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Buildings
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Intelligence Techniques Applied in Infrastructure, Engineering and Construction
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Intelligence Techniques Applied in Infrastructure, Engineering and Construction

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Construction Management, and Computers & Digitization".

Deadline for manuscript submissions: 30 July 2024 | Viewed by 1055

Special Issue Editors

Dr. Kaiwen Liu

E-Mail Website
Guest Editor
MOE Key Laboratory of High-Speed Railway Engineering, Southwest Jiaotong University, Chengdu 610031, China
Interests: data-driven maintenance in civil and infrastructure engineering; ground improvement; sensor-enabled geosynthetics; transportation geotechnics, subgrade dynamics; soil stabilization
Special Issues, Collections and Topics in MDPI journals
Dr. Tengfei Wang

E-Mail Website
Guest Editor
School of Civil Engineering, Southwest Jiaotong University, Chengdu 610031, China
Interests: deep learning in civil and infrastructure engineering; transportation geotechnics; subgrade dynamics; ground improvement; frozen ground engineering; soil stabilization
Dr. Xiaoning Zhang

E-Mail Website
Guest Editor
School of Civil Engineering, Chongqing University, Chongqing 400045, China
Interests: traffic geotechnical engineering; subgrade composite structure design; intelligent construction of subgrade; long-term performance prediction of subgrade; subgrade risk assessment and management

Special Issue Information

Dear Colleagues,

In an era where intelligent techniques are increasingly pivotal, their integration into infrastructure, engineering, and construction represents a groundbreaking shift towards more innovative, efficient, and sustainable approaches. This Special Issue focuses on the transformative role of artificial intelligence, machine learning, predictive analytics, and smart construction techniques within these sectors. By emphasizing the synergy between advanced technologies and traditional practices, we seek to highlight how these tools are redefining the paradigms of infrastructure development and management.

We invite contributions that delve into the application of these intelligent techniques across a broad spectrum, including green transportation solutions, intelligent transportation systems, and the enhancement of infrastructure durability and robustness. Papers exploring big data applications in transportation, risk assessment, and management strategies, as well as energy optimization in the context of infrastructure projects, are particularly welcome.

This Special Issue aims to showcase interdisciplinary research that bridges the gap between emerging technologies and conventional infrastructure methodologies. By highlighting innovative applications and theoretical progress, this Special Issue aspires to contribute to the advancement of intelligent techniques in creating more resilient, efficient, and sustainable infrastructure systems.

We look forward to receiving your insightful contributions to this important and timely topic.

Dr. Kaiwen Liu
Dr. Tengfei Wang
Dr. Xiaoning Zhang
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. Buildings 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 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

  • artificial intelligence
  • machine learning
  • predictive analytics
  • smart construction techniques
  • green transportation solutions
  • intelligent transportation systems
  • infrastructure durability and robustness
  • big data in transportation
  • risk assessment and management
  • energy optimization

Published Papers (2 papers)

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Research

18 pages, 7074 KiB  
Article
Numerical Investigation on the Seismic Behavior of Novel Precast Beam–Column Joints with Mechanical Connections
by Mei-Ling Zhuang, Chuanzhi Sun, Zhen Yang, Ran An, Liutao Bai, Yixiang Han and Guangdong Bao
Buildings 2024, 14(5), 1199; https://doi.org/10.3390/buildings14051199 - 23 Apr 2024
Viewed by 340
Abstract
Traditional cast-in-place beam–column joints have the defects of high complexity and high construction difficulty, which seriously affect the efficiency and safety of the building construction line, and precast beam–column joints (PBCJs) can greatly improve the construction efficiency and quality. At present, the investigations [...] Read more.
Traditional cast-in-place beam–column joints have the defects of high complexity and high construction difficulty, which seriously affect the efficiency and safety of the building construction line, and precast beam–column joints (PBCJs) can greatly improve the construction efficiency and quality. At present, the investigations on the seismic behavior of precast reinforced concrete structures are still mainly focused on experiments, while the numerical simulations for their own characteristics are still relatively lacking. In the present study, the seismic behavior of novel precast beam–column joints with mechanical connections (PBCJs-MCs) is investigated numerically. Based on the available experimental data, fiber models for four PBCJs-MCs are developed. Then, the simulated and experimental seismic behaviors of the prefabricated BCJs are compared and discussed. Finally, the factors influencing the seismic behavior of the PBCJs-MCs are further investigated numerically. The numerical results indicate that the fiber models can consider the effect of the bond–slip relationship of concrete and reinforcement under reciprocating loads. The relative errors of the simulated seismic behavior indexes are about 15%. The bearing capacity and displacement ductility coefficients of the PBCJs-MCs decrease rapidly as the shear-to-span ratio (λ) increases. It is recommended that the optimum λ for PBCJs-MCs is 2.0–2.5. The effect of the axial load ratio on the seismic behavior of PBCJs-MCs can be negligible in the case of the PBCJs-MCs with a moderate value of λ. Full article
(This article belongs to the Special Issue Intelligence Techniques Applied in Infrastructure, Engineering and Construction)
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14 pages, 6648 KiB  
Article
Study of Fatigue Performance of Ultra-Short Stud Connectors in Ultra-High Performance Concrete
by Ran An, You-Zhi Wang, Mei-Ling Zhuang, Zhen Yang, Chang-Jin Tian, Kai Qiu, Meng-Ying Cheng and Zhao-Yuan Lv
Buildings 2024, 14(4), 1179; https://doi.org/10.3390/buildings14041179 - 21 Apr 2024
Viewed by 448
Abstract
Steel–UHPC composite bridge decking made of ultra-high performance concrete (UHPC) has been progressively employed to reinforce historic steel bridges. The coordinated force and deformation between the steel deck and UHPC are therefore greatly influenced by the shear stud connectors at the shear interface. [...] Read more.
Steel–UHPC composite bridge decking made of ultra-high performance concrete (UHPC) has been progressively employed to reinforce historic steel bridges. The coordinated force and deformation between the steel deck and UHPC are therefore greatly influenced by the shear stud connectors at the shear interface. Four fatigue push-out specimens of ultra-short studs with an aspect ratio of 1.84 in UHPC were examined to investigate the fatigue properties of ultra-short studs with an aspect ratio below 2.0 utilized in UHPC reinforcing aged steel bridges. The test results indicated that three failure modes—fracture surface at stud shank, fracture surface at steel flange, and fracture surface at stud cap—were noted for ultra-short studs in UHPC under various load ranges. The fatigue life decreased from 1287.3 × 104 to 24.4 × 104 as the shear stress range of the stud increased from 88.2 MPa to 158.8 MPa. The UHPC can ensure that the failure mode of the specimens was stud shank failure. Based on the test and literature results, a fatigue strength design S–N curve for short studs in UHPC was proposed, and calculation models for stiffness degradation and plastic slip accumulation of short studs in UHPC were established. The employment of ultra-short studs in the field of UHPC reinforcing aging steel bridges can be supported by the research findings. Full article
(This article belongs to the Special Issue Intelligence Techniques Applied in Infrastructure, Engineering and Construction)
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