Construction method of activation mechanical model of super-large open-pit mine slope rock mass based on geological occurrence
By constructing a dynamic mechanical model of rock mass activation on ultra-large open-pit mine slopes based on geological occurrence, the problem of integrating geological occurrence conditions and mining disturbance effects in existing technologies has been solved. This model enables quantitative identification and early warning of rock mass activation state, improves the accuracy and early warning capability of slope stability analysis, and reduces engineering costs.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA UNIV OF MINING & TECH
- Filing Date
- 2026-04-09
- Publication Date
- 2026-07-14
AI Technical Summary
Existing technologies cannot accurately construct dynamic models of rock mass activation on ultra-large open-pit mine slopes, cannot integrate geological conditions and mining disturbance effects, lack quantitative descriptions of rock mass damage evolution mechanisms, cannot achieve quantitative identification and early warning of rock mass activation status, and are difficult to integrate multi-scale information, resulting in low model prediction accuracy.
A dynamic mechanical model of rock mass activation on ultra-large open-pit mine slope based on geological occurrence is constructed. The influence of geological conditions is quantified by the geological occurrence influence factor GFI. A dynamic mapping model of rock mass equivalent mechanical parameters is established, the rock mass activation index RAI is defined, and multi-field coupled numerical solution is performed by the finite element discrete element coupling method FEM/DEM. A two-way feedback mechanism for monitoring model is established to realize dynamic model updating.
It achieves a precise mapping between geological occurrence conditions and rock mass mechanical response, dynamically characterizes the evolution of rock mass damage under mining disturbance, provides quantitative identification and early warning of rock mass activation state, improves the accuracy and early warning capability of slope stability analysis, reduces unnecessary reinforcement projects, and saves treatment costs.
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Abstract
Description
Technical Field
[0001] This invention relates to the fields of geotechnical engineering and mine safety technology, specifically to a method for constructing a dynamic mechanical model of rock mass activation on ultra-large open-pit mine slopes based on geological occurrence. Background Technology
[0002] With the continuous increase in mineral resource development, the mining depth and scale of ultra-large open-pit mines are constantly improving. The mechanical properties of slope rock masses are significantly deteriorated due to long-term mining disturbance, geological tectonic activity, and changes in hydrogeological conditions. The process of slope rock masses gradually transforming from a stable state to a damaged, activated, and ultimately unstable state exhibits a high degree of nonlinearity and complexity. The instability and activation of slope rock masses not only cause economic losses such as damage to mining faces and production interruptions, but also easily trigger major safety accidents such as landslides and collapses, threatening the lives of mine workers. Therefore, accurately constructing a mechanical model of slope rock mass activation and achieving early prediction and quantitative identification of the rock mass activation state has become a core technological requirement for safe production and efficient mining in ultra-large open-pit mines.
[0003] Currently, various technical systems have been developed for analyzing the stability of open-pit mine slopes both domestically and internationally. Among these, the three most widely used in engineering applications are the limit equilibrium method, the traditional finite element method, and the empirical analogy method. The limit equilibrium method, a classic slope stability analysis method, treats the potential sliding body of the slope as a rigid body. It determines the slope's stability by calculating the ratio of the resisting force to the sliding force. This method has a simple calculation process and requires few parameters, making it widely used in the stability evaluation of simple slopes in small and medium-sized open-pit mines. However, this method is based on the assumption of rigid homogeneity and completely ignores the elastoplastic deformation characteristics of the rock mass itself and the gradual damage evolution process under mining disturbance. It cannot reflect the dynamic changes in the rock mass from microcrack initiation to macroscopic rupture. For ultra-large open-pit mine slopes with complex geological conditions, its evaluation results deviate significantly from the actual engineering situation. Traditional finite element methods (FEMs), relying on continuum mechanics theory, can reflect the stress-strain distribution characteristics of rock masses through meshing and numerical solutions. However, their constitutive models often employ linear elastic or ideal elastoplastic constitutive models, which can only describe the ideal mechanical response of the rock mass. They struggle to accurately characterize the continuous deterioration of rock mass strength under mining disturbances such as blasting vibration, excavation unloading, and groundwater seepage, and cannot achieve dynamic coupling analysis of rock mass damage development and mechanical parameter decay. Empirical analogy methods rely on existing open-pit mine slope engineering cases, determining the evaluation results of target slopes by comparing the stability state under similar geological conditions and mining processes. However, this method is significantly limited by the specific engineering cases, exhibiting poor adaptability to sudden changes in geological conditions and adjustments in mining processes. Furthermore, parameter selection and result judgment are highly subjective, making it difficult to meet the technical requirements for quantitative evaluation of the stability of ultra-large open-pit mine slopes.
[0004] Besides the inherent defects of the aforementioned mainstream methods, existing rock mechanics analysis techniques for ultra-large open-pit mine slopes have also revealed a series of core technical problems that urgently need to be solved in practical engineering applications, becoming key bottlenecks restricting the accurate prediction of rock mass activation state. Firstly, there is a serious disconnect between geological conditions and rock mass mechanical response. Existing mechanical models often simplify complex geological conditions into homogeneous mechanical parameters, failing to fully consider the influence of geological conditions such as the heterogeneity of strata, the spatial distribution characteristics of geological structures, the dynamic changes in hydrogeology, and the differences in rock mass weathering on the macroscopic mechanical properties of the rock mass. This results in the parameter values assigned to the models not matching the actual geological characteristics of the project, and the mechanical calculation results lacking reliability. Secondly, the characterization of rock mass strength loss mechanisms is significantly insufficient. Existing technologies have failed to establish quantitative characterization methods for multi-factor mining disturbances such as blasting vibration, excavation unloading, and groundwater seepage. They also lack a quantitative description of the coupling mechanism of the development and propagation of micro-cracks in the rock mass caused by mining disturbances, leading to macroscopic strength deterioration. Therefore, they cannot dynamically reflect the attenuation law of rock mass mechanical properties during the mining process. Third, there is a lack of critical criteria for slope rock mass activation. Existing technologies can only qualitatively determine the stability or instability of slopes, without establishing a critical state discrimination standard for the continuous evolution process of slope rock mass from stability and damage to activation. This makes it impossible to identify the precursory characteristics of rock mass instability, resulting in slope stability analysis often being a passive "post-hoc analysis," making it difficult to achieve early warning of rock mass activation and instability. Fourth, there are technical obstacles to multi-scale information fusion. Existing models have failed to establish an effective mapping method between microscopic rock mass test data, on-site macroscopic monitoring data, and mechanical models. Microscopic rock mass damage mechanisms cannot effectively support macroscopic mechanical response analysis, and on-site monitoring data has not been fully used for model parameter correction and optimization. This makes it difficult to guarantee the predictive accuracy of the models and cannot adapt to the dynamic needs of long-term mining in ultra-large open-pit mines.
[0005] In summary, existing stability analysis technologies for slope rock masses in ultra-large open-pit mines, whether in basic analysis methods or practical engineering applications, fail to organically integrate geological occurrence conditions, mining disturbance effects, and rock mass damage evolution mechanisms. They struggle to accurately construct mechanical models that reflect the entire rock mass activation process, and thus cannot meet the engineering needs of ultra-large open-pit mines for quantitative identification and early warning of slope rock mass activation states. Therefore, developing a method for constructing a mechanical model for the activation of rock masses in ultra-large open-pit mine slopes that can integrate multi-source geological occurrence information, dynamically characterize the deterioration of rock mass damage intensity under mining disturbance, and establish critical criteria for rock mass activation has become an urgent technical challenge to be solved in this field. Summary of the Invention
[0006] To address the shortcomings of existing technologies, this invention provides a method for constructing a dynamic mechanical model of rock mass activation on ultra-large open-pit mine slopes based on geological occurrence, thus solving the problems mentioned in the background section.
[0007] To achieve the above objectives, the present invention provides the following technical solution: a method for constructing a dynamic mechanical model of rock mass activation on ultra-large open-pit mine slopes based on geological occurrence, comprising the following steps: Step S1: Construct a slope geological occurrence information database containing stratigraphic structure, rock mass mechanical properties, geological structure, hydrogeology, and mining history information; propose the Geological Occurrence Influence Factor (GFI) and quantify the impact of geological conditions on the macroscopic mechanical parameters of the rock mass. The GFI calculation formula is as follows:
[0008] in, The structural complexity coefficient, For structural development coefficient, The hydrological influence coefficient, The weathering degree coefficient, These are the weighting coefficients of each influencing factor; Step S2: Establish a dynamic mapping model of rock mass quality and mechanical parameters, determine the equivalent mechanical parameters of the rock mass, and the mapping model formula is:
[0009]
[0010] in, Equivalent parameters of the rock mass; Here, D represents the rock test parameters, and D represents the damage variable. Both V and V are attenuation coefficients; Step S3: Construct a disturbance-damage coupled constitutive model DDCM. First, define an anisotropic damage tensor D based on microcrack density and energy dissipation. Then, construct an equivalent disturbance intensity index ηd by integrating blasting vibration, excavation unloading, and groundwater seepage. Finally, establish a segmented damage evolution equation to describe the rock mass damage development process. Step S4: Define the Rock Mass Activation Index (RAI) as a precursor criterion for slope rock mass instability. The RAI calculation formula is as follows:
[0011] in For damage rate, For damage gradient, Potential slip velocity, The critical damage threshold, This is the current damage value. These are the maximum and minimum principal stresses, respectively. The tensile strength of the rock mass is used to classify the activation state level of the slope rock mass based on the RAI value; Step S5: The finite element discrete element coupled method (FEM) is used to realize multi-field coupled numerical solution. The model solution is completed by following the process of initial geostress balance, geological occurrence parameter assignment, mining step simulation, disturbance intensity calculation and damage update, RAI calculation, stability discrimination, and result output. Step S6: Establish a two-way feedback mechanism for the monitoring model, verify the model accuracy based on on-site monitoring data, and achieve dynamic model updates through parameter inversion and adaptive correction.
[0012] Preferably, in step S1, the stratigraphic structure information is characterized by establishing a three-dimensional geological body model to represent the rock strata's attitude, thickness, and contact relationship; the geological structure information is characterized by using a discrete fracture network (DFN) model to represent the spatial distribution, attitude, density, and filling characteristics of faults, joints, and fractures; the rock mass mechanical properties are statistically analyzed according to stratigraphic zones, including uniaxial compressive strength, elastic modulus, Poisson's ratio, internal friction angle, and cohesion; and the mining history information includes mining and stripping plans, slope morphology evolution, and blasting parameters.
[0013] Preferably, in step S1, the weighting coefficient The attenuation coefficient was determined using the analytic hierarchy process. , and Determined through in-situ field tests and inversion analysis.
[0014] Preferably, in step S3, the equivalent disturbance intensity index The calculation formula is:
[0015] in The blasting vibration velocity, The critical threshold for blasting vibration velocity. For excavation unloading rate, This is the critical threshold for excavation unloading rate. For seepage pressure, This is the critical threshold for seepage pressure. , denoted as the coupling coefficient of each disturbance factor.
[0016] Preferably, in step S3, the segmented damage evolution equation is:
[0017] in This is the stable creep stage of the rock mass. This is the stage of accelerated damage to the rock mass. For material constants, This is an equivalent change.
[0018] Preferably, the material constant The data was obtained through creep testing and acoustic emission monitoring data calibration.
[0019] Preferably, in step S4, the slope rock mass activation classification standard based on the RAI value is as follows: when RAI < 0.3, the slope rock mass is in a stable state; when 0.3 ≤ RAI < 0.7, the slope rock mass is in a state of damage accumulation, and a yellow warning is issued; when 0.7 ≤ RAI < 1.0, the slope rock mass is in a critical activation state, and an orange warning is issued; when RAI ≥ 1.0, the slope rock mass is in an unstable activation state, and a red warning is issued.
[0020] Preferably, in step S5, the application rules of the finite element / discrete element coupling method FEM / DEM are as follows: the finite element method is used for the continuous region outside the damage zone, and the disturbance-damage coupling constitutive model DDCM is embedded; the discrete element method is used for the discontinuous region of the fracture zone to simulate crack propagation and block motion; the transfer of displacement and force is realized at the coupling interface through interface elements to complete the multi-field coupling numerical simulation.
[0021] Preferably, in step S6, the verification indicators for model validation include surface displacement, deep displacement, acoustic emission event rate, and microseismic energy. The parameter inversion adopts the particle swarm optimization algorithm (PSO), with the field monitoring data as the objective function, to invert the parameters of the disturbance-damage coupled constitutive model (DDCM).
[0022] Preferably, in step S6, the trigger condition for dynamic model update is that the model prediction error exceeds a preset threshold. When the displacement error is >15%, the adaptive correction of the model parameters is triggered to complete the dynamic update of the model and ensure the model prediction accuracy and reliability.
[0023] This invention provides a method for constructing a dynamic mechanical model of rock mass activation on ultra-large open-pit mine slopes based on geological occurrence. It has the following beneficial effects: 1. This invention effectively solves the technical problems of disconnect between geological occurrence and mechanical response, and insufficient characterization of strength loss mechanism in existing open-pit mine slope rock mass mechanical models. By proposing the geological occurrence influence factor (GFI), a quantitative mapping relationship between geological conditions and macroscopic mechanical parameters of rock mass is established, breaking through the limitations of the homogenization assumption of traditional models. At the same time, a disturbance-damage coupled constitutive model (DDCM) is established, revealing the inherent coupling mechanism between mining disturbances such as blasting vibration, excavation unloading, and groundwater seepage and rock mass damage evolution and strength deterioration. This fills the gap in the disturbance-damage constitutive theory of rock mass in ultra-large open-pit mine slopes, realizes the accurate transformation of geological occurrence conditions into mechanical parameters, and makes the parameter assignment of the mechanical model more consistent with the geological characteristics of actual engineering.
[0024] 2. This invention solves the technical bottleneck of existing technologies, which lack criteria for slope rock mass activation and cannot achieve quantitative prediction of instability precursors. By defining the Rock Mass Activation Index (RAI) and establishing a four-level activation classification early warning standard, it constructs a quantitative judgment basis for the entire process of slope rock mass from stable state to damage accumulation state, then to activation critical state, and finally to instability activation state. This breaks through the limitations of traditional post-analysis of slope stability analysis and achieves accurate early warning of slope rock mass instability. Combined with the multi-field coupled numerical solution method of finite element and discrete element coupling, it further improves the accuracy of rock mass activation state prediction and early warning lead time, providing scientific quantitative criteria support for safety monitoring of ultra-large open-pit mine slopes.
[0025] 3. This invention effectively solves the problems of difficulty in multi-scale information fusion and easy decay of model prediction accuracy with mining progress in existing slope analysis methods. It adopts the FEM / DEM coupling method to realize multi-field coupled numerical simulation of stress field, seepage field and blasting vibration field, and integrates the micro-damage mechanism of rock mass, macro-mechanical response and stability evaluation at the engineering scale. At the same time, it establishes a particle swarm optimization parameter inversion and model dynamic update mechanism based on field monitoring data. When the prediction error exceeds the threshold, the parameters can be adaptively corrected, so that the model can be adapted to ultra-large open-pit mines with different geological conditions and mining technology, which significantly improves the accuracy of slope stability evaluation. It can not only effectively avoid the risk of slope instability, but also reduce unnecessary slope reinforcement projects, optimize mine mining design, and greatly save the engineering cost of slope treatment, while ensuring the reliability of long-term prediction of the model. Attached Figure Description
[0026] Figure 1 This is a flowchart of the present invention. Detailed Implementation
[0027] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0028] Please see the appendix Figure 1 This invention provides a method for constructing a dynamic mechanical model of rock mass activation on ultra-large open-pit mine slopes based on geological occurrence, comprising the following steps: Step S1: Construct a slope geological occurrence information database containing stratigraphic structure, rock mass mechanical properties, geological structure, hydrogeology, and mining history information; propose the Geological Occurrence Influence Factor (GFI) and quantify the impact of geological conditions on the macroscopic mechanical parameters of the rock mass. The GFI calculation formula is as follows:
[0029] in, The structural complexity coefficient, For structural development coefficient, The hydrological influence coefficient, The weathering degree coefficient, These are the weighting coefficients of each influencing factor; Specifically, this step integrates multi-dimensional geological information, including slope stratigraphic structure, rock mass mechanical properties, geological structure, hydrogeology, and mining history, to construct a comprehensive geological occurrence information database. Based on this, complex geological conditions are broken down into four quantifiable core influence dimensions: structural complexity, tectonic development, hydrological influence, and weathering degree. By assigning weights to the influence of each dimension, the comprehensive influence of geological conditions on the macroscopic mechanical parameters of the rock mass is quantitatively characterized. This provides a quantitative geological basis for the accurate determination of the equivalent mechanical parameters of the rock mass, allowing the mechanical model to better reflect the actual geological occurrence characteristics of ultra-large open-pit mine slopes and effectively avoid the evaluation bias caused by the homogenization assumption of traditional models.
[0030] Stratigraphic structure information is represented by establishing a three-dimensional geological body model to depict the attitude, thickness, and contact relationships of rock strata; geological structural information is represented by discrete fracture network (DFN) modeling to depict the spatial distribution, attitude, density, and filling characteristics of faults, joints, and fractures; rock mass mechanical properties are statistically analyzed by stratigraphic zone, including uniaxial compressive strength, elastic modulus, Poisson's ratio, internal friction angle, and cohesion; mining history information includes stripping plans, slope morphology evolution, and blasting parameters. Weighting coefficients are also included. The attenuation coefficient was determined using the analytic hierarchy process. and Determined through in-situ field tests and inversion analysis.
[0031] Specifically, through differentiated digital characterization of different types of geological endowment information and scientific calibration of mechanical parameters, the precise transformation of geological conditions into mechanical model input parameters is achieved: For stratigraphic structure information, a three-dimensional geological body model can intuitively restore the spatial attitude, thickness, and contact relationship of rock strata, accurately depicting the heterogeneous characteristics of slope geological structure; For geological structure information, discrete fracture network modeling can quantitatively characterize the spatial distribution, attitude, density, and filling characteristics of faults, joints, and fractures, clearly reflecting the weakening effect of tectonic development on rock mass integrity; For rock mass mechanical properties, core parameters such as uniaxial compressive strength and elastic modulus of rock are statistically analyzed according to stratigraphic zones, effectively avoiding the limitations of traditional homogenization assumptions, making the mechanical parameter assignments more consistent with the real mechanical performance of different strata; At the same time, mining history information such as stripping plans, slope morphology evolution, and blasting parameters are incorporated, which can dynamically reflect the continuous impact of mining disturbance on slope rock mass. Based on this, the weight coefficients of various geological influencing factors were determined by the analytic hierarchy process, realizing the scientific allocation of the degree of influence of different geological factors on the mechanical properties of rock mass. The attenuation coefficients were determined by in-situ tests and inversion analysis, and the degradation law of mechanical parameters was calibrated by combining actual engineering data. Finally, a reliable parameter basis and data support were provided for the subsequent construction of a rock mass activation mechanics model that can truly reflect the geological occurrence characteristics of ultra-large open-pit mine slopes.
[0032] Step S2: Establish a dynamic mapping model of rock mass quality and mechanical parameters, determine the equivalent mechanical parameters of the rock mass, and the mapping model formula is: in, Equivalent parameters of the rock mass; Here, D represents the rock test parameters, and D represents the damage variable. and All are attenuation coefficients; Specifically, firstly, the complete rock mechanical parameters obtained from laboratory tests are used as a benchmark. These parameters represent the intrinsic mechanical properties of the rock in a state without geological defects or damage, and are the basis for subsequent parameter corrections.
[0033] Secondly, two types of key degradation effects are introduced for dynamic correction: One type is the inherent weakening effect of geological occurrence, which is the comprehensive influence of geological occurrence quantified in the early stage. It reflects the damage to the integrity of the rock mass caused by natural geological factors such as stratigraphic structure, geological structure, hydrological conditions and weathering degree. Another type is the acquired deterioration effect of rock mass damage, that is, the damage state of the rock mass itself, which reflects the weakening of the mechanical properties of the rock mass caused by the development and propagation of microcracks triggered by mining disturbances, stress changes and other engineering activities.
[0034] By coupling these two types of degradation effects into the parameter correction logic, the baseline parameters of intact rock can be gradually attenuated to rock mass equivalent mechanical parameters that can truly reflect the on-site geological environment and degree of damage. This mapping relationship is not fixed, but dynamically updated with the differences in geological occurrence conditions and the evolution of rock mass damage, which can accurately capture the dynamic changes in rock mass mechanical properties during the mining of ultra-large open-pit mines.
[0035] Ultimately, this dynamic mapping model provides input parameters that fit the actual engineering situation for the subsequent construction of a disturbance-damage coupled constitutive model. It fundamentally makes up for the shortcomings of traditional mechanical parameter assignment that ignores geological heterogeneity and damage evolution, and improves the accuracy and reliability of slope rock mass mechanical behavior simulation.
[0036] Step S3: Construct a disturbance-damage coupled constitutive model (DDCM). First, define the anisotropic damage tensor D based on microcrack density and energy dissipation. Then, construct an equivalent disturbance intensity index by integrating blasting vibration, excavation unloading, and groundwater seepage. Finally, a segmented damage evolution equation was established to describe the rock mass damage development process; Equivalent disturbance intensity index The calculation formula is:
[0037] in The blasting vibration velocity, The critical threshold for blasting vibration velocity. For excavation unloading rate, This is the critical threshold for excavation unloading rate. For seepage pressure, This is the critical threshold for seepage pressure. denoted as the coupling coefficient of each disturbance factor.
[0038] The segmented damage evolution equation is:
[0039] in This is the stable creep stage of the rock mass. This is the stage of accelerated damage to the rock mass. For material constants, Equivalent strain. Material constants. The data was obtained through creep testing and acoustic emission monitoring data calibration.
[0040] The core of this step is to construct a disturbance-damage coupled constitutive model (DDCM), which comprehensively describes the mechanical deterioration law of rock mass under mining disturbance, from the microscopic damage mechanism to the macroscopic disturbance effect. It mainly consists of three core steps: Definition of anisotropic damage tensor: Starting from the microscopic nature of rock mass damage, the damage tensor is defined with microcrack density and energy dissipation as the core. It breaks through the limitations of the traditional isotropic damage assumption and can accurately reflect the differences in rock mass damage in different directions caused by geological structure, mining disturbance and other factors. It provides a microscopic physical basis for subsequent quantification of the deterioration of rock mass mechanical properties.
[0041] Construction of Equivalent Disturbance Intensity Index: For the three core disturbances in ultra-large open-pit mining—blasting vibration, excavation unloading, and groundwater seepage—a unified equivalent disturbance intensity index was established, achieving quantitative coupled characterization of multi-source and multi-type disturbances. By introducing critical thresholds for each disturbance factor, this index can intuitively determine whether the current disturbance intensity exceeds the rock mass's bearing capacity limit, providing a quantitative basis for distinguishing between stable and accelerated damage states of the rock mass.
[0042] A segmented damage evolution equation was established: Based on the strength of equivalent disturbance, the rock mass damage development process was divided into two stages: stable creep and accelerated damage. When the disturbance intensity was low, the rock mass was in the stable creep stage, and damage accumulated slowly. When the disturbance intensity exceeded the critical threshold, the rock mass entered the accelerated damage stage, and the damage rate increased sharply, indicating that the mechanical properties of the rock mass deteriorated rapidly and gradually developed towards instability. The material constants in the model were calibrated using indoor creep tests and acoustic emission monitoring data, ensuring that the constitutive model could truly reflect the damage evolution law of different rock masses under different disturbance conditions, providing constitutive theoretical support for the subsequent determination of the activation state of slope rock mass.
[0043] Step S4: Define the Rock Mass Activation Index (RAI) as a precursor criterion for slope rock mass instability. The RAI calculation formula is as follows:
[0044] in For damage rate, For damage gradient, Potential slip velocity, The critical damage threshold, This is the current damage value. These are the maximum and minimum principal stresses, respectively. The tensile strength of the rock mass is used to classify the activation state level of the slope rock mass based on the RAI value; The slope rock mass activation classification standard based on RAI value is as follows: when RAI < 0.3, the slope rock mass is in a stable state; when 0.3 ≤ RAI < 0.7, the slope rock mass is in a state of damage accumulation, and a yellow warning is issued; when 0.7 ≤ RAI < 1.0, the slope rock mass is in a critical activation state, and an orange warning is issued; when RAI ≥ 1.0, the slope rock mass is in an unstable activation state, and a red warning is issued.
[0045] Specifically, the principle behind this step can be broken down into the following core logic: Multi-dimensional precursor information fusion: RAI integrates three core types of precursor information for instability: rock mass damage evolution, slip trend, and stress state. It includes the development rate and spatial non-uniformity of damage within the rock mass, as well as the movement trend of potential slip surfaces. It also takes into account the gap between the current damage level and the critical instability damage, and the degree to which the stress environment approaches the tensile strength of the rock mass. It comprehensively depicts the nonlinear evolution characteristics of the rock mass from microscopic damage accumulation to macroscopic instability activation.
[0046] Continuous state-based hierarchical early warning: Based on RAI values, the slope rock mass is divided into four continuous activation state levels, from stable state, damage accumulation state (yellow warning), activation critical state (orange warning) to unstable activation state (red warning), achieving refined quantitative identification of the degree of rock mass activation. This hierarchical mechanism allows on-site engineers to intuitively grasp the slope safety situation and issue early warnings before the rock mass enters the activation critical stage or even the unstable activation stage.
[0047] Engineering adaptability of precursory indicators: RAI accurately captures the core precursory signals of slope instability—accelerated damage development, enhanced slippage trend, and stress approaching the bearing limit. Therefore, it can adapt to the slope safety management needs under the complex geology and mining disturbance of ultra-large open-pit mines, providing a scientific quantitative basis for dynamically evaluating the rock mass activation state and avoiding landslide instability risks. Step S5: The finite element discrete element coupled method (FEM) is used to realize multi-field coupled numerical solution. The model solution is completed by following the process of initial geostress balance, geological occurrence parameter assignment, mining step simulation, disturbance intensity calculation and damage update, RAI calculation, stability discrimination, and result output. The application rules of the finite element-discrete element coupling method (FEM / DEM) are as follows: the finite element method is used for the continuous region outside the damage zone, and a disturbance-damage coupled constitutive model (DDCM) is embedded; the discrete element method is used for the discontinuous region of the fracture zone to simulate crack propagation and block motion; and the transfer of displacement and force is realized at the coupling interface through interface elements to complete the multi-field coupled numerical simulation.
[0048] Specifically, the principle of this step can be divided into two parts: the solution process and the coupling method. The dynamic solution process is designed as follows: First, the original stress state of the slope before mining disturbance is restored through initial geostress equilibrium, laying the foundation for subsequent simulations. Then, the geological occurrence parameters and rock mass mechanical parameters quantified in the early stage are assigned to the numerical model to ensure that the model is highly matched with the on-site geological conditions. Next, the mining and stripping operations are simulated step by step according to the actual mining progress, and the current mining disturbance intensity is calculated, the rock mass damage state is updated, and the rock mass activation index (RAI) is calculated. Finally, the slope stability is judged and the results are output. This realizes the full-chain dynamic simulation from geological conditions to mechanical response and activation state, which can accurately track the state changes of the slope rock mass throughout the mining process.
[0049] The adaptability principle of the FEM / DEM coupling method: For continuous and intact rock mass areas outside the damage zone, the finite element method is used and a disturbance-damage coupled constitutive model is embedded to accurately simulate the stress-strain distribution and damage evolution law of the rock mass under multi-field disturbance. For discontinuous areas with cracks and joints, such as fracture zones, the discrete element method is used to intuitively simulate discontinuous deformation behaviors such as crack propagation, block slippage and rotation, which is more in line with the real mechanical performance of geological structure development areas. Through interface elements, the continuous transmission of displacement and force is realized at the interface between the two types of areas, ensuring the mechanical coordination of the entire slope model. Finally, the coupled numerical simulation of multiple physical fields such as stress field, seepage field, and disturbance field is realized, providing reliable numerical calculation support for the quantitative evaluation of the activation state of slope rock mass.
[0050] Step S6: Establish a two-way feedback mechanism for the monitoring model, verify the model accuracy based on on-site monitoring data, and achieve dynamic model updates through parameter inversion and adaptive correction.
[0051] The validation metrics for the model include surface displacement, deep displacement, acoustic emission event rate, and microseismic energy. Parameter inversion employs the Particle Swarm Optimization (PSO) algorithm, using field monitoring data as the objective function to invert the parameters of the Disturbance-Damage Coupled Constitutive Model (DDCM). The dynamic update of the model is triggered when the model prediction error exceeds a preset threshold. When the displacement error > 15%, adaptive correction of the model parameters is triggered, completing the dynamic update of the model and ensuring the accuracy and reliability of model predictions.
[0052] Specifically, the core of this step is to establish a two-way feedback closed-loop mechanism between monitoring and the model, breaking through the limitations of the static application of traditional mechanical models. This allows the model to dynamically iterate and optimize along with the mining process of ultra-large open-pit mines and the evolution of rock mass conditions, continuously ensuring the accuracy and reliability of the model's prediction of the activation state of slope rock mass. This fundamentally solves the technical problems of difficulty in multi-scale information fusion and the decline in model prediction accuracy as the project progresses. It is divided into three core links: Multi-dimensional and comprehensive model accuracy verification was conducted, selecting surface displacement, deep displacement, acoustic emission event rate, and microseismic energy as core verification indicators. Among them, surface and deep displacement directly reflect the macroscopic deformation of the slope rock mass, while acoustic emission event rate and microseismic energy are microscopic representations of the initiation and propagation of microcracks within the rock mass. These two types of indicators comprehensively reflect the true activation and evolution state of the slope rock mass from the two dimensions of macroscopic deformation and microscopic damage. Based on this, the consistency between the model calculation results and the actual situation on the engineering site was verified, providing real and reliable field data support for subsequent model optimization and correction.
[0053] Accurate parameter inversion based on particle swarm optimization algorithm: Using actual field monitoring data as the objective function, the parameters of the disturbance-damage coupled constitutive model are inverted and calibrated using particle swarm optimization algorithm. Through algorithm iteration, the calculation results of the model are made to fit the field monitoring values as closely as possible. This effectively compensates for the model deviation caused by parameter assumptions and differences between laboratory tests and engineering field environments during theoretical modeling. The mechanical characterization of the model is made to better fit the real response law of the rock mass in the field, thereby improving the engineering adaptability of the model from the parameter level.
[0054] The threshold-triggered adaptive dynamic update of the model sets a displacement error >15% as the quantitative trigger condition for dynamic model updates. This threshold is a key standard for judging whether the model's prediction accuracy meets the requirements of engineering safety management. When the error between the model's predicted value and the field monitoring value exceeds this threshold, the adaptive correction of the model parameters is automatically triggered, realizing dynamic iterative optimization of the model. This design can effectively adapt to the engineering characteristics of long-term mining in ultra-large open-pit mines, such as continuous evolution of rock mass damage, constant changes in mining disturbance, and dynamic adjustment of slope geological conditions. It avoids the problem of static models failing to predict due to changes in engineering conditions, ensuring that the model always maintains the ability to accurately identify the activation state of the slope rock mass.
Claims
1. A method for constructing a dynamic mechanical model of rock mass activation on ultra-large open-pit mine slopes based on geological occurrence, characterized in that, Includes the following steps: Step S1: Construct a slope geological occurrence information database containing stratigraphic structure, rock mass mechanical properties, geological structure, hydrogeology, and mining history information; propose the Geological Occurrence Influence Factor (GFI) and quantify the impact of geological conditions on the macroscopic mechanical parameters of the rock mass. The GFI calculation formula is as follows: in, The structural complexity coefficient, For structural development coefficient, The hydrological influence coefficient, The weathering degree coefficient, These are the weighting coefficients of each influencing factor; Step S2: Establish a dynamic mapping model of rock mass quality and mechanical parameters, determine the equivalent mechanical parameters of the rock mass, and the mapping model formula is: ； in, Equivalent parameters of the rock mass; Here, D represents the rock test parameters, and D represents the damage variable. Both v and are attenuation coefficients; Step S3: Construct a disturbance-damage coupled constitutive model DDCM. First, define an anisotropic damage tensor D based on microcrack density and energy dissipation. Then, construct an equivalent disturbance intensity index ηd by integrating blasting vibration, excavation unloading, and groundwater seepage. Finally, establish a segmented damage evolution equation to describe the rock mass damage development process. Step S4: Define the Rock Mass Activation Index (RAI) as a precursor criterion for slope rock mass instability. The RAI calculation formula is as follows: ； in For damage rate, For damage gradient, Potential slip velocity, The critical damage threshold, This is the current damage value. These are the maximum and minimum principal stresses, respectively. The tensile strength of the rock mass is used to classify the activation state level of the slope rock mass based on the RAI value; Step S5: The finite element discrete element coupled method (FEM) is used to realize multi-field coupled numerical solution. The model solution is completed by following the process of initial geostress balance, geological occurrence parameter assignment, mining step simulation, disturbance intensity calculation and damage update, RAI calculation, stability discrimination, and result output. Step S6: Establish a two-way feedback mechanism for the monitoring model, verify the model accuracy based on on-site monitoring data, and achieve dynamic model updates through parameter inversion and adaptive correction.
2. The method for constructing a dynamic mechanical model of ultra-large open-pit mine slope rock mass based on geological occurrence as described in claim 1, characterized in that, In step S1, the stratigraphic structure information is characterized by establishing a three-dimensional geological body model to represent the rock strata's attitude, thickness, and contact relationships; the geological structure information is characterized by using a discrete fracture network (DFN) model to represent the spatial distribution, attitude, density, and filling characteristics of faults, joints, and fractures; the rock mass mechanical properties are statistically analyzed according to stratigraphic zones, including uniaxial compressive strength, elastic modulus, Poisson's ratio, internal friction angle, and cohesion; and the mining history information includes mining and stripping plans, slope morphology evolution, and blasting parameters.
3. The method for constructing a dynamic mechanical model of ultra-large open-pit mine slope rock mass based on geological occurrence as described in claim 1, characterized in that, In step S1, the weighting coefficient The attenuation coefficient was determined using the analytic hierarchy process (AHP). and v were determined through in-situ field tests and inversion analysis.
4. The method for constructing a dynamic mechanical model of ultra-large open-pit mine slope rock mass based on geological occurrence as described in claim 1, characterized in that, In step S3, the equivalent disturbance intensity index The calculation formula is: ； in The blasting vibration velocity, The critical threshold for blasting vibration velocity. For excavation unloading rate, This is the critical threshold for excavation unloading rate. For seepage pressure, This is the critical threshold for seepage pressure. , , denoted as the coupling coefficient of each disturbance factor.
5. The method for constructing a dynamic mechanical model of ultra-large open-pit mine slope rock mass based on geological occurrence as described in claim 4, characterized in that, In step S3, the segmented damage evolution equation is: ； in This is the stable creep stage of the rock mass. This is the stage of accelerated damage to the rock mass. For material constants, This is an equivalent change.
6. The method for constructing a dynamic mechanical model of ultra-large open-pit mine slope rock mass based on geological occurrence as described in claim 5, characterized in that, The material constant The data was obtained through creep testing and acoustic emission monitoring data calibration.
7. The method for constructing a dynamic mechanical model of ultra-large open-pit mine slope rock mass based on geological occurrence as described in claim 1, characterized in that, In step S4, the slope rock mass activation classification standard based on RAI value is: when RAI < 0.3, the slope rock mass is in a stable state; When RAI < 0.7, the slope rock mass is in a state of damage accumulation, and a yellow warning is issued; when RAI < 1.0, the slope rock mass is in a critical state of activation, and an orange warning is issued; when RAI ≥ 1.0, the slope rock mass is in a state of instability and activation, and a red warning is issued.
8. The method for constructing a dynamic mechanical model of ultra-large open-pit mine slope rock mass based on geological occurrence as described in claim 1, characterized in that, In step S5, the application rules of the finite element / discrete element coupling method FEM / DEM are as follows: the finite element method is used for the continuous region outside the damage zone, and the disturbance-damage coupling constitutive model DDCM is embedded; the discrete element method is used for the discontinuous region of the fracture zone to simulate crack propagation and block motion; the transfer of displacement and force is realized at the coupling interface through interface elements to complete the multi-field coupling numerical simulation.
9. The method for constructing a dynamic mechanical model of ultra-large open-pit mine slope rock mass based on geological occurrence as described in claim 1, characterized in that, In step S6, the validation metrics for model verification include surface displacement, deep displacement, acoustic emission event rate, and microseismic energy. The parameter inversion uses the particle swarm optimization algorithm (PSO) with field monitoring data as the objective function to invert the parameters of the disturbance-damage coupled constitutive model (DDCM).
10. The method for constructing a dynamic mechanical model of ultra-large open-pit mine slope rock mass based on geological occurrence as described in claim 9, characterized in that, In step S6, the trigger condition for dynamic model update is that the model prediction error exceeds a preset threshold. When the displacement error is >15%, the adaptive correction of the model parameters is triggered to complete the dynamic update of the model and ensure the accuracy and reliability of model prediction.