A method and system for assessing the risk of machine jamming in the after-sales systems of a tunnel boring machine.

Abstract

This invention relates to the field of tunnel boring machine (TBM) technology, specifically a method and system for assessing the risk of TBM jamming in its supporting systems. The method includes establishing a surrounding rock mechanics model; loading the face support effect, initial lining support effect, and the reserved space between the supporting systems and the initial lining as boundary conditions into the surrounding rock mechanics model; advancing the tunneling process in a time-incremental manner; calculating the convergence response of the lining / support components based on the stiffness and installation status of the current support components; comparing the obtained convergence differences; repeating the steps until a preset termination condition is reached; comparing the maximum convergence value obtained from the time-series calculation with the reserved space between the supporting systems and the initial lining, determining and outputting a jamming risk warning. This invention achieves dynamic coupling calculation of tunnel convergence and support pressure through numerical iteration, thereby significantly improving the accuracy of risk assessment and the reliability of construction control.

Description

Technical Field

[0001] This invention relates to the field of tunnel boring machine technology, and specifically to a method and system for assessing the risk of machine jamming in the downstream systems of a tunnel boring machine. Background Technology

[0002] When tunnel boring machines (TBMs) operate in weak surrounding rock or high-stress strata, they often face problems such as significant rock convergence, support system failure, and jamming of auxiliary systems. Existing risk assessment methods mostly rely on empirical judgment or single elasticity models, failing to comprehensively consider the time-varying deformation characteristics of the surrounding rock, the spatial effects at the tunnel face, and the progressive stress process of the initial lining components. For example, some methods estimate support requirements solely through static equilibrium analysis, without incorporating time factors and creep effects into the calculations, thus failing to accurately reflect the convergence evolution of the surrounding rock under long-term shutdown or low tunneling rates. On the other hand, the space reserved between the auxiliary systems and the initial lining in the construction design often lacks dynamic verification. When the surrounding rock converges beyond the reserved space, the auxiliary equipment is highly prone to jamming, but current technologies mostly rely on empirical assumptions to determine this process, lacking precise calculation methods for iterative solutions. Furthermore, traditional models often fail to integrate the spatial support effect provided by the unexcavated rock mass at the tunnel face with the stiffness evolution process of different lining components (such as steel arches, shotcrete, and anchor bolts) into a single calculation framework, resulting in significant bias in risk assessment.

[0003] In summary, existing technologies lack a comprehensive calculation method that can simultaneously consider the time-varying characteristics of the surrounding rock viscoelastic-plastic properties, the spatial effect of the tunnel face, the lining support effect, and the construction conditions when assessing the risk of TBM-related system jamming. This results in insufficient accuracy of the prediction results and fails to provide reliable risk warnings and parameter optimization basis for construction. Summary of the Invention

[0004] To address the problems in existing tunnel boring machine (TBM) construction, such as insufficient characterization of the time-varying deformation characteristics of the surrounding rock, incomplete consideration of the spatial support effect at the tunnel face and the supporting role of the initial lining, and lack of a quantitative criterion-based method for predicting the risk of jamming in the subsequent supporting systems, which leads to risk assessment relying on experience and lacking accuracy, making it difficult to provide a reliable basis for construction control in a timely manner, this invention proposes a method and system for assessing the risk of jamming in the subsequent supporting systems of a TBM.

[0005] This invention is achieved through the following technical solution:

[0006] A method for assessing the risk of machine jamming in the downstream systems of a tunnel boring machine includes the following steps:

[0007] S1. Establish a surrounding rock mechanics model to characterize the functional relationship between the deformation characteristics of the surrounding rock and the support pressure under time evolution;

[0008] S2. The spatial support effect of the working face, the initial lining support effect, and the reserved space between the subsequent supporting system and the initial lining are loaded into the surrounding rock mechanics model as boundary conditions of the model.

[0009] S3. Advance the tunneling process in a time increment manner, and calculate the surrounding rock convergence increment based on the current support pressure and the surrounding rock mechanics model in each time step;

[0010] S4. Calculate the convergence response of the lining / support components based on the current stiffness and installation status of the supporting components;

[0011] S5. Compare the convergence difference obtained in step S3 and step S4, and update the support pressure based on the difference. Use numerical iteration until the convergence error is less than a preset threshold to determine the steady-state convergence and support pressure at this time step.

[0012] S6. Repeat steps S3 to S5 until the preset termination condition is met.

[0013] S7. Compare the maximum convergence value obtained by time series calculation with the reserved space between the subsequent supporting system and the initial lining. When the maximum convergence value exceeds the reserved space, determine and output a machine jam risk warning.

[0014] Furthermore, the surrounding rock mechanics model adopts a viscoelastic-plastic constitutive model to describe the creep characteristics of the surrounding rock and its convergence behavior under different support pressures.

[0015] Furthermore, the spatial support effect at the tunnel face is characterized by virtual support pressure related to the distance to the tunnel face, the tunneling rate, and time, and the support pressure distribution in the model is corrected by this virtual support pressure.

[0016] Furthermore, the initial lining support effect is jointly determined by the equivalent stiffness and maximum allowable convergence value of several support components, including but not limited to steel arches, shotcrete and anchor bolts, and each support component takes effect at its installation position and its stiffness contribution is superimposed sequentially.

[0017] Furthermore, the numerical iteration is an iterative solution based on pressure increment and convergence increment, and the convergence condition is that the convergence difference is less than a preset error threshold, which is a settable numerical parameter.

[0018] Furthermore, when the convergence of the support components reaches their respective maximum allowable convergence values, their equivalent stiffness is set to zero to simulate support failure, and the total stiffness and support pressure of the system are recalculated accordingly.

[0019] Furthermore, it also includes determining a critical value for the tunneling rate based on parameter scanning or sensitivity analysis, such that when the tunneling rate is lower than the critical value, the maximum convergence amount calculated by the surrounding rock mechanics model exceeds the reserved space, and is output as a construction control suggestion.

[0020] This invention also proposes a system for assessing the risk of machine jamming in the downstream systems of a tunnel boring machine, comprising:

[0021] Modeling units are used to establish mechanical models that characterize the evolution of surrounding rocks over time;

[0022] The parameter input unit is used to input geological parameters, support component parameters, reserved space, tunneling rate and shutdown information; the calculation unit is used to calculate the surrounding rock convergence increment and lining convergence increment in each time step with time increment and perform iterative solution to obtain steady-state convergence and support pressure.

[0023] Correction unit, used to correct support pressure based on the spatial effect of the working face;

[0024] The discrimination unit is used to compare the maximum convergence value obtained by the solution with the reserved space and output the card machine risk assessment result and related alarm information.

[0025] The display / storage unit is used to present the timing convergence curve, support pressure distribution, evaluation conclusions, and save calculation records.

[0026] The beneficial effects of this invention are:

[0027] (1) The present invention adopts a viscoelastic-plastic constitutive model, which describes the creep effect and plastic deformation process of the surrounding rock through the time function of equivalent shear modulus and Poisson's ratio. It can not only reflect the instantaneous deformation of the surrounding rock in the short term, but also simulate the convergence amount that gradually accumulates when the machine is stopped or the tunneling is at low speed. It solves the problem that the existing methods cannot reflect long-term deformation. This modeling method ensures the accuracy of risk assessment and provides a solid foundation for long-term stability analysis under construction conditions.

[0028] (2) By introducing virtual support pressure, this invention transforms the spatial support provided by the unexcavated rock mass at the tunnel face into a correction term that varies with time, tunneling rate and tunnel face distance. This is more reasonable than the traditional simplified support assumption and can effectively simulate the inhibitory effect of the tunnel face on the convergence of the surrounding rock under different tunneling speeds, thus avoiding the calculation deviation caused by underestimating the initial support capacity.

[0029] (3) This invention superimposes the stiffness of various support components such as steel arches, shotcrete, and anchor bolts, and considers their installation order and maximum allowable convergence value. When a support component reaches its limit deformation, its equivalent stiffness is automatically set to zero, thereby accurately simulating the dynamic process of support gradually taking effect and failing. Compared with existing methods that assume constant support stiffness, this significantly improves the realism of support effect calculation;

[0030] (4) The present invention adopts the method of time increment advancement and pressure increment iteration. In each time step, the support pressure is corrected by calculating the difference between the convergence of the surrounding rock and the convergence of the lining until the error is less than the preset threshold, which ensures the consistency between the convergence and the support pressure and the stability of the calculation, and avoids the problem of non-convergence or error accumulation caused by a single static solution.

[0031] (5) This invention compares the maximum convergence amount obtained by numerical simulation with the reserved space between the subsequent supporting system and the initial lining. When the maximum convergence amount exceeds the reserved space, it automatically determines that there is a risk of machine jamming and outputs early warning information, avoiding the defect of relying solely on experience values ​​for rough judgment, and realizing the quantification and operability of risk prediction.

[0032] (6) This invention obtains the critical value of the tunneling rate through parameter scanning and sensitivity analysis. That is, when the rate is lower than this, the maximum convergence of the surrounding rock will exceed the reserved space. As a direct suggestion for construction control, it provides a quantitative basis for construction organization and solves the problem that the tunneling rate is traditionally set based solely on experience.

[0033] (7) This invention further proposes a supporting system, including a modeling unit, a parameter input unit, a calculation unit, a correction unit, a discrimination unit, and a display / storage unit, which can realize the entire process of calculation and visualization from parameter input and model solving to result judgment and early warning output. This system can be directly applied on the construction site, supports real-time early warning and data archiving, and improves the level of informatization and intelligence in construction.

[0034] In summary, this invention can comprehensively consider the time-varying characteristics of the viscoelastic-plastic properties of the surrounding rock, the spatial effect of the tunnel face, and the initial lining support. It achieves dynamic coupling calculation of tunnel convergence and support pressure through numerical iteration, and determines the risk of subsequent system jamming using quantitative criteria, thereby significantly improving the accuracy of risk assessment and the reliability of construction control. Attached Figure Description

[0035] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 This invention provides a flowchart of a method for assessing the risk of machine jamming in the downstream systems of a tunnel boring machine.

[0037] Figure 2This is a schematic diagram of a CVISC model for assessing the risk of machine jamming in the downstream systems of a tunnel boring machine, as proposed in this invention.

[0038] Figure 3 This is a diagram illustrating the spatial support effect of the tunnel face during tunnel excavation using the tunnel boring machine proposed in this invention.

[0039] Figure 4 This is a schematic diagram of an open-type tunneling machine with different support components proposed in this invention.

[0040] Figure 5 This is a schematic diagram of the terminal equipment of a system for assessing the risk of machine jamming in the downstream system of a tunnel boring machine, as proposed in this invention.

[0041] Figure 6 This is a schematic diagram of a readable storage medium for a system proposed in this invention for assessing the risk of machine jamming in the downstream systems of a tunnel boring machine;

[0042] In the diagram, 200 is the terminal device, 210 is the memory, 211 is the RAM, 212 is the cache, 213 is the ROM, 214 is the program / utility, 215 is the program module, 220 is the processor, 230 is the bus, 240 is the external device, 250 is the I / O interface, 260 is the network adapter, and 300 is the program product. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0044] Example 1

[0045] refer to Figure 1 This embodiment provides a method for assessing the risk of jamming in the downstream systems of a tunnel boring machine (TBM). In this embodiment, the method is applied to the construction scenario of an open-face TBM in a high-altitude, stress-prone soft-foundation geological condition, such as a mountain tunnel project. This tunnel is a circular tunnel with a diameter of approximately 8.4 meters and a burial depth exceeding 600 meters. The surrounding rock is mainly composed of sandstone and mudstone, facing the risk of large deformation. This method establishes a surrounding rock mechanics model to characterize the functional relationship between the deformation characteristics of the surrounding rock over time and the supporting pressure.

[0046] First, in step S1, a surrounding rock mechanics model is established. This model adopts a viscoelastic-plastic constitutive model to describe the creep characteristics of the surrounding rock and its convergence behavior under different support pressures. Specifically, the surrounding rock mechanics model is the Burgers creep viscoplastic CVISC model, such as... Figure 2The model consists of a Burgers body and a slider, used to simulate viscoelastic and plastic behavior, respectively. The Burgers model is composed of a Maxwell model and a Kelvin model in series, and its equivalent shear modulus and Poisson's ratio are expressed by the following formulas:

[0047]

[0048] Where G(t) is the time-dependent equivalent shear modulus, in units of (Pa), and η M This is the viscosity in Maxwell's model, measured in Pa·s, G. M The shear modulus of the Maxwell model is expressed in Pa, η. K The viscosity expressed in the Kelvin model is measured in Pa·s (G). K It is the shear modulus of the Kelvin model, with units of (Pa).

[0049] This model assumes that the rock mass material is homogeneous and isotropic, following the Mohr-Coulomb failure criterion, where the slider is controlled by the Mohr-Coulomb constitutive model, and its yield criterion is expressed by the formula:

[0050]

[0051] The potential function for using the non-associated flow rule is:

[0052] g = σ θ -K ps σ r (4); where K ps Indicates the coefficient of thermal expansion;

[0053] K ps = (1+sinφ) / (1-sinφ); where φ represents the expansion angle.

[0054] The total strain in the CVISC model consists of viscoelastic and plastic components. According to the Prandtl-Royce flow law for small deformations, the increments of tangential and radial strain around the tunnel can be written as:

[0055]

[0056] Where dε θ , These are the total tangential strain increment, the viscoelastic tangential strain increment, and the plastic tangential strain increment, respectively, dε r , These are the total radial strain increment, the viscoelastic radial strain increment, and the plastic radial strain increment, respectively, with the plastic strain increment shown below:

[0057] in σ is the plastic strain component, λ is the plastic multiple, and σ is the plastic strain component. ij It is a stress component.

[0058] Viscoelastic strain is a deviatoric strain, depending only on the deviatoric stress s. ij Therefore, the equation for viscoelastic strain can be expressed using the formula for the time-dependent equivalent shear modulus:

[0059] Where s ij It is the deviatoric stress component, σ kk K represents the volumetric stress component, and K represents the bulk modulus. It is viscoelastic strain, δ ij It is a ring weight calculation.

[0060] The tangential and radial stresses in the elastic and plastic regions of this model are expressed by formulas:

[0061]

[0062] Where, σ r and σ θ These are radial stress and tangential stress, respectively, with units of (Pa), P i It is the support pressure applied to the excavation boundary, with the unit being Pa, and r representing the radius, with the unit being m; r i The inner radius of the tunnel is represented by r (m). p P0 is the radius of the plastic zone, in meters (m); P0 is the initial in-situ stress, σ rp It is the radial stress at the boundary between the elastic and plastic regions, with units of (Pa); σ c It is uniaxial strength, with units of (Pa). It is the angle of friction. as well as

[0063] The radius of the elastoplastic boundary is calculated using the formula:

[0064]

[0065] The tangential and radial viscoelastic strains around the circular tunnel are solved using formulas:

[0066]

[0067] Where "is" represents the displacement of the rock mass surrounding the tunnel, in meters (m). Substituting formula (9) into formula (12), the displacement within the elastic zone is obtained as follows:

[0068]

[0069] Substituting equation (13) into equation (7), we obtain the tangential and radial plastic strains expressed by equations (14) and (15), respectively:

[0070]

[0071]

[0072] The increment of plastic strain within the plastic region always follows the correlation in formula (17):

[0073]

[0074] Substituting formulas (5) and (6) into formula (16) yields:

[0075]

[0076] Combining formulas (10) and (12), formula (17) can be rewritten as:

[0077]

[0078] Integrating equation (18) and considering the elastoplastic boundary continuity condition u p (r p )=u e (r p Thus, the formula for radial displacement in the plastic zone is obtained:

[0079]

[0080] in

[0081] Let r = r i The convergence of the tunnel can be written as:

[0082]

[0083] In formulas (19) and (22), time and support pressure are the only variables; all other parameters are constants determined by material properties and geometry. The time-varying displacement of the surrounding rock is simulated using the equivalent shear modulus G(t) and Poisson's ratio v(t). This model ensures a functional relationship between the deformation of the surrounding rock and the support pressure, and this functional relationship includes the surrounding rock material parameters and geometric parameters as constant inputs. In this embodiment, the model is verified through numerical simulation and is consistent with the FLAC3D results. The convergence evolution is divided into a primary stage (rapid increase but slowing rate) and a secondary stage (constant rate increase).

[0084] For a certain mountain tunnel, the surrounding rock parameters are set as follows: in this embodiment, the bulk modulus K = 10.0 GPa, and the Maxwell model shear modulus G...M = 4.6 GPa, Maxwell model viscosity η M =4.12×10 5 GPa·s, Kelvin model shear modulus G K =1.0 GPa, Kelvin model viscosity η K =5.12×10 3 GPa·s, friction angle Expansion angle φ = 15°, cohesion c = 2.3 MPa, initial hydrostatic pressure P0 = 30 MPa, tunnel radius r i =4.2m. The above parameters were verified by field data to ensure that the model accurately describes the time-varying deformation of the surrounding rock under plateau stress. For example, creep behavior may account for more than 70% of the total deformation.

[0085] refer to Figure 3 In step S2, the face space support effect, the initial lining support effect, and the reserved space between the subsequent supporting system and the initial lining are loaded into the surrounding rock mechanics model as boundary conditions. Specifically, the face space support effect is characterized by virtual support pressure related to the face distance, tunneling rate, and time, and this virtual support pressure is used as the boundary condition for the model.

[0086] The support pressure distribution in the pseudo-support pressure correction model, this effect is expressed through the coefficient λ. e express:

[0087] Where λ e X is the coefficient of the spatial effect at the tunnel face, where X represents the distance from the tunnel face in meters (m). * In this embodiment, X represents the extent of the spatial effect at the tunnel face. * =3r i The distance X from the working face is calculated using the formula:

[0088] X = Vt (24); where V is the tunneling rate of the TBM, in m / s, and t represents the tunneling time, in seconds. The virtual support pressure is calculated using the formula:

[0089] P a (V, t) = (1-λ) e (V,t))P0 (25); where P a (V, t) is the virtual pressure, and the unit is (Pa).

[0090] The virtual pressure dynamic adjustment simulates the limitation of the tunnel face on the deformation of the surrounding rock and is loaded into the model as a boundary condition to correct the support pressure. In a certain mountain tunnel application, this effect causes the convergence value to start from a non-zero value near the tunnel face and increase significantly as the spatial effect weakens. The initial lining support effect is determined by the equivalent stiffness and maximum allowable convergence value of several support components, including but not limited to steel arches, shotcrete, and anchor bolts. Each support component takes effect at its installation position and its stiffness contribution is superimposed sequentially.

[0091] refer to Figure 4 Specifically, the initial lining consists of a steel arch, shotcrete, and anchor bolts. Installation is divided into L1 and L2 sections. The steel arch is installed at a distance X1 from the working face, and the shotcrete is installed at section L2. The effectiveness of different support components is determined by the support stiffness K and the maximum support pressure P. max and maximum allowable convergence u max Confirmed. For steel arches:

[0092]

[0093] Where K ste This is the supporting stiffness of the steel arch, measured in Pa (E). ste The Young's modulus of steel is expressed in Pa (A). ste It is the cross-sectional area of ​​the steel arch, in meters. 2 ), d represents the longitudinal spacing of the steel arches, in meters (m), h ste P is the height of the steel arch section, in meters (m). max，ste It is the maximum permissible support pressure, in Pa, σ ste，y ε is the yield strength of the steel arch, expressed in Pa. br,ste It is the ultimate strain at the time of destruction.

[0094] For shotcrete:

[0095]

[0096] Where K sho This refers to the support stiffness of shotcrete, measured in Pa (E). con This represents the Young's modulus of concrete, expressed in Pa (v). con t represents the Poisson's ratio of concrete. sho It refers to the thickness of the shotcrete, in meters (m), σ c P is the compressive strength of concrete, measured in Pa. max，sho ε is the maximum allowable support pressure of shotcrete, expressed in Pa. br，sho It is the ultimate strain at the time of destruction.

[0097] For anchor bolts:

[0098]

[0099] u max,bol =u in,bol +ε br,ste L bol (34);

[0100] Where K bol This refers to the support stiffness of the anchor bolt, measured in Pa (L). bol This indicates the length of the anchor bolt, in meters (m), s t and S l These represent the circumferential and longitudinal spacing of the anchor bolts, respectively, in meters (m). Φ is the diameter of the anchor bolt, also in meters (m). ste P represents the Young's modulus of steel, measured in Pa. Q represents the load-deformation characteristic constant, measured in m / N. max，bol This indicates the maximum permissible support pressure, expressed in Pa (T). max It is the yield strength of the anchor-rock system, measured in Pa (ε). br，ste It is the ultimate strain at the time of failure, u max，bol It is the maximum allowable convergence of the anchor bolt.

[0101] In this embodiment, the parameters are set as follows:

[0102] Steel frame parameters:

[0103] E ste =206 GPa, A ste =3.95×10 -3 m 2 d = 0.5m, h ste =0.2m, σ ste，y =345MPa;

[0104] Shotcrete parameters:

[0105] E con =16.5GPa, v con =0.2, t sho =0.2m, σ c =30MPa;

[0106] Anchor bolt parameters:

[0107] S t =1.25m, S l =1.25m, Φ=0.025m, E bol =200GPa, T max =150kN;

[0108] The total stiffness of multiple supporting members is determined by the formula:

[0109]

[0110] Where K s，tot It is the total stiffness of the multi-support system, expressed in Pa (K). s，j u is the stiffness of the supporting member j, expressed in Pa. in，j It is the tunnel convergence amount during the installation of supporting component j, with units of (m). The function H(x) is defined as follows:

[0111]

[0112] Given the stiffness of the support system, the support pressure of the system can be calculated using the following formula:

[0113] ΔP s =K s，tot Δu i / r i (37);

[0114] If any support system fails, its supporting effect will be lost; therefore, the maximum convergence of the tunnel will be determined by the minimum u in the support system. max，j The decision is as shown in formula (38):

[0115] u max，tot =min[u max，j (38);

[0116] The maximum support pressure is then estimated using formula (39):

[0117] P max,tot =∑ j p s，j (39);

[0118] The reserved space Δr between the post-supporting system and the initial lining g As a boundary condition, it is set as Δr in this embodiment. g =0.35m (considering the initial lining thickness), used for subsequent judgment, when the tunnel convergence exceeds Δr g When a machine freezes, the determination is described by the following formula:

[0119] Δr g >u i,max (40);

[0120] Where Δr g This represents the minimum reserved space between equipment and supporting components in the backup section, expressed in meters (m). i，max This represents the maximum convergence amount entering the TBM segment, expressed in meters (m).

[0121] In step S3, the tunneling process is advanced in time increments. Within each time step, the surrounding rock convergence increment is calculated based on the current support pressure and the surrounding rock mechanics model. Specifically, the time step Δt is set to 1 hour or adjusted according to accuracy, and the tunneling process is advanced using the following formula:

[0122] t n+1 =t n +Δt (41);

[0123] X n+1 =f(V,t) n+1 (42);

[0124] Where X n+1 V is the tunneling distance, in meters (m), and V is the tunneling rate, in meters per day (m / day).

[0125] The convergence increment of the surrounding rock is calculated using the formula:

[0126]

[0127] in and The partial derivative from formula (22) is an increment based on the time increment and the pressure increment. In this embodiment, this step simulates a tunneling scheme that includes periodic excavation and shutdown, where the exposure time of the surrounding rock affects creep behavior, causing the convergence increment to increase rapidly near the tunnel face.

[0128] In step S4, the convergence response of the lining / support member is calculated based on the current stiffness and installation state of the support member. Specifically, the convergence increment of the lining is determined by the formula:

[0129]

[0130] Where K s，tot From formula (35), considering the sequential installation of support components and the superposition of stiffness, if the convergence reaches u max，j If the support component fails, its equivalent stiffness is set to zero to simulate support failure, and the total stiffness and support pressure of the system are recalculated accordingly. For example, when the steel arch fails at X>125m, the stiffness is set to zero and the support pressure is adjusted accordingly.

[0131] In this embodiment, the response matches the field data, and the convergence rate after installation decreases from 25 mm / day to 2.5 mm / day.

[0132] In step S5, the convergence difference obtained in steps S3 and S4 is compared, and the support pressure is updated based on this difference. Numerical iteration is used until the convergence error is less than a preset threshold to determine the steady-state convergence and support pressure at that time step. Specifically, the convergence difference is calculated using the formula:

[0133]

[0134] The numerical iteration is an iterative solution based on pressure increment and convergence increment. The convergence condition is that the convergence difference is less than a preset error threshold. The error threshold is a settable numerical parameter; in this embodiment, the threshold is set to 10. -5 (Corresponding to a 1% error within a 1mm accuracy range), when R < 10 -5 At that time, the support and resistance levels are updated using the formula:

[0135] P s，n+1 =P s，n +ΔP s (46);

[0136] Virtual pressure and total support pressure are expressed by the formula:

[0137] P i，n+1 =P a，n+1 +P s，n+1 (47);

[0138] The convergent displacement is expressed by the formula:

[0139] u i，n+1 =u i，n +K s，tot Δu i，n+1 (P s，n , t n ΔP s ,Δt) (48);

[0140] Where P s，n+1 P represents the support and resistance levels at the current time step, expressed in Pa. a，n+1 This represents the virtual pressure under the tunnel face effect, expressed in Pa (u). i，n+1 It is the convergence amount at the current time step, in units of (m). This iterative process ensures the coupled solution of the convergence amount and the support pressure. In this embodiment, the support pressure drops from 20MPa at the working face to a lower level and then rises back.

[0141] In step S6, steps S3 to S5 are repeated until a preset termination condition is reached. In this embodiment, the termination condition is that the simulation time reaches 600 days or convergence stabilizes. The process is repeated to generate a time-series convergence curve, for example, the maximum convergence amount reaches u. i，max =0.38m.

[0142] In step S7, the maximum convergence value obtained from the time-series calculation is compared with the reserved space between the subsequent supporting system and the initial lining. When the maximum convergence value exceeds the reserved space, a machine jam risk warning is determined and output. Specifically, formula (40) is used for the determination:

[0143] Δu max (t)≥Δr g If this condition is met, the system outputs a jamming risk warning. For example, this warning can be triggered under specific tunneling rate conditions. This method also includes determining a critical value for the tunneling rate based on parameter scanning or sensitivity analysis. That is, when the tunneling rate is lower than this critical value, the maximum convergence amount calculated by the surrounding rock mechanics model exceeds the reserved space, thus serving as a criterion for construction control.

[0144] In this embodiment, by scanning parameters at different tunneling rates, the corresponding critical tunneling rate can be determined. When the tunneling rate is lower than this value, the risk of machine jamming increases significantly. Simultaneously, under long-term shutdown conditions, model calculations show that the convergence amount will continue to increase, eventually exceeding the reserved space and triggering a warning. Furthermore, the installation positions of anchor bolts and shotcrete have an impact on the convergence process. When the installation of lining components is delayed, the increasing trend of convergence is more significant. Therefore, the timing of component installation should be reasonably arranged based on model results. For steel arch support, calculation results show that increasing its stiffness has a limited impact on overall convergence control. However, when the steel arch yields, numerical simulations show that its internal forces tend to stabilize, the support bearing capacity decreases, and the convergence can easily expand further.

[0145] The method not only provides the dynamic evolution trend of machine jamming risk through numerical calculation, but also outputs construction control conditions by combining parameter analysis, including the safety range under different tunneling rates, the risk evolution law of long-term shutdown, and the rationality judgment of the timing arrangement of support components.

[0146] Example 2

[0147] Based on the method proposed in Embodiment 1, this embodiment also provides a system for assessing the risk of machine jamming in the downstream systems of a tunnel boring machine. This system is implemented through a combination of hardware and software, and mainly consists of a modeling unit, a parameter input unit, a calculation unit, a correction unit, a discrimination unit, and a display / storage unit. The units are coupled through a data bus or software interface to ensure efficient data transmission and retrieval in various processing stages within the system.

[0148] First, the modeling unit is used to establish a mechanical model characterizing the evolution of the surrounding rock over time. This unit calls the preset viscoelastic-plastic constitutive relation and uses time-dependent parametric functions to characterize the stress-strain evolution law of the surrounding rock. The model is based on the CVISC-type model and uses series and parallel viscous and elastic elements to reflect the instantaneous deformation and time-dependent creep effect of the surrounding rock. During the modeling process, the modeling unit calls formulas (1) to (22) to gradually complete the derivation and calculation of elastic modulus, viscous parameters, Poisson's ratio and equivalent modulus. Specifically, this unit executes step S1, outputs a mathematical expression that can characterize the response of the surrounding rock under time-series loading, forms a complete mechanical model framework, and provides a unified model interface for subsequent calculation units.

[0149] Secondly, the parameter input unit is used to input various engineering parameters required for the calculation. This unit supports geological parameter input, including the initial stress state of the surrounding rock, stratum distribution characteristics, and mechanical parameters; support component parameter input, including anchor bolt arrangement, steel arch stiffness, and shotcrete thickness; construction condition parameter input, including tunneling rate, downtime, face location, and installation location of subsequent supporting systems; in addition, it also includes the input of reserved space, used for comparison and judgment with the calculated convergence. The design of the parameter input unit ensures that the system can cover the calculation needs under various working conditions. The input data can be completed through manual entry, database retrieval, or real-time transmission from on-site monitoring equipment, and stored in a unified format for subsequent calculation.

[0150] After the parameters are input, the calculation unit is responsible for simulating the convergence process of the surrounding rock in a time increment manner. This unit implements steps S3 to S6, calculating the convergence increment of the surrounding rock and the convergence increment of the lining at each time step, and then iteratively solving the convergence equilibrium state and the evolution process of the support pressure. The core of the calculation unit calls formulas (41) to (48), updates the distribution of the stress field and displacement field in each iteration cycle, and determines whether the convergence condition has been met. When the convergence condition is met, the calculation unit outputs the steady-state convergence value and the corresponding support pressure curve. The implementation of this unit ensures the continuity and timeliness of the calculation process, and can reflect the coupled deformation process of the surrounding rock and support under different tunneling rates and different shutdown conditions.

[0151] To improve the accuracy of the calculation results, a correction unit is set up in the system. This unit is used to correct the support pressure based on the spatial effect of the tunnel face. In actual construction, the spatial effect of the tunnel face causes changes in the stress state of the surrounding rock, which cannot be accurately reflected by relying solely on one-dimensional or two-dimensional models. Therefore, the correction unit calls formulas (23) to (25) to add the tunnel face influence factor when calculating the support pressure, thereby correcting the pressure distribution. The output of the correction unit can more accurately reflect the stress release and support bearing capacity of the surrounding rock near the tunnel face, making the overall calculation results closer to the actual engineering conditions.

[0152] After the convergence calculation and pressure correction are completed, the discrimination unit plays a crucial role. This unit compares the calculated maximum convergence value with the reserved space and performs logical discrimination based on formula (40). If the maximum convergence value is greater than or equal to the reserved space, it is determined that there is a risk of machine jamming, and the risk assessment result and alarm information are output; if the critical condition is not reached, the output is a safe state. The discrimination unit not only provides the final risk conclusion, but also stores the risk level and triggering conditions together to form a standardized discrimination logic, so as to facilitate rapid comparison and application during construction.

[0153] Finally, the display / storage unit presents the system's calculation results and evaluation conclusions. This unit outputs time-series convergence curves, support pressure evolution distribution, face correction results, and jamming risk assessment results in the form of charts or reports, allowing construction or design personnel to intuitively obtain key information. Simultaneously, the display / storage unit has historical data storage capabilities, completely archiving the parameters input for each calculation, intermediate results of the model calculation, and the final assessment conclusions. Archived data can be retrieved for subsequent construction scheme optimization or risk review, forming a systematic engineering database.

[0154] The system provided in this embodiment for assessing the risk of machine jamming in the supporting systems of a tunnel boring machine (TBM) can achieve a closed-loop process of modeling, parameter input, iterative calculation, face correction, risk identification, and result storage within a unified framework. Through this system, the convergence and support response relationships can be quickly obtained under different geological conditions and construction scenarios. Based on the comparison between convergence and reserved space, a jamming risk conclusion is output, thereby providing scientific risk identification and assessment support for subsequent tunneling construction.

[0155] Example 3

[0156] refer to Figure 5 Based on Example 1, this example proposes a terminal device for assessing the risk of machine jamming in the supporting system of a tunnel boring machine. The terminal device 200 includes at least one memory 210, at least one processor 220, and a bus 230 connecting different platform systems.

[0157] The memory 210 may include a readable medium in the form of volatile memory, such as RAM 211 and / or cache memory 212, and may further include ROM 213.

[0158] The memory 210 also stores a computer program that can be executed by the processor 220. This allows the processor 220 to execute any of the above-described applications of a system for assessing the risk of machine jamming in the downstream systems of a tunnel boring machine. The specific implementation and technical effects are consistent with those described in the above-described application embodiments, and some details will not be repeated here. The memory 210 may also include a program / utility 214 having at least one set of program modules 215. Such program modules include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment.

[0159] Accordingly, processor 220 can execute the aforementioned computer program, as well as executable program / utility 214.

[0160] Bus 230 can represent one or more of several types of bus structures, including a memory bus or memory controller, peripheral bus, graphics acceleration port, processor, or a local bus using any of the various bus structures.

[0161] Terminal device 200 can also communicate with one or more external devices 240, such as keyboards, pointing devices, Bluetooth devices, etc., and with one or more devices capable of interacting with it, and / or with any device that enables it to communicate with one or more other computing devices (e.g., routers, modems, etc.). This communication can be performed via I / O interface 250. Furthermore, terminal device 200 can communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via network adapter 260. Network adapter 260 can communicate with other modules of terminal device 200 via bus 230. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with terminal device 200, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms.

[0162] Example 4

[0163] This embodiment proposes a computer-readable storage medium for assessing the risk of jamming in the downstream systems of a tunnel boring machine. The computer-readable storage medium stores instructions that, when executed by a processor, implement any of the above-mentioned systems for assessing the risk of jamming in the downstream systems of a tunnel boring machine. The specific implementation method and the technical effects achieved are consistent with those described in the above-mentioned application embodiments, and some details will not be repeated.

[0164] Figure 6The present embodiment illustrates a program product 300 for implementing the above-described applications. This product may employ a portable compact disc read-only memory (CD-ROM) and include program code, and may run on a terminal device, such as a personal computer. However, the program product 300 of the present invention is not limited thereto. In this embodiment, the readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device. The program product 300 may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0165] Computer-readable storage media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable storage medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof. Program code for performing operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on a user computing device, partially on a user device, as a standalone software package, partially on a user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing devices can be connected to user computing devices via any type of network, including local area networks (LANs) or wide area networks (WANs), or they can be connected to external computing devices (e.g., via the Internet using an Internet service provider).

[0166] The foregoing has shown and described 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 to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A method for assessing the risk of machine jamming in the downstream systems of a tunnel boring machine, characterized in that, Includes the following steps: S1. Establish a surrounding rock mechanics model to characterize the functional relationship between the deformation characteristics of the surrounding rock and the support pressure under time evolution; S2. The spatial support effect of the working face, the initial lining support effect, and the reserved space between the subsequent supporting system and the initial lining are loaded into the surrounding rock mechanics model as boundary conditions of the model. S3. Advance the tunneling process in a time increment manner, and calculate the surrounding rock convergence increment based on the current support pressure and the surrounding rock mechanics model in each time step; S4. Calculate the convergence response of the lining / support components based on the current stiffness and installation status of the supporting components; S5. Compare the convergence difference obtained in step S3 and step S4, and update the support pressure based on the difference. Use numerical iteration until the convergence error is less than a preset threshold to determine the steady-state convergence and support pressure at this time step. S6. Repeat steps S3 to S5 until the preset termination condition is met. S7. Compare the maximum convergence value obtained by time series calculation with the reserved space between the subsequent supporting system and the initial lining. When the maximum convergence value exceeds the reserved space, determine and output a machine jam risk warning. The surrounding rock mechanical model adopts a viscoelastic-plastic constitutive model to describe the creep characteristics of the surrounding rock and its convergence behavior under different support pressures. The spatial support effect at the tunnel face is characterized by virtual support pressure related to the distance to the tunnel face, tunneling rate, and time, and the support pressure distribution in the model is corrected by this virtual support pressure. The initial lining support effect is determined by the equivalent stiffness and maximum allowable convergence value of several support components, including steel arches, shotcrete and anchor bolts. Each support component takes effect at its installation position and its stiffness contribution is superimposed sequentially.

2. The method for assessing the risk of machine jamming in the downstream systems of a tunnel boring machine according to claim 1, characterized in that, The numerical iteration is an iterative solution based on pressure increment and convergence increment. The convergence condition is that the convergence difference is less than a preset error threshold, which is a settable numerical parameter.

3. The method for assessing the risk of machine jamming in the downstream systems of a tunnel boring machine according to claim 1, characterized in that, When the convergence of the support components reaches their respective maximum allowable convergence values, their equivalent stiffness is set to zero to simulate support failure, and the total stiffness and support pressure of the system are recalculated accordingly.

4. The method for assessing the risk of machine jamming in the downstream systems of a tunnel boring machine according to claim 1, characterized in that, It also includes determining a critical value for the tunneling rate based on parameter scanning or sensitivity analysis, such that when the tunneling rate is lower than the critical value, the maximum convergence amount calculated by the surrounding rock mechanics model exceeds the reserved space, and is output as a construction control suggestion.

5. A system for assessing the risk of machine jamming in the downstream systems of a tunnel boring machine, characterized in that, A method for assessing the risk of machine jamming in the downstream systems of a tunnel boring machine as described in claim 1, comprising: Modeling units are used to establish mechanical models that characterize the evolution of surrounding rocks over time; The parameter input unit is used to input geological parameters, support component parameters, reserved space, tunneling rate and shutdown information; The calculation unit is used to calculate the convergence increment of the surrounding rock and the convergence increment of the lining in each time step with time increments and to perform iterative solutions to obtain steady-state convergence and support pressure. Correction unit, used to correct support pressure based on the spatial effect of the working face; The discrimination unit is used to compare the maximum convergence value obtained by the solution with the reserved space and output the card machine risk assessment result and related alarm information. The display / storage unit is used to present the timing convergence curve, support pressure distribution, evaluation conclusions, and save calculation records.

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