True triaxial hard rock dynamic disturbance frequency influence long-term strength prediction method and system
By acquiring true triaxial test data, constructing characteristic curves, and performing equivalent static mapping, the problem of quantitative characterization and long-term strength prediction of dynamic disturbance effects under true triaxial stress state was solved, achieving accurate prediction of high-frequency dynamic disturbances and supporting engineering design and stability evaluation.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NORTHEASTERN UNIV CHINA
- Filing Date
- 2026-05-12
- Publication Date
- 2026-06-09
Smart Images
Figure CN122172345A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of computer technology, and more specifically, to a method and system for predicting the long-term strength of hard rock under the influence of dynamic disturbance frequency in true triaxial rock. Background Technology
[0002] With the development of rock mechanics and deep engineering safety evaluation, the long-term stability analysis of hard rock surroundings in deep tunnels, underground caverns, and other engineering projects has received increasing attention. These projects are situated in environments characterized by high ground stress and strong dynamic disturbances. The surrounding rock is subjected to long-term, multi-source dynamic disturbances such as those caused by TBM excavation, blasting, and equipment operation. Its strength degradation and failure mechanisms are significantly influenced by the coupling effects of multi-dimensional factors such as disturbance frequency, amplitude, and direction. Currently, in addressing the core issue of long-term strength prediction of surrounding rock, this field generally relies on true triaxial tests based on static conditions or short-duration dynamic disturbance tests. These existing methods have significant shortcomings: at the level of experimental mechanism, it is difficult to simultaneously consider the dynamic disturbance effects of different principal stress directions under true triaxial stress conditions, especially lacking a practical method that can equivalently transform complex dynamic disturbances of high frequency and long duration in engineering practice into long-term strength indicators that can be used for engineering design and stability evaluation; at the level of experimental equipment and engineering feasibility, due to the limitation of ultra-high energy consumption, it is impossible to truly reproduce continuous dynamic disturbance loading on an engineering timescale in the laboratory, resulting in a serious disconnect between experimental conditions and actual field conditions. Therefore, the strength parameters obtained by existing technical approaches are not only unable to reflect the long-term cumulative aging effects of dynamic disturbances, but also lack a unified and quantifiable long-term strength criterion system, ultimately making it difficult to directly apply and promote their prediction results in engineering practice.
[0003] Based on the shortcomings of the existing technologies, there is an urgent need for a method and system for predicting the long-term strength of hard rock under the influence of dynamic disturbance frequency in true triaxial hard rock. Summary of the Invention
[0004] The purpose of this invention is to provide a method and system for predicting the long-term strength of hard rock under the influence of dynamic disturbance frequency in true triaxial rock, so as to improve the above-mentioned problems. To achieve the above objective, the technical solution adopted by this invention is as follows: Firstly, this application provides a method for predicting the long-term strength of hard rock under the influence of dynamic disturbance frequency, including: To obtain dynamic disturbance parameters, rock compression process data, and fracture morphology data in long-term dynamic disturbance true triaxial tests; Characteristic curves are constructed based on the dynamic disturbance parameters and the rock compression process data. The rate of change information of the data is extracted through differential operation to construct the characteristic curves. The characteristic curves include stress-strain curves, strain-time curves and strain rate evolution curves at different disturbance frequencies. Based on the dynamic disturbance parameters and the characteristic curve, an equivalent static mapping is performed. By converting the periodic dynamic disturbance load into an equivalent static load, the equivalent static stress state under the limiting frequency condition is obtained. By fitting the equivalent static stress state, and by conducting a load-bearing test under the equivalent static conditions and analyzing the entire process from creep to failure, the long-term strength prediction value under the equivalent static conditions is obtained. A model is constructed based on the characteristic curves and the fracture morphology data. A multidimensional criterion score is obtained by quantitatively evaluating the consistency between the deformation response mechanism, fracture mechanism, time-effect damage mechanism and equivalent static state. The long-term intensity prediction value is determined and corrected based on the multidimensional criterion score to obtain the output result.
[0005] Secondly, this application also provides a true triaxial hard rock dynamic disturbance frequency influence long-term strength prediction system, including: The acquisition module is used to acquire dynamic disturbance parameters, rock compression process data, and fracture morphology data in long-term dynamic disturbance true triaxial tests. The construction module is used to construct characteristic curves based on the dynamic disturbance parameters and the rock compression process data. It extracts the rate of change information of the data through differential operations to construct characteristic curves, which include stress-strain curves, strain-time curves and strain rate evolution curves at different disturbance frequencies. The mapping module is used to perform equivalent static mapping based on the dynamic disturbance parameters and the characteristic curve, and to obtain the equivalent static stress state under the limiting frequency condition by converting the periodic dynamic disturbance load into an equivalent static load. The fitting module is used to fit the equivalent static stress state. By implementing a load-bearing test under the equivalent static condition and analyzing the entire process from creep to failure, the long-term strength prediction value under the equivalent static condition is obtained. The quantization module is used to construct a model based on the characteristic curve and the fracture morphology data, and to obtain a multi-dimensional criterion score by quantifying and evaluating the consistency between the deformation response mechanism, fracture mechanism, time-effect damage mechanism and equivalent static state. The output module is used to determine and correct the long-term intensity prediction value based on the multidimensional criterion score, and obtain the output result.
[0006] The beneficial effects of this invention are as follows: This invention acquires true triaxial test data of long-term dynamic disturbance, constructs characteristic curves and multidimensional criterion models that can reflect the deformation, fracture and time-related damage mechanisms of rocks, and equates high-frequency dynamic disturbances to static states for long-term strength prediction. This invention achieves quantitative characterization of the influence of high-frequency and long-term dynamic disturbances and accurate prediction of long-term strength under true triaxial conditions. Attached Figure Description
[0007] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.
[0008] Figure 1 This is a flowchart illustrating a method for predicting the long-term strength of true triaxial hard rock dynamic disturbance frequency as described in an embodiment of the present invention. Figure 2 This is a schematic diagram of the structure of a true triaxial hard rock dynamic disturbance frequency influence long-term strength prediction system as described in an embodiment of the present invention; Figure 3 The stress-strain curve for dynamic disturbance in the direction of the intermediate principal stress; Figure 4 The stress-strain curve for dynamic disturbance in the direction of minimum principal stress; Figure 5 This is a schematic diagram for judging the similarity of stress-strain curves. Figure 6 This is a schematic diagram for determining the similarity of fracture modes; Figure 7 A schematic diagram for judging the similarity of dynamic creep acceleration in the direction of the intermediate principal stress; Figure 8 This is a schematic diagram for judging the similarity of dynamic creep acceleration in the direction of minimum principal stress.
[0009] The diagram is labeled as follows: 901, Acquisition module; 902, Construction module; 903, Mapping module; 904, Fitting module; 905, Quantization module; 906, Output module. Detailed Implementation
[0010] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of 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, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.
[0011] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this invention, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.
[0012] In underground engineering projects such as deep tunnels and mine roadways, the surrounding rock is subjected to a high geostress environment for extended periods and continuously endures complex dynamic disturbances generated during construction and operation. These disturbances include periodic loads from the rotating rock-breaking action of a full-face hard rock tunnel boring machine (TBM), blasting shock waves from adjacent areas, and vibrations caused by the operation of large machinery. These disturbances are not singular or instantaneous, but rather composite loads with specific frequencies, amplitudes, directions, and extremely long durations. They superimpose with the high geostatic stress field, repeatedly acting on brittle hard rock from different directions, triggering a time-dependent process of progressive damage accumulation and strength degradation. Existing strength testing methods, whether purely static tests or short-term dynamic tests, struggle to realistically reproduce this harsh environment of "true triaxial stress state" coupled with "multi-source, long-term, directional dynamic disturbances" in the laboratory. Consequently, they cannot accurately obtain the long-term strength of the rock under this environment, leading to significant uncertainties in the long-term stability evaluation and prediction of engineering projects based on existing test results. Therefore, a method is needed that can effectively bridge complex field disturbance conditions with feasible indoor tests and provide clear long-term strength indicators.
[0013] Example 1: This embodiment provides a method for predicting the long-term strength of hard rock under the influence of dynamic disturbance frequency in true triaxial hard rock.
[0014] See Figure 1 The figure shows that the method includes steps S100 to S600.
[0015] Step S100: Obtain dynamic disturbance parameters, rock compression process data, and fracture morphology data from the long-term dynamic disturbance true triaxial test; Understandably, in deep underground engineering, the surrounding rock is subjected to long-term dynamic disturbances with specific frequencies, amplitudes, and directions, such as those caused by TBM tunneling and blasting. Step S100 aims to systematically acquire all the fundamental data necessary to evaluate the mechanical behavior of hard rock under long-term dynamic disturbances under true triaxial stress conditions. This step comprises two logically continuous but physically phased experimental data acquisition processes. The first is to acquire undisturbed baseline data: non-destructive brittle hard rock samples are obtained under in-situ conditions in deep engineering. Confining pressure conditions consistent with the in-situ stress are applied in a true triaxial test system, and undisturbed loading to failure tests are conducted to obtain basic static parameters, including peak strength, elastic modulus, damage stress, and crack initiation stress. These parameters constitute the baseline for comparing the starting point of stress application and mechanical behavior in subsequent dynamic disturbance tests. Secondly, it is necessary to acquire data on the entire dynamic disturbance process: Based on the aforementioned static parameters, a reasonable disturbance initiation point is selected, and a long-term dynamic disturbance loading test is conducted under true triaxial conditions. During this process, it is necessary to precisely control and record parameters such as the frequency, amplitude, direction (direction of intermediate principal stress or minimum principal stress), and duration of the dynamic disturbance, and to use sensors to synchronously collect the stress, strain, and corresponding time series data of the rock throughout the entire disturbance loading process. After the test, it is also necessary to record the finally failed specimen and obtain its macroscopic fracture surface morphology data, such as the shape, angle, and roughness. Therefore, the acquired data is a complete dataset consisting of reference static parameters, preset dynamic disturbance loading parameters, dynamic response process data, and final failure morphology data.
[0016] Step S200: Construct characteristic curves based on dynamic disturbance parameters and rock compression process data. Extract the rate of change information of the data through differential operation to construct characteristic curves. The characteristic curves include stress-strain curves, strain-time curves and strain rate evolution curves at different disturbance frequencies. It should be noted that this step, based on the original, time-varying response data, reveals its inherent variation patterns through mathematical processing such as differentiation, thereby constructing characteristic curves that can intuitively reflect the deformation behavior, time effect, and damage development rate of rocks under dynamic disturbances at different frequencies. These curves transform discrete time-series data into graphical features with clear mechanical meaning, forming the basis for analyzing the time-dependent mechanical behavior of rocks under dynamic disturbances.
[0017] Step S300: Perform equivalent static mapping based on dynamic disturbance parameters and characteristic curves. By converting periodic dynamic disturbance loads into equivalent static loads, the equivalent static stress state under the limiting frequency condition is obtained. Understandably, this step is based on the physical principle that "when the disturbance frequency is extremely high, its mechanical effect can be approximated as a constant average action". It maps the complex dynamic disturbance containing information on frequency, amplitude and direction into a definite equivalent static stress state that reduces the load-bearing capacity in the corresponding direction, thereby providing a clear loading target corresponding to the specific high-frequency disturbance limit condition for subsequent static tests.
[0018] Step S400: Fit the equivalent static stress state, and obtain the long-term strength prediction value under the equivalent static condition by carrying out a load-bearing test under the equivalent static condition and analyzing the whole process from creep to failure. It should be noted that the purpose of this step is to obtain the long-term strength benchmark value under the aforementioned equivalent static state through a directly executable physical test. The idea is to apply a long-term constant load to the rock sample under the mapped equivalent static state, observe and record its entire process from initial deformation, steady-state creep to accelerated failure, and finally identify and determine the strength threshold leading to long-term failure from the creep evolution law. This value is the predicted long-term strength value under this equivalent condition.
[0019] Step S500: Construct a model based on the characteristic curves and fracture morphology data. Quantitatively evaluate the consistency between the deformation response mechanism, fracture mechanism, and time-effect damage mechanism and the equivalent static state to obtain a multidimensional criterion score. Understandably, this step aims to establish an objective verification and prediction mechanism. The specific idea is that the reliability of long-term strength depends not only on a single strength value, but also on the consistency of the failure mechanisms that generate that strength. Therefore, this step starts with three core mechanical mechanisms: deformation response, final fracture morphology, and aging damage evolution. Quantitative features are extracted from characteristic curves and fracture morphologies, respectively, and compared with equivalent static test results to obtain a multi-dimensional scoring system that reflects the consistency of the mechanisms, providing a criterion for the credibility of the final predicted value.
[0020] Step S600: Determine and correct the long-term intensity prediction value based on the multidimensional criterion score to obtain the output result.
[0021] It should be noted that this step is the decision-making and output stage of the entire method. Based on the multidimensional score obtained in step S500, the validity of the long-term intensity prediction value is determined. If the mechanism is highly consistent, it is directly adopted; if there is a deviation, it is corrected; if the mechanism is significantly different, the equivalent method is deemed inapplicable, thereby ensuring the engineering applicability of the final output result supported by a clear physical mechanism.
[0022] Further, step S200 includes steps S210 to S230.
[0023] Step S210: Based on the dynamic disturbance parameters and rock compression process data, feature extraction is performed. By aligning the timestamps and removing outliers from the synchronously recorded stress, strain and time data, a stress-strain-time series dataset is obtained. Step S220: Calculate the strain rate based on the stress-strain-time series dataset. The strain rate data series is obtained by the core processing of the ratio of strain increment to time in the long-term disturbance period for each principal stress direction. Step S230: Construct and correlate curves based on the stress-strain-time series dataset and strain rate data series. By synchronously correlating and plotting the stress-strain series, strain-time series and strain rate-time series according to the same time base, characteristic curves are obtained.
[0024] Specifically, steps S210, S220, and S230 constitute a coherent processing flow from raw data to feature information. First, in step S210, feature extraction involves timestamping the synchronously but potentially asynchronously acquired stress, strain, and time raw signals and removing outliers caused by sensor transient failures or environmental electromagnetic interference. This preprocessing ensures the temporal consistency and reliability of the data, laying a clean data foundation for subsequent quantitative analysis. Next, in step S220, strain rate calculation is performed using the processed, regularized time-series dataset. The specific technique involves calculating, for each independent principal stress direction under true triaxial conditions, the ratio of the strain increment in that direction to the duration of that cycle within each complete dynamic disturbance cycle. This transforms macroscopic deformation data into a strain rate data sequence revealing the rate of rock damage evolution, converting cumulative deformation over time into a more sensitive state indicator—rate. Finally, in step S230, the technical means for curve construction and correlation is to synchronously plot and correlate the stress-strain-time series obtained in step S210 and the strain rate data series obtained in step S220 based on a unified time reference, thereby generating a set of mutually comparable stress-strain curves, strain-time curves, and strain rate evolution curves under different perturbation frequencies. The strain rate is calculated as the ratio of strain to time within the perturbation period, expressed as: ; ; ; In the formula, , and These represent the strain rates along the directions of maximum principal stress, intermediate principal stress, and minimum principal stress, respectively. , and These represent the strains in the directions of maximum principal stress, intermediate principal stress, and minimum principal stress, respectively. The differential symbol; For time intervals.
[0025] Further, step S300 includes steps S310 to S330.
[0026] Step S310: Analyze the disturbance conditions based on the dynamic disturbance parameters. By extracting the specific direction and amplitude information of the applied dynamic disturbance, obtain the identifier of the direction of the disturbed principal stress and its corresponding disturbance amplitude. Step S320: Based on the indication of the direction of the disturbed principal stress and the disturbance amplitude, and combined with the condition that the frequency in the dynamic disturbance parameters tends to infinity, perform equivalent static calculation to obtain the equivalent static stress value in the direction of the disturbed principal stress. Step S330: Based on the equivalent static stress value, the original static stress value in the undisturbed direction is integrated. By combining the stress values of the maximum principal stress, intermediate principal stress, and minimum principal stress, the equivalent static stress state characterizing the high-frequency disturbance limit condition is obtained.
[0027] Specifically, firstly, step S310 determines the principal stress direction and corresponding disturbance amplitude of the applied dynamic disturbance in the true triaxial dynamic disturbance test, wherein: The intermediate principal stress is denoted as: ; The minimum principal stress is denoted as: ; The disturbance amplitudes are denoted as follows: and ; In the formula, This is the symbol for the intermediate principal stress; This is the intermediate principal stress; The symbol for the minimum principal stress; It is the minimum principal stress; The amplitude of the dynamic disturbance applied in the direction of the intermediate principal stress; This represents the amplitude of the dynamic disturbance applied in the direction of the minimum principal stress. The dynamic disturbance can be applied in the direction of the intermediate principal stress, the direction of the minimum principal stress, or both simultaneously. The purpose of this step is to clarify "where the disturbance is applied" and "how large the disturbance is," providing a clear input for subsequent mechanical equivalence. Next, step S320 applies the equivalent static mapping principle of high-frequency dynamic disturbances. This principle states that when the frequency of the dynamic disturbance approaches infinity, the rock does not have enough time to complete a full dynamic response within a single cycle. Therefore, periodic dynamic disturbances can be considered as a constant static average action, the mechanical effect of which is that the effective stress actually felt by the rock in the disturbed direction, which can be used for bearing load, is reduced, and the amount of reduction is exactly equal to the disturbance amplitude. The equivalent static mapping relationship is expressed as: ; In the formula, For the sample at the The original static stress value borne in each principal stress direction; For the sample at the The amplitude of dynamic disturbance in each principal stress direction; For the sample at the The equivalent static stress value borne in each principal stress direction; The prerequisite for the mapping relationship to hold is that the frequency of the dynamic disturbance approaches infinity.
[0028] Finally, step S330 combines the equivalent static stress value (corresponding to the disturbed direction) with the original static stress values in the other undisturbed principal stress directions to construct a complete true triaxial static stress state with stress values in three directions. This final stress state provides a precise loading target for subsequent equivalent static load-holding tests.
[0029] Further, step S400 includes steps S410 to S430.
[0030] Step S410: Design a load-holding test scheme based on the equivalent static stress state. By applying the stress state as a constant load to the new hard rock specimen and setting a preset duration, a long-term load-holding test loading scheme is obtained. Step S420: Implement the test and monitor the data according to the long-term load test loading scheme. By continuously monitoring and recording the strain and time data of the rock during the test, strain-time series data describing the whole process of creep evolution of the rock under equivalent static load are obtained. Step S430: Determine the long-term strength based on strain-time series data. By analyzing the characteristics of strain rate change over time, identify the critical point from steady-state creep to accelerated creep and ultimately failure, and obtain the predicted long-term strength value under equivalent static conditions.
[0031] Specifically, firstly, step S410 sets the equivalent static stress state as the true triaxial load required to be applied to the new hard rock specimen and maintained constant throughout the test. Simultaneously, a duration for inducing complete creep failure in the rock is set to simulate long-term engineering effects, thus forming a load-holding test loading scheme. Next, step S420 is the physical implementation and data acquisition step. Strictly following the above loading scheme, a constant stress is applied to the specimen on a true triaxial testing machine, and a high-precision strain sensor monitors and records the strain in all directions of the rock and its corresponding time throughout the process, thereby obtaining a complete set of strain-time series data describing the rock under equivalent static stress from initial deformation, through steady-state creep, to final accelerated failure. Finally, step S430 performs differential processing on the strain-time series data to obtain the characteristics of the strain rate evolution over time. By identifying the critical point at which the strain rate first transitions from a relatively gentle steady-state creep stage to a sustained accelerated creep stage, and based on rock creep mechanics theory, the constant stress value corresponding to this critical point is determined as the long-term load-holding strength under the corresponding working condition. The long-term strength under load is defined as the predicted long-term strength under the condition that the frequency of the dynamic disturbance approaches infinity, and is expressed as: ; In the formula, This is a long-term intensity prediction value; This is the equivalent static long-term strength; The prerequisite for the mapping relationship to hold is that the frequency of the dynamic disturbance approaches infinity; This is the symbol for the intermediate principal stress; The symbol for the minimum principal stress; It is the minimum principal stress; The amplitude of the dynamic disturbance applied in the direction of the intermediate principal stress; The amplitude of the dynamic disturbance applied in the direction of minimum principal stress.
[0032] Further, step S500 includes steps S510 to S530.
[0033] Step S510: Based on the characteristic curve and fracture morphology data, feature extraction is performed. The full curve morphology deviation is calculated from the stress-strain curve and strain-time curve respectively. The fracture angle and JRC roughness index are extracted from the fracture morphology. The average rate of the accelerated creep stage is identified and calculated from the strain rate evolution curve to obtain a set of quantitative parameters. Step S520: Perform consistency scoring of sub-mechanisms based on the set of quantitative parameters. By comparing the parameters in the set of quantitative parameters with the corresponding results of the equivalent static test, and calculating based on the preset similarity threshold, the consistency scoring results of deformation response, fracture mechanism and time-effect damage mechanism are obtained. Step S530: Construct a model based on the consistency score, and obtain a multi-mechanism fusion prediction model that includes weighted comprehensive score output and judgment rules through weight allocation and linear weighted fusion.
[0034] Specifically, firstly, step S510, based on the physical definitions of the three criteria, precisely calculates a set of comparable quantization parameters from different types of raw data, including: Step S511: From the stress-strain curve, by calculating the normalized mean square deviation of the entire curve, extract the curve shape deviation parameter that reflects the overall deformation response mechanism, which is used to judge the consistency of deformation response under equivalent static loading and high-frequency dynamic disturbance conditions.
[0035] It is understandable that when the perturbation frequency... In such cases, the rock mass cannot complete a full inertial response process within a single cycle, which macroscopically manifests as a "quasi-static deformation path under equivalent average stress state." Therefore, the constitutive response under high-frequency dynamic disturbance can be approximated by an equivalent static stress path, and its rationality is verified by the consistency of the stress-strain curve morphology. For brittle hard rock, the key morphological features of the stress-strain curve (elastic segment slope, yield / damage inflection point, peak point, and post-peak softening segment) essentially correspond to the elastic response-damage evolution-instability and fracture mechanism chain. Therefore, if the curve morphology of the two conditions is highly consistent in these features, they can be considered to have a consistent mechanical mechanism basis, thus supporting long-term strength mapping.
[0036] Preferably, the stress-stress curve is first normalized: ; In the formula, This is the normalized stress function; The stress function; Peak strain; For normalized strain; This represents the peak stress. In response to the situation.
[0037] Next, calculate the mean square deviation of the entire curve: ; In the formula, The normalized mean square deviation of the entire curve; This represents the maximum value of the normalized strain range; For normalized strain; This is the normalized stress-strain function for the dynamic disturbance test; This is the normalized stress-strain function for the equivalent static test; This is the differential symbol.
[0038] Step S512: Based on the fracture morphology data, by measuring the dynamic high-frequency ultimate fracture angle and the equivalent static fracture angle, and by measuring or calculating the surface roughness and the equivalent static surface roughness when the frequency approaches infinity, the fracture angle and JRC roughness index parameters are extracted. Step S512: Based on the strain-time curve and strain rate evolution curve, determine the acceleration start time by ensuring the second derivative is greater than zero for a certain time window, then calculate the average rate during the acceleration phase, and extract the average rate parameter for the accelerated creep phase. The calculation formula is as follows: ; In the formula, For the first The average strain rate during the accelerated creep stage under each stress step; For the first The total time lasting for the accelerated creep stage of each stress step; For the first Accelerated creep initiation time of each stress step; For the first The time it takes for the specimen to fail under each stress step; For the first Under each stress step, over time The changing instantaneous creep rate; The differential symbol; For time intervals.
[0039] Understandably, under high-frequency limiting conditions, the microcracks within the rock cannot periodically open and close in response to the load. The creep behavior is then dominated by the gradual accumulation of macroscopic damage, with the accelerated failure stage representing the critical state of damage evolution rather than a direct result of a single periodic dynamic effect. Therefore, the key to evaluating long-term stability lies in comparing the "accelerated creep rate" exhibited under different principal stress disturbance levels. Specifically, the starting point of the accelerated creep stage must first be determined. This point is not determined by a single instantaneous fluctuation but should be based on a comprehensive assessment of the rate of change of strain rate (i.e., acceleration) becoming consistently positive and remaining stable for a continuous period. This is because a typical rock creep process comprises three stages: an initial stage with decreasing rate, a stable stage with an approximately constant rate, and an accelerated stage with a continuously increasing rate. In the accelerated stage, due to the continuous increase in creep rate, its rate of change (acceleration) is positive. If the acceleration is momentarily positive due to data noise, measurement error, or numerical calculation fluctuations, it cannot be determined that the acceleration phase has been entered. The acceleration must be positive for a sufficiently long period of time (e.g., more than 5% of the total duration of the creep phase, or more than 30 consecutive seconds) to confirm that the rock has entered an accelerated creep state controlled by damage instability.
[0040] The above process yields a set of quantization parameters that includes all of the above items.
[0041] The consistency scoring process of the sub-item mechanism in step S520 involves comparing the quantitative parameter set with the corresponding results of the equivalent static test. For the deformation response mechanism, the curve shape deviation parameter is substituted into the formula to calculate the similarity. The similarity calculation formula is as follows: ; In the formula, Score the similarity of the curve shapes. The closer they are to 1, the more similar they are. The sensitivity coefficient can be set to 1 or determined experimentally. This is the normalized mean square deviation of the entire curve.
[0042] The following conditions must be met to determine if the shapes are similar: ; In the formula, Score the similarity of the curve shapes; The similarity threshold is recommended to be 0.9, which can be calibrated experimentally.
[0043] For the fracture mechanism, it is required that the fracture type be consistent and the fracture angle deviation satisfy the following: ; In the formula, This refers to the maximum breaking angle at high frequencies. This is the equivalent static fracture angle; The allowable deviation is 5~10°.
[0044] And the relative deviation of JRC (joint roughness coefficient) satisfies: ; In the formula, To meet the limits of high-frequency dynamic disturbance After a true triaxial dynamic disturbance test, the measured joint roughness coefficient of the fracture surface of the specimen; The measured joint roughness coefficient of the specimen fracture surface after a load-bearing test under equivalent static conditions; The critical allowable relative deviation is set to 0.15 in this embodiment, and preferably not greater than 0.10. When the relative deviation of interface roughness exceeds 15%, the shear slip friction characteristics of the fracture surface change significantly, which has a substantial impact on the energy dissipation mechanism of failure, indicating that the failure control mechanism has shifted. A consistency score for the fracture mechanism is then obtained by comprehensively considering these factors.
[0045] For the time-related damage mechanism, the relative deviation of the accelerated creep rate is calculated as follows: ; In the formula, No. The relative deviation of the accelerated creep rate under each stress step; To achieve the first under the high-frequency dynamic disturbance limit condition, The average strain rate of the accelerated creep stage of each stress step; To achieve the first under equivalent static conditions, The average strain rate of the accelerated creep stage of each stress step.
[0046] And based on The threshold (more stringent is 0.10, with an engineering upper limit of 0.20) is used for judgment. From a physical and experimental perspective, since the creep rate itself has a large dispersion (5–10%), there are boundary disturbances during the step loading process, and there are still microstructural differences even under the high-frequency limit. Therefore, less than 10% is too precise, while greater than 20% means that the creep mechanism has changed significantly. 15% is a more reasonable physical consistency threshold, and finally, the consistency score of the time-related damage mechanism is obtained.
[0047] The model construction process in step S530 involves allocating weight coefficients based on the consistency score results described above, according to the importance of the criteria (time-dependent damage as the primary controller, damage mechanism as the control, and macroscopic response as the auxiliary). The weight allocation is not arbitrary but based on the fundamental role of the physical mechanisms reflected by each criterion in long-term intensity formation. For example, Figure 6 As shown, the time-dependent damage mechanism is given the highest weight because long-term strength essentially depends on the accumulation of damage and the accelerated instability process, and the dynamic creep acceleration characteristics directly characterize this dominant mechanism. Figure 5 As shown, the failure mechanism determines the final instability mode and energy dissipation path of the rock mass, and is a direct manifestation of strength failure. For example... Figure 4 As shown, the macroscopic deformation response serves as an auxiliary criterion, reflecting the overall mechanical behavior trend but not directly determining the instability control mechanism. Therefore, the weight allocation is clearly defined as follows: ; In the formula, For deformation response weights, preferably, ; For the fracture mode weights, preferably, ; For dynamic creep acceleration weights, preferably, ; The linear weighted fusion formula is expressed as: ; In the formula, This represents the overall consistency score under the limiting condition where the frequency approaches infinity. , , The consistency scores are for deformation response mechanism, fracture mechanism, and aging damage mechanism, respectively. For deformation response weights; Weights for fracture modes; Weights are added to accelerate dynamic creep. Decision rules are integrated (e.g., if...). It is believed that the high-frequency ultimate dynamic disturbance is consistent with the equivalent static failure mechanism, and the equivalent static long-term strength can be adopted; if This suggests that there is some mechanistic bias, requiring a correction of the long-term intensity; if If the dynamic disturbance alters the control mechanism (and cannot be directly extrapolated), then a multi-mechanism fusion prediction model containing weighted comprehensive score output and specific judgment rules is obtained.
[0048] Further, step S600 includes steps S610 to S630.
[0049] Step S610: Calculate the weighted comprehensive consistency score based on the long-term intensity prediction value and the multidimensional criterion score to obtain the comprehensive score result output by the model; Step S620: Make a consistency judgment based on the comprehensive scoring result. By comparing the scoring result with the preset consistency threshold, determine whether the equivalent static failure mechanism is consistent with the high-frequency dynamic disturbance failure mechanism based on whether the threshold is reached, and obtain a judgment conclusion on whether the equivalent static reference value can be directly adopted. Step S630: Output according to the judgment conclusion. If it is determined that it can be used directly, the long-term intensity prediction value is directly output as the final long-term intensity value. If it is determined that it needs to be corrected, the long-term intensity prediction value is scaled proportionally according to the scoring deviation. If it is determined that it is unusable, a prompt indicating that the mechanism has failed is output.
[0050] Specifically, step S610, based on the obtained long-term strength prediction value under equivalent static conditions and the multi-dimensional criterion score reflecting the consistency of the three mechanisms of deformation, fracture, and aging damage, obtains a single, comprehensive consistency score result from the model output through a core calculation involving assigning predetermined weights to each sub-item score and performing a weighted summation. Step S620 is a step of logical judgment based on the score. By comparing it with a pre-set acceptable lower limit threshold, and based on whether the score reaches or exceeds the threshold, it determines at the principle level whether the "equivalent static failure mechanism" and the "target high-frequency dynamic disturbance failure mechanism" are essentially consistent, and accordingly obtains a judgment conclusion on whether the equivalent static long-term strength prediction value can be directly adopted as the final prediction value. Step S630 is a step of executing the output rules based on the judgment conclusion. The final output is a definite value that can be directly used for engineering stability evaluation or a conclusion with guiding significance.
[0051] Example 2: like Figure 2As shown, this embodiment provides a true triaxial hard rock dynamic disturbance frequency influence long-term strength prediction system, the system including: The acquisition module 901 is used to acquire dynamic disturbance parameters, rock compression process data and fracture morphology data in long-term dynamic disturbance true triaxial test. The construction module 902 is used to construct characteristic curves based on dynamic disturbance parameters and rock compression process data. It extracts the rate of change information of the data through differential operation and constructs characteristic curves, including stress-strain curves, strain-time curves and strain rate evolution curves at different disturbance frequencies. The mapping module 903 is used to perform equivalent static mapping based on dynamic disturbance parameters and characteristic curves. By converting periodic dynamic disturbance loads into equivalent static loads, the equivalent static stress state under the limiting frequency condition is obtained. The fitting module 904 is used to fit the equivalent static stress state. By implementing a load-bearing test under equivalent static conditions and analyzing the entire process from creep to failure, the long-term strength prediction value under equivalent static conditions is obtained. The quantization module 905 is used to build a model based on the characteristic curves and fracture morphology data. It evaluates the consistency between the deformation response mechanism, fracture mechanism, and time-effect damage mechanism and the equivalent static state by quantification, and obtains a multi-dimensional criterion score. Output module 906 is used to determine and correct the long-term intensity prediction value based on the multidimensional criterion score, and obtain the output result.
[0052] In one specific embodiment of this application, the construction module 902 includes: The first building unit is used to extract features based on dynamic disturbance parameters and rock compression process data. By aligning the timestamps and removing outliers from the synchronously recorded stress, strain and time data, a stress-strain-time series dataset is obtained. The second building unit is used to calculate the strain rate based on the stress-strain-time series dataset. It obtains the strain rate data sequence through the core processing of the ratio of strain increment to time in the long-term disturbance period for each principal stress direction. The third building unit is used to construct and correlate curves based on the stress-strain-time series dataset and the strain rate data series. By synchronously correlating and plotting the stress-strain series, strain-time series and strain rate-time series according to the same time base, the characteristic curve is obtained.
[0053] In one specific embodiment of this application, the mapping module 903 includes: The first mapping unit is used to perform disturbance condition analysis based on dynamic disturbance parameters. By extracting the specific direction and amplitude information of the applied dynamic disturbance, it obtains the identifier of the direction of the disturbed principal stress and its corresponding disturbance amplitude. The second mapping unit is used to perform equivalent static calculations based on the orientation of the disturbed principal stress and the disturbance amplitude, combined with the condition that the frequency in the dynamic disturbance parameters tends to infinity, to obtain the equivalent static stress value in the direction of the disturbed principal stress. The third mapping unit is used to integrate the equivalent static stress value with the original static stress value in the undisturbed direction. By combining the stress values of the maximum principal stress, intermediate principal stress, and minimum principal stress, the equivalent static stress state characterizing the high-frequency disturbance limit condition is obtained.
[0054] In one specific embodiment of this application, the fitting module 904 includes: The first fitting unit is used to design a load-bearing test scheme based on the equivalent static stress state. By applying the stress state as a constant load to the new hard rock specimen and setting a preset duration, a long-term load-bearing test loading scheme is obtained. The second fitting unit is used to carry out the test and monitor the data according to the loading scheme of the long-term load test. By continuously monitoring and recording the strain and time data of the rock during the test, strain-time series data describing the whole process of creep evolution of the rock under equivalent static force are obtained. The third fitting unit is used to determine the long-term strength based on strain-time series data. By analyzing the characteristics of strain rate change over time, it identifies the critical point from steady-state creep to accelerated creep and eventually failure, and obtains the predicted long-term strength value under equivalent static conditions.
[0055] In one specific embodiment of this application, the quantization module 905 includes: The first quantization unit is used to extract features based on characteristic curves and fracture morphology data. It calculates the full curve morphology deviation from stress-strain curves and strain-time curves respectively, extracts the fracture angle and JRC roughness index from fracture morphology, and identifies and calculates the average rate of accelerated creep stage from strain rate evolution curve to obtain a set of quantization parameters. The second quantification unit is used to perform consistency scoring of sub-mechanisms based on the quantification parameter set. By comparing the parameters in the quantification parameter set with the corresponding results of the equivalent static test, and calculating based on the preset similarity threshold, the consistency score results of deformation response, fracture mechanism and time-effect damage mechanism are obtained. The third quantization unit is used to build a model based on the consistency score. Through weight allocation and linear weighted fusion, a multi-mechanism fusion prediction model containing weighted comprehensive score output and judgment rules is obtained.
[0056] In one specific embodiment of this application, the output module 906 includes: The first output unit is used to calculate the weighted comprehensive consistency score based on the long-term intensity prediction value and the multidimensional criterion score, and obtain the comprehensive score result output by the model. The second output unit is used to make a consistency judgment based on the comprehensive scoring result. By comparing the scoring result with a preset consistency threshold, it determines whether the equivalent static failure mechanism and the high-frequency dynamic disturbance failure mechanism are consistent based on whether the threshold is reached, and obtains a judgment conclusion on whether the equivalent static reference value can be directly adopted. The third output unit is used to output based on the judgment conclusion. If it is determined that it can be directly adopted, the long-term intensity prediction value is directly output as the final long-term intensity value. If it is determined that it needs to be corrected, the long-term intensity prediction value is scaled proportionally according to the scoring deviation. If it is determined that it is unusable, a prompt indicating that the mechanism has failed is output.
[0057] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.
Claims
1. A method for predicting the long-term strength of hard rock under the influence of dynamic disturbance frequency in true triaxial hard rock, characterized in that, include: To obtain dynamic disturbance parameters, rock compression process data, and fracture morphology data in long-term dynamic disturbance true triaxial tests; Characteristic curves are constructed based on the dynamic disturbance parameters and the rock compression process data. The rate of change information of the data is extracted through differential operation to construct the characteristic curves. The characteristic curves include stress-strain curves, strain-time curves and strain rate evolution curves at different disturbance frequencies. Based on the dynamic disturbance parameters and the characteristic curve, an equivalent static mapping is performed. By converting the periodic dynamic disturbance load into an equivalent static load, the equivalent static stress state under the limiting frequency condition is obtained. By fitting the equivalent static stress state, and by conducting a load-bearing test under the equivalent static conditions and analyzing the entire process from creep to failure, the long-term strength prediction value under the equivalent static conditions is obtained. A model is constructed based on the characteristic curves and the fracture morphology data. A multidimensional criterion score is obtained by quantitatively evaluating the consistency between the deformation response mechanism, fracture mechanism, time-effect damage mechanism and equivalent static state. The long-term intensity prediction value is determined and corrected based on the multidimensional criterion score to obtain the output result.
2. The method for predicting the long-term strength of true triaxial hard rock dynamic disturbance frequency according to claim 1, characterized in that, Characteristic curves are constructed based on the dynamic disturbance parameters and the rock compression process data, including: Feature extraction is performed based on the dynamic disturbance parameters and the rock compression process data. By aligning the timestamps and removing outliers from the synchronously recorded stress, strain and time data, a stress-strain-time series dataset is obtained. Strain rate is calculated based on the stress-strain-time series dataset. The strain rate data sequence is obtained by the core processing of the ratio of strain increment to time in a long-term disturbance period for each principal stress direction. Curves are constructed and correlated based on the stress-strain-time series dataset and the strain rate data series. By synchronously correlating and plotting the stress-strain series, strain-time series and strain rate-time series according to the same time base, characteristic curves are obtained.
3. The method for predicting the long-term strength of true triaxial hard rock dynamic disturbance frequency according to claim 1, characterized in that, Equivalent static mapping based on the dynamic disturbance parameters and the characteristic curve includes: Based on the dynamic disturbance parameters, the disturbance condition analysis is carried out. By extracting the specific direction and amplitude information of the applied dynamic disturbance, the identification of the direction of the disturbed principal stress and its corresponding disturbance amplitude are obtained. Based on the identified principal stress direction and the disturbance amplitude, and combined with the condition that the frequency in the dynamic disturbance parameters tends to infinity, an equivalent static stress calculation is performed to obtain the equivalent static stress value in the principal stress direction. Based on the equivalent static stress value, and combined with the original static stress value in the undisturbed direction, the equivalent static stress state characterizing the high-frequency disturbance limit condition is obtained by combining the stress values of the maximum principal stress, intermediate principal stress, and minimum principal stress.
4. The method for predicting the long-term strength of true triaxial hard rock dynamic disturbance frequency according to claim 1, characterized in that, Fitting based on the equivalent static stress state includes: Based on the equivalent static stress state, a load-holding test scheme is designed. By applying the stress state as a constant load to a new hard rock specimen and setting a preset duration, a long-term load-holding test loading scheme is obtained. The test was carried out and data monitoring was conducted according to the long-term load test loading scheme. By continuously monitoring and recording the strain and time data of the rock during the test, strain-time series data describing the entire creep evolution process of the rock under equivalent static load were obtained. Based on the strain-time series data, long-term strength is determined. By analyzing the characteristics of strain rate change over time, the critical point from steady-state creep to accelerated creep and ultimately failure is identified, and the predicted long-term strength value under equivalent static conditions is obtained.
5. The method for predicting the long-term strength of true triaxial hard rock dynamic disturbance frequency according to claim 1, characterized in that, Model construction based on the characteristic curves and the fracture morphology data includes: Feature extraction is performed based on the characteristic curve and the fracture morphology data. The full curve morphology deviation is calculated from the stress-strain curve and the strain-time curve, respectively. The fracture angle and JRC roughness index are extracted from the fracture morphology. The average rate of the accelerated creep stage is identified and calculated from the strain rate evolution curve to obtain a set of quantitative parameters. Consistency scores for sub-mechanisms are calculated based on the set of quantified parameters. The parameters in the set of quantified parameters are compared with the corresponding results of equivalent static tests, and the consistency scores for deformation response, fracture mechanism and time-effect damage mechanism are calculated based on a preset similarity threshold. The model is constructed based on the consistency score, and a multi-mechanism fusion prediction model containing weighted comprehensive score output and judgment rules is obtained through weight allocation and linear weighted fusion.
6. A system for predicting the long-term strength of hard rock under the influence of dynamic disturbance frequency, characterized in that, include: The acquisition module is used to acquire dynamic disturbance parameters, rock compression process data, and fracture morphology data in long-term dynamic disturbance true triaxial tests. The construction module is used to construct characteristic curves based on the dynamic disturbance parameters and the rock compression process data. It extracts the rate of change information of the data through differential operations to construct characteristic curves, which include stress-strain curves, strain-time curves and strain rate evolution curves at different disturbance frequencies. The mapping module is used to perform equivalent static mapping based on the dynamic disturbance parameters and the characteristic curve, and to obtain the equivalent static stress state under the limiting frequency condition by converting the periodic dynamic disturbance load into an equivalent static load. The fitting module is used to fit the equivalent static stress state. By implementing a load-bearing test under the equivalent static condition and analyzing the entire process from creep to failure, the long-term strength prediction value under the equivalent static condition is obtained. The quantization module is used to construct a model based on the characteristic curve and the fracture morphology data, and to obtain a multi-dimensional criterion score by quantifying and evaluating the consistency between the deformation response mechanism, fracture mechanism, time-effect damage mechanism and equivalent static state. The output module is used to determine and correct the long-term intensity prediction value based on the multidimensional criterion score, and obtain the output result.
7. The long-term strength prediction system for the influence of true triaxial hard rock dynamic disturbance frequency as described in claim 6, characterized in that, The building module includes: The first construction unit is used to extract features based on the dynamic disturbance parameters and the rock compression process data, and to obtain a stress-strain-time series dataset by performing timestamp alignment and outlier removal on the synchronously recorded stress, strain and time data. The second building unit is used to calculate the strain rate based on the stress-strain-time series dataset. It obtains the strain rate data sequence through the core processing of the ratio of strain increment to time in a long-term disturbance period for each principal stress direction. The third construction unit is used to construct and correlate curves based on the stress-strain-time series dataset and the strain rate data series. By synchronously correlating and plotting the stress-strain series, strain-time series and strain rate-time series according to the same time base, a characteristic curve is obtained.
8. The long-term strength prediction system for the influence of true triaxial hard rock dynamic disturbance frequency as described in claim 6, characterized in that, The mapping module includes: The first mapping unit is used to perform disturbance condition analysis based on dynamic disturbance parameters. By extracting the specific direction and amplitude information of the applied dynamic disturbance, it obtains the identifier of the direction of the disturbed principal stress and its corresponding disturbance amplitude. The second mapping unit is used to perform equivalent static calculation based on the perturbed principal stress direction identifier and the perturbation amplitude, combined with the condition that the frequency in the dynamic perturbation parameters tends to infinity, to obtain the equivalent static stress value in the perturbed principal stress direction. The third mapping unit is used to integrate the equivalent static stress value with the original static stress value in the undisturbed direction, and obtain the equivalent static stress state characterizing the high-frequency disturbance limit condition by combining the stress values of the maximum principal stress, intermediate principal stress and minimum principal stress.
9. The long-term strength prediction system for the influence of true triaxial hard rock dynamic disturbance frequency as described in claim 6, characterized in that, The fitting module includes: The first fitting unit is used to design a load-bearing test scheme based on the equivalent static stress state. By applying the stress state as a constant load to the new hard rock specimen and setting a preset duration, a long-term load-bearing test loading scheme is obtained. The second fitting unit is used to carry out the test and monitor the data according to the long-term load test loading scheme. By continuously monitoring and recording the strain and time data of the rock during the test, strain-time series data describing the whole process of creep evolution of the rock under equivalent static force are obtained. The third fitting unit is used to determine the long-term strength based on the strain-time series data. By analyzing the characteristics of the strain rate change over time, it identifies the critical point from steady-state creep to accelerated creep and eventually leads to failure, and obtains the predicted long-term strength value under equivalent static conditions.
10. The long-term strength prediction system for the influence of true triaxial hard rock dynamic disturbance frequency according to claim 6, characterized in that, The quantization module includes: The first quantization unit is used to extract features based on the characteristic curve and the fracture morphology data. It calculates the full curve morphology deviation from the stress-strain curve and the strain-time curve respectively, extracts the fracture angle and JRC roughness index from the fracture morphology, and identifies and calculates the average rate of the accelerated creep stage from the strain rate evolution curve to obtain a set of quantization parameters. The second quantification unit is used to perform consistency scoring of sub-mechanisms based on the quantification parameter set. By comparing the parameters in the quantification parameter set with the corresponding results of the equivalent static test, and calculating based on a preset similarity threshold, the consistency scoring results of deformation response, fracture mechanism and time-effect damage mechanism are obtained. The third quantization unit is used to construct a model based on the consistency score, and obtain a multi-mechanism fusion prediction model containing a weighted comprehensive score output and judgment rules through weight allocation and linear weighted fusion.