大连地铁分岔隧道施工风险评估
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摘要
在建的大连地铁1号线大连海事大学至高新园区区间隧道渡线段工程是大连地铁1号线的重难点控制性工程之一。本工程分岔隧道由大跨度结构经非对称小净距结构过渡到分离式结构,断面形式变化复杂,施工工序转换大,施工过程中开挖与支护相互影响,围岩应力多次重分布,支护与衬砌结构上荷载转换复杂；另外,施工过程中隧道变形控制难度大,稍有不慎,就会造成塌方。不管是设计还是施工,分岔隧道结构相对来说是十分复杂的。因此,对大连地铁进行施工阶段风险评估具有重要的理论意义和工程实用价值。
主要研究内容包括：
(1)分岔隧道施工力学分析
基于地层—结构模型,采用数值模拟分析方法,建立分岔隧道的6个特征断面数值模型,模拟隧道实际施工方法,分析分岔隧道的受力变形特征。
(2)分岔隧道施工风险评估
总结归纳分岔隧道施工风险的主要影响因素,建立隧道施工风险因素的层次结构模型,采用层次分析法进行施工风险因素的敏感性分析及隧道安全状况内在关系研究。采用模糊回归和BP人工神经网络等数学方法,建立分岔隧道施工风险预测模型。并对大跨度、高水位、小净距等特征断面进行风险评估,基于评估结果进行风险控制管理。
(3)分岔隧道施工风险管理
在大连地铁隧道建设过程中,将风险控制理论与大连地铁隧道工程充分结合,在隧道施工中不断调整、完善、提高,最终形成一套有针对性的隧道工程建设的风险控制管理措施制度。通过建立以超前地质预报、风险评估和监控量测为核心的“三位一体”的动态信息管理系统,可以全方位立体地将隧道开挖前、开挖中和开挖后的安全状态全部以数据形式显示出来,为工程施工提出技术参考,对施工技术负责人做出施工决策有重大的帮助。
通过上述研究,得到以下结果：
(1)分岔隧道施工的重点是施工工序的控制,通过合理安排双洞的开挖、支护的间隔和顺序,可有效地控制两隧道之间由于净距较小引起的围岩变形,从而保证隧道结构的安全。
(2)确定了大连地铁隧道施工风险评估指标为围岩变形、地表沉降、结构受力、塑性区范围、涌水以及塌方。然后采用模糊回归和人工神经网络等数学方法,建立了分岔隧道施工风险预测模型。对大跨、小净距等特征断面进行了风险预测,基于预测结果提出了风险控制管理。
(3)地铁分岔隧道施工过程数值模拟及隧道安全状况内在关系研究的结论与工程原位的实测数据拟合度较高,隧道施工风险评估及隧道施工风险管理等研究结论较为全面地控制了地铁分岔隧道施工的风险,可用于指导施工。同时现场实测值较好地弥补数值分析的不足,检验并深化了分岔隧道施工风险评估理论系统,为后续施工方法选择及改进工艺提供实测数据参考。
The being built new Line1of Dalian Metro between Maritime University and High-tech zone is one of the important controlling project. The engineering tunnel transition asymmetric small clear space structure by the large span structures change to the structure, cross-section in the form of separate complex construction process to convert, the construction process of excavation and support mutual influence, surrounding rock stress multiple distribution support and lining structural load conversion complex. In addition, the construction process in the tunnel deformation control difficult, the slightest mistake, it will cause a collapse. Regardless of design or construction, bifurcation tunnel structure is relatively very complicated. Therefore, has important practical significance and value of the works carried out a risk assessment of the construction phase of Dalian Metro.
The main contents include:
(1) Bifurcation tunnel construction mechanics analysis
Six feature sections numerical model, numerical simulation analysis method based on stratigraphic-structural model, forked tunnel simulation of the actual tunnel construction method, analysis of the force-deformation characteristics of the bifurcation tunnel.
(2) Bifurcation tunnel construction risk assess
Subway tunnel construction risk assessment modeling and application Randomness and fuzziness of the subway tunnel construction risk, the use of fuzzy regression model and neural networks theory to risk prediction. Subway tunnel collapse data through statistical analysis, and summarize the risk factors affect the construction of the tunnel, the main factors were selected as fuzzy regression analysis of the impact factor. Adopt-level analysis and membership functions, respectively, calculated tunneling various risk factors the relative rights weight and risk factors of tunnel construction risk level of membership degree, the various related risk factors of the weight and the risk factors on the level of risk attached to the degree carried fuzzy integrated computing to draw tunnel construction risk level. And research on intrinsic relationship of tunnel security situation.
(3) The bifurcation identification and sensitivity analysis of the risk factors of tunnel construction
Main factors establish the model of the hierarchy of the tunnel construction risk factors summarized the bifurcation tunnel construction risk, construction risk factors using the analytic hierarchy sensitivity analysis. Mathematical methods using fuzzy regression and BP artificial neural network to establish the bifurcation tunnel construction risk prediction model. Fixed BP artificial neural network technology, using the negative gradient descent algorithm and using iterative computing to solve network weights heavy and the threshold corresponding network learning memory process, adding hidden nodes so that the optimization problem of adjustable parameters increases, which can be more precise the solution. The assessment system in the process of compiling the built-in core of artificial neural network algorithm, node sample training layers weight threshold input evaluation system, constitutes a complete neural network evaluation model. Based on the current conditions of the tunnel construction risk factors evaluation, the evaluation results into the input layer of the artificial neural network model has been calculated, the output layer evaluation index values of the tunnel. Reference to the the assessment index value calculated will get the size of the tunnel construction risk. The large cross, small clear space and other features section for risk assessment, and risk control management based on the results of the assessment.
Through the study, the following results were obtained:
(1) The bifurcation tunnel construction the focus is the control of the construction process, reasonable arrangements for the excavation of the two-hole interval and order of support, can effectively control the surrounding rock deformation caused clear distance smaller between the two tunnels, in order to ensure the safety of the tunnel structure.
(2) Determine the Dalian metro tunnel construction risk assessment indicators surrounding rock deformation, surface subsidence, the structure of the force, the plastic zone, gushing and landslides. Then regression and artificial neural networks using fuzzy mathematical methods, bifurcation tunnel construction risk prediction model. The large cross, small clear space and other features section risk prediction, risk control management based on the predicted results.
(3) Higher subway bifurcation tunnel construction process inherent relationship between the conclusions of the study of the numerical simulation and tunnel security situation and Engineering in situ measured data fit, more comprehensive conclusions of the tunnel construction risk assessment and tunnel construction risk management control subway bifurcation tunnel construction risk, can be used to guide the construction. The measured values are good to make up for the lack of numerical analysis, inspection, and deepen the bifurcation tunneling theory of risk assessment system provides measured data reference for subsequent construction methods and process improvements.
主要研究内容包括：
(1)分岔隧道施工力学分析
基于地层—结构模型,采用数值模拟分析方法,建立分岔隧道的6个特征断面数值模型,模拟隧道实际施工方法,分析分岔隧道的受力变形特征。
(2)分岔隧道施工风险评估
总结归纳分岔隧道施工风险的主要影响因素,建立隧道施工风险因素的层次结构模型,采用层次分析法进行施工风险因素的敏感性分析及隧道安全状况内在关系研究。采用模糊回归和BP人工神经网络等数学方法,建立分岔隧道施工风险预测模型。并对大跨度、高水位、小净距等特征断面进行风险评估,基于评估结果进行风险控制管理。
(3)分岔隧道施工风险管理
在大连地铁隧道建设过程中,将风险控制理论与大连地铁隧道工程充分结合,在隧道施工中不断调整、完善、提高,最终形成一套有针对性的隧道工程建设的风险控制管理措施制度。通过建立以超前地质预报、风险评估和监控量测为核心的“三位一体”的动态信息管理系统,可以全方位立体地将隧道开挖前、开挖中和开挖后的安全状态全部以数据形式显示出来,为工程施工提出技术参考,对施工技术负责人做出施工决策有重大的帮助。
通过上述研究,得到以下结果：
(1)分岔隧道施工的重点是施工工序的控制,通过合理安排双洞的开挖、支护的间隔和顺序,可有效地控制两隧道之间由于净距较小引起的围岩变形,从而保证隧道结构的安全。
(2)确定了大连地铁隧道施工风险评估指标为围岩变形、地表沉降、结构受力、塑性区范围、涌水以及塌方。然后采用模糊回归和人工神经网络等数学方法,建立了分岔隧道施工风险预测模型。对大跨、小净距等特征断面进行了风险预测,基于预测结果提出了风险控制管理。
(3)地铁分岔隧道施工过程数值模拟及隧道安全状况内在关系研究的结论与工程原位的实测数据拟合度较高,隧道施工风险评估及隧道施工风险管理等研究结论较为全面地控制了地铁分岔隧道施工的风险,可用于指导施工。同时现场实测值较好地弥补数值分析的不足,检验并深化了分岔隧道施工风险评估理论系统,为后续施工方法选择及改进工艺提供实测数据参考。
The being built new Line1of Dalian Metro between Maritime University and High-tech zone is one of the important controlling project. The engineering tunnel transition asymmetric small clear space structure by the large span structures change to the structure, cross-section in the form of separate complex construction process to convert, the construction process of excavation and support mutual influence, surrounding rock stress multiple distribution support and lining structural load conversion complex. In addition, the construction process in the tunnel deformation control difficult, the slightest mistake, it will cause a collapse. Regardless of design or construction, bifurcation tunnel structure is relatively very complicated. Therefore, has important practical significance and value of the works carried out a risk assessment of the construction phase of Dalian Metro.
The main contents include:
(1) Bifurcation tunnel construction mechanics analysis
Six feature sections numerical model, numerical simulation analysis method based on stratigraphic-structural model, forked tunnel simulation of the actual tunnel construction method, analysis of the force-deformation characteristics of the bifurcation tunnel.
(2) Bifurcation tunnel construction risk assess
Subway tunnel construction risk assessment modeling and application Randomness and fuzziness of the subway tunnel construction risk, the use of fuzzy regression model and neural networks theory to risk prediction. Subway tunnel collapse data through statistical analysis, and summarize the risk factors affect the construction of the tunnel, the main factors were selected as fuzzy regression analysis of the impact factor. Adopt-level analysis and membership functions, respectively, calculated tunneling various risk factors the relative rights weight and risk factors of tunnel construction risk level of membership degree, the various related risk factors of the weight and the risk factors on the level of risk attached to the degree carried fuzzy integrated computing to draw tunnel construction risk level. And research on intrinsic relationship of tunnel security situation.
(3) The bifurcation identification and sensitivity analysis of the risk factors of tunnel construction
Main factors establish the model of the hierarchy of the tunnel construction risk factors summarized the bifurcation tunnel construction risk, construction risk factors using the analytic hierarchy sensitivity analysis. Mathematical methods using fuzzy regression and BP artificial neural network to establish the bifurcation tunnel construction risk prediction model. Fixed BP artificial neural network technology, using the negative gradient descent algorithm and using iterative computing to solve network weights heavy and the threshold corresponding network learning memory process, adding hidden nodes so that the optimization problem of adjustable parameters increases, which can be more precise the solution. The assessment system in the process of compiling the built-in core of artificial neural network algorithm, node sample training layers weight threshold input evaluation system, constitutes a complete neural network evaluation model. Based on the current conditions of the tunnel construction risk factors evaluation, the evaluation results into the input layer of the artificial neural network model has been calculated, the output layer evaluation index values of the tunnel. Reference to the the assessment index value calculated will get the size of the tunnel construction risk. The large cross, small clear space and other features section for risk assessment, and risk control management based on the results of the assessment.
Through the study, the following results were obtained:
(1) The bifurcation tunnel construction the focus is the control of the construction process, reasonable arrangements for the excavation of the two-hole interval and order of support, can effectively control the surrounding rock deformation caused clear distance smaller between the two tunnels, in order to ensure the safety of the tunnel structure.
(2) Determine the Dalian metro tunnel construction risk assessment indicators surrounding rock deformation, surface subsidence, the structure of the force, the plastic zone, gushing and landslides. Then regression and artificial neural networks using fuzzy mathematical methods, bifurcation tunnel construction risk prediction model. The large cross, small clear space and other features section risk prediction, risk control management based on the predicted results.
(3) Higher subway bifurcation tunnel construction process inherent relationship between the conclusions of the study of the numerical simulation and tunnel security situation and Engineering in situ measured data fit, more comprehensive conclusions of the tunnel construction risk assessment and tunnel construction risk management control subway bifurcation tunnel construction risk, can be used to guide the construction. The measured values are good to make up for the lack of numerical analysis, inspection, and deepen the bifurcation tunneling theory of risk assessment system provides measured data reference for subsequent construction methods and process improvements.
引文
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