of 3D space with embedded fabrication principles and their relational constraints over how they connect to each other and the quantifiable goals to drive the distribution of effective features. The methodology has been developed over three years through three case study projects called ArchiGo (2017–2018), NoMAS (2018–2019), and IRSILA (2019-2020). Each demonstrates the potential for buildings with reconfigurable and adaptive life cycles.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

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