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

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_id acadia20_238
id acadia20_238
authors Zhang, Hang
year 2020
title Text-to-Form
doi https://doi.org/10.52842/conf.acadia.2020.1.238
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. 238-247.
summary Traditionally, architects express their thoughts on the design of 3D architectural forms via perspective renderings and standardized 2D drawings. However, as architectural design is always multidimensional and intricate, it is difficult to make others understand the design intention, concrete form, and even spatial layout through simple language descriptions. Benefiting from the fast development of machine learning, especially natural language processing and convolutional neural networks, this paper proposes a Linguistics-based Architectural Form Generative Model (LAFGM) that could be trained to make 3D architectural form predictions based simply on language input. Several related works exist that focus on learning text-to-image generation, while others have taken a further step by generating simple shapes from the descriptions. However, the text parsing and output of these works still remain either at the 2D stage or confined to a single geometry. On the basis of these works, this paper used both Stanford Scene Graph Parser (Sebastian et al. 2015) and graph convolutional networks (Kipf and Welling 2016) to compile the analytic semantic structure for the input texts, then generated the 3D architectural form expressed by the language descriptions, which is also aided by several optimization algorithms. To a certain extent, the training results approached the 3D form intended in the textual description, not only indicating the tremendous potential of LAFGM from linguistic input to 3D architectural form, but also innovating design expression and communication regarding 3D spatial information.
series ACADIA
type paper
email
last changed 2023/10/22 12:06

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

_id acadia20_382
id acadia20_382
authors Hosmer, Tyson; Tigas, Panagiotis; Reeves, David; He, Ziming
year 2020
title Spatial Assembly with Self-Play Reinforcement Learning
doi https://doi.org/10.52842/conf.acadia.2020.1.382
source ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 382-393.
summary We present a framework to generate intelligent spatial assemblies from sets of digitally encoded spatial parts designed by the architect with embedded principles of prefabrication, assembly awareness, and reconfigurability. The methodology includes a bespoke constraint-solving algorithm for autonomously assembling 3D geometries into larger spatial compositions for the built environment. A series of graph-based analysis methods are applied to each assembly to extract performance metrics related to architectural space-making goals, including structural stability, material density, spatial segmentation, connectivity, and spatial distribution. Together with the constraint-based assembly algorithm and analysis methods, we have integrated a novel application of deep reinforcement (RL) learning for training the models to improve at matching the multiperformance goals established by the user through self-play. RL is applied to improve the selection and sequencing of parts while considering local and global objectives. The user’s design intent is embedded through the design of partial units of 3D space with embedded fabrication principles and their relational constraints over how they connect to each other and the quantifiable goals to drive the distribution of effective features. The methodology has been developed over three years through three case study projects called ArchiGo (2017–2018), NoMAS (2018–2019), and IRSILA (2019-2020). Each demonstrates the potential for buildings with reconfigurable and adaptive life cycles.
series ACADIA
type paper
email
last changed 2023/10/22 12:06

_id ecaade2020_184
id ecaade2020_184
authors Kycia, Agata and Guiducci, Lorenzo
year 2020
title Self-shaping Textiles - A material platform for digitally designed, material-informed surface elements
doi https://doi.org/10.52842/conf.ecaade.2020.2.021
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. 21-30
summary Despite the cutting edge developments in science and technology, architecture to a large extent still tends to favor form over matter by forcing materials into predefined, often superficial geometries, with functional aspects relegated to materials or energy demanding mechanized systems. Biomaterials research has instead shown a variety of physical architectures in which form and matter are intimately related (Fratzl, Weinkamer, 2007). We take inspiration from the morphogenetic processes taking place in plants' leaves (Sharon et al., 2007), where intricate three-dimensional surfaces originate from in-plane growth distributions, and propose the use of 3D printing on pre-stretched textiles (Tibbits, 2017) as an alternative, material-based, form-finding technique. We 3D print open fiber bundles, analyze the resulting wrinkling phenomenon and use it as a design strategy for creating three-dimensional textile surfaces. As additive manufacturing becomes more and more affordable, materials more intelligent and robust, the proposed form-finding technique has a lot of potential for designing efficient textile structures with optimized structural performance and minimal usage of material.
keywords self-shaping textiles; material form-finding; wrinkling; surface instabilities; bio-inspired design; leaf morphogenesis
series eCAADe
email
last changed 2022/06/07 07:52

_id acadia20_192p
id acadia20_192p
authors Doyle, Shelby; Hunt, Erin
year 2020
title Melting 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. 192-197
summary This project presents computational design and fabrication methods for locating standard steel reinforcement within 3D printed water-soluble PVA (polyvinyl alcohol) molds to create non-standard concrete columns. Previous methods from “Melting: Augmenting Concrete Columns with Water Soluble 3D Printed Formwork” and “Dissolvable 3D Printed Formwork: Exploring Additive Manufacturing for Reinforced Concrete” (Doyle & Hunt 2019) were adapted for larger-scale construction, including the introduction of new hardware, development of custom programming strategies, and updated digital fabrication techniques. Initial research plans included 3D printing continuous PVA formwork with a KUKA Agilus Kr10 R1100 industrial robotic arm. However, COVID-19 university campus closures led to fabrication shifting to the author’s home, and this phase instead relied upon a LulzBot TAZ 6 (build volume of 280 mm x 280 mm x 250 mm) with an HS+ (Hardened Steel) tool head (1.2 mm nozzle diameter). Two methods were developed for this project phase: new 3D printing hardware and custom GCode production. The methods were then evaluated in the fabrication of three non-standard columns designed around five standard reinforcement bars (3/8-inch diameter): Woven, Twisted, Aperture. Each test column was eight inches in diameter (the same size as a standard Sonotube concrete form) and 4 feet tall, approximately half the height of an architecturally scaled 8-foot-tall column. Each column’s form was generated from combining these diameter and height restrictions with the constraints of standard reinforcement placement and minimum concrete coverage. The formwork was then printed, assembled, cast, and then submerged in water to dissolve the molds to reveal the cast concrete. This mold dissolving process limits the applicable scale for the work as it transitions from the research lab to the construction site. Therefore, the final column was placed outside with its mold intact to explore if humidity and water alone can dissolve the PVA formwork in lieu of submersion.
series ACADIA
type project
email
last changed 2021/10/26 08:08

_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 sigradi2020_962
id sigradi2020_962
authors Evrim, Berfin; Davis, Grant; Tubay, Josh; Gursoy, Benay
year 2020
title Recipes for Waste-Tooling: Using Food Waste in 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. 962-967
summary In this research, we propose an alternate consumption cycle in which the traditional landfill waste disposal model is averted by developing design objects that are fabricated with household biowaste materials. Food decomposition in landfills not only wastes the energy and emissions input into the original production process, but also releases methane. By rerouting this waste for secondary use as novel design objects and tools, in this research we seek to prevent some amounts of household biowaste from reaching landfills. This process, that we call waste-tooling, repurposes food waste to make kitchen tools by employing different fabrication strategies.
keywords Circular economy, Biowaste, 3D printing
series SIGraDi
email
last changed 2021/07/16 11:53

_id ecaade2020_222
id ecaade2020_222
authors Ikeno, Kazunosuke, Fukuda, Tomohiro and Yabuki, Nobuyoshi
year 2020
title Automatic Generation of Horizontal Building Mask Images by Using a 3D Model with Aerial Photographs for Deep Learning
doi https://doi.org/10.52842/conf.ecaade.2020.2.271
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. 271-278
summary Information extracted from aerial photographs is widely used in urban planning and design. An effective method for detecting buildings in aerial photographs is to use deep learning for understanding the current state of a target region. However, the building mask images used to train the deep learning model are manually generated in many cases. To solve this challenge, a method has been proposed for automatically generating mask images by using virtual reality 3D models for deep learning. Because normal virtual models do not have the realism of a photograph, it is difficult to obtain highly accurate detection results in the real world even if the images are used for deep learning training. Therefore, the objective of this research is to propose a method for automatically generating building mask images by using 3D models with textured aerial photographs for deep learning. The model trained on datasets generated by the proposed method could detect buildings in aerial photographs with an accuracy of IoU = 0.622. Work left for the future includes changing the size and type of mask images, training the model, and evaluating the accuracy of the trained model.
keywords Urban planning and design; Deep learning; Semantic segmentation; Mask image; Training data; Automatic design
series eCAADe
email
last changed 2022/06/07 07:50

_id acadia20_446
id acadia20_446
authors Norell, Daniel; Rodhe, Einar; Hedlund, Karin
year 2020
title Completions
doi https://doi.org/10.52842/conf.acadia.2020.1.446
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. 446-455.
summary Reuse of construction and demolition waste tends to be exceptional rather than systemic, despite the fact that such waste exists in excess. One of the challenges in handling used elements and materials is integrating them into a digital workflow through means of survey and representation. Techniques such as 3D scanning and robotic fabrication have been used to target irregular geometries of such extant material. Scanning can be applied to digitally define a unique rather than standard stock of materials or, as in the field of preservation, to transfer specific forms and qualities onto a new stock. This paper melds these two approaches through Completions, a project that promotes reuse by integrating salvaged elements and materials into new assemblies. Drawing from the ancient practice of reuse known as spolia, the work develops from the identification and documentation of a varied set of used entities that become points of departure for subsequent design and production of new entities. This involves multiple steps, from locating and selecting used elements to scanning and fabrication. Three assemblies based on salvaged objects are produced: a window frame, a door panel, and a mantelpiece. Different means of documentation are outlined in relation to specific qualities of these objects, from photogrammetry to image and mesh-based tracing. Authentic qualities belonging to these elements, such as wear and patina, are coupled with more ambiguous forms and materialities only attainable through digital survey and fabrication. Finally, Completions speculates on how more automated workflows might make it feasible to develop extensive virtual catalogs of used objects that designers could interact with remotely.
series ACADIA
type paper
email
last changed 2023/10/22 12:06

_id ecaade2021_011
id ecaade2021_011
authors Nováková, Kateøina and Vele, Jiøí
year 2021
title Prvok - An experiment with 3D printing large doublecurved concrete structure
doi https://doi.org/10.52842/conf.ecaade.2021.2.137
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. 137-144
summary In this experimental research project we report on the manufacturing process of the first full-size 3D printed concrete structure in our country. The house was 3D printed by an ABB IRB 6700 robot whose range we made fit with the requirements for transportation size and also, its range determined the size and geometry of the house. During the transformation process from sketch to code we involved students to apply computational design methods. We designed the main load bearing structure which had to be thinnest and lightest possible together with its insulation features and printability. We were aware of the world-wide research in this field started by NASA centennial Challenge called 3D-printed-habitat [Roman,2020] as well as start-ups derived from this research [1,2,3,4]. During the project, we investigated the following matters: (1) the relationship between geometry of the wall in model and in practice (2), setting of the robot and the mixture; and (3) stress test of the wall. With the results of the test we aimed at contribution to standardisation of 3D printed structures in ISO/ASTM 52939:2021. The finalized structure, named "Prvok", was made to prove printability of the mixture and stability of the design.
keywords 3D printing; robot; concrete; grasshopper; experiment; house
series eCAADe
email
last changed 2022/06/07 07:58

_id caadria2020_398
id caadria2020_398
authors Tseng, Li-Min and Hou, June-Hao
year 2020
title Representation of Sound in 3D
doi https://doi.org/10.52842/conf.caadria.2020.1.609
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. 609-618
summary This study is based on Chladni figures and tries to spatially extend its representation of sound. The current Chladni figures only see parts of the sound. There should be more spatial representation of sounds because they are transmitted in space. This study explores how to capture and reconstruct invisible sound information to create three-dimensional forms. A series of steps are taken to record Chladni figures of different frequencies and decibels. Pure Data is used to generate sounds. The Chladni figures are captured in Grasshopper and converted into point clouds. These point clouds are processed by using different algorithms to produce layers of superimposed state from which 3D forms of sound can be generated and fabricated. Through the proposed methods of processing and representation, sound not only stays at the level of hearing, but can also be seen, touched, and reinterpreted spatially. With the spatial forms of sound, viewers no longer perceive sound through single but multiple states. This can help us comprehend sound in a vast variety of ways.
keywords Sound visualization; Form-finding; Spatial-temporal; Chladni figures; Cymatics
series CAADRIA
email
last changed 2022/06/07 07:57

_id artificial_intellicence2019_15
id artificial_intellicence2019_15
authors Antoine Picon
year 2020
title What About Humans? Artificial Intelligence in Architecture
doi https://doi.org/https://doi.org/10.1007/978-981-15-6568-7_2
source Architectural Intelligence Selected Papers from the 1st International Conference on Computational Design and Robotic Fabrication (CDRF 2019)
summary Artificial intelligence is about to reshape the architectural discipline. After discussing the relations between artificial intelligence and the broader question of automation in architecture, this article focuses on the future of the interaction between humans and intelligent machines. The way machines will understand architecture may be very different from the reading of humans. Since the Renaissance, the architectural discipline has defined itself as a conversation between different stakeholders, the designer, but also the clients and the artisans in charge of the realization of projects. How can this conversation be adapted to the rise of intelligent machines? Such a question is not only a matter of design effectiveness. It is inseparable from expressive and artistic issues. Just like the fascination of modernist architecture for industrialization was intimately linked to the quest for a new poetics of the discipline, our contemporary interest for artificial intelligence has to do with questions regarding the creative core of the architectural discipline.
series Architectural Intelligence
email
last changed 2022/09/29 07:28

_id caadria2020_023
id caadria2020_023
authors Liu, Chenjun
year 2020
title Double Loops Parametric Design of Surface Steel Structure Based on Performance and Fabrication
doi https://doi.org/10.52842/conf.caadria.2020.1.023
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. 23-33
summary In intelligent epoch, automatic parameter design systems reduce the requirements of the skills needed to create objects. The creator only needs to select the most perceptual primitive form to automatically generate the data system that iterates to the most efficient solution. In this paper, a method of combining performance driven optimization with parametric design is proposed. The iterative evolution is under the control of performance loop and fabrication loop, which makes all the data provided by parametric design in a practical project available for exploring structural analysis and digital prefabrication. Related to the case of surface steel structure, parametric optimization is not limited to a set of shape types or design problems, it would be based on the generality and built-in characteristics of parametric modelling environment in the most convenient and flexible way. (Rolvink et al. 2010)And the given parameters would be fed back on geometric structure, performance indicators, and design variables, so that designers can easily and effectively coordinate and try different solutions. The system transforms the generated data into machine language so that the process including design, analysis, manufacturing, and construction can maintain the orthogonal persistence of the data.
keywords parametric design; component prefabrication; curved steel structure; performance driven
series CAADRIA
email
last changed 2022/06/07 07:59

_id caadria2020_091
id caadria2020_091
authors Ren, Yue and Zheng, Hao
year 2020
title The Spire of AI - Voxel-based 3D Neural Style Transfer
doi https://doi.org/10.52842/conf.caadria.2020.2.619
source D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 619-628
summary In the architecture field, humans have mastered various skills for creating unique spatial experiences with unknown interplays between known contents and styles. Meanwhile, machine learning, as a popular tool for mapping different input factors and generating unpredictable outputs, links the similarity of the machine intelligence with the typical form-finding process. Style Transfer, therefore, is widely used in 2D visuals for mixing styles while inspiring the architecture field with new form-finding possibilities. Researchers have applied the algorithm in generating 2D renderings of buildings, limiting the results in 2D pixels rather than real full volume forms. Therefore, this paper aims to develop a voxel-based form generation methodology to extend the 3D architectural application of Style Transfer. Briefly, through cutting the original 3D model into multiple plans and apply them to the 2D style image, the stylized 2D results generated by Style Transfer are then abstracted and filtered as groups of pixel points in space. By adjusting the feature parameters with user customization and replacing pixel points with basic voxelization units, designers can easily recreate the original 3D geometries into different design styles, which proposes an intelligent way of finding new and inspiring 3D forms.
keywords Form Finding; Machine Learning; Artificial Intelligence; Style Transfer
series CAADRIA
email
last changed 2022/06/07 07:56

_id caadria2020_037
id caadria2020_037
authors Yoon, Jungwon and Choi, Seok-won
year 2020
title Thermo-Shading - Digital Design and Additive Manufacturing of SMP Prototypes
doi https://doi.org/10.52842/conf.caadria.2020.1.035
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. 35-44
summary We present results on the development of an intelligent and informed SMP prototypes, as proof-of-concept models to assess applicability of thermo-responsive materials in adaptive façades. SMP has the intrinsic properties to detect environmental heat changes and react by changing its form into memorized shapes. Among different morphology and deformation behaviours of SMP components, this design-to-fabrication study focuses on design and 3D printing fabrication of prototypes. Additionally, casting was tested to validate the rapid prototyping of additive manufacturing. Furthermore, two different activation systems of SMP were presented to compare mechanisms between a surface-active system and an actuator system.
keywords SMP; AM; thermo-responsive
series CAADRIA
email
last changed 2022/06/07 07:57

_id caadria2020_276
id caadria2020_276
authors Chuang, I-Ting
year 2020
title Sensing the Diversity of Social Hubs through Social Media
doi https://doi.org/10.52842/conf.caadria.2020.2.061
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. 61-70
summary As we continue to discover the potential of social media data as an insightful source for academic research, the majority of previous work tends to focus on the density of socio-spatial relations as the foundation for understanding urban phenomena. This paper extended those approaches by introducing the concepts of diversity and inclusiveness through an investigation of the 'differences' within the networks of relations that are inherent to social media data. The author constructs a diversity measure based on the variety of home locations of social media user visitors to each geographical location in the city. This home location, in its turn, is derived from each user's digital spatio-temporal footprint. This proposed method demonstrates that through the visualization of this diversity measure, 'social hubs' (which are frequently visited by different groups of people) were able to be located that would otherwise be overlooked in conventional data analyses that focus only on density. As such, this research expands the usefulness of social media as a practical tool to help understand urban processes by making the concept of diversity - a key consideration in many planning and design contexts - measurable and mappable.
keywords Social Media Data; Home Location Detection; Diversity Analysis
series CAADRIA
email
last changed 2022/06/07 07:56

_id ecaade2020_392
id ecaade2020_392
authors Hadighi, Mahyar and Duarte, Jose P.
year 2020
title Local Adaptation of the International Style - Contextualizing Global Architecture between East and West
doi https://doi.org/10.52842/conf.ecaade.2020.2.331
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. 331-340
summary The aim of this paper is to highlight the effectiveness of shape grammar as a computational design methodology for verifying and describing hybridity in architectural design and generating a contextualized architecture. Part of a larger study, the present paper focuses on describing and verifying the respective influences of European modern and American traditional architecture on the mid-twentieth-century houses designed and built by a Penn State faculty-practitioner in State College, a college town in central Pennsylvania that is home to the university's largest campus. This hybridity phenomenon is analyzed using the shape grammar methodology, which is then also used to generate a hybrid architecture, not only for the same context, but also for contexts worldwide. Results from a workshop on the local adaptation of modern architecture focusing on the hybridity between the Persian garden style and the International Style of architecture to generate architecture appropriate to the context of Shiraz, the ancient capital of Iran, are analyzed in order to advance discussions of the methodology.
keywords Shape grammar; Persian garden; William Hajjar; Hybridity; local adaptation
series eCAADe
email
last changed 2022/06/07 07:49

_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
doi https://doi.org/10.52842/conf.ecaade.2021.2.095
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
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 acadia20_108p
id acadia20_108p
authors Akbarzadeh, Masoud; Ghomi, Ali Tabatabaie; Bolhassani, Mohammad; Akbari, Mostafa; Seyedahmadian, Alireza; Papalexiou, Konstantinos
year 2020
title Saltatur
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. 108-113.
summary The Saltatur (Dancer in Latin) demonstrates innovative research in the design and fabrication of a prefab structure consisting of spatial concrete nodes assembled in a compression-only configuration. The compression-only body is kept in equilibrium using the post-tensioning steel rods at the top and the bottom of the structure, supporting an ultra-thin glass structure on its top. A node-based assembly was considered as a method of construction. An innovative detailing was developed that allows locking each member in its exact location in the body, obviating the need for a particular assembly sequence. A bespoke steel connection transfers the tensile forces between the concrete members effectively. Achieving a high level of efficiency in utilizing concrete for spatial systems requires a robust and powerful structural design and fabrication approach that has been meticulously exhibited in this project. The structural form of the project was developed using a three-dimensional geometry-based structural design method known as 3D Graphic Statics with precise control over the magnitude of the lateral forces in the system. The entire concrete body of the structure is held in compression by the tension ties at the top and bottom of the structure with no horizontal reactions at the supports. This particular internal distribution of forces in the form of the compression-only body reduces the bending moment in the system and, therefore, the required mass to span such a distance.
series ACADIA
type project
email
last changed 2021/10/26 08:03

_id sigradi2020_60
id sigradi2020_60
authors Asmar, Karen El; Sareen, Harpreet
year 2020
title Machinic Interpolations: A GAN Pipeline for Integrating Lateral Thinking in Computational Tools of Architecture
source SIGraDi 2020 [Proceedings of the 24th Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Online Conference 18 - 20 November 2020, pp. 60-66
summary In this paper, we discuss a new tool pipeline that aims to re-integrate lateral thinking strategies in computational tools of architecture. We present a 4-step AI-driven pipeline, based on Generative Adversarial Networks (GANs), that draws from the ability to access the latent space of a machine and use this space as a digital design environment. We demonstrate examples of navigating in this space using vector arithmetic and interpolations as a method to generate a series of images that are then translated to 3D voxel structures. Through a gallery of forms, we show how this series of techniques could result in unexpected spaces and outputs beyond what could be produced by human capability alone.
keywords Latent space, GANs, Lateral thinking, Computational tools, Artificial intelligence
series SIGraDi
email
last changed 2021/07/16 11:48

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