A shield sealing cabin inner muck state visual system and method

Abstract

The present application relates to the technical field of granular state detection, in particular to a shield sealing cabin inner muck state visualization system and method, in the present application, through the stress direction difference matching of SIMPLE algorithm, the inter-particle shear strength distribution is converted into a set of calculable parameters, the quantitative extraction of shear characteristics can be realized under complex stress environment, the stable mechanical boundary conditions are provided for flow state calculation, the numerical coupling model of momentum exchange is established, the determination of turbulent flow and slow flow partition in the flow field is no longer dependent on empirical threshold, the eigenvalue change of mathematical matrix is used as the partition basis, the self-adaptability and accuracy of flow field division are enhanced, the combination of strength matrix and centrality algorithm enables the main load channel in the particle contact network to be automatically identified, the path sorting takes the connectivity as the core calculation index, the structural level of load transmission is clearly presented, the weighted superposition based on the path shear and support force ratio forms a stable matrix, and the extreme point extraction makes the low stability area identification have quantitative precision.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of particle state detection, in particular to a shield sealing cabin internal muck state visualization system and method. BACKGROUND

[0002] The technical field of particle state detection aims to establish a quantitative determination model of particle medium state by measuring and analyzing the physical characteristics of granular substances, to describe their morphology, distribution, density, water content and flowability under the conditions of stress, motion and environmental change, to visually characterize and numerically calculate the macroscopic morphology and microscopic state of the particle medium, and to realize real-time monitoring and evaluation of the running state of the particle medium.

[0003] The purpose of the shield sealing cabin internal muck state visualization system is to realize real-time monitoring and quantitative determination of the internal muck state of the sealing cabin during shield construction, to obtain physical characteristic data such as the morphology, distribution, flowability and density of the muck in the sealing cabin, to present the muck state in a visual form which cannot be directly observed, to provide accurate muck state feedback for shield construction, to assist the automatic control system in adjusting the tunneling parameters, to avoid water inrush, collapse and equipment damage caused by abnormal muck state, and to realize intelligent monitoring and efficient control of the construction process.

[0004] The existing particle state detection technology relies on single-point sensing signals and empirical parameter mapping in muck monitoring, and the data is distributed discretely, which is difficult to continuously reflect the overall response of the particle group under stress changes. The determination of muck morphology and density is mainly based on macroscopic indicators, and the stress chain structure characteristics between microscopic particles are not reflected, which leads to the inability to identify potential unstable trends in the early stage of abnormal state formation. The flow field and particle dynamics parameters are usually treated separately, lacking a unified calculation system, resulting in misjudgment of the muck state in the transition zone between turbulence and slow flow. When the tunneling rate changes and the cabin pressure fluctuates, the feedback lags behind. Since there is no spatial coupling determination mechanism for compaction and flow behavior, the evolution trend of the muck dense area can only be inferred from the late results, lacking real-time adjustment basis. When the load transmission path deviates, it is difficult to track the direction of contact force transmission between particles, and the identification accuracy of unstable areas is insufficient, which may lead to risks such as local collapse, water inrush and cutter damage. SUMMARY

[0005] The purpose of the present application is to solve the shortcomings in the prior art and to provide a shield sealing cabin internal muck state visualization system and method.

[0006] In order to achieve the above purpose, the present application adopts the following technical scheme: a shield sealing cabin internal muck state visualization system comprises:

[0007] The particle dynamic response analysis module: based on the muck particle group in the shield sealing cabin, the particle velocity, displacement and stress are calculated in time sequence, the energy change is compared by step, the abnormal stress area is identified, the SIMPLE algorithm is used, the stress direction difference between the particles in the abnormal area is matched and the shear strength distribution is extracted, and the particle stress distribution parameter set is formed;

[0008] The cabin flow coupling calculation module: based on the particle stress distribution parameter set, the node system in the cabin is established, the flow velocity difference and pressure gradient are calculated, the momentum exchange value is merged to judge the turbulent and slow flow partition, the local shear and flux are matrix combined to obtain the cabin flow field response data;

[0009] The muck density evolution determination module: based on the cabin flow field response data, the flow velocity gradient and the density change rate are analyzed, the section standard deviation is calculated to judge the compaction state, the boundary gradient is interpolated and the space sequence is reorganized to obtain the muck dense structure parameter field;

[0010] The contact transfer network identification module: based on the muck dense structure parameter field, the particle contact force and displacement deviation are extracted, the strength matrix is constructed and the node connectivity is analyzed, the centrality algorithm is used to identify the main load channel and sort the transfer path, and the particle load transfer structure set is established;

[0011] The muck structure stability calculation module: based on the particle load transfer structure set, the path shear and support force ratio are calculated to judge the instability area, the low stability area range and direction are weighted and superimposed, the extreme value point is extracted to form the stability matrix, and the muck structure stability determination result is established.

[0012] As a further scheme of the application, the particle stress distribution parameter set includes particle velocity distribution parameters, displacement increment parameters and shear stress difference parameters, the cabin flow field response data includes flow velocity vector parameters, density gradient parameters and momentum flux parameters, the muck dense structure parameter field includes muck density distribution parameters, compaction gradient parameters and structure continuity parameters, the particle load transfer structure set includes node connectivity parameters, main force chain path parameters and stress center parameters, and the muck structure stability determination result includes stability coefficient parameters, instability area range parameters and direction strength parameters.

[0013] As a further scheme of the application, the particle dynamic response analysis module includes:

[0014] The particle motion measurement submodule: based on the muck particle group in the shield sealing cabin, the velocity, displacement and stress information of the particles are continuously recorded, the position change of each particle in the time sequence is mapped as a motion trajectory, the particle acceleration is calculated by comparing the velocity change amount at adjacent time, and the stress direction and size are recorded synchronously, the three-dimensional motion data table is formed after being summarized, and the particle motion basic data set is generated;

[0015] Energy difference determination sub-module: based on the particle motion basic data set, the kinetic energy change value of each particle in a continuous period is calculated, the area of energy sudden increase and sudden drop is marked as an abnormal area, the force difference and direction difference between the particles in the area are extracted, the energy change rate and the force deviation amplitude are compared, the particle group with shearing effect is identified, and the stress distribution table is arranged to obtain the particle energy difference parameter set;

[0016] Force distribution construction sub-module: based on the particle energy difference parameter set, the SIMPLE algorithm is used to superimpose the shear strength, normal force and direction vector in the spatial coordinates, the stress transmission ratio between each area is calculated, the force distribution curve is drawn, the gradient difference of adjacent areas is spliced in space, and a complete stress network diagram is formed to generate the particle force distribution parameter set.

[0017] As a further scheme of the application, the SIMPLE algorithm first sets the velocity component and pressure value of each node in the initial step, discretizes and calculates the momentum term in the flow control equation, then uses the predicted velocity field to calculate the momentum residual and correct the pressure gradient to form a corrected pressure field, and then recalculates the node velocity component with the updated pressure value to obtain the corrected velocity field. The difference between the new and old velocity and pressure is judged for convergence, and when the difference is less than the set threshold, the iteration is ended, and the matching result of velocity and pressure is output, and the calculation of the force balance of the particles in the cabin is completed.

[0018] As a further scheme of the application, the cabin flow coupling calculation module comprises:

[0019] Node parameter construction sub-module: based on the particle force distribution parameter set, the node area is divided in the sealed cabin space, the flow velocity, pressure and density parameters are assigned to each node, the velocity difference of adjacent nodes is compared and the pressure gradient is calculated, the node momentum information is arranged according to the spatial sequence, the numerical relationship of each layer of nodes is integrated, and a unified cabin node momentum data set is formed;

[0020] Flow field difference calculation sub-module: based on the cabin node momentum data set, the momentum exchange amplitude of each node is compared to identify high-energy flow areas and slow flow areas, the shear strength and flux value of different areas are fused, the result is mapped to the spatial coordinates, the flow direction change trend is extracted, a continuous flow distribution map is formed, and cabin flow field response data is generated.

[0021] As a further scheme of the application, the slag densification evolution determination module comprises:

[0022] The compaction feature recognition submodule: based on the flow field response data in the cabin, the flow velocity gradient and the density change amplitude in the slag flow area are counted, the gradient difference of different sections is compared, the demarcation points of the compaction area and the loose area are located, the partition results are arranged according to the cabin position, the slag compaction distribution table is formed, and the slag compaction state parameter set is obtained;

[0023] The dense structure generation submodule: based on the slag compaction state parameter set, the boundary gradient value is subjected to interpolation operation, the space sequence is rearranged to reflect the structure continuity, the node information of the compaction area and the loose area is combined to generate a complete density matrix, and after merging and arranging, a three-dimensional structure mapping is formed, and a slag dense structure parameter field is obtained.

[0024] As a further scheme of the application, the contact transfer network recognition module comprises:

[0025] The contact feature extraction submodule: based on the slag dense structure parameter field, the contact points between particles and their relative positions are identified, the normal force and the tangential force components of each contact point are recorded, and the displacement offset is measured, the force data of adjacent particles is integrated through space aggregation, the high-strength contact area and the low-strength contact area are screened out, the corresponding data index is established, and a particle contact feature data set is generated;

[0026] The connection path recognition submodule: based on the particle contact feature data set, the contact points are gradually connected according to the continuity of the force direction and the contact strength, the particle node chain is formed, the main channel is determined by detecting the force consistency in the chain, the connectivity and the hierarchical order between channels are identified, the structure path table is drawn, and a particle transfer path structure set is obtained;

[0027] The load relationship modeling submodule: based on the particle transfer path structure set, the centrality algorithm is adopted, the force value distribution of each path and the mutual support relationship between nodes are counted, the load components are combined according to the path direction, the load concentration area and the transfer strength between different channels are analyzed, the overall induction of the force direction relationship of each area is carried out, a three-dimensional force topology diagram is established, and a particle load transfer structure set is formed.

[0028] As a further scheme of the application, the centrality algorithm first establishes an adjacency matrix of the particle contact network, takes the edge weight as the load strength between nodes, then traverses all paths, records the appearance frequency of nodes in each path, and takes it as the betweenness value, and then normalizes the node connectivity, the betweenness value and the weight of the adjacent node, calculates the centrality index, obtains the influence degree sorting of each node in the network, and draws the load relationship matrix according to the centrality value distribution.

[0029] As a further scheme of the application, the slag structure stability calculation module comprises:

[0030] A mechanical equilibrium calculation submodule: based on the particle load transmission structure set, the shear force and support force values of each path are extracted, the ratio of the two is calculated and abnormal sections are screened, low stability zones are numbered and arranged into a force relationship table to provide basic data for subsequent stability determination, and a path stress ratio data set is obtained;

[0031] A stable distribution evaluation submodule: based on the path stress ratio data set, the range and direction information of the low stability zone is summarized, the stability coefficient of each section is calculated and the extreme value node is determined, the extreme value region difference is processed to construct a stability matrix, the overall stress distribution structure in the cabin is output, and the slag structure stability determination result is established.

[0032] A kind of shield sealing cabin slag state visualization method, the shield sealing cabin slag state visualization method is based on above-mentioned shield sealing cabin slag state visualization system execution, comprising the following steps:

[0033] S1: based on the particle group in the shield sealing cabin slag, record particle velocity, displacement and stress, calculate stress difference by comparing time series changes, extract shear strength using SIMPLE algorithm balance iteration, generate particle stress distribution parameter set;

[0034] S2: based on the particle stress distribution parameter set, establish a node system in the cabin, calculate the flow velocity difference and pressure gradient, correct the flow velocity and pressure using SIMPLE algorithm, judge the turbulent and slow flow partition and integrate the shear flux, obtain the cabin flow field response data;

[0035] S3: based on the cabin flow field response data, calculate the flow velocity gradient and density change rate, compare the section standard deviation to determine the compaction state, interpolate the boundary gradient to form a continuous sequence, and obtain the slag dense structure parameter field;

[0036] S4: based on the slag dense structure parameter field, extract the particle contact force and displacement deviation, calculate the node weight using centrality algorithm to identify the main load channel, and establish a particle load transmission structure set;

[0037] S5: based on the particle load transmission structure set, calculate the shear and support force ratio to identify unstable zones, weight and integrate the range and direction of low stability zones, extract extreme value nodes to form a stability matrix, and establish a slag structure stability determination result.

[0038] Compared with the prior art, the advantages and positive effects of the present application are:

[0039] In the present application, by introducing time sequence step comparison and energy change analysis in particle dynamics calculation, dynamic tracking of particle group stress evolution is realized, and identification of abnormal stress zones is converted from static threshold judgment to continuous time sequence judgment, improving the sensitivity and response accuracy of stress anomaly detection;

[0040] In the present application, by matching the force direction difference of SIMPLE algorithm, the inter-particle shear strength distribution is converted into a set of calculable parameters, which can realize the quantitative extraction of shear characteristics in complex stress environment, provide stable mechanical boundary conditions for flow state calculation, matrix operation of the difference between the flow rate and the pressure gradient in the cabin, establish a numerical coupling model of momentum exchange, make the determination of turbulent and slow flow partitions in the flow field no longer rely on empirical threshold, use the eigenvalue change of mathematical matrix as the basis for partition, and enhance the adaptability and accuracy of flow field division;

[0041] In the present application, the combination of strength matrix and centrality algorithm enables the automatic identification of the main load channel in the particle contact network, the path sorting takes the connectivity as the core calculation index, the structural level of load transfer is clearly presented, the weighted superposition based on the ratio of path shear and support force forms a stable matrix, and the extreme point extraction makes the identification of low stability area have quantitative precision. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 The system flowchart of the present application is shown in the figure.

[0043] Figure 2 The method step schematic diagram of the present application is shown in the figure. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application is further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application, and are not used to limit the present application.

[0045] Example 1

[0046] Please refer to Figure 1 The present application provides a technical scheme: a slurry state visualization system in a shield sealing cabin includes:

[0047] Particle dynamic response analysis module: based on the particle group in the slurry in the shield sealing cabin, the particle velocity, displacement and force are calculated in time sequence, the force abnormal area is identified by comparing the energy change with the step length, the SIMPLE algorithm is used to match the force direction difference between the particles in the abnormal area and extract the shear strength distribution, and a particle force distribution parameter set is formed;

[0048] Cabin flow coupling calculation module: based on the particle force distribution parameter set, a cabin node system is established, the flow rate difference and the pressure gradient are calculated, the momentum exchange value is merged to determine the turbulent and slow flow partitions, the local shear and flux are matrix merged, and the cabin flow field response data is obtained;

[0049] Slag dense evolution determination module: based on the cabin flow field response data, analyze the flow velocity gradient and the density change rate, calculate the standard deviation of the section to judge the compaction state, interpolate the boundary gradient and reorganize the spatial sequence to obtain the slag dense structure parameter field;

[0050] Contact transmission network identification module: based on the slag dense structure parameter field, extract the particle contact force and displacement deviation, build the strength matrix and analyze the node connectivity, use the centrality algorithm to identify the main load channel and sort the transmission path, and establish the particle load transmission structure set;

[0051] Slag structure stability calculation module: based on the particle load transmission structure set, calculate the ratio of path shear to support force to judge the instability area, weight and superimpose the low stability area range and direction, extract the extreme value point to form the stability matrix, and establish the slag structure stability determination result.

[0052] The particle stress distribution parameter set includes particle velocity distribution parameters, displacement increment parameters and shear stress difference parameters, the cabin flow field response data includes flow velocity vector parameters, density gradient parameters and momentum flux parameters, the slag dense structure parameter field includes slag density distribution parameters, compaction gradient parameters and structure continuity parameters, the particle load transmission structure set includes node connectivity parameters, main force chain path parameters and stress center parameters, and the slag structure stability determination result includes stability coefficient parameters, instability area range parameters and direction strength parameters.

[0053] Particle dynamic response analysis module includes:

[0054] Particle motion measurement submodule: based on the slag particles in the shield sealing cabin, continuously record the velocity, displacement and stress information of the particles, map the position change of each particle in the time sequence to the motion trajectory, calculate the particle acceleration by comparing the velocity change amount at adjacent time, and record the stress direction and size synchronously, and after summarizing, form a three-dimensional motion data table to generate a particle motion basic data set;

[0055] Energy difference determination submodule: based on the particle motion basic data set, calculate the kinetic energy change value of each particle in the continuous period, mark the area with energy sudden increase and sudden drop as abnormal area, and then extract the stress difference and direction difference between particles in the area, compare the energy change rate and stress deviation amplitude, identify the particle group with shearing effect, and organize into a stress distribution table to obtain a particle energy difference parameter set;

[0056] Stress distribution construction submodule: based on the particle energy difference parameter set, using the SIMPLE algorithm, superimpose the shear strength, normal force and direction vector in the spatial coordinates, calculate the stress transmission ratio between each region, draw the force direction distribution curve, and spatially splice the gradient difference between adjacent regions to form a complete stress network diagram, and generate a particle stress distribution parameter set;

[0057] Particle motion determination submodule: Based on the group of muck particles in the shield capsule, the Euler-Lagrange mixed solution algorithm is used to continuously record the particle velocity, displacement and force information. The time step parameter is set to 0.002 seconds, and the spatial resolution unit is 1.5x10 -3 6 meters. The position difference calculation is performed between consecutive time points for each particle. The instantaneous velocity is obtained by dividing the position difference by the time step. The acceleration is obtained by dividing the difference between the velocities of two consecutive frames by the time step. The loop traversal operation is performed on all particles. The force direction vector and force size parameters are recorded. The five-tuple containing position, velocity, acceleration, force direction and force size is recorded in time series storage format. The linear interpolation method is used to perform trajectory continuous reconstruction on the particle trajectory. The missing points are inserted on the time axis using the data interpolation instruction to maintain time continuity. The three-dimensional array structure is formed by stacking all particle information in matrix form, which contains the continuous displacement values of each particle in the spatial three-axis. The particle motion basic data set is generated;

[0058] Energy difference determination submodule: Based on the particle motion basic data set, the kinetic energy change difference algorithm is used to calculate the kinetic energy change value of each particle in the continuous time period. The time period length is set to 0.01 seconds. The instantaneous kinetic energy is obtained by multiplying the mass by half the square of the velocity. The energy change value is calculated by the difference between the kinetic energies of adjacent time periods. The energy change absolute value and the set threshold 5.0x10 -3 Joule are compared to determine the energy mutation area. The energy surge and sudden drop particles are marked using the logical judgment instruction, and the abnormal area list is generated. The force difference and direction difference between particles in the abnormal area are calculated. The direction difference is obtained by the unit direction vector angle function. The force difference is obtained by the absolute value of the force value difference between two particles. After comparing the energy change rate and the force deviation amplitude, the strongest particle group in shear action is selected by the sorting command. The particle group is arranged in matrix form to generate the stress distribution table. The particle energy difference parameter set is output.

[0059] Force distribution construction submodule: Based on the particle energy difference parameter set, the SIMPLE algorithm is used to superimpose the shear strength, normal force and direction vector in the spatial coordinates. The density, viscosity, pressure and velocity four input variables are defined. The alternating update operation of pressure field and velocity field is performed. The pressure relaxation coefficient is set to 0.7, and the velocity relaxation coefficient is set to 0.8. The loop iteration is performed until the pressure residual is less than the set limit value. The stress transfer ratio between calculation regions is calculated and recorded in the numerical matrix. The force direction distribution curve is drawn using the drawing command. Then the gradient difference between adjacent spatial units is performed three-dimensional splicing operation. The complete spatial data field is generated by the coordinate grid command. The gradient matrix after superposition is combined according to the spatial direction to construct the stress transfer matrix to obtain the stress network diagram, and the particle force distribution parameter set is generated.

[0060] The SIMPLE algorithm first sets the velocity components and pressure values ​​of each node in the initial step, discretizes the momentum term in the flow control equation, then uses the predicted velocity field to obtain the momentum residual and corrects the pressure gradient to form a corrected pressure field. Then, it recalculates the node velocity components with the updated pressure values ​​to obtain the corrected velocity field. It then performs a convergence judgment on the difference between the old and new velocities and pressures. When the difference is lower than a set threshold, the iteration ends and the matching results of velocity and pressure are output, thus completing the calculation of the force balance of particles in the chamber.

[0061] The SIMPLE algorithm, according to the formula:

[0062]

[0063] in: This represents the surface flux predicted by the fluid momentum equation of the slag and soil inside the sealed chamber. This represents the Patankar momentum correction coefficient obtained after discretization using the SIMPLE algorithm. This represents the pressure correction term for the i-th space unit within the cabin. Indicates the cabin number Pressure correction term for space unit, This represents the numerical stability constant set to prevent iterative divergence. Represents the direction vector between the i-th and j-th units. The average shear strength of the projection, Indicates the first With the Spatial distance between unit centroids Indicates the first The normal force acting on the element, This represents the normal force acting on the j-th element. Indicates by the first Unit points to the first The unit direction vector of the element. This represents the anisotropy coefficient calculated based on the eigenvalue ratio of the tensor of the particle contact structure within the cabin. The shear dilatation geometric factor is used to describe the geometric coupling relationship between the particle volume fraction gradient and the contact orientation angle. The inelastic dissipation ratio of particles measures the degree of energy loss during a collision. This represents the micro-contact roughness coefficient of the particle surface to characterize the microscale friction enhancement effect. The local packing factor is used to reflect the density distribution of soil particles within the sealed compartment. This represents the shear strength weighting coefficient. Indicates the normal force weighting coefficient. This represents the anisotropy weighting coefficient. This represents the energy dissipation weighting coefficient. This represents the roughness weighting coefficient. This represents the stacking coefficient and weighting coefficient. This represents the calculated stress transfer ratio between the slag and soil regions within the sealed chamber.

[0064] Execution process: First, a discrete control volume model of the slag fluid is established inside the sealed chamber, and the momentum equation is used for prediction and calculation. That is, the predicted mass flux values ​​on each control surface, and the pressure field of each spatial unit is corrected using the framework to obtain... and This is to reflect the pressure correction value of the slag inside the compartment under local stress difference, and at the same time, the Patankar coefficient is obtained based on the discrete scheme solution. To characterize the equilibrium relationship between momentum convection and diffusion, the positions of the centroids of adjacent units are then extracted in spatial coordinates for calculation. With direction vector The mean value is obtained by projecting the shear strength distribution along this direction. To characterize the flow tendency of the slag under shearing action, the normal force is then calculated based on the contact force sensing data of each unit node. and and through its along The normal stress gradient is obtained by calculating the difference in directions. Then, the eigenvalue ratio is calculated using the tensor of the particle contact network structure to obtain the anisotropy coefficient. And by combining the volume fraction gradient with the contact angle, a dilatation geometry factor is constructed. To reflect the local shear dilatation coupling effect, and at the same time, to calculate the inelastic dissipation ratio using the particle restitution coefficient and the energy loss ratio. and its relationship with The flux attenuation characteristics are corrected by multiplication, and the micro-contact roughness coefficient is then obtained by integrating the surface power spectral density. ,and Combined with methods to reflect microscale friction amplification effects, the local packing factor is then calculated based on Voronoi volume inverse normalization. To correct for the influence of density, a design matrix was constructed using experimental and simulation data, and weighting coefficients were determined using ridge regression with nonnegative constraints. By minimizing the prediction error through cross-validation and limiting the coefficient range to 0 to 1, all parameters are substituted into the formula to obtain the result. This process generates a stress transfer ratio matrix between different regions and stitches them together to form a stress network diagram, enabling a visual representation of the stress state of the slag and soil inside the sealed chamber.

[0065] The in-cabin flow coupling calculation module includes:

[0066] The node parameter construction submodule: based on the particle force distribution parameter set, the node area is divided in the sealed cabin space, the flow velocity, pressure and density parameters of each node are assigned, the velocity difference of adjacent nodes is compared and the pressure gradient is calculated, the node momentum information is arranged according to the space sequence, the numerical relationship of each layer node is integrated, and a unified cabin node momentum data set is formed;

[0067] The flow field difference calculation submodule: based on the cabin node momentum data set, the momentum exchange amplitude of each node is compared to identify the high-energy flow area and the slow flow area, the shear strength and flux value of different areas are fused, the result is mapped to the spatial coordinates, the flow direction change trend is extracted, a continuous flow distribution map is formed, and the cabin flow field response data is generated;

[0068] The node parameter construction submodule: based on the particle force distribution parameter set, the node area is divided in the sealed cabin space, the flow velocity, pressure and density parameters of each node are assigned, the velocity difference of adjacent nodes is compared and the pressure gradient is calculated, the node momentum information is arranged according to the space sequence, the numerical relationship of each layer node is integrated, and a unified cabin node momentum data set is formed;

[0069] The flow field difference calculation submodule: based on the cabin node momentum data set, the momentum exchange amplitude of each node is compared to identify the high-energy flow area and the slow flow area, the shear strength and flux value of different areas are fused, the result is mapped to the spatial coordinates, the flow direction change trend is extracted, a continuous flow distribution map is formed, and the cabin flow field response data is generated.

[0070] The slag evolution determination module comprises:

[0071] The compaction feature recognition submodule: based on the flow field response data in the tank, the flow velocity gradient and the density change amplitude in the slag flow region are counted, the gradient difference of different sections is compared, the demarcation points of the compacted zone and the loose zone are located, the partition results are arranged according to the tank position, the slag compaction distribution table is formed, and the slag compaction state parameter set is obtained;

[0072] The dense structure generation submodule: based on the slag compaction state parameter set, the boundary gradient value is subjected to interpolation operation, the spatial sequence is rearranged to reflect the continuity of the structure, the node information of the compacted zone and the loose zone is combined to generate a complete density matrix, and after merging and arranging, a three-dimensional structure mapping is formed to obtain the slag dense structure parameter field;

[0073] The compaction feature recognition submodule: based on the flow field response data in the tank, the flow velocity gradient and the density change amplitude in the slag flow region are counted, the gradient difference of different sections is compared, the demarcation points of the compacted zone and the loose zone are located, the partition results are arranged according to the tank position, the slag compaction distribution table is formed, and the slag compaction state parameter set is obtained;

[0074] The dense structure generation submodule: based on the slag compaction state parameter set, the boundary gradient value is subjected to interpolation operation, the spatial sequence is rearranged to reflect the continuity of the structure, the node information of the compacted zone and the loose zone is combined to generate a complete density matrix, and after merging and arranging, a three-dimensional structure mapping is formed to obtain the slag dense structure parameter field.

[0075] The contact transmission network identification module comprises:

[0076] The contact feature extraction submodule: based on the dense structure parameter field of the slag, the contact points between the particles and their relative positions are identified, the normal force and tangential force components of each contact point are recorded, and the displacement offset is measured. The force data of adjacent particles is integrated through spatial aggregation, high and low intensity contact areas are screened out, corresponding data index is established, and particle contact feature data set is generated;

[0077] The connection path identification submodule: based on the particle contact feature data set, the contact points are gradually connected according to the continuity of force direction and contact strength, the particle node chain is formed, the force consistency in the chain is detected to determine the main channel, the connectivity and hierarchical order between channels are identified, the structure path table is drawn, and the particle transmission path structure set is obtained;

[0078] The load relationship modeling submodule: based on the particle transmission path structure set, the centrality algorithm is used to count the force value distribution of each path and the mutual support relationship between nodes, the load components are combined according to the path direction, the load concentration areas and transmission strength between different channels are analyzed, the overall induction of force direction relationship of each area is carried out, the three-dimensional force topology diagram is established, and the particle load transmission structure set is formed;

[0079] The contact feature extraction submodule: based on the dense structure parameter field of the slag, the three-dimensional contact point clustering identification algorithm is used to identify the contact points between the particles and their relative positions, the spatial resolution step is set to 0.01 meters, the coordinate index matrix is established for the input three-dimensional parameter field and traversed in the order of x, y and z three axes, the contact detection command is executed to determine whether the contact by the distance between the centers of adjacent particles and the difference in radius, the contact determination threshold is set to 1.2 times the average particle size, the contact coordinates and contact number of the particle pairs meeting the conditions are recorded, the normal force calculation command is executed to obtain the normal force component by multiplying the contact direction unit vector and the force scalar, the tangential force calculation command is executed to obtain the tangential force component by the cross product of the force direction and the tangent direction vector of the contact surface, the displacement offset is measured by comparing the displacement value obtained by the difference between the center positions of adjacent particles and the initial contact distance, a record matrix is established for each contact point information, including contact number, coordinate position, normal force value, tangential force value and displacement offset, the spatial aggregation command is executed to integrate the particle groups with similar force direction in the three-dimensional coordinate into the same aggregation unit, the force data of the aggregation unit is summed and averaged to generate the force aggregation table, and the loop filtering command is executed for all aggregation units to screen out the high intensity contact area with force average greater than 500 Newton and the low intensity contact area with force average less than 100 Newton, the high and low intensity partition data index table is established, and the output is the particle contact feature data set;

[0080] The connection path identification sub-module: based on the particle contact feature data set, the force direction continuous chain generation algorithm is adopted to connect the contact points according to the force direction and contact strength continuity, the direction deviation threshold is set to 15 degrees, the direction vector and intensity value of each contact point are extracted, the connection condition is judged by calculating the angle between the direction vectors of adjacent nodes, the nodes with a direction deviation less than the threshold are connected in the form of an adjacency matrix, the chain construction command is executed to extend the connection to the end node in turn, the particle node chain is generated and each chain is assigned a unique number, and the force direction consistency detection command is executed to calculate the standard deviation of the direction vector of each node in the chain. The chain with a standard deviation less than 0.05 is marked as the main channel, the connectivity check command is executed on the main channel and its adjacent channels to determine the hierarchical relationship by comparing the number of node overlaps and the connection order, the hierarchical structure is numbered and arranged to generate a channel hierarchy table, and the table drawing command is executed to generate a structure path table, and the output is a particle transfer path structure set;

[0081] The load relationship modeling sub-module: based on the particle transfer path structure set, the weighted centrality modeling algorithm is adopted to statistically analyze the force value distribution and support relationship between nodes of each path, the centrality calculation weight parameter α is set to 0.65, the node force value of each path is extracted and sorted according to the path direction, the load merging command is executed to sum the force values of adjacent nodes according to the vector weighting along the path direction, the path load vector sequence is generated, the aggregation command is executed on the load concentrated area between paths to aggregate the nodes with a force value difference less than 30 N, the node coordinates, path number and concentrated force value of the aggregation result are recorded, the transfer strength analysis command is executed to calculate the transfer strength of the region by comparing the average force value and length of the path, the matrix arrangement command is executed on the force direction relationship of all regions to establish a node force direction matrix, including path number, node coordinates, load vector and transfer ratio, and the node connection network is generated by performing a three-dimensional topological mapping operation on the matrix, and a force direction diagram is drawn, and a particle load transfer structure set is generated.

[0082] The centrality algorithm first establishes an adjacency matrix of the particle contact network, with edge weight representing the load intensity between nodes, then traverses all paths, records the frequency of each node appearing in each path as the betweenness value, and then normalizes the node degree, betweenness value and adjacent node weight to calculate the centrality index, and obtains the influence degree sorting of each node in the network. The load relationship matrix is drawn according to the centrality value distribution;

[0083] The centrality algorithm is according to the formula:

[0084]

[0085] Wherein: represents the betweenness centrality value of node v in the force network of the muck in the shield sealing cabin, represents the cost metric from node to node the shortest path count function of the shortest path, denotes the load line integral component in the edge path direction, denotes the support strength coefficient between the nodes and , denotes the path orientation coupling weight, denotes the structure tightness factor, denotes the path timing stability coefficient, denotes the community bridging coefficient, denotes the path curvature penalty term, denotes the load fluctuation coefficient, denotes the load line integral weight coefficient, denotes the support strength weight coefficient, denotes the orientation coupling weight coefficient, denotes the structure tightness weight coefficient, denotes the timing stability weight coefficient, denotes the community bridging weight coefficient, denotes the curvature penalty weight coefficient, denotes the load fluctuation weight coefficient, denotes the numerical stability constant, and denotes any starting node and ending node in the slag force network, and denotes adjacent nodes in the network;

[0086] Execution process: First, based on the slag transmission path structure set, a weighted directed network graph is established, taking the in-cabin particle contact point as the node and the load transmission direction to construct the edge relationship, and the load line integral component on the edge is extracted to represent the bearing strength of the particle force along the transmission direction, and the support strength coefficient is calculated according to the local particle support redundancy and pressure balance , which measures the support stability between particles, and then the path orientation coupling weight is calculated , the coupling degree is determined by the cosine value of the angle between the principal stress direction and the path direction, and the local contact density and node connectivity of the network are extracted and the structure tightness factor is calculated to reflect the concentration of local force chain, the system tracks the load change in time dimension and calculates the path timing stability coefficient , which represents the proportion of the path that continues to bear in the time sequence, then through the division of the network community structure, the community bridging coefficient of the cross-regional connection is calculated to measure the load propagation effect of the path between different slag aggregation areas, and the curvature penalty term is calculated by the ratio of the total curvature of the three-dimensional path curve segment to the average arc length , reflecting the attenuation of path geometry tortuosity on load transfer efficiency, and then calculating the load fluctuation coefficient with the ratio of load standard deviation to mean value in the sliding time window , for evaluating load stability, and then normalizing all parameters and constructing path cost function with weights representing the importance of different physical characteristics in path calculation, the weight values are determined by minimizing prediction error through elastic net regression with non-negative constraint combined with cross-validation and normalized to the range of 0 to 1, and then the shortest path number of nodes to node is calculated as the weight and the number of paths passing through node v , and finally the ratio is accumulated to get the node betweenness centrality value , for quantifying the key degree of node V in the force chain transmission network of slag, and mapping to three-dimensional force topology graph to realize dynamic visualization of the force concentration area, channel load strength and stress network structure of the slag in the cabin.

[0087] The slag structure stability calculation module includes:

[0088] Mechanical equilibrium calculation submodule: based on the particle load transfer structure set, the shear force and support force values of each path are extracted, the ratio of the two is calculated and abnormal sections are selected, low stable areas are numbered and sorted into a force relationship table, providing basic data for subsequent stability determination, and obtaining path force ratio data set;

[0089] Stable distribution evaluation submodule: based on the path force ratio data set, the range and direction information of low stable areas are summarized, the stability coefficients of each section are calculated and the extreme value nodes are determined, the extreme value area difference is processed to construct the stability matrix, and the overall force distribution structure in the cabin is output, and the slag structure stability determination result is established;

[0090] The mechanical equilibrium calculation submodule: based on the particle load transfer structure set, the numerical iterative balance algorithm is used to extract and calculate the shear force and support force values of each path. First, read the path number, node coordinates, shear force value and support force value from the input structure set, establish the path index matrix, execute the data traversal command for each path in order, calculate the difference between the shear force and support force of adjacent nodes and store them in the temporary vector table, execute the ratio calculation command to get the force ratio parameter by dividing the shear force value by the support force value, retain three decimal places of accuracy, combine all the force ratio data into a two-dimensional matrix according to the path number and node order, set the abnormal screening threshold interval to 0.75 to 1.25, execute the condition judgment command to screen out the node sequence with a ratio value outside the interval, generate a low stability zone number list and map it with the path number as the primary key, use the data arrangement command to write the low stability zone number, node coordinates, shear force value, support force value and ratio information into the stress relationship table according to the path number, execute the number sorting and index merging operation on the table data, and generate the path stress ratio data set;

[0091] The stable distribution evaluation submodule: based on the path stress ratio data set, the stability coefficient merging algorithm is used to summarize and calculate the low stability zone range and direction information. Read the low stability zone number table and establish the node index according to the spatial coordinates. Execute the range extraction command for each low stability zone node to get the adjacent node coordinate difference and record the direction vector. Execute the stability coefficient calculation command to get the section stability coefficient value by multiplying the average of the adjacent node stress ratio and the force direction angle deviation. Set the merging step to 0.05 meters. Average the stability coefficients of consecutive nodes in the same section and write them into the stability coefficient matrix. Execute the extreme value identification command to extract the maximum and minimum value nodes in each section stability coefficient sequence. Record the extreme value node number, coordinates and stability coefficient value into the extreme value table. Execute the difference processing command to take the absolute value of the stability coefficient difference between adjacent extreme value sections to form the difference matrix. Index match the difference matrix and node coordinates to construct the stability matrix, which contains node number, stability coefficient, direction vector and difference parameter. Execute the three-dimensional drawing command to output the overall stress distribution structure in the cabin body and generate the slag structure stability judgment result.

[0092] Please refer to Figure 2 A shield sealing cabin slag state visualization method, the shield sealing cabin slag state visualization method is based on the above shield sealing cabin slag state visualization system and is executed, comprising the following steps:

[0093] S1: Based on the particle group in the shield sealing cabin, record the particle velocity, displacement and stress, calculate the stress difference by comparing the time sequence changes, extract the shear strength by using the SIMPLE algorithm balance iteration, and generate the particle stress distribution parameter set;

[0094] S2: Based on the particle force distribution parameter set, establish the node system in the cabin, calculate the flow velocity difference and pressure gradient, use the SIMPLE algorithm to correct the flow velocity and pressure, judge the turbulent and slow flow partition and integrate the shear flux, and obtain the cabin flow field response data;

[0095] S3: Based on the cabin flow field response data, calculate the flow velocity gradient and density change rate, compare the section standard deviation to determine the compaction state, interpolate the boundary gradient to form a continuous sequence, and obtain the slag soil dense structure parameter field;

[0096] S4: Based on the slag soil dense structure parameter field, extract the particle contact force and displacement deviation, calculate the node weight to identify the main load channel using the centrality algorithm, and establish a set of particle load transfer structure;

[0097] S5: Based on the particle load transfer structure set, calculate the shear and support force ratio to identify the instability area, weight and integrate the low stability area range and direction, extract the extreme value node to form a stability matrix, and establish a slag soil structure stability determination result.

[0098] The above is only a preferred embodiment of the present application, and is not intended to limit the present application in other forms. Any skilled person in the art can use the disclosed technical content to make changes or modifications to equivalent embodiments applied to other fields. However, any simple modification, equivalent change and modification made in accordance with the technical essence of the present application to the above embodiments, without departing from the technical solution content of the present application, still belongs to the protection scope of the present application technical solution.

Claims

1. A visualization system for the status of excavated soil inside a shield tunneling sealed chamber, characterized in that, The system includes: Particle dynamic response analysis module: Based on the slag particle group in the shield sealed chamber, the module performs time-series calculations on particle velocity, displacement and stress. By comparing energy changes through step size, it identifies stress anomaly zones. Using the SIMPLE algorithm, it matches the force direction difference between particles in the anomaly zone and extracts the shear strength distribution to form a set of particle stress distribution parameters. In-cabin flow coupling calculation module: Based on the set of particle force distribution parameters, establish an in-cabin node system, calculate the velocity difference and pressure gradient, merge momentum exchange values ​​to determine turbulent and slow flow zones, and perform matrix merging of local shear and flux to obtain in-cabin flow field response data. Slag compaction evolution determination module: Based on the in-cabin flow field response data, analyze the velocity gradient and density change rate, calculate the standard deviation of the section to determine the compaction state, interpolate the boundary gradient and reorganize the spatial sequence to obtain the slag compaction structure parameter field. Contact transfer network identification module: Based on the parameter field of the compacted soil structure, extract particle contact force and displacement deviation, construct strength matrix and analyze node connectivity, use centrality algorithm to identify main load channels and sort transfer paths, and establish particle load transfer structure set; The slag and soil structure stability calculation module: Based on the particle load transfer structure set, it calculates the ratio of path shear to support force to determine the instability zone, performs weighted superposition of the range and direction of the low stability zone, extracts extreme points to form a stability matrix, and establishes the slag and soil structure stability judgment result. Particle motion measurement submodule: Based on the slag particle group in the shield sealed chamber, the velocity, displacement and force information of the particles are continuously recorded. The position change of each particle in the time series is mapped to the motion trajectory. The particle acceleration is calculated by comparing the velocity change at adjacent time moments. The direction and magnitude of the force are recorded simultaneously. After summarizing, a three-dimensional motion data table is formed, and a basic dataset of particle motion is generated. Energy difference determination submodule: Based on the particle motion basic dataset, calculate the kinetic energy change value of each particle in a continuous time period, mark the areas of sudden energy increase and decrease as abnormal areas, extract the force difference and direction difference between particles in the area, compare the energy change rate and force deviation amplitude, identify the particle group with shearing effect, organize it into a stress distribution table, and obtain the particle energy difference parameter set. The stress distribution construction submodule: Based on the particle energy difference parameter set, the SIMPLE algorithm is used to superimpose shear strength, normal force and direction vector in spatial coordinates, calculate the stress transfer ratio between each region, draw the force distribution curve, and spatially stitch the gradient difference between adjacent regions to form a complete stress network diagram and generate the particle stress distribution parameter set.

2. The visualization system for the status of excavated soil inside the shield tunnel sealed chamber according to claim 1, characterized in that, The set of particle stress distribution parameters includes particle velocity distribution parameters, displacement increment parameters, and shear stress difference parameters. The in-chamber flow field response data includes flow velocity vector parameters, density gradient parameters, and momentum flux parameters. The slag compaction structure parameter field includes slag density distribution parameters, compaction gradient parameters, and structural continuity parameters. The particle load transfer structure set includes node connectivity parameters, main chain path parameters, and stress center parameters. The slag structure stability determination results include stability coefficient parameters, instability region range parameters, and directional strength parameters.

3. The visualization system for the status of excavated soil inside the shield tunnel sealed chamber according to claim 1, characterized in that, The SIMPLE algorithm first sets the velocity components and pressure values ​​of each node in the initial step, discretizes the momentum term in the flow control equation, then uses the predicted velocity field to obtain the momentum residual and corrects the pressure gradient to form a corrected pressure field. Then, it recalculates the node velocity components with the updated pressure values ​​to obtain the corrected velocity field. It then performs a convergence judgment on the difference between the old and new velocities and pressures. When the difference is lower than a set threshold, the iteration ends and the matching result of velocity and pressure is output, thus completing the force balance calculation of the particles inside the chamber.

4. The visualization system for the status of excavated soil inside the shield tunnel sealed chamber according to claim 1, characterized in that, The in-cabin flow coupling calculation module includes: Node parameter construction submodule: Based on the particle force distribution parameter set, the node region is divided in the sealed chamber space. The flow velocity, pressure and density parameters are assigned to each node. The velocity difference between adjacent nodes is compared and the pressure gradient is calculated. The node momentum information is organized according to the spatial sequence and the numerical relationship of nodes in each layer is integrated to form a unified intra-chamber node momentum dataset. The flow field difference calculation submodule: Based on the momentum dataset of nodes in the cabin, it compares the momentum exchange amplitude of each node to identify high-energy flow regions and slow flow regions, fuses the shear intensity and flux values ​​of different regions, maps the results to spatial coordinates, extracts the trend of flow direction change, forms a continuous flow distribution map, and generates flow field response data in the cabin.

5. The visualization system for the status of excavated soil inside the shield tunnel sealed chamber according to claim 1, characterized in that, The soil compaction evolution determination module includes: Compaction Feature Recognition Submodule: Based on the in-cabin flow field response data, the velocity gradient and density change amplitude in the soil flow area are statistically analyzed, the gradient difference of different sections is compared, the boundary point between the compacted zone and the loose zone is located, the zoning results are arranged according to the cabin position to form a soil compaction distribution table, and a set of soil compaction state parameters is obtained. The compacted structure generation submodule: Based on the set of compaction state parameters of the slag soil, interpolation calculation is performed on the boundary gradient values, the spatial sequence is rearranged to reflect the structural continuity, the node information of the compacted and loose zones is merged to generate a complete density matrix, and after merging and sorting, a three-dimensional structural mapping is formed to obtain the compacted structure parameter field of the slag soil.

6. The visualization system for the status of excavated soil inside the shield tunnel sealed chamber according to claim 1, characterized in that, The contact transmission network identification module includes: Contact feature extraction submodule: Based on the structural parameter field of compacted slag, the contact points between particles and their relative positions are identified, the normal and tangential force components of each contact point are recorded, and the displacement offset is measured. The force data of adjacent particles are integrated through spatial aggregation, high-intensity contact areas and low-intensity contact areas are selected, corresponding data indexes are established, and particle contact feature dataset is generated. Connection path recognition submodule: Based on the particle contact feature dataset, the contact points are connected step by step according to the continuity of the force direction and contact intensity to form a particle node chain. The main channel is determined by detecting the consistency of force direction within the chain. The connectivity and hierarchical order between each channel are identified, and a structural path table is drawn to obtain the particle transmission path structure set. Load relationship modeling submodule: Based on the particle transfer path structure set, the centrality algorithm is used to statistically analyze the force distribution of each path and the mutual support relationship between nodes, merge the load components according to the path direction, analyze the load concentration area and transfer intensity between different channels, summarize the force direction relationship of each region, establish a three-dimensional force topology map, and form a particle load transfer structure set.

7. The visualization system for the status of excavated soil inside the shield tunnel sealed chamber according to claim 6, characterized in that, The centrality algorithm first establishes the adjacency matrix of the particle contact network, using edge weights to represent the load intensity between nodes. Then, it traverses all paths, records the frequency of node occurrence in each path, and uses it as the median value. Next, it normalizes the node connectivity, median value, and adjacent node weights, calculates the centrality index, obtains the influence ranking of each node in the network, and draws the load relationship matrix based on the centrality value distribution.

8. The visualization system for the status of excavated soil inside the shield tunnel sealed chamber according to claim 1, characterized in that, The slag and soil structure stability calculation module includes: Mechanical equilibrium calculation submodule: Based on the particle load transfer structure set, extract the shear force and support force values ​​of each path, calculate the ratio of the two and screen abnormal sections, number the low stability zone and organize it into a force relationship table, provide basic data for subsequent stability determination, and obtain the path force ratio dataset. Stability distribution assessment submodule: Based on the path force ratio dataset, it summarizes the range and direction information of the low stability zone, merges and calculates the stability coefficient of each section and determines the extreme value nodes, processes the difference of the extreme value area to construct the stability matrix, outputs the overall force distribution structure inside the cabin, and establishes the stability judgment result of the slag structure.

9. A method for visualizing the state of excavated soil inside a shield tunneling sealed chamber, characterized in that, The implementation of the shield tunnel sealed chamber slag status visualization system according to any one of claims 1-8 includes the following steps: S1: Based on the slag particle group in the shield tunnel sealed chamber, record the particle velocity, displacement and force, compare the time series changes to calculate the force difference, use the SIMPLE algorithm to extract shear strength through equilibrium iteration, and generate a set of particle force distribution parameters. S2: Based on the set of particle force distribution parameters, establish the intra-chamber node system, calculate the velocity difference and pressure gradient, use the SIMPLE algorithm to correct the velocity and pressure, determine the turbulent and slow flow zones and integrate the shear flux to obtain the intra-chamber flow field response data. S3: Based on the in-cabin flow field response data, calculate the velocity gradient and density change rate, compare the standard deviation of the section to determine the compaction state, interpolate the boundary gradient to form a continuous sequence, and obtain the compaction structure parameter field of the slag soil. S4: Based on the structural parameter field of the compacted slag soil, extract the particle contact force and displacement deviation, use the centrality algorithm to calculate the node weights to identify the main load channels, and establish a particle load transfer structure set. S5: Based on the particle load transfer structure set, calculate the ratio of shear force to support force to identify the instability zone, perform weighted integration of the range and direction of the low stability zone, extract extreme value nodes to form a stability matrix, and establish the stability judgment result of the slag and soil structure.

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