滑坡易发环境下公路隧道洞口施工安全系统韧性评价

王德凯; 郝伟

doi:10.3973/j.issn.2096-4498.2024.07.005

隧道建设 >

2024 , Vol. 44 >Issue 7: 1377 - 1384

DOI: https://doi.org/10.3973/j.issn.2096-4498.2024.07.005

研究与探索

滑坡易发环境下公路隧道洞口施工安全系统韧性评价

王德凯 ,
郝伟

展开

（兰州交通大学土木工程学院，甘肃兰州 730070）

王德凯（1997—），男，甘肃白银人，兰州交通大学土木工程建造与管理专业在读硕士，研究方向为桥梁隧道灾害风险评估。E-mail: 1805175044@qq.com。

网络出版日期: 2024-08-05

收起

Evaluation of Safety System Resilience for Highway Tunnel Portal Construction in Landslide-Prone Environment

WANG Dekai ,
HAO Wei

Expand

(School of Civil Engineering, Lanzhou Jiaotong University, Lanzhou 730070, Gansu, China)

Online published: 2024-08-05

Fold

摘要

为合理评价公路隧道在滑坡易发区进洞阶段施工安全系统的韧性，首先，构建基于 D-S 证据理论的贝叶斯网络韧性评价模型： 1）依据PSR模型从压力、状态、响应3方面建立公路隧道洞口施工安全系统的16个韧性评价指标； 2）通过各指标间的二元关系绘制贝叶斯网络； 3）使用 D-S 证据理论计算BN节点条件概率并利用 Netica 软件对韧性水平进行分析计算。然后，以甘肃省卓合高速公路白崖山隧道洞口施工为例，运用该模型进行实例分析。计算结果表明：在滑坡灾害影响下，白崖山隧道洞口施工安全系统韧性水平为良好，评价结果与现场施工监测数据相符，有效验证了该指标体系的合理性和韧性评价模型的适用性。

关键词： 公路隧道; 韧性评价; 贝叶斯网络; 滑坡灾害; D-S证据理论; PSR模型

本文引用格式

王德凯 , 郝伟 . 滑坡易发环境下公路隧道洞口施工安全系统韧性评价[J]. 隧道建设, 2024 , 44(7) : 1377 -1384 . DOI: 10.3973/j.issn.2096-4498.2024.07.005

Abstract

To effectively assess the resilience of highway tunnel construction safety systems during the tunnel entry stage in landslideprone areas, a Bayesian network resilience evaluation model is developed using Dempster-Shafer(D-S) evidence theory. This model establishes 16 resilience evaluation indices for the construction safety system of highway tunnel openings from the perspectives of pressure, state, and response according to the pressure-state-response model. Subsequently, a Bayesian network is constructed based on the binary relationships among these indices. Finally, D-S evidence theory is applied to compute conditional probabilities of BN node, and the resilience level is analyzed using Netica software. The model was implemented for the portal construction of the Baiyashan tunnel on the Zhuoni-Hezuo expressway in Gansu province, China. The calculation results indicate that the resilience level of the construction safety system at the tunnel entrance is robust under the influence of landslide disasters. These findings agree well with the monitoring results, thus validating the feasibility and applicability of the proposed evaluation model.

Key words： highway tunnel; resilience evaluation; Bayesian network; landslide disaster; DempsterShafer evidence theory; pressurestateresponse model

Options

文章导航

〈

〉

模态框（Modal）标题

摘要

本文引用格式

Abstract