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	ecaade2023_44
id	ecaade2023_44
authors	Mayrhofer-Hufnagl, Ingrid and Ennemoser, Benjamin
year	2023
title	From Linear to Manifold Interpolation: Exemplifying the paradigm shift through interpolation
doi	https://doi.org/10.52842/conf.ecaade.2023.2.419
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 419–429
summary	The advent of artificial intelligence, specifically neural networks, has marked a significant turning point in the field of computation. During such transformative times, we are often faced with a dearth of appropriate vocabulary, which forces us to rely on existing terms, regardless of their inadequacy. This paper argues that the term “interpolation,” typically used in deep learning (DL), is a prime example of this phenomenon. It is not uncommon for beginners to misunderstand its meaning, as DL pioneer Francois Chollet (2017) has noted. This misreading is especially true in the discipline of architecture, and this study aims to demonstrate how the meaning of “interpolation” has evolved in the second digital turn. We begin by illustrating, using 2D data, the difference between linear interpolation in the context of topological figures and its use in DL algorithms. We then demonstrate how 3DGANs can be employed to interpolate across different topologies in complex 3D space, highlighting the distinction between linear and manifold interpolation. In both 2D and 3D examples, our results indicate that the process does not involve continuous morphing but instead resembles the piecing together of a jigsaw puzzle to form many parts of a larger ambient space. Our study reveals how previous architectural research on DL has employed the term “interpolation” without clarifying the crucial differences from its use in the first digital turn. We demonstrate the new possibilities that manifold interpolation offers for architecture, which extend well beyond parametric variations of the same topology.
keywords	Interpolation, 3D Generative Adversarial Networks, Deep Learning, Hybrid Space
series	eCAADe
email
last changed	2023/12/10 10:49

_id	ecaade2017_009
id	ecaade2017_009
authors	Takizawa, Atsushi and Furuta, Airi
year	2017
title	3D Spatial Analysis Method with First-Person Viewpoint by Deep Convolutional Neural Network with Omnidirectional RGB and Depth Images
doi	https://doi.org/10.52842/conf.ecaade.2017.2.693
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 693-702
summary	The fields of architecture and urban planning widely apply spatial analysis based on images. However, many features can influence the spatial conditions, not all of which can be explicitly defined. In this research, we propose a new deep learning framework for extracting spatial features without explicitly specifying them and use these features for spatial analysis and prediction. As a first step, we establish a deep convolution neural network (DCNN) learning problem with omnidirectional images that include depth images as well as ordinary RGB images. We then use these images as explanatory variables in a game engine to predict a subjects' preference regarding a virtual urban space. DCNNs learn the relationship between the evaluation result and the omnidirectional camera images and we confirm the prediction accuracy of the verification data.
keywords	Space evaluation; deep convolutional neural network; omnidirectional image; depth image; Unity; virtual reality
series	eCAADe
email
last changed	2022/06/07 07:56

_id	cf2017_084
id	cf2017_084
authors	Chen, Kian Wee; Janssen, Patrick; Norford, Leslie
year	2017
title	Automatic Generation of Semantic 3D City Models from Conceptual Massing Models
source	Gülen Çagdas, Mine Özkar, Leman F. Gül and Ethem Gürer (Eds.) Future Trajectories of Computation in Design [17th International Conference, CAAD Futures 2017, Proceedings / ISBN 978-975-561-482-3] Istanbul, Turkey, July 12-14, 2017, pp. 84-100.
summary	We present a workflow to automatically generate semantic 3D city models from conceptual massing models. In the workflow, the massing design is exported as a Collada file. The auto-conversion method, implemented as a Python library, identifies city objects by analysing the relationships between the geometries in the Collada file. For example, if the analysis shows that a closed poly surface satisfies certain geometrical relationships, it is automatically converted to a building. The advantage of this workflow is that no extra modelling effort is required, provided the designers are consistent in the geometrical relationships while modelling their massing design. We will demonstrate the feasibility of the workflow using three examples of increasing complexity. With the success of the demonstrations, we envision the utoconversion of massing models into semantic models will facilitate the sharing of city models between domain-specific experts and enhance communications in the urban design process.
keywords	Interoperability, GIS, City Information Modelling, Conceptual Urban Design, Collaborative Urban Design Process
series	CAAD Futures
email
last changed	2017/12/01 14:37

_id	acadia17_474
id	acadia17_474
authors	Peng, Wenzhe; Zhang, Fan; Nagakura, Takehiko
year	2017
title	Machines’ Perception of Space: Employing 3D Isovist Methods and a Convolutional Neural Network in Architectural Space Classification
doi	https://doi.org/10.52842/conf.acadia.2017.474
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 474- 481
summary	Simple and common architectural elements can be combined to create complex spaces. Different spatial compositions of elements define different spatial boundaries, and each produces a unique local spatial experience to observers inside the space. Therefore an architectural style brings about a distinct spatial experience. While multiple representation methods are practiced in the field of architecture, there lacks a compelling way to capture and identify spatial experiences. Describing an observer’s spatial experiences quantitatively and efficiently is a challenge. In this paper, we propose a method that employs 3D isovist methods and a convolutional neural network (CNN) to achieve recognition of local spatial compositions. The case studies conducted validate that this methodology works well in capturing and identifying local spatial conditions, illustrates the pattern and frequency of their appearance in designs, and indicates peculiar spatial experiences embedded in an architectural style. The case study used small designs by Mies van der Rohe and Aldo van Eyck. The contribution of this paper is threefold. First, it introduces a sampling method based on 3D Isovist that generates a 2D image that can be used to represent a 3D space from a specific observation point. Second, it employs a CNN model to extract features from the sampled images, then classifies their corresponding space. Third, it demonstrates a few case studies where this space classification method is applied to different architectural styles.
keywords	design methods; information processing; AI; machine learning; computer vision; representation
series	ACADIA
email
last changed	2022/06/07 08:00

_id	ecaade2017_202
id	ecaade2017_202
authors	Sollazzo, Aldo, Trento, Armando and Baseta, Efilena
year	2017
title	Machinic Agency - Implementing aerial robotics and machine learning to map public space
doi	https://doi.org/10.52842/conf.ecaade.2017.2.611
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 611-618
summary	The research presented in this paper is focused on proposing a new digital workflow, involving unmanned aerial vehicles (UAV) and machines learning systems, in order to detect and map citizen's behaviors in the context of public spaces.Novel machinic abilities can be implemented in the understanding of the human context, decoding, through computer visions and machine learning, complex systems into intelligible outputs (Olson, 2008), mapping the relationships of our reality. In this framework, robotic and computational strategies can be implemented in order to offer a new description of public spaces, bringing to light the hidden forces and multiple layers constituting the urban habitat. The presented study focuses on the development of a methodology turning video frames collected from cameras installed on drones into large datasets used to train convolutional networks and enable machines learning systems to detect and map pedestrians in public spaces.
keywords	mapping; drones; machine learning; computer vision; city
series	eCAADe
email
last changed	2022/06/07 07:56

_id	acadia17_552
id	acadia17_552
authors	Sjoberg, Christian; Beorkrem, Christopher; Ellinger, Jefferson
year	2017
title	Emergent Syntax: Machine Learning for the Curation of Design Solution Space
doi	https://doi.org/10.52842/conf.acadia.2017.552
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 552- 561
summary	The expanding role of computational models in the process of design is producing exponential growth in parameter spaces. As designers, we must create and implement new methods for searching these parameter spaces, considering not only quantitative optimization metrics but also qualitative features. This paper proposes a methodology that leverages the pattern modeling properties of artificial neural networks to capture designers' inexplicit selection criteria and create user-selection-based fitness functions for a genetic solver. Through emulation of learned selection patterns, fitness functions based on trained networks provide a method for qualitative evaluation of designs in the context of a given population. The application of genetic solvers for the generation of new populations based on the trained network selections creates emergent high-density clusters in the parameter space, allowing for the identification of solutions that satisfy the designer’s inexplicit criteria. The results of an initial user study show that even with small numbers of training objects, a search tool with this configuration can begin to emulate the design criteria of the user who trained it.
keywords	design methods; information processing; AI; machine learning; generative system
series	ACADIA
email
last changed	2022/06/07 07:56

_id	ecaade2017_041
id	ecaade2017_041
authors	Fukuda, Tomohiro, Kuwamuro, Yasuyuki and Yabuki, Nobuyoshi
year	2017
title	Optical Integrity of Diminished Reality Using Deep Learning
doi	https://doi.org/10.52842/conf.ecaade.2017.1.241
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 1, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 241-250
summary	A new method is proposed to improve diminished reality (DR) simulations to allow the demolition and removal of entire buildings in large-scale spaces. Our research goal was to obtain optical integrity by using a scientific and reliable simulation approach. Further, we tackled presumption of the texture of the background sky by applying deep learning. Our approach extracted the background sky using information from the actual sky obtained from a photographed image. This method comprised two steps: (1) detection of the sky area from the image through image segmentation and (2) creation of an image of the sky through image inpainting. The deep convolutional neural networks developed by us to train and predict images were evaluated to be feasible and effective.
keywords	Diminished Reality; Optical Integrity; Deep Learning; Augmented Reality; Landscape assessment
series	eCAADe
email
last changed	2022/06/07 07:50

_id	cf2017_648
id	cf2017_648
authors	Dounas, Theodoros; Spaeth, A. Benjamin; Wu, Hao; Zhang, Chenke
year	2017
title	Dense Urban Typologies and the Game of Life: Evolving Cellular Automata
source	Gülen Çagdas, Mine Özkar, Leman F. Gül and Ethem Gürer (Eds.) Future Trajectories of Computation in Design [17th International Conference, CAAD Futures 2017, Proceedings / ISBN 978-975-561-482-3] Istanbul, Turkey, July 12-14, 2017, pp. 648-666.
summary	The ongoing rate of urbanization in China is the motivator behind this paper. As a response to the observed monotonous housing developments in Suzhou Industrial Park (SIP) and elsewhere our method exploits Cellular Automata (CA) combined with fitness evaluation algorithms to explore speculatively the potential of existing developments and respective building regulations for increased density and diversity through an automated design algorithm. The well-known Game of Life CA is extended from its original 2-dimensional functionality into the realm of three dimensions and enriched with the opportunity of resizing the involved cells according to their function. Moreover our method integrates an earlier technique of constrcuctivists namely the “social condenser” as a means of diversifying functional distribution within the Cellular Automata as well as solar radiation as requested by the existing building regulation. The method achieves a densification of the development from 31% to 39% ratio of footprint to occupied volume whilst obeying the solar radiation rule and offering a more diverse functional occupation. This proof of concept demonstrates a solid approach to the automated design of housing developments at an urban scale with a ,yet limited, evaluation procedure including solar radiation which can be extended to other performance criteria in future work.
keywords	Evolutionary Design, Generative Urbanism, Integrated Strategy
series	CAAD Futures
email
last changed	2017/12/01 14:38

_id	ecaade2017_240
id	ecaade2017_240
authors	Al-Sudani, Amer, Hussein, Hussein and Sharples, Steve
year	2017
title	Sky View Factor Calculation - A computational-geometrical approach
doi	https://doi.org/10.52842/conf.ecaade.2017.2.673
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 673-682
summary	Sky view factor (SVF) is a well-known parameter in urban-climatic studies, but there is a lack of consensus on its effectiveness, especially with regard to the interpretation of changes in urban air temperatures. This led the authors to develop the new concept of the partial sky view factor (SVFp), which showed promise in a previous study. The objective of this study is to save the time associated with manual methods of calculating SVF and SVFp by developing a Rhino-Grasshopper component to quantify them via the hemispheric projection of a 3D model. In addition, a different approach, in terms of a hemispheric projection to calculate SVF, will be introduced by another component, and the pros and cons of each approach are considered. We will name these methods 'Ray Method' and 'Geometrical Method' respectively. The Ray Method has achieved a good balance between accuracy, processing time and urban scale and complexity compared to the Geometrical Method.
keywords	Sky view factor; parametric design; Rhino - Grasshopper; urban morphology; partial Sky view factor
series	eCAADe
email
last changed	2022/06/07 07:54

_id	acadia17_72
id	acadia17_72
authors	Alfaiate, Pedro; Caetano, In?s; Leit?o, António
year	2017
title	Luna Moth: Supporting Creativity in the Cloud
doi	https://doi.org/10.52842/conf.acadia.2017.072
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 72-81
summary	Algorithmic design allows architects to design using a programming-based approach. Current algorithmic design environments are based on existing computer-aided design applications or building information modeling applications, such as AutoCAD, Rhinoceros 3D, or Revit, which, due to their complexity, fail to give architects the immediate feedback they need to explore algorithmic design. In addition, they do not address the current trend of moving applications to the cloud to improve their availability. To address these problems, we propose a software architecture for an algorithmic design integrated development environment (IDE), based on web technologies, that is more interactive than competing algorithmic design IDEs. Besides providing an intuitive editing interface which facilitates programming tasks for architects, its performance can be an order of magnitude faster than current algorithmic design IDEs, thus supporting real-time feedback with more complex algorithmic design programs. Moreover, our solution also allows architects to export the generated model to their preferred computer-aided design applications. This results in an algorithmic design environment that is accessible from any computer, while offering an interactive editing environment that integrates into the architect’s workflow.
keywords	design methods; information processing; generative system; computational / artistic cultures
series	ACADIA
email
last changed	2022/06/07 07:54

_id	ecaade2017_208
id	ecaade2017_208
authors	Beaudry Marchand, Emmanuel, Han, Xueying and Dorta, Tomás
year	2017
title	Immersive retrospection by video-photogrammetry - UX assessment tool of interactions in museums, a case study
doi	https://doi.org/10.52842/conf.ecaade.2017.2.729
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 729-738
summary	Studying interactions in museums often omits to consider the complexity of the space and the visitors' behaviors. Visitors' walking paths do not provide enough insight of their user experience (UX) since they are distant from the experiential realities. Videogrammetry can convey such dimensions of an environmental experience. Because of limitations of real-time playback, a twofold approach is suggested: "immersive videos" combined with "photogrammetric models". A granular optimal experience assessment method using retrospection interviews is also applied providing a finer evaluation of the perceived experience through time. This method permits to characterize museum interactive installations, according to the perceived challenges and skills of the interaction's task, based this time on immersive retrospection. This paper proposes the "Immersive retrospection" by "Immersive video-photogrammetry" as a UX assessment tool of interactions in museums. A hybrid virtual environment was used in this study, allowing social VR without the use of headsets, through a life-sized projection of interactive 3D content. The study showed that Immersive video-photogrammetry facilitates the recall of memories and allows a deepened self-observation analysis.
keywords	immersive retrospection; photogrammetry; videogrammetry; UX assessment; museum environments
series	eCAADe
email
last changed	2022/06/07 07:54

_id	cf2017_585
id	cf2017_585
authors	Ben, Yuqiang; Niblock, Chantelle; Bonenberg, Lukasz
year	2017
title	Lincoln Cathedral Interactive Virtual Reality Exhibition
source	Gülen Çagdas, Mine Özkar, Leman F. Gül and Ethem Gürer (Eds.) Future Trajectories of Computation in Design [17th International Conference, CAAD Futures 2017, Proceedings / ISBN 978-975-561-482-3] Istanbul, Turkey, July 12-14, 2017, pp. 585-595.
summary	This paper demonstrates a workflow converting terrestrial laser scan (TLS) data into an interactive virtual reality (VR) platform. A VR exhibition prototype of Lincoln Cathedral was created to validate the established workflow in terms of the technical and visual performance, usability, and functionality. It combined TLS data and storytelling to produce a shareable platform, inviting opportunities for public engagement, and to facilitate custodians with the tools to maintain the building’s heritage. The paper discusses the use of open sourcesoftware and suggests future work.
keywords	3D Laser Scan, Virtual Reality, User Experience, Building Heritage
series	CAAD Futures
email
last changed	2017/12/01 14:38

_id	caadria2017_055
id	caadria2017_055
authors	Caetano, In?s and Leit?o, António
year	2017
title	Integration of an Algorithmic BIM Approach in a Traditional Architecture Studio
doi	https://doi.org/10.52842/conf.caadria.2017.633
source	P. Janssen, P. Loh, A. Raonic, M. A. Schnabel (eds.), Protocols, Flows, and Glitches - Proceedings of the 22nd CAADRIA Conference, Xi'an Jiaotong-Liverpool University, Suzhou, China, 5-8 April 2017, pp. 633-642
summary	Algorithmic BIM combines BIM and Generative Design (GD), merging the potentialities of both approaches. In this paper we describe the design process of a set of parametric facades developed using Algorithmic-BIM, and how this approach was integrated into the design workflow of two architectural studios. We demonstrate how the integration of GD together with BIM influenced the whole design process and also the selection of the final solution. Some of the limitations found during the entire process are also addressed in the paper, such as tight deadlines and financial constraints. Finally, we explain the pros and cons of using this design method compared to a traditional BIM approach, and we discuss the implementation of this paradigm in a traditional design practice. This work was developed using Rosetta, an IDE for Generative Design that supports scripts using different programming languages and allows the generation and edition of 3D models in a variety of CAD and BIM applications. The result of this work is an information model of three parametric facades for a residential building, from which we can extract material quantities and construction performance tests.
keywords	Generative design; collaborative design; CAD-BIM portability; parametric facade design
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	ecaade2017_031
id	ecaade2017_031
authors	Castelo Branco, Renata and Leit?o, António
year	2017
title	Integrated Algorithmic Design - A single-script approach for multiple design tasks
doi	https://doi.org/10.52842/conf.ecaade.2017.1.729
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 1, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 729-738
summary	Many great architectural endeavors today engage in a multi software approach, as each specialty involved needs a different software, and different task required from the architect, such as 3D modeling, analysis or rendering, also benefit from the use of different tools. Combining them in the same process is not always a successful endeavor. A more effective portability mechanism is needed, and Algorithmic Design (AD) has the potential to become one. This paper explores the advantages of the algorithmic approach to the design process, and proposes a methodology capable of integrating the different tools and paradigms currently used in architecture. The methodology is based on the development of a computer program that describes not only the intended model, but also additional tasks, such as the required analysis and rendering. It takes advantage of CAD, BIM and analysis tools, with little effort when it comes to the transition between them.
keywords	Algorithmic Design; CAD; BIM; Analysis tools
series	eCAADe
email
last changed	2022/06/07 07:55

_id	ecaade2017_244
id	ecaade2017_244
authors	Chaltiel, Stephanie, Bravo, Maite and Chronis, Angelos
year	2017
title	Digital fabrication with Virtual and Augmented Reality for Monolithic Shells
doi	https://doi.org/10.52842/conf.ecaade.2017.2.211
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 211-218
summary	The digital fabrication of monolithic shell structures is presenting some challenges related to the interface between computational design and fabrication techniques, such as the methods chosen for the suitable parametrization of the geometry based on materiality characteristics and construction constrains, the digital optimization criteria of variables, and the translation of the relevant code used for digital fabrication. Specifically, the translation from the digital to the physical when a definite materiality appears during the digital fabrication process proves to be a crucial step, which is typically approached as a linear and predetermined sequence. This often-difficult step offers the potential of embedding a certain level of interactivity between the fabricator and the materialized model during the fabrication process in order to allow for real time adjustments or corrections. This paper features monolithic shell construction processes that promote a simple interface of live interaction between the fabricator and the tool control during the digital fabrication process. The implementation of novel digital and physical methods will be explored, offering the possibility of being combined with automated fabrication actions controlled by real time inputs with virtual reality [VR] influenced by 3d scanning and 3d CAD programs, and the possibility of incorporating augmented reality [AR].
keywords	virtual reality; augmented reality; monolithic shells
series	eCAADe
email
last changed	2022/06/07 07:55

_id	acadia23_v1_166
id	acadia23_v1_166
authors	Chamorro Martin, Eduardo; Burry, Mark; Marengo, Mathilde
year	2023
title	High-performance Spatial Composite 3D Printing
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 1: Projects Catalog of the 43rd Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-8-1]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 166-171.
summary	This project explores the advantages of employing continuum material topology optimization in a 3D non-standard lattice structure through fiber additive manufacturing processes (Figure 1). Additive manufacturing (AM) has gained rapid adoption in architecture, engineering, and construction (AEC). However, existing optimization techniques often overlook the mechanical anisotropy of AM processes, resulting in suboptimal structural properties, with a focus on layer-by-layer or planar processes. Materials, processes, and techniques considering anisotropy behavior (Kwon et al. 2018) could enhance structural performance (Xie 2022). Research on 3D printing materials with high anisotropy is limited (Eichenhofer et al. 2017), but it holds potential benefits (Liu et al. 2018). Spatial lattices, such as space frames, maximize structural efficiency by enhancing flexural rigidity and load-bearing capacity using minimal material (Woods et al. 2016). From a structural design perspective, specific non-standard lattice geometries offer great potential for reducing material usage, leading to lightweight load-bearing structures (Shelton 2017). The flexibility and freedom of shape inherent to AM offers the possibility to create aggregated continuous truss-like elements with custom topologies.
series	ACADIA
type	project
email
last changed	2024/04/17 13:58

_id	cf2017_051
id	cf2017_051
authors	Chen, Kian Wee; Janssen, Patrick; Norford, Leslie
year	2017
title	Automatic Parameterisation of Semantic 3D City Models for Urban Design Optimisation
source	Gülen Çagdas, Mine Özkar, Leman F. Gül and Ethem Gürer (Eds.) Future Trajectories of Computation in Design [17th International Conference, CAAD Futures 2017, Proceedings / ISBN 978-975-561-482-3] Istanbul, Turkey, July 12-14, 2017, pp. 51-65.
summary	We present an auto-parameterisation tool, implemented in Python, that takes in a semantic model, in CityGML format, and outputs a parametric model. The parametric model is then used for design optimisation of solar availability and urban ventilation potential. We demonstrate the tool by parameterising a CityGML model regarding building height, orientation and position and then integrate the parametric model into an optimisation process. For example, the tool parameterises the orientation of a design by assigning each building an orientation parameter. The parameter takes in a normalised value from an optimisation algorithm, maps the normalised value to a rotation value and rotates the buildings. The solar and ventilation performances of the rotated design is then evaluated. Based on the evaluation results, the optimisation algorithm then searches through the parameter values to achieve the optimal performances. The demonstrations show that the tool eliminates the need to set up a parametric model manually, thus making optimisation more accessible to designers.
keywords	City Information Modelling, Conceptual Urban Design, Parametric Modelling, Performance-Based Urban Design
series	CAAD Futures
email
last changed	2017/12/01 14:37

_id	caadria2019_657
id	caadria2019_657
authors	Chen, Zhewen, Zhang, Liming and Yuan, Philip F.
year	2019
title	Innovative Design Approach to Optimized Performance on Large-Scale Robotic 3D-Printed Spatial Structure
doi	https://doi.org/10.52842/conf.caadria.2019.2.451
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 2, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 451-460
summary	This paper presents an innovative approach on designing large-scale spatial structure with automated robotic 3D-printing. The incipient design approach mainly focused on optimizing structural efficiency at an early design stage by transform the object into a discrete system, and the elements in this system contains unique structural parameters that corresponding to its topology results of stiffness distribution. Back in 2017, the design team already implemented this concept into an experimental project of Cloud Pavilion in Shanghai, China, and the 3D-printed spatial structure was partitioned into five zones represent different level of structure stiffness and filled with five kinds of unit toolpath accordingly. Through further research, an upgrade version, the project of Cloud Pavilion 2.0 is underway and will be completed in January 2019. A detailed description on innovative printing toolpath design in this project is conducted in this paper and explains how the toolpath shape effects its overall structural stiffness. This paper contributes knowledge on integrated design in the field of robotic 3D-printing and provides an alternative approach on robotic toolpath design combines with the optimized topological results.
keywords	3D-Printing; Robotic Fabrication; Structural Optimization; Discrete System; Toolpath Design
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	ecaade2017_002
id	ecaade2017_002
authors	Costa, Fábio, Eloy, Sara, Sales Dias, Miguel and Lopes, Mariana
year	2017
title	ARch4models - A tool to augment physical scale models
doi	https://doi.org/10.52842/conf.ecaade.2017.1.711
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 1, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 711-718
summary	This paper focus on the development and evaluation of a computer tool that enriches physical scale models of buildings, which are commonly used during architecture and civil engineering design processes. The main goal of this work is to enable designers, namely architects, to use the affordances of the physical scale models, by enhancing them with digital characteristics that can be easily changed, allowing an enriched interaction of the designer with such models. Our in-house developed Augmented Reality tool, referred to as ARch4models, augments the user experience with visual features and interactive capabilities, not possible to accomplish with physical models (see this video in https://goo.gl/5zbdTQ). The tool allows the coherent registration between the real and the digital in the same space. Satisfaction evaluation studies were conducted that have shown that ARch4models improves the building design process when compared with a traditional methodology employing solely physical scale models.
keywords	augmented reality; architecture; physical scale model; 3D model; AEC design process
series	eCAADe
email
last changed	2022/06/07 07:56

_id	caadria2017_031
id	caadria2017_031
authors	Crolla, Kristof, Williams, Nicholas, Muehlbauer, Manuel and Burry, Jane
year	2017
title	SmartNodes Pavilion - Towards Custom-optimized Nodes Applications in Construction
doi	https://doi.org/10.52842/conf.caadria.2017.467
source	P. Janssen, P. Loh, A. Raonic, M. A. Schnabel (eds.), Protocols, Flows, and Glitches - Proceedings of the 22nd CAADRIA Conference, Xi'an Jiaotong-Liverpool University, Suzhou, China, 5-8 April 2017, pp. 467-476
summary	Recent developments in Additive Manufacturing are creating possibilities to make not only rapid prototypes, but directly manufactured customised components. This paper investigates the potential for combining standard building materials with customised nodes that are individually optimised in response to local load conditions in non-standard, irregular, or doubly curved frame structures. This research iteration uses as a vehicle for investigation the SmartNodes Pavilion, a temporary structure with 3D printed nodes built for the 2015 Bi-City Biennale of Urbanism/Architecture in Hong Kong. The pavilion is the most recent staged output of the SmartNodes Project. It builds on the findings in earlier iterations by introducing topologically constrained node forms that marry the principals of the evolved optimised node shape with topological constraints imposed to meet the printing challenges. The 4m high canopy scale prototype structure in this early design research iteration represents the node forms using plastic Fused Deposition Modelling (FDM).
keywords	Digital Fabrication; Additive Manufacturing; File to Factory; Design Optimisation; 3D printing for construction
series	CAADRIA
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last changed	2022/06/07 07:56

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