• CSCD核心中文核心科技核心
  • RCCSE(A+)公路运输高质量期刊T1
  • Ei CompendexScopusWJCI
  • EBSCOPж(AJ)JST
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隧道建设(中英文) ›› 2026, Vol. 46 ›› Issue (4): 804-816.DOI: 10.3973/j.issn.2096-4498.2026.04.013

• 规划与设计 • 上一篇    下一篇

基于LCA与遗传优化的公路隧道衬砌低碳维修加固设计方法

胡强1, 刘文星2, 3, 张安睿1, 4, 吴铭芳1, 郭春2, 3, *   

  1. (1. 贵州省交通规划勘察设计研究院股份有限公司, 贵州 贵阳 550000; 2. 西南交通大学土木工程学院,四川 成都 610031; 3. 西南交通大学 交通隧道工程教育部重点实验室, 四川 成都 610031; 4. 贵州省山区桥隧工程智能建造与运维全省重点实验室, 贵州 贵阳 550000)
  • 出版日期:2026-04-20 发布日期:2026-04-20
  • 作者简介:胡强(1993—),男,江西上饶人,2018年毕业于长安大学,桥梁与隧道工程专业,硕士,高级工程师,现从事隧道与地下空间设计、研究工作。E-mail: 654435715@qq.com。*通信作者: 郭春, E-mail: guochun@swjtu.edu.cn。

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

摘要: 为解决公路隧道衬砌维修加固工程中缺乏低碳设计指导的问题,建立基于生命周期评估(life cycle assessment,LCA)的模块化碳排放计算方法,结合数值模拟与遗传优化算法,提出兼顾安全性与低碳性的加固参数优化路径。首先,整合各规范数据明确衬砌维修加固方法与设计参数,基于全生命周期理论构建涵盖材料生产、运输及施工全过程的碳排放计算模型,量化各工序的基元碳排放。其次,通过数值模拟正交试验,揭示设计参数对安全系数与碳排放的敏感性规律: 粘钢带法中钢带厚度对碳排放与衬砌安全系数影响最显著; 套拱法中钢架间距对碳排放影响最显著,而喷射混凝土厚度对安全系数影响最显著。最后,结合BP神经网络与遗传算法,建立安全系数约束下的碳排放最小化模型。结果表明,衬砌安全系数与碳排放呈显著正相关且存在2阶段变化规律: 以粘钢带法为例,在安全系数处于[2.392, 2.504]区间时,安全系数每提高0.01,碳排放平均增加45.66 kgCO2eq; 当安全系数>2.504,安全系数每提高001,碳排放平均增加305.25 kgCO2eq。因此,在满足安全性的前提下,低碳设计应优先选择增加单位安全系数时碳排放增量较低的阶段。

关键词: 公路隧道, 隧道病害; 衬砌加固; 碳排放; 低碳加固; 生命周期评估

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