Optimization design method and system of pile foundation

Abstract

The application provides a pile foundation optimization design method and system, and the method comprises the following steps: obtaining geological survey data of a target engineering site and a pile foundation optimization design scheme to be used, constructing a three-dimensional geomechanics model and an initial pile foundation model; simulating the working condition of the initial pile foundation model to obtain a bearing efficiency coefficient; obtaining a design cost corresponding to the pile foundation optimization design scheme to be used, and selecting a final optimization design scheme from a plurality of pile foundation optimization design schemes to be used based on the bearing efficiency coefficient and the design cost. By constructing the three-dimensional geomechanics model and generating the initial pile foundation model, the traditional simplified calculation is replaced, the key performance parameters of the initial pile foundation model can be more accurately predicted, and reliable data basis is provided for optimization; the bearing efficiency coefficient and the design cost cooperatively constitute an optimization target item, the safety specification and the economy are comprehensively considered, and multi-dimensional comprehensive evaluation of the pile foundation optimization design scheme to be used is completed.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to an optimized design method and system for pile foundations. Background Technology

[0002] As the main form of deep foundation, pile foundations are widely used in major projects such as high-rise buildings, bridges, and offshore platforms. The rationality of their design is directly related to the safety of the superstructure and the economy of the project.

[0003] The main purpose of pile foundation design is to effectively transfer the load of the upper part of the building to the deep bearing layer by rationally selecting the pile type, pile diameter, pile length and pile layout scheme, so as to prevent excessive settlement or tilting instability, while taking into account economy and construction feasibility.

[0004] Current pile foundation optimization design methods typically treat pile groups as equivalent to single piles or use elastic theory to simplify the calculation of interactions. This makes it difficult to accurately reflect the joint working mechanism of pile-soil-structure in complex soil layers, especially the insufficient prediction accuracy for problems such as the redistribution of internal forces in the pile body and differential settlement caused by the pile group effect. Furthermore, they often focus on meeting the single objective of safety specifications, while economic considerations are mostly calculated after the fact, lacking a systematic and quantitative multi-objective collaborative optimization framework. Summary of the Invention

[0005] In view of the shortcomings of the prior art, the purpose of this invention is to provide an optimization design method and system for pile foundations, which aims to solve the technical problems of traditional pile foundation optimization design methods relying on local experience and simplified models, and having a single judgment dimension.

[0006] To achieve the above objectives, in a first aspect, embodiments of this application provide an optimized design method for pile foundations, comprising the following steps: Obtain geological survey data and several pile foundation optimization design schemes for the target project site; construct a three-dimensional geomechanical model based on the geological survey data; and generate an initial pile foundation model in the three-dimensional geomechanical model based on the pile foundation optimization design schemes. The initial pile foundation model is subjected to working condition simulation to obtain the bearing capacity coefficient corresponding to the initial pile foundation model; Obtain the design cost corresponding to the proposed optimized design scheme for the pile foundation, and select the final optimized design scheme from several proposed optimized design schemes for the pile foundation based on the bearing capacity coefficient and the design cost.

[0007] Furthermore, the geological exploration data includes borehole data, static cone penetration test data, and beamforming data. The borehole data includes the depth of the top of the strata, the depth of the bottom of the strata, the stratum type, and precise stratum parameters. The step of constructing a three-dimensional geomechanical model based on the geological exploration data includes: Obtain the ground elevation corresponding to the borehole point, obtain the top elevation of the stratum based on the ground elevation and the burial depth of the top stratum, and obtain the bottom elevation of the stratum based on the ground elevation and the burial depth of the bottom stratum. The precise top plate control point and precise bottom plate control point of the formation corresponding to the borehole point are obtained by using the top plate elevation of the formation, the bottom plate elevation of the formation, and the spatial coordinates of the borehole point. Based on the Kriging algorithm and several precise top plate control points, several estimated top plate control points are generated. An initial three-dimensional surface of the top plate is constructed using these precise and estimated top plate control points. Based on the Kriging algorithm and several precise bottom plate control points, several estimated bottom plate control points are generated. An initial three-dimensional surface of the bottom plate is constructed using these precise and estimated bottom plate control points. The initial three-dimensional surface of the top plate and the initial three-dimensional surface of the bottom plate enclose a three-dimensional stratigraphic surface model, which includes several element nodes. The undrained shear strength of the unit node is obtained based on the static penetration test data and the Kriging algorithm. The formation density is obtained through the formation type. The small strain shear modulus of the unit node is obtained based on the formation density, the beam test data, and the Kriging algorithm. The mechanical data of the unit node is obtained based on the precise formation parameters and the Kriging algorithm. The undrained shear strength, the small strain shear modulus, and the mechanical data are combined into mechanical parameters to generate a three-dimensional mechanical parameter field in the three-dimensional formation surface model and form a three-dimensional geological entity model. Initial stress conditions are applied to the three-dimensional geological entity model to obtain a three-dimensional geomechanical model.

[0008] Furthermore, the formula for obtaining the small strain shear modulus is: , in, This represents the small strain shear modulus. Indicates the density of the bottom layer. This represents beam test data.

[0009] Furthermore, the step of performing working condition simulation on the initial pile foundation model to obtain the bearing capacity coefficient corresponding to the initial pile foundation model includes: A static load is applied to the initial pile foundation model to obtain a cloud map of the internal force distribution of the pile body and a contour map of the settlement of the pile group, and to obtain the cost of the pile foundation materials. The ultimate bearing capacity and structural redundancy coefficient of the pile group are obtained by using the pile internal force distribution cloud map, the maximum foundation settlement is obtained by using the pile group settlement contour map, and the bearing efficiency coefficient is obtained based on the pile foundation material cost, the ultimate bearing capacity of the pile group, the structural redundancy coefficient and the maximum foundation settlement.

[0010] Furthermore, the formula for obtaining the load-bearing efficiency coefficient is as follows: , in, Indicates the load-bearing capacity coefficient. Indicates the ultimate bearing capacity of the pile group. This indicates the maximum foundation settlement. This indicates the cost of the pile foundation materials. This represents the structural redundancy coefficient.

[0011] Furthermore, the step of selecting the final optimized design scheme from several proposed pile foundation optimization design schemes based on the bearing capacity coefficient and the design cost includes: One of the proposed optimized design schemes for the unused pile foundations is selected as the benchmark scheme, and the remaining proposed optimized design schemes for the unused pile foundations are selected as reference schemes. If the load-bearing efficiency coefficient of the benchmark scheme is greater than that of all reference schemes, and the design cost of the benchmark scheme is less than that of all reference schemes, then the benchmark scheme will be selected as the final optimized design scheme.

[0012] Furthermore, after the step of selecting the benchmark scheme as the final optimized design scheme if the load-bearing efficiency coefficient of the benchmark scheme is greater than that of all reference schemes and the design cost of the benchmark scheme is less than that of all reference schemes, the method further includes: Each reference scheme and the benchmark scheme are paired. In the pair of schemes, if the load-bearing efficiency coefficient of the benchmark scheme is greater than that of the reference scheme, and the design cost of the benchmark scheme is greater than that of the reference scheme, then the pair of schemes is determined to be a non-dominant pair. In the aforementioned scheme pair, if the load-bearing efficiency coefficient of the benchmark scheme is less than that of the reference scheme, and the design cost of the benchmark scheme is less than that of the reference scheme, then the scheme pair is determined to be a non-dominant pair. If all the scheme pairs corresponding to the baseline scheme are non-dominated pairs, then the baseline scheme is determined to be a non-dominated scheme, and the final optimal design scheme is selected from several of the non-dominated schemes.

[0013] Furthermore, the step of selecting the final optimal design scheme from the plurality of non-dominated schemes includes: The non-dominated schemes are sorted in a first order using the load-bearing efficiency coefficient to obtain a first sequence, and the non-dominated schemes are sorted in a second order using the design cost to obtain a second sequence. Obtain the first dimension side length of the non-dominated scheme from the first sequence, and obtain the second dimension side length of the non-dominated scheme from the second sequence. Combine the first dimension side length and the second dimension side length to form the crowding degree, and select the non-dominated scheme with the highest crowding degree as the final optimized design scheme.

[0014] Furthermore, the step of obtaining the first dimension side length of the non-dominated scheme in the first sequence includes: Select one of its non-dominated schemes as the scheme to be cored, and select the non-dominated schemes adjacent to the scheme to be cored as the adjacent schemes; The absolute value of the difference between the load-bearing efficiency coefficients of two adjacent schemes is determined as the first dimension side length of the scheme to be verified.

[0015] Secondly, embodiments of this application provide an optimized design system for pile foundations, applied to the optimized design method for pile foundations as described in the first aspect above, the system comprising: A construction module is used to acquire geological survey data of the target engineering site and several pile foundation optimization design schemes to be used, construct a three-dimensional geomechanical model based on the geological survey data, and generate an initial pile foundation model in the three-dimensional geomechanical model based on the pile foundation optimization design schemes to be used. The test module is used to simulate the working conditions of the initial pile foundation model in order to obtain the bearing capacity coefficient corresponding to the initial pile foundation model; The execution module is used to obtain the design cost corresponding to the proposed pile foundation optimization design scheme, and select the final optimization design scheme from several proposed pile foundation optimization design schemes based on the bearing capacity coefficient and the design cost.

[0016] Thirdly, embodiments of this application provide a computer, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the pile foundation optimization design method as described in the first aspect above.

[0017] Fourthly, embodiments of this application provide a storage medium storing a computer program that, when executed by a processor, implements the optimized design method for pile foundations as described in the first aspect above.

[0018] Compared with the prior art, the beneficial effects of the present invention are as follows: by constructing the three-dimensional geomechanical model and generating the initial pile foundation model, the traditional simplified calculation is replaced, which can more accurately predict the key performance parameters of the initial pile foundation model and provide a reliable data foundation for optimization; by obtaining the bearing capacity coefficient, the data of multiple dimensions are unified into quantifiable indicators, which, together with the design cost, constitute the optimization target item. In the optimization process, safety standards and economy are comprehensively considered, and a multi-dimensional comprehensive evaluation of the optimization design scheme of the pile foundation to be used is completed to obtain the optimal final optimization design scheme. Attached Figure Description

[0019] Figure 1 This is a flowchart of the optimized design method for pile foundations in the first embodiment of the present invention; Figure 2 This is a structural block diagram of the pile foundation optimization design system in the second embodiment of the present invention; The following detailed description, in conjunction with the accompanying drawings, will further illustrate the present invention. Detailed Implementation

[0020] To facilitate understanding of the present invention, a more complete description will be given below with reference to the accompanying drawings. Several embodiments of the invention are illustrated in the drawings. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.

[0021] It should be noted that when a component is said to be "fixed to" another component, it can be directly on the other component or there may be an intervening component. When a component is said to be "connected to" another component, it can be directly connected to the other component or there may be an intervening component. The terms "vertical," "horizontal," "left," "right," and similar expressions used in this document are for illustrative purposes only.

[0022] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0023] Please see Figure 1 The optimized design method for pile foundations provided in the first embodiment of the present invention includes the following steps: S10: Obtain geological survey data of the target engineering site and several pile foundation optimization design schemes to be used, construct a three-dimensional geomechanical model based on the geological survey data, and generate an initial pile foundation model in the three-dimensional geomechanical model based on the pile foundation optimization design schemes to be used. The geological exploration data includes borehole data, static cone penetration test data, and beam test data. Understandably, borehole data is obtained by drilling to create boreholes, extracting core samples or maps, and using a static cone penetration test vehicle to press a standard cone probe into the map at a constant speed. Shear waves are generated by ground seismic sources or by a shear wave hammer in the borehole, and the propagation speed of the shear waves at different depths in the stratum is measured using a geophone to obtain the beam test data.

[0024] The borehole data includes the burial depth of the top plate of the formation, the burial depth of the bottom plate of the formation, the formation type, and precise formation parameters. The precise formation parameters include cohesion, internal friction angle, and compression modulus. The penetration test data includes cone tip resistance and sidewall friction resistance.

[0025] Step S10 includes: S110: Obtain the ground elevation corresponding to the borehole point, obtain the top elevation of the stratum based on the ground elevation and the burial depth of the top stratum, and obtain the bottom elevation of the stratum based on the ground elevation and the burial depth of the bottom stratum. The difference between the ground elevation and the burial depth of the top plate of the stratum is the elevation of the top plate of the stratum. The elevation of the bottom plate of the stratum is similar and will not be described again here.

[0026] S120: Obtain the precise top plate control point and precise bottom plate control point of the formation corresponding to the borehole point by using the top plate elevation of the formation, the bottom plate elevation of the formation and the spatial coordinates of the borehole point; In three-dimensional space, the x-axis and y-axis coordinates of a control point can be formed by determining the spatial coordinates, and the z-axis coordinate of the control point can be formed by the elevation. Thus, a control point can be established in three-dimensional space. The distance between the precise top plate control point and the precise bottom plate control point of the formation is the thickness of the formation.

[0027] S130: Based on the Kriging algorithm and several precise top plate control points, several estimated top plate control points are generated. An initial three-dimensional surface of the top plate is constructed using the several precise top plate control points and the several estimated top plate control points. Based on the Kriging algorithm and several precise bottom plate control points, several estimated bottom plate control points are generated. An initial three-dimensional surface of the bottom plate is constructed using the several precise bottom plate control points and the several estimated bottom plate control points. The initial three-dimensional surface of the top plate and the initial three-dimensional surface of the bottom plate enclose a three-dimensional stratum surface model. The three-dimensional stratum surface model includes several element nodes. The Kriging algorithm defines a dense, regular two-dimensional planar grid above the entire modeling region. For each node in the grid, the Kriging algorithm analyzes the spatial correlation between known precise top and bottom control points of the formation (using a variogram model), determining that points closer together have stronger elevation correlations. Then, based on the distance and spatial structure relationship between the grid node and the known precise top and bottom control points, a weight is calculated for the elevation of each grid node. Finally, the elevations of the precise top and bottom control points within a certain distance range of the grid node are weighted and averaged to obtain the estimated elevation of the grid node, thus transforming the grid node into the estimated top and bottom control points of the formation. The corresponding estimated top and bottom control points of the formation form the unit node.

[0028] S140: Based on the static penetration test data and Kriging algorithm, obtain the undrained shear strength of the unit node; obtain the formation density through the formation type; obtain the small strain shear modulus of the unit node based on the formation density, the beam test data, and Kriging algorithm; obtain the mechanical data of the unit node based on the precise formation parameters and Kriging algorithm; combine the undrained shear strength, the small strain shear modulus, and the mechanical data into mechanical parameters to generate a three-dimensional mechanical parameter field in the three-dimensional formation surface model and form a three-dimensional geological entity model; The static cone penetration test data includes cone tip resistance. The undrained shear strength has a linear relationship with the cone tip resistance; therefore, the undrained shear strength can be obtained from the cone tip resistance. The formula for obtaining the undrained shear strength is as follows: , in, Indicates the undrained shear strength. Indicates the cone tip resistance. Indicates the effective vertical stress. Represents the cone coefficient, and The value ranges from 15 to 20; The formula for obtaining the small strain shear modulus is: , in, This represents the small strain shear modulus. Indicates the density of the bottom layer. This represents beam test data.

[0029] The precise formation parameters can be directly used as the mechanical data of the unit nodes. It should be noted that some unit nodes correspond to borehole points, some to static penetration test points, and some to beam test points. Therefore, most unit nodes have partial data or no data at all. Based on this, the Kriging algorithm can be used to interpolate other unit nodes based on the unit nodes with partially acquired data. The interpolation principle is consistent with that described in step S130 and will not be repeated here. After interpolation using the Kriging algorithm, all unit nodes possess mechanical parameters, thus forming the three-dimensional mechanical parameter field.

[0030] S150: Apply initial stress conditions to the three-dimensional geological entity model to obtain a three-dimensional geomechanical model; After obtaining the three-dimensional geological entity model, the vertical stress generated by gravity is calculated based on the stratum density, and the lateral pressure coefficient is determined based on the internal friction angle. The horizontal stress is obtained based on the product of the vertical stress and the lateral pressure coefficient. The vertical stress and the horizontal stress are then applied to the three-dimensional geological entity model to obtain the three-dimensional geomechanical model. Further, based on the specifications and locations of several pile foundations in the proposed optimized pile foundation design scheme, an initial pile foundation model is set in the three-dimensional geomechanical model.

[0031] S20: Perform working condition simulation on the initial pile foundation model to obtain the bearing capacity coefficient corresponding to the initial pile foundation model; Step S20 includes: S210: Apply static load to the initial pile foundation model to obtain the pile internal force distribution cloud map and the pile group settlement contour map, and obtain the pile foundation material cost; The static load is applied to the initial pile foundation model in the form of concentrated force or uniformly distributed pressure according to the most unfavorable combination. Under the action of static load, the continuous distribution of axial force and bending moment of each pile along the depth direction can be obtained through finite element calculation, that is, the internal force distribution cloud map of the pile body. At the same time, the vertical displacement of each pile can also be obtained and drawn into a contour map, that is, the settlement contour map of the pile group. The cost of pile foundation materials can be obtained according to the material design of the pile body.

[0032] S220: Obtain the ultimate bearing capacity and structural redundancy coefficient of the pile group through the internal force distribution cloud map of the pile body, obtain the maximum foundation settlement through the settlement contour map of the pile group, and obtain the bearing efficiency coefficient based on the pile foundation material cost, the ultimate bearing capacity of the pile group, the structural redundancy coefficient and the maximum foundation settlement. At each step of the static load increment, the axial force and bending moment on all sections of all piles are read. Based on the material of the pile, the section resistance at that section can be obtained. If the axial force and bending moment at any section of any pile exceeds the section resistance, the static load applied at this time is determined as the ultimate bearing capacity of the pile group.

[0033] Under static load, the maximum axial force and maximum bending moment of each pile at the most unfavorable section are obtained. Based on the material strength of the pile, the allowable bearing capacity and allowable bending moment of a single pile are obtained, and then the actual utilization rate of the internal forces of each pile is obtained. The formula for obtaining the actual utilization rate of the internal forces is as follows: , in, This represents the actual utilization rate of the internal forces of the i-th pile. This represents the maximum axial force of the i-th pile. This represents the maximum bending moment of the i-th pile. Indicates the allowable bearing capacity of a single pile. Indicates the allowable bending moment of a single pile. , Both represent coupling coefficients, and 1 ≤ ≤2、1≤ ≤2; Obtain the standard deviation and average value of the actual utilization rate of internal forces of all piles, obtain the coefficient of variation by dividing the product of the standard deviation and the average value, and convert the coefficient of variation into the structural redundancy coefficient by a decreasing function.

[0034] The settlement contour map of the pile group represents the vertical displacement of each pile, and the maximum vertical displacement is determined as the maximum foundation settlement.

[0035] The formula for obtaining the load-bearing capacity coefficient is as follows: , in, Indicates the load-bearing capacity coefficient. Indicates the ultimate bearing capacity of the pile group. This indicates the maximum foundation settlement. This indicates the cost of the pile foundation materials. This represents the structural redundancy coefficient. The bearing capacity efficiency coefficient simultaneously measures the pile's bearing capacity (ultimate bearing capacity of the pile group) and stiffness (maximum foundation settlement), quantifying the design goal of providing higher bearing capacity under the same settlement or generating less settlement under the same bearing capacity. By introducing the cost of pile foundation materials, an economic dimension is introduced to ensure that when pile foundation performance is similar across different schemes, the lower the material cost, the better. The higher the value of , the better. Simultaneously, by evaluating the load distribution quality in the pile foundation system through the structural redundancy coefficient, a pile foundation design scheme with a more uniform internal force distribution will... The higher the value, the better.

[0036] S30: Obtain the design cost corresponding to the proposed pile foundation optimization design scheme, and select the final optimization design scheme from several proposed pile foundation optimization design schemes based on the bearing capacity coefficient and the design cost; Step S30 includes: S310: Select one of the proposed pile foundation optimization design schemes as the benchmark scheme, and select the remaining proposed pile foundation optimization design schemes as reference schemes; S320: If the load-bearing efficiency coefficient of the benchmark scheme is greater than that of all reference schemes, and the design cost of the benchmark scheme is less than that of all reference schemes, then the benchmark scheme will be selected as the final optimized design scheme. Understandably, if there exists a candidate pile foundation optimization design scheme with a better bearing capacity coefficient than the remaining candidate pile foundation optimization design schemes, and also has the lowest design cost, then it can be directly determined as the final optimization design scheme. It should be noted that if the bearing capacity coefficient of any reference scheme is greater than that of the benchmark scheme, and the design cost of the reference scheme is less than that of the benchmark scheme, then the benchmark scheme will be selected as the discarded scheme, and a new benchmark scheme will be selected.

[0037] S330: Each reference scheme and the benchmark scheme are respectively paired. In the pair of schemes, if the load-bearing efficiency coefficient of the benchmark scheme is greater than that of the reference scheme, and the design cost of the benchmark scheme is greater than that of the reference scheme, then the pair of schemes is determined to be a non-dominant pair. S340: In the pair of schemes, if the load-bearing efficiency coefficient of the benchmark scheme is less than that of the reference scheme, and the design cost of the benchmark scheme is less than that of the reference scheme, then the pair of schemes is determined to be a non-dominant pair. S350: If all the scheme pairs corresponding to the baseline scheme are non-dominated pairs, then the baseline scheme is determined to be a non-dominated scheme, and the final optimized design scheme is selected from several of the non-dominated schemes. Specifically, the non-dominated schemes are sorted in a first order by the load-bearing efficiency coefficient to obtain a first sequence, and the non-dominated schemes are sorted in a second order by the design cost to obtain a second sequence. The first dimension edge length of the non-dominated scheme is obtained from the first sequence. Specifically, one of the non-dominated schemes is selected as the scheme to be cored, and the non-dominated schemes adjacent to the scheme to be cored are selected as the adjacent schemes. The absolute value of the difference between the carrying capacity efficiency coefficients of the two adjacent schemes is determined as the first dimension edge length of the scheme to be cored. It should be noted that if the non-dominated scheme is a side scheme, then it is selected as one of its adjacent schemes. Assuming there are 5 non-dominated schemes A, B, C, D, and E, after sorting based on the carrying capacity efficiency coefficient, the first sequence {E(5.0), D(6.0), C(7.0), B(7.8), A(8.5)} is formed. If C is the scheme to be cored, then the adjacent schemes are D and B. The absolute value of the difference between the two is 1.3, so 1.3 is the first dimension edge length of C. If E is the scheme to be cored, since there are no other schemes to its left, the adjacent schemes of E are E and D. The absolute value of the difference between the two is 1. The second dimension side length of the non-dominated scheme is obtained from the second sequence. The method of obtaining the second dimension side length is the same as that of obtaining the first dimension side length, and will not be repeated here. The first dimension side length and the second dimension side length are combined to form the crowding degree. The non-dominated scheme with the highest crowding degree is selected as the final optimized design scheme. The crowding degree is the sum of the first dimension side length and the second dimension side length.

[0038] By constructing the three-dimensional geomechanical model and generating the initial pile foundation model, the traditional simplified calculation is replaced, which can more accurately predict the key performance parameters of the initial pile foundation model and provide a reliable data foundation for optimization. By obtaining the bearing capacity coefficient, the data from multiple dimensions are unified into quantifiable indicators, which, together with the design cost, constitute the optimization target. In the optimization process, safety standards and economy are comprehensively considered, and a multi-dimensional comprehensive evaluation of the proposed pile foundation optimization design scheme is completed to obtain the optimal final optimization design scheme.

[0039] Please see Figure 2 The second embodiment of the present invention provides an optimized design system for pile foundations. This system is applied to the optimized design method for pile foundations described in the above embodiments, and will not be repeated hereafter. As used below, the terms "module," "unit," "subunit," etc., can refer to a combination of software and / or hardware that performs a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0040] The system includes: The construction module 10 is used to acquire geological survey data of the target engineering site and several pile foundation optimization design schemes to be used, construct a three-dimensional geomechanical model based on the geological survey data, and generate an initial pile foundation model in the three-dimensional geomechanical model based on the pile foundation optimization design schemes to be used. The construction module 10 includes: The first unit is used to obtain the ground elevation corresponding to the borehole point, obtain the top elevation of the stratum based on the ground elevation and the burial depth of the top stratum, and obtain the bottom elevation of the stratum based on the ground elevation and the burial depth of the bottom stratum. The second unit is used to obtain the precise top plate control point and precise bottom plate control point of the formation corresponding to the borehole point through the top plate elevation of the formation, the bottom plate elevation of the formation and the spatial coordinates of the borehole point. The third unit is used to generate several estimated top plate control points based on the Kriging algorithm and several accurate top plate control points of the formation, construct an initial three-dimensional surface of the top plate of the formation using the several accurate top plate control points and several estimated top plate control points of the formation, generate several estimated bottom plate control points based on the Kriging algorithm and several accurate bottom plate control points of the formation, construct an initial three-dimensional surface of the bottom plate of the formation using the several accurate bottom plate control points and several estimated bottom plate control points of the formation, and the initial three-dimensional surface of the top plate of the formation and the initial three-dimensional surface of the bottom plate of the formation enclose a three-dimensional formation surface model, which includes several unit nodes. The fourth unit is used to obtain the undrained shear strength of the unit node based on the static penetration test data and the Kriging algorithm, obtain the formation density through the formation type, obtain the small strain shear modulus of the unit node based on the formation density, the beam test data and the Kriging algorithm, obtain the mechanical data of the unit node based on the precise formation parameters and the Kriging algorithm, and combine the undrained shear strength, the small strain shear modulus and the mechanical data into mechanical parameters to generate a three-dimensional mechanical parameter field in the three-dimensional formation surface model and form a three-dimensional geological entity model. The fifth unit is used to apply initial stress conditions to the three-dimensional geological entity model in order to obtain a three-dimensional geomechanical model; Test module 20 is used to simulate the working conditions of the initial pile foundation model in order to obtain the bearing capacity coefficient corresponding to the initial pile foundation model; The test module 20 includes: The sixth unit is used to apply static loads to the initial pile foundation model to obtain the pile internal force distribution cloud map and the pile group settlement contour map, and to obtain the pile foundation material cost. The seventh unit is used to obtain the ultimate bearing capacity and structural redundancy coefficient of the pile group through the internal force distribution cloud map of the pile body, obtain the maximum foundation settlement through the settlement contour map of the pile group, and obtain the bearing efficiency coefficient based on the pile foundation material cost, the ultimate bearing capacity of the pile group, the structural redundancy coefficient and the maximum foundation settlement. Execution module 30 is used to obtain the design cost corresponding to the proposed pile foundation optimization design scheme, and select the final optimization design scheme from several proposed pile foundation optimization design schemes based on the bearing capacity coefficient and the design cost; The execution module 30 includes: The eighth unit is used to select one of the proposed pile foundation optimization design schemes as the benchmark scheme and select the remaining proposed pile foundation optimization design schemes as reference schemes. The ninth unit is used to select the benchmark scheme as the final optimized design scheme if the load-bearing efficiency coefficient of the benchmark scheme is greater than that of all reference schemes and the design cost of the benchmark scheme is less than that of all reference schemes. The tenth unit is used to form a scheme pair with each reference scheme and the benchmark scheme respectively. In the scheme pair, if the load-bearing efficiency coefficient of the benchmark scheme is greater than that of the reference scheme, and the design cost of the benchmark scheme is greater than that of the reference scheme, then the scheme pair is determined to be a non-dominant pair. The eleventh unit is used to determine the scheme pair as a non-dominant pair if the load-bearing efficiency coefficient of the benchmark scheme is less than that of the reference scheme and the design cost of the benchmark scheme is less than that of the reference scheme. The twelfth unit is used to determine the benchmark scheme as a non-dominated scheme if all scheme pairs corresponding to the benchmark scheme are non-dominated pairs, and to select the final optimized design scheme from several of the non-dominated schemes. The twelfth unit is specifically used to perform a first sorting process on several non-dominated schemes using the carrying capacity efficiency coefficient to obtain a first sequence, and to perform a second sorting process on several non-dominated schemes using the design cost to obtain a second sequence; to obtain the first dimension side length of the non-dominated schemes in the first sequence, and to obtain the second dimension side length of the non-dominated schemes in the second sequence, to combine the first dimension side length and the second dimension side length to form a congestion degree, and to select the non-dominated scheme with the highest congestion degree as the final optimized design scheme.

[0041] The present invention also provides a computer, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the pile foundation optimization design method as described in the above technical solutions.

[0042] The present invention also provides a storage medium storing a computer program thereon, which, when executed by a processor, implements the pile foundation optimization design method as described in the above technical solution.

[0043] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0044] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the appended claims.

Claims

1. An optimized design method for pile foundations, characterized in that, Includes the following steps: Obtain geological survey data and several pile foundation optimization design schemes for the target project site; construct a three-dimensional geomechanical model based on the geological survey data; and generate an initial pile foundation model in the three-dimensional geomechanical model based on the pile foundation optimization design schemes. The initial pile foundation model is subjected to working condition simulation to obtain the bearing capacity coefficient corresponding to the initial pile foundation model; Obtain the design cost corresponding to the proposed optimized design scheme for the pile foundation, and select the final optimized design scheme from several proposed optimized design schemes for the pile foundation based on the bearing capacity coefficient and the design cost.

2. The optimized design method for pile foundations according to claim 1, characterized in that, The geological exploration data includes borehole data, static cone penetration test data, and beamforming data. The borehole data includes the depth of the top of the strata, the depth of the bottom of the strata, the stratum type, and precise stratum parameters. The steps for constructing a three-dimensional geomechanical model based on the geological exploration data include: Obtain the ground elevation corresponding to the borehole point, obtain the top elevation of the stratum based on the ground elevation and the burial depth of the top stratum, and obtain the bottom elevation of the stratum based on the ground elevation and the burial depth of the bottom stratum. The precise top plate control point and precise bottom plate control point of the formation corresponding to the borehole point are obtained by using the top plate elevation of the formation, the bottom plate elevation of the formation, and the spatial coordinates of the borehole point. Based on the Kriging algorithm and several precise top plate control points, several estimated top plate control points are generated. An initial three-dimensional surface of the top plate is constructed using these precise and estimated top plate control points. Based on the Kriging algorithm and several precise bottom plate control points, several estimated bottom plate control points are generated. An initial three-dimensional surface of the bottom plate is constructed using these precise and estimated bottom plate control points. The initial three-dimensional surface of the top plate and the initial three-dimensional surface of the bottom plate enclose a three-dimensional stratigraphic surface model, which includes several element nodes. The undrained shear strength of the unit node is obtained based on the static penetration test data and the Kriging algorithm. The formation density is obtained through the formation type. The small strain shear modulus of the unit node is obtained based on the formation density, the beam test data, and the Kriging algorithm. The mechanical data of the unit node is obtained based on the precise formation parameters and the Kriging algorithm. The undrained shear strength, the small strain shear modulus, and the mechanical data are combined into mechanical parameters to generate a three-dimensional mechanical parameter field in the three-dimensional formation surface model and form a three-dimensional geological entity model. Initial stress conditions are applied to the three-dimensional geological entity model to obtain a three-dimensional geomechanical model.

3. The optimized design method for pile foundations according to claim 2, characterized in that, The formula for obtaining the small strain shear modulus is: ， in, This represents the small strain shear modulus. Indicates the density of the bottom layer. This represents beam test data.

4. The optimized design method for pile foundations according to claim 1, characterized in that, The step of performing working condition simulation on the initial pile foundation model to obtain the bearing capacity coefficient corresponding to the initial pile foundation model includes: A static load is applied to the initial pile foundation model to obtain a cloud map of the internal force distribution of the pile body and a contour map of the settlement of the pile group, and to obtain the cost of the pile foundation materials. The ultimate bearing capacity and structural redundancy coefficient of the pile group are obtained by using the pile internal force distribution cloud map, the maximum foundation settlement is obtained by using the pile group settlement contour map, and the bearing efficiency coefficient is obtained based on the pile foundation material cost, the ultimate bearing capacity of the pile group, the structural redundancy coefficient and the maximum foundation settlement.

5. The optimized design method for pile foundations according to claim 4, characterized in that, The formula for obtaining the load-bearing capacity coefficient is as follows: ， in, Indicates the load-bearing capacity coefficient. Indicates the ultimate bearing capacity of the pile group. This indicates the maximum foundation settlement. This indicates the cost of the pile foundation materials. This represents the structural redundancy coefficient.

6. The optimized design method for pile foundations according to claim 1, characterized in that, The step of selecting the final optimized design scheme from several proposed pile foundation optimized design schemes based on the bearing capacity coefficient and the design cost includes: One of the proposed optimized design schemes for the unused pile foundations is selected as the benchmark scheme, and the remaining proposed optimized design schemes for the unused pile foundations are selected as reference schemes. If the load-bearing efficiency coefficient of the benchmark scheme is greater than that of all reference schemes, and the design cost of the benchmark scheme is less than that of all reference schemes, then the benchmark scheme will be selected as the final optimized design scheme.

7. The optimized design method for pile foundations according to claim 6, characterized in that, After the step of selecting the benchmark scheme as the final optimized design scheme if the load-bearing efficiency coefficient of the benchmark scheme is greater than that of all reference schemes and the design cost of the benchmark scheme is less than that of all reference schemes, the method further includes: Each reference scheme and the benchmark scheme are paired. In the pair of schemes, if the load-bearing efficiency coefficient of the benchmark scheme is greater than that of the reference scheme, and the design cost of the benchmark scheme is greater than that of the reference scheme, then the pair of schemes is determined to be a non-dominant pair. In the aforementioned scheme pair, if the load-bearing efficiency coefficient of the benchmark scheme is less than that of the reference scheme, and the design cost of the benchmark scheme is less than that of the reference scheme, then the scheme pair is determined to be a non-dominant pair. If all the scheme pairs corresponding to the baseline scheme are non-dominated pairs, then the baseline scheme is determined to be a non-dominated scheme, and the final optimal design scheme is selected from several of the non-dominated schemes.

8. The optimized design method for pile foundations according to claim 7, characterized in that, The step of selecting the final optimal design from the plurality of non-dominated solutions includes: The non-dominated schemes are sorted in a first order using the load-bearing efficiency coefficient to obtain a first sequence, and the non-dominated schemes are sorted in a second order using the design cost to obtain a second sequence. Obtain the first dimension side length of the non-dominated scheme from the first sequence, and obtain the second dimension side length of the non-dominated scheme from the second sequence. Combine the first dimension side length and the second dimension side length to form the crowding degree, and select the non-dominated scheme with the highest crowding degree as the final optimized design scheme.

9. The optimized design method for pile foundations according to claim 8, characterized in that, The step of obtaining the first dimension side length of the non-dominated scheme in the first sequence includes: Select one of its non-dominated schemes as the scheme to be cored, and select the non-dominated schemes adjacent to the scheme to be cored as the adjacent schemes; The absolute value of the difference between the load-bearing efficiency coefficients of two adjacent schemes is determined as the first dimension side length of the scheme to be verified.

10. An optimization design system for pile foundations, applied to the optimization design method for pile foundations as described in any one of claims 1 to 9, characterized in that, The system includes: A construction module is used to acquire geological survey data of the target engineering site and several pile foundation optimization design schemes to be used, construct a three-dimensional geomechanical model based on the geological survey data, and generate an initial pile foundation model in the three-dimensional geomechanical model based on the pile foundation optimization design schemes to be used. The test module is used to simulate the working conditions of the initial pile foundation model in order to obtain the bearing capacity coefficient corresponding to the initial pile foundation model; The execution module is used to obtain the design cost corresponding to the proposed pile foundation optimization design scheme, and select the final optimization design scheme from several proposed pile foundation optimization design schemes based on the bearing capacity coefficient and the design cost.

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