Method for predicting soil displacement caused by double-line shield construction based on number-object fusion

Abstract

The invention relates to a method for predicting soil displacement caused by double-line shield construction based on number-object fusion. Comprising the steps of establishing a finite element numerical model based on shield parameters and geological data; numerical model parameters are corrected through actual monitoring data, the double-line shield distance, the advancing speed difference and the soil displacement field evolution law are analyzed, and dynamic visual prediction of the displacement field at different construction stages is achieved. According to the method, a two-way feedback mechanism of numerical simulation and engineering actual monitoring data is constructed, a three-dimensional dynamic coupling analysis method is innovatively provided, and the problem of insufficient prediction precision caused by dynamic change of soil parameters and a double-line construction coupling effect in traditional construction is solved. Through iterative optimization of a digital model and measured data, the maximum displacement error of a soil body is further reduced, the stratum standard-exceeding deformation risk is predicted in advance, the quantitative evaluation problem of the stratum disturbance superposition effect in double-line shield construction is effectively solved, and intelligent decision support is provided for tunnel construction safety control in a complex urban environment.

Description

Technical Field

[0001] The present invention relates to the field of tunnel engineering, and in particular to a method for predicting soil displacement caused by double-line shield construction based on the fusion of mathematics and physics. Background Art

[0002] With the increasing density of urban underground space development, dual-track parallel shield tunnels are gaining widespread application in projects such as subways and integrated utility corridors due to their high space utilization and construction efficiency. However, the combined effects of soil displacements caused by dual-track shield construction are significantly more complex than those under single-track conditions. Specifically, the initial stress field of the strata is redistributed during the construction of the leading tunnel, and the superposition of disturbance waves during the advancement of the trailing tunnel induces asymmetric displacements. Soil parameters evolve dynamically with the construction process, and the coupled effects of the dual-track shield machine operating parameters further exacerbate the nonlinear characteristics of the spatial evolution of the displacement field.

[0003] Patent CN 106126775 B proposes a method for analyzing soil displacement caused by shield construction in a dual-track tunnel. This method combines analytical methods with finite difference software to estimate and simulate the settlement caused by construction. It provides a static estimate of soil displacement but fails to reflect the dynamic characteristics of the disturbance source that evolves over time during shield advancement.

[0004] Patent CN 111914334 A proposes a method for calculating soil deformation caused by dual-track shield construction in saturated soil, taking into account multiple factors. By deriving a series of analytical deformation formulas, this method estimates the displacement caused by various disturbance sources during shield construction, making it suitable for analyzing construction conditions in saturated soils. However, this displacement prediction is based solely on theoretical derivation and calculations, failing to effectively incorporate field monitoring data and lacking a model correction mechanism. Summary of the Invention

[0005] The purpose of this application is to provide a method for predicting soil displacement caused by double-line shield construction based on the fusion of mathematics and physics, aiming to solve the problems existing in the existing technology.

[0006] The present application provides a method for predicting soil displacement caused by dual-line shield construction based on the fusion of mathematics and physics, including the following steps: S1. Establish a numerical model. Based on the construction parameters of the double-line shield machine and geological survey data, a three-dimensional finite element numerical model including the shield machine geometry model, segment model, and soil mesh is constructed. The Moore-Coulomb criterion is used to describe the elastic-plastic behavior of the soil. S2. Deploy a sensor network to obtain real-time monitoring data. The sensor network collects soil stress, displacement, and shield machine operating parameters during the construction process in real time. The shield machine operating parameters include cutterhead thrust, grouting pressure, and propulsion speed. S3, correcting the numerical model with real-time monitoring data; performing dynamic parameter feedback correction on the real-time monitoring data in step S2 and the numerical model in step S1, optimizing the soil elastic modulus, Poisson's ratio, and permeability coefficient of the model and updating them in real time to generate an updated high-precision numerical model; S4. Simulate the superposition effect of volume disturbances in the leading and trailing tunnels during twin-track shield construction using a high-precision numerical model, analyze the impact of advancement speed differences and grouting lag time on the spatiotemporal evolution of the displacement field, and output soil displacement cloud maps and maximum settlement predictions for future construction phases. S5. Based on the coupling of displacement field, seepage field and stress field, a soil displacement prediction model is constructed that integrates current monitoring data and simulation predictions. The soil displacement evolution trend is output and multi-level settlement risk thresholds are set. When the predicted value exceeds the threshold, an early warning is triggered. S6. Repeat steps S3 to S5 to improve prediction accuracy through iterative optimization of monitoring data and models.

[0007] In step S1, the construction parameters include the shield machine propulsion speed and grouting pressure; the geological survey data include soil distribution and physical and mechanical indicators; and the Moore-Coulomb criterion is used to describe and characterize the soil distribution data.

[0008] In step S2, the sensor network is deployed as follows: earth pressure gauges, displacement gauges, and pore water pressure sensors are deployed along the axis of the double-track tunnel; a three-dimensional digital level and a total station group are arranged in the key disturbed areas of the soil between the tunnels to synchronously monitor horizontal and vertical displacements; and earth pressure gauges are used to obtain real-time grouting pressure diffusion range and soil stress redistribution data during the shield tail release stage.

[0009] In step S3, the real-time monitoring data and the numerical model are fed back and corrected by formula (1): Formula (1) Among them, X α To modify the model parameters, including elastic modulus E, Poisson's ratio ν and permeability coefficient k; X β is the numerical model parameter of step S1; H A is the actual observed value; H B is the numerical simulation value.

[0010] The soil displacement prediction model is shown in formula (2): Formula (2) Among them, H P is the model prediction value; H B is the numerical simulation value; P is the pore water pressure; σ is the soil pressure; θ is the empirical coefficient.

[0011] In step S5, the warning levels are divided into: Orange warning: soil displacement rate 5-8 mm / h; Red alert: soil displacement rate > 8 mm / h.

[0012] In step S6, the target displacement prediction error rate is calculated using formula (3): Formula (3) Among them, ε （t） is the displacement prediction error rate; H A is the actual observed value; H P is the model prediction value; the soil displacement prediction error rate is controlled to be ≤10%.

[0013] The beneficial effects of the present invention are: 1. The present invention expands the traditional Mohr-Coulomb model from a static parameter system to a time-varying model that integrates "geological initial values ​​and dynamic construction corrections", effectively breaking through the bottleneck of traditional models in characterizing the evolution of soil states. Compared with existing technologies, the present invention constructs a complete three-dimensional finite element model, combines measured construction parameters such as propulsion speed and grouting pressure, dynamically simulates the superposition effect of construction disturbances, and can more realistically restore the construction process. The present invention introduces data assimilation technology, integrates multi-source monitoring data such as levels, total stations, and earth pressure gauges, and corrects key parameters in the model in real time, effectively improving the accuracy and adaptability of the prediction model.

[0014] 2. This invention achieves a coordinated calibration between strength parameters and construction disturbances, resolving the difficulty in quantifying the dual-line coupling effect. On this basis, the physical model provides an interpretable prediction baseline, while the data-driven model further exploits the nonlinear characteristics of the residuals. This enables 48-hour advance deformation warning, promoting a shift in construction safety control from "passive monitoring" to "active regulation," and providing real-time decision support for scenarios such as tunnels crossing existing structures and sensitive buildings in densely populated urban areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 Flow chart of the method of the present invention.

[0016] Figure 2 It is a three-dimensional finite element numerical model of a double-line shield tunnel model.

[0017] Figure 3 This is the layout diagram of monitoring points in the sensor network.

[0018] Figure 4 Schematic diagram for comparison between the method of the present invention and measured data. DETAILED DESCRIPTION

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0020] like Figure 1 The method for predicting soil displacement caused by double-line shield construction based on the integration of mathematics and physics is shown, which includes the following steps: S1. Establish a numerical model. Based on the double-line shield construction parameters and geological survey data, a three-dimensional finite element numerical model is constructed. Figure 2 As shown in the figure, a 3D finite element numerical model was constructed using ABAQUS software, including the shield machine geometry, segment model, and soil mesh. Input construction parameters included the shield machine propulsion speed and grouting pressure. Geological survey data included soil distribution and physical and mechanical properties.

[0021] The Moore-Coulomb criterion was used to describe the soil's elastic-plastic behavior. The boundary conditions and loading sequence simulated followed the actual construction phase. The initial surrounding rock parameters for different soil types are shown in Table 1. The lining and grouting layers were simulated using an elastic constitutive model; specific parameters are shown in Table 2.

[0022] S2. Deploy sensor networks to obtain real-time monitoring data. By deploying sensor networks, soil stress, displacement, and shield machine operating parameters are collected in real time during the construction process. Shield machine operating parameters include cutter head thrust, grouting pressure, and propulsion speed. Figure 3 As shown in the figure, the sensor network is deployed as follows: earth pressure gauges, displacement gauges, and pore water pressure sensors are deployed along the axis of the double-track tunnel, and the monitoring data are synchronized to the cloud analysis platform in real time via wireless transmission. A three-dimensional digital level and total station set with an instrument rating of ≤0.3 mm / km are deployed in the key disturbed areas of the soil between the tunnels to simultaneously monitor horizontal and vertical displacements. Earth pressure gauges are used to obtain real-time data on the grouting pressure diffusion range and soil stress redistribution during the shield tail release stage. The earth pressure gauge range is 0-1 MPa and the accuracy is ±0.5%.

[0023] S3. Using data assimilation technology, the real-time monitoring data in step S2 and the numerical model in step S1 are dynamically fed back and corrected, as shown in formula (1). The soil elastic modulus, Poisson's ratio, and permeability coefficient of the model are optimized. The model parameters are updated every time one ring of segments (1.6 m) is advanced to generate an updated high-precision numerical model.

[0024] Formula (1) Among them, Xα To modify the model parameters, including elastic modulus E, Poisson's ratio ν and permeability coefficient k; X β is the numerical model parameter of step S1; H A is the actual observed value; H B is the numerical simulation value.

[0025] S4. Based on the revised high-precision numerical model, simulate the soil disturbance superposition effect of the leading and trailing tunnels during twin-track shield construction, analyze the influence of the advancement speed difference and grouting lag time on the spatiotemporal evolution of the displacement field, and output soil displacement cloud maps and maximum settlement predictions for future construction phases; S5. Based on the coupling of displacement field, seepage field and stress field, the current monitoring data and simulation prediction are integrated, and an adaptive soil displacement prediction model for the construction phase is constructed through formula (2), such as Figure 4 As shown in the figure, the model's predicted values ​​are closer to the measured values, and the model then outputs the soil displacement evolution trend within the next 48 hours. It also sets multiple settlement risk thresholds. When the predicted value exceeds the threshold, an early warning is triggered, and a construction parameter optimization plan is generated and fed back to the shield operation system. Formula (2) Among them, H P is the model prediction value; H B is the numerical simulation value; P is the pore water pressure; σ is the soil pressure; θ is the empirical coefficient. In this embodiment, θ1 is 0.05421 and θ2 is 0.07528. B As the main variable, a soil displacement prediction model is established.

[0026] The warning levels are: Orange warning: soil displacement rate 5-8 mm / h; Red alert: soil displacement rate > 8 mm / h.

[0027] S6. Repeat steps S3 to S5 to improve prediction accuracy through iterative optimization of monitoring data and models. Calculate the target displacement prediction error rate using formula (3), control the soil displacement prediction error rate to ≤10%, and dynamically adjust construction parameters to minimize construction disturbance and optimize ground stability.

[0028] Formula (3) Among them, ε （t） is the displacement prediction error rate; H A is the actual observed value; H P The model predicted value was repeated 27 times in this embodiment, and the error rate was less than 10%, which met the engineering requirements.

[0029] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention. Therefore, the embodiments should be considered in all respects as exemplary and non-restrictive.

Claims

1. A method for predicting soil displacement caused by double-line shield construction based on the integration of mathematics and physics, characterized by: The following steps are involved: S1. Establish a numerical model; construct a three-dimensional finite element numerical model based on the double-line shield construction parameters and geological survey data; S2. Deploy a sensor network to obtain real-time monitoring data. The sensor network collects soil stress, displacement, and shield machine operating parameters during the construction process in real time. The shield machine operating parameters include cutterhead thrust, grouting pressure, and propulsion speed. S3, correcting the numerical model with real-time monitoring data; performing dynamic parameter feedback correction on the real-time monitoring data in step S2 and the numerical model in step S1, optimizing the soil elastic modulus, Poisson's ratio, and permeability coefficient of the model and updating them in real time to generate an updated high-precision numerical model; S4. Simulate the superposition effect of volume disturbances in the leading and trailing tunnels during twin-track shield construction using a high-precision numerical model, analyze the impact of advancement speed differences and grouting lag time on the spatiotemporal evolution of the displacement field, and output soil displacement cloud maps and maximum settlement predictions for future construction phases. S5. Based on the coupling of displacement field, seepage field and stress field, a soil displacement prediction model is constructed that integrates current monitoring data and simulation predictions. The soil displacement evolution trend is output and multi-level settlement risk thresholds are set. When the predicted value exceeds the threshold, an early warning is triggered. S6. Repeat steps S3 to S5 to improve prediction accuracy through iterative optimization of monitoring data and models.

2. The method for predicting soil displacement caused by double-line shield construction based on the fusion of mathematics and physics according to claim 1 is characterized in that: The three-dimensional finite element numerical model in step S1 includes a shield machine geometric model, a segment model, and a soil mesh; The input construction parameters include the shield machine propulsion speed and grouting pressure; the geological survey data include soil distribution and physical and mechanical indicators; the Moore-Coulomb criterion is used to describe and characterize the elastic-plastic behavior of the soil.

3. The method for predicting soil displacement caused by double-line shield construction based on the fusion of mathematics and physics according to claim 1 is characterized in that: In step S2, the sensor network is deployed as follows: earth pressure gauges, displacement gauges, and pore water pressure sensors are deployed along the axis of the double-track tunnel; a three-dimensional digital level and total station are arranged in the key disturbed areas of the soil between the tunnels to simultaneously monitor horizontal and vertical displacements; The soil pressure gauge is used to obtain the grouting pressure diffusion range and soil stress redistribution data in real time during the shield tail release stage.

4. The method for predicting soil displacement caused by double-line shield construction based on the fusion of mathematics and physics according to claim 1 is characterized in that: In step S3, the real-time monitoring data and the numerical model are fed back and corrected by formula (1): Formula (1) Among them, X α To modify the model parameters, including elastic modulus E, Poisson's ratio ν and permeability coefficient k; X β is the numerical model parameter of step S1; H A is the actual observed value; H B is the numerical simulation value.

5. The method for predicting soil displacement caused by double-line shield construction based on the fusion of mathematics and physics according to claim 1 is characterized in that: In step S5, the soil displacement prediction model is shown in formula (2): Formula (2) Among them, H P is the model prediction value; H B is the numerical simulation value; P is the pore water pressure; σ is the soil pressure; θ is the empirical coefficient.

6. The method for predicting soil displacement caused by double-line shield construction based on the fusion of mathematics and physics according to claim 1 is characterized in that: In step S5, the warning levels are divided into: Orange warning: soil displacement rate 5-8 mm / h; Red alert: soil displacement rate > 8 mm / h.

7. The method for predicting soil displacement caused by double-line shield construction based on the fusion of mathematics and physics according to claim 1 is characterized in that: In step S6, the target displacement prediction error rate is calculated using formula (3): Formula (3) Among them, ε （t） is the displacement prediction error rate; H A is the actual observed value; H P is the model prediction value; the soil displacement prediction error rate is controlled to be ≤10%.

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