A quantitative calculation method and system for damage degree of underground surrounding rock using multi-physics field coupling

Abstract

This invention relates to the field of damage calculation technology, specifically to a method and system for quantitatively calculating the damage degree of underground surrounding rock using multi-physics field coupling. The system includes a model construction module, a quantitative damage calculation module, and a cloud map generation module. Based on engineering geological survey data, a geometric model of the underground surrounding rock in the area to be analyzed is established. A set rock mass stress field module and a rock mass seepage field module are bidirectionally coupled based on predetermined coupling variables to obtain a multi-physics field coupled numerical model. The multi-physics field coupled damage potential is calculated based on the rock mass parameters calculated from the multi-physics field coupled numerical model, and the corresponding quantitative damage degree is calculated based on a predetermined damage degree function. Based on the acquired actual surrounding rock data, time-step iterative calculations are performed using the multi-physics field coupled numerical model, and the calculated quantitative damage degrees are aggregated to generate a damage degree cloud map. This method solves the problem of insufficient consideration of the multi-physics field coupling mechanism, which leads to low quantitative accuracy.

Description

Technical Field

[0001] This invention relates to the field of damage calculation technology, and in particular to a method and system for quantitative calculation of damage degree of underground surrounding rock coupled with multi-physics field coupling. This invention can be applied to the fields of damage assessment, early warning and support design in geotechnical engineering such as tunnels, mines and underground caverns. Background Technology

[0002] In the construction and operation of geotechnical engineering projects such as tunnels, mines, and underground caverns, accurate assessment of the damage level of underground surrounding rock is crucial for disaster early warning, stability evaluation, and support design. Traditional methods for assessing surrounding rock damage mainly rely on the following two approaches: 1. Empirical methods based on field monitoring: This involves deploying sensors such as displacement gauges and stress gauges inside or on the surface of the surrounding rock to acquire single physical field data such as displacement and stress. Engineers use this data and engineering experience (such as convergence displacement thresholds) to qualitatively or semi-quantitatively determine the stability state of the surrounding rock. This method heavily relies on the engineer's personal experience, lacks universality and precise quantitative standards, and is difficult to provide accurate early warnings in the early stages of damage. 2. Numerical simulation based on a single physical field: This uses finite element or discrete element software to consider only the influence of single factors such as stress field or seepage field on the surrounding rock, and assesses stability by calculating the plastic zone or safety factor of the rock mass. However, underground surrounding rock is actually in a complex thermo-hydraulic-mechanical-chemical (THMC) multi-physics coupled environment. For example, excavation disturbance causes stress redistribution (mechanical field), which alters the rock mass fracture structure and consequently affects groundwater seepage (seepage field). The resulting changes in pore water pressure further affect rock mass stress, while the softening effect of water reduces rock mass strength. This multi-field coupling effect is a significant cause of surrounding rock damage evolution. Traditional single-physics-field simulation methods cannot accurately reflect this complex process, leading to significant discrepancies between calculated results and actual conditions, and hindering precise quantitative calculation of damage. Both of the aforementioned approaches fail to adequately consider the multi-physics-field coupling mechanism, resulting in low quantitative accuracy. Summary of the Invention

[0003] The purpose of this invention is to provide a method and system for quantitatively calculating the damage degree of underground surrounding rock by multi-physics field coupling, which solves the problem of low quantitative accuracy caused by insufficient consideration of the multi-physics field coupling mechanism.

[0004] To achieve the above objectives, in a first aspect, the present invention provides a method for quantitatively calculating the damage degree of underground surrounding rock using multi-physics field coupling, comprising the following steps:

[0005] Based on engineering geological survey data, a geometric model of the underground surrounding rock in the area to be analyzed is established, and the set rock stress field module and rock seepage field module are bidirectionally coupled based on the set coupling variables to obtain a multi-physics field coupled numerical model.

[0006] The multiphysics coupled damage potential is calculated based on the rock mass parameters calculated by the multiphysics coupled numerical model, and the corresponding quantitative damage degree is calculated based on the set damage degree function.

[0007] Based on the acquired actual surrounding rock data, the multi-physics field coupled numerical model is used to perform time-step iterative calculations, and the calculated quantitative damage is aggregated to generate a damage cloud map.

[0008] The formula for calculating the multi-physics coupled damage potential is: D_p=(σ1-σ3) / [(σ_c-α*P_w)*(1+β*(σ1+σ3-2*P_w) / (σ_c-α*P_w))], where σ1 is the first principal stress, σ3 is the third principal stress, σ_c is the uniaxial compressive strength of the rock mass, P_w is the pore water pressure, α is the water-rock softening coefficient, and β is the lithological empirical coefficient.

[0009] Based on engineering geological survey data, a geometric model of the underground surrounding rock in the area to be analyzed is established. Then, based on the set coupling variables, the set rock mass stress field module and rock mass seepage field module are bidirectionally coupled to obtain a multi-physics coupled numerical model, including:

[0010] The computational domain and the corresponding three-dimensional solid region are determined based on engineering geological survey data and geophysical exploration results.

[0011] Based on the geological structure, the surrounding rock in the three-dimensional solid area is divided into rock mass material partitions, and after partitioning, it is discretized to obtain a computational grid. At the same time, a gradient densification strategy is used to divide the grid to obtain a geometric model of the underground surrounding rock in the area to be analyzed.

[0012] Based on the set coupling variables, the set rock mass stress field module and rock mass seepage field module are bidirectionally coupled to obtain a multi-physics field coupled numerical model.

[0013] Specifically, based on the set coupling variables, the set rock mass stress field module and rock mass seepage field module are bidirectionally coupled to obtain a multi-physics coupled numerical model, including:

[0014] Based on the geometric model of the underground surrounding rock in the area to be analyzed, a rock mass stress field module and a rock mass seepage field module are constructed, and values ​​are assigned to the rock mass stress field module and the rock mass seepage field module respectively.

[0015] The rock mass stress field module and the rock mass seepage field module are bidirectionally coupled by setting coupling variables: the volumetric strain of the rock mass calculated by the rock mass stress field module is transferred to the rock mass seepage field module to dynamically update the porosity and permeability coefficient of the rock mass; at the same time, the pore water pressure calculated by the rock mass seepage field module is applied to the rock mass stress field module as a volume force to obtain a multi-physics field coupled numerical model.

[0016] The multiphysics field coupled damage potential includes a numerator and a denominator. The numerator is the difference between the first principal stress and the third principal stress calculated by the rock mass stress field module.

[0017] The denominator is the actual strength of the rock mass after being weakened by the seepage field multiplied by the strength enhancement coefficient of the confining pressure effect, and then divided by the actual strength of the rock mass after being weakened by the seepage field.

[0018] Specifically, the multiphysics coupled damage potential is calculated based on the rock mass parameters calculated by the multiphysics coupled numerical model, and the corresponding quantitative damage degree is calculated based on the set damage degree function, including:

[0019] The multiphysics coupled damage potential is calculated based on the rock mass parameters calculated by the multiphysics coupled numerical model.

[0020] When the multiphysics field coupled damage potential is less than 1, the quantitative damage degree is 0;

[0021] When the multiphysics coupling damage potential is greater than or equal to 1, the corresponding quantitative damage degree is calculated based on the set damage degree function.

[0022] The formula for calculating the damage degree function is as follows:

[0023] D = 1 - exp[-k * (D_p - 1.0)], where D_p is the multiphysics coupling damage potential, (D_p - 1.0) is the damage driving increment, and k is the damage evolution rate coefficient.

[0024] The method further includes:

[0025] The low-stress field and seepage field in the multiphysics coupled numerical model are initialized;

[0026] The entire project process is discretized into several consecutive computational construction steps, each computational construction step representing a project activity; each computational construction step is discretized into multiple computational time steps.

[0027] Specifically, based on the acquired actual surrounding rock data, the multiphysics coupled numerical model is used for time-step iterative calculations, and the calculated quantitative damage is aggregated to generate a damage cloud map, including:

[0028] Update the geometry and boundaries of the multiphysics coupled numerical model according to the instructions of the current calculation construction step;

[0029] The rock mass stress field module and the rock mass seepage field module are calculated separately, and the coupling variables are transferred.

[0030] Determine whether the calculation results of the rock mass stress field module and the rock mass seepage field module are less than the preset convergence tolerance. If they are greater than the set convergence tolerance, recalculate. If they are less than the set convergence tolerance, calculate the corresponding quantitative damage degree and aggregate the calculated quantitative damage degree to generate a damage degree cloud map.

[0031] If the damage is less than the set convergence tolerance, the corresponding quantitative damage degree is calculated, and a damage degree cloud map is generated based on the calculated quantitative damage degree, including:

[0032] Traverse each unit or node in the multiphysics coupled numerical model, read the field variable data that has converged at the current calculation time step, and calculate the corresponding quantitative damage degree.

[0033] The predefined color spectrum is mapped onto the quantitative damage value of each unit or node, and a damage cloud map is generated using graphics rendering technology.

[0034] In a second aspect, the present invention provides a multi-physics field coupled underground surrounding rock damage quantitative calculation system, which is applied to a multi-physics field coupled underground surrounding rock damage quantitative calculation system as provided in the first aspect. The multi-physics field coupled underground surrounding rock damage quantitative calculation system includes a model building module, a quantitative damage calculation module and a cloud map generation module.

[0035] The model building module is used to establish a geometric model of the underground surrounding rock in the area to be analyzed based on engineering geological survey data, and to bidirectionally couple the set rock mass stress field module and the rock mass seepage field module based on the set coupling variables to obtain a multi-physics field coupled numerical model.

[0036] The quantitative damage calculation module is used to calculate the multi-physics field coupled damage potential based on the rock mass parameters calculated by the multi-physics field coupled numerical model, and to calculate the corresponding quantitative damage degree based on the set damage degree function.

[0037] The cloud map generation module is used to perform time-step iterative calculations based on the acquired actual surrounding rock data using the multi-physics field coupled numerical model, and to generate a damage cloud map based on the calculated quantitative damage degree.

[0038] This invention discloses a method and system for quantitatively calculating the damage degree of underground surrounding rock using multi-physics field coupling. The system includes a model construction module, a quantitative damage calculation module, and a cloud map generation module. Based on engineering geological survey data, a geometric model of the underground surrounding rock in the area to be analyzed is established. A rock mass stress field module and a rock mass seepage field module are bidirectionally coupled based on set coupling variables to obtain a multi-physics field coupled numerical model. The multi-physics field coupled damage potential is calculated based on the rock mass parameters calculated from the multi-physics field coupled numerical model, and the corresponding quantitative damage degree is calculated based on a set damage degree function. Based on the acquired... Actual surrounding rock data is used to perform time-step iterative calculations using the multiphysics coupled numerical model. Based on the calculated quantitative damage degree, a damage degree cloud map is generated. By establishing a mathematical model that considers seepage-stress coupling and defining a damage degree function that integrates stress state and seepage effect, the damage degree calculation is not only based on mechanical response but also includes the weakening effect of seepage field, which is more in line with the actual physical process of underground engineering. By constructing a continuous damage degree scalar from 0 (no damage) to 1 (complete destruction), the originally vague and empirical judgment of surrounding rock condition is transformed into a precise numerical index, which greatly improves the objectivity and accuracy of the assessment. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below.

[0040] Figure 1 This is a schematic diagram illustrating the steps of a method for quantitatively calculating the damage degree of underground surrounding rock through multi-physics field coupling, according to the first embodiment of the present invention.

[0041] Figure 2 This is a flowchart illustrating a method for quantitatively calculating the damage degree of underground surrounding rock using multi-physics field coupling, as provided by this invention.

[0042] Figure 3 This is a schematic diagram of the structural principle of a multi-physics field coupled underground surrounding rock damage quantitative calculation system according to the second embodiment of the present invention.

[0043] Figure 4 This is a schematic diagram of the electronic device of the present invention.

[0044] In the diagram: 101 - Model building module, 102 - Quantitative damage calculation module, 103 - Cloud map generation module. Detailed Implementation

[0045] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application.

[0046] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any and all possible combinations of one or more of the associated listed items.

[0047] It should be understood that although the terms first, second, third, etc., may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."

[0048] The first embodiment of this application is as follows:

[0049] Please see Figures 1-2 This invention provides a method for quantitatively calculating the damage degree of underground surrounding rock through multi-physics field coupling, comprising the following steps:

[0050] S101. Based on the engineering geological survey data, establish a geometric model of the underground surrounding rock in the area to be analyzed, and couple the set rock mass stress field module and the rock mass seepage field module in two directions based on the set coupling variables to obtain a multi-physics field coupled numerical model.

[0051] Specifically, firstly, based on engineering geological survey reports, borehole data, and geophysical exploration results (such as seismic wave CT and resistivity imaging), the computational domain of the model is determined. This computational domain should be large enough to ensure that boundary effects do not significantly affect the calculation results for areas of engineering interest (such as the tunnel perimeter). Typically, the distance between the model boundary and the edge of the tunnel is no less than 3 to 5 times the characteristic size (such as the diameter) of the tunnel. In three-dimensional space, the geometric boundaries of the model are delineated according to the above data, forming a three-dimensional solid region that includes the excavation space such as underground tunnels and caverns.

[0052] Within a defined three-dimensional geometric entity, the surrounding rock is divided into several rock mass material zones based on geological structures such as lithological variations, faults, and densely jointed zones. Each zone represents a geological unit with relatively uniform mechanical and hydraulic properties. For example, the model can be divided into "intact sandstone zones," "fault fracture zones," and "mudstone interlayer zones." For large-scale faults and joints, they are embedded into the model as discrete structural surface geometric entities, and given thickness (even zero-thickness interfaces need to be numerically treated as units with minute physical thickness) and specific spatial attitude (strike, dip, and dip angle).

[0053] The previously partitioned geometric model is discretized to generate a computational mesh. Mesh element types can be tetrahedral, hexahedral, or a combination thereof. To achieve a balance between computational accuracy and efficiency, a gradient refinement strategy is employed for mesh generation. Specifically, dense mesh elements are used in areas near excavation walls, faults, and other regions with stress concentrations and drastic seepage changes; while a relatively sparse mesh is used at the model's outer boundary, away from these critical areas. This strategy ensures that computational resources are concentrated on the most critical areas. Thus, a discretized geometric model of the surrounding rock of the area to be analyzed, faithfully representing the geological prototype, is complete.

[0054] On the generated geometric mesh, two core physics modules are established: a rock mass stress field module and a rock mass seepage field module, and each module is assigned corresponding material properties and governing equations. After bidirectional coupling of the two modules, a multiphysics coupled numerical model is obtained.

[0055] Rock mass stress field module definition: To simulate the entire process of rock mass from elastic to plastic and finally to failure after excavation, an elastoplastic constitutive model is assigned to all rock mass material zones. Specifically, the Mohr-Coulomb plasticity criterion is adopted, which can well describe the shear failure characteristics of soil and rock materials, and its yield surface is determined by cohesion and internal friction angle.

[0056] A complete set of mechanical parameters is assigned to each rock mass material partition and structural plane geometry. This set of parameters includes:

[0057] Elastic parameters: elastic modulus, Poisson's ratio.

[0058] Strength parameters: cohesion, internal friction angle.

[0059] Unit weight: The natural unit weight of a rock mass.

[0060] These parameters were determined comprehensively through indoor rock mechanics tests, in-situ field tests (such as flat jack tests), and engineering geological analogy.

[0061] Rock mass seepage field module definition: Assuming that the flow of groundwater in the pores and fissures of the rock mass follows Darcy's law, a rock mass seepage field module is established.

[0062] Assign corresponding hydraulic parameters to each rock mass material zone and structural surface geometry, mainly including:

[0063] Initial permeability coefficient: Characterizes the water conductivity of a rock mass in an undisturbed state.

[0064] Porosity: The volume ratio of pores in a unit volume of rock mass.

[0065] Coupling mechanism explanation:

[0066] The influence of stress field on seepage field (stress-seepage coupling): When rock mass deforms under engineering disturbance, its internal pores and fractures open or close. Opening leads to increased porosity, which in turn increases the permeability coefficient; closing leads to decreased porosity and a lower permeability coefficient. This is a dynamic coupling path in which deformation controls seepage capacity.

[0067] The influence of the seepage field on the stress field (seepage-stress coupling): The pore water pressure in the seepage field affects the stress field in two ways: First, it acts on the rock mass skeleton, generating a "volume force" (equivalent to hydrostatic pressure), changing the effective stress state of the rock mass; second, the physicochemical effects of water soften the bonds between rock mineral particles, leading to the deterioration of its mechanical parameters (especially cohesion). This is a coupling path where fluid pressure and chemical effects control the mechanical response.

[0068] To achieve the above mechanism, two explicit variable transfer channels are established in the model:

[0069] Coupling Channel 1: Volumetric Strain to Pore / Permeability (Stress → Seepage)

[0070] At each calculation step, the rock mass stress field module first solves for the volumetric strain of the rock mass in each grid cell, i.e., the change in volume per unit volume. This volumetric strain is then transmitted in real time to the rock mass seepage field module. Upon receiving this data, the rock mass seepage field module dynamically updates the porosity and permeability coefficient of the cell based on a built-in dynamic seepage model. A typical innovative model is as follows:

[0071] The updated porosity is the initial porosity + (1 - initial porosity) multiplied by the volumetric strain increment, i.e., n_new = n_initial + (1 - n_initial) * Δε_v, where n_initial is the initial porosity and Δε_v is the volumetric strain increment.

[0072] The updated permeability coefficient is the initial permeability coefficient multiplied by (updated porosity divided by initial porosity) raised to the power of A, i.e., k_new = k_initial * (n_new / n_initial)^A, where k_initial is the initial permeability coefficient, and A is an empirical index, usually calibrated experimentally, reflecting the amplification effect of fracture connectivity on permeability. Through this channel, the deformation of the rock mass directly and dynamically controls its water conductivity.

[0073] Coupling Channel Two: From Pore Water Pressure to Body Force and Strength (Seepage → Stress)

[0074] Within the same calculation time step, the rock mass seepage field module uses the updated seepage parameters to solve for the pore water pressure distribution of each grid cell.

[0075] The pore water pressure is transmitted back to the rock mass stress field module in real time. Upon receiving this data, the rock mass stress field module performs two key operations:

[0076] Applying equivalent volume force: This applies the negative gradient of pore water pressure. As an additional volume force, it is introduced into the equilibrium equation of the stress field to characterize the pushing effect of water pressure on the rock mass skeleton.

[0077] Strength degradation is implemented: Based on the current pore water pressure value of the element, the mechanical strength parameters (mainly cohesion) of the element are reduced in real time using a water-rock softening function. For example, c_effective = c_initial * exp(-λ * P_w), where c_initial is the initial cohesion, λ is the water softening coefficient, c_effective is the reduced effective cohesion, and P_w is the current pore water pressure value of the element. The physicochemical softening effect of water is directly incorporated into the stress calculation.

[0078] Through iterative calculations and data exchange between the two coupled channels, the rock mass stress field module and the rock mass seepage field module no longer operate independently, but instead form a closely interactive and mutually feedback-based collaborative computing system. Within each time increment step, the two modules solve alternately until the displacement, stress, and pore water pressure of the entire system all satisfy the convergence criteria, thus completely reproducing the complex multiphysics coupling process in the underground surrounding rock.

[0079] S102. Calculate the multi-physics coupled damage potential based on the rock mass parameters calculated by the multi-physics coupled numerical model, and calculate the corresponding quantitative damage degree based on the set damage degree function.

[0080] Specifically, the multiphysics coupled numerical model provides time-varying rock mass data for each point within the entire surrounding rock area, including:

[0081] From the rock mass stress field module: complete stress tensor components such as the first principal stress (σ1) and the third principal stress (σ3). From the rock mass seepage field module: pore water pressure (P_w).

[0082] The multiphysics coupled damage potential is constructed, and its formula includes a numerator and a denominator. The numerator is the difference between the first principal stress and the third principal stress calculated by the rock mass stress field module. The formula expression is:

[0083] D_p=(σ1-σ3) / [(σ_c-α*P_w)*(1+β*(σ1+σ3-2*P_w) / (σ_c-α*P_w))].

[0084] Wherein, D_p: multiphysics coupling damage potential; σ1: first principal stress, unit: Pascal (Pa); σ3: third principal stress; σ_c: uniaxial compressive strength of rock mass, unit: Pascal (Pa), refers to the ultimate strength of an intact rock sample under uniaxial compression conditions when it fails in a dry or natural state. This parameter is a basic mechanical property of rock mass material zoning and is determined through indoor rock mechanics tests; P_w: pore water pressure, unit: Pascal (Pa), refers to the pressure acting on water in the pores and fissures of the rock mass. This data is directly derived from the real-time calculation results of the rock mass seepage field module in the multiphysics coupling numerical model; α: water-rock softening coefficient, a dimensionless empirical coefficient (α ≥ 0), used to quantitatively characterize the chemical softening and physical degradation effects of pore water pressure on rock mass strength. Its value is calibrated by comparing the uniaxial compressive strength tests of rock samples in dry and saturated states. α = 0 indicates that water has no softening effect; α > 0 The larger the value, the more significant the softening and deterioration effect of water; β: lithological empirical coefficient, a dimensionless material constant (β ≥ 0), used to characterize the sensitivity of different lithologies to the confining pressure effect. For soft, highly plastic rock masses (such as mudstone), the confining pressure has a significant strength-enhancing effect, and the β value is large; for hard, brittle rock masses (such as granite), the confining pressure effect is relatively weak, and the β value is small. This coefficient is determined by fitting the results of triaxial compression tests on rock samples.

[0085] Molecular part: (σ1-σ3)

[0086] This is called the maximum shear stress or deviatoric stress. It directly reflects the strength of the shear driving force on the rock mass. The larger this value, the stronger the "driving force" that causes the rock mass to undergo shear failure. This part comes directly from the calculation results of the rock mass stress field module. Among them, under the three-dimensional stress state, the three principal stresses are ordered according to their algebraic values ​​as follows: first principal stress σ1 ≥ second principal stress σ2 ≥ third principal stress σ3. Under the Mohr-Coulomb strength criterion framework adopted by the technical solution described in this paper, the shear failure of the material mainly depends on the maximum shear stress, that is, it is driven by the difference (σ1-σ3) between the maximum principal stress (σ1) and the minimum principal stress (σ3). The second principal stress σ2 has a very small influence on the strength under this criterion and is usually ignored. Therefore, σ2 is not included in the formula for defining the multiphysics coupled damage potential D_p. This is a standard treatment method based on classical theory and taking into account engineering practicality.

[0087] Denominator: Overall shear resistance

[0088] The denominator represents the comprehensive shear strength of the rock mass under the current environment (considering confining pressure and seepage). (σ_c-α*P_w): This is a multi-field coupling correction for the uniaxial compressive strength σ_c of the rock mass. σ_c is the inherent strength of the rock mass when it is dry or without softening. α*P_w is a coupling term. The introduction of the coefficient α (water-rock softening coefficient) allows this term to quantify the chemical softening and deterioration effect of pore water pressure P_w on the rock mass strength. The value of α can be determined by comparing the laboratory "uniaxial compressive strength test of saturated rock" with the dry test. Therefore, (σ_c-α*P_w) represents the actual strength of the rock mass after being weakened by the seepage field.

[0089] The overall term within parentheses (1+β*(σ1+σ3-2*P_w) / (σ_c-α*P_w)) quantifies the enhancing effect of confining pressure on rock mass strength. Here, (σ1 + σ3 - 2·P_w) represents the effective principal stress, and β is an empirical lithology coefficient reflecting the sensitivity of different lithologies to confining pressure. For hard rocks like granite, the β value is smaller; for soft rocks like mudstone, the confining pressure effect is more significant, and the β value is larger.

[0090] Importantly, the same combination of effective stresses (σ1-P_w) and (σ3-P_w) is used here, which captures the mechanical effect of pore water pressure (reducing confining pressure).

[0091] The complete physical meaning of the multiphysics coupled damage potential D_p is: D_p = (shear force driving rock mass failure) / (comprehensive shear strength of the rock mass after considering confining pressure enhancement and seepage weakening). When D_p < 1: it indicates that the comprehensive shear strength of the rock mass is greater than the shear driving force it experiences, and the rock mass is in a stable state. When D_p ≥ 1: it indicates that the shear driving force has reached or exceeded the comprehensive shear capacity of the rock mass, and the rock mass enters the stage of damage initiation and evolution.

[0092] When the multiphysics coupling damage potential D_p is less than 1, microcracks, pores, and other defects within the rock mass are in a stable state and will not propagate. At this time, the mechanical behavior of the rock mass is mainly characterized by recoverable elastic deformation, so its quantitative damage degree D is defined as 0. When the multiphysics coupling damage potential D_p reaches or exceeds 1, it indicates that the rock mass begins to enter a yielding state, and the internal microcracks begin to activate, propagate stably, and converge. This is a continuous process from quantitative change to qualitative change: in the initial stage, the propagation of a small number of microcracks has little impact on the macroscopic stiffness and strength of the rock mass; as the multiphysics coupling damage potential D_p further increases, the damage accelerates and forms macroscopic cracks; finally, when the damage accumulates to a critical state, the rock mass completely loses its bearing capacity.

[0093] To accurately describe the aforementioned continuous damage process, a continuous damage degree function based on an exponential function is introduced. The choice of this function has a solid physical basis: the exponential function can well simulate the typical S-shaped evolution of material damage, characterized by "slow initiation, accelerated development, and eventual saturation." This function ensures that the quantitative damage degree D increases continuously, smoothly, and monotonically with the increase of the multiphysics coupled damage potential D_p, asymptotically approaching 1 from 0, perfectly conforming to the physical nature of rock damage.

[0094] When the multiphysics coupling damage potential D_p < 1.0: the quantitative damage degree D = 0;

[0095] Physical meaning: The rock mass is in a stable or elastic state, with no new internal damage or damage not developing. This is a clearly defined non-destructive threshold.

[0096] When the multiphysics coupling damage potential D_p ≥ 1.0: the quantitative damage degree D = 1 - exp[-k*(D_p - 1.0)];

[0097] Physical meaning: The rock mass has entered the damage evolution stage. The damage degree starts from 0 and increases continuously as D_p exceeds the critical value (1.0). When the driving potential increases infinitely, exp[-k*(D_p-1.0)]→0, so D→1, indicating that the rock mass tends to be completely destroyed.

[0098] (D_p-1.0): Damage-driven increment. This term represents the "excess amount" of the multiphysics coupled damage potential D_p exceeding its critical state (D_p=1). It is the direct cause driving the occurrence and development of damage. The larger the value of (D_p-1.0), the stronger the "residual force" driving rock mass failure, and the more rapid and severe the damage development should be.

[0099] k: Damage evolution rate coefficient. k is a core material constant in this model, a scalar value greater than 0. k characterizes the sensitivity of a specific lithology to damage-driving forces. For hard, brittle rocks (such as granite and quartzite), once the yield point is reached, microcracks rapidly destabilize and propagate, leading to macroscopic fracture. These rocks have relatively large k values. The damage degree D increases rapidly when D_p just exceeds 1. For soft, ductile rocks (such as mudstone and salt rock), they exhibit good rheological properties after yielding, and damage development is slow. These rocks have relatively small k values. Even if D_p is significantly greater than 1, the increase in damage degree D is relatively gradual.

[0100] The k value needs to be calibrated through corresponding indoor rock mechanics tests. For example, by conducting triaxial compression tests on rock samples and simultaneously monitoring their full stress-strain curves and changes in acoustic emission or wave velocity (these are indirect measurements of damage), the relationship between axial strain (or deviatoric stress) and damage degree can be established, and then the k value that best fits the experimental data can be calculated.

[0101] After completing the first step of the multiphysics coupled numerical model calculation, the program automatically traverses every element or integration point in the computational domain. For each traversed object, the calculated multiphysics coupled damage potential D_p is substituted into the aforementioned continuous damage degree function. Simultaneously, the damage evolution rate coefficient k, which has been preset for the rock mass material partition, is called to calculate the final quantitative damage degree D for that element / node. This process is repeated for all locations, thereby generating a completely new, spatially distributed scalar field—the quantitative damage degree D field—within the entire model region.

[0102] S103. Based on the acquired actual surrounding rock data, the multi-physics field coupled numerical model is used to perform time-step iterative calculations, and the calculated quantitative damage is aggregated to generate a damage cloud map.

[0103] Specifically, after the multiphysics coupled numerical model is constructed, when new surrounding rock data is obtained, the multiphysics coupled numerical model first needs to be initialized, including: initial geostress field: usually obtained through gravity loading or inversion of measured geostress data, as the initial condition of the rock mass stress field module; initial seepage field: based on the groundwater level or measured pore pressure data, the initial pore water pressure P_w distribution of the entire model is defined as the initial condition of the rock mass seepage field module.

[0104] Then, the entire engineering process (such as tunnel excavation in stages and anchor bolt installation) is discretized into several consecutive computational construction steps. Each computational construction step represents a specific engineering activity (e.g., "excavating the first ring" or "installing the first set of anchor bolts"). Each computational construction step itself may be a continuous process, so it is further discretized into multiple computational time steps (Δt). The length of the time step is automatically controlled or manually set by the solver's stability and accuracy requirements.

[0105] For each computation time step, execute the following core loop operation until the convergence criterion is met:

[0106] A. Update Model State: Update the model geometry and boundaries according to the instructions of the current construction step. For example, in the excavation step, "kill" the elements within the excavation area (make them no longer participate in the calculation) and remove the constraints on the excavation boundaries.

[0107] B. Solving the rock mass stress field module:

[0108] Based on the pore water pressure P_w field of the previous time step, it is applied as a volume force to the equilibrium equation, and mechanical parameters (such as effective cohesion) are used after reduction by the water-rock softening function.

[0109] The equilibrium equations of the rock mass stress field module are calculated to solve for the displacement, strain, and stress (including the first principal stress σ1 and the third principal stress σ3) of all elements at the current time step.

[0110] C. Coupled variable transfer (stress field → seepage field):

[0111] Extract the volumetric strain increment of the rock mass for each unit from the output of the rock mass stress field module.

[0112] The volumetric strain increment of this rock mass is transmitted to the rock mass seepage field module.

[0113] The rock mass seepage field module dynamically updates the porosity and permeability coefficient of each unit based on the received volumetric strain, according to the built-in dynamic permeability model.

[0114] D. Solving the rock mass seepage field module:

[0115] After updating the material hydraulic parameters, the seepage equation calculation of the rock mass seepage field module is performed under the current boundary conditions (such as the excavation face becoming a drainage boundary).

[0116] Solve for the new distribution of pore water pressure P_w in the entire model at the current time step.

[0117] E. Transfer of coupled variables (seepage field → stress field):

[0118] Transfer the newly calculated pore water pressure \(P_w\) field back to the rock mass stress field module to provide input for stress calculation in the next iteration step or time step.

[0119] F. Convergence check:

[0120] Check whether the solution results (such as displacement increment, pore water pressure increment) of the rock mass stress field module and the rock mass seepage field module are less than the preset convergence tolerance.

[0121] If not converged, return to step B and perform a new round of iteration using the latest calculated field variables until the solutions of both physical fields reach a steady state.

[0122] If converged, it indicates that the fully coupled calculation for the current calculation time step is completed. Save all field variables, then automatically advance to the next calculation time step and repeat the process from A to F.

[0123] After the coupled solution converges at each calculation time step, start calculating the damage degree.

[0124] It will traverse each element or node in the model and read the converged field variable data at the current time step: the first principal stress \(\sigma_1\), the third principal stress \(\sigma_3\), and the pore water pressure \(P_w\).

[0125] For each calculation point:

[0126] First, calculate the current multi - physical - field coupling damage potential \(D_p\) according to the formula in step S102.

[0127] Subsequently, according to the rock mass material partition to which the point belongs, call its corresponding damage evolution rate coefficient \(k\) and substitute it into the continuous damage degree function to calculate the quantitative damage degree \(D\) of this point at the current time step.

[0128] This process is executed once after each converged time step, thus generating a sequence of quantitative damage degree \(D\) fields evolving with time (or with construction steps).

[0129] When the entire simulation (all construction steps and time steps) is completed, the spatial distribution data of the quantitative damage degree \(D\) in the final state at the last time step is obtained.

[0130] Color mapping scheme definition:

[0131] Define a continuous color spectrum. For example:

[0132] The blue color system represents the low - damage area (\(D\approx0\)): representing stable and undamaged rock mass.

[0133] The green - to - yellow color system represents the moderate - damage area (\(0 < D < 0.6\)): representing that the rock mass has been damaged but still has a certain bearing capacity and needs attention.

[0134] Orange to red indicates a highly damaged area (0.6≤D<1.0): representing severe rock mass damage, possibly with macroscopic cracks and poor stability.

[0135] Dark red / black indicates a completely destroyed area (D≈1.0): This means the rock mass has lost its bearing capacity.

[0136] The defined color spectrum is mapped to the quantitative damage value D of each unit or node. That is, a corresponding color is assigned to each location based on the D value.

[0137] Using graphics rendering technology, the entire 3D computational model and its color information are rendered into a single (or series of) colored, continuously gradient images. This is the final surrounding rock damage cloud map. Outputting the final state of the surrounding rock damage cloud map clearly shows the damage distribution of the surrounding rock after the project is completed, and can accurately delineate high-damage areas and potential failure areas that require reinforcement.

[0138] A precise quantification of damage degree has been achieved: By constructing a continuous damage degree scalar from 0 (no damage) to 1 (complete destruction), the originally vague and empirical judgment of the surrounding rock condition is transformed into a precise numerical index, which greatly improves the objectivity and accuracy of the assessment.

[0139] It truly reflects the multi-field coupling mechanism: By establishing a mathematical model that considers seepage-stress coupling and defining a "damage potential" function that integrates stress state and seepage effect, the calculation of damage degree is not only based on mechanical response, but also includes the weakening effect of seepage field, which is more in line with the actual physical process of underground engineering.

[0140] Possessing dynamic evolution and spatial visualization capabilities: This method can not only calculate the static damage degree at a certain moment, but also simulate the dynamic evolution of damage as the project progresses (such as excavation and support) through time-step iteration. The final generated "surrounding rock damage degree cloud map" can intuitively display the spatial distribution of damage, accurately locate potential weak areas and failure areas, and provide a direct basis for targeted support design.

[0141] The second embodiment of this application is as follows:

[0142] Please see Figure 3 The present invention provides a multi-physics field coupled underground surrounding rock damage quantitative calculation system, which is applied to a multi-physics field coupled underground surrounding rock damage quantitative calculation method provided in the first embodiment. The multi-physics field coupled underground surrounding rock damage quantitative calculation system includes a model construction module 101, a quantitative damage calculation module 102 and a cloud map generation module 103.

[0143] The model construction module 101 is used to establish a geometric model of the underground surrounding rock in the area to be analyzed based on engineering geological survey data, and to bidirectionally couple the set rock stress field module and the rock seepage field module based on the set coupling variables to obtain a multi-physics field coupled numerical model.

[0144] The quantitative damage calculation module 102 is used to calculate the multi-physics field coupled damage potential based on the rock mass parameters calculated by the multi-physics field coupled numerical model, and to calculate the corresponding quantitative damage degree based on the set damage degree function.

[0145] The cloud map generation module 103 is used to perform time-step iterative calculations based on the acquired actual surrounding rock data using the multi-physics field coupled numerical model, and to generate a damage cloud map based on the calculated quantitative damage degree.

[0146] Regarding the system in the above embodiments, the specific ways in which each module performs operations have been described in detail in the embodiments related to the method, and will not be elaborated here.

[0147] For the system embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this application according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0148] Accordingly, this application also provides an electronic device, comprising: one or more processors; a memory for storing one or more programs; and, when the one or more programs are executed by the one or more processors, causing the one or more processors to implement the multiphysics-coupled underground surrounding rock damage quantitative calculation method as described above. Figure 4 The diagram shown is a hardware structure diagram of any device with data processing capabilities, which is part of a multi-physics field coupled underground surrounding rock damage quantitative calculation system provided in an embodiment of the present invention. (Except for...) Figure 4 In addition to the processor, memory, and network interface shown, any data processing device in the embodiment may also include other hardware depending on the actual function of the data processing device, which will not be described in detail here.

[0149] Accordingly, this application also provides a computer-readable storage medium storing computer instructions, which, when executed by a processor, implement the above-described method for quantitative calculation of underground surrounding rock damage using multi-physics coupling. The computer-readable storage medium can be an internal storage unit of any data-processing device as described in any of the foregoing embodiments, such as a hard disk or memory. The computer-readable storage medium can also be an external storage device, such as a plug-in hard disk, smart media card (SMC), SD card, flash card, etc., equipped on the device. Furthermore, the computer-readable storage medium can include both internal storage units of any data-processing device and external storage devices. The computer-readable storage medium is used to store the computer program and other programs and data required by the data-processing device, and can also be used to temporarily store data that has been output or will be output. Its operating environment mainly includes:

[0150] Hardware: A computing device with a multi-core CPU and large memory (≥32GB), supporting GPU acceleration and 3D graphics rendering;

[0151] Software: Supports multiphysics simulation platforms that support finite element / finite difference methods (such as COMSOL, Abaqus, etc.), and integrates geological modeling, mesh generation, and visualization tools;

[0152] Data: Engineering geological survey data, rock mechanics and seepage parameters, construction sequence and other input data are required;

[0153] Deployment: It can run on local workstations, servers or cloud computing platforms, and supports the entire process from modeling and calculation to damage cloud map generation.

[0154] It is applicable to damage assessment and early warning scenarios in geotechnical engineering such as tunnels, mines, and underground caverns.

[0155] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

[0156] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope.

Claims

1. A method for quantitatively calculating the damage degree of underground surrounding rock through multi-physics field coupling, characterized in that, Includes the following steps: Based on engineering geological survey data, a geometric model of the underground surrounding rock in the area to be analyzed is established, and the set rock stress field module and rock seepage field module are bidirectionally coupled based on the set coupling variables to obtain a multi-physics field coupled numerical model. The multiphysics coupled damage potential is calculated based on the rock mass parameters calculated by the multiphysics coupled numerical model, and the corresponding quantitative damage degree is calculated based on the set damage degree function. Based on the acquired actual surrounding rock data, the multi-physics field coupled numerical model is used to perform time-step iterative calculations, and the calculated quantitative damage is aggregated to generate a damage cloud map. The formula for calculating the multi-physics coupled damage potential is: D_p=(σ1-σ3) / [(σ_c-α*P_w)*(1+β*(σ1+σ3-2*P_w) / (σ_c-α*P_w))], where σ1 is the first principal stress, σ3 is the third principal stress, σ_c is the uniaxial compressive strength of the rock mass, P_w is the pore water pressure, α is the water-rock softening coefficient, and β is the lithological empirical coefficient.

2. The method for quantitatively calculating the damage degree of underground surrounding rock using multi-physics field coupling as described in claim 1, characterized in that, Based on engineering geological survey data, a geometric model of the underground surrounding rock in the area to be analyzed is established. Then, based on the set coupling variables, the set rock mass stress field module and rock mass seepage field module are bidirectionally coupled to obtain a multi-physics coupled numerical model, including: The computational domain and the corresponding three-dimensional solid region are determined based on engineering geological survey data and geophysical exploration results. Based on the geological structure, the surrounding rock in the three-dimensional solid area is divided into rock mass material partitions, and after partitioning, it is discretized to obtain a computational grid. At the same time, a gradient densification strategy is used to divide the grid to obtain a geometric model of the underground surrounding rock in the area to be analyzed. Based on the set coupling variables, the set rock mass stress field module and rock mass seepage field module are bidirectionally coupled to obtain a multi-physics field coupled numerical model.

3. The method for quantitatively calculating the damage degree of underground surrounding rock using multi-physics field coupling as described in claim 2, characterized in that, Based on the defined coupling variables, the rock mass stress field module and the rock mass seepage field module are bidirectionally coupled to obtain a multiphysics coupled numerical model, including: Based on the geometric model of the underground surrounding rock in the area to be analyzed, a rock mass stress field module and a rock mass seepage field module are constructed, and values ​​are assigned to the rock mass stress field module and the rock mass seepage field module respectively. The rock mass stress field module and the rock mass seepage field module are bidirectionally coupled by setting coupling variables: the volumetric strain of the rock mass calculated by the rock mass stress field module is transferred to the rock mass seepage field module to dynamically update the porosity and permeability coefficient of the rock mass; at the same time, the pore water pressure calculated by the rock mass seepage field module is applied to the rock mass stress field module as a volume force to obtain a multi-physics field coupled numerical model.

4. The method for quantitatively calculating the damage degree of underground surrounding rock using multi-physics field coupling as described in claim 1, characterized in that, The multiphysics coupled damage potential is calculated based on the rock mass parameters obtained from the multiphysics coupled numerical model, and the corresponding quantitative damage degree is calculated based on the set damage degree function, including: The multiphysics coupled damage potential is calculated based on the rock mass parameters calculated by the multiphysics coupled numerical model. When the multiphysics field coupled damage potential is less than 1, the quantitative damage degree is 0; When the multiphysics coupling damage potential is greater than or equal to 1, the corresponding quantitative damage degree is calculated based on the set damage degree function.

5. The method for quantitatively calculating the damage degree of underground surrounding rock using multi-physics field coupling as described in claim 4, characterized in that, The formula for calculating the damage degree function is as follows: D = 1 - exp[-k * (D_p - 1.0)], where D_p is the multiphysics coupling damage potential, (D_p - 1.0) is the damage driving increment, and k is the damage evolution rate coefficient.

6. The method for quantitatively calculating the damage degree of underground surrounding rock using multi-physics field coupling as described in claim 1, characterized in that, The method further includes: The low-stress field and seepage field in the multiphysics coupled numerical model are initialized; The entire project process is discretized into several consecutive computational construction steps, each computational construction step representing a project activity; each computational construction step is discretized into multiple computational time steps.

7. The method for quantitatively calculating the damage degree of underground surrounding rock using multi-physics field coupling as described in claim 6, characterized in that, Based on the acquired actual surrounding rock data, the multiphysics coupled numerical model is used for time-step iterative calculations, and the calculated quantitative damage is aggregated to generate a damage cloud map, including: Update the geometry and boundaries of the multiphysics coupled numerical model according to the instructions of the current calculation construction step; The rock mass stress field module and the rock mass seepage field module are calculated separately, and the coupling variables are transferred. Determine whether the calculation results of the rock mass stress field module and the rock mass seepage field module are less than the preset convergence tolerance. If they are greater than the set convergence tolerance, recalculate. If they are less than the set convergence tolerance, calculate the corresponding quantitative damage degree and aggregate the calculated quantitative damage degree to generate a damage degree cloud map.

8. The method for quantitatively calculating the damage degree of underground surrounding rock using multi-physics field coupling as described in claim 7, characterized in that, If the value is less than the set convergence tolerance, the corresponding quantitative damage degree is calculated, and a damage degree cloud map is generated based on the calculated quantitative damage degree, including: Traverse each unit or node in the multiphysics coupled numerical model, read the field variable data that has converged at the current calculation time step, and calculate the corresponding quantitative damage degree. The predefined color spectrum is mapped onto the quantitative damage value of each unit or node, and a damage cloud map is generated using graphics rendering technology.

9. A multi-physics field coupled underground surrounding rock damage quantitative calculation system, applied to the multi-physics field coupled underground surrounding rock damage quantitative calculation method as described in claim 1, characterized in that, The multi-physics field coupled underground surrounding rock damage quantitative calculation system includes a model building module, a quantitative damage calculation module, and a cloud map generation module; The model building module is used to establish a geometric model of the underground surrounding rock in the area to be analyzed based on engineering geological survey data, and to bidirectionally couple the set rock mass stress field module and the rock mass seepage field module based on the set coupling variables to obtain a multi-physics field coupled numerical model. The quantitative damage calculation module is used to calculate the multi-physics field coupled damage potential based on the rock mass parameters calculated by the multi-physics field coupled numerical model, and to calculate the corresponding quantitative damage degree based on the set damage degree function. The cloud map generation module is used to perform time-step iterative calculations based on the acquired actual surrounding rock data using the multi-physics field coupled numerical model, and to generate a damage cloud map based on the calculated quantitative damage degree.

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