Calcium sand grading effect analysis method and system, electronic equipment and storage medium

Abstract

The invention discloses a calcareous sand grading effect analysis method and system, electronic equipment and a storage medium. The method comprises the steps that grading parameters are constructed according to calcareous sand particle size data; shear strength data are obtained through calculation of the grading parameters; constructing a strength index model according to the shear strength data, the grading parameters and the relative compactness data; constructing a target analysis model according to the strength index model and the relative breakage rate parameter; and performing performance index analysis through the target analysis model to obtain performance index prediction data. According to the embodiment of the invention, the accuracy of the grading effect analysis of the calcareous sand can be effectively improved, and support is provided for the practical application analysis of the calcareous sand. The method can be widely applied to the technical field of calcareous sand property analysis.

Description

Technical Field

[0001] This application relates to the technical field of calcareous sand property analysis, and particularly to a method, system, electronic device and storage medium for analyzing the grading effect of calcareous sand. Background Art

[0002] Due to its particle structure, calcareous sand is fragile, porous and rough, and is extremely prone to breakage under external forces. This friability causes significant changes in the particle size distribution of calcareous sand under stress conditions, thus having an important impact on engineering properties such as shear strength and breakage rate. For example, in reef engineering, the difference in the particle size distribution of coral sand caused by different filling positions and depths directly affects the safety and durability of engineering structures. In related technologies, it is mainly difficult to comprehensively understand the relationship between the particle size distribution of calcareous sand and its mechanical properties, breakage characteristics and shear strength, and it is difficult to be used for the actual application analysis of calcareous sand.

[0003] In summary, the technical problems existing in related technologies need to be improved. Summary of the Invention

[0004] The main purpose of the embodiments of this application is to propose a method, system, electronic device and storage medium for analyzing the grading effect of calcareous sand, which can effectively improve the accuracy of analyzing the grading effect of calcareous sand and provide support for the actual application analysis of calcareous sand.

[0005] To achieve the above object, on the one hand, an embodiment of this application proposes a method for analyzing the grading effect of calcareous sand, and the method includes the following steps:

[0006] Construct grading parameters according to the particle size data of calcareous sand;

[0007] Calculate shear strength data through the grading parameters;

[0008] Construct a strength index model according to the shear strength data, the grading parameters and the relative density data;

[0009] Construct a target analysis model according to the strength index model and the relative breakage rate parameter;

[0010] Perform performance index analysis through the target analysis model to obtain performance index prediction data.

[0011] In some embodiments, the constructing grading parameters according to the particle size data of calcareous sand includes:

[0012] Construct a calcareous sand specimen model according to the particle size data of calcareous sand through a preset particle distribution equation;

[0013] Determine the median grain size according to the calcareous sand sample model, and construct the grading parameters through the median grain size.

[0014] In some embodiments, the shear strength data calculated through the grading parameters includes:

[0015] Sort out the peak stress according to the grading parameters to obtain the peak stress data;

[0016] Calculate the shear strength data through the preset mechanical theory according to the peak stress data; wherein, the shear strength data includes cohesion data and internal friction angle data.

[0017] In some embodiments, the strength index model constructed according to the shear strength data, the grading parameters and the relative density data includes:

[0018] Construct a first model relation according to the shear strength data, the grading parameters and the relative density data;

[0019] Conduct three-dimensional surface analysis according to the first model relation to construct a grading model function relation;

[0020] Construct a coupling parameter according to the grading parameters and the relative density data;

[0021] Construct the strength index model according to the coupling parameter and the grading model function relation.

[0022] In some embodiments, the target analysis model constructed according to the strength index model and the relative breakage rate parameter includes:

[0023] Construct a second model relation according to the relative breakage rate parameter and the grading parameters;

[0024] Construct a third model relation according to the relative breakage rate parameter and the coupling parameter;

[0025] Construct the target analysis model according to the second model relation and the third model relation.

[0026] In some embodiments, the performance index analysis through the target analysis model to obtain performance index prediction data includes:

[0027] Predict the mechanical properties of the preset calcareous sand through the target analysis model to obtain the performance index prediction data; wherein, the performance index prediction data includes calcareous sand strength data and calcareous sand breakage rate data.

[0028] In some embodiments, constructing the first model relationship according to the shear strength data, the grading parameters, and the relative density data includes:

[0029] Constructing a functional relationship equation between the shear strength data and the grading parameters to construct a preset grading model according to the functional relationship equation and the relative density data;

[0030] Performing data processing on the preset grading model and the relative density data to obtain the first model relationship.

[0031] To achieve the above object, on the other hand, an embodiment of the present application proposes a calcareous sand grading effect analysis system, which includes:

[0032] A first module for constructing grading parameters according to calcareous sand particle size data;

[0033] A second module for calculating shear strength data through the grading parameters;

[0034] A third module for constructing a strength index model according to the shear strength data, the grading parameters, and the relative density data;

[0035] A fourth module for constructing a target analysis model according to the strength index model and the relative breakage rate parameter;

[0036] A fifth module for performing performance index analysis through the target analysis model to obtain performance index prediction data.

[0037] To achieve the above object, on the other hand, an embodiment of the present application proposes an electronic device, which includes:

[0038] At least one processor;

[0039] At least one memory for storing at least one program;

[0040] When the at least one program is executed by the at least one processor, the at least one processor implements the above method.

[0041] To achieve the above object, on the other hand, an embodiment of the present application proposes a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the above method is implemented.

[0042] The embodiments of the present application at least include the following beneficial effects: The present application provides a method, system, electronic device and storage medium for analyzing the grading effect of calcareous sand. This solution constructs grading parameters through the particle size data of calcareous sand, and calculates shear strength data through the grading parameters. Then, the embodiments of the present invention construct a strength index model based on the shear strength data, grading parameters and relative density data, and construct a target analysis model based on the strength index model and relative breakage rate parameters, so as to perform performance index analysis through the target analysis model and obtain performance index prediction data, realizing the analysis of the grading effect of calcareous sand. It is easy to understand that the embodiments of the present invention construct grading parameters through the particle size data of calcareous sand to characterize the particle size distribution characteristics, combine the relative density data and shear strength data to construct a strength index model, and then combine the relative breakage rate parameters to construct a target analysis model, so as to be able to predict the performance index of calcareous sand, effectively improving the accuracy of the grading effect analysis of calcareous sand and providing support for the actual application analysis of calcareous sand. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 is a flowchart of the method for analyzing the grading effect of calcareous sand provided by the embodiments of the present invention;

[0044] Figure 2 is a schematic diagram of the overall process architecture of the grading effect analysis calculation provided by the embodiments of the present invention;

[0045] Figure 3 is a schematic diagram of the structure of the system for analyzing the grading effect of calcareous sand provided by the embodiments of the present invention;

[0046] Figure 4 is a schematic diagram of the hardware structure of the electronic device provided by the embodiments of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0047] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of the present application. They are only examples of devices and methods consistent with some aspects of the embodiments of the present application as detailed in the appended claims.

[0048] It is understood that the terms "first", "second", etc. used in this application may be used herein to describe various concepts, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of this application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, as used herein, the words "if", "when" can be interpreted as "when...", "when...", or "in response to determining".

[0049] The terms "at least one", "a plurality of", "each", "any one", etc. used in this application, at least one includes one, two or more than two, a plurality of includes two or more than two, each refers to each of the corresponding plurality, and any one refers to any one of the plurality.

[0050] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0051] Before elaborating on the embodiments of this application in detail, some nouns and terms involved in the embodiments of this application are first explained, and the nouns and terms involved in the embodiments of this application are applicable to the following explanations.

[0052] Calcareous sand: It is mainly composed of calcium carbonate and other insoluble carbonate substances. For example, coral sand is composed of coral or shell fragments, with different particle sizes and irregular shapes, and rich micropores.

[0053] Gradation effect: It refers to the influence of the size distribution (gradation) of calcareous sand particles on its physical and mechanical properties. Among them, gradation refers to the particle size distribution of the soil particles, that is, the proportion of particles with different particle sizes in the soil.

[0054] Due to its particle structure, calcareous sand has the characteristics of being fragile, porous and rough, and is extremely easy to break under external forces. This fragility causes a significant change in the particle size distribution of calcareous sand under stress conditions, thus having an important impact on engineering properties such as shear strength and breakage rate. For example, in reef engineering, the difference in the filling position and depth will cause differences in the particle size distribution of coral sand, which directly affects the safety and durability of the engineering structure. In related technologies, it is mainly difficult to comprehensively understand the relationship between the particle size distribution of calcareous sand and its mechanical properties, breakage characteristics and shear strength, and it is difficult to be used for the actual application analysis of calcareous sand.

[0055] In view of this, an analysis method, system, electronic device and storage medium for the grading effect of calcareous sand are provided in the embodiments of the present application. This solution constructs grading parameters through the particle size data of calcareous sand, and calculates shear strength data through the grading parameters. Then, the embodiments of the present invention construct a strength index model based on the shear strength data, grading parameters and relative density data, and construct a target analysis model based on the strength index model and relative breakage rate parameters, so as to perform performance index analysis through the target analysis model and obtain performance index prediction data, realizing the analysis of the grading effect of calcareous sand, effectively improving the accuracy of the grading effect analysis of calcareous sand, and providing support for the actual application analysis of calcareous sand.

[0056] The analysis method for the grading effect of calcareous sand provided by the embodiments of the present application relates to the technical field of calcareous sand property analysis. The analysis method for the grading effect of calcareous sand provided by the embodiments of the present application can be applied to a terminal, a server, or software running on a terminal or a server. In some embodiments, the terminal can be a smart phone, a tablet computer, a notebook computer, a desktop computer, a smart speaker, a smart watch, a vehicle-mounted terminal, etc., but is not limited thereto; the server side can be configured as an independent physical server, or can be configured as a server cluster or distributed system composed of multiple physical servers, or can be configured as a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network; the software can be an application for implementing the analysis method for the grading effect of calcareous sand, etc., but is not limited to the above forms.

[0057] This application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multi-processor systems, microprocessor-based systems, set-top boxes, programmable consumer electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. This application can also be practiced in a distributed computing environment where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0058] Figure 1 is an optional flowchart of the analysis method for the grading effect of calcareous sand provided by the embodiments of the present application. Figure 1The method in may include but is not limited to steps S110 to S150.

[0059] Step S110: Construct grading parameters based on calcareous sand particle size data.

[0060] Step S120: Calculate shear strength data through the grading parameters.

[0061] Step S130: Construct a strength index model based on the shear strength data, grading parameters, and relative density data.

[0062] Step S140: Construct a target analysis model based on the strength index model and relative breakage rate parameters.

[0063] Step S150: Conduct performance index analysis through the target analysis model to obtain performance index prediction data.

[0064] During the working process of this specific embodiment, in the embodiment of the present invention, the grading parameters are first constructed based on the particle size data of calcareous sand, so as to calculate the shear strength data through the grading parameters. Specifically, in the embodiment of the present invention, the particle size data of calcareous sand refers to the particle size information of calcareous sand, such as the maximum particle size and minimum particle size of each grading. Correspondingly, the grading parameters are parameters that quantitatively and qualitatively reflect the grading characteristics. Among them, in the embodiment of the present invention, the grading characteristics are analyzed through the particle size data of calcareous sand, so as to construct the grading parameters. In addition, in the embodiment of the present invention, the shear strength data refers to the limit ability data of calcareous sand to resist damage under the action of a shear blade, which can evaluate the low bearing capacity and stability of calcareous sand. Correspondingly, in the embodiment of the present invention, the shear strength of calcareous sand is calculated by introducing the grading parameters, and the shear strength data of calcareous sand (such as coral sand) under different grading effects is obtained. Further, in the embodiment of the present invention, a strength index model is constructed based on the shear strength data, grading parameters and relative density data, and then a target analysis model is constructed based on the strength index model and relative breakage rate parameters, so as to perform performance index analysis through the target analysis model and obtain performance index prediction data. Specifically, in the embodiment of the present invention, the relative density data refers to the ratio of the density of calcareous sand in the natural state to the theoretical maximum density. Among them, the theoretical maximum density refers to the density in the completely dense state of the substance. In addition, in the embodiment of the present invention, the relative breakage rate refers to the ratio of the current breakage to the breakage potential. Correspondingly, in the embodiment of the present invention, based on the influence of the grading level and grading state on the shear characteristics of coral sand, that is, the grading parameters and shear strength data, a strength index model that comprehensively considers the particle size distribution and relative density is constructed. Then, in the embodiment of the present invention, according to the constructed strength index model, combined with the relative breakage rate parameters, the relationship between the mechanical parameters of calcareous sand (such as shear strength, breakage rate, etc.) is analyzed, so as to construct a target analysis model. Finally, in the embodiment of the present invention, the performance index analysis of calcareous sand is carried out through the constructed target analysis model to predict the mechanical properties of calcareous sand, so as to effectively improve the accuracy of the grading effect analysis of calcareous sand and provide support for the actual application analysis of calcareous sand.

[0065] In some embodiments of the present invention, constructing the grading parameters according to the particle size data of calcareous sand includes, but is not limited to, the following steps:

[0066] Construct a calcareous sand specimen model according to the particle size data of calcareous sand through a preset particle distribution equation.

[0067] Determine the median particle size according to the calcareous sand specimen model, so as to construct the grading parameters through the median particle size.

[0068] In this specific embodiment, the embodiment of the present invention introduces grading parameters to characterize the particle size distribution characteristics of calcareous sand. Among them, in the embodiment of the present invention, a calcareous sand specimen model is constructed according to the calcareous sand data through a preset particle equation, and then the median particle size is determined according to the calcareous sand specimen model, so as to construct grading parameters through the median particle size. Specifically, the preset particle distribution equation in the embodiment of the present invention refers to a function equation used to describe the particle packing characteristics, such as the Dinger-Funk equation, the discrete element algorithm, or the Andreassen equation, etc. For example, in the embodiment of the present invention, by combining the Dinger-Funk equation with the calcareous sand particle size data, calcareous sand specimens with different gradings are calculated, and a calcareous sand specimen model is constructed, as shown in the following formula (1):

[0069]

[0070] Wherein, in the formula, U(D P ) refers to the cumulative particle percentage content, D P refers to the current particle size of the grading to be determined, D Ps refers to the minimum particle size in this grading, D PL refers to the maximum particle size in this grading, and n is the fractal dimension.

[0071] Correspondingly, the median particle size in the embodiment of the present invention refers to the particle size corresponding to 50% of the total mass of calcareous sand with a mass less than this particle size on the particle size distribution curve. Correspondingly, in the embodiment of the present invention, the particle size data corresponding to different cumulative percentage contents are determined through the calcareous sand specimen model, and then the particle size with a cumulative percentage content of 50% is determined, that is, the median particle size. Then, the embodiment of the present invention introduces a grading equation containing the median particle size, as shown in the following formula (2), to construct the grading parameter (β).

[0072]

[0073] Wherein, in the formula, d 50 is the median particle size (mm) in the grading, β is a parameter that quantitatively and qualitatively reflects the grading characteristics, that is, the grading parameter, d is the particle size, and p is the percentage content of particles passing through the sieve hole of size d.

[0074] In some embodiments of the present invention, shear strength data is calculated through grading parameters, including but not limited to the following steps:

[0075] Sort out the peak stress according to the grading parameters to obtain the peak stress data.

[0076] Calculate the shear strength data according to the peak stress data through a preset mechanical theory. Among them, the shear strength data includes cohesion data and internal friction angle data.

[0077] In this specific embodiment, the embodiment of the present invention first sorts out the peak stress according to the grading parameters to obtain the peak stress data, and then calculates the shear strength data according to the peak stress data through the preset mechanical theory. Specifically, in order to facilitate the calculation of the subsequent shear strength data, the embodiment of the present invention sorts out the peak stresses of different gradations. Accordingly, the embodiment of the present invention sorts out the stress peaks corresponding to different confining pressures (such as 100, 200, 400 kPa) and different relative densities (such as 50%, 70%, 90%) of each gradation according to the grading parameters to obtain the peak stress data. For example, the embodiment of the present invention calculates the pore water pressure u corresponding to the stress peak of coral sand p The pore water pressure u under different effective confining pressures is analyzed and sorted out with different gradations. p Data processing is performed. Accordingly, the preset mechanical theory in the embodiment of the present invention refers to the soil mechanics theory that predicts the failure behavior of calcareous sand under various stress conditions, such as the Mohr-Coulomb strength theory. Among them, the shear strength data in the embodiment of the present invention includes cohesion data and internal friction angle data. The embodiment of the present invention calculates the cohesion strength data and the internal friction angle data through the Mohr-Coulomb strength theory based on the sorted stress peak data. For example, the embodiment of the present invention calculates the shear strength of calcareous sand through the Mohr-Coulomb strength theory to obtain the shear strength data of calcareous sand under different grading effects, uses the limiting Mohr circle to calculate the shear strength parameters of calcareous sand, calculates the common tangent of the effective stress circle, and obtains the shear strength parameters of calcareous sand (cohesion data c and internal friction angle data ).

[0078] In some embodiments of the present invention, a strength index model is constructed based on shear strength data, gradation parameters and relative density data, including but not limited to the following steps:

[0079] The first model relationship is constructed based on the shear strength data, gradation parameters and relative density data.

[0080] A three-dimensional surface analysis is performed according to the first model relationship to construct a gradation model function relationship.

[0081] The coupling parameters are constructed based on the grading parameters and relative density data.

[0082] The strength index model is constructed based on the functional relationship between coupling parameters and gradation model.

[0083] In this specific embodiment, the embodiment of the present invention first constructs a first model relationship based on the shear strength data, gradation parameters, and relative density data, and then performs three-dimensional surface analysis according to the first model relationship to construct a gradation model function relationship. Specifically, the embodiment of the present invention plots the relationship curve between the shear strength data of calcareous sand, the relative density data, and the gradation parameters, and then establishes a first model relationship based on the relationship curve. Correspondingly, the embodiment of the present invention analyzes the first model relationship to obtain a three-dimensional surface of the shear strength data of calcareous sand under the combined influence of relative density and gradation parameters, thereby constructing a gradation model function relationship. Further, the embodiment of the present invention constructs a coupling parameter based on the gradation parameters and relative density data to construct a strength index model according to the coupling parameter and the gradation model function relationship. Specifically, the embodiment of the present invention constructs a coupling parameter based on the relationship between the gradation parameters, relative density data, and shear strength data to characterize the combined effect of the gradation parameters and relative density data on the soil strength, and simplifies the above three-dimensional surface into a two-dimensional plane. For example, in the embodiment of the present invention, when the gradation parameters remain unchanged, there is a proportional relationship between the shear strength data and the relative density data. Correspondingly, when the relative density data remains unchanged, the shear strength data and the gradation parameters follow a quadratic parabola relationship. Based on this, the embodiment of the present invention constructs a coupling parameter as shown in the following formula (3):

[0084] ω = β 2 + Dr 2 + β + Dr (3)

[0085] Wherein, in the formula, ω represents the coupling parameter, β represents the gradation parameter, and Dr represents the relative density data.

[0086] Correspondingly, the embodiment of the present invention constructs a new strength index model by introducing a coupling parameter, as shown in the following formula (4):

[0087]

[0088] Wherein, in the formula, K 1 、K 2 represent the coefficients under the combined action of gradation and Dr, K 3 is the factor not considered, such as the strength change caused by the energy loss due to particle breakage, etc., ω is the coupling parameter of gradation and Dr, representing their combined action.

[0089] In some embodiments of the present invention, a target analysis model is constructed according to the strength index model and the relative breakage rate parameter, including but not limited to the following steps:

[0090] A second model relationship is constructed according to the relative breakage rate parameter and the gradation parameter.

[0091] The third model relation is constructed based on the relative breakage rate parameter and the coupling parameter.

[0092] The target analysis model is constructed based on the second model relation and the third model relation.

[0093] In this specific embodiment, the embodiment of the present invention first constructs the second model relation based on the relative breakage rate parameter and the gradation parameter, and constructs the third model relation based on the relative breakage rate parameter and the coupling parameter, and then constructs the target analysis model based on the second model relation and the third model relation. Specifically, the embodiment of the present invention first constructs the relative breakage rate parameter B of calcareous sand r The data model relation with the gradation parameter β, that is, the second model relation, is shown in the following formula (5):

[0094] B r = k 1 β 2 + k 2 β - k 3 (5)

[0095] At the same time, the embodiment of the present invention constructs the mathematical model relation between the relative breakage rate parameter B of calcareous sand r and the coupling parameter ω, that is, the third model relation, as shown in the following formula (6):

[0096] B r = k 4 ω 2 + k 5 ω + k 6 (6)

[0097] Among them, in the above formulas (5) and (6), k 1 , k 2 , k 3 , k 4 , k 5 , k 6 are all coefficient parameters, β is the gradation parameter, and ω is the coupling parameter that comprehensively considers the combined influence of gradation and Dr.

[0098] Correspondingly, the embodiment of the present invention constructs the target analysis model by combining the second model relation and the third model relation, and constructs the target analysis model for analyzing the gradation effect of calcareous sand by introducing the coupling parameter that combines the gradation parameter and the relative density data, which can adapt to various gradation combinations under complex loading conditions and provides support for the calculation and prediction of the performance indexes of calcareous sand.

[0099] In some embodiments of the present invention, the performance index prediction data is obtained through performance index analysis by the target analysis model, including but not limited to the following steps:

[0100] The mechanical properties of the preset calcareous sand are predicted by the target analysis model to obtain the predicted data of performance indicators. Among them, the predicted data of performance indicators includes the calcareous sand strength data and the calcareous sand breakage rate data.

[0101] In this specific embodiment, after the target analysis model is constructed in the embodiment of the present invention, the mechanical properties of the preset calcareous sand are predicted by the target analysis model to obtain the predicted data of performance indicators. Specifically, the preset calcareous sand in the embodiment of the present invention refers to the calcareous sand that needs to be analyzed for gradation effect, such as coral sand. Correspondingly, when determining the particle size distribution curve of the preset calcareous sand in the embodiment of the present invention, the mechanical property parameters of the preset calcareous sand are predicted by the constructed target analysis model. For example, in the embodiment of the present invention, the calcareous sand strength data is predicted by the second model relational expression in the target analysis model, and the calcareous sand breakage rate data is predicted by the third model relational expression, so as to obtain the predicted data of performance indicators.

[0102] In some embodiments of the present invention, constructing the first model relational expression according to the shear strength data, gradation parameters and relative density data includes but is not limited to the following steps:

[0103] Construct a functional relationship equation between the shear strength data and the gradation parameters, so as to construct a preset gradation model according to the functional relationship equation and the relative density data.

[0104] Perform data processing on the preset gradation model and the relative density data to obtain the first model relational expression.

[0105] In this specific embodiment, in the embodiment of the present invention, first, a functional relationship equation between the shear strength data and the gradation parameters is constructed, and a preset gradation model is constructed according to the functional relationship equation and the relative density data, and then data processing is performed on the preset gradation model and the relative density data to obtain the first model relational expression. Specifically, in the embodiment of the present invention, a relationship curve between the shear strength and the gradation parameters is drawn. Among them, the shear strength data of the calcareous sand includes the cohesion data c and the internal friction angle data is a quadratic equation of one variable about the gradation parameters, and they are summarized to obtain a preset gradation model of the calcareous sand with respect to the shear strength data under different relative density data, as shown in the following formulas (7) and (8):

[0106]

[0107]

[0108] Correspondingly, in the embodiment of the present invention, the cohesion data c and the internal friction angle data under different relative density data Dr Arrange and simplify to obtain the first model relational expression as shown in the following formula (9):

[0109]

[0110] Among them, the quadratic coefficient A, A in the formula 1 , the linear coefficient B, A 2 and the constant term D, A 3 are all characteristic coefficient parameters.

[0111] Next, the embodiment of the present invention processes the above formula (9) with the relative density data Dr to obtain the cohesion data c of calcareous sand and the internal friction angle data Three-dimensional model relational expression of gradation effect, that is, the first model relational expression, as shown in the following formula (10):

[0112]

[0113] Among them, k in the formula 1 , k 3 , k 6 , k 8 represent the relationship coefficients between β and c, ; k 2 , k 4 , k 7 , k 9 is the rising relationship of the cohesion of calcareous sand with the influence of Dr; k 10 is the combined action of β and Dr, and k 5 , k 11 are constant terms, representing the influence of some factors not considered in the embodiment of the present invention on the strength of calcareous sand, such as energy loss caused by particle breakage, relative interaction relationship between particles, and cracks developed inside particles.

[0114] Correspondingly, the embodiment of the present invention performs three-dimensional surface analysis according to the first model relational expression, and constructs the gradation model function relational expression as shown in the following formula (11):

[0115]

[0116] Next, combined with specific calcareous sand gradation effect analysis of specific application examples, the solution of the embodiment of the present invention will be introduced and described in detail:

[0117] Exemplarily, refer to Figure 2 , Figure 2Schematic diagram of the overall process architecture for analyzing and calculating the grading effect provided by the embodiments of the present invention. Specifically, in the process of analyzing the grading effect of coral sand, the embodiments of the present invention first establish a model of coral sand specimens with different gradings using the Dinger-Funk equation, introduce a grading equation containing the median grain size, and propose a grading parameter β. Then, the embodiments of the present invention organize and analyze the pore water pressure corresponding to the stress peak of coral sand and β with different gradings to process the pore water pressure under different effective confining pressures, so as to calculate the shear strength data according to the Mohr-Coulomb strength theory, including cohesion data and internal friction angle data. Further, the embodiments of the present invention establish a model relationship among the grading parameter, the shear strength data, and the relative density data, analyze the three-dimensional surface of the shear strength data of coral sand under the combined influence of the relative density data and the grading parameter, and construct a grading model function relationship. Then, the embodiments of the present invention construct a coupling parameter ω according to the relationship among the grading parameter, the shear strength data, and the relative density data to characterize the combined action of the grading effect and the relative density data, simplify the three-dimensional surface into a two-dimensional plane, and propose a new strength index model. Finally, the embodiments of the present invention construct a mathematical model relationship between the relative breakage rate of coral sand and the grading parameter, and between the relative breakage rate and the coupling parameter according to the constructed strength index model, so as to construct a target analysis model, which can predict the mechanical properties of coral sand and provide support for predicting the performance indexes of coral sand.

[0118] It is easy to understand that based on the influence of the grading level and grading state on the shear characteristics of coral sand, the embodiments of the present invention construct a strength index analysis model that comprehensively considers the particle size distribution and relative density (Dr). Correspondingly, the embodiments of the present invention establish a target analysis model for analyzing the grading effect of coral sand by introducing a coupling parameter ω that combines β and Dr, so as to analyze the grading effect of coral sand. Correspondingly, the embodiments of the present invention introduce a grading parameter β to characterize the characteristics of the particle size distribution, and combine the influence of the relative density (Dr) to propose a coupling parameter ω to systematically analyze the theoretical relationship between mechanical parameters such as shear strength and breakage rate and β, ω, so as to make the analysis of the grading effect of coral sand more comprehensive and systematic. Among them, when the particle size distribution curve is known, the target analysis model can be used to predict the mechanical properties of coral sand and adapt to various grading combinations under complex loading conditions. Correspondingly, this model can provide theoretical support for the calculation and prediction of performance indexes such as the strength and breakage rate of coral sand, effectively improve the accuracy of the grading effect analysis of calcareous sand, and provide support for the practical application analysis of calcareous sand, such as providing a reference basis for the calculation of foundation bearing capacity.

[0119] Please refer to Figure 3 , the embodiments of the present application also provide a calcareous sand grading effect analysis system, which can implement the above calcareous sand grading effect analysis method. The system includes:

[0120] The first module 210 is configured to construct grading parameters according to calcareous sand particle size data.

[0121] The second module 220 is configured to calculate shear strength data through the grading parameters.

[0122] The third module 230 is configured to construct a strength index model according to the shear strength data, grading parameters, and relative density data.

[0123] The fourth module 240 is configured to construct a target analysis model according to the strength index model and relative breakage rate parameters.

[0124] The fifth module 250 is configured to perform performance index analysis through the target analysis model to obtain performance index prediction data.

[0125] It can be understood that the content in the above method embodiments is applicable to the system embodiments of the present application. The functions specifically implemented in the system embodiments of the present application are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those in the above method embodiments.

[0126] An embodiment of the present application further provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the above calcareous sand grading effect analysis method is implemented. The electronic device can be any intelligent terminal including a tablet computer, an in-vehicle computer, etc.

[0127] It can be understood that the content in the above method embodiments is applicable to the device embodiments of the present application. The functions specifically implemented in the device embodiments of the present application are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those in the above method embodiments.

[0128] Please refer to Figure 4 , Figure 4 , which schematically shows the hardware structure of an electronic device according to another embodiment. The electronic device includes:

[0129] The processor 310 can be implemented in ways such as a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is configured to execute relevant programs to implement the technical solutions provided by the embodiments of the present application;

[0130] The memory 320 can be implemented in the form of a Read Only Memory (ROM), a static storage device, a dynamic storage device, or a Random Access Memory (RAM), etc. The memory 320 can store an operating system and other application programs. When implementing the technical solutions provided in the embodiments of this specification through software or firmware, the relevant program codes are stored in the memory 320 and are called by the processor 310 to execute the calcareous sand gradation effect analysis method of the embodiments of this application;

[0131] The input / output interface 330 is used to implement information input and output;

[0132] The communication interface 340 is used to implement communication interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or through wireless means (such as mobile network, WIFI, Bluetooth, etc.);

[0133] The bus 350 transmits information between various components of the device (such as the processor 310, the memory 320, the input / output interface 330, and the communication interface 340);

[0134] Among them, the processor 310, the memory 320, the input / output interface 330, and the communication interface 340 achieve communication connections with each other inside the device through the bus 350.

[0135] The embodiments of this application also provide a computer-readable storage medium. This computer-readable storage medium stores a computer program, and when this computer program is executed by a processor, it implements the above-mentioned calcareous sand gradation effect analysis method.

[0136] It can be understood that the content in the above method embodiments is applicable to the embodiments of this storage medium. The functions specifically implemented by the embodiments of this storage medium are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those of the above method embodiments.

[0137] As a non-transitory computer-readable storage medium, the memory can be used to store non-transitory software programs and non-transitory computer-executable programs. In addition, the memory can include high-speed random access memory, and can also include non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some embodiments, the memory optionally includes a memory remotely set relative to the processor, and these remote memories can be connected to the processor through a network. Examples of the above networks include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0138] The embodiments described in the embodiments of the present application are to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation to the technical solutions provided by the embodiments of the present application. Those skilled in the art can know that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of the present application are equally applicable to similar technical problems.

[0139] Those skilled in the art can understand that the technical solutions shown in the figures do not constitute a limitation to the embodiments of the present application, and may include more or fewer steps than those shown in the figures, or combine certain steps, or different steps.

[0140] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0141] Those of ordinary skill in the art can understand that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware and their appropriate combinations.

[0142] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0143] It should be understood that in this application, "at least one (item)" means one or more, and "a plurality" means two or more. "And / or" is used to describe the association relationship of associated objects and indicates that there can be three relationships. For example, "A and / or B" can mean: only A exists, only B exists, and both A and B exist at the same time. Among them, A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects before and after. "At least one (item) of the following" or its similar expression refers to any combination of these items, including any combination of single item (item) or plural items (items). For example, at least one (item) of a, b, or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0144] In several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the above division of units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces. The indirect coupling or communication connection of devices or units can be in electrical, mechanical or other forms.

[0145] The units described above as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or they can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0146] In addition, each functional unit in various embodiments of this application can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0147] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of various embodiments of this application. The foregoing storage medium includes: various media that can store programs such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs.

[0148] The preferred embodiments of the embodiments of this application have been described above with reference to the accompanying drawings, which does not limit the scope of rights of the embodiments of this application. Any modifications, equivalent replacements, and improvements made by those skilled in the art without departing from the scope and essence of the embodiments of this application shall be within the scope of rights of the embodiments of this application.

Claims

1. A method for analyzing the grading effect of calcareous sand, characterized in that: The method comprises the following steps: Construct grading parameters based on calcareous sand particle size data; Obtain shear strength data by calculating the gradation parameters; A strength index model is constructed according to the shear strength data, the gradation parameters and the relative density data; Constructing a target analysis model according to the strength index model and the relative crushing rate parameter; The performance indicator analysis is performed through the target analysis model to obtain performance indicator prediction data.

2. The method according to claim 1, characterized in that The step of constructing grading parameters according to the calcareous sand particle size data includes: A calcareous sand sample model is constructed based on the calcareous sand particle size data by using a preset particle distribution equation; The median particle size is determined according to the calcareous sand sample model, so as to construct the grading parameter through the median particle size.

3. The method according to claim 1, characterized in that The shear strength data is obtained by calculating the gradation parameters, including: Perform peak stress sorting according to the gradation parameters to obtain peak stress data; The shear strength data is obtained by calculating the stress peak data through a preset mechanical theory; wherein the shear strength data includes cohesion data and internal friction angle data.

4. The method according to claim 1, characterized in that: The strength index model is constructed according to the shear strength data, the gradation parameters and the relative density data, including: Constructing a first model relationship according to the shear strength data, the gradation parameter and the relative density data; Perform three-dimensional surface analysis according to the first model relationship to construct a gradation model function relationship; Constructing coupling parameters according to the grading parameters and the relative density data; The strength index model is constructed based on the coupling parameter and the grading model functional relationship.

5. The method according to claim 4, characterized in that The target analysis model is constructed according to the strength index model and the relative crushing rate parameter, including: A second model relationship is constructed according to the relative crushing rate parameter and the grading parameter; A third model relationship is constructed according to the relative fragmentation rate parameter and the coupling parameter; The target analysis model is constructed based on the second model relationship formula and the third model relationship formula.

6. The method according to claim 5, characterized in that The performing of performance indicator analysis through the target analysis model to obtain performance indicator prediction data includes: The mechanical properties of the preset calcareous sand are predicted by the target analysis model to obtain the performance index prediction data; wherein the performance index prediction data includes calcareous sand strength data and calcareous sand crushing rate data.

7. The method according to claim 4, characterized in that The constructing of a first model relationship according to the shear strength data, the gradation parameter and the relative density data comprises: Constructing a functional relationship equation between the shear strength data and the gradation parameter, so as to construct a preset gradation model according to the functional relationship equation and the relative density data; The preset gradation model and the relative density data are processed to obtain the first model relationship.

8. A calcareous sand grading effect analysis system, characterized in that: The system comprises: The first module is used to construct grading parameters based on the calcareous sand particle size data; The second module is used to calculate the shear strength data through the gradation parameters; The third module is used to construct a strength index model according to the shear strength data, the gradation parameters and the relative density data; The fourth module is used to construct a target analysis model according to the strength index model and the relative crushing rate parameter; The fifth module is used to perform performance indicator analysis through the target analysis model to obtain performance indicator prediction data.

9. An electronic device, characterized in that: include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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