Method for detecting porosity of earth-rock roadbed filler based on particle flow simulation database

Abstract

The invention relates to the technical field of highway subgrade compactness detection, and discloses an earth-rock subgrade filler porosity detection method based on a particle flow simulation database, and the method comprises the following steps: setting filler parameters of an earth-rock filler, and obtaining characteristic parameters of the earth-rock filler; a three-dimensional particle flow model of the earth-rock roadbed is generated, and the porosity is recorded; recording dynamic response data corresponding to different porosities, and fitting a porosity calculation model; changing filler parameters and load conditions to obtain porosity calculation models of different filler parameters under different load conditions, and constructing a particle flow simulation database; carrying out PFWD test on the earth-rock roadbed, and measuring roadbed surface dynamic response data; retrieving a corresponding porosity calculation model in the particle flow simulation database, and calculating the porosity of the earth-rock roadbed; according to the invention, an efficient and accurate solution is provided for detecting the porosity of the earth-rock roadbed filler, and the quality and efficiency of the porosity detection work are improved.

Description

Technical Field

[0001] The invention relates to the technical field of highway roadbed compaction detection, and in particular to a soil-rock roadbed filler porosity detection method based on a particle flow simulation database. Background Art

[0002] Soil-rock mixed filler is a common roadbed filling material. Different from soil filler, soil-rock mixed filler is a typical bulk material with complex material composition and strong variability in mechanical properties. The study of the performance of soil-rock roadbed based on continuous medium theory has certain limitations. Porosity is one of the key indicators for evaluating the compaction quality of fillers, which is related to the stability, bearing capacity and durability of the roadbed. Traditional porosity detection methods mainly include core sampling method, sand filling method and nuclear density meter method. Although these methods can provide certain detection data, they have many shortcomings in efficiency, accuracy and real-time performance.

[0003] Traditional detection methods usually require sampling and then laboratory analysis, which is not only time-consuming and labor-intensive, but also difficult to meet the needs of rapid detection in large-scale engineering projects. Traditional detection methods rely on manual operation and are easily affected by the technical level of the operator. The process of manual sampling and analysis is cumbersome, which increases the cost of detection. Traditional detection methods are often difficult to implement under complex geological conditions. For example, in mountainous areas or soft soil areas, core sampling and sand filling methods may not be able to perform effective detection due to the limitations of geological conditions. In addition, although the nuclear density meter method is not restricted by terrain, its equipment is bulky and difficult to carry. In addition, traditional detection methods can only provide static data and cannot achieve dynamic monitoring of the porosity of roadbed fillers. During the construction process, the porosity of the roadbed filler will change with the change of compaction degree. Traditional detection methods cannot track these changes in real time, resulting in the inability to adjust construction parameters in time, thus affecting the quality of the project.

[0004] For example, the patent application with publication number CN113310868A discloses a device and method for measuring the porosity of an in-situ soil-rock mixture by resistivity method, the device includes a geotextile, the geotextile is coated with polyvinyl chloride insulating coating, the polyvinyl chloride insulating coating is provided with an electrode, and a GPS positioning point is provided in the electrode, the electrode is led out with an electric wire, and an impedance meter is provided at one end of the electric wire away from the electrode. In the device for measuring the porosity of an in-situ soil-rock mixture by resistivity method, the porosity of the soil-rock mixture can be measured quickly at the construction site, the operation is simple, the excavation of a test pit in a solid soil layer after rolling on site is avoided, and the error of human reading is reduced, but there are still problems of low detection accuracy and low detection efficiency.

[0005] The information disclosed in this background technology section is only intended to enhance the understanding of the overall background of the invention and should not be regarded as an acknowledgement or any form of suggestion that the information constitutes the prior art already known to ordinary technicians in this field. Summary of the invention

[0006] The technical problem to be solved by the present invention is to overcome the defects of the prior art and provide a porosity detection method for soil-rock roadbed fillers based on a particle flow simulation database, thereby improving the quality and efficiency of porosity detection work.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] In one aspect, the present invention provides a method for detecting porosity of soil-rock roadbed filler based on a particle flow simulation database, comprising the following steps:

[0009] S1: Set the filling parameters of the soil-rock filling and obtain the characteristic parameters of the soil-rock filling through triaxial test;

[0010] S2: generating a three-dimensional particle flow model of the soil-rock roadbed based on the filler parameters and characteristic parameters, and recording the porosity of the three-dimensional particle flow model;

[0011] S3: setting load conditions and applying simulated loads to the three-dimensional particle flow model, and recording dynamic response data of the surface of the three-dimensional particle flow model;

[0012] S4: Keeping the filler parameters and the load conditions unchanged, repeating steps S1 to S3, recording the dynamic response data corresponding to different porosities, and fitting the porosity calculation model;

[0013] S5: Keep the load condition unchanged, change the filler parameters and repeat steps S1 to S4 to obtain a porosity calculation model with different filler parameters under the same load condition;

[0014] S6: changing the load condition and repeating steps S1 to S5 to obtain a porosity calculation model for different filler parameters under different load conditions, and constructing a particle flow simulation database;

[0015] S7: collecting soil and rock samples of the soil and rock roadbed and determining the filling parameters of the soil and rock roadbed; setting load conditions to apply PFWD test loads to the soil and rock roadbed and measuring dynamic response data of the soil and rock roadbed surface;

[0016] S8: Retrieve a corresponding porosity calculation model from a particle flow simulation database based on the filling parameters and load conditions of the soil-rock roadbed, and calculate the porosity of the soil-rock roadbed based on the corresponding porosity calculation model.

[0017] As a preferred solution of the porosity detection method of soil-rock roadbed filler based on particle flow simulation database of the present invention, wherein: the filler parameters include soil-rock ratio, particle size distribution, density, and water content; the characteristic parameters include internal friction angle, cohesion, stress-strain curve, elastic modulus, and Poisson's ratio;

[0018] The method for obtaining characteristic parameters of soil-rock filler through triaxial test is as follows:

[0019] Through the sieving experiment, soil and rock particles of each particle size range are obtained, and the materials are batched according to the set filling parameters to obtain cylindrical filling samples;

[0020] applying a confining pressure to the fill sample;

[0021] Apply an axial load to the filler sample, gradually increase the axial load until the filler sample is destroyed, record the stress magnitude of the axial load and the corresponding axial strain and lateral strain, and draw a stress-strain curve; wherein the abscissa of the stress-strain curve is the axial strain of the filler sample, and the ordinate is the stress magnitude of the axial load, in kilopascals;

[0022] The initial straight line segment of the stress-strain curve is intercepted and the slope is calculated to obtain the elastic modulus; any point is selected from the initial straight line segment to obtain the corresponding axial strain and transverse strain, and the Poisson's ratio is calculated;

[0023] The stress of the axial load and the confining pressure when the filler sample is destroyed are recorded, a Mohr circle diagram is drawn, and the internal friction angle and cohesion are calculated by the Mohr-Cou l omb law.

[0024] As a preferred solution of the porosity detection method of soil-rock roadbed filler based on particle flow simulation database of the present invention, the method of generating a three-dimensional particle flow model of the soil-rock roadbed and recording the porosity of the three-dimensional particle flow model is as follows:

[0025] Set the filling parameters and characteristic parameters of soil-rock filling in discrete element software;

[0026] A three-dimensional particle flow model of an earth-rock roadbed is generated from bottom to top in three layers by the falling rain method; the three-dimensional particle flow models are, from bottom to top, an embankment, a lower roadbed, and an upper roadbed; each time a layer is generated, a simple harmonic load is applied to the upper surface of the three-dimensional particle flow model; a complete three-dimensional particle flow model of an earth-rock roadbed is obtained, and the porosity of the three-dimensional particle flow model is read and recorded by discrete element software.

[0027] As a preferred solution of the porosity detection method of soil-rock roadbed filler based on particle flow simulation database of the present invention, wherein: applying simulated load to the three-dimensional particle flow model is a simulation process of PFWD test; the load conditions include load size, load plate parameters, and load height; wherein the load size represents the weight of the heavy hammer in the PFWD test; the load plate parameters represent the shape and size of the load plate in the PFWD test; the load height represents the release height of the heavy hammer in the PFWD test;

[0028] The dynamic response data includes surface displacement, surface acceleration, and deflection; wherein the surface displacement represents the displacement of the roadbed surface, including horizontal displacement and vertical displacement; the surface acceleration represents the acceleration of the roadbed surface, including horizontal acceleration and vertical acceleration; the deflection represents the maximum sinking amount of the roadbed surface; N sampling points are set around the load plate, the horizontal displacement, vertical displacement, horizontal acceleration, and vertical acceleration of the N sampling points are recorded and averaged respectively to obtain the surface displacement and surface acceleration in the dynamic response data; the displacement of the roadbed surface corresponding to the impact point of the heavy hammer is recorded to obtain the deflection.

[0029] As a preferred scheme of the porosity detection method of soil-rock roadbed filler based on particle flow simulation database described in the present invention, the porosity calculation model is any one of a linear regression model, a polynomial regression model, and a support vector regression model; the input is dynamic response data, and the output is porosity; the linear regression model, the polynomial regression model, and the support vector regression model are respectively fitted through different porosities and their corresponding dynamic response data, and the model is tested, and the model with the smallest calculation error is taken as the porosity calculation model.

[0030] As a preferred scheme of the porosity detection method of soil-rock roadbed filler based on particle flow simulation database described in the present invention, wherein: the particle flow simulation database includes filler parameters, load conditions, porosity, dynamic response data corresponding to any porosity of each filler parameter under each load condition, and a porosity calculation model of each filler parameter under each load condition; wherein any porosity calculation model corresponds to a unique set of filler parameters and load conditions.

[0031] As a preferred solution of the porosity detection method of soil-rock roadbed filler based on particle flow simulation database of the present invention, the method of measuring the dynamic response data of the soil-rock roadbed surface is as follows:

[0032] Based on the set load plate parameters, the corresponding load plate is selected and placed horizontally on the surface of the soil-rock roadbed, and the load plate is impact preloaded;

[0033] Select the corresponding weight based on the set load size and load height and lift it to the corresponding height;

[0034] Release the heavy hammer to hit the load plate, and collect real-time displacement data of the earth-rock roadbed surface through the displacement sensor;

[0035] The dynamic response data of the earth-rock roadbed surface are calculated based on the real-time displacement data, including horizontal displacement, vertical displacement, horizontal acceleration, vertical acceleration, and deflection.

[0036] In a second aspect, the present invention provides an electronic device, comprising: a memory for storing instructions; a processor for executing the instructions, so that the device performs operations to implement the porosity detection method of soil-rock roadbed filling material based on a particle flow simulation database described in the present invention.

[0037] In a third aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the porosity detection method for soil-rock roadbed filler based on a particle flow simulation database described in the present invention.

[0038] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0039] The present invention proposes a new porosity detection method, which improves detection efficiency, reduces manual operations, and reduces detection costs. Through a small number of field tests, the mathematical relationship between PFWD test parameters and porosity can be quickly retrieved and calibrated, thereby realizing rapid porosity detection of soil-rock roadbed fillers based on PFWD testing.

[0040] The present invention fills the gap in data coverage of traditional methods by simulating porosity under different filler parameters and load conditions, and can fully cover various working conditions of roadbed. By simulating different filler parameters, the present invention can adapt to various complex engineering environments. By establishing a particle flow simulation database, efficient management and analysis of a large amount of test data is achieved, and the porosity calculation model is used to automatically analyze the dynamic response data, simplifying the data processing process and improving the accuracy and efficiency of data analysis.

[0041] The present invention can record the dynamic response data under different load conditions in real time, and calculate the porosity based on it, thus realizing the dynamic monitoring of the porosity of the roadbed filler. By real-time monitoring of the porosity change, it can guide the timely adjustment of construction parameters, optimize the compaction process, and ensure the construction quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0043] Figure 1 A flow chart of the porosity detection method for soil-rock roadbed filler based on a particle flow simulation database provided by the present invention;

[0044] Figure 2 A flow chart of the method for measuring dynamic response data of the earth-rock roadbed surface provided by the present invention. DETAILED DESCRIPTION

[0045] The technical solution of the present invention is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations on the technical solution of the present invention. The embodiments of the present invention and the technical features in the embodiments may be combined with each other unless there is a conflict.

[0046] Example 1

[0047] This embodiment introduces a porosity detection method for soil-rock roadbed filler based on a particle flow simulation database. Figure 1 , the method comprises the following steps:

[0048] S1: Set the filling parameters of the soil-rock filling and obtain the characteristic parameters of the soil-rock filling through triaxial test;

[0049] The filler parameters include soil-rock ratio, particle size distribution, density, and water content; the soil-rock ratio is the ratio of soil to stone, which will affect the overall mechanical properties of the soil-rock filler. The particle size distribution refers to the ratio of soil and stone particles within each particle size range. Fillers with different particle size distributions have different forces on the internal particles. Density affects the mass of the filler per unit volume, thereby affecting the load-bearing capacity and deformation characteristics of the filler. Water content also affects the mechanical properties of the filler.

[0050] The characteristic parameters include internal friction angle, cohesion, stress-strain curve, elastic modulus, and Poisson's ratio; the method for obtaining the characteristic parameters of soil-stone filler through triaxial test is as follows:

[0051] Through the sieving experiment, soil and rock particles of each particle size range are obtained, and the materials are batched according to the set filling parameters to obtain cylindrical filling samples;

[0052] Applying confining pressure to the filler sample; wherein the confining pressure is 200 kPa; this step simulates the lateral pressure in actual engineering;

[0053] Apply an axial load to the filler sample, gradually increase the axial load until the filler sample is destroyed, record the stress magnitude of the axial load and the corresponding axial strain and lateral strain, and draw a stress-strain curve; wherein the abscissa of the stress-strain curve is the axial strain of the filler sample, and the ordinate is the stress magnitude of the axial load, in kilopascals; the axial strain is the ratio of the change in the axial length of the filler sample under the axial load to the original axial length;

[0054] The initial straight line segment of the stress-strain curve is intercepted and the slope is calculated to obtain the elastic modulus; any point is selected from the initial straight line segment, the corresponding axial strain and transverse strain are obtained, and the Poisson's ratio is calculated; the Poisson's ratio is the ratio of the selected transverse strain to the corresponding axial strain.

[0055] The stress of the axial load and the confining pressure when the filler sample is destroyed are recorded, a Mohr circle diagram is drawn, and the internal friction angle and cohesion are calculated by the Mohr-Cou l omb law.

[0056] The stress-strain curve reflects the deformation of the filler under different stress levels and describes the deformation characteristics of the filler under different load conditions; the elastic modulus describes the elastic deformation characteristics of soil-rock particles under stress; the cohesion describes the bonding characteristics between soil-rock particles; the internal friction angle describes the friction characteristics of soil-rock particles under shear load; and the Poisson's ratio affects the lateral deformation characteristics of the filler under stress. Marking these characteristic parameters in the discrete element software can help the software more accurately simulate the structural changes and dynamic responses of the soil-rock roadbed when subjected to external forces, ensuring that the three-dimensional particle flow model can simulate the real working conditions.

[0057] S2: generating a three-dimensional particle flow model of the soil-rock roadbed based on the filler parameters and characteristic parameters, and recording the porosity of the three-dimensional particle flow model;

[0058] The method of generating a three-dimensional particle flow model of a soil-rock roadbed and recording the porosity of the three-dimensional particle flow model is as follows:

[0059] Set the filling parameters and characteristic parameters of soil-rock filling in discrete element software;

[0060] A three-dimensional particle flow model of an earth-rock roadbed is generated from bottom to top in three layers by the falling rain method; the three-dimensional particle flow models are, from bottom to top, an embankment, a lower roadbed, and an upper roadbed; each time a layer is generated, a simple harmonic load is applied to the upper surface of the three-dimensional particle flow model; a complete three-dimensional particle flow model of an earth-rock roadbed is obtained, and the porosity is read and recorded by discrete element software.

[0061] Discrete element software such as PFC3D, EDEM, and YADE can simulate the behavior of granular materials in three-dimensional space; by marking filler parameters such as soil-rock ratio, particle size distribution, density, and water content, and characteristic parameters such as internal friction angle, cohesion, stress-strain curve, elastic modulus, and Poisson's ratio, discrete element software can simulate the structure and dynamic response of a real soil-rock roadbed when subjected to external loads, thereby providing data support for the exploration of the relationship between porosity and dynamic response. Discrete element software can calculate porosity by calculating the space and total volume occupied by soil-rock particles.

[0062] S3: setting load conditions and applying simulated loads to the three-dimensional particle flow model, and recording dynamic response data of the surface of the three-dimensional particle flow model;

[0063] Applying a simulated load to the three-dimensional particle flow model is a simulation process of the PFWD test; the load conditions include load size, load plate parameters, and load height; wherein the load size represents the weight of the heavy hammer in the PFWD test, such as 5000N; the load plate parameters represent the shape and size of the load plate in the PFWD test, such as a circle with a diameter of 30cm; the load height represents the release height of the heavy hammer in the PFWD test, such as 0.5 meters;

[0064] The dynamic response data includes surface displacement, surface acceleration, and deflection; wherein the surface displacement represents the displacement of the roadbed surface, including horizontal displacement and vertical displacement; the surface acceleration represents the acceleration of the roadbed surface, including horizontal acceleration and vertical acceleration; the deflection represents the maximum sinking amount of the roadbed surface; N sampling points are set around the load plate, where N is a positive integer; the horizontal displacement, vertical displacement, horizontal acceleration, and vertical acceleration of the N sampling points are recorded and averaged respectively to obtain the surface displacement and surface acceleration in the dynamic response data; the displacement of the roadbed surface corresponding to the impact point of the heavy hammer is recorded to obtain the deflection.

[0065] When a simulated load is applied to the three-dimensional particle flow model, the discrete element software will infer the deformation of the three-dimensional particle flow model based on the preset characteristic parameters and calculate the dynamic response data of the surface of the three-dimensional particle flow model.

[0066] S4: Keeping the filler parameters and the load conditions unchanged, repeating steps S1 to S3, recording the dynamic response data corresponding to different porosities, and fitting the porosity calculation model;

[0067] The porosity calculation model is any one of a linear regression model, a polynomial regression model, and a support vector regression model; the input is dynamic response data, and the output is porosity; the linear regression model, the polynomial regression model, and the support vector regression model are respectively fitted through different porosities and their corresponding dynamic response data, and the model test is performed, and the model with the smallest calculation error is taken as the porosity calculation model.

[0068] In actual production, each time a layer of roadbed is filled, the filler is compacted by a roller; a simple harmonic load is applied to the upper surface of each layer of the model generated by the rain method to simulate the compaction process of the filler by the roller; the compaction degree of the soil-rock filler is different due to the different rolling times and pressures of the roller, that is, the porosity is different. Based on this principle, different simple harmonic loads are applied each time the three-dimensional particle flow model is generated, and roadbed models with different porosities can be obtained. When the soil-rock roadbed with different porosities is subjected to the test load under the same load condition on the surface, its dynamic response data is different; therefore, by repeatedly executing steps S1 to S3, a large number of different porosities and their corresponding dynamic response data under the same load condition can be obtained, which provides a data basis for fitting the porosity calculation model.

[0069] S5: Keep the load condition unchanged, change the filler parameters and repeat steps S1 to S4 to obtain a porosity calculation model with different filler parameters under the same load condition;

[0070] Different filling parameters correspond to different actual conditions of earth-rock roadbed. Under the same load condition test, the dynamic response data of the surface of earth-rock roadbeds with different actual conditions are also different. Therefore, they correspond to different porosity calculation models. It is necessary to fit the porosity calculation models of earth-rock roadbeds with different filling parameters under the same load condition respectively.

[0071] S6: changing the load condition and repeating steps S1 to S5 to obtain a porosity calculation model for different filler parameters under different load conditions, and constructing a particle flow simulation database;

[0072] The particle flow simulation database includes packing parameters, load conditions, porosity, dynamic response data corresponding to any porosity of each packing parameter under each load condition, and a porosity calculation model of each packing parameter under each load condition; wherein any porosity calculation model corresponds to a unique set of packing parameters and load conditions.

[0073] When exploring the relationship between porosity and dynamic response data, the same test load may not be able to adapt to a variety of soil-rock roadbeds. For example, the filler parameters of a soil-rock roadbed may not respond sensitively to commonly used load conditions, resulting in inaccurate porosity calculation. Therefore, in order to expand the data of the particle flow simulation database, a porosity calculation model under various test load conditions is constructed so that the particle flow simulation database can provide an effective reference for porosity calculation under the actual conditions of variable soil-rock roadbeds. In order to improve the accuracy of the porosity calculation model in the particle flow simulation database, PFWD can be used to conduct field tests on soil-rock roadbeds, and sensors can be arranged to collect dynamic response data on the roadbed surface. The corresponding porosity calculation model is used to obtain the calculated porosity value, and then the actual value of the porosity is obtained based on the field measurement. The porosity calculation model is tuned based on the gap between the actual value and the calculated value of the porosity.

[0074] S7: collecting soil and rock samples of the soil and rock roadbed and determining the filling parameters of the soil and rock roadbed; setting load conditions to apply PFWD test loads to the soil and rock roadbed and measuring dynamic response data of the soil and rock roadbed surface;

[0075] Since the porosity calculation model corresponds to a unique set of filling parameters and load conditions in the particle flow simulation database, in practical applications, it is necessary to sample the earth-rock roadbed, determine its filling parameters, and record the load conditions of the test load in order to retrieve the mathematical relationship between the dynamic response data of the calibration earth-rock roadbed surface and the porosity, that is, to find the porosity calculation model corresponding to the actual earth-rock roadbed in the particle flow simulation database.

[0076] Reference Figure 2 , the method for measuring the dynamic response data of the soil-rock roadbed surface is as follows:

[0077] Based on the set load plate parameters, the corresponding load plate is selected and placed horizontally on the surface of the soil-rock roadbed, and the load plate is impact preloaded;

[0078] Select the corresponding weight based on the set load size and load height and lift it to the corresponding height;

[0079] Release the heavy hammer to hit the load plate, and collect real-time displacement data of the earth-rock roadbed surface through the displacement sensor;

[0080] The dynamic response data of the earth-rock roadbed surface are calculated based on the real-time displacement data, including horizontal displacement, vertical displacement, horizontal acceleration, vertical acceleration, and deflection.

[0081] S8: Retrieve a corresponding porosity calculation model from a particle flow simulation database based on the filling parameters and load conditions of the soil-rock roadbed, and calculate the porosity of the soil-rock roadbed based on the corresponding porosity calculation model.

[0082] The dynamic response data of the soil-rock roadbed surface are input into the corresponding porosity calculation model retrieved from the particle flow simulation database, and the corresponding porosity calculation model calculates and outputs the porosity of the soil-rock roadbed.

[0083] Example 2

[0084] Based on the same inventive concept as Example 1, this embodiment introduces an electronic device, including a memory and a processor, the memory is used to store instructions, and the processor is used to execute the instructions, so that the computer device executes the porosity detection method of soil-rock roadbed filling based on the particle flow simulation database provided in the above embodiment.

[0085] Since the electronic device introduced in this embodiment is an electronic device used to implement the porosity detection method of soil-rock roadbed filler based on particle flow simulation database in the embodiment of this application, based on the porosity detection method of soil-rock roadbed filler based on particle flow simulation database introduced in the embodiment of this application, the technical personnel of this field can understand the specific implementation of the electronic device of this embodiment and its various variations, so how the electronic device implements the method in the embodiment of this application will not be described in detail here. As long as the technical personnel of this field implement the electronic device used by the porosity detection method of soil-rock roadbed filler based on particle flow simulation database in the embodiment of this application, it belongs to the scope of protection of this application.

[0086] Example 3

[0087] Based on the same inventive concept as other embodiments, this embodiment introduces a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the porosity detection method of soil-rock roadbed filler based on a particle flow simulation database provided in the above embodiments is implemented.

[0088] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0089] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the purpose and scope of protection of the present invention, which are all within the protection of the present invention.

Claims

1. A porosity detection method for soil-rock roadbed filler based on a particle flow simulation database, characterized in that: The following steps are involved: S1: Set the filling parameters of the soil-rock filling and obtain the characteristic parameters of the soil-rock filling through triaxial test; S2: generating a three-dimensional particle flow model of the soil-rock roadbed based on the filler parameters and characteristic parameters, and recording the porosity of the three-dimensional particle flow model; S3: setting load conditions and applying simulated loads to the three-dimensional particle flow model, and recording dynamic response data of the surface of the three-dimensional particle flow model; S4: Keeping the filler parameters and the load conditions unchanged, repeating steps S1 to S3, recording the dynamic response data corresponding to different porosities, and fitting the porosity calculation model; S5: Keep the load condition unchanged, change the filler parameters and repeat steps S1 to S4 to obtain a porosity calculation model with different filler parameters under the same load condition; S6: changing the load condition and repeating steps S1 to S5 to obtain a porosity calculation model for different filler parameters under different load conditions, and constructing a particle flow simulation database; S7: collecting soil and rock samples of the soil and rock roadbed and determining the filling parameters of the soil and rock roadbed; setting load conditions to apply PFWD test loads to the soil and rock roadbed and measuring dynamic response data of the soil and rock roadbed surface; S8: Retrieve a corresponding porosity calculation model from a particle flow simulation database based on the filling parameters and load conditions of the soil-rock roadbed, and calculate the porosity of the soil-rock roadbed based on the corresponding porosity calculation model.

2. The porosity detection method of soil-rock roadbed filler based on particle flow simulation database according to claim 1 is characterized in that: The filler parameters include soil-rock ratio, particle size distribution, density, and water content; the characteristic parameters include internal friction angle, cohesion, stress-strain curve, elastic modulus, and Poisson's ratio; The method for obtaining characteristic parameters of soil-rock filler through triaxial test is as follows: Through the sieving experiment, soil and rock particles of each particle size range are obtained, and the materials are batched according to the set filling parameters to obtain cylindrical filling samples; applying a confining pressure to the fill sample; Apply an axial load to the filler sample, gradually increase the axial load until the filler sample is destroyed, record the stress magnitude of the axial load and the corresponding axial strain and lateral strain, and draw a stress-strain curve; wherein the abscissa of the stress-strain curve is the axial strain of the filler sample, and the ordinate is the stress magnitude of the axial load, in kilopascals; The initial straight line segment of the stress-strain curve is intercepted and the slope is calculated to obtain the elastic modulus; any point is selected from the initial straight line segment to obtain the corresponding axial strain and transverse strain, and the Poisson's ratio is calculated; The stress magnitude of the axial load and the pressure of the confining pressure when the filler sample is destroyed are recorded, a Mohr circle diagram is drawn, and the internal friction angle and cohesion are calculated using the Mohr-Coulomb law.

3. The porosity detection method for soil-rock roadbed filler based on particle flow simulation database according to claim 2 is characterized in that: The method of generating a three-dimensional particle flow model of a soil-rock roadbed and recording the porosity of the three-dimensional particle flow model is as follows: Set the filling parameters and characteristic parameters of soil-rock filling in discrete element software; A three-dimensional particle flow model of a soil-rock roadbed is generated from bottom to top in three layers by a rain method; the three-dimensional particle flow model is respectively a road embankment, a lower roadbed, and an upper roadbed from bottom to top; a simple harmonic load is applied to the upper surface of the three-dimensional particle flow model once each layer is generated; A complete three-dimensional particle flow model of the soil-rock roadbed is obtained, and the porosity of the three-dimensional particle flow model is read and recorded by discrete element software.

4. The porosity detection method of soil-rock roadbed filler based on particle flow simulation database according to claim 3 is characterized in that: Applying a simulated load to the three-dimensional particle flow model is a simulation process of the PFWD test; the load conditions include load size, load plate parameters, and load height; wherein the load size represents the weight of the heavy hammer in the PFWD test; the load plate parameters represent the shape and size of the load plate in the PFWD test; and the load height represents the release height of the heavy hammer in the PFWD test; The dynamic response data includes surface displacement, surface acceleration, and deflection; wherein the surface displacement represents the displacement of the roadbed surface, including horizontal displacement and vertical displacement; the surface acceleration represents the acceleration of the roadbed surface, including horizontal acceleration and vertical acceleration; the deflection represents the maximum sinking amount of the roadbed surface; N sampling points are set around the load plate, the horizontal displacement, vertical displacement, horizontal acceleration, and vertical acceleration of the N sampling points are recorded and averaged respectively to obtain the surface displacement and surface acceleration in the dynamic response data; the displacement of the roadbed surface corresponding to the impact point of the heavy hammer is recorded to obtain the deflection.

5. The porosity detection method of soil-rock roadbed filler based on particle flow simulation database according to claim 4 is characterized in that: The porosity calculation model is any one of a linear regression model, a polynomial regression model, and a support vector regression model; the input is dynamic response data, and the output is porosity; the linear regression model, the polynomial regression model, and the support vector regression model are respectively fitted through different porosities and their corresponding dynamic response data, and the model test is performed, and the model with the smallest calculation error is taken as the porosity calculation model.

6. The porosity detection method of soil-rock roadbed filler based on particle flow simulation database according to claim 5 is characterized in that: The particle flow simulation database includes packing parameters, load conditions, porosity, dynamic response data corresponding to any porosity of each packing parameter under each load condition, and a porosity calculation model of each packing parameter under each load condition; wherein any porosity calculation model corresponds to a unique set of packing parameters and load conditions.

7. The porosity detection method for soil-rock roadbed filler based on particle flow simulation database according to claim 6 is characterized in that: The method for measuring the dynamic response data of the soil-rock roadbed surface is as follows: Based on the set load plate parameters, the corresponding load plate is selected and placed horizontally on the surface of the soil-rock roadbed, and the load plate is impact preloaded; Select the corresponding weight based on the set load size and load height and lift it to the corresponding height; Release the heavy hammer to hit the load plate, and collect real-time displacement data of the earth-rock roadbed surface through the displacement sensor; The dynamic response data of the earth-rock roadbed surface are calculated based on the real-time displacement data, including horizontal displacement, vertical displacement, horizontal acceleration, vertical acceleration, and deflection.

8. An electronic device, characterized in that: include: A memory for storing instructions; The processor is used to execute the instructions so that the device performs the operation of implementing the porosity detection method of soil-rock roadbed filling material based on a particle flow simulation database as described in any one of claims 1-7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the porosity detection method of soil-rock roadbed filler based on a particle flow simulation database as described in any one of claims 1 to 7 is implemented.

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