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State-of-the-Art Construction Materials and Technologies for Structural Health Monitoring of Infrastructures

A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Construction and Building Materials".

Deadline for manuscript submissions: 10 October 2024 | Viewed by 1093

Special Issue Editors

Dr. Byeong Hun Woo

E-Mail Website
Guest Editor
Civil and Environmental Engineering Department, Room 404, Jaesung Civil Engineering Building, Hanyang University, 222 Wangsimni-ro, Seongdong Gu, Seoul, Republic of Korea
Interests: green/smart construction materials; rebar corrosion; maintenance; structural health monitoring; durability; Bayesian inference; artificial neural networks
Dr. Hong Gi Kim

E-Mail Website
Guest Editor
Civil and Environmental Engineering Department, Hanyang University, Jaesung Civil Engineering Building, 222 Wangsimni-ro, Seongdong Gu, Seoul 04763, Republic of Korea
Interests: cement composites; durability; thermal/electrical conductivity

Special Issue Information

Dear Colleagues,

Technology is advancing at an incredibly fast pace around the world; subsequently, construction technology is evolving to keep pace as well, and remarkable technologies are launched every year, from advances in materials to smart construction using artificial neural networks. Research in this field aims to analyze the performance, properties, and characteristics of different materials, such as concrete, steel, wood, and composites, in order to optimize their structural integrity, energy efficiency, fire resistance, and environmental impact. By examining the behavior and durability of construction materials under different conditions and loads, researchers can identify potential weaknesses and develop novel solutions to enhance their performance and sustainability requirements, ultimately contributing to the advancement of the construction industry as a whole. Consequently, this Special Issue is a specially proposed issue with the purpose of including excellent technical articles from researchers. Therefore, this Special Issue actively welcomes your submissions and awaits your excellent research, aiming to include studies on advanced technologies such as smart construction materials, machine learning, structural health monitoring, corrosion monitoring, durability smart analysis, and so on.

It is our pleasure to invite you to submit a manuscript for this Special Issue. Full papers, communications, and reviews are all welcome.

Dr. Byeong Hun Woo
Dr. Hong Gi Kim
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. Materials 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 2600 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

  • smart construction materials
  • self-sensing cement composites
  • thermal properties of the cement composites
  • smart snow-melting systems
  • rebar corrosion monitoring
  • durability analysis
  • machine learning
  • advanced statistical approaches

Published Papers (2 papers)

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Research

25 pages, 9928 KiB  
Article
Machine Learning-Based Simulation of the Air Conditioner Operating Time in Concrete Structures with Bayesian Thresholding
by Changhwan Jang, Hong-Gi Kim and Byeong-Hun Woo
Materials 2024, 17(9), 2108; https://doi.org/10.3390/ma17092108 - 29 Apr 2024
Viewed by 298
Abstract
Efficient energy use is crucial for achieving carbon neutrality and reduction. As part of these efforts, research is being carried out to apply a phase change material (PCM) to a concrete structure together with an aggregate. In this study, an energy consumption simulation [...] Read more.
Efficient energy use is crucial for achieving carbon neutrality and reduction. As part of these efforts, research is being carried out to apply a phase change material (PCM) to a concrete structure together with an aggregate. In this study, an energy consumption simulation was performed using data from concrete mock-up structures. To perform the simulation, the threshold investigation was performed through the Bayesian approach. Furthermore, the spiking part of the spiking neural network was modularized and integrated into a recurrent neural network (RNN) to find accurate energy consumption. From the training-test results of the trained neural network, it was possible to predict data with an R2 value of 0.95 or higher through data prediction with high accuracy for the RNN. In addition, the spiked parts were obtained; it was found that PCM-containing concrete could consume 32% less energy than normal concrete. This result suggests that the use of PCM can be a key to reducing the energy consumption of concrete structures. Furthermore, the approach of this study is considered to be easily applicable in energy-related institutions and the like for predicting energy consumption during the summer. Full article
(This article belongs to the Special Issue State-of-the-Art Construction Materials and Technologies for Structural Health Monitoring of Infrastructures)
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17 pages, 9417 KiB  
Article
Utilizing Wheel Washing Machine Sludge as a Cement Substitute in Repair Mortar: An Experimental Investigation into Material Characteristics
by Changhwan Jang and Tadesse Natoli Abebe
Materials 2024, 17(9), 2037; https://doi.org/10.3390/ma17092037 - 26 Apr 2024
Viewed by 275
Abstract
The construction industry strives for sustainable solutions to tackle environmental challenges and optimize resource use. One such focus area is the management of industrial byproducts and waste materials, including fugitive dust control through wheel washers. While wheel washers play a pivotal role in [...] Read more.
The construction industry strives for sustainable solutions to tackle environmental challenges and optimize resource use. One such focus area is the management of industrial byproducts and waste materials, including fugitive dust control through wheel washers. While wheel washers play a pivotal role in dust management, they generate a challenging byproduct known as wheel washer sludge (WWS). The disposal of WWS is complicated due to its composition and potential hazards. Recent research explores reusing WWS in construction materials, particularly in repair mortar, aiming for sustainability and circular economy principles. This study investigates the incorporation of WWS into repair mortar formulations, evaluating mechanical properties, durability, and environmental implications. Results show that WWS enhances workability but prolongs setting time. Mechanical strength tests reveal improvements with WWS addition, especially when pretreated. Water absorption rates decrease with pretreated WWS, indicating enhanced durability. Chemical attack tests demonstrate resistance to carbonation and chloride penetration, especially with modified WWS. Freeze–thaw tests reveal improved resistance with WWS addition, particularly modified. Microstructure analysis confirms hydration products and denser matrices with WWS inclusion. Environmental hazard analysis shows WWS contains no harmful heavy metals, indicating its suitability for use in repairs. Overall, this study highlights the technical feasibility and environmental benefits of incorporating WWS into repair mortar, contributing to sustainable construction practices. Full article
(This article belongs to the Special Issue State-of-the-Art Construction Materials and Technologies for Structural Health Monitoring of Infrastructures)
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