ISSN 2096-4498

   CN 44-1745/U

二维码

Tunnel Construction ›› 2026, Vol. 46 ›› Issue (4): 804-816.DOI: 10.3973/j.issn.2096-4498.2026.04.013

Previous Articles     Next Articles

Low-Carbon Design Method for Highway Tunnel Lining Maintenance and Reinforcement Based on Life Cycle Assessment and Genetic Algorithm Optimization

HU Qiang1, LIU Wenxing2, 3, ZHANG Anrui1, 4, WU Mingfang1, GUO Chun2, 3, *   

  1. (1. Guizhou Provincial Traffic Planning Survey & Design Research Institute Co., Ltd., Guiyang 550000, Guizhou, China; 2. School of Civil Engineering, Southwest Jiaotong University, Chengdu 610031, Sichuan, China; 3. Key Laboratory of Traffic Tunnel Engineering of the Ministry of Education, Southwest Jiaotong University, Chengdu 610031, Sichuan, China; 4. Guizhou Provincial Key Laboratory of Intelligent Construction and Operation & Maintenance for Bridge and Tunnel Engineering in Mountainous Areas, Guiyang 550000, Guizhou, China)
  • Online:2026-04-20 Published:2026-04-20

Abstract: Highway tunnel lining maintenance and reinforcement projects currently lack low-carbon design guidance. To address this gap, a modular carbon emission calculation method based on life cycle assessment is established. By integrating numerical simulation with genetic algorithm (GA) optimization, an optimization approach for reinforcement parameters that balances structural safety and low-carbon performance is proposed. First, data from relevant codes are consolidated to identify the maintenance and reinforcement methods for tunnel linings and their associated design parameters. Based on life cycle theory, a carbon emission calculation model encompassing the entire process of material production, transportation, and construction is developed to quantify the carbon emissions at each stage. Second, orthogonal experiments conducted through numerical simulation reveal the sensitivity of design parameters to safety factors and carbon emissions: in the steel strip bonding method, steel strip thickness exerts the greatest influence on both carbon emissions and the lining safety factor; in the collar arch method, steel frame spacing has the greatest influence on carbon emissions, whereas shotcrete thickness has the greatest influence on the safety factor. Finally, by coupling a back-propagation neural network with the GA, a model for minimizing carbon emissions subject to safety factor constraints is established. The results indicate a notable positive correlation between the lining safety factor and carbon emissions, characterized by a two-stage variation pattern. Taking the steel strip bonding method as an example, when the safety factor falls within the range of [2.392, 2.504], each 0.01 increase in the safety factor corresponds to an average increase of 45.66 kgCO2eq in carbon emissions; when the safety factor exceeds 2.504, each 0.01 increase results in an average increase of 305.25 kgCO2eq. Therefore, provided that safety requirements are met, low-carbon design should prioritize the stage associated with a lower carbon emission increment per unit increase in the safety factor.

Key words: highway tunnel, tunnel defects, lining reinforcement, carbon emissions, low-carbon reinforcement, life cycle assessment