Most tunnel engineering projects face significant challenges in accurately estimating construction duration, primarily due to the complex hydrogeological conditions and the involvement of multiple stakeholders. Addressing the limitation of traditional methods in considering the interactions among multiple risk factors, the Bayesian network is employed to analyze the interactions between various risk factors at the construction process level. Meanwhile, the Program Evaluation and Review Technique (PERT) has been improved to achieve the transmission of risk impacts from each construction process to the overall project duration. Thus, a probabilistic estimation method for tunnel construction duration is established. The proposed method is demonstrated through its application to a subsea tunnel project in China as a typical case study, yielding probability distributions and characteristic parameters for different duration values to provide a scientific basis for project schedule risk assessment. The findings indicate that, compared with traditional methods, the present approach can better reflect actual circumstances and maintain the reliability of prediction results even in extreme cases such as severe delays. Furthermore, the results reveal the uncertainty of duration distribution and its correlation with various risk factors, which strongly supports the dynamic management of tunnel construction schedule risk.
Song Hejie
,
Zhang Le
,
Liu Daoping
,
Huang Hongwei
. Probabilistic Estimation Method for Tunnel Construction Duration Based on Bayesian Network and PERT[J]. Chinese Journal of Underground Space and Engineering, 2026
, 22(4)
: 1420
-1427
.
DOI: 10.20174/j.JUSE.2026.04.30
[1] Einstein H H, Indermitte C, Sinfield J, et al. Decision aids for tunneling[J]. TransportationResearch Record, 1999, 1656(1): 6-13.
[2] Mahmoodzadeh A, Mohammadi M, Daraei A, et al. Updating ground conditions and time-cost scatter-gram intunnels during excavation[J]. Automation in Construction, 2019, 105: 102822.
[3] Špačková O, Šejnoha J, Straub D. Probabilistic assessment of tunnel construction performance based on data[J]. Tunnelling and Underground Space Technology, 2013, 37: 62-78.
[4] 颉芳弟. 基于贝叶斯网络方法的TBM施工项目进度风险研究[D].兰州:兰州交通大学, 2022.(Xie Fangdi. Study on schedule risk of TBM construction project based on Bayesian network method[D]. Lanzhou: Lanzhou Jiaotong University, 2022.(in Chinese))
[5] 商宝强.计划评审技术在海洋工程项目进度风险评估中的应用——以K平台项目为例[J].项目管理技术,2023,21(4):150-153.(Shang Baoqiang. Application of plan review technology in schedule risk assessment of offshore engineering projects——taking K platform project as an example [J]. Project Management Technology, 2023, 21(4): 150-153.(in Chinese))
[6] Dho H J,Khaled E. Fast and accurate risk evaluation for scheduling large-scale construction projects[J]. Journal of Computing in Civil Engineering, 2011, 25(5): 407-417.
[7] Aziz R F. RPERT: Repetitive-projects evaluation and review technique[J]. Alexandria Engineering Journal, 2014, 53(1): 81-93.
[8] 巴延廷.基于PERT的工程进度风险分析研究[D].大连:大连理工大学,2010.(Ba Yantin. The research on project risk analysis based on PERT [D].Dalian: Dalian University of Technology, 2010.(in Chinese))
[9] Mohammadi M, Spross J, Stille H. Probabilistic time estimation of tunneling projects: The Uri Headrace Tunnel[J]. Rock Mechanics and Rock Engineering, 2023, 56(1): 703-717.
[10] 肖明清,徐晨,谢壁婷,等.高速铁路钻爆法隧道分序支护设计技术研究[J].隧道建设(中英文),2023,43(3):369-382.(Xiao Mingqing, Xu Chen, Xie Biting, et al. Research on design technology of sequential supporting for high-speed railway tunnel constructed by drilling-and-blasting method[J]. Tunnel Construction, 2023, 43(3): 369-382.(in Chinese))
[11] 王燕,黄宏伟,李术才.海底隧道施工风险辨识及其控制[J].地下空间与工程学报,2007,3(增1):1261-1264.(Wang Yan, Huang Hongwei, Li Shucai. Risk identification and handling during construction of subsea tunnel[J]. Chinese Journal of Underground Space and Engineering, 2007, 3(Supp.1): 1261-1264.(in Chinese))
[12] 陈远,金蕊,查亚闯.基于贝叶斯网络的大型公共项目进度延误风险研究[J].郑州大学学报(工学版),2022,43(2):91-97.(Chen Yuan, Jin Rui, Zha Yachuang. Research on delay risk of large complex public projects based on Bayesian network[J]. Journal of Zhengzhou University (Engineering Science), 2022, 43(2): 91-97.(in Chinese))
[13] 于海莹,隗秀,石锐,等.地铁施工期坍塌风险预测和事故诊断耦合方法研究[J].地下空间与工程学报,2024,20(增2):940-948. (Yu Haiying, Kui Xiu, Shi Rui, et al. Research on the coupling method of collapse risk prediction and accident diagnosis during subway construction period [J]. Chinese Journal of Underground Space and Engineering, 2024, 20(Supp.2): 940-948. (in Chinese))
[14] 谢行皓,韩更赞.PERT计算机仿真的理论与实践[J].土木工程学报,1992(3):35-41.(Xie Xinghao, Han Gengzan.The theory and practice of computer simulation for PERT[J]. China Civil Engineering Journal, 1992(3):35-41.(in Chinese))
[15] 钟登,闫玉亮,张隽,等.耦合改进PERT和BBNs的堆石坝施工进度风险分析[J].水利学报,2017,48(1):52-60.(Zhong Denghua, Yan Yuliang, Zhang Jun, et al. Construction schedule risk analysis of rockfill dams based on coupling improved PERT and BBNs[J]. Journal of Hydraulic Engineering, 2017, 48(1): 52-60.(in Chinese))
[16] 方维.基于蒙特卡洛模拟的项目风险管理方法研究[J].计算机与现代化,2012(4):33-36.(Fang Wei. Project risk management methods based on monte carlo simulation[J]. Computer and Modernization, 2012(4): 33-36.(in Chinese))
[17] 中华人民共和国住房与城乡建设部,中华人民共和国国家质量监督检验检疫总局.城市轨道交通地下工程建设风险管理规范(GB50652-2011)[S].北京:中国建筑工业出版社,2011.(Ministry of Housing and Urban-rural Development of the People's Republic of China, General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China. Code for risk management of underground works in urban rail transit(GB50652-2011)[S]. Beijing: China Architecture and Building Press,2011.(in Chinese))
