Cumincad : CUMINCAD Papers : Search Results

CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

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_id	caadria2020_259
id	caadria2020_259
authors	Rhee, Jinmo, Veloso, Pedro and Krishnamurti, Ramesh
year	2020
title	Integrating building footprint prediction and building massing - an experiment in Pittsburgh
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. 669-678
doi	https://doi.org/10.52842/conf.caadria.2020.2.669
summary	We present a novel method for generating building geometry using deep learning techniques based on contextual geometry in urban context and explore its potential to support building massing. For contextual geometry, we opted to investigate the building footprint, a main interface between urban and architectural forms. For training, we collected GIS data of building footprints and geometries of parcels from Pittsburgh and created a large dataset of Diagrammatic Image Dataset (DID). We employed a modified version of a VGG neural network to model the relationship between (c) a diagrammatic image of a building parcel and context without the footprint, and (q) a quadrilateral representing the original footprint. The option for simple geometrical output enables direct integration with custom design workflows because it obviates image processing and increases training speed. After training the neural network with a curated dataset, we explore a generative workflow for building massing that integrates contextual and programmatic data. As trained model can suggest a contextual boundary for a new site, we used Massigner (Rhee and Chung 2019) to recommend massing alternatives based on the subtraction of voids inside the contextual boundary that satisfy design constraints and programmatic requirements. This new method suggests the potential that learning-based method can be an alternative of rule-based design methods to grasp the complex relationships between design elements.
keywords	Deep Learning; Prediction; Building Footprint; Massing; Generative Design
series	CAADRIA
email
last changed	2022/06/07 07:56

_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_228
id	acadia20_228
authors	Alawadhi, Mohammad; Yan, Wei
year	2020
title	BIM Hyperreality
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. 228-236.
doi	https://doi.org/10.52842/conf.acadia.2020.1.228
summary	Deep learning is expected to offer new opportunities and a new paradigm for the field of architecture. One such opportunity is teaching neural networks to visually understand architectural elements from the built environment. However, the availability of large training datasets is one of the biggest limitations of neural networks. Also, the vast majority of training data for visual recognition tasks is annotated by humans. In order to resolve this bottleneck, we present a concept of a hybrid system—using both building information modeling (BIM) and hyperrealistic (photorealistic) rendering—to synthesize datasets for training a neural network for building object recognition in photos. For generating our training dataset, BIMrAI, we used an existing BIM model and a corresponding photorealistically rendered model of the same building. We created methods for using renderings to train a deep learning model, trained a generative adversarial network (GAN) model using these methods, and tested the output model on real-world photos. For the specific case study presented in this paper, our results show that a neural network trained with synthetic data (i.e., photorealistic renderings and BIM-based semantic labels) can be used to identify building objects from photos without using photos in the training data. Future work can enhance the presented methods using available BIM models and renderings for more generalized mapping and description of photographed built environments.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	cdrf2019_93
id	cdrf2019_93
authors	Jiaxin Zhang , Tomohiro Fukuda , and Nobuyoshi Yabuki
year	2020
title	A Large-Scale Measurement and Quantitative Analysis Method of Façade Color in the Urban Street Using Deep Learning
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_9
summary	Color planning has become a significant issue in urban development, and an overall cognition of the urban color identities will help to design a better urban environment. However, the previous measurement and analysis methods for the facade color in the urban street are limited to manual collection, which is challenging to carry out on a city scale. Recent emerging dataset street view image and deep learning have revealed the possibility to overcome the previous limits, thus bringing forward a research paradigm shift. In the experimental part, we disassemble the goal into three steps: firstly, capturing the street view images with coordinate information through the API provided by the street view service; then extracting facade images and cleaning up invalid data by using the deep-learning segmentation method; finally, calculating the dominant color based on the data on the Munsell Color System. Results can show whether the color status satisfies the requirements of its urban plan for façade color in the street. This method can help to realize the refined measurement of façade color using open source data, and has good universality in practice.
series	cdrf
email
last changed	2022/09/29 07:51

_id	caadria2020_161
id	caadria2020_161
authors	Kido, Daiki, Fukuda, Tomohiro and Yabuki, Nobuyoshi
year	2020
title	Mobile Mixed Reality for Environmental Design Using Real-Time Semantic Segmentation and Video Communication - Dynamic Occlusion Handling and Green View Index Estimation
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. 681-690
doi	https://doi.org/10.52842/conf.caadria.2020.1.681
summary	Mixed reality (MR), that blends the real and virtual worlds, attracted attention for consensus-building among stakeholders in environmental design with the visualization of planned landscape onsite. One of the technical challenges in MR is the occlusion problem which occurs when virtual objects hide physical objects that should be rendered in front of virtual objects. This problem may cause inappropriate simulation. And the visual environmental assessment of present and proposed landscape with MR can be effective for the evidence-based design, such as urban greenery. Thus, this study aims to develop a MR-based environmental assessment system with dynamic occlusion handling and green view index estimation using semantic segmentation based on deep learning. This system was designed for the use on a mobile device with video communication over the Internet to implement a real-time semantic segmentation whose computational cost is high. The applicability of the developed system is shown through case studies.
keywords	Mixed Reality (MR); Environmental Design; Dynamic Occlusion Handling; Semantic Segmentation; Green View Index
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	caadria2020_028
id	caadria2020_028
authors	Xia, Yixi, Yabuki, Nobuyoshi and Fukuda, Tomohiro
year	2020
title	Development of an Urban Greenery Evaluation System Based on Deep Learning and Google Street View
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. 783-792
doi	https://doi.org/10.52842/conf.caadria.2020.1.783
summary	Street greenery has long played a vital role in the quality of urban landscapes and is closely related to people's physical and mental health. In the current research on the urban environment, researchers use various methods to simulate and measure urban greenery. With the development of computer technology, the way to obtain data is more diverse. For the assessment of urban greenery quality, there are many methods, such as using remote sensing satellite images captured from above (antenna, space) sensors, to assess urban green coverage. However, this method is not suitable for the evaluation of street greenery. Unlike most remote sensing images, from a pedestrian perspective, urban street images are the most common view of green plants. The street view image presented by Google Street View image is similar to the captured by the pedestrian perspective. Thus it is more suitable for studying urban street greening. With the development of artificial intelligence, based on deep learning, we can abandon the heavy manual statistical work and obtain more accurate semantic information from street images. Furthermore, we can also measure green landscapes in larger areas of the city, as well as extract more details from street view images for urban research.
keywords	Green View Index; Deep Learning; Google Street View; Segmentation
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	caadria2020_088
id	caadria2020_088
authors	Kado, Keita, Furusho, Genki, Nakamura, Yusuke and Hirasawa, Gakuhito
year	2020
title	rocess Path Derivation Method for Multi-Tool Processing Machines Using Deep-Learning-Based Three Dimensional Shape Recognition
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 609-618
doi	https://doi.org/10.52842/conf.caadria.2020.2.609
summary	When multi-axis processing machines are employed for high-mix, low-volume production, they are operated using a dedicated computer-aided design/ computer-aided manufacturing (CAD/CAM) process that derives an operating path concurrently with detailed modeling. This type of work requires dedicated software that occasionally results in complicated front-loading and data management issues. We proposed a three-dimensional (3D) shape recognition method based on deep learning that creates an operational path from 3D part geometry entered by a CAM application to derive a path for processing machinery such as a circular saw, drill, or end mill. The methodology was tested using 11 joint types and five processing patterns. The results show that the proposed method has several practical applications, as it addresses wooden object creation and may also have other applications.
keywords	Three-dimensional Shape Recognition; Deep Learning; Digital Fabrication; Multi-axis Processing Machine
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	acadia20_426
id	acadia20_426
authors	Zohier, Islam; EL Antably, Ahmed; S. Madani, Ahmed
year	2020
title	An AI Lens on Historic Cairo
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. 426-434.
doi	https://doi.org/10.52842/conf.acadia.2020.1.426
summary	Reports show that numerous heritage sites are in danger due to conflicts and heritage mismanagement in many parts of the world. Experts have resorted to digital tools to attempt to conserve and preserve endangered and damaged sites. To that end, in this applied research, we aim to develop a deep learning framework applied to the decaying tangible heritage of Historic Cairo, known as “The City of a Thousand Minarets.” The proposed framework targets Cairo’s historic minaret styles as a test case study for the broader applications of deep learning in digital heritage. It comprises recognition and segmentation tasks, which use a deep learning semantic segmentation model trained on two data sets representing the two most dominant minaret styles in the city, Mamluk (1250–1517 CE) and Ottoman (1517–1952 CE). The proposed framework aims to classify these two types using images. It can help create a multidimensional model from just a photograph of a historic building, which can quickly catalog and document a historic building or element. The study also sheds light on the obstacles preventing the exploration and implementation of deep learning techniques in digital heritage. The research presented in this paper is a work-in-progress of a larger applied research concerned with implementing deep learning techniques in the digital heritage domain.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	acadia20_120p
id	acadia20_120p
authors	Hirth, Kevin
year	2020
title	Short Stack
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. 120-123
summary	Short Stack is a bare minimal structure using only laminated sheets of structural metal decking for all elements of its structure and enclosure. The project operates under a simple principle. Structural metal decking is a one-way system that resists loads well in one direction, but not in the other. When this decking is stacked into rotated sections and tensioned together, the resultant sandwich of corrugated metal is resistant to loading in every direction. These sandwiches become walls, floors, and roofs to a temporary structure. The compounded effect at the edges of the rotated and cropped decking is one of filigree or an ornamental articulation. The sandwich, which is mostly hollow due to the section of the decking, provides a sense of airy lightness that is at odds with its bulky mass. The structure, therefore, teeters between being unexpectedly open and at once heavy. The economy of the project is in its uniformity and persistent singularity. By maintaining a single palette of material and using a plasma cutting CNC bed to cut each section of the decking, the structure is simply assembled. The digital intelligence that lies underneath the apparent formal simplicity of the project is two-fold. Firstly, each sheet of metal decking is different from the next. Because of the locations of bolt-holes and constant variability of rotation and cropping of each sheet, it is a project that expresses uniformity rather than articulation through discretization. Secondly, the project appears solid and monolithic but is hollowed structurally to minimize the weight of the assembly. Parametric tools are implemented to maximize material efficiencies by hollowing the interior of each sandwich for load optimization. The project is presently in prototyping and documentation and will go into construction in Spring 2021 on a site in downtown Denver.
series	ACADIA
type	project
email
last changed	2021/10/26 08:03

_id	ecaade2020_009
id	ecaade2020_009
authors	Reaver, Kai
year	2020
title	After Imagery - Evaluating the use of mixed reality (MR) in urban planning
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. 187-196
doi	https://doi.org/10.52842/conf.ecaade.2020.1.187
summary	While many researchers have developed interesting use cases for Mixed Reality (MR) in urban environments, the paper argues that determining the long-term viability of such applications as planning tools will likely require evaluating whether such applications are compatible with the democratically mandated procedures in Urban Planning. The paper compares this claim to current debates regarding the legality of the use of digital imagery in Urban Planning today. The paper elaborates these arguments through case studies done in Oslo, Norway in the context of developing the "Nordic Digital City". The case studies involve the use of MR in 1) a public competition, 2) a regulation plan, and 3) a building permit. The study thus presents some of the benefits and challenges of using these technologies in such a manner, particularly regarding accuracy, user feedback, and robustness as a common interface. The paper concludes that MR offers several benefits to Urban Planning, but will likely require a highly digitized competent public sector in order to function, in addition to requiring negotiation between the required user data and user privacy rights, suggesting that MR development may migrate from a primarily technical domain to a matter of public policy.
keywords	Mixed Reality; Urban Planning; Urbanism; Augmented Reality
series	eCAADe
email
last changed	2022/06/07 08:00

_id	ecaade2021_067
id	ecaade2021_067
authors	Weissenböck, Renate
year	2021
title	Augmented Quarantine - An experiment in online teaching using augmented reality for customized design interventions
source	Stojakovic, V and Tepavcevic, B (eds.), Towards a new, configurable architecture - Proceedings of the 39th eCAADe Conference - Volume 2, University of Novi Sad, Novi Sad, Serbia, 8-10 September 2021, pp. 95-104
doi	https://doi.org/10.52842/conf.ecaade.2021.2.095
summary	This paper presents experimental research about using Augmented Reality (AR) for interactive design processes, exploring a spatial "live" design method taking place in an overlay of real space and digital models. It discusses the processes and outcomes of a seminar undertaken at Graz University of Technology in winter term 2020/2021. Due to the Covid-19 pandemic, the course was taught online, and conceptualized to allow students the biggest possible learning experience during the lockdown. Ensuring accessibility to all participants, the seminar was based on the use of ubiquitous devices. The implementation of newly developed software, such as "Fologram", enabled the students to use AR systems at home with their personal computers and smartphones. The task of the course was to design customized interventions for the students' own domestic spaces, reacting to changing conditions and needs during the lockdown. The employed workflow was driven by an instant connection between 3D-modeling (Rhinoceros3D), parametric design (Grasshopper) and holographic immersion (Fologram).
keywords	augmented reality; remote collaboration; interactive design; customization; online teaching
series	eCAADe
email
last changed	2022/06/07 07:58

_id	ecaade2020_235
id	ecaade2020_235
authors	Li, Bin, Guo, Weihong, schnabel, Marc Aurel and Zhang, Ziqi
year	2020
title	Virtual Simulation of New Residential Buildings in Lingnan Using Vernacular Wisdom
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. 269-278
doi	https://doi.org/10.52842/conf.ecaade.2020.1.269
summary	Every new idea has some sort of precedent or echoes from the past. It is the same for the new residential buildings in Lingnan, China. In Lingnan, the vernacular knowledge of building design has been established over thousands of years. Whether it is suitable for use today should be verified. In this research, virtual simulations are employed to arrive at an overall conclusion. Virtual simulations based on PHOENICS, ENVI_MET, CadnaA, and Ecotect software were separately used for analysing the case of new residential buildings located in Lingnan. The study analysed the wind, thermal, acoustic, and light environments, which are four aspects of these new residential buildings. According to the results of our research, the paper discussed ways to amend and improve the new residential buildings that sit within the overall spirit of the vernacular knowledge of Lingnan; thus, it helps to put the traditional knowledge into the current context. The vernacular knowledge from XS to XL scale contexts, such as Feng-shui, was verified as being suitable for use in Lingnan today.
keywords	Virtual simulation; Vernacular wisdom; Residential building; Lingnan; Feng-shui
series	eCAADe
email
last changed	2022/06/07 07:52

_id	sigradi2020_441
id	sigradi2020_441
authors	Torreblanca-Díaz, David A.; Valencia Cardona, Raúl Adolfo; Perafán Lopez, Juan Carlos ; Sevilla Cadavid, Gustavo Adolfo
year	2020
title	A methodology for the evaluation, analysis, and selection of bioinspired textures, using Computational Fluid Dynamics (CFD) and wind tunnel for aerodynamic improvements in sports design
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. 441-448
summary	Sports disciplines have evolved in recent decades to improve the performance of athletes, as a result of interdisciplinary convergence. Computational Fluid Dynamics (CFD) and wind tunnel have gained relevance in sports design to predict the aerodynamic behavior. On the other hand, Bio-informed disciplines study nature to solve human problems, in order to generate innovation with or without sustainable results. This text presents a first proposal of a methodology oriented to the evaluation, analysis, and selection of bioinspired digital textures, in order to improve the aerodynamic performance in sports product design, through the integration of CFD and wind tunnel testing.
keywords	Aerodynamics, Bio-informed disciplines, Computational Fluid Dynamics (CFD), Sports Engineering, Computer Aided Engineering (CAE)
series	SIGraDi
email
last changed	2021/07/16 11:49

_id	caadria2020_156
id	caadria2020_156
authors	Yan, Hainan and Ji, Guohua
year	2020
title	An Investigation on the Deviation of Microclimate Simulation Based on ENVI-met - Taking Suzhou Industrial Park as 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. 527-536
doi	https://doi.org/10.52842/conf.caadria.2020.1.527
summary	In this study, the applicability of ENVI-met was tested in the Suzhou Industrial Park (SIP). Eight selected parks in the core area of SIP were selected as samples for site measurement and simulation. Measurements were compared with estimated values derived from the ENVI-met model by the analysis of Root Mean Square Error (RMSE). Results showed that RMSE can properly represent simulation deviations and there was a significant positive correlation between the area of parks and relative humidity. During the daytime, the ENVI-met model overestimated air temperature and underestimated relative humidity, with no consistent simulations deviation for wind speed; During the nighttime, the simulation deviation of the ENVI-met model for the three climate parameters mentioned above did not show a consistent pattern. Consequently, this study considers that the ENVI-met model is not suitable for simulation at night time. The findings of this study will help researchers and planners recognize the limitations of the model and the accuracy of the results.
keywords	ENVI-met; Microclimate; Deviation; Suzhou Industrial Park
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	acadia20_124p
id	acadia20_124p
authors	Zhang, Catty Dan
year	2020
title	Vents 2.0
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. 124-129
summary	VENTS 2.0 is a responsive environment that relates the moving air at separate locations using real-time data transmission. Functioning as an exhibition installation, a kinetic canopy produces a “rain” of air puffs subtly felt on the skin with a visual pattern of color LED, translating environmental conditions elsewhere into visual, audial, and tactile experiences within the Wurster Gallery at the University of California at Berkeley. The project articulates forms of airflow as part of a dynamic spatial device that stimulates senses beyond sight in a contemporary exhibition setting. It establishes an active system that triggers the emergence of initial states of air and modulates its evolvement. The installation collects real-time and recorded wind velocities via weather API (Application Programmer Interface). The computed data input controls multisensorial effects output by an array of air chambers using a customized script running on a Raspberry Pi. Each chamber generates air vortex rings one can feel when collapsing onto the skin, a typological form of airflow widely used in both art installations and the gaming industry due to its visual and tactile properties. These puffs of air, produced asynchronously, are distributed across the space by a total of twenty-four pairs of chambers assembled onto modified umbrellas on a lightweight aluminum frame. Undulating along the central axis of the 2,200 square feet gallery, the canopy locates right above average human height, illuminating softly a series of projects on display underneath, while at the same time providing visitors unexpected encounters with the constructed “breezes,” the echoing sound, and the fluctuating light.
series	ACADIA
type	project
email
last changed	2021/10/26 08:03

_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	ecaade2020_197
id	ecaade2020_197
authors	Haghighi, MohammadYousef and Mahdavinejad, Mohammadjavad
year	2020
title	HelioPhilia Intelligent Kinetic Canopy
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. 243-250
doi	https://doi.org/10.52842/conf.ecaade.2020.2.243
summary	In the contemporary changing world, digital architecture is to bring us new horizons and opportunities to take a determining step toward future. It results in speed and precision in process of design and construction. Moreover, the world is shifting to smartness. This paper is to develop a comprehensive mechanism to design an innovative canopy inspired from nature. Therefore, the canopy is going to inspire from young sunflowers. The canopy consists of a multi-functional waffle-frame. The main wing of the platform structure can have alternative utilization and the amount of light passing through it can be adjusted by using shade on the waffle spaces. Solar panels can also be used on the frames conductive to supply the energy independently. This HelioPhilia canopy always seeking the daylight, therefore, it cast a shadow behind itself to provide much more comfortable environment for whom choose there to be inside as a user. The results emphasize on the role of learning from nature in successful digital design process.
keywords	HelioPhilia Architecture; Intelligent Architecture; Kinetic Spaces; Digital Fabrication; High-Performance Architecture; Interactive Design
series	eCAADe
email
last changed	2022/06/07 07:51

_id	acadia21_76
id	acadia21_76
authors	Smith, Rebecca
year	2021
title	Passive Listening and Evidence Collection
source	ACADIA 2021: Realignments: Toward Critical Computation [Proceedings of the 41st Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-986-08056-7]. Online and Global. 3-6 November 2021. edited by B. Bogosian, K. Dörfler, B. Farahi, J. Garcia del Castillo y López, J. Grant, V. Noel, S. Parascho, and J. Scott. 76-81.
doi	https://doi.org/10.52842/conf.acadia.2021.076
summary	In this paper, I present the commercial, urban-scale gunshot detection system ShotSpotter in contrast with a range of ecological sensing examples which monitor animal vocalizations. Gunshot detection sensors are used to alert law enforcement that a gunshot has occurred and to collect evidence. They are intertwined with processes of criminalization, in which the individual, rather than the collective, is targeted for punishment. Ecological sensors are used as a “passive” practice of information gathering which seeks to understand the health of a given ecosystem through monitoring population demographics, and to document the collective harms of anthropogenic change (Stowell and Sueur 2020). In both examples, the ability of sensing infrastructures to “join up and speed up” (Gabrys 2019, 1) is increasing with the use of machine learning to identify patterns and objects: a new form of expertise through which the differential agendas of these systems are implemented and made visible. I trace the differential agendas of these systems as they manifest through varied components: the spatial distribution of hardware in the existing urban environment and / or landscape; the software and other informational processes that organize and translate the data; the visualization of acoustical sensing data; the commercial factors surrounding the production of material components; and the apps, platforms, and other forms of media through which information is made available to different stakeholders. I take an interpretive and qualitative approach to the analysis of these systems as cultural artifacts (Winner 1980), to demonstrate how the political and social stakes of the technology are embedded throughout them.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_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	ecaade2020_133
id	ecaade2020_133
authors	Andrade Zandavali, Barbara, Paul Anderson, Joshua and Patel, Chetan
year	2020
title	Embodied Learning through Fabrication Aware Design
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 145-154
doi	https://doi.org/10.52842/conf.ecaade.2020.2.145
summary	The contemporary culture of geometry-driven design stands as consequence of an institutionalised segregation between the fields of architecture, structure and construction. In turn, digital design methods that are both material and fabrication aware from the outset create space for uncertainty and the potential for embodied learning. Following this principle, this paper summarises the outcomes of a workshop developed to investigate the contribution of fabrication aware design methods in the production of a masonry block using both analogue and digital manufacturing. Students were to develop and investigate a design, through assembly techniques and configurations orientated around manual hot wire cutting, robotic tooling and three-dimensional printing. Outcomes were manufactured and compared regarding work precision, production time, material efficiency, cost and scalability. The analysis indicated that the most accurate results yielded from the robotic tooling system, and simultaneously exhibited the most efficient use of time, while the three-dimensional printer generated the least material waste, due to the nature of additive production. Fabrication aware design and comparative analysis enabled students to make more informed decisions while the use of rapid prototyping facilitated a relationship between digitalization and materiality allowing for a space in which uncertainty and reflection could be fostered. Reinforcing that fabrication aware design methods can unify the field and provide guidance to designers over multi-lateral aspects of a project.
keywords	Fabrication-Aware Design; Rapid Prototyping; Embodiment
series	eCAADe
email
last changed	2022/06/07 07:54

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