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Digital twin technology in railway infrastructure
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Shubao Song, Jingyu Zhang
Railway Sciences | 2026, 5(4) : 505 - 523
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Railway Sciences | 2026, 5(4): 505-523
Digital twin technology in railway infrastructure
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Shubao Song, Jingyu Zhang
Affiliations
  • Postgraduate Department, China Academy of Railway Sciences Corporation Limited, Beijing, China
  • Railway Science and Technology Research and Development Center, China Academy of Railway Sciences Corporation Limited, Beijing, China
  • Shubao Song is working at and is pursuing a doctoral degree at China Academy of Railway Sciences. Her research focuses on digital and intelligent railway track engineering. She has participated in the design and research and development of the digital twin railway system for national major scientific and technological projects.

About Author:

Shubao Song is working at and is pursuing a doctoral degree at China Academy of Railway Sciences. Her research focuses on digital and intelligent railway track engineering. She has participated in the design and research and development of the digital twin railway system for national major scientific and technological projects.

doi: 10.1108/RS-02-2026-0013
Outline
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Purpose-

This review aims to provide insights for researchers and practitioners to utilize the full potential of digital twins (DT) in railway infrastructure, furthermore, promoting the future advances of DT technology in the field.

Design/methodology/approach-

This paper comprehensively reviews the latest progress in the application of digital twins in railway infrastructure (Digital Twin for Railway Infrastructure (DTRI)). It systematically summarizes the application scenarios and elaborates on the core components of DTRI.

Findings-

The core components of DTRI include virtual entity models, twin data, and virtual-physical connections. Emerging developments such as artificial intelligence (AI), data fusion, the Internet of Things (IoT) and advanced algorithms have been incorporated as the key technologies. The primary application scenarios focus on monitoring and maintenance, failure prediction and prevention and life cycle management.

Originality/value-

DT technology has emerged as an innovative framework in the railway infrastructure sector, offering unprecedented opportunities for real-time monitoring, predictive maintenance and optimization control. The paper analyzes current and future challenges alongside emerging development directions, highlighting the transformative potential of DT technology in promoting intelligent and efficient railway infrastructure operations.

Digital twin  /  Railway infrastructure  /  Predictive maintenance  /  IoT  /  Artificial intelligence  /  Cyber-physical systems
Shubao Song, Jingyu Zhang. Digital twin technology in railway infrastructure[J]. Railway Sciences, 2026 , 5 (4) : 505 -523 . DOI: 10.1108/RS-02-2026-0013
  • Special Research Project of China State Railway Group(PATI-STR-2025-IV-006)
Year 2026 volume 5 Issue 4
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Article Info
doi: 10.1108/RS-02-2026-0013
  • Online Date:2026-09-17
Article Data
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History
  • Revised:2026-04-07
  • Accepted:2026-04-30
Funding
Special Research Project of China State Railway Group(PATI-STR-2025-IV-006)
Affiliations
    Postgraduate Department, China Academy of Railway Sciences Corporation Limited, Beijing, China
    Railway Science and Technology Research and Development Center, China Academy of Railway Sciences Corporation Limited, Beijing, China

Corresponding:

Shubao Song can be contacted at:
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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