Submit to Applied Sciences Review for Applied Sciences Propose a Special Issue

Journal Menu

Journal Browser

► Journal Browser

Advanced Technologies in Construction and Infrastructure: Theory, Methods and Applications

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Published Papers

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".

Deadline for manuscript submissions: closed (31 March 2024) | Viewed by 13148

Share This Special Issue

Special Issue Editors

Prof. Dr. Joo-Sung Lee

E-Mail Website
Guest Editor

Department of Architecture, Kangwon National University, 346 Jungang-ro, Samchuk 25913, Kangwon-do, Korea
Interests: construction management; construction ICT for automation; BIM; delivery system; lean & pre-construction
Special Issues, Collections and Topics in MDPI journals

Dr. Zhen Lei

E-Mail Website
Guest Editor

Offsite Construction Research Centre (OCRC), Department of Civil Engineering, University of New Brunswick, Fredericton, NB E3B 5A3, Canada
Interests: offsite construction; prefabricated construction; digital technologies in construction; data analytics and decision making in construction; building information modeling (BIM) and virtual design and construction (VDC)
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Kyubyung Kang

E-Mail Website
Guest Editor

School of Construction Management Technology, Purdue University, 401 N. Grant Street, West Lafayette, IN 47907, USA
Interests: computer vision; digital twin; infrastructure management; public participation; blockchain

Prof. Dr. Sungkon Moon

E-Mail Website
Guest Editor

Department of Civil Systems Engineering, Ajou University, Suwon 16499, Korea
Interests: construction engineering; automation and control engineering; logistics and supply chain management; technology innovation

Special Issue Information

Dear Colleagues,

The scope of this Special Issue covers innovative technology applications in construction and infrastructure. It also presents theory, methods, and cases of new technologies. New construction technologies can allow the relevant academics and those working in industry to conduct more innovative, faster, and more sustainable projects. The final goal of this Special Issue is to advance sustainable development in the industry by achieving successful application of new technologies. Construction technology is a collective terminology that includes many different types of innovations. Cutting-edge ideas and methods will be the main focus of this issue, and the practical and theoretical topics associated with construction technology will also be a core area of this Special Issue.

Topics of interest include, but are not limited to, the following:

Innovation in buildings, civil, and infrastructure engineering;
Virtual Technologies, including BIM, AR, VR, and the Metaverse;
Artificial Intelligence (AI) and construction robotics;
Offsite construction and design for manufacture and assembly;
Renewable energy and power plant construction;
Smart database and cloud communication in supply chains;
Blockchain and information security;
Unmanned aerial vehicles;
Additive technology and 3DP construction;
Data-driven analysis in construction.

Prof. Dr. Joo-Sung Lee
Dr. Zhen Lei
Prof. Dr. Kyubyung Kang
Prof. Dr. Sungkon Moon
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.

Published Papers (10 papers)

Download All Papers

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

Jump to: Review, Other

15 pages, 4237 KiB

Open AccessArticle

Intelligent Detection of Rebar Size and Position Using Improved DeeplabV3+

by Wei Chen, Xianglin Fu, Wanqing Chen and Zijun Peng

Appl. Sci. 2023, 13(19), 11094; https://doi.org/10.3390/app131911094 - 09 Oct 2023

Viewed by 1075

Abstract

For the development of reinforced concrete structures and infrastructure construction, traditional rebar checking and acceptance methods have shortcomings in terms of efficiency. The use of digital image processing technology cannot easily identify a rebar configuration with complex and diverse backgrounds. To solve this problem, an inspection method combining deep learning and digital image processing techniques is proposed using an improved DeeplabV3+ model to identify reinforcing bars, with the identification results subjected to digital image processing operations to obtain the size information of the reinforcing bar. The proposed method was validated through a field test. The results of the experiment indicated that the proposed model is more accurate than other models, with a mean Intersection over Union (mIoU), precision, recall, and F1 score reaching 94.62%, 97.42%, 96.95%, and 97.18%, respectively. Moreover, the accuracy of the dimension estimations for the test reinforcements met the engineering acceptance standards. Full article

(This article belongs to the Special Issue Advanced Technologies in Construction and Infrastructure: Theory, Methods and Applications)

► Show Figures

Figure 1

26 pages, 2999 KiB

Open AccessArticle

Risk Interdependency Network Model for the Cost and Time of Pile Installation in Saudi Arabia, Using Partial Least Squares Structural Equation Modeling

by Naif M. Alsanabani, Khalid S. Al-Gahtani, Abdulmohsen S. Almohsen and Abdullah Alsharef

Appl. Sci. 2023, 13(19), 10886; https://doi.org/10.3390/app131910886 - 30 Sep 2023

Cited by 1 | Viewed by 739

Abstract

Pile construction projects cause significant time and expense overruns. The pile installation activity is the primary reason for project underperformance and uncertainties. Additionally, the risks associated with pile installation are mostly considered independent in the overall risk management process, leading to inadequate risk assessment and response. However, few studies have evaluated the risks associated with pile installation. Thus, this study aims to establish the risks of the time and cost of pile installation, using an interdependency network model with a particular emphasis on sand and rocky terrain conditions. In addition, this study introduces a new method for establishing a model that considers the interrelationships among risks via a partial least squares structural equation model (PLS-SEM). The research methodology involves assessing the probability and impact of 53 risk factors of pile installation time and cost. Twelve pile construction experts participated in this assessment. Then, a Monte Carlo Simulation was utilized before the data were integrated into the PLS-SEM. The research findings reveal that the site and economic risks indirectly affect the cost of installing pile in sand through construction risks. Also, the risk group comprising site and equipment risks indirectly affects the cost of installing pile in rock through design risks. This study’s findings will help construction organizations to improve time and cost risk assessments for pile installation projects. Full article

(This article belongs to the Special Issue Advanced Technologies in Construction and Infrastructure: Theory, Methods and Applications)

► Show Figures

Figure 1

13 pages, 2130 KiB

Open AccessArticle

Transfer Learning-Based Object Detection Model for Steel Structure Bolt Fastening Inspection

by Jaehyun Choi, Minhui Ha and Jin Gang Lee

Appl. Sci. 2023, 13(17), 9499; https://doi.org/10.3390/app13179499 - 22 Aug 2023

Cited by 1 | Viewed by 921

Abstract

As improper inspection of construction works can cause an increase in project costs and a decrease in project quality, construction inspection is considered a critical factor for project success. While traditional inspection tasks are still mainly labor-intensive and time-consuming, computer vision has the potential to revolutionize the construction inspection process by providing more efficient and effective ways to monitor the progress and quality of construction projects. However, previous studies have also indicated that the performance of vision-based site monitoring heavily relies on the volume of training data. To address the issues of challenging data collection at construction sites, this study developed models using transfer learning-based object detection models incorporating data augmentation and transfer learning. The performance of three object detection algorithms was compared based on average precision and inference time for detecting T/S bolt fastening of steel structure. Despite the limited training data available, the model’s performance was improved through data augmentation and transfer learning. The proposed inspection model can increase the efficiency of quality control works for building construction projects and the safety of inspectors. Full article

(This article belongs to the Special Issue Advanced Technologies in Construction and Infrastructure: Theory, Methods and Applications)

► Show Figures

Figure 1

19 pages, 3500 KiB

Open AccessArticle

Artificial Neural Network Model to Predict Final Construction Contract Duration

by Abdullah M. Alsugair, Khalid S. Al-Gahtani, Naif M. Alsanabani, Abdulmajeed A. Alabduljabbar and Abdulmohsen S. Almohsen

Appl. Sci. 2023, 13(14), 8078; https://doi.org/10.3390/app13148078 - 11 Jul 2023

Cited by 4 | Viewed by 1040

Abstract

Forecasting the final construction contract duration at an early stage plays a vital role in the progress of a project. An inaccurate project duration prediction may lead to the project’s benefits being lost. It is essential to precisely predict the duration due to the presence of several different factors. This paper contributed to developing a model to predict final construction contract duration (FCCD) in the early stages based on parameters characterized as few and shared for any contract. (contract cost, contract duration, and sector). This paper developed an Artificial Neural Network (ANN) model based on 135 Saudi construction project data. The development model has three stages. The first stage was standardization and augmentation using Zavadskas and Turskis’ logarithmic and Pasini methods. The second and third stages were the first and second analyses of the ANN models, respectively. The first analysis aimed to promote the used data and integrate them into the second analysis to develop the ANN model. The ANN models were compared with three linear regression (LR) models (LR1, LR2, and LR3) and other models in the literature. The results revealed that the accuracy of the ANN model provides reasonable accuracy with an average mean absolute percentage error (MAPE) of 12.22%, which is lower than the LR3′s MAPE by 27.03%. The accuracy of the ANN model is similar to that of earned value management (EVM) in the previous study. This paper supports research to deal with relatively little data and integrate them into a neural network. The ANN model assists the stakeholder in making appropriate decisions for the project during the pre-tendering phase by predicting the actual contract duration based on the CC, CD, and project sector. Full article

(This article belongs to the Special Issue Advanced Technologies in Construction and Infrastructure: Theory, Methods and Applications)

► Show Figures

Figure 1

12 pages, 604 KiB

Open AccessArticle

Formation of Rational Sets of Machines for Excavation Work in Urban Areas

by Azariy Lapidus, Dmitriy Topchiy, Tatyana Kuzmina and Vladimir Efimov

Appl. Sci. 2023, 13(12), 7023; https://doi.org/10.3390/app13127023 - 11 Jun 2023

Viewed by 726

Abstract

The study is aimed at developing a tool for the formation of a rational set of machines for excavation work in urban areas. The instrument to be developed will affect the main project parameters, such as the project cost and term of implementation. An expert survey was launched among the leading specialists of the construction industry to make a set of significant parameters and identify the weighting ratio, since both are required to select the machines for rational sets designated for excavation work in urban environments. The equation of multiple regression was solved to determine the extent of significance by calculating Fisher’s ratio. This equation shows that significant parameters are inter-related and can be used in this method. A method for making a rational set of machines, designated for the performance of excavation work in urban environments, has the following stages: at the first stage, the choice of the necessary excavation work at the construction site is made; at the second stage, limitations, arising at the site, are introduced; at the third stage, the minimum number of major machines is determined; at the fourth stage, a rational set of machines is made step by step. If implemented, this study demonstrates the high economic efficiency of the proposed method of expanding excavation work in urban environments. The study shows that the use of a mathematical model will boost the project’s success, as it demonstrates the critical factors of risk at the initial stage of the life cycle of a construction project. Full article

(This article belongs to the Special Issue Advanced Technologies in Construction and Infrastructure: Theory, Methods and Applications)

► Show Figures

Figure 1

17 pages, 1365 KiB

Open AccessArticle

Analysis of Design Change Mechanism in Apartment Housing Projects Using Association Rule Mining (ARM) Model

by Moonhwan Kim, Joosung Lee and Jaejun Kim

Appl. Sci. 2022, 12(21), 11036; https://doi.org/10.3390/app122111036 - 31 Oct 2022

Viewed by 1241

Abstract

Apartment housing occupies the highest proportion of the domestic construction market and significantly influences the flow of the real estate market. Frequent design changes and reconstruction in new apartment housing projects lead to an increase in construction cost and schedule, and a decline in design and construction quality, which is an important issue affecting the quality of use for occupants. The causal relationship of design changes and error in new apartment building projects has not been previously identified. Accordingly, design changes management activities in the construction phase using reactive manner are a critical risk that causes the productivity of the project to deteriorate. In this study, a complex and non-linear causal relationship between the design change factors was investigated using the association rule mining technique (ARM), a type of data mining technique. In particular, the associated relationship between design change factors that can be changed according to conditions that significantly affect the productivity and performance of projects, such as a contractor’s ranking in the field, contract price which means the project size, and contractor selection methods, was identified. The association rule between the design changes at the construction phase derived in this research can be used as a guide to identify and minimize the risk of design changes in advance. Full article

(This article belongs to the Special Issue Advanced Technologies in Construction and Infrastructure: Theory, Methods and Applications)

► Show Figures

Figure 1

17 pages, 4213 KiB

Open AccessArticle

Research on Optimization Design of Geometric Parameters of a Novel Frame-Embedded Track (NFET)

by Zhiping Zeng, Yancai Xiao, Xudong Huang, Weidong Wang, Di Wang, Ayoub Abdullah Senan Qahtan, Weidong Yuan and Saidi Boumedienne Houdou

Appl. Sci. 2022, 12(20), 10441; https://doi.org/10.3390/app122010441 - 16 Oct 2022

Viewed by 1416

Abstract

A novel frame-embedded track (NFET) with additional beams between the prefabricated rail seats before was proposed, but its geometric parameters need to be further optimized, in order to solve the problem of difficulty in adjustment, due to the independence of the two prefabricated rail seats during the construction of tram. Based on the finite element method, the geometric parameters of the NFET structure are systematically studied and optimized. The research shows: (1) As the width of the beams and the thickness of the lower slab increases, the mechanical characteristics of the NFET structure does not change significantly; therefore, the recommended design reference value for these two are 240 and 80 mm, respectively. (2) When considering the cable and the drainage facilities, the stress state of the NFET structure is less affected (or even improved), which proves that the layout of the cable and the drainage facilities is feasible. (3) According to the analysis during different construction stages, the stress of the NFET rail seats is generally greater than the stress of the cast-in-place concrete. It is recommended that the intensity of the cast-in-place concrete should be greater than that of the prefabricated frame structure. Full article

(This article belongs to the Special Issue Advanced Technologies in Construction and Infrastructure: Theory, Methods and Applications)

► Show Figures

Figure 1

21 pages, 6467 KiB

Open AccessArticle

Numerical Simulation Research on Mechanical Optimization of a Novel Fastener Type Ballastless Track (NFTBT) for Tram

by Zhiping Zeng, Xiaodong He, Xudong Huang, Weidong Wang, Di Wang, Ayoub Abdullah Senan Qahtan, Weidong Yuan and Houdou Saidi Boumedienne

Appl. Sci. 2022, 12(17), 8807; https://doi.org/10.3390/app12178807 - 01 Sep 2022

Cited by 2 | Viewed by 1383

Abstract

In view of the problems present in the construction process of the embedded track structure of modern tram, we have designed a Novel Fastener Type Ballastless Track (NFTBT) for tram. To optimize the size of the NFTBT’s structure, the finite element model of the NFTBT’s structure in the tram running stage is built, the mechanical characteristics of the NFTBT’s structure are calculated, and the geometric parameters of the NFTBT’s structure are systematically studied. The research results are as follows: (1) As the size of the track slab increases, the displacement differences of the middle part of the NFTBT are similar, and the size of the track slab has little effect on the displacement. (2) The stress difference of the NFTBT’s structure under the different distances between the centers of the adjacent grouting holes’ conditions is small. Although a larger distance between the centers of the adjacent grouting holes can reduce the number of grouting holes in the track slab, the distance should not be too large to reduce the peak stress at the bottom of the NFTBT. (3) When the distance between the adjacent fasteners of the NFTBT changes within a certain range, the rail is greatly affected by the uneven settlement of the subgrade, and the track irregularity will be aggravated. (4) The NFTBT does not require the implementation of cable passages at intervals, which facilitates the passage and fixation of the cables in the tram operation section and can reduce the difficulty of adjusting the geometry of the track structure, thus accelerating the construction progress. Full article

(This article belongs to the Special Issue Advanced Technologies in Construction and Infrastructure: Theory, Methods and Applications)

► Show Figures

Figure 1

Review

Jump to: Research, Other

25 pages, 2764 KiB

Open AccessReview

Cybersecurity Vulnerabilities in Off-Site Construction

by Kudakwashe Nyamuchiwa, Zhen Lei and Clodualdo Aranas, Jr.

Appl. Sci. 2022, 12(10), 5037; https://doi.org/10.3390/app12105037 - 16 May 2022

Cited by 2 | Viewed by 2488

Abstract

Industry 4.0 is seeking to advance traditional construction practices towards more efficient and internet of things (IoT)-based construction practices, such as offsite construction. Offsite construction (OSC) allows for the simultaneous fabrication of building modules and onsite work. Integrating IoT technologies in construction practice is projected to improve the industry’s growth. However, there is an increase in cybersecurity vulnerabilities. Cyber threats are becoming more disruptive and targeted, resulting in monetary and infrastructure losses. Furthermore, the COVID pandemic and the instability in Europe have seen over 100% increases in cyber-attacks, and most industries have weak cybersecurity protocols. The adoption of cybersecurity frameworks in the construction industry is sluggish, and the existing security frameworks fall short in addressing the needs of the industry. This paper gives a concise review of the offsite construction value chain vulnerabilities. We explore the existing cybersecurity frameworks and identify their limitations. Cybersecurity is presented as one of the most crucial components that has received little or no attention in OSC. The future of OSC is promising with the incorporation of Industry 4.0 technologies; however, its development needs to consider more proactive security approaches and management techniques that are adapted to the current hostile cyber landscape. Full article

(This article belongs to the Special Issue Advanced Technologies in Construction and Infrastructure: Theory, Methods and Applications)

► Show Figures

Figure 1

Other

Jump to: Research, Review

19 pages, 4815 KiB

Open AccessSystematic Review

Suitability Evaluation of Old Industrial Buildings Transformed into Stadiums

by Lixin Jia, Cheng Sun, Wenhao Lv and Wenlong Li

Appl. Sci. 2023, 13(14), 8065; https://doi.org/10.3390/app13148065 - 10 Jul 2023

Viewed by 1002

Abstract

The regeneration and utilization of idle, old industrial buildings in urban areas has become a focus of urban development, owing to urban renewal and industrial structural adjustment. At the same time, the increasing demand for sports space has highlighted the insufficient supply of sports facilities in cities. To solve this dilemma, the transformation of old industrial buildings into sports venues has become another mode of recycling and reuse in recent years. Due to the many specialties, complex contents, and numerous influencing factors involved in the transformation process, the suitability of these buildings is uncertain. To ensure the suitability of the transformation project, the theory of old industrial buildings recycling and sports building design specifications was used. An index system was established for the evaluating the suitability of transforming old industrial buildings into stadiums, which included five first-level and twenty second-level indices. Based on the matter–element extension theory, a suitability evaluation model was constructed to transform old industrial buildings into sports venues. The correlation function of each evaluation index was calculated, and the index weight was determined using the entropy weight method to obtain the suitability grade of the renovation project, which was verified by the renovation project case. The research shows that the suitability level of the renovation project is level II, which is consistent with the actual situation, indicating that the evaluation model—based on entropy weight method and matter–element extension method—for the transformation of old industrial buildings and stadiums has high reliability. Full article

(This article belongs to the Special Issue Advanced Technologies in Construction and Infrastructure: Theory, Methods and Applications)

► Show Figures

Journal Menu

Journal Browser

Advanced Technologies in Construction and Infrastructure: Theory, Methods and Applications

Share This Special Issue

Special Issue Editors

Special Issue Information

Published Papers (10 papers)

Research

Review

Other

Further Information

Guidelines

MDPI Initiatives

Follow MDPI