Digital twins for managing railway bridge maintenance, resilience, and climate change adaptation

Sakdirat Kaewunruen*, Mohannad AbdelHadi, Manwika Kongpuang, Withit Pansuk, Alex Remennikov

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Innovative digital twins (DTs) that allow engineers to visualise, share information, and monitor the condition during operation is necessary to optimise railway construction and maintenance. Building Information Modelling (BIM) is an approach for creating and managing an inventive 3D model simulating digital information that is useful to project management, monitoring and operation of a specific asset during the whole life cycle assessment (LCA). BIM application can help to provide an efficient cost management and time schedule and reduce the project delivery time throughout the whole life cycle of the project. In this study, an innovative DT has been developed using BIM integration through a life cycle analysis. Minnamurra Railway Bridge (MRB), Australia, has been chosen as a real-world use case to demonstrate the extended application of BIM (i.e., the DT) to enhance the operation, maintenance and asset management to improve the sustainability and resilience of the railway bridge. Moreover, the DT has been exploited to determine GHG emissions and cost consumption through the integration of BIM. This study demonstrates the feasibility of DT technology for railway maintenance and resilience optimisation. It also generates a virtual collaboration for co-simulations and co-creation of values across stakeholders participating in construction, operation and maintenance, and enhancing a reduction in costs and GHG emission.
Original languageEnglish
Article number252
Number of pages22
JournalSensors (Switzerland)
Volume23
Issue number1
DOIs
Publication statusPublished - 26 Dec 2022

Keywords

  • digital twin
  • railway maintenance
  • asset management
  • sustainability
  • BIM
  • life cycle
  • circular economy
  • materials stock flow
  • resilience
  • climate change adaptation

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