Pile foundation structure optimization method and device based on grey correlation analysis method

Abstract

The invention provides a pile foundation structure optimization method and device based on a grey correlation analysis method, provides a method for determining the optimal structural form of a pile foundation, and effectively overcomes the design defects existing in a previous pile foundation structure design method. The method comprises the steps that pile foundation design is conducted on a to-be-driven area according to obtained geological profile data and soil characteristic data of the to-be-driven area, and multiple pile foundation structure combinations are obtained; corresponding pile foundation models are constructed on the basis of the multiple pile foundation structure combinations, the pile foundation models are simulated, and corresponding evaluation data are obtained; performing correlation degree calculation on the plurality of influence factors of the evaluation data through a grey correlation analysis method to obtain correlation degrees corresponding to the plurality of influence factors, and screening out influence factors meeting preset conditions based on the correlation degrees; and a target pile foundation combination of the pile foundations is determined based on the influence factors meeting the preset conditions, and the pile foundation structure of the to-be-driven area is optimized through the target pile foundation combination.

Description

Technical Field

[0001] The present application relates to the field of building technology, and in particular to a method and device for optimizing a pile foundation structure based on a grey correlation analysis method. Background Art

[0002] A nine-story tower starts with a pile of earth. Every time a new landmark building is built, new requirements are put forward for the development of foundation engineering. With the rapid development of infrastructure construction in my country, the scale of engineering construction is getting larger and larger, and the construction difficulty is getting greater and greater. In the past infrastructure construction process, bored piles were widely used in engineering due to their high bearing capacity, low steel consumption, low noise and no vibration during construction. In recent years, new pile foundation technology has emerged and has been continuously developed in the direction of large diameter, extra-long piles and special-shaped piles.

[0003] In terms of the structural form of pile foundation, for ordinary straight-hole piles, determining the length (pile length) and diameter (pile diameter) of the pile is a key step in pile foundation design. These two parameters are directly related to the bearing capacity, stability and economic efficiency of the pile. For rock-embedded piles, the embedded rock layer and rock embedding depth also need to be considered. For special-shaped piles, on the basis of determining the pile length and pile diameter, the shape of the pile diameter or the influence of other components on the bearing capacity of the pile foundation also needs to be considered.

[0004] In the previous pile foundation structure design method, the design steps are as follows: At the beginning, the designer estimates the pile length and diameter based on preliminary load and geological data combined with personal experience. Then, through trial calculations and iterations, the pile length and diameter are continuously adjusted until all design requirements are met. The final design needs to be calculated and checked in detail to ensure that the structure is safe and meets the specifications.

[0005] This design method has the following problems:

[0006] 1. When initially determining the pile length and pile foundation, one relies too much on personal experience;

[0007] 2. The trial calculation and iteration process are cumbersome and inefficient. Taking ordinary straight-hole piles as an example, 5 types of pile lengths and 5 types of pile diameters are initially confirmed, that is, there are 25 combinations. If the pile foundation is a rock-embedded pile or a special-shaped column, the factors that need to be considered on this basis will be further increased, and the calculation workload will increase exponentially.

[0008] 3. When there are many factors to be considered during the design, the correlation coefficients of the factors become complicated and it is not easy to evaluate the comparative series, so it is not easy to determine the influence of various factors on the bearing characteristics of the pile. In order to meet the requirements of bearing capacity and settlement control, the pile diameter and pile length are usually simply increased, which not only increases the difficulty of construction, but also increases the construction cost. At the same time, due to the difficulty of long pile construction and low material utilization, resources are wasted. Summary of the invention

[0009] In view of this, the purpose of the present application is to provide a pile foundation structure optimization method and device based on the grey correlation analysis method. The pile foundation structure optimization method and device based on the grey correlation analysis method provide a method for determining the optimal structural form of the pile foundation, effectively solving the design defects existing in the previous pile foundation structure design methods.

[0010] In a first aspect, an embodiment of the present application provides a pile foundation structure optimization method based on a grey correlation analysis method, the method comprising:

[0011] Obtaining geological profile data and soil property data of the area to be piled, designing pile foundations for the area to be piled based on the geological profile data and soil property data of the area to be piled, and obtaining multiple pile foundation structure combinations for the area to be piled in multiple dimensions; the dimensions include diameter, length, and special-shaped piles;

[0012] Based on the plurality of pile foundation structure combinations, corresponding pile foundation models are respectively constructed, and the pile foundation models corresponding to the plurality of pile foundation structure combinations are respectively simulated to obtain evaluation data corresponding to the plurality of pile foundation combinations; the pile foundation model is a finite element model;

[0013] Calculating the correlation degree of the multiple influencing factors of the evaluation data by using the grey correlation analysis method to obtain the correlation degrees corresponding to the multiple influencing factors, so as to screen out the influencing factors that meet the preset conditions based on the correlation degrees;

[0014] A target pile foundation combination of the pile foundation is determined based on the influencing factors that meet the preset conditions, so as to optimize the pile foundation structure of the area to be piled through the target pile foundation combination.

[0015] In combination with the first aspect, the embodiment of the present application provides a first possible implementation of the first aspect, wherein corresponding pile foundation models are constructed based on the multiple pile foundation structure combinations, and the pile foundation models corresponding to the multiple pile foundation structure combinations are simulated respectively to obtain evaluation data corresponding to the multiple pile foundation combinations, including:

[0016] Construct finite element pile foundation models corresponding to various pile foundation structure combinations based on geological types and multiple model parameters;

[0017] The pile foundation models are simulated respectively according to a preset simulation method to calculate evaluation data generated by the pile foundation models corresponding to the various pile foundation structure combinations.

[0018] In combination with the first aspect, the embodiment of the present application provides a second possible implementation of the first aspect, wherein the pile foundation models corresponding to the plurality of pile foundation structure combinations are constructed based on the plurality of model parameters and the types of geology, including:

[0019] Acquire multiple contact surfaces of different types of geology between corresponding pile foundations in multiple pile foundation combinations and areas to be piled;

[0020] Based on a plurality of model parameters, pile foundation models corresponding to a plurality of contact surfaces between the pile foundation and areas to be piled of different geological types are respectively constructed, and parameter values ​​corresponding to the model parameters are determined.

[0021] In combination with the first aspect, the embodiment of the present application provides a third possible implementation of the first aspect, wherein the grey correlation analysis method is used to calculate the correlation degree of multiple influencing factors of the evaluation data to obtain the correlation degrees corresponding to the multiple influencing factors, including:

[0022] The grey correlation analysis method calculates the evaluation data corresponding to multiple influencing factors of different values ​​and the reference series to obtain the grey correlation coefficients corresponding to the multiple influencing factors respectively;

[0023] The correlation degrees corresponding to multiple influencing factors are obtained by conversion based on the grey correlation coefficient.

[0024] In combination with the first aspect, the embodiment of the present application provides a fourth possible implementation of the first aspect, wherein the grey correlation analysis method calculates the evaluation data corresponding to multiple influencing factors of different values ​​and the reference series to obtain the grey correlation coefficients corresponding to the multiple influencing factors, including:

[0025] By using reference series, a comparison matrix composed of evaluation data corresponding to multiple influencing factors of different values ​​is dimensionally processed to obtain a dimensionless matrix;

[0026] The dimensionless matrix is ​​input into a preset grey relational network, so that the grey relational network calculates the dimensionless matrix to obtain grey relational coefficients corresponding to a plurality of influencing factors.

[0027] In combination with the first aspect, the embodiment of the present application provides a fifth possible implementation of the first aspect, wherein the influencing factors meeting the preset conditions are screened out based on the correlation, including:

[0028] Determining whether the multiple influencing factors meet preset conditions, wherein the preset conditions include that the correlation of the influencing factors can be adjusted;

[0029] If so, the influencing factors that meet the preset conditions are retained and the remaining influencing factors are eliminated.

[0030] In combination with the first aspect, the embodiment of the present application provides a sixth possible implementation of the first aspect, wherein determining a target pile foundation combination of the pile foundation based on the influencing factors that meet the preset conditions, so as to optimize the pile foundation structure based on the target pile foundation combination, includes:

[0031] Recalculate the correlation degree of the screened influencing factors based on the grey correlation analysis method;

[0032] By sorting the correlation of the screened influencing factors, the target pile foundation combination is determined based on the sorted influencing factors.

[0033] In a second aspect, an embodiment of the present application provides a pile foundation structure optimization device based on a grey correlation analysis method, the device comprising:

[0034] A design module is used to obtain geological profile data and soil property data of the area to be piled, and to design the pile foundation of the area to be piled based on the geological profile data and soil property data of the area to be piled, so as to obtain a plurality of pile foundation structure combinations for the area to be piled in multiple dimensions; the dimensions include diameter, length, and special-shaped piles;

[0035] A construction module, for constructing corresponding pile foundation models based on the plurality of pile foundation structure combinations, and simulating the pile foundation models corresponding to the plurality of pile foundation structure combinations, to obtain evaluation data corresponding to the plurality of pile foundation combinations; the pile foundation model is a finite element model;

[0036] A calculation module, used to calculate the correlation degree of multiple influencing factors of the evaluation data by using a grey correlation analysis method, to obtain the correlation degrees corresponding to the multiple influencing factors, so as to screen out the influencing factors that meet the preset conditions based on the correlation degrees;

[0037] The optimization module is used to determine a target pile foundation combination of the pile foundation based on the influencing factors that meet the preset conditions, so as to optimize the pile foundation structure of the area to be piled through the target pile foundation combination.

[0038] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and when the machine-readable instructions are executed by the processor, any step of a pile foundation structure optimization method based on grey correlation analysis is performed.

[0039] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the computer program executes any one of the steps of a pile foundation structure optimization method based on grey correlation analysis.

[0040] The embodiment of the present application provides a method for optimizing pile foundation structure based on grey correlation analysis method, which first obtains geological profile data and soil property data of the area to be piled, performs pile foundation design on the area to be piled based on the geological profile data and soil property data of the area to be piled, and obtains a plurality of pile foundation structure combinations for the area to be piled in multiple dimensions; the dimensions include diameter, length, and special-shaped piles; secondly, corresponding pile foundation models are respectively constructed based on the various pile foundation structure combinations, and the pile foundation models corresponding to the various pile foundation structure combinations are respectively simulated to obtain evaluation data corresponding to the various pile foundation combinations; the pile foundation model is a finite element model; and then the evaluation data are respectively simulated by grey correlation analysis method. The correlation degree of multiple influencing factors of the price data is calculated to obtain the correlation degrees corresponding to the multiple influencing factors, so as to screen out the influencing factors that meet the preset conditions based on the correlation degrees; finally, the target pile foundation combination of the pile foundation is determined based on the influencing factors that meet the preset conditions, so as to optimize the pile foundation structure of the area to be piled through the target pile foundation combination, thereby avoiding the existing pile foundation structure design method that relies too much on personal experience, trial calculation and iterative process when designing the pile foundation, which is cumbersome, inefficient, increases the difficulty of construction, increases the construction cost and wastes resources, thereby ensuring the accuracy of the pile foundation design, improving the design efficiency, reducing the difficulty of construction and reducing the construction cost, and avoiding the waste of resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0042] Figure 1 A schematic flow chart of a first method for optimizing pile foundation structure based on grey correlation analysis method provided in an embodiment of the present application is shown;

[0043] Figure 2 The structural schematic diagram of the DX rock-embedded pile provided in the embodiment of the present application is shown;

[0044] Figure 3 The constitutive model diagram of the DX rock-embedded pile provided in the embodiment of the present application is shown;

[0045] Figure 4 A schematic diagram of a contact surface provided in an embodiment of the present application is shown;

[0046] Figure 5 A schematic diagram showing the minimum size of the contact surface in the normal direction provided by an embodiment of the present application is shown;

[0047] Figure 6A schematic structural diagram of a first pile foundation structure optimization device based on grey correlation analysis method provided in an embodiment of the present application is shown;

[0048] Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0049] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the drawings in the present application only serve the purpose of explanation and description and are not used to limit the scope of protection of the present application. In addition, it should be understood that the schematic drawings are not drawn in real proportion. The flowchart used in this application shows the operations implemented according to some embodiments of the present application. It should be understood that the operations of the flowchart can be implemented out of sequence, and the steps without logical context can be reversed in order or implemented simultaneously. In addition, those skilled in the art can add one or more other operations to the flowchart under the guidance of the content of the present application, or remove one or more operations from the flowchart.

[0050] In addition, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0051] It should be noted that the term "comprising" will be used in the embodiments of the present application to indicate the existence of the features declared thereafter, but does not exclude the addition of other features.

[0052] The following problems exist in the previous pile foundation structure design methods: when initially determining the pile length and pile foundation, personal experience is overly relied upon; the trial calculation and iteration process is cumbersome and inefficient. Taking ordinary straight-hole piles as an example, 5 types of pile lengths and 5 types of pile diameters are initially determined, that is, there are 25 combinations with each other; if the pile foundation is a rock-embedded pile or a special-shaped column, the factors that need to be considered on this basis are further increased, and the calculation workload increases exponentially; when there are many factors to be considered during the design, the correlation coefficients of the factors become complicated, and it is not easy to evaluate and compare the series, so it is not easy to determine the degree of influence of each factor on the pile bearing characteristics; in order to meet the requirements of bearing capacity and settlement control, the pile diameter and pile length are usually simply increased, which not only increases the difficulty of construction, but also increases the construction cost; at the same time, due to the difficulty of long pile construction and low material utilization, resources are wasted.

[0053] Based on this, the embodiments of the present application provide a pile foundation structure optimization method and device based on grey correlation analysis, which will be described below through embodiments.

[0054] Example 1

[0055] To facilitate understanding of this embodiment, firstly, a pile foundation structure optimization method based on grey correlation analysis method disclosed in the embodiment of this application is introduced in detail. Figure 1 The flowchart of a pile foundation structure optimization method based on grey correlation analysis is shown in FIG. The present application provides a pile foundation structure optimization method based on grey correlation analysis, and the method comprises:

[0056] S101, obtaining geological profile data and soil property data of the area to be piled, performing pile foundation design on the area to be piled based on the geological profile data and soil property data of the area to be piled, and obtaining multiple pile foundation structure combinations for the area to be piled in multiple dimensions; the dimensions include diameter, length, and special-shaped piles;

[0057] S102, constructing corresponding pile foundation models based on the multiple pile foundation structure combinations, and simulating the pile foundation models corresponding to the multiple pile foundation structure combinations to obtain evaluation data corresponding to the multiple pile foundation combinations; the pile foundation model is a finite element model;

[0058] S103, calculating the correlation degree of multiple influencing factors of the evaluation data by using a grey correlation analysis method to obtain the correlation degrees corresponding to the multiple influencing factors, and screening out the influencing factors that meet the preset conditions based on the correlation degrees;

[0059] S104: determining a target pile foundation combination of the pile foundation based on the influencing factors meeting the preset conditions, so as to optimize the pile foundation structure of the area to be piled by using the target pile foundation combination.

[0060] In step S101, geological exploration is performed on the area to be piled based on various methods to obtain a geological exploration report, which includes a geological profile map, geological profile data and soil property data of the area to be piled. For example, for geological profile data, it can be the official website of an official geological survey agency, the official website of an academic research institution, and professional databases and platforms, or GIS software and tools. For soil property data, it can be the official website of a soil science data center, an agricultural and environmental protection department, and professional databases and platforms, or it can be field sampling and analysis, that is, soil is collected through professional sampling tools and equipment, and then sent to a laboratory for chemical, physical and biological property analysis, or remote sensing technology; the geological profile data and soil property data of the area to be piled are used to provide basic data for the design of the pile foundation, so as to design the pile foundation for the area to be piled, and obtain a variety of pile foundation structure combinations for the area to be piled in multiple dimensions, the dimensions including diameter, length, and special-shaped piles, that is, the various pile foundation structure combinations are combined and designed in three dimensions of the pile foundation diameter, length, and special-shaped piles.

[0061] This application uses the design of DX rock-embedded piles as an example to illustrate this method. DX rock-embedded piles are a special-shaped multi-bearing plate pile foundation form developed in recent years. Its bearing plate is placed in a strongly weathered rock layer, and the pile end is placed in a strongly weathered rock or medium weathered rock layer. It has the advantages of high bearing capacity, less settlement, short pile length, low energy consumption, and environmental protection. In some strata with shallow cover thickness and deep weathered rock layer thickness, DX rock-embedded piles are used to replace long straight-hole rock-embedded piles. While meeting the requirements of bearing capacity and settlement, the rock embedding depth and construction difficulty can be significantly reduced. After drilling, a special DX rotary excavation and expansion device is used in the hole. The excavation and expansion of the extrusion and expansion arm of the device is controlled by a hydraulic system. After the bearing capacity requirements and stratum conditions are met, a truncated cone-shaped bearing plate cavity with upper and lower mirror images is excavated and expanded at different positions around the pile, and a steel cage is placed and poured with concrete to form a pile type that is jointly supported by the pile body, the bearing plate and the pile end. Figure 2 The figure shows the structural diagram of DX rock-embedded piles. Due to the existence of the bearing plate, its bearing characteristics become relatively complex. Therefore, when designing DX rock-embedded piles, in addition to the pile length and pile diameter that need to be considered for straight-hole piles, it is also affected by factors such as rock mass characteristics, pile-rock interface, rock-embedded depth, and plate-diameter ratio.

[0062] In step S102, FLAC 3D 5.00 numerical simulation software is used to construct corresponding finite element pile foundation models for the multiple pile foundation structure combinations, that is, each of the multiple pile foundation structure combinations is constructed to obtain a finite element pile foundation model corresponding to each pile foundation structure combination, that is, the pile foundation model is a finite element model, and the pile foundation models corresponding to the multiple pile foundation structure combinations are simulated by FLAC 3D 5.00 numerical simulation software according to a preset simulation method to obtain evaluation data corresponding to the multiple pile foundation combinations, the evaluation data including ultimate bearing capacity and maximum displacement of pile top. In the present application, the ultimate bearing capacity is used as the main evaluation data to evaluate the multiple pile foundation structure combinations corresponding to the finite element pile foundation model, so as to obtain the bearing effect of the pile foundation of the multiple pile foundation structure combinations.

[0063] During the implementation of step S102, there is an implementation method in which corresponding pile foundation models are constructed based on the plurality of pile foundation structure combinations, and the pile foundation models corresponding to the plurality of pile foundation structure combinations are simulated respectively to obtain evaluation data corresponding to the plurality of pile foundation combinations, including:

[0064] S1021. Constructing pile foundation models corresponding to various pile foundation structure combinations based on the geological type and multiple model parameters;

[0065] S1022, simulating the pile foundation models respectively according to a preset simulation method to calculate evaluation data generated by the pile foundation models corresponding to the plurality of pile foundation structure combinations.

[0066] In steps S1021-S1022, the FLAC 3D 5.00 numerical simulation software obtains the type of geology of the area to be piled based on the acquired geological profile data and soil property data, including silty clay, silty sand, fully weathered siltstone, and strongly weathered siltstone, and then establishes pile foundation models corresponding to various pile foundation structure combinations based on the contact part between the pile foundation and the geology of the area to be piled and the pile foundation and multiple model parameters. When constructing the pile foundation models corresponding to various pile foundation structure combinations, it is necessary to construct them based on multiple parameters, and the multiple parameters include: shear modulus G, bulk modulus K, cohesion C, internal friction angle Tensile strength t , dilatancy angle ψ, bulk modulus K, and shear modulus G are not directly given in general geological survey reports. They need to be converted using elastic modulus E and Poisson's ratio ν through formulas (1)-(2). Formulas (1)-(2) are:

[0067]

[0068] The cohesion C and internal friction angle Tensile strengtht The values ​​of the shear dilatancy angle ψ are obtained from the geological exploration report, as shown in Table 1.

[0069] Table 1 Model parameter values

[0070]

[0071] After the pile foundation models corresponding to the various pile foundation structure combinations are constructed, for the convenience of simulation, the constructed multiple pile foundation models are divided into grids, and simulation is performed according to a preset simulation method. For example, the preset simulation method is to apply gravity after the grid division is completed, calculate the ground stress balance, and after the ground stress is balanced, the displacement of the rock and soil body is reset to zero, and then apply normal stress to the pile top, combined with the upper load conditions. The upper load conditions are determined according to the building type and building use requirements of the upper part of the pile foundation. For example, if the building type is a bridge, it is necessary to consider the bridge diameter, traffic volume, etc. Here, the total load is set to 15000kN, and the loading is performed in 10 levels to obtain the ultimate bearing capacity, and the ultimate bearing capacity is used to perform bearing capacity analysis on the various pile foundation structure combinations.

[0072] In the specific implementation process of step S1021, there is an implementation method in which the pile foundation models corresponding to the plurality of pile foundation structure combinations are constructed based on the plurality of model parameters and the types of geology, including:

[0073] S10211, obtaining a plurality of contact surfaces between pile foundations corresponding to the plurality of pile foundation combinations and different types of geological contacts between the areas to be piled;

[0074] S10212. Constructing pile foundation models corresponding to a plurality of contact surfaces between the pile foundation and areas to be piled of different geological types based on a plurality of model parameters, and determining parameter values ​​corresponding to the model parameters.

[0075] In steps S10211-S10212, multiple contact surfaces between the pile foundations corresponding to the multiple pile foundation combinations and the different types of geological conditions in the area to be piled are obtained, that is, the pile body of the pile foundation has multiple different contact surfaces with different types of geological conditions. The contact surface is set in the FLAC 3D 5.00 numerical simulation software. The contact surface of a single pile is as follows: Figure 4 As shown in FIG. 1 , the slip and closure of the pile body and the rock and soil body on the contact surface under load can be simulated in numerical analysis. The pile body is taken as an example to build a pile foundation model. The constitutive model of the pile foundation is represented by the constitutive model of the pile body concrete. The pile body concrete adopts an elastic model, such as Figure 3 The figure shows the DX rock-embedded pile model. The contact surface adopts the Mohr-Coulomb model (hereinafter referred to as MC), which has simple and clear mechanical parameters and is easy to obtain. The main parameters characterizing the contact surface are the tangential stiffness k s , normal stiffness k n, cohesion, expansion angle, friction angle, etc., normal stiffness k n , tangential stiffness k s When the value is unclear, it can be determined according to formula (3):

[0076]

[0077] In the formula, K, G are the same as before, ΔZ min is the size of the normal connection area of ​​the contact surface, which is related to the meshing and is expressed in terms of tangential stiffness k s , normal stiffness k n , cohesion, expansion angle, and friction angle are used as multiple model parameters for constructing pile foundation models corresponding to multiple contact surfaces, such as Figure 5 The figure shows the minimum dimension diagram in the normal direction of the contact surface. The constitutive model and parameter values ​​adopted by the DX rock-embedded pile are shown in Table 2.

[0078] Table 2 Constitutive model and parameter values ​​used for DX rock-embedded piles

[0079]

[0080] In step S103, the influencing factors of the evaluation data are determined, that is, the influencing factors can have a greater impact on the value of the evaluation data. Since the evaluation data of this application takes the ultimate bearing capacity as an example, the influencing factors of the ultimate bearing capacity include the aspect ratio (l / d), the plate diameter ratio (D / d), the pile rock elastic modulus ratio (E r / E p ), rock mass (γ), pile diameter (d), then the pile diameter d = 1m, pile length 10m (length-diameter ratio l / d = 10), disk diameter ratio (D / d) = 2.5, pile-rock elastic modulus ratio (Er / Ep) = 1, rock mass (γ) = 20, respectively, with the above indicators as variables, the control variable method is used to change the research object, the finite element model is established, and the ultimate bearing capacity of each group is obtained, as shown in Table 3, the grey correlation analysis method is used to calculate the correlation of multiple influencing factors of the evaluation data, and the correlation corresponding to the multiple influencing factors is obtained. The correlation represents the influence of the influencing factors on the ultimate bearing capacity, so as to screen out the influencing factors that meet the preset conditions based on the correlation, and to judge a variety of pile foundation structure combinations based on the influencing factors that meet the preset conditions.

[0081] Table 3 Ultimate bearing capacity data under different influencing factors

[0082]

[0083] In the specific implementation process of step S103, there is an embodiment in which: the correlation degree calculation of the multiple influencing factors of the evaluation data by the grey correlation analysis method to obtain the correlation degrees corresponding to the multiple influencing factors includes:

[0084] S10311, the grey correlation analysis method is used to calculate the evaluation data corresponding to the multiple influencing factors of different values ​​and the reference series to obtain the grey correlation coefficients corresponding to the multiple influencing factors respectively;

[0085] S10312. Calculate the correlation degrees corresponding to the multiple influencing factors based on the grey correlation coefficient.

[0086] In steps S10311-S10312, the reference sequence is an ideal comparison standard. The optimal value (or the worst value) of each indicator can be used to form a reference data sequence, and other reference values ​​can also be selected according to the evaluation purpose. This application selects the optimal value as the reference sequence, and the reference sequence is shown in formula (4):

[0087] (X 0 ) = (10500 11975.6 14201 17290 18650)(4);

[0088] The evaluation data corresponding to multiple influencing factors with different values, i.e., the ultimate bearing capacity, are combined into a comparison matrix, as shown in formula (5):

[0089]

[0090] The grey correlation coefficient is obtained by calculating the comparison matrix composed of the reference series and the evaluation data corresponding to multiple influencing factors with different values. The obtained multiple grey correlation coefficients are output to the correlation degree calculation model represented by formula (6) for conversion to obtain the correlation degrees corresponding to the multiple influencing factors. Formula (6) is expressed as follows:

[0091]

[0092] Among them, γ i is the correlation between the ith influencing factor and the reference sequence, ξ oi (k) is the grey correlation coefficient of the comparison sequence Xi at point k, and the correlation degree of multiple influencing factors of the ultimate bearing capacity is expressed by formula (7):

[0093] (γ 1 ,γ 2 ,γ 3 ,γ 4 ,γ 5)=(0.656173 0.819099 0.985492 0.599311 0.726483) (7).

[0094] In the specific implementation process of step S10311, there is an embodiment in which the grey correlation analysis method calculates the evaluation data corresponding to the multiple influencing factors of different values ​​and the reference series to obtain the grey correlation coefficients corresponding to the multiple influencing factors, including:

[0095] S103111. Performing dimensionless processing on a comparison matrix composed of evaluation data corresponding to multiple influencing factors of different values ​​by using a reference sequence to obtain a dimensionless matrix;

[0096] S103112. Input the dimensionless matrix into a preset grey relational network, so that the grey relational network calculates the dimensionless matrix to obtain grey relational coefficients corresponding to a plurality of influencing factors.

[0097] In steps S103111-S103112, the reference sequence (4) and the comparison matrix (5) composed of the evaluation data corresponding to the multiple influencing factors are dimensionally non-dimensionalized. The dimensionally non-dimensionalized data sequence forms the following dimensionless matrix, which is expressed by formula (8):

[0098]

[0099] The dimensionless matrix represented by formula (8) is input into the preset grey relational network, and the dimensionless matrix is ​​calculated by the grey relational network to obtain the grey relational coefficients corresponding to the multiple influencing factors. The formula (9) is expressed as follows:

[0100]

[0101] Where ρ is the resolution coefficient, ρ>0, generally taken as 0.5; Δ min Is the comparison matrix Xi and the reference sequence X 0 The minimum difference in the absolute value of the spreads of each point on the max Is the comparison matrix Xi and the reference sequence X 0 The maximum difference in the absolute value of the difference between the points on the oi (k) represents the comparison matrix X i With reference series X 0 The absolute value of the difference at each point on the curve.

[0102] In the specific implementation process of step S103, there is also an embodiment of: screening out influencing factors that meet the preset conditions based on the correlation, including:

[0103] S10321, determining whether the multiple influencing factors meet preset conditions, wherein the preset conditions include that the correlation of the influencing factors can be adjusted;

[0104] S10322. If it is met, the influencing factors that meet the preset conditions are retained and the remaining influencing factors are eliminated.

[0105] In steps S10321-S10322, the influencing factors of the ultimate bearing capacity such as aspect ratio, plate diameter ratio, pile-rock elastic modulus ratio, rock mass, pile diameter, and the corresponding correlation are represented by Table 4. From Table 4, it can be seen that the order of the correlation of the relevant influencing factors affecting the DX rock-embedded pile on the bearing capacity is: pile-rock elastic modulus ratio>plate diameter ratio>pile diameter>aspect ratio>rock mass, and the rock mass has a smaller influence on the bearing capacity. Generally, the formation conditions cannot be changed, and the correlation of the rock mass cannot be changed. The pile foundation is a reinforced concrete structure with a constant elastic modulus, that is, the correlation of the pile-rock elastic modulus ratio is not easy to change. Therefore, the rock mass and the pile-rock elastic modulus ratio do not meet the preset conditions. The preset conditions include that the influencing factors can be adjusted, so the rock mass and the pile-rock elastic modulus ratio are eliminated, and only the aspect ratio, plate diameter ratio, and pile diameter are retained. The optimal pile foundation optimization combination is determined by the aspect ratio, plate diameter ratio, and pile diameter to achieve the best design of the pile foundation. The following is Table 4:

[0106] Table 4 Influencing factors and corresponding correlation

[0107]

[0108] In step S104, a target pile foundation combination of the pile foundation is determined based on the influencing factors that meet the preset conditions, namely, the aspect ratio, the pile diameter ratio, and the pile diameter. The target pile foundation combination is the optimal pile foundation combination. The pile foundation structure of the area to be piled is optimized through the target pile foundation combination, so as to reduce the construction difficulty, reduce the construction cost, and avoid the waste of resources. The pile foundation is constructed with the target pile foundation combination, and the safety and accuracy of the designed pile foundation are also guaranteed.

[0109] In the specific implementation process of step S104, there is an embodiment in which: determining a target pile foundation combination of pile foundations based on the influencing factors that meet the preset conditions, so as to optimize the pile foundation structure based on the target pile foundation combination, includes:

[0110] S1041, recalculating the correlation degree of the screened influencing factors based on the grey correlation analysis method;

[0111] S1042. Sorting the correlations of the screened influencing factors, and determining a target pile foundation combination based on the sorted influencing factors.

[0112] In steps S1041-S1042, the correlation of the selected influencing factors is calculated again based on the grey correlation analysis method, that is, the shear modulus G, bulk modulus K, cohesion C, internal friction angle of the geological area to be piled are fixed. Tensile strength t , the parameters of the shear dilatancy angle ψ, only need to calculate the correlation of the three influencing factors of aspect ratio, plate diameter ratio and pile diameter according to the above method and the first four sets of ultimate bearing capacity data, and the correlation of the aspect ratio, plate diameter ratio and pile diameter is: (γ' 1 ,γ' 2 ,γ' 5 )=(0.720678 0.851931 0.739449), sorting the correlations of the three influencing factors, it can be seen that the plate diameter ratio is most beneficial to the bearing capacity improvement, followed by the pile diameter and the length-diameter ratio. Therefore, when the construction conditions permit, it is most beneficial to set the largest possible bearing plate for DX rock-embedded piles. For this project, in order to consider the construction cost, if the plate diameter ratio is the largest, the length of the pile is controlled, and the pile diameter d=1.5m, the pile length 10m (length-diameter ratio l / d=10), and the plate diameter ratio (D / d)=3 are set as the target pile foundation combination. Then, producing the pile foundation with the target pile foundation combination is more in line with the construction requirements.

[0113] Example 2

[0114] The present application also provides a pile foundation structure optimization device based on the grey correlation analysis method, such as Figure 6 The block diagram of a pile foundation structure optimization device based on grey correlation analysis method is shown. The function implemented by the pile foundation structure optimization device based on grey correlation analysis method corresponds to the steps of executing a pile foundation structure optimization method based on grey correlation analysis method on the terminal device. The device can be understood as a component of a server including a processor, and the device includes: A pile foundation structure optimization device based on grey correlation analysis method, the device includes:

[0115] The design module 601 is used to obtain geological profile data and soil property data of the area to be piled, and to design the pile foundation of the area to be piled based on the geological profile data and soil property data of the area to be piled, so as to obtain a plurality of pile foundation structure combinations for the area to be piled in multiple dimensions; the dimensions include diameter, length, and special-shaped piles;

[0116] A construction module 602 is used to construct corresponding pile foundation models based on the plurality of pile foundation structure combinations, and simulate the pile foundation models corresponding to the plurality of pile foundation structure combinations to obtain evaluation data corresponding to the plurality of pile foundation combinations;

[0117] The calculation module 603 is used to calculate the correlation degree of the multiple influencing factors of the evaluation data by using the grey correlation analysis method to obtain the correlation degrees corresponding to the multiple influencing factors, so as to screen out the influencing factors that meet the preset conditions based on the correlation degrees;

[0118] The optimization module 604 is used to determine a target pile foundation combination of the pile foundation based on the influencing factors that meet the preset conditions, so as to optimize the pile foundation structure of the area to be piled by using the target pile foundation combination.

[0119] In a feasible implementation, the building module includes:

[0120] Construct finite element pile foundation models corresponding to various pile foundation structure combinations based on geological types and multiple model parameters;

[0121] The pile foundation models are simulated respectively according to a preset simulation method to calculate evaluation data generated by the pile foundation models corresponding to the various pile foundation structure combinations.

[0122] In a feasible implementation manner, the building module further includes:

[0123] Acquire multiple contact surfaces of different types of geology between corresponding pile foundations in multiple pile foundation combinations and areas to be piled;

[0124] Based on a plurality of model parameters, pile foundation models corresponding to a plurality of contact surfaces between the pile foundation and areas to be piled of different geological types are respectively constructed, and parameter values ​​corresponding to the model parameters are determined.

[0125] In a feasible implementation manner, the computing module includes:

[0126] The grey correlation analysis method calculates the evaluation data corresponding to multiple influencing factors of different values ​​and the reference series to obtain the grey correlation coefficients corresponding to the multiple influencing factors respectively;

[0127] The correlation degrees corresponding to multiple influencing factors are obtained by conversion based on the grey correlation coefficient.

[0128] In a feasible implementation manner, the calculation module further includes:

[0129] By using reference series, a comparison matrix composed of evaluation data corresponding to multiple influencing factors of different values ​​is dimensionally processed to obtain a dimensionless matrix;

[0130] The dimensionless matrix is ​​input into a preset grey relational network, so that the grey relational network calculates the dimensionless matrix to obtain grey relational coefficients corresponding to a plurality of influencing factors.

[0131] In a feasible implementation manner, the calculation module further includes:

[0132] Determining whether the multiple influencing factors meet preset conditions, wherein the preset conditions include that the correlation of the influencing factors can be adjusted;

[0133] If so, the influencing factors that meet the preset conditions are retained and the remaining influencing factors are eliminated.

[0134] In a feasible implementation manner, the optimization module further includes:

[0135] Recalculate the correlation degree of the screened influencing factors based on the grey correlation analysis method;

[0136] By sorting the correlation of the screened influencing factors, the target pile foundation combination is determined based on the sorted influencing factors.

[0137] Example 3

[0138] The present application also provides an electronic device, such as Figure 7 As shown, it includes: a processor 701, a memory 702 and a bus 703, the memory 702 stores machine-readable instructions executable by the processor 701, when the electronic device is running, the processor 701 and the memory 702 communicate through the bus 703, when the machine-readable instructions are executed by the processor 701, any one of the steps of the pile foundation structure optimization method based on the grey correlation analysis method is executed.

[0139] Example 3

[0140] The present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the computer program executes any one of the steps of the method for optimizing a pile foundation structure based on the grey correlation analysis method.

[0141] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, the specific working process of the system and device described above can refer to the corresponding process in the method embodiment, and will not be repeated in this application. In the several embodiments provided in this application, it should be understood that the disclosed system, device and method can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation. For example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0142] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0143] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0144] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a platform server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard drives, ROM, RAM, magnetic disks, or optical disks.

[0145] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A pile foundation structure optimization method based on grey correlation analysis, characterized in that: The method comprises: Obtaining geological profile data and soil property data of the area to be piled, designing pile foundations for the area to be piled based on the geological profile data and soil property data of the area to be piled, and obtaining multiple pile foundation structure combinations for the area to be piled in multiple dimensions; the dimensions include diameter, length, and special-shaped piles; Based on the plurality of pile foundation structure combinations, corresponding pile foundation models are respectively constructed, and the pile foundation models corresponding to the plurality of pile foundation structure combinations are respectively simulated to obtain evaluation data corresponding to the plurality of pile foundation combinations; the pile foundation model is a finite element model; Calculating the correlation degree of the multiple influencing factors of the evaluation data by using the grey correlation analysis method to obtain the correlation degrees corresponding to the multiple influencing factors, so as to screen out the influencing factors that meet the preset conditions based on the correlation degrees; A target pile foundation combination of the pile foundation is determined based on the influencing factors that meet the preset conditions, so as to optimize the pile foundation structure of the area to be piled through the target pile foundation combination.

2. The method according to claim 1, characterized in that The corresponding pile foundation models are constructed based on the various pile foundation structure combinations, and the pile foundation models corresponding to the various pile foundation structure combinations are simulated respectively to obtain evaluation data corresponding to the various pile foundation combinations, including: Construct finite element pile foundation models corresponding to various pile foundation structure combinations based on geological types and multiple model parameters; The pile foundation models are simulated respectively according to a preset simulation method to calculate evaluation data generated by the pile foundation models corresponding to the various pile foundation structure combinations.

3. The method according to claim 2, characterized in that The finite element pile foundation models corresponding to various pile foundation structure combinations are constructed based on multiple model parameters and geological types, including: Acquire multiple contact surfaces of different types of geology between corresponding pile foundations in multiple pile foundation combinations and areas to be piled; Based on a plurality of model parameters, pile foundation models corresponding to a plurality of contact surfaces between the pile foundation and areas to be piled of different geological types are respectively constructed, and parameter values ​​corresponding to the model parameters are determined.

4. The method according to claim 1, characterized in that: The grey correlation analysis method is used to calculate the correlation of the multiple influencing factors of the evaluation data to obtain the correlation corresponding to the multiple influencing factors, including: The grey correlation analysis method calculates the evaluation data corresponding to multiple influencing factors of different values ​​and the reference series to obtain the grey correlation coefficients corresponding to the multiple influencing factors respectively; The correlation degrees corresponding to multiple influencing factors are obtained by conversion based on the grey correlation coefficient.

5. The method according to claim 4, characterized in that The grey correlation analysis method calculates the evaluation data corresponding to multiple influencing factors of different values ​​and the reference series to obtain the grey correlation coefficients corresponding to the multiple influencing factors, including: By using reference series, a comparison matrix composed of evaluation data corresponding to multiple influencing factors of different values ​​is dimensionally processed to obtain a dimensionless matrix; The dimensionless matrix is ​​input into a preset grey relational network, so that the grey relational network calculates the dimensionless matrix to obtain grey relational coefficients corresponding to a plurality of influencing factors.

6. The method according to claim 1, characterized in that Based on the correlation, the influencing factors meeting the preset conditions are screened out, including: Determining whether the multiple influencing factors meet preset conditions, wherein the preset conditions include that the correlation of the influencing factors can be adjusted; If so, the influencing factors that meet the preset conditions are retained and the remaining influencing factors are eliminated.

7. The method according to claim 1, characterized in that The step of determining a target pile foundation combination of the pile foundation based on the influencing factors meeting the preset conditions, so as to optimize the pile foundation structure based on the target pile foundation combination, includes: Recalculate the correlation degree of the screened influencing factors based on the grey correlation analysis method; By sorting the correlation of the screened influencing factors, the target pile foundation combination is determined based on the sorted influencing factors.

8. A pile foundation structure optimization device based on grey correlation analysis method, characterized in that: The device comprises: A design module is used to obtain geological profile data and soil property data of the area to be piled, and to design the pile foundation of the area to be piled based on the geological profile data and soil property data of the area to be piled, so as to obtain a plurality of pile foundation structure combinations for the area to be piled in multiple dimensions; the dimensions include diameter, length, and special-shaped piles; A construction module, for constructing corresponding pile foundation models based on the plurality of pile foundation structure combinations, and simulating the pile foundation models corresponding to the plurality of pile foundation structure combinations, to obtain evaluation data corresponding to the plurality of pile foundation combinations; the pile foundation model is a finite element model; A calculation module, used to calculate the correlation degree of multiple influencing factors of the evaluation data by using a grey correlation analysis method, to obtain the correlation degrees corresponding to the multiple influencing factors, so as to screen out the influencing factors that meet the preset conditions based on the correlation degrees; The optimization module is used to determine a target pile foundation combination of the pile foundation based on the influencing factors that meet the preset conditions, so as to optimize the pile foundation structure of the area to be piled through the target pile foundation combination.

9. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate via the bus, and when the machine-readable instructions are executed by the processor, the steps of a pile foundation structure optimization method based on grey correlation analysis method as described in any one of claims 1 to 7 are performed.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the pile foundation structure optimization method based on the grey correlation analysis method as claimed in any one of claims 1 to 7 are executed.

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