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Technologies
Special Issues
Computer-Aided Architectural Design
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Computer-Aided Architectural Design

A special issue of Technologies (ISSN 2227-7080).

Deadline for manuscript submissions: closed (30 November 2019) | Viewed by 26950

Special Issue Editor

Assoc. Prof. Dr. Taro Narahara

E-Mail Website
Guest Editor
College of Architecture and Design, New Jersey Institute of Technology, Newark, NJ, USA
Interests: architecture; computational design; AI; deep learning; self-organizing systems; agent-based simulations; participatory design; robotic fabrication; physical computing; human–computer interaction

Special Issue Information

Dear Colleagues,

Computer-aided architectural design (CAAD) has evolved over the last decade due to environmental changes and rapid technological advancement. Since the so-called “super-smart society” is going to become a reality in the near future, CAAD is currently exploring its expanded new roles and approaches, such as generative design, additive manufacturing, smart buildings and cities, seamless simulations for evidence-based design, intuitive and interactive visualization for participatory design, digital twin, telepresence, robotic process automation, and digital conservation, in addition to the further upgraded architectural design and communication medium, which were its original major roles. CAAD also covers impact, transformation, and education for architects, designers, engineers, and citizens in the future architecture and building fields.
In this Special Issue, we seek contributions in the field of CAAD in a broad sense. CAAD covers interdisciplinary fields which include natural science, arts and humanities, and social science. We invite your submissions related to but not limited to the keywords below.
If you are not sure if your paper fits the focus of this Special Issue, please contact the Guest Editor.

Assoc. Prof. Dr. Tomohiro Fukuda
Assoc. Prof. Dr. Taro Narahara
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Technologies is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Artificial intelligence and machine learning
  • Smart buildings, smart cities
  • Virtual, augmented, and mixed reality (VR/AR/MR)
  • Digital fabrication and robotics
  • Telepresence, collaborative design
  • Digital twin
  • Generative, algorithmic, and parametric design
  • Internet of Things (IoT), Big Data
  • Performance-based design
  • Interactive and responsive design/environments
  • Human–computer interaction
  • Computational design education
  • Digital conservation, digital heritage
  • Building information modeling (BIM)
  • Modeling, simulation, and analysis
  • Laser scanning, photogrammetry, structure from motion (SfM), point clouds

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Published Papers (3 papers)

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Research

22 pages, 9745 KiB  
Article
Integrating Animated Computational Fluid Dynamics into Mixed Reality for Building-Renovation Design
by Yuehan Zhu, Tomohiro Fukuda and Nobuyoshi Yabuki
Technologies 2020, 8(1), 4; https://doi.org/10.3390/technologies8010004 - 29 Dec 2019
Cited by 18 | Viewed by 8800
Abstract
In advanced society, the existing building stock has a high demand for stock renovation, which gives existing buildings new lives, rather than building new ones. During the renovation process, it is necessary to simultaneously achieve architectural, facilities, structural, and environmental design in order [...] Read more.
In advanced society, the existing building stock has a high demand for stock renovation, which gives existing buildings new lives, rather than building new ones. During the renovation process, it is necessary to simultaneously achieve architectural, facilities, structural, and environmental design in order to accomplish a healthy, comfortable, and energy-saving indoor environment, prevent delays in problem-solving, and achieve a timely feedback process. This study tackled the development of an integrated system for stock renovation by considering computational fluid dynamics (CFD) and mixed reality (MR) in order to allow the simultaneous design of a building plan and thermal environment. The CFD analysis enables simulation of the indoor thermal environment, including the entire thermal change process. The MR system, which can be operated by voice command and operated on head-mounted display (HMD), enables intuitive visualization of the thermal change process and, in a very efficient manner, shows how different renovation projects perform for various stakeholders. A prototype system is developed with Unity3D engine and HoloLens HMD. In the integrated system, a new CFD visualization method generating 3D CFD animation sequence for the MR system is proposed that allows stakeholders to consider the entirety of changes in the thermal environment. Full article
(This article belongs to the Special Issue Computer-Aided Architectural Design)
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14 pages, 32289 KiB  
Article
3D Model Generation on Architectural Plan and Section Training through Machine Learning
by Hang Zhang
Technologies 2019, 7(4), 82; https://doi.org/10.3390/technologies7040082 - 15 Nov 2019
Cited by 22 | Viewed by 11968
Abstract
Machine learning, especially the GAN (Generative Adversarial Network) model, has been developed tremendously in recent years. Since the NVIDIA Machine Learning group presented the StyleGAN in December 2018, it has become a new way for designers to make machines learn different or similar [...] Read more.
Machine learning, especially the GAN (Generative Adversarial Network) model, has been developed tremendously in recent years. Since the NVIDIA Machine Learning group presented the StyleGAN in December 2018, it has become a new way for designers to make machines learn different or similar types of architectural photos, drawings, and renderings, then generate (a) similar fake images, (b) style-mixing images, and (c) truncation trick images. The author both collected and created input image data, and specially made architectural plan and section drawing inputs with a clear design purpose, then applied StyleGAN to train specific networks on these datasets. With the training process, we could look into the deep relationship between these input architectural plans or sections, then generate serialized transformation images (truncation trick images) to form the 3D (three-dimensional) model with a decent resolution (up to 1024 × 1024 × 1024 pixels). Though the results of the 3D model generation are difficult to use directly in 3D spatial modeling, these unexpected 3D forms still could inspire new design methods and greater possibilities of architectural plan and section design. Full article
(This article belongs to the Special Issue Computer-Aided Architectural Design)
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22 pages, 5032 KiB  
Article
From Undesired Flaws to Esthetic Assets: A Digital Framework Enabling Artistic Explorations of Erroneous Geometric Features of Robotically Formed Molds
by Malgorzata A. Zboinska
Technologies 2019, 7(4), 78; https://doi.org/10.3390/technologies7040078 - 31 Oct 2019
Cited by 2 | Viewed by 4994
Abstract
Until recently, digital fabrication research in architecture has aimed to eliminate manufacturing errors. However, a novel notion has just been established—intentional computational infidelity. Inspired by this notion, we set out to develop means than can transform the errors in fabrication from an undesired [...] Read more.
Until recently, digital fabrication research in architecture has aimed to eliminate manufacturing errors. However, a novel notion has just been established—intentional computational infidelity. Inspired by this notion, we set out to develop means than can transform the errors in fabrication from an undesired complication to a creative opportunity. We carried out design experiment-based investigations, which culminated in the construction of a framework enabling fundamental artistic explorations of erroneous geometric features of robotically formed molds. The framework consists of digital processes, assisting in the explorations of mold errors, and physical processes, enabling the inclusion of physical feedback in digital explorations. Other complementary elements embrace an implementation workflow, an enabling digital toolset and a visual script demonstrating how imprecise artistic explorations can be included within the computational environment. Our framework application suggests that the exploration of geometrical errors aids the emergence of unprecedented design features that would not have arisen if error elimination were the ultimate design goal. Our conclusion is that welcoming error into the design process can reinstate the role of art, craft, and material agency therein. This can guide the practice and research of architectural computing onto a new territory of esthetic and material innovation. Full article
(This article belongs to the Special Issue Computer-Aided Architectural Design)
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