Modeling, Sensing, Diagnosis and Lifecycle Maintenance for Rail Transit Infrastructure

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Structures".

Deadline for manuscript submissions: closed (31 May 2026) | Viewed by 850

Editors

School of Mechanics and Transportation Engineering, Northwestern Polytechnical University, Xi'an 710129, China
Interests: railway; bridge; vibration; dynamics
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Guest Editor
State Key Laboratory of Safety and Resilience of Civil Engineering in Mountain Area, East China Jiaotong University, Nanchang 330013, China
Interests: railway; bridge; vibration; noise; dynamics
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Special Issue Information

Dear Colleagues,

Rail transit infrastructure, as the backbone of efficient and sustainable urban and intercity transportation, plays a crucial role in supporting economic development and improving people's travel experience. With the rapid expansion of rail networks worldwide and the increasing demands for operational safety, reliability, and sustainability, the industry is facing unprecedented challenges in ensuring the long-term performance of infrastructure such as tracks, bridges, and tunnels. Conventional approaches to dynamics analysis, defect detection, and maintenance management are gradually insufficient to address the complex and dynamic issues arising from aging assets, heavy traffic loads, and environmental uncertainties.

This Special Issue aims to showcase cutting-edge research and practical advancements in the interdisciplinary field of rail transit infrastructure, focusing on the integration of modeling, sensing, diagnosis, and lifecycle maintenance technologies. It seeks to bridge the gap between theoretical dynamics analysis and engineering applications, promote the innovation of intelligent sensing and diagnostic methods, and explore optimized lifecycle maintenance strategies that enhance infrastructure resilience and reduce lifecycle costs. By bringing together scholars, researchers, and practitioners from diverse backgrounds including rail engineering, dynamics modeling, intelligent sensing, signal processing, and maintenance management, this Special Issue will provide a platform for exchanging novel ideas, methodologies, and case studies.

We welcome high-quality original research articles and systematic literature reviews that address the following (but not limited to) topics:

  • Modeling for rail transit dynamics: Vehicle-track/bridge/subgrade/tunnel coupled dynamics modeling, multi-physics coupling analysis (e.g., mechanics-electronics-thermal), uncertainty quantification in dynamics models, and dynamics-based performance evaluation of infrastructure.
  • Intelligent sensing technologies: Advanced sensing systems, distributed sensing for large-scale infrastructure, wireless sensor networks, and data acquisition and transmission technologies under harsh rail environments.
  • Defect diagnosis and condition assessment: Signal processing and feature extraction for defect detection, machine learning and deep learning-based diagnostic algorithms, damage identification and localization, and condition grading methods for rail transit assets.
  • Lifecycle maintenance and management: Predictive maintenance based on condition monitoring data, reliability-centered maintenance strategies, lifecycle cost analysis and optimization, digital twins for maintenance decision-making, and resilient maintenance planning under extreme events.

We sincerely appreciate your interest in this Special Issue and look forward to receiving your valuable contributions that will advance the state-of-the-art in rail transit infrastructure engineering. We also encourage you to share this call with your colleagues and peers who may be interested in participating, to collectively promote the development of safer, more reliable, and sustainable rail transit systems.

You may choose our Joint Special Issue in Infrastructures.

Dr. Lifeng Xin
Prof. Dr. Lizhong Song
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized 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 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

  • rail transit infrastructure
  • dynamics modeling
  • intelligent sensing
  • defect diagnosis
  • lifecycle maintenance
  • condition monitoring
  • predictive maintenance

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Published Papers (1 paper)

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Research

16 pages, 13270 KB  
Article
Noise from Different Metro Train Types on Elevated Tracks: A Case Study Based on Field Measurements
by Lizhong Song, Zhichao Wang, Pengfei Zhang, Quanmin Liu and Bingyang Bai
Buildings 2026, 16(6), 1191; https://doi.org/10.3390/buildings16061191 - 18 Mar 2026
Viewed by 546
Abstract
To systematically investigate the influence of metro train types on the operational noise of elevated rail transit, this study conducted field measurements on elevated sections of the Wuhan Metro Yangluo Line, Wuhan Metro Line 2, and Guangzhou Metro Line 4, comparing the noise [...] Read more.
To systematically investigate the influence of metro train types on the operational noise of elevated rail transit, this study conducted field measurements on elevated sections of the Wuhan Metro Yangluo Line, Wuhan Metro Line 2, and Guangzhou Metro Line 4, comparing the noise characteristics of 4-car A-type, 6-car B-type, and 4-car L-type trains operating at 70 ± 2 km/h. Analysis of sound pressure levels and frequency spectra at multiple points revealed that wheel-rail noise peaks occurred at 630 Hz and 2500 Hz for A-type trains, around 800 Hz for B-type trains, and within 800–1250 Hz for L-type trains, while bridge structure-borne noise was consistently concentrated in the 63–100 Hz low-frequency range. Distinct emission patterns were observed: at on-girder points, noise levels were highest for A-type trains, followed by B-type and then L-type trains, a trend potentially linked to axle loads; conversely, at under-girder points, the order reversed with L-type trains producing the highest noise. At points 7.5 m and 25 m from the track centerline, A-type and B-type trains exhibited similar noise levels, whereas L-type trains were slightly quieter. Furthermore, all three train types showed a consistent noise attenuation rate of approximately 6 dB(A) per doubling of distance from the track centerline. The findings will serve as a reference and basis for rail transit noise prediction and control. Full article
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