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Cutting-Edge Additive Manufacturing Technologies for Construction Applications

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Additive Manufacturing Technologies".

Deadline for manuscript submissions: closed (10 May 2022) | Viewed by 3460

Special Issue Editors


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Guest Editor
School of Civil and Environmental Engineering, Faculty of Engineering and Information Technology, University of Technology Sydney, Broadway, NSW 2007, Australia
Interests: additive manufacturing; 3D printing concrete; structural health monitoring; sustainable materials; FEA simulation

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Guest Editor
School of Civil and Environmental Engineering, Engineering Faculty, University of New South Wales, Kensington, NSW 2052, Australia
Interests: concrete 3D printing; sustainable concrete technologies; circular economy in construction
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Additive Manufacturing (AM) technologies are the most suitable technologies for construction applications in the fourth industrial revolution. Among these techniques extrusion printing, binder jetting (inkjet) printing, powder bed fusion, robocasting and smart dynamic casting are among the most usable printing techniques for construction applications. Extrusion 3D printing is a well-known AM technique for construction printing. However, this is not the only AM technology for construction but also binder jetting is another most promising technique for cementitious and metal printing materials. In addition, other techniques like powder bed fusion will be the future of 3D printing technology for construction applications, particularly in the harsh environment and beyond earth’s application. Steel 3D printing is considered the most vital material for construction purposes, it is required to be investigated further particularly in powder bed fusion. These techniques could be used to create 3D printing composite materials in the cast-in-situ or precast structures, this will be highly efficient to make a sustained environment. Obviously, this could be challenging when printing two different materials in one application. However, there are limited studies that could be found on this topic. This special issue could assist researchers, engineers and scientists to share their new conceptual, experimental, theoretical and numerical methods of AM technology in order to optimise the materials mix design and process. Accordingly, selecting proper materials and AM technologies could be measured as a vital stage to increase the potential of 3D printing for construction applications. 

This issue is anticipated to provide a collection of papers presenting a various range of original research and review papers on AM techniques for different materials in construction and outcomes forthcoming perspectives for infrastructure and construction applications.

Dr. Pshtiwan Shakor
Dr. Alireza Kashani
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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2400 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

  • additive manufacturing
  • extrusion 3DP
  • binder jetting 3DP
  • powder bed fusion
  • construction materials
  • construction application
  • curing
  • post-processing

Published Papers (1 paper)

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Research

22 pages, 6566 KiB  
Article
Predicting Compressive Strength of 3D Printed Mortar in Structural Members Using Machine Learning
by Hamed Izadgoshasb, Amirreza Kandiri, Pshtiwan Shakor, Vittoria Laghi and Giada Gasparini
Appl. Sci. 2021, 11(22), 10826; https://doi.org/10.3390/app112210826 - 16 Nov 2021
Cited by 21 | Viewed by 2694
Abstract
Machine learning is the discipline of learning commands in the computer machine to predict and expect the results of real application and is currently the most promising simulation in artificial intelligence. This paper aims at using different algorithms to calculate and predict the [...] Read more.
Machine learning is the discipline of learning commands in the computer machine to predict and expect the results of real application and is currently the most promising simulation in artificial intelligence. This paper aims at using different algorithms to calculate and predict the compressive strength of extrusion 3DP concrete (cement mortar). The investigation is carried out using multi-objective grasshopper optimization algorithm (MOGOA) and artificial neural network (ANN). Given that the accuracy of a machine learning method depends on the number of data records, and for concrete 3D printing, this number is limited to few years of study, this work develops a new method by combining both methodologies into an ANNMOGOA approach to predict the compressive strength of 3D-printed concrete. Some promising results in the iteration process are achieved. Full article
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