Long-distance pipe-jacking tunnel construction method based on three-dimensional stability analysis

Abstract

A long-distance pipe-jacking tunnel construction method based on three-dimensional stability analysis comprises the following steps: constructing a three-dimensional numerical model based on geological exploration data; performing high-precision discretization processing to form an infinitesimal triangular mesh; assigning physical and mechanical parameters to the soil body in the model; deducing a pipe-jacking tunnel excavation face supporting force calculation formula by applying a limit analysis upper limit theorem; developing an integrated calculation program, and performing comparative analysis with measured data; the accuracy of a calculation program is verified through actual measurement data, the jacking force is dynamically optimized by integrating construction parameters, and the influence of additional stress of the upper structure on construction stability is evaluated; the three-dimensional stability analysis model is optimized and updated, and accurate control over the construction process is achieved; and according to the optimization model and a data analysis result, a construction scheme is adjusted in real time to adapt to stratum change and construction deviation. Compared with a traditional method, the stability analysis precision of pipe-jacking tunnel construction is improved, the construction scheme is optimized, and the method has remarkable engineering application value and popularization prospects.

Description

Technical Field

[0001] The invention relates to the technical field of underground engineering construction, and in particular to a long-distance pipe-jacking tunnel construction method based on three-dimensional stability analysis. Background Art

[0002] In the field of underground engineering, pipe jacking tunnel construction technology has been widely used because of its small impact on ground traffic and the environment. However, with the continuous expansion of the scale of pipe jacking tunnel projects, the stability problem during the construction process has gradually become a key factor restricting project safety and efficiency. Especially in long-distance pipe jacking construction, due to the complexity of geological conditions and the uncertainty of the construction environment, the traditional two-dimensional stability analysis method can no longer meet the needs of modern engineering.

[0003] Existing pipe-jacking tunnel construction technology has certain limitations in stability analysis. On the one hand, traditional analysis methods are often based on simplified theoretical models, ignoring the diversity of geological conditions and dynamic changes during the construction process, resulting in deviations between the analysis results and the actual situation. On the other hand, key parameters in the construction process, such as soil compartment pressure, grouting pressure, and pipe-soil friction, have an important impact on the stability of pipe-jacking tunnels, but existing technologies are not mature enough in real-time monitoring and dynamic adjustment of these parameters.

[0004] In addition, the additional stress effect of superstructures such as levees on the construction of pipe jacking tunnels is also a problem that is less considered in the prior art. These additional stresses may have an adverse effect on the stability of the pipe jacking tunnel and increase the construction risk. Therefore, the development of a new technology that can comprehensively consider multiple factors and accurately predict and control the stability of long-distance pipe jacking tunnel construction is of great significance to improving construction safety and efficiency. In response to this demand, the present invention proposes a long-distance pipe jacking tunnel construction method based on three-dimensional stability analysis. Summary of the invention

[0005] The purpose of the present invention is to provide a three-dimensional stability analysis method for long-distance pipe jacking tunnel construction, which can accurately evaluate the stability of the excavation face during the construction process, optimize the construction parameters in real time, and adapt to the changing geological conditions and construction environment, thereby improving the safety and efficiency of the construction.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] A long distance pipe jacking tunnel construction method based on three-dimensional stability analysis comprises the following steps:

[0008] Step (1): Based on geological exploration data, a three-dimensional numerical model including the tunnel geometry, stratum structure and soil physical and mechanical properties is constructed; the three-dimensional numerical model uses finite element or finite difference method to simulate the soil failure process; the three-dimensional numerical model provides an accurate virtual representation of the geological and structural environment, laying the foundation for subsequent analysis.

[0009] Step (2): The excavation surface of the jacking tunnel is discretized with high precision to form a micro-element triangular mesh to approximate the polyhedron of the soil damage zone; the high-precision discretization is the key to achieving refined prediction of the model, ensuring that the three-dimensional numerical model can capture the complex soil behavior during the construction process.

[0010] Step (3): assign physical and mechanical parameters to the soil in the model, which are determined by comprehensive indoor tests and on-site geological exploration data. The physical and mechanical parameters include cohesion, internal friction angle, elastic modulus, Poisson's ratio and compression coefficient; in specific implementation, the cohesion of the embodiment is c=30 kPa, the internal friction angle is Elastic modulus E = 100 MPa, Poisson's ratio ν = 0.3 and compression coefficient C c =0.1MPa ∧ -1.

[0011] Step (4): applying the upper limit theorem of limit analysis, combining the soil stress path, velocity field and associated flow laws, to derive a calculation formula for the support force of the excavation face of the jacking tunnel; the application of the upper limit theorem of limit analysis includes constructing and solving the static equilibrium equation of the excavation face support force; applying the upper limit theorem of limit analysis, combining the soil stress path, velocity field and associated flow laws, to derive a calculation formula for the support force of the excavation face of the jacking tunnel; the calculation formula for the support force of the excavation face of the jacking tunnel can calculate the minimum support force required at different construction stages, thereby ensuring the safety of the construction.

[0012] Step (5): Develop an integrated calculation program that can run on a variety of computing platforms, automatically calculate the ultimate support pressure of the excavation face, achieve fast and accurate calculations, and conduct comparative analysis with measured data; the automated nature of the integrated calculation program significantly improves calculation efficiency and reduces human errors.

[0013] Step (6): Verify the accuracy of the calculation program using measured data, including monitoring of formation deformation, support pressure and thrust force; the measured data verification uses measured data, including formation deformation δ, support pressure P support and thrust F jacking , statistical analysis and error evaluation are performed on the calculation results of the integrated calculation program; the measured data verification step ensures the consistency between the model prediction and the actual situation on site.

[0014] Step (7): Dynamic feedback control and adaptive adjustment algorithm are used to dynamically optimize the jacking force based on comprehensive construction parameters; dynamic optimization of the jacking force includes real-time monitoring and automatic adjustment of the jacking force, and dynamic feedback control and adaptive adjustment algorithm are used to integrate construction parameters based on real-time monitoring data; dynamic optimization of the jacking force enables the construction process to respond to changes in geological conditions and construction environment in real time.

[0015] Step (8): Combine numerical simulation and on-site monitoring to evaluate the impact of additional stress on the superstructure on construction stability; the superstructure additional stress evaluation adopts a method of comprehensive numerical simulation and on-site monitoring data, combined with numerical simulation and on-site monitoring, to evaluate the impact of additional stress on the superstructure on construction stability; evaluating the additional stress on the superstructure can clarify the potential impact of the additional stress on the construction process and take corresponding preventive measures.

[0016] Step (9): Apply machine learning algorithms to analyze construction data, conduct in-depth analysis and prediction of the data collected during the construction process, optimize and update the three-dimensional stability analysis model, and achieve precise control of the construction process; the application of machine learning algorithms improves the model's adaptability to changes in the construction process and its prediction accuracy.

[0017] Step (10): According to the optimization model and data analysis results, the construction plan is adjusted in real time to adapt to the formation changes and construction deviations; the optimization model includes a machine learning algorithm to conduct in-depth analysis and prediction of the construction data to improve the stability and efficiency of the construction process; the construction plan is adjusted according to the optimized model and data analysis results, including the optimization of the jacking speed, support type, grouting strategy and construction sequence, to ensure that the construction process can adapt to the formation changes and construction deviations, and improve the flexibility and safety of the construction.

[0018] The technical solution of the present invention realizes the intelligent management of pipe jacking tunnel construction, improves the stability and efficiency of construction, reduces construction risks, and realizes real-time optimization and intelligent management of the construction process, which has significant engineering application value and promotion prospects. It can mainly bring the following three specific technical effects:

[0019] Technical Effects 1. Significantly improve construction safety: By establishing an accurate three-dimensional numerical model and applying the upper limit theorem of limit analysis, the present invention can accurately predict the instability of the excavation surface that may occur during the construction of the jacking tunnel. Real-time monitoring is combined with dynamic adjustment of construction parameters to ensure the balance of soil pressure and support force during construction, effectively prevent tunnel collapse and surface settlement, and significantly improve construction safety.

[0020] Technical Effect 2. Greatly improve construction efficiency: The integrated calculation program developed by the present invention can quickly perform stability analysis and support force calculation, greatly reducing the time of traditional manual calculation and empirical judgment. At the same time, the adaptive adjustment algorithm can automatically optimize the construction parameters according to real-time data, reduce construction delays caused by construction plan adjustments, thereby speeding up the construction progress and improving the overall construction efficiency.

[0021] Technical Effect 3. Effectively reduce project costs: Through accurate stability analysis and real-time optimized construction plans, the present invention can reduce additional costs caused by construction accidents or rework. Automated calculations reduce dependence on professionals and reduce labor costs. In addition, the optimized construction plan reduces the waste of materials and energy, further reduces the direct cost of the project, and makes the entire construction process more economical and efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 The present invention is a flow chart of the innovative long-distance pipe jacking tunnel construction method. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] Example 1

[0025] A long distance pipe jacking tunnel construction method based on three-dimensional stability analysis comprises the following steps:

[0026] Step (1): Based on geological exploration data, a three-dimensional numerical model including the tunnel geometry, stratum structure and soil physical and mechanical properties is constructed; the three-dimensional numerical model uses finite element or finite difference method to simulate the soil failure process; the three-dimensional numerical model provides an accurate virtual representation of the geological and structural environment, laying the foundation for subsequent analysis.

[0027] Step (2): The excavation surface of the jacking tunnel is discretized with high precision to form a micro-element triangular mesh to approximate the polyhedron of the soil damage zone; the high-precision discretization is the key to achieving refined prediction of the model, ensuring that the three-dimensional numerical model can capture the complex soil behavior during the construction process.

[0028] Step (3): assign physical and mechanical parameters to the soil in the model, which are determined by comprehensive indoor tests and on-site geological exploration data. The physical and mechanical parameters include cohesion, internal friction angle, elastic modulus, Poisson's ratio and compression coefficient; in specific implementation, the cohesion of the embodiment is c=30 kPa, the internal friction angle is Elastic modulus E = 100 MPa, Poisson's ratio ν = 0.3 and compression coefficient C c =0.1MPa ∧ -1.

[0029] Step (4): applying the upper limit theorem of limit analysis, combining the soil stress path, velocity field and associated flow laws, to derive a calculation formula for the support force of the excavation face of the jacking tunnel; the application of the upper limit theorem of limit analysis includes constructing and solving the static equilibrium equation of the excavation face support force; applying the upper limit theorem of limit analysis, combining the soil stress path, velocity field and associated flow laws, to derive a calculation formula for the support force of the excavation face of the jacking tunnel; the calculation formula for the support force of the excavation face of the jacking tunnel can calculate the minimum support force required at different construction stages, thereby ensuring the safety of the construction.

[0030] Step (5): Develop an integrated calculation program that can run on a variety of computing platforms, automatically calculate the ultimate support pressure of the excavation face, achieve fast and accurate calculations, and conduct comparative analysis with measured data; the automated nature of the integrated calculation program significantly improves calculation efficiency and reduces human errors.

[0031] Step (6): Verify the accuracy of the calculation program using measured data, including monitoring of formation deformation, support pressure and thrust force; the measured data verification uses measured data, including formation deformation δ, support pressure P support and thrust F jacking , statistical analysis and error evaluation are performed on the calculation results of the integrated calculation program; the measured data verification step ensures the consistency between the model prediction and the actual situation on site.

[0032] Step (7): Dynamic feedback control and adaptive adjustment algorithm are used to dynamically optimize the jacking force based on comprehensive construction parameters; dynamic optimization of the jacking force includes real-time monitoring and automatic adjustment of the jacking force, and dynamic feedback control and adaptive adjustment algorithm are used to integrate construction parameters based on real-time monitoring data; dynamic optimization of the jacking force enables the construction process to respond to changes in geological conditions and construction environment in real time.

[0033] Step (8): Combine numerical simulation and on-site monitoring to evaluate the impact of additional stress on the superstructure on construction stability; the superstructure additional stress evaluation adopts a method of comprehensive numerical simulation and on-site monitoring data, combined with numerical simulation and on-site monitoring, to evaluate the impact of additional stress on the superstructure on construction stability; evaluating the additional stress on the superstructure can clarify the potential impact of the additional stress on the construction process and take corresponding preventive measures.

[0034] Step (9): Apply machine learning algorithms to analyze construction data, conduct in-depth analysis and prediction of the data collected during the construction process, optimize and update the three-dimensional stability analysis model, and achieve precise control of the construction process; the application of machine learning algorithms improves the model's adaptability to changes in the construction process and its prediction accuracy.

[0035] Step (10): According to the optimization model and data analysis results, the construction plan is adjusted in real time to adapt to the formation changes and construction deviations; the optimization model includes a machine learning algorithm to conduct in-depth analysis and prediction of the construction data to improve the stability and efficiency of the construction process; the construction plan is adjusted according to the optimized model and data analysis results, including the optimization of the jacking speed, support type, grouting strategy and construction sequence, to ensure that the construction process can adapt to the formation changes and construction deviations, and improve the flexibility and safety of the construction.

[0036] Example 2

[0037] A long distance pipe jacking tunnel construction method based on three-dimensional stability analysis comprises the following steps:

[0038] First, a detailed analysis of the geological conditions is carried out, and detailed geological exploration data of the construction area is collected, including soil types, distribution characteristics, and physical and mechanical properties of the soil, such as cohesion c, internal friction angle phi, elastic modulus E, and Poisson's ratio ν. Secondly, evaluating the impact of groundwater levels and water quality on soil stability is also an important aspect of geotechnical engineering and environmental engineering, including groundwater level monitoring (installing water level meters or observation wells to regularly monitor the dynamic changes of groundwater levels, understand the pattern of its changes over time and conditions, and determine the range and frequency of groundwater level fluctuations), hydrogeological surveys (conducting geological surveys to determine groundwater recharge, runoff and discharge conditions), water quality analysis (collecting groundwater samples for laboratory analysis, including pH value, dissolved salts, organic matter content, heavy metal content, etc.), soil sample collection and soil property analysis (conducting soil particle size analysis, density, water content, permeability and other related physical properties), permeability analysis. Analysis (determine the permeability coefficient of the soil through permeability test and evaluate the permeability of the soil), soil-water effective stress analysis (study the interaction between the soil and groundwater, including the change of soil saturation and effective stress), numerical simulation (use numerical simulation software such as ABAQUS, FLAC, etc. to simulate the stress-strain behavior of the soil and groundwater flow), environmental impact assessment (assess the potential impact of groundwater level and water quality on the surrounding environment such as ecosystems, buildings, and infrastructure), risk assessment (determine the risk level of groundwater level changes and water quality changes on soil stability), monitoring and maintenance plan (formulate a monitoring plan to track the long-term changes of groundwater level and water quality, and formulate corresponding maintenance and response measures). Through these steps and taking appropriate measures to ensure engineering safety and environmental health. Based on the engineering design requirements, the relevant specifications are consulted to determine the design dimensions of the top pipe tunnel, including the tunnel diameter D, the total length of the tunnel L, the wall thickness t of the pipe segment and the cross-sectional shape of the pipe end, and the design optimization is carried out using computer-aided design (CAD). These parameters are crucial to the construction process and the establishment of numerical models. The parametric processing of the construction process involves the type of pipe jacking machine, jacking speed, support method, grouting material characteristics and grouting pressure p_g, etc., to ensure that these parameters can be accurately input into the numerical model.

[0039] The three-dimensional numerical model of the tunnel and its surrounding strata is established by numerical simulation software. Fine micro-element triangular meshes are generated for the pipe-soil components. In key areas where stress and strain change drastically, such as the pipe-soil contact area, finer meshes are used to capture details. The adaptive mesh refinement function of the numerical simulation software is used to automatically adjust the mesh size and density according to the needs of the analysis process. High-order elements are used to improve the discretization accuracy, such as using quadratic or cubic elements to improve the simulation accuracy. Accurate boundary conditions and loading conditions are used to ensure accurate simulation of external loads and constraints. Appropriate numerical integration methods (such as reduced integration methods) are selected to reduce numerical errors. Through high-precision discretization processing, the interaction between the excavation surface and the surrounding soil during construction is captured. Different failure criteria are set in the model according to the physical and mechanical properties of the soil. For example, the Mohr-Coulomb criterion can be selected for sand. The mechanical properties of the soil components are improved. The soil failure behavior is simulated by giving the soil plastic properties such as friction angle and expansion angle and viscous properties such as cohesive yield stress and absolute plastic strain. By comparing with actual engineering cases or field test data, the model is verified and adjusted, and the model parameters are fine-tuned according to the verification results to improve the prediction accuracy, ensure its accuracy and reliability, enable the model to adapt to different geological conditions, construction speeds and support methods, and provide a comprehensive and accurate analysis tool for the formulation of construction plans.

[0040] The physical and mechanical parameters of the soil in the model are multiplied by the safety factor, and extreme values ​​are used to determine the performance of the structure under the worst-case scenario. A series of rigorous, ordered and highly specialized steps are followed to ensure the accuracy and reliability of the model's predictions under extreme geological conditions: comprehensive collection of key physical and mechanical properties that affect soil behavior, including cohesion c = 30 kPa, internal friction angle phi = 35°, elastic modulus E = 100 MPa, Poisson's ratio ν = 0.3, and compression coefficient Cc = 0.1 MPa^-1. The selection of these parameters is based on a deep understanding of soil properties and provides a solid foundation for the model. During the indoor test phase, refined test methods are used, such as direct shear tests to determine cohesion and internal friction angles, and advanced triaxial compression tests to test elastic modulus and Poisson's ratio under different stress paths to ensure the accuracy and applicability of parameters under extreme stress conditions. Detailed information on soil layers is collected through deep drilling, geological radar and geophysical exploration, especially soil properties under conditions of high water pressure pw>300 kPa, high compressibility or soft soil layers. The indoor test data is combined with the field exploration results to accurately assign soil parameters in the model, taking into account the anisotropy and heterogeneity of the soil, especially the adjustment of parameters under extreme conditions, such as high water pressure or soft soil layers, where cohesion and internal friction angle may decrease, and elastic modulus and compression coefficient may increase. The model is calibrated through strict comparison with actual engineering cases or field monitoring data to ensure extreme accuracy of model predictions.

[0041] In this process, iteratively adjust parameters such as material properties and load size, determine the iteration range and step size of parameters, such as the upper and lower limits and change step size of material properties, write ABAQUS built-in scripts or Python scripts to automate the iteration process, use ABAQUS optimization module, set objective functions and design variables, post-process the results of each iteration, compare the responses under different parameters, and determine the optimal solution until the model prediction is highly consistent with the actual observation value. Pay special attention to the sensitivity of parameters under extreme geological conditions, such as the change of soil strength parameters in high water pressure or soft soil layers. By keeping other parameters constant and changing one parameter within the allowable range, compare the degree of influence of each parameter change on the prediction results to identify the parameters that have the greatest impact on model prediction.

[0042] After completing the above steps, the physical and mechanical parameters of the soil suitable for extreme geological conditions are finally determined. For example, under high water pressure conditions, a lower internal friction angle phi and cohesion c, as well as a higher compression coefficient Cc may be selected to ensure the reliability of the model and the accuracy of the prediction under various extreme construction conditions.

[0043] The present invention ensures the stability of the excavation surface of the jacking tunnel. First, the theoretical basis of the analysis is established based on the upper limit theorem of limit analysis. This theorem can determine the stress distribution of the soil under the limit state and the required minimum support force Pmin through optimization methods. The stress path of the soil is analyzed in detail, and various stress states that may be experienced during the construction process, such as the change of the principal stress ratio Kmax, are considered. At the same time, the flow and deformation trends of the soil are evaluated in combination with the distribution of the velocity field Vfield. After determining the stress path and velocity field, the Mohr-Coulomb correlation flow law is introduced to describe the flow and failure mode of the soil under different stress states, establish a three-dimensional model of the soil failure surface, and predict possible failure mechanisms. Combined with the physical and mechanical properties of the soil, such as cohesion c, internal friction angle phi, outer diameter D of the jacking machine, soil bulk density γ, pipe section cover height H, as well as construction conditions and geometric parameters of the stratum, the support force calculation formula for the jacking tunnel excavation surface is derived:

[0044] Where: H p - The distance from the soil pressure point to the top axis of the tunnel boring machine, γ w -Gravity of water; H W -The distance from the soil pressure point to the groundwater level; Phi-soil internal friction angle; H-soil cover height of the pipe segment; D-outer diameter of the jacking pipe segment.

[0045] This formula can accurately calculate the minimum support force required for the excavation face at different construction stages. Finally, through comparative analysis with actual engineering cases, the accuracy and applicability of the derived support force calculation formula are verified to ensure the stability and safety of the excavation face during construction.

[0046] The highly integrated calculation program developed in the present invention automates the calculation process of the ultimate support pressure of the excavation face in the construction of the top pipe tunnel, and uses programming languages ​​such as MATLAB, Python, and C++ to achieve cross-platform operation. The input parameters of the program include soil cohesion c=30kPa, internal friction angle phi is 35°, elastic modulus E=100MPa, Poisson's ratio ν=0.3, compression coefficient Cc=0.1MPa^-1, as well as tunnel diameter D=6m, construction speed v=5m / day, support type (such as reinforced concrete), and grouting pressure pg=250kPa. Using the upper limit theorem of limit analysis (the upper limit theorem is part of the limit analysis method, also known as the safety factor method or limit equilibrium method, which is a method for evaluating the stability of soil, writing scripts or functions to calculate the performance of the structure when it reaches the limit state), based on the Moore-Coulomb yield criterion in material mechanics, the program automatically calculates the ultimate support pressure Pmin of the excavation face, for example, the calculation result may be 150kPa. The program combines field monitoring data, such as formation deformation delta = 1.5mm / d and support pressure Pactual = 145kPa, for comparative analysis and evaluation of construction stability. The user interface is simple and intuitive, making it easy for engineers to input parameters and interpret calculation results, such as a chart of the ultimate support pressure of the excavation face and a comparison with measured data. Finally, the program outputs a detailed report containing ultimate support pressure, construction parameter sensitivity analysis, and measured data comparison to support engineering design and construction decisions and ensure construction safety and efficiency.

[0047] A series of meticulous steps were taken to validate and calibrate the calculation program to ensure the accuracy and reliability of its output results. First, measured data were collected from the construction process of the pipe jacking tunnel, including the formation deformation delta (e.g., average deformation rate 0.5 mm / d), support pressure Psupport (e.g., 250 kPa), and jacking force Fjacking (e.g., 1500 kN). These data were acquired in real time by high-precision monitoring equipment and covered the key physical quantities during the construction process. Next, these measured data were subjected to in-depth statistical analysis to calculate the mean, standard deviation, skewness, kurtosis, and correlation analysis to identify the relationship between different parameters. The error between the measured data and the prediction results of the calculation program was evaluated by comparing the two, and the accuracy of the prediction was quantified using error indicators such as root mean square error (RMSE) 0.05, mean absolute error (MAE) ≈ 0.03, and coefficient of determination (R^2) ≈ 0.98. Based on the error assessment, the parameters in the calculation program were adjusted, such as the internal friction angle phi of the soil from 35° to 33°, and the cohesion c from 30kPa to 32kPa, to reduce the prediction error. Sensitivity analysis revealed that the parameters that had the greatest impact on the calculation results, such as the support pressure and jacking force, had a particularly significant impact on the stability of the excavation face. The calculation program was continuously optimized through an iterative approach, with each iteration including recalculation, error assessment, and model calibration until the error between the calculated results and the measured data was reduced to an acceptable range, such as RMSE less than 0.05. Finally, a detailed validation report was prepared to summarize the accuracy and reliability of the calculation program and record the key findings and adjustments made during the calibration process. This report provides the construction team with detailed information on the performance of the calculation program, such as the 95% confidence interval of the model prediction, to ensure its effective application in actual projects and provide strong data support for the stability analysis of pipe jacking tunnel construction.

[0048] Adopt dynamic feedback control and adaptive adjustment algorithm (using the output of the system or a function of the output as input to adjust the input of the system, thereby changing the behavior of the system, and automatically adjusting the parameters of the controller according to the changes in system performance to maintain or optimize the control effect) to achieve real-time monitoring and automatic adjustment of key construction parameters during pipe jacking tunnel construction: Develop a dynamic feedback control system that can receive parameters from the construction site in real time. The system dynamically adjusts the construction strategy based on this data to ensure the stability and safety of the construction process. The adaptive adjustment algorithm integrated in the system can automatically adjust the construction parameters according to the real-time monitoring data. For example, if the monitored soil compartment pressure exceeds the preset safety Value P cabin >P threshold, the algorithm will automatically increase the grouting volume or adjust the jacking speed to reduce the soil chamber pressure and prevent excessive deformation of the formation. Comprehensive consideration of key construction parameters: During the adaptive adjustment process, the system not only considers the changes in a single parameter, but also comprehensively considers the interaction of all key construction parameters. For example, the system will analyze the mutual influence between the soil chamber pressure, grouting pressure and pipe-soil friction, and calculate the optimal parameter combination to achieve a balance between construction efficiency and safety. The system implements a real-time monitoring mechanism to collect data in real time through sensors installed at the construction site. Once a parameter deviation is detected, the system will immediately start the adaptive adjustment algorithm to automatically adjust the jacking force F jacking and other construction parameters to respond to changes in construction conditions. Through dynamic feedback control and adaptive adjustment, the construction process is continuously optimized. The system can learn data patterns during the construction process and predict potential risks, so as to make adjustments in advance and avoid construction interruptions or accidents.

[0049] A comprehensive evaluation method is adopted to evaluate the influence of the additional stress of the superstructure on the stability of the jacking tunnel construction by combining numerical simulation and on-site monitoring: First, a detailed three-dimensional geological model including the superstructure is established using numerical simulation software such as ABAQUS or ANSYS. In the model, the weight, distribution and mechanical behavior of the superstructure interacting with the tunnel are simulated to calculate the additional stress σ caused by the superstructure additional At the same time, monitoring points are arranged at the construction site, and monitoring equipment such as stress gauges, displacement gauges and inclinometers are installed. These devices can monitor the actual impact of the superstructure on the tunnel construction area in real time, including the soil pressure σ soil , support reaction force F support and formation displacement δ ground . . The impact of additional stress on the superstructure on construction stability is evaluated through comparative analysis of numerical simulation results and field monitoring data. This evaluation process includes determining the distribution range, peak value and degree of influence of additional stress on the support structure of the purlin. A comprehensive judgment on construction stability is made based on the results of numerical simulation and field monitoring. If the evaluation results show that the additional stress exceeds the design safety factor, measures such as increasing the support strength or adjusting the construction plan will be taken to ensure construction safety. Based on the evaluation results, risk management measures and emergency plans are formulated. These measures may include strengthening the superstructure, optimizing the design of tunnel pipe sections or adjusting the construction process to reduce the adverse effects of additional stress on construction stability. During the construction process, numerical simulation and field monitoring are continuously carried out to update the evaluation of additional stress on the superstructure in real time. Ensure that the construction plan can respond to any changes in a timely manner to maintain the stability and safety of the construction process.

[0050] In the implementation of the present invention, a machine learning algorithm is used to conduct in-depth analysis and prediction of a large amount of data collected during the construction process to optimize and update the three-dimensional stability analysis model so that it can adapt to the stratum changes and construction deviations that may occur during the construction process. By collecting key data, such as soil cohesion c = 30kPa, internal friction angle phi = 35°, tunnel circumferential displacement deltahoop = 10mm, support pressure Psupport = 250kPa and jacking force Fjacking = 1500kN, these data are preprocessed for algorithm analysis. Using a support vector machine (SVM) or a deep neural network (DNN), the model is trained to identify key factors affecting construction stability in the data and predict potential risks, such as the possible increase of stratum deformation deltaprediction to 15mm. The model integrated into the construction management system can receive new monitoring data in real time and dynamically adjust construction parameters according to the prediction of the machine learning algorithm, such as automatically adjusting the grouting pressure Pgrouting to 280kPa to cope with stratum instability. As construction progresses, the model is continuously iterated and optimized through continuous learning to improve prediction accuracy, ensure that the construction plan responds promptly to real-time changes in geological conditions, and maintain the stability and safety of the construction process.

[0051] Ensure that the construction plan is adjusted in real time according to the optimized model and data analysis results, conduct an in-depth review of the data obtained through the machine learning algorithm analysis, and identify key influencing factors and potential risk points in the construction process. Based on these analysis results, the three-dimensional stability analysis model is optimized to improve its prediction accuracy. Then, based on the optimized model and data analysis results, make decisions on the adjustment of the construction plan. This includes evaluating the differences between the current construction parameters and the model predictions, and determining the construction parameters that need to be adjusted, such as the jacking speed Vjacking, support type, grouting strategy Sgrouting, and construction sequence. During the construction process, a real-time monitoring system is implemented to automatically collect construction parameter data and compare it with the optimized model predictions. If the monitored jacking speed or support reaction force exceeds the preset safety range, the system will automatically trigger the adjustment mechanism. Specifically, if the model prediction shows that the formation stability is reduced, it may be necessary to reduce the jacking speed Vjacking from 5m / day to 3m / day to reduce the formation disturbance. At the same time, it may be necessary to adjust the support type from steel arch support to reinforced concrete support to provide greater support force. Depending on the permeability and deformation of the formation, it may be necessary to optimize the grouting strategy, such as increasing the grouting volume Qgrouting or changing the slurry ratio to improve the stability of the formation. The construction sequence may also be adjusted based on the risk assessment predicted by the model, for example, giving priority to sections with lower construction risks. After adjusting the construction plan, the construction process is continuously monitored to evaluate the effectiveness of the adjustment measures. If the actual construction performance is consistent with the model prediction, it means that the adjustment plan is effective; if there is still a deviation, the cause will be further analyzed and necessary secondary adjustments will be made. Establish a mechanism for continuous optimization and feedback loops. New data collected during the construction process is continuously input into the model, and the model self-learns and optimizes based on the latest data, forming a dynamic and self-improving construction management process.

[0052] Implement intelligent construction management by deploying a comprehensive monitoring system to continuously collect key parameters of geological conditions and construction processes, such as soil cohesion c = 30 kPa, internal friction angle phi = 35°, groundwater level changes, tunnel perimeter stress sigma tunnel = 2000 kPa, and displacement delta tunnel = 5 mm. These data are input into a pre-trained machine learning model, such as a model using a random forest algorithm, which is able to process and analyze large amounts of data and identify patterns and trends during construction. As construction progresses, the model is continuously updated and optimized using newly collected data, such as soil cabinet pressure Pcabin = 0.5 MPa and grouting pressure Pgrouting = 1.0 MPa, to adapt to changes in geological conditions or adjustments in construction parameters through an iterative process. Iterative optimization of the model is able to predict possible problems during construction, such as a possible increase in formation deformation deltaprediction to 10 mm, and take preventive measures to improve construction stability and efficiency and reduce delays. The construction management system automatically adjusts the construction plan based on the predictions and suggestions of the machine learning algorithm, such as adjusting the jacking speed Vjacking = 10 cm / h and the support type, to optimize resource allocation. The optimized model provides risk assessment, helps construction teams manage potential risks, and recommends the best construction strategies to cope with the ever-changing construction environment. As experience accumulates, the system's prediction and decision-making capabilities continue to improve, providing more accurate and efficient management for future construction projects, such as automatically raising the risk assessment threshold from Rthreshold = 0.8 to Rthreshold = 0.85 through learning to adapt to higher safety standards.

[0053] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A long distance pipe jacking tunnel construction method based on three-dimensional stability analysis, characterized in that: The following steps are involved: Step (1): Based on geological exploration data, a three-dimensional numerical model including the tunnel geometry, stratum structure and soil physical and mechanical properties is constructed; the three-dimensional numerical model uses finite element or finite difference method to simulate the soil failure process; the three-dimensional numerical model provides an accurate virtual representation of the geological and structural environment, laying a foundation for subsequent analysis; Step (2): high-precision discretization is performed on the excavation surface of the jacking tunnel to form a micro-element triangular mesh to approximate the polyhedron of the soil damage zone; the high-precision discretization is the key to achieving refined prediction of the model, ensuring that the three-dimensional numerical model can capture the complex soil behavior during the construction process; Step (3): assigning physical and mechanical parameters to the soil in the model, wherein the physical and mechanical parameters are determined comprehensively through indoor tests and on-site geological exploration data; the physical and mechanical parameters include cohesion, internal friction angle, elastic modulus, Poisson's ratio and compression coefficient; Step (4): applying the upper limit theorem of limit analysis, combining the soil stress path, velocity field and associated flow laws, and deriving the calculation formula for the support force of the excavation face of the jacking tunnel; the application of the upper limit theorem of limit analysis includes constructing and solving the static equilibrium equation of the excavation face support force; applying the upper limit theorem of limit analysis, combining the soil stress path, velocity field and associated flow laws, and deriving the calculation formula for the support force of the excavation face of the jacking tunnel; the calculation formula for the support force of the excavation face of the jacking tunnel can calculate the minimum support force required at different construction stages, thereby ensuring the safety of the construction; Step (5): Develop an integrated calculation program that can run on a variety of computing platforms, automatically calculate the ultimate support pressure of the excavation face, achieve fast and accurate calculations, and conduct comparative analysis with measured data; the automated nature of the integrated calculation program significantly improves calculation efficiency and reduces human errors; Step (6): Verify the accuracy of the calculation program using measured data, including monitoring of formation deformation, support pressure and jacking force; The measured data verification uses measured data, including formation deformation δ, support pressure P support and thrust F jacking , statistical analysis and error evaluation are performed on the calculation results of the integrated calculation program; the measured data verification step ensures the consistency between the model prediction and the actual situation on site; Step (7): using dynamic feedback control and adaptive adjustment algorithm to dynamically optimize the jacking force based on comprehensive construction parameters; dynamic optimization of the jacking force includes real-time monitoring and automatic adjustment of the jacking force, using dynamic feedback control and adaptive adjustment algorithm to integrate construction parameters based on real-time monitoring data; dynamic optimization of the jacking force enables the construction process to respond to changes in geological conditions and construction environment in real time; Step (8): combining numerical simulation and on-site monitoring to evaluate the impact of the additional stress of the superstructure on the construction stability; the additional stress of the superstructure is evaluated by combining numerical simulation and on-site monitoring data to evaluate the impact of the additional stress of the superstructure on the construction stability; evaluating the additional stress of the superstructure can clarify the potential impact of the additional stress on the construction process and take corresponding preventive measures; Step (9): Apply machine learning algorithms to analyze construction data, conduct in-depth analysis and prediction of data collected during the construction process, optimize and update the three-dimensional stability analysis model, and achieve precise control of the construction process; the application of machine learning algorithms improves the model's adaptability to changes in the construction process and its prediction accuracy; Step (10): According to the optimization model and data analysis results, the construction plan is adjusted in real time to adapt to the formation changes and construction deviations; the optimization model includes a machine learning algorithm to conduct in-depth analysis and prediction of the construction data to improve the stability and efficiency of the construction process; the construction plan is adjusted according to the optimized model and data analysis results, including the optimization of the jacking speed, support type, grouting strategy and construction sequence, to ensure that the construction process can adapt to the formation changes and construction deviations, and improve the flexibility and safety of the construction.

2. The long distance pipe jacking tunnel construction method based on three-dimensional stability analysis according to claim 1 is characterized in that: In step (2): the design dimensions of the jacking tunnel, including the tunnel diameter D, the total length of the tunnel L, the wall thickness t of the pipe segment and the cross-sectional shape of the pipe end, are optimized using computer-aided design; the construction process parameterization processing involves the type of jacking machine, jacking speed, support method, grouting material characteristics and grouting pressure p_g, ensuring that these parameters can be accurately input into the numerical model.

3. The long distance pipe jacking tunnel construction method based on three-dimensional stability analysis according to claim 1 is characterized in that: Use numerical simulation software to build a three-dimensional numerical model of the tunnel and its surrounding strata, generate fine micro-element triangular meshes for the pipe-soil components, and use finer meshes to capture details in key areas where stress and strain change dramatically, such as the pipe-soil contact area; use the adaptive mesh refinement function of the numerical simulation software to automatically adjust the mesh size and density according to the needs of the analysis process; use high-order elements to improve discretization accuracy, such as using quadratic or cubic elements to improve simulation accuracy; precise boundary conditions and loading conditions to ensure accurate simulation of external loads and constraints; select appropriate numerical integration methods to reduce numerical errors; and use high-precision discretization processing to improve the accuracy of the simulation. , capture the interaction between the excavation surface and the surrounding soil during the construction process; set different failure criteria in the model according to the physical and mechanical properties of the soil, improve the mechanical properties of the soil component materials, and simulate the soil failure behavior by giving the soil plastic properties such as friction angle and expansion angle and viscous properties such as cohesive yield stress and absolute plastic strain; verify and adjust the model by comparing with actual engineering cases or field test data, fine-tune the model parameters according to the verification results, improve the prediction accuracy, ensure its accuracy and reliability, enable the model to adapt to different geological conditions, construction speeds and support methods, and provide a comprehensive and accurate analysis tool for the formulation of construction plans.

4. The long distance pipe jacking tunnel construction method based on three-dimensional stability analysis according to claim 1 is characterized in that: The physical and mechanical parameters of the soil in the model are multiplied by the safety factor, and extreme values ​​are used to determine the performance of the structure under the worst-case scenario. A series of strictly ordered and highly specialized steps are followed to ensure the predictive accuracy and reliability of the model under extreme geological conditions: comprehensive collection of key physical and mechanical properties that affect soil behavior. During the indoor test phase, refined test methods are used, and advanced triaxial compression tests are used to test the elastic modulus and Poisson's ratio under different stress paths to ensure the accuracy and applicability of the parameters under extreme stress conditions.

5. The long distance pipe jacking tunnel construction method based on three-dimensional stability analysis according to claim 1 is characterized in that: The theoretical basis of the analysis is established based on the upper limit theorem of limit analysis to determine the stress distribution of the soil under the limit state and the required minimum support force Pmin; various stress states that may be experienced during the construction process are considered, and the flow and deformation trends of the soil are evaluated in combination with the distribution of the velocity field Vfield; after determining the stress path and velocity field, the Mohr-Coulomb correlation flow law is introduced to describe the flow and failure mode of the soil under different stress states, establish a three-dimensional model of the soil failure surface, and predict possible failure mechanisms; combined with the physical and mechanical properties of the soil, the support force calculation formula for the excavation surface of the jacking tunnel is derived: Where: H p - The distance from the soil pressure point to the top axis of the tunnel boring machine, γ w -Gravity of water; H W -The distance from the soil pressure point to the groundwater level; Phi-soil internal friction angle; H-soil cover height of the pipe segment; D-outer diameter of the jacking pipe segment.

6. The long distance pipe jacking tunnel construction method based on three-dimensional stability analysis according to claim 1 is characterized in that: The highly integrated calculation program automates the calculation process of the ultimate support pressure of the excavation face during pipe-jacking tunnel construction. Using the upper limit theorem of limit analysis and based on the Moore-Coulomb yield criterion in material mechanics, the program automatically calculates the ultimate support pressure Pmin of the excavation face, conducts comparative analysis, and evaluates construction stability.

7. The long distance pipe jacking tunnel construction method based on three-dimensional stability analysis according to claim 1 is characterized in that: Collect measured data from the construction process of the pipe jacking tunnel. These data are obtained in real time through high-precision monitoring equipment and cover the key physical quantities in the construction process. Conduct in-depth statistical analysis on these measured data, calculate the mean, standard deviation, skewness, kurtosis, and perform correlation analysis to identify the relationship between different parameters. By comparing the measured data with the predicted results of the calculation program, evaluate the error between the two, and adjust the parameters in the calculation program based on the error evaluation; Sensitivity analysis reveals the parameters that have the greatest impact on the calculation results. The calculation program is continuously optimized through an iterative approach. Each iteration includes recalculation, error assessment and model calibration until the error between the calculated results and the measured data is reduced to an acceptable range. A detailed validation report is prepared to summarize the accuracy and reliability of the calculation program and record the key findings and adjustments made during the calibration process.

8. The long distance pipe jacking tunnel construction method based on three-dimensional stability analysis according to claim 1 is characterized in that: Dynamic feedback control and adaptive adjustment algorithms are used to achieve real-time monitoring and automatic adjustment of key construction parameters during pipe jacking tunnel construction: a dynamic feedback control system is developed, which can receive parameters from the construction site in real time; the system dynamically adjusts the construction strategy based on these data to ensure the stability and safety of the construction process; the adaptive adjustment algorithm integrated in the system can automatically adjust the construction parameters based on real-time monitoring data; comprehensive consideration of key construction parameters: during the adaptive adjustment process, the system not only considers the changes in a single parameter, but also comprehensively considers the interaction of all key construction parameters; the system implements a real-time monitoring mechanism to collect data in real time through sensors installed at the construction site; once a parameter deviation is detected, the system will immediately start the adaptive adjustment algorithm to automatically adjust the jacking force F jacking and other construction parameters in response to changes in construction conditions.

9. The long distance pipe jacking tunnel construction method based on three-dimensional stability analysis according to claim 1 is characterized in that: A detailed three-dimensional geological model including the superstructure is established using numerical simulation software. In the model, the weight, distribution and mechanical behavior of the superstructure interacting with the tunnel are simulated to calculate the additional stress σ caused by the superstructure. additional ; At the same time, monitoring points are arranged at the construction site, and monitoring equipment such as stress gauges, displacement gauges and inclinometers are installed; These devices can monitor in real time the actual impact of the superstructure on the tunnel construction area, including the earth pressure σ soil , support reaction force F support and formation displacement δ ground； ; Through comparative analysis of numerical simulation results and field monitoring data, the impact of additional stress on the superstructure on construction stability is evaluated.

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