Article(id=1273953263037735468, tenantId=1146029695717560320, journalId=1272209045839646724, issueId=1273953231114887613, articleNumber=null, orderNo=null, doi=10.20174/j.JUSE.2026.02.06, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1747843200000, receivedDateStr=2025-05-22, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1781663726815, onlineDateStr=2026-06-17, pubDate=1776614400000, pubDateStr=2026-04-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1781663726815, onlineIssueDateStr=2026-06-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1781663726815, creator=13701087609, updateTime=1781663726815, updator=13701087609, issue=Issue{id=1273953231114887613, tenantId=1146029695717560320, journalId=1272209045839646724, year='2026', volume='22', issue='2', pageStart='377', pageEnd='752', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1781663719203, creator=13701087609, updateTime=1781663760928, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1273953406235467954, tenantId=1146029695717560320, journalId=1272209045839646724, issueId=1273953231114887613, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1273953406235467955, tenantId=1146029695717560320, journalId=1272209045839646724, issueId=1273953231114887613, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=437, endPage=447, ext={EN=ArticleExt(id=1273953263473943086, articleId=1273953263037735468, tenantId=1146029695717560320, journalId=1272209045839646724, language=EN, title=Dynamic Inversion for the Mechanical Parameters of Tunnel Surrounding Rock Based on UBPSO Algorithm, columnId=null, journalTitle=Chinese Journal of Underground Space and Engineering, columnName=null, runingTitle=null, highlight=null, articleAbstract=

With the excavation of tunnels, the surrounding rock is disturbed and damaged, resulting in changes in its geotechnical parameters. To obtain dynamic variation laws of geotechnical parameters accurately, an inversion method for mechanical parameters of tunnel surrounding rock based on updated boundaries particle swarm optimization (UBPSO) algorithm is proposed. Due to the large fluctuation of optimization results with the particle swarm algorithm, an updated boundaries particle swarm algorithm is proposed. By updating the upper and lower limits of search boundaries dynamically, performing reversal and mutation operations on individual historical optimal values, and updating inertia weights adaptively, the updated boundaries particle swarm algorithm achieves high-precision and fast optimization. The stability test of the Ackley function indicates that compared to the particle swarm optimization algorithm, the updated boundaries particle swarm algorithm has the following advantages, fast optimization speed, high accuracy of results, small fluctuation of outcomes, and less sensitivity to getting stuck in local optima. Based on the updated boundaries particle swarm optimization algorithm, a reverse analysis model for mechanical parameters of tunnel surrounding rock using MATLAB-PYTHON-ABAQUS and on-site monitoring data is established. Taking the YK76+470 to YK76+502.5 section of the Tongluoshan tunnel as an example, the model was used to analyze the on-site monitoring data of the tunnel arch settlement. It was found that the elastic modulus of the colluvial soil layer decreased from 0.200 GPa to 0.106 GPa, the internal friction angle dropped from 14° to 12.072°, and the cohesion value fell from 22 kPa to 19.373 kPa.

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隧道开挖过程中，围岩受扰动而损伤，其岩土参数将发生变化。为准确掌握岩土参数动态变化规律，提出基于边界更新粒子群算法（UBPSO）的隧道围岩力学参数反演方法。针对粒子群算法寻优结果波动性大的问题，提出边界更新粒子群算法。通过动态更新搜索边界上下限、个体历史最优值进行交叉与变异操作和惯性权重自适应更新，实现边界更新粒子群算法高精度、快速寻优。Ackley函数稳定性测试实验可知，相对于传统粒子群算法，边界更新粒子群算法具有寻优速度快、结果精度高、结果波动性小和不易陷入局部最优值等优点。基于边界更新粒子群算法，建立MATLAB-PYTHON-ABAQUS和现场监测数据联合使用的隧道围岩力学参数反分析模型。以铜锣山隧道YK76+470 ~ YK76+502.5区段为例，通过该模型反分析隧道拱顶沉降现场监测数据可知，最终崩坡积土层弹性模量从0.200 GPa下降至0.106 GPa、内摩擦角从14°下降至12.072°、黏聚力从22 kPa下降至19.373 kPa。

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罗林（1985—），女，四川泸州人，博士，副教授，主要从事隧道、岩土和结构工程方面的研究。E-mail: 346978265@qq.com

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罗林（1985—），女，四川泸州人，博士，副教授，主要从事隧道、岩土和结构工程方面的研究。E-mail: 346978265@qq.com

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