Water Inrush Risk Prediction of Karst Tunnel Based on IAHP-Fuzzy Method
-
摘要: 突水突泥是岩溶隧道施工阶段的主要工程灾害之一,有必要对其潜在风险等级进行预测。以宜万铁路野三关隧道工程为背景,采用文献调研法,将影响隧道突水风险的因素归结为工程地质条件、水文地质条件和岩体质量条件,并建立了对应的评价指标体系,通过形成各层次因素的区间判断矩阵确定指标权重,运用IAHP-Fuzzy法实现了岩溶隧道突水风险分级。综合3个一级指标和11个二级指标形成了隧道突水突泥的层次分析模型和风险分级体系。通过区间层次分析法确定了指标权重,计算结果显示,水压力特征在各指标中占比最高,高水压是造成野三关隧道突水的最直接诱因。通过验算,水压力为0.1 MPa时隧道突水风险为弱风险,建议采取预注浆加固等主动防护措施降低水压力,该验算进一步证明了模型的可行性。Abstract: Water and mud inrush is one of the main engineering disasters in the construction stage of karst tunnel, so it is necessary to predict its potential risk level. Taking Yesanguan tunnel of Yiwan railway as the engineering background, the factors affecting the water inrush risk of the tunnel are summed up as engineering geological conditions, hydrogeological conditions and rock mass quality conditions by the literature survey method, and the corresponding evaluation index system is established. The interval judgment matrix of factors at each level is formed to determine the index weight, and the interval analytic hierarchy process (IAHP)-Fuzzy method is used to realize the classification of water inrush risk in karst tunnels. The analytic hierarchy process model and risk classification system of water and mud inrush in tunnels are formed by combining 3 first-level indexes and 11 second-level indexes. The index weights are determined by IAHP. The calculation results show that water pressure characteristics account for the highest proportion in all indexes, and high water pressure is the most direct cause of water inrush in Yesanguan tunnel. Through the verification calculation, the risk of water inrush in the tunnel is weak when the water pressure is 0.1 MPa, which effectively reduces the risk of water inrush. It is suggested to take active protective measures such as pre-grouting reinforcement to reduce the water pressure and guide the actual construction. The verification further proves the feasibility of the model.
-
表 1 突水突泥风险分级
Table 1. Risk classification of water inrush and mud inrush
Level Ⅰ: no risk Level Ⅱ: weak risk Level Ⅲ: medium risk Level Ⅳ: high risk The tunnel is
in an ideal
safe conditionDuring the construction process, pay
attention to control the excavation
disturbance and support, so as not
to cause water inrush accidentsThe gradual destruction of the
water-resistant rock mass may
induce the accident of water
inrush and mud inrushWater-resistant rock mass is
directly damaged, resulting
in major water and
mud inrush accidents表 2 突水综合评价指标体系及界限分布
Table 2. Comprehensive evaluation index system and boundary distribution of water inrush
Evaluation
indexRisk level Ⅰ Ⅱ Ⅲ Ⅳ S1 Noncatastrophic (0) Weak catastrophic (0.25) Medium catastrophic (0.50) High catastrophic
(0.75)S2 <1 (0.143) 3 (0.429) 5.5 (0.786) >7 (1.000) S3 Regardless of
direction (0.25)The strike is parallel to
the tunnel axis (0.50)Strike perpendicular to the
axis of the tunnel, tunneling
along the dip (0.75)Strike perpendicular to the
axis of the tunnel, tunneling
against the dip (1.00)S4 0 (0) 0.1 MPa (0.167) 0.3 MPa (0.500) >0.6 MPa (1.000) S5 Nonnegative
terrain (0)Small negative
terrain (0.25)Medium negative
terrain (0.50)Large negative
terrain (0.75)S6 Micro hydraulic
conductivity (0)Weak hydraulic
conductivity (0.25)Medium hydraulic
conductivity (0.50)Strong hydraulic
conductivity (0.75)S7 >90% (0.90) 75% (0.75) 50% (0.50) <25% (0.25) S8 <1 (0.25) 2 (0.50) 3 (0.75) >4 (1.00) S9 1 (0) 1.1 (0.2) 1.4 (0.4) >1.6 (0.6) S10 >250 MPa (1.0) 100 MPa (0.4) 50 MPa (0.2) 0 (0) S11 <0.50 L/(min·m) (0.04) 2.25 L/(min·m) (0.18) 7.50 L/(min·m) (0.60) >12.50 L/(min·m) (1.00) 表 3 一级指标判断矩阵
Table 3. Judgment matrix of first-level index
Standard Relative importance degree F1 F2 F3 F1 [1.00, 1.00] [0.50, 0.75] [0.75, 1.00] F2 [1.33, 2.00] [1.00, 1.00] [1.00, 1.25] F3 [1.00, 1.33] [0.80, 1.00] [1.00, 1.00] 表 4 一级指标权重
Table 4. Weight of first-level index
Standard m(Ai) ri F1 0.2660 0.0162 F2 0.4016 0.0225 F3 0.3314 0.0104 Consistency requirement k=0.9499<1, β=1.0482. Meet consistency requirements. 表 5 综合指标权重
Table 5. Weight of comprehensive index
Primary index Weight of primary index Secondary index Weight of secondary index Comprehensive weight F1 0.2660 S1 0.8584 0.2283 S2 0.0706 0.0188 S3 0.0706 0.0188 F2 0.4016 S4 0.6415 0.2576 S5 0.1822 0.0731 S6 0.1822 0.0731 F3 0.3314 S7 0.3256 0.1080 S8 0.3256 0.1080 S9 0.2029 0.0672 S10 0.0957 0.0317 S11 0.0502 0.0166 表 6 各指标的实际值和归一化值
Table 6. Actual and normalized values of each evaluation index
Evaluation
indexValue Normalized
valueEvaluation
indexValue Normalized
valueS1 Strong–medium 0.625 S7 70% 0.70 S2 7 1.00 S8 1 0.25 S3 Tunneling against the dip 0.75 S9 1.4 0.40 S4 0.3–0.9 0.75 S10 90–110 0.44 S5 Large–medium 0.625 S11 Seepage–a drip or linear flow
or gushing of water0.80 S6 Strong–medium 0.625 表 7 隧址区突水风险验算
Table 7. Water inrush risk checking in tunnel address area
Water pressure/MPa Normalized water pressure B Risk level 0.30 0.5 [0.1101, 0.1160, 0.5607, 0.2144] Ⅲ 0.36 0.6 [0.1101, 0.1160, 0.5092, 0.2659] Ⅲ 0.42 0.7 [0.1101, 0.1160, 0.4577, 0.3174] Ⅲ 0.48 0.8 [0.1101, 0.1160, 0.4062, 0.3689] Ⅲ 0.54 0.9 [0.1101, 0.1160, 0.3547, 0.4204] Ⅳ 0.60 1.0 [0.1101, 0.1160, 0.3031, 0.4720] Ⅳ -
[1] 李新平, 瞿江文, 唐结齐, 等. 基于组合赋权法-TOPSIS法的北天山隧道突水风险评价研究 [J]. 水利水电技术, 2019, 50(9): 114–119. doi: 10.13928/j.cnki.wrahe.2019.09.015LI X P, QU J W, TANG J Q, et al. Study on combination weighting method-TOPSIS method-based risk assessment of water inrush in construction of North Tianshan Mountain Tunnel [J]. Water Resources and Hydropower Engineering, 2019, 50(9): 114–119. doi: 10.13928/j.cnki.wrahe.2019.09.015 [2] 洪开荣. 近2年我国隧道及地下工程发展与思考(2017−2018年) [J]. 隧道建设, 2019, 39(5): 710–723. doi: 10.3973/j.issn.2096-4498.2019.05.002HONG K R. Development and thinking of tunnels and underground engineering in China in recent 2 years (from 2017 to 2018) [J]. Tunnel Construction, 2019, 39(5): 710–723. doi: 10.3973/j.issn.2096-4498.2019.05.002 [3] LIN C J, ZHANG M, ZHOU Z Q, et al. A new quantitative method for risk assessment of water inrush in karst tunnels based on variable weight function and improved cloud model [J]. Tunnelling and Underground Space Technology, 2020, 95: 103136. doi: 10.1016/j.tust.2019.103136 [4] SHI S S, XIE X K, BU L, et al. Hazard-based evaluation model of water inrush disaster sources in karst tunnels and its engineering application [J]. Environmental Earth Sciences, 2018, 77(4): 141. doi: 10.1007/s12665-018-7318-5 [5] LI S C, ZHOU Z Q, LI L P, et al. Risk assessment of water inrush in karst tunnels based on attribute synthetic evaluation system [J]. Tunnelling and Underground Space Technology, 2013, 38: 50–58. doi: 10.1016/j.tust.2013.05.001 [6] HU Y B, LI W P, WANG Q Q, et al. Evaluation of water inrush risk from coal seam floors with an AHP-EWM algorithm and GIS [J]. Environmental Earth Sciences, 2019, 78(10): 290. doi: 10.1007/s12665-019-8301-5 [7] WU J S, XU S D, ZHOU R, et al. Scenario analysis of mine water inrush hazard using Bayesian networks [J]. Safety Science, 2016, 89: 231–239. doi: 10.1016/j.ssci.2016.06.013 [8] 游波, 施式亮, 刘何清, 等. 基于信息熵和集对分析理论的公路隧道水害倾向性判定 [J]. 公路交通科技, 2019, 36(6): 73–78. doi: 10.3969/j.issn.1002-0268.2019.06.010YOU B, SHI S L, LIU H Q, et al. Determination of flood tendency of highway tunnel based on entropy and set pair analysis theory [J]. Journal of Highway and Transportation Research and Development, 2019, 36(6): 73–78. doi: 10.3969/j.issn.1002-0268.2019.06.010 [9] ZHANG K, ZHENG W B, XU C, et al. An improved extension system for assessing risk of water inrush in tunnels in carbonate karst terrain [J]. KSCE Journal of Civil Engineering, 2019, 23(5): 2049–2064. doi: 10.1007/s12205-019-0756-0 [10] MENG Z P, LI G Q, XIE X T. A geological assessment method of floor water inrush risk and its application [J]. Engineering Geology, 2012, 143-144: 51–60. doi: 10.1016/j.enggeo.2012.06.004 [11] JIA X L, DAI Q M, YANG H Z. Susceptibility zoning of karst geological hazards using machine learning and cloud model [J]. Cluster Computing, 2019, 22(S4): 8051–8058. doi: 10.1007/s10586-017-1590-0 [12] 李术才, 周宗青, 李利平, 等. 岩溶隧道突水风险评价理论与方法及工程应用 [J]. 岩石力学与工程学报, 2013, 32(9): 1858–1867. doi: 10.3969/j.issn.1000-6915.2013.09.018LI S C, ZHOU Z Q, LI L P, et al. Risk evaluation theory and method of water inrush in karst tunnels and its applications [J]. Chinese Journal of Rock Mechanics and Engineering, 2013, 32(9): 1858–1867. doi: 10.3969/j.issn.1000-6915.2013.09.018 [13] 匡星, 白明洲, 王成亮, 等. 基于模糊评价方法的隧道岩溶突水地质灾害综合预警方法 [J]. 公路交通科技, 2010, 27(11): 100–103. doi: 10.3969/j.issn.1002-0268.2010.11.018KUANG X, BAI M Z, WANG C L, et al. Research of comprehensive warning of water inrush hazards in karst tunnel based on fuzzy evaluation method [J]. Journal of Highway and Transportation Research and Development, 2010, 27(11): 100–103. doi: 10.3969/j.issn.1002-0268.2010.11.018 [14] WANG Y, YANG W F, LI M, et al. Risk assessment of floor water inrush in coal mines based on secondary fuzzy comprehensive evaluation [J]. International Journal of Rock Mechanics and Mining Sciences, 2012, 52: 50–55. doi: 10.1016/j.ijrmms.2012.03.006 [15] 卢庆钊. 基于AHP-Fuzzy的隧道穿富水断层破碎带突水涌泥评估 [J]. 地下空间与工程学报, 2021, 17(Suppl 1): 439–448, 462.LU Q Z. Risk Assessment of water and mud inrush in tunnel crossing water-rich fault fracture zone based on AHP-Fuzzy [J]. Chinese Journal of Underground Space and Engineering, 2021, 17(Suppl 1): 439–448, 462. [16] 王宇, 李建旺, 周喻. 隧道突水涌泥AHP-Fuzzy风险评价 [J]. 地下空间与工程学报, 2021, 17(4): 1257–1263.WANG Y, LI J W, ZHOU Y. Risk assessment of tunnel water inrush and burst mud by AHP-Fuzzy [J]. Chinese Journal of Underground Space and Engineering, 2021, 17(4): 1257–1263. [17] 贺华刚. 深埋特长隧道的突涌水危险性评价研究 [J]. 中国岩溶, 2020, 39(3): 384–390.HE H G. Assessment of water inrush risk in deep buried long tunnels [J]. Carsologica Sinica, 2020, 39(3): 384–390. [18] 石州, 罗彦斌, 陈建勋, 等. 木寨岭公路隧道大变形综合评价预测 [J]. 公路交通科技, 2020, 37(8): 90–98, 158. doi: 10.3969/j.issn.1002-0268.2020.08.012SHI Z, LUO Y B, CHEN J X, et al. Comprehensive evaluation and prediction of large deformation of Muzhailing highway tunnel [J]. Journal of Highway and Transportation Research and Development, 2020, 37(8): 90–98, 158. doi: 10.3969/j.issn.1002-0268.2020.08.012 [19] LIN S S, SHEN S L, ZHOU A N, et al. Novel model for risk identification during karst excavation [J]. Reliability Engineering & System Safety, 2021, 209: 107435. doi: 10.1016/J.RESS.2021.107435 [20] 黄鑫, 林鹏, 许振浩, 等. 岩溶隧道突水突泥防突评判方法及其工程应用 [J]. 中南大学学报(自然科学版), 2018, 49(10): 2533–2544. doi: 10.11817/j.issn.1672?7207.2018.10.021HUANG X, LIN P, XU Z H, et al. Prevention structure assessment method against water and mud inrush in karst tunnels and its application [J]. Journal of Central South University (Science and Technology), 2018, 49(10): 2533–2544. doi: 10.11817/j.issn.1672?7207.2018.10.021 [21] 李术才, 许振浩, 黄鑫, 等. 隧道突水突泥致灾构造分类、地质判识、孕灾模式与典型案例分析 [J]. 岩石力学与工程学报, 2018, 37(5): 1041–1069. doi: 10.13722/j.cnki.jrme.2017.1332LI S C, XU Z H, HUANG X, et al. Classification, geological identification, hazard mode and typical case studies of hazard-causing structures for water and mud inrush in tunnels [J]. Chinese Journal of Rock Mechanics and Engineering, 2018, 37(5): 1041–1069. doi: 10.13722/j.cnki.jrme.2017.1332 [22] 李利平, 李术才, 陈军, 等. 基于岩溶突涌水风险评价的隧道施工许可机制及其应用研究 [J]. 岩石力学与工程学报, 2011, 30(7): 1345–1355.LI L P, LI S C, CHEN J, et al. Construction license mechanism and its application based on karst water inrush risk evaluation [J]. Chinese Journal of Rock Mechanics and Engineering, 2011, 30(7): 1345–1355. [23] WANG X T, LI S C, XU Z H, et al. An interval risk assessment method and management of water inflow and inrush in course of karst tunnel excavation [J]. Tunnelling and Underground Space Technology, 2019, 92: 103033. doi: 10.1016/j.tust.2019.103033 [24] 许振浩, 李术才, 李利平, 等. 基于层次分析法的岩溶隧道突水突泥风险评估 [J]. 岩土力学, 2011, 32(6): 1757–1766. doi: 10.3969/j.issn.1000-7598.2011.06.027XU Z H, LI S C, LI L P, et al. Risk assessment of water or mud inrush of karst tunnels based on analytic hierarchy process [J]. Rock and Soil Mechanics, 2011, 32(6): 1757–1766. doi: 10.3969/j.issn.1000-7598.2011.06.027 [25] 陈卫忠, 田云, 王学海, 等. 基于修正值的软岩隧道挤压变形预测 [J]. 岩土力学, 2019, 40(8): 3125–3134.CHEN W Z, TIAN Y, WANG X H, et al. Squeezing prediction of tunnel in soft rocks based on modified [J]. Rock and Soil Mechanics, 2019, 40(8): 3125–3134. [26] PRAMANIK R, BAIDYA D K, DHANG N. Implementation of fuzzy reliability analysis for elastic settlement of strip footing on sand considering spatial variability [J]. International Journal of Geomechanics, 2019, 19(12): 04019126. doi: 10.1061/(ASCE)GM.1943-5622.0001514 [27] HE S Q, SONG D Z, MITRI H, et al. Integrated rockburst early warning model based on fuzzy comprehensive evaluation method [J]. International Journal of Rock Mechanics and Mining Sciences, 2021, 142: 104767. doi: 10.1016/j.ijrmms.2021.104767 [28] 张梅, 张民庆, 孙国庆. 宜万铁路野三关隧道高压富水充填溶腔溃口处理技术 [J]. 铁道工程学报, 2010, 27(3): 81–86. doi: 10.3969/j.issn.1006-2106.2010.03.018ZHANG M, ZHANG M Q, SUN G Q. Technology for treating burst port of filling solution cavity with high-pressure and rich water of Yesanguan tunnel on Yichang-Wanzhou railway [J]. Journal of Railway Engineering Society, 2010, 27(3): 81–86. doi: 10.3969/j.issn.1006-2106.2010.03.018