Utilizing Advanced Modelling for Fire Damage Assessment of Reinforced Concrete Tunnel Linings

Abstract

Fire hazards can cause severe and irrecoverable damage to reinforced concrete (RC) tunnel linings. Historically, major fire events have led to months of downtime and millions of dollars of losses owing to repair costs and affected operations. The potential threat to the serviceability of transportation networks emphasizes the need to establish a standardized and effective post-fire damage assessment method to guide repairs and restore functionality. This paper proposes a fire damage assessment framework for RC tunnel linings that integrates advanced modeling with visual inspections, non-destructive testing and material sampling. The framework quantifies fire damage to RC tunnel linings in terms of surface discoloration, crack width, concrete spalling, sectional temperatures, strength loss of materials and residual displacement. A damage classification system is proposed based on a collection of international guidelines and feedback from industry experts to map damage metrics and repair strategies. A case study, using data from recent experiments, is conducted to demonstrate the applicability of the proposed framework and the benefits of the information obtained from numerical modeling. This framework can also be integrated with risk-assessment methods to optimize the fire design of tunnels with associated active and/or passive fire protection.

Keywords:

• tunnel lining
• fire hazard
• damage assessment framework
• damage classification
• advanced modeling

Acknowledgements

The authors gratefully acknowledge the Structural Engineering and Earthquake Simulation Laboratory (SEESL) at the University at Buffalo for their generous support. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the CAIT Region 2 UTC Consortium. The authors sincerely appreciate the valuable feedback received via questionnaire from our private industry and government colleagues. Their time, opinions and comments are greatly appreciated.

Disclosure Statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the CAIT Region 2 UTC Consortium and the Institute of Bridge Engineering (IBE) at the University at Buffalo.