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	cdrf2019_265
id	cdrf2019_265
authors	Yue Qi, Ruqing Zhong, Benjamin Kaiser, Long Nguyen,Hans Jakob Wagner, Alexander Verl, and Achim Menges
year	2020
title	Working with Uncertainties: An Adaptive Fabrication Workflow for Bamboo Structures
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_25
summary	This paper presents and investigates a cyber-physical fabrication work-flow, which can respond to the deviations between built- and designed form in realtime with vision augmentation. We apply this method for large scale structures built from natural bamboo poles. Raw bamboo poles obtain evolutionarily optimized fibrous layouts ideally suitable for lightweight and sustainable building construction. Nevertheless, their intrinsically imprecise geometries pose a challenge for reliable, automated construction processes. Despite recent digital advancements, building with bamboo poles is still a labor-intensive task and restricted to building typologies where accuracy is of minor importance. The integration of structural bamboo poles with other building layers is often limited by tolerance issues at the interfaces, especially for large scale structures where deviations accumulate incrementally. To address these challenges, an adaptive fabrication process is developed, in which existing deviations can be compensated by changing the geometry of subsequent joints to iteratively correct the pose of further elements. A vision-based sensing system is employed to three-dimensionally scan the bamboo elements before and during construction. Computer vision algorithms are used to process and interpret the sensory data. The updated conditions are streamed to the computational model which computes tailor-made bending stiff joint geometries that can then be directly fabricated on-the-fly. In this paper, we contextualize our research and investigate the performance domains of the proposed workflow through initial fabrication tests. Several application scenarios are further proposed for full scale vision-augmented bamboo construction systems.
series	cdrf
email
last changed	2022/09/29 07:51

_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	caadria2020_446
id	caadria2020_446
authors	Cho, Dahngyu, Kim, Jinsung, Shin, Eunseo, Choi, Jungsik and Lee, Jin-Kook
year	2020
title	Recognizing Architectural Objects in Floor-plan Drawings Using Deep-learning Style-transfer Algorithms
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. 717-725
doi	https://doi.org/10.52842/conf.caadria.2020.2.717
summary	This paper describes an approach of recognizing floor plans by assorting essential objects of the plan using deep-learning based style transfer algorithms. Previously, the recognition of floor plans in the design and remodeling phase was labor-intensive, requiring expert-dependent and manual interpretation. For a computer to take in the imaged architectural plan information, the symbols in the plan must be understood. However, the computer has difficulty in extracting information directly from the preexisting plans due to the different conditions of the plans. The goal is to change the preexisting plans to an integrated format to improve the readability by transferring their style into a comprehensible way using Conditional Generative Adversarial Networks (cGAN). About 100-floor plans were used for the dataset which was previously constructed by the Ministry of Land, Infrastructure, and Transport of Korea. The proposed approach has such two steps: (1) to define the important objects contained in the floor plan which needs to be extracted and (2) to use the defined objects as training input data for the cGAN style transfer model. In this paper, wall, door, and window objects were selected as the target for extraction. The preexisting floor plans would be segmented into each part, altered into a consistent format which would then contribute to automatically extracting information for further utilization.
keywords	Architectural objects; floor plan recognition; deep-learning; style-transfer
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	acadia20_464
id	acadia20_464
authors	Elberfeld, Nathaniel; Tessmer, Lavender; Waller, Alexandra
year	2020
title	A Case for Lace
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. 464-473.
doi	https://doi.org/10.52842/conf.acadia.2020.1.464
summary	Textiles and architecture share a long, intertwined history from the earliest enclosures to contemporary high-tech tensile structures. In the Four Elements of Architecture, Gottfried Semper (2010) posited wickerwork and carpet enclosures to be the essential origins of architectural space. More recently, architectural designers are capitalizing on the characteristics of textiles that are difficult or impossible to reproduce with other material systems: textiles are pliable, scalable, and materially efficient. As industrial knitting machines join robotic systems in architecture schools with fabrication- forward agendas, much of the recent developments in textile-based projects make use of knitting. In this paper, we propose an alternative textile technique, lacemaking, for architectural fabrication. We present a method for translating traditional lacemaking techniques to an architectural scale and explore its relative advantages over other textiles. In particular, we introduce bobbin lace and describe its steps both in traditional production and at an architectural scale. We use the unique properties of bobbin lace to form workflows for fabrication and computational analysis. An example of computational analysis demonstrates the ability to optimize lace-based designs towards particular labor objectives. We discuss opportunities for automation and consider the broader implications of understanding a material system relative to the cost of labor to produce designs using it.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	acadia20_574
id	acadia20_574
authors	Nguyen, John; Peters, Brady
year	2020
title	Computational Fluid Dynamics in Building Design Practice
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. 574-583.
doi	https://doi.org/10.52842/conf.acadia.2020.1.574
summary	This paper provides a state-of-the-art of computational fluid dynamics (CFD) in the building industry. Two methods were used to find this new knowledge: a series of interviews with leading architecture, engineering, and software professionals; and a series of tests in which CFD software was evaluated using comparable criteria. The paper reports findings in technology, workflows, projects, current unmet needs, and future directions. In buildings, airflow is fundamental for heating and cooling, as well as occupant comfort and productivity. Despite its importance, the design of airflow systems is outside the realm of much of architectural design practice; but with advances in digital tools, it is now possible for architects to integrate air flow into their building design workflows (Peters and Peters 2018). As Chen (2009) states, “In order to regulate the indoor air parameters, it is essential to have suitable tools to predict ventilation performance in buildings.” By enabling scientific data to be conveyed in a visual process that provides useful analytical information to designers (Hartog and Koutamanis 2000), computer performance simulations have opened up new territories for design “by introducing environments in which we can manipulate and observe” (Kaijima et al. 2013). Beyond comfort and productivity, in recent months it has emerged that air flow may also be a matter of life and death. With the current global pandemic of SARS-CoV-2, it is indoor environments where infections most often happen (Qian et al. 2020). To design architecture in a post-COVID-19 environment will require an in-depth understanding of how air flows through space.
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	caadria2020_257
id	caadria2020_257
authors	Lu, Yao, Birol, Eda Begum, Johnson, Colby, Hernandez, Christopher and Sabin, Jenny
year	2020
title	A Method for Load-responsive Inhomogeneity and Anisotropy in 3D Lattice Generation Based on Ellipsoid Packing
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. 395-404
doi	https://doi.org/10.52842/conf.caadria.2020.1.395
summary	3D lattice structures are gaining widespread application in multiple design fields. While the number of projects that utilize load-responsive inhomogeneous and anisotropic 3D lattices in design applications increase, accessible and effective algorithmic generation methodologies remain lacking. This paper addresses this gap by introducing a novel computational method for controlled load-responsive inhomogeneity and anisotropy in 3D lattice generation. The presented methods employ a responsive Ellipsoid Packing algorithm informed by the global tensor field of the packing geometry, followed by a Kissing Ellipsoids algorithm to generate the lattice. Load specific anisotropy and inhomogeneity in the ellipsoid packing process is achieved in response to the magnitude and directionality values of the global tensor field and specialized responsive lattices are easily generated. The proposed Ellipsoid Packing workflow is compared to various common lattice generation algorithms. Results show improvement in mechanical performance.
keywords	3D lattice; ellipsoid packing; bio-inspired; algorithmic design; ceramic brick
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	ecaade2020_284
id	ecaade2020_284
authors	Tan, Rachel, Patt, Trevor, Koh, Seow Jin and Chen, Edmund
year	2020
title	Exploration & Validation - Making sense of generated data in large option sets
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. 653-662
doi	https://doi.org/10.52842/conf.ecaade.2020.1.653
summary	The project is a real-world case study where we advised our client in the selection of a viable and well-performing design from a set of computationally generated options. This process was undertaken while validating the algorithmic generative process and user-defined evaluation criteria through scrutinizing the other alternative options to ensure ample variability was considered. Optimisation algorithms were not ideal as low performing options were not visible to validate variability. We established variability by extracting the different groups of options, proving to the client that various operational behaviours were present and accounted for. In order to sieve through the noise and derive meaningful results, we employed methods to filter through thousands of options, including: k-means clustering, archetypal labelling and analysis, pareto front analysis and visualisation overlays. We present a sense-making and decision-making process that utilizes principles of genetic algorithms and analysis of multi-dimensional user-derived evaluation scores. To enable the client's confidence in the computational model, we proved the effectiveness of the generative model through communicating and visualizing the impact of different criterias. This ensured that operational needs were considered. The visualization methods we employed, including pareto front extraction and analysis eventually helped our clients to arrive at a decision.
keywords	generative design; validation; multi-objective optimisation; k-means; pareto front; decision-making
series	eCAADe
email
last changed	2022/06/07 07:56

_id	ecaade2020_517
id	ecaade2020_517
authors	Lharchi, Ayoub, Ramsgaard Thomsen, Mette and Tamke, Martin
year	2020
title	Connected Augmented Assembly - Cloud based Augmented Reality applications in architecture
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. 179-186
doi	https://doi.org/10.52842/conf.ecaade.2020.1.179
summary	Current design practices rely on a set of computational tools to simulate and optimize the design in regards to questions concerning architecture, engineering, and construction. However, little progress has been made in tools related to the design and execution of a building assembly. This paper aims to present an integrated procedure that targets the assembly of complex structures. Two challenges are identified and addressed: first, the necessity of a connected design environment where multiple stakeholders can communicate, modify, and give feedback on the assembly sequence. Second, the instructions for the assembly of structures to untrained users. The suggested method is based on the Assembly Information Modeling framework, which provides a general approach to generate assembly information from CAD data and utilizes AEC cloud platforms as a base for communication and Augmented Reality devices as a Human Machine Interface. Ultimately, both cases are combined to constitute Connected Augmented Assembly, a bidirectional approach to assembly design, review, and execution.
keywords	assembly sequence; augmented reality; assisted assembly; cloud aec; assembly information modeling
series	eCAADe
email
last changed	2022/06/07 07:52

_id	cdrf2019_114
id	cdrf2019_114
authors	Namju Lee
year	2020
title	Understanding and Analyzing the Characteristics of the Third Place in Urban Design: A Methodology for Discrete and Continuous Data in Environmental 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_11
summary	With a rapid development of data-driven technologies, many opportunities have arisen to understand and characterize urban contexts. This paper addresses the methodology to understand a place in urban settings through the lens of third places and motility based on the walkable distance. To capture and process third-place data, fetched from Google Places, based on a given location, this paper discuses two data structures and process of discrete and continuous data. Representation of third places in a specific location of a city is characterized by representative queries. Its identified chart as a perspective of understanding a designated area could compare with other charts in different places. This method allows us to distinguish the constitution of third places based on the distance among places, enabling us to develop design strategies to differentiate or accord the sites based on mobility. The goal is to set up a method to process, interpolate, and visualize discrete and continuous urban data with representative queries of third places based on distance.
series	cdrf
email
last changed	2022/09/29 07:51

_id	acadia20_188
id	acadia20_188
authors	Tian, Runjia; Wang, Yujie; Yüce Gün, Onur
year	2020
title	Data-Driven Midsole
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. 188-197.
doi	https://doi.org/10.52842/conf.acadia.2020.2.188
summary	With the advancement of additive manufacturing, computational approaches are gaining popularity in midsole design. We develop an experimental understanding of the midsole as a field and develop designs that are informed by running data. We streamline two data types, namely underfoot pressure and surface deformation, to generate designs. Unlike typical approaches in which certain types of lattices get distributed across the midsole according to average pressure data, we use ARAMIS data, reflecting the distinct surface deformation characteristics, as our primary design driver. We analyze both pressure and deformation data temporally, and temporal data patterns help us generate and explore a design space to search for optimal designs. First, we define multiple zones across the midsole space using ARAMIS data clustering. Then we develop ways to blend and distribute auxetic and isosurface lattices across the midsole. We hybridize these two structures and blend data-determined zones to enhance visual continuity while applying FEA simulations to ensure structural integrity. This multi-objective optimization approach helps enhance the midsole’s structural performance and visual coherence while introducing a novel approach to 3D-printed footwear design.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	acadia20_236p
id	acadia20_236p
authors	Anton, Ana; Jipa, Andrei; Reiter, Lex; Dillenburger, Benjamin
year	2020
title	Fast Complexity
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. 236-241
summary	The concrete industry is responsible for 8% of the global CO2 emissions. Therefore, using concrete in more complex and optimized shapes can have a significant benefit to the environment. Digital fabrication with concrete aims to overcome the geometric limitations of standardized formworks and thereby reduce the ecological footprint of the building industry. One of the most significant material economy potentials is in structural slabs because they represent 85% of the weight of multi-story concrete structures. To address this opportunity, Fast Complexity proposes an automated fabrication process for highly optimized slabs with ornamented soffits. The method combines reusable 3D-printed formwork (3DPF) and 3D concrete printing (3DCP). 3DPF uses binder-jetting, a process with submillimetre resolution. A polyester coating is applied to ensure reusability and smooth concrete surfaces otherwise not achievable with 3DCP alone. 3DPF is selectively used only where high-quality finishing is necessary, while all other surfaces are fabricated formwork-free with 3DCP. The 3DCP process was developed interdisciplinary at ETH Zürich and employs a two-component material system consisting of Portland cement mortar and calcium aluminate cement accelerator paste. This fabrication process provides a seamless transition from digital casting to 3DCP in a continuous automated process. Fast Complexity selectively uses two complementary additive manufacturing methods, optimizing the fabrication speed. In this regard, the prototype exhibits two different surface qualities, reflecting the specific resolutions of the two digital processes. 3DCP inherits the fine resolution of the 3DPF strictly for the smooth, visible surfaces of the soffit, for which aesthetics are essential. In contrast, the hidden parts of the slab use the coarse resolution specific to the 3DCP process, not requiring any formwork and implicitly achieving faster fabrication. In the context of an increased interest in construction additive manufacturing, Fast Complexity explicitly addresses the low resolution, lack of geometric freedom, and limited reinforcement options typical to layered extrusion 3DCP, as well as the limited customizability in concrete technology.
series	ACADIA
type	project
email
last changed	2021/10/26 08:08

_id	caadria2020_071
id	caadria2020_071
authors	Carroll, Stan
year	2020
title	Managing Risk in a Research-Based Practice as Projects Scale To Construction:A Case Study
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. 65-74
doi	https://doi.org/10.52842/conf.caadria.2020.1.065
summary	Research-based architectural practices often experiment along the bleeding edge of the new frontier of design and include developing methodologies unfamiliar to the construction industry. Successfully implementing the resulting research methodologies to an architectural scale requires careful consideration of risk management within a Design-Bid-Build construction project. How a firm manages the risk when scaling a research conclusion to an architectural scale is an essential aspect of assuring the success of the project. These considerations are particularly acute within firms whose research involves convoluted geometry. In the field of doubly-curved geometric material systems, the level of precision required to manage professional risk is commensurate with the level of geometric complexity. Adopting the mindset of a Medieval master mason's process within the context of twenty-first-century materials and processes can be a method toward a successful project. By performing well thought-out transfer procedures of digital data, resolving the fundamental challenges of fabrication, and including structural analysis as a part of the early design phases, experimental architectural expressions can be realized without extra financial risk to the designer.
keywords	Risk Management; Research-Based Practice; Complex Geometry; Digital Fabrication; Computational Design
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	sigradi2020_627
id	sigradi2020_627
authors	Lima, Fernando T.; Muthumanickam, Naveen K.; Miller, Marc L.; Duarte, José P.
year	2020
title	World Studio: a pedagogical experience using shape grammars and parametric approaches to design in the context of informal settlements
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. 627-634
summary	The World is experiencing a rapid surge in urban population, in addition to fast urbanization processes. Contemporary cities witness the rise of numerous urban and social problems, leading to the emergence of informal settlements. Still, computational and parametric resources have increasingly been adopted in novel approaches to urban planning and design. These resources can be used in informal settlements to improve urban quality without losing their essential features. This paper describes a teaching experience in the context of a design studio that uses shape grammars and parametric tools to design for an informal settlement context in Ahmedabad, India.
keywords	Shape grammars, Parametrization, Informal settlements, Urban design, Teaching experience
series	SIGraDi
email
last changed	2021/07/16 11:52

_id	caadria2020_384
id	caadria2020_384
authors	Patt, Trevor Ryan
year	2020
title	Spectral Clustering for Urban Networks
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. 91-100
doi	https://doi.org/10.52842/conf.caadria.2020.2.091
summary	As planetary urbanization accelerates, the significance of developing better methods for analyzing and making sense of complex urban networks also increases. The complexity and heterogeneity of contemporary urban space poses a challenge to conventional descriptive tools. In recent years, the emergence of urban network analysis and the widespread availability of GIS data has brought network analysis methods into the discussion of urban form. This paper describes a method for computationally identifying clusters within urban and other spatial networks using spectral analysis techniques. While spectral clustering has been employed in some limited urban studies, on large spatialized datasets (particularly in identifying land use from orthoimages), it has not yet been thoroughly studied in relation to the space of the urban network itself. We present the construction of a weighted graph Laplacian matrix representation of the network and the processing of the network by eigen decomposition and subsequent clustering of eigenvalues in 4d-space.In this implementation, the algorithm computes a cross-comparison for different numbers of clusters and recommends the best option based on either the 'elbow method,' or by "eigen gap" criteria. The results of the clustering operation are immediately visualized on the original map and can also be validated numerically according to a selection of cluster metrics. Cohesion and separation values are calculated simultaneously for all nodes. After presenting these, the paper also expands on the 'silhouette' value, which is a composite measure that seems especially suited to urban network clustering.This research is undertaken with the aim of informing the design process and so the visualization of results within the active 3d model is essential. Within the paper, we illustrate the process as applied to formal grids and also historic, vernacular urban fabric; first on small, extract urban fragments and then over an entire city networks to indicate the scalability.
keywords	Urban morphology; network analysis; spectral clustering; computation
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	caadria2020_436
id	caadria2020_436
authors	Teng, Teng and Sabin, Jenny
year	2020
title	PICA - A Designer Oriented Low-Cost Personal Robotic Fabrication Platform for Sketch Level Prototyping
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. 473-483
doi	https://doi.org/10.52842/conf.caadria.2020.2.473
summary	As digital design and fabrication are becoming increasingly prevalent, it is essential to consider how these technologies can be made more affordable and intuitively introduced to individual designers with limited computing skills. In this paper, we present an affordable personal robotic fabrication platform, PICA, consisting of a 3D printed robotic arm with a set of controller programs. The platform allows designers with limited computational design skills to assemble motors and 3D printed parts easily and to operate it in a code-free environment with direct manipulation through 3D modeling software. With the real-time communication between 3D modeling software and this robotic fabrication platform, PICA also allows designers to efficiently change the topological properties of geometry during the fabrication process. Based on a comparative observation of several application scenarios of using PICA among two groups of architecture students, the research can be summarized as follows: 1.) The project has proved to be an affordable approach to ease the materializing process when converting a designer's initial intent from digital space to a physical prototype. 2.) Designers could be facilitated by utilizing this robotic fabrication platform, especially during the period of conceptual design.
keywords	Robotic Fabrication; Design and Fabrication; Tool Development; Designer Oriented ; Ubiquitous Manufacturing
series	CAADRIA
email
last changed	2022/06/07 07:58

_id	cdrf2019_199
id	cdrf2019_199
authors	Ana Herruzo and Nikita Pashenkov
year	2020
title	Collection to Creation: Playfully Interpreting the Classics with Contemporary Tools
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_19
summary	This paper details an experimental project developed in an academic and pedagogical environment, aiming to bring together visual arts and computer science coursework in the creation of an interactive installation for a live event at The J. Paul Getty Museum. The result incorporates interactive visuals based on the user’s movements and facial expressions, accompanied by synthetic texts generated using machine learning algorithms trained on the museum’s art collection. Special focus is paid to how advances in computing such as Deep Learning and Natural Language Processing can contribute to deeper engagement with users and add new layers of interactivity.
series	cdrf
email
last changed	2022/09/29 07:51

_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	ecaade2020_515
id	ecaade2020_515
authors	Chadha, Kunaljit, Dubor, Alexandre, Puigpinos, Laura and Rafols, Irene
year	2020
title	Space Filling Curves for Optimising Single Point Incremental Sheet Forming using Supervised Learning Algorithms
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. 555-562
doi	https://doi.org/10.52842/conf.ecaade.2020.1.555
summary	Increasing use of computational design tools have led to an increase in the demand for mass customised fabrication, rendering decades old industrial CAD-CAM protocols limiting for such fabrication processes. This bespoke demand of components has led to a unified workflow between design strategies and production techniques. Recent advances in computation have allowed us to predict and register the tolerances of fabrication before and while being fabricated. Procedural algorithms are a set of novel problem-solving methods and have been attracting considerable attention for their good performance.They follow a procedural way of iteration with an established way of behavior.In the particular case of Incremental Sheet forming (ISF), these algorithms can realize several functions such as edge detection and segmentation required for optimizing machining time and accuracy.In this context, this paper presents a methodology to optimize long-drawn-out ISF operation by using geometrical intervention informed by supervised machine learning algorithms.
keywords	Procedural Algorithms; Incremental Sheet Forming; Robotic Cold forming; Mass Customization
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

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