华南理工大学学报(自然科学版) ›› 2025, Vol. 53 ›› Issue (6): 34-43.doi: 10.12141/j.issn.1000-565X.240176

• 土木建筑工程 • 上一篇    下一篇

考虑加固时间区间的在役混凝土桥梁运维策略分析

王晓明1(), 李鹏飞2, 吴润涵1, 杨文杰1, 李晨曦1   

  1. 1.长安大学 公路学院,陕西 西安 710064
    2.浙江数智交院科技股份有限公司,浙江 杭州 310030
  • 收稿日期:2024-04-12 出版日期:2025-06-10 发布日期:2024-12-06
  • 作者简介:王晓明(1983—),男,博士,教授,主要从事大跨缆索体系分析与优化及长寿命桥梁建养即时决策研究。E-mail: wxm512061228@gmail.com
  • 基金资助:
    国家自然科学基金项目(52178104);长安大学中央高校基本科研业务费专项资金资助项目(300102214901)

Analysis of Operation and Maintenance Strategy of Existing Concrete Bridge Considering Reinforcement Time Interval

WANG Xiaoming1(), LI Pengfei2, WU Runhan1, YANG Wenjie1, LI Chenxi1   

  1. 1.School of Highway,Chang’an University,Xi’an 710064,Shaanxi,China
    2.Zhejiang Institute of Communications Co. ,Ltd. ,Hangzhou 310030,Zhejiang,China
  • Received:2024-04-12 Online:2025-06-10 Published:2024-12-06
  • Supported by:
    the National Nature Science Foundation of China(52178104)

摘要:

针对在役桥梁维修加固策略在制定和实施过程中存在的主观不确定性问题,提出一种考虑加固时间区间的桥梁运维决策框架。该框架首先基于区间数学的概念,引入区间数量化不能用概率描述的主观不确定性;其次利用代理模型高效率高精度映射的特点,基于代理模型实现概率-区间混合不确定性下最不利可靠度指标的直接映射;最后通过多目标优化算法NSGA-Ⅱ对该框架进行高效驱动。为了验证该框架在工程问题上的适用性,以典型装配式简支T梁桥为例,基于WIM系统实测数据建立了车辆荷载效应时变模型,之后引入抗力退化时变模型,对T梁桥的运维策略进行了优化,并制定了典型T梁桥的运维决策库。结果表明:时间区间较小的策略对应的全生命周期成本(LCC)较小,容许的主观不确定性也较小;时间区间较大的策略虽LCC较大,但为施工、决策等留了更充足的空间;对于跨径20~40 m的简支T梁桥,均可通过不同的加固策略使其在LCC最小的情况下,满足服役期的可靠度指标要求,表明该框架具有良好的适用性,可为在役桥梁维修加固策略的制定提供方法依据。

关键词: 桥梁运维策略, 主观不确定性, 时变可靠度, 全生命周期成本, 车辆荷载效应

Abstract:

To address the issue of subjective uncertainty in the formulation and implementation of maintenance and strengthening strategies for existing bridges, this study proposed a bridge operation and maintenance decision-making framework that incorporates reinforcement time intervals. Firstly, based on the concept of interval mathematics, interval numbers were introduced to quantify subjective uncertainties that cannot be described using probability theory. Secondly, by leveraging the high efficiency and accuracy of surrogate models, the framework enables the direct mapping of the worst-case reliability index under mixed probabilistic and interval uncertainties. Finally, the multi-objective optimization algorithm NSGA-‍ Ⅱ was employed to efficiently drive the framework, ensuring optimized decision-making outcomes. To verify the applicability of the proposed framework in practical engineering scenarios, a typical prefabricated simply supported T-beam bridge was selected as a case study. Based on field data obtained from a Weigh-In-Motion (WIM) system, a probabilistic model of vehicle load effects was established. A time-dependent resistance degradation model was then introduced to optimize the operation and maintenance strategy for the T-beam bridge, culminating in the development of a decision-making library for its maintenance and reinforcement. The results indicate that strategies with smaller time intervals correspond to smaller Life Cycle Cost (LCC) and lower permissible subjective uncertainty. Conversely, strategies with longer time intervals, while resulting in higher LCC, offer greater flexibility for construction and decision-making processes. For simply supported T-beam bridges with spans ranging from 20 to 40 meters, it is possible to meet the required reliability index over the service life while minimizing LCC through appropriate reinforcement strategies. These findings demonstrate the strong applicability of the proposed framework and suggest it can serve as a methodological foundation for formulating maintenance and reinforcement strategies for existing bridges.

Key words: bridge operation and maintenance strategy, subjective uncertainties,time-dependent reliability, life cycle cost, vehicle load effect

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