A BIM-assisted precast pile rock embedding depth analysis method and system

Abstract

The present invention discloses a BIM-assisted precast pile rock-embedded depth analysis method and system, which relates to the field of civil engineering. The technical scheme of the present invention is as follows: constructing a three-dimensional model of precast piles and geological layers; generating a finite element model including precast piles, geological layers and boundary conditions; solving stress and displacement; extracting the stress distribution in the contact area between the pile foundation and the bearing layer and the displacement of the pile bottom; using the linear interpolation method to estimate the preliminary rock-embedded depth of the finite element simulation data; combining the top surface elevation of the bearing layer with the pile foundation hole depth to calculate the preliminary rock-embedded depth; modeling the pile foundation hole depth and the bearing layer depth according to the probability distribution; recalculating and adjusting the preliminary rock-embedded depth; using a genetic algorithm to evaluate the fitness of multiple rock-embedded depth configuration schemes, and selecting the optimal scheme to determine the final rock-embedded depth. The present invention improves the safety and stability of the entire building structure and reduces the risk of building settlement and structural deformation.

Description

Technical Field

[0001] The present invention relates to the field of civil engineering, and more specifically, to a BIM-assisted prefabricated pile rock-embedded depth analysis method and system. Background Art

[0002] In modern construction projects, pile foundations are an important part of the load-bearing structure, and their design and construction are crucial to the safety and stability of the building. Precast piles are increasingly being used in various construction projects due to their controllable quality, fast construction speed, and low environmental impact. Especially in projects with complex geological conditions and tight construction schedules, precast piles have more advantages than traditional cast-in-place piles, which can significantly improve construction efficiency and reduce interference with the environment.

[0003] Because precast piles are produced in factories, their material quality and geometric dimensions can be strictly controlled, thus ensuring the strength and consistency of the piles. Compared with cast-in-place piles, precast piles are faster to construct and can significantly shorten the construction period, especially suitable for projects with tight construction schedules. In addition, the construction process of precast piles has less impact on the environment, which is conducive to their application in densely populated urban areas and ecologically sensitive areas.

[0004] However, despite the above advantages of precast piles, their rock embedding depth in actual projects must be precisely controlled. The rock embedding depth of precast piles refers to the depth of the pile foundation into the bearing layer. This depth determines the interaction ability between the pile foundation and the foundation soil, thus affecting the bearing capacity of the entire building. If the rock embedding depth is insufficient, the pile foundation may not meet the designed bearing capacity requirements, resulting in uneven settlement, structural deformation, and even failure of the building. If the precast piles are too long, the amount of pile cutting will increase, resulting in waste. Therefore, accurate rock embedding depth analysis of precast piles to ensure that they are effectively embedded in the bearing layer is a key step to ensure project quality and building safety. Summary of the invention

[0005] In order to solve the deficiencies in the prior art, the purpose of the present invention is to provide a BIM-assisted precast pile rock-embedded depth analysis method and system, which can effectively improve the accuracy of pile foundation design by integrating design drawings and geological data in the BIM platform, constructing a three-dimensional model, and using finite element analysis tools to simulate and analyze the rock-embedded depth of precast piles; the precise calculation and optimization of the rock-embedded depth ensures the reliable connection between the pile foundation and the bearing layer, thereby improving the safety and stability of the entire building structure and reducing the risks of building settlement and structural deformation.

[0006] The above technical objectives of the present invention are achieved through the following technical solutions:

[0007] In a first aspect, a BIM-assisted precast pile rock embedding depth analysis method is provided, comprising the following steps:

[0008] Construct a 3D model of precast piles and geological layers in the BIM platform according to the design drawings and geological data to obtain a BIM model;

[0009] The finite element analysis tool integrated in the BIM platform is used to call the geometric and physical properties in the BIM model to generate a finite element model including precast piles, geological layers and boundary conditions;

[0010] Apply the load conditions of precast piles in the finite element model, solve the stress and displacement, and obtain the solution results;

[0011] The stress distribution in the contact area between the pile foundation and the bearing layer and the displacement of the pile bottom are extracted from the solution results to obtain the finite element simulation data;

[0012] The linear interpolation method is used to estimate the initial rock embedding depth of the finite element simulation data, and based on the estimation results, it is determined whether the initial position of the pile foundation in the bearing layer meets the design requirements;

[0013] When the design requirements are met, the top elevation of the bearing layer and the pile foundation hole depth are combined through the BIM model to calculate the preliminary rock embedding depth;

[0014] The preliminary rock-embedded depth is used as the basic input of the Monte Carlo simulation, the probability distribution of the pile foundation hole depth and the top depth of the geological layer is defined, and the pile foundation hole depth and the bearing layer depth are modeled according to the probability distribution;

[0015] According to the pile foundation hole depth and the top surface depth of the geological layer randomly selected from the probability distribution, the preliminary rock-embedded depth is recalculated and adjusted to obtain the rock-embedded depth range;

[0016] A genetic algorithm is used to evaluate the fitness of multiple rock-embedded depth configuration schemes generated according to the rock-embedded depth range, and the optimal scheme is selected to determine the final rock-embedded depth.

[0017] Furthermore, the geological data include the type, distribution, physical and mechanical properties of the strata, groundwater level and bearing layer depth.

[0018] Furthermore, the generation process of the finite element model is specifically as follows:

[0019] Discretize the BIM model into finite elements according to the geometry of precast piles and geological layers;

[0020] Use the physical property data in the BIM model to assign corresponding material properties to each unit;

[0021] In the finite element model, boundary conditions are used to define the interaction between the structure and the external environment;

[0022] Various loads are applied in the finite element model according to actual construction conditions and design requirements.

[0023] Furthermore, the load conditions include self-weight load, superstructure load, horizontal load and foundation reaction force.

[0024] Furthermore, the process of solving stress and displacement is specifically as follows:

[0025] The finite element model is established as a set of linear or nonlinear equations to describe the mechanical equilibrium state of each unit under the external load, and the equation group is obtained;

[0026] Solve the displacement of each node from the equation set to obtain the displacement result;

[0027] Based on the stress-strain relationship, the stress distribution of each element is calculated from the displacement results.

[0028] Furthermore, the stress in the contact area between the pile foundation and the bearing layer includes normal stress and shear stress.

[0029] Furthermore, the displacement of the pile bottom includes vertical displacement and horizontal displacement.

[0030] Furthermore, the preliminary rock-embedded depth is used as the basic input of the Monte Carlo simulation, the probability distribution of the pile foundation hole depth and the top surface depth of the geological layer is defined, and the pile foundation hole depth and the bearing layer depth are modeled according to the probability distribution, including:

[0031] Define the probability distribution of pile foundation hole depth and top depth of geological layer based on historical data, field survey results and reference data;

[0032] Monte Carlo simulation uses random sampling to draw multiple random samples from a probability distribution;

[0033] For each random sample, the corresponding rock embedment depth is calculated.

[0034] Furthermore, the optimization objectives of selecting the best solution include structural safety, economy and construction feasibility.

[0035] In a second aspect, a BIM-assisted precast pile rock embedding depth analysis system is provided, and the system is used to implement a BIM-assisted precast pile rock embedding depth analysis method as described in any one of the first aspects, including:

[0036] A 3D modeling module is used to construct a 3D model of precast piles and geological layers in the BIM platform according to the design drawings and geological data to obtain a BIM model;

[0037] Finite element analysis module, which is used to call the geometric and physical properties in the BIM model through the finite element analysis tool integrated in the BIM platform to generate a finite element model including precast piles, geological layers and boundary conditions;

[0038] The load solving module is used to apply the load conditions of the precast piles in the finite element model, solve the stress and displacement, and obtain the solution results;

[0039] The data extraction module is used to extract the stress distribution in the contact area between the pile foundation and the bearing layer and the displacement of the pile bottom from the solution results to obtain the finite element simulation data;

[0040] The estimation and judgment module is used to estimate the initial rock embedding depth of the finite element simulation data using the linear interpolation method, and to determine whether the initial position of the pile foundation in the bearing layer meets the design requirements based on the estimation results;

[0041] The depth calculation module is used to combine the top elevation of the bearing layer with the pile foundation hole depth through the BIM model to calculate the preliminary rock-embedded depth when the design requirements are met;

[0042] The simulation modeling module is used to use the preliminary rock embedding depth as the basic input of the Monte Carlo simulation, define the probability distribution of the pile foundation hole depth and the top surface depth of the geological layer, and model the pile foundation hole depth and the bearing layer depth according to the probability distribution;

[0043] An update calculation module is used to recalculate and adjust the preliminary rock-embedded depth according to the pile foundation hole depth and the top surface depth of the geological layer randomly extracted from the probability distribution to obtain the rock-embedded depth range;

[0044] The depth optimization module is used to use a genetic algorithm to evaluate the fitness of multiple rock-embedded depth configuration schemes generated according to the rock-embedded depth range, and select the optimal scheme to determine the final rock-embedded depth.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] 1. A BIM-assisted precast pile rock-embedded depth analysis method provided by the present invention can effectively improve the accuracy of pile foundation design by integrating design drawings and geological data in the BIM platform, constructing a three-dimensional model, and using finite element analysis tools to simulate and analyze the rock-embedded depth of precast piles; accurate calculation and optimization of the rock-embedded depth ensures a reliable connection between the pile foundation and the bearing layer, thereby improving the safety and stability of the entire building structure and reducing the risk of building settlement and structural deformation;

[0047] 2. The present invention generates multiple rock-embedded depth configuration schemes through optimization tools such as genetic algorithms in the BIM platform, and performs fitness evaluation and optimization on these schemes, so that the final rock-embedded depth design not only meets the structural requirements, but also takes into account the actual feasibility of construction. This process can effectively reduce the uncertainty in construction, optimize the construction plan, improve construction efficiency, and reduce rework and delays caused by improper design. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0049] Figure 1 is a flow chart of Embodiment 1 of the present invention;

[0050] Figure 2 It is a system block diagram in Example 2 of the present invention. DETAILED DESCRIPTION

[0051] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments and drawings. The exemplary embodiments of the present invention and their description are only used to explain the present invention and are not intended to limit the present invention.

[0052] Embodiment 1: The present invention provides a BIM-assisted precast pile rock embedment depth analysis method.

[0053] BIM refers to a method of integrating and managing the geometric information, physical properties and functional characteristics of buildings through digital technology. BIM technology is not only a three-dimensional modeling, but also a comprehensive platform that can integrate design drawings, engineering information, construction records, operation and maintenance and other data to achieve the management and analysis of the entire life cycle of the building. In the BIM environment, various types of building information are integrated and visualized in a digital way, allowing the design, construction and operation teams to work together more efficiently, reduce errors and improve project quality.

[0054] Precast piles are prefabricated pile foundation components made of concrete or steel in a factory. Because they are produced in a factory, the quality of precast piles can be strictly controlled, and their size and shape are more standardized and consistent. After being transported to the construction site, the precast piles are driven into the foundation by mechanical equipment to form the foundation of the building. Precast piles are widely used in various construction and infrastructure projects due to their advantages such as fast construction speed, reliable quality and low environmental impact.

[0055] The rock-embedded depth refers to the depth of the pile foundation into the underground bearing layer (rock layer). This depth determines the contact area and interaction force between the pile foundation and the bearing layer, thus affecting the bearing capacity of the pile foundation. Accurate calculation of the rock-embedded depth is crucial to ensure the stability of the pile foundation and the safety of the building. If the rock-embedded depth is insufficient, the pile foundation may not provide sufficient support, resulting in building settlement or structural failure.

[0056] Specifically, Figure 1 As shown, a BIM-assisted precast pile rock embedding depth analysis method includes the following steps:

[0057] Step S1, in the BIM platform, construct a three-dimensional model of prefabricated piles and geological layers based on design drawings and geological data.

[0058] Design drawings are the initial documents of a construction project, containing detailed design information of the building, such as floor plans, elevations, sections, detailed structural drawings, etc. These drawings are drawn by architects, structural engineers and other professionals, defining the shape, size, layout, and location and specifications of each component of the building. In the BIM platform, design drawings are used as basic data input to generate a 3D model.

[0059] Geological data refers to information about underground conditions at the construction site obtained through geological exploration, including the type, distribution, physical and mechanical properties of the strata (such as density, porosity, compressive strength, etc.), groundwater level, depth of the bearing layer, etc. These data are crucial for pile foundation design because geological conditions directly affect the bearing capacity and stability of the pile foundation. In the BIM model, geological data is used to construct a three-dimensional model of the underground structure to ensure that the design solution can adapt to the actual geological environment.

[0060] Design drawings serve as the blueprint of a building, providing the overall layout, component specifications and structural requirements of the building. In the BIM platform, design drawings are digitized and converted into a three-dimensional geometric model, which includes all the components of the building and their spatial relationships.

[0061] At the same time, geological data provides underground information of the construction site. This information is obtained through geological exploration and includes the distribution of strata, the physical properties of soil and rock, groundwater level, etc. In the BIM model, geological data is used to construct a three-dimensional model of the geological layer, which can accurately reflect the geological conditions of the construction site and provide a reliable basis for the design of the pile foundation.

[0062] Information about the precast piles was also integrated into the BIM model, including the length, diameter, material properties, etc. In the 3D model, the precast piles were simulated as to how they would be embedded in the geological layer during actual construction, especially how they would enter the bearing layer. This process not only helps to assess the rock embedding depth of the precast piles, but also analyzes the bearing capacity and stability of the pile foundation through simulation.

[0063] Step S2, in the BIM platform, a finite element analysis tool is integrated to generate a finite element model using the geometric and physical properties in the BIM model, including precast piles, geological layers, and boundary conditions.

[0064] Integrate finite element analysis (FEM) tools in the BIM platform, such as through plug-ins or integration with external finite element software (such as ANSYS, ABAQUS). Use the geometric and physical properties in the BIM model to automatically generate a finite element model, including precast piles, geological layers, and some related boundary conditions.

[0065] The BIM model contains detailed geometric information of the building and its components, such as the length, diameter, shape, etc. of precast piles, as well as the distribution and structure of geological layers. In addition, the BIM model also records the physical properties of these components, including key parameters such as material density, elastic modulus, Poisson's ratio, etc. These geometric and physical properties are the basic data for finite element analysis.

[0066] When generating a finite element model, these geometric and physical properties are used to define the material properties and structural behavior of each element. For example, the geometry of the precast pile determines how it is meshed, while the elastic modulus and Poisson's ratio of the material affect the stress distribution and deformation behavior of the pile under load. The physical properties of the geological layer, such as density and shear strength, are used to simulate the support and reaction forces of the foundation on the pile foundation.

[0067] The finite element model is a mathematical model that is analyzed by discretizing a continuous structure into a finite number of units (i.e., meshes). Each unit is connected by a node, and loads and boundary conditions are applied to the nodes. In the BIM platform, the process of generating a finite element model includes the following steps:

[0068] Meshing: The BIM model is discretized into finite units according to the geometry of the precast piles and geological layers. The accuracy of the meshing affects the accuracy of the analysis results, so a finer mesh is used in the area where the precast piles and geological layers meet.

[0069] Material property assignment: Use the physical property data in the BIM model to assign corresponding material properties to each unit, such as the concrete strength of precast piles and the elastic modulus of geological layers. These properties will directly affect the results of finite element analysis and determine the stress-strain response of the pile foundation under external forces.

[0070] Boundary condition setting: In the finite element model, boundary conditions define the interaction between the structure and the external environment. For models of precast piles and geological layers, boundary conditions may include the contact conditions between the pile bottom and the bearing layer, the friction between the pile body and the surrounding soil layer, and the constraints of the foundation. These conditions are crucial to simulate the actual stress conditions of the pile foundation and must be set accurately.

[0071] Load application: According to the actual construction conditions and design requirements, various loads are applied in the finite element model, such as the deadweight of the pile foundation, static load and dynamic load of the building superstructure, etc. These loads will be used to analyze the stress distribution, deformation and stability of the pile foundation.

[0072] Step S3, in the finite element model, the load condition of the precast pile is applied, and the stress and displacement are solved.

[0073] In the analysis of precast pile foundations, the finite element model can accurately describe the interaction between the pile foundation and the foundation and simulate the mechanical performance of the precast pile under different loads. This simulation helps to understand the actual stress conditions of the pile foundation, verify the rationality of the design, and foresee possible structural problems.

[0074] Load conditions refer to external forces or environmental influences acting on a structure. In finite element analysis, applying load conditions is a key step in analyzing how a structure responds to these external forces. For precast pile foundations, the load conditions of the present invention include the following:

[0075] Self-weight load: The weight of the precast pile itself is applied in the longitudinal direction of the pile, resulting in axial compression of the pile body.

[0076] Superstructure load: The weight of the building's superstructure is transferred to the foundation through the pile foundation. This is the main load carried by the pile foundation, applied to the top of the pile and transferred along the axial direction of the pile.

[0077] Horizontal loads: such as wind loads, earthquakes or horizontal thrusts, which can cause lateral deformation and tilting of the pile foundation. In the finite element model, these loads are applied to the side or top of the pile to simulate the performance of the pile foundation under extreme conditions.

[0078] Foundation reaction force: The reaction force exerted by the foundation on the pile foundation is the support force of the foundation soil or rock layer on the pile body. These forces are applied as boundary conditions in the finite element model to simulate the interaction between the foundation and the pile foundation.

[0079] Other environmental loads: such as temperature changes, groundwater level fluctuations, etc., these factors may also affect the mechanical behavior of the pile foundation. In the finite element analysis, these load conditions are applied according to the specific engineering requirements.

[0080] In the finite element model, after the load conditions are applied, the system calculates the stress and displacement distribution of the structure by solving a series of equilibrium equations. This process includes the following steps:

[0081] Establishment of equations: The finite element method describes the mechanical equilibrium state of each unit under external loads by establishing a set of linear or nonlinear equations. The equations include the relationship between the displacement and force of the nodes.

[0082] Solve the displacement field: Solve the equations to get the displacement of each node. These displacements represent the deformation of the pile under load. By solving the displacement, we can understand the overall deformation mode of the pile and the deformation characteristics of the local area.

[0083] Calculation of stress field: Based on the displacement results, the stress distribution of each unit is calculated through the stress-strain relationship (such as the constitutive relationship of the material). Stress is an expression of internal force and reflects the stress conditions of the pile foundation at different locations.

[0084] Step S4, extracting the stress distribution in the contact area between the pile foundation and the bearing layer and the displacement of the pile bottom.

[0085] The contact area between the pile foundation and the bearing layer is a key part in the pile foundation design. It is the main path for the pile foundation to transfer the load to the foundation. In this area, complex interactions occur between the pile foundation and the bearing layer, including pressure transmission, friction, and possible shear deformation. This interaction determines the bearing capacity and settlement performance of the pile foundation and is the basis of the pile foundation stability.

[0086] In the finite element model, the contact area between the pile foundation and the bearing layer is simulated through fine meshing and appropriate contact conditions. Finite element analysis can accurately calculate the stress distribution in this area and identify possible stress concentration areas or weak points.

[0087] Stress distribution refers to the stress variation in the contact area between the pile foundation and the bearing layer. Stress is a manifestation of internal force and reflects the stress state of the pile foundation under specific load conditions. In pile foundation design, understanding stress distribution is crucial to ensure the safety and long-term stability of the structure.

[0088] Normal stress (axial stress): In the contact area between the pile foundation and the bearing layer, the normal stress is mainly transmitted from the pile top load along the pile body to the pile bottom, and distributed to the foundation through the bearing layer. The distribution of normal stress is manifested as a pressure concentration area on the contact surface, especially at the junction of the pile bottom and the bearing layer. If the normal stress exceeds the allowable stress of the material, it may cause local damage to the pile foundation or the bearing layer.

[0089] Shear stress: Shear stress occurs on the lateral contact surface between the pile foundation and the bearing layer. Especially when the pile foundation is subjected to horizontal load, the distribution of shear stress is very important for evaluating the anti-overturning and anti-slip capabilities of the pile foundation. Excessive shear stress may cause relative slip between the pile foundation and the foundation, thereby affecting the overall stability of the pile foundation.

[0090] The displacement of the pile bottom refers to the horizontal and vertical displacement of the bottom of the pile foundation under the action of external loads. The size and direction of the pile bottom displacement directly affect the bearing capacity of the pile foundation and the overall stability of the building.

[0091] Vertical displacement (settlement): Vertical displacement is the downward displacement of the pile foundation under the action of axial load, which is called settlement. Reasonable settlement is part of the pile foundation work, but excessive settlement may cause uneven settlement of the building, causing structural deformation or cracking. Finite element analysis can accurately calculate the settlement of the pile bottom under various load conditions, helping to design a pile foundation that meets the settlement control requirements.

[0092] Horizontal displacement: Horizontal displacement is caused by lateral loads (such as wind loads, seismic forces, etc.). If the horizontal displacement of the pile bottom is too large, the pile foundation may lose stability or even overturn. The finite element model can be used to simulate the horizontal displacement of the pile foundation under extreme loads, and the design of the pile foundation can be adjusted accordingly to ensure its ability to resist lateral forces.

[0093] Displacement distribution: The displacement of the pile bottom depends not only on the size of the load, but also on the properties of the foundation soil and the thickness of the bearing layer. Finite element analysis can show the distribution of the pile bottom displacement, help understand the deformation characteristics of the pile foundation at different locations, and optimize the matching between the pile foundation and the bearing layer.

[0094] Step S5: in the BIM platform, a linear interpolation method is used to perform a preliminary estimation of the rock embedding depth on the extracted finite element simulation data.

[0095] Finite element simulation is a numerical method that analyzes the mechanical behavior of a continuous structure by discretizing it into a finite number of units. In pile foundation design, finite element simulation data include stress distribution, displacement field, deformation, etc. These data can reflect the stress state and deformation characteristics of the pile foundation under different load conditions.

[0096] Select key stress points and displacement points from the finite element simulation data, especially the node data in the contact area with the bearing layer. These data points will serve as the basis for linear interpolation.

[0097] According to the geological exploration report and finite element model, the top and bottom elevations of the bearing layer are determined. The top elevation of the bearing layer is used as the starting point for linear interpolation calculation.

[0098] The embedding depth of the pile foundation in the bearing layer is estimated by linear interpolation using the top elevation of the bearing layer and the displacement or stress data of the pile bottom. This estimate provides a preliminary position of the pile foundation in the bearing layer to determine whether it meets the design requirements.

[0099] Step S6, using the BIM model, the top surface elevation of the bearing layer is combined with the pile foundation drilling depth to calculate the preliminary rock embedding depth.

[0100] The bearing layer refers to the geological layer that can bear and transfer the pile foundation load to the underlying geological layer. It is a hard rock layer or a dense soil layer. The top elevation of the bearing layer refers to the height position of the top of the bearing layer. This elevation is an important parameter that must be considered in pile foundation design.

[0101] The top elevation of the bearing layer is provided by geological exploration data and determined through drilling and sampling analysis. In the BIM model, the top elevation of the bearing layer is accurately represented as part of the geological layer. This information is used to guide the pile foundation design to ensure that the pile foundation can be properly embedded in the bearing layer to achieve the designed bearing capacity.

[0102] The pile foundation hole depth refers to the depth of the pile hole drilled or pile sunk below the ground during the construction process. This depth determines the contact position and interaction characteristics between the pile foundation and the foundation soil layer or bearing layer. The pile foundation hole depth is determined by the on-site construction records and dynamically updated in the BIM model to reflect the actual construction progress and conditions.

[0103] The pile foundation hole depth should be large enough to ensure that the pile foundation can be embedded in the bearing layer with the required bearing capacity. If the pile foundation hole depth is insufficient, the pile foundation may not reach the designed rock embedment depth, which will affect the bearing capacity of the pile foundation and the safety of the building. Therefore, in the construction of pile foundation, accurately controlling and recording the pile foundation hole depth is an important part of ensuring construction quality.

[0104] Rock embedment depth refers to the depth of the pile foundation into the bearing layer. This depth directly affects the bearing capacity of the pile foundation and determines the contact area and stress distribution between the pile foundation and the bearing layer. The calculation of the preliminary rock embedment depth is a key step in the design and construction of pile foundations, aiming to ensure that the pile foundation can meet or exceed the design bearing capacity.

[0105] The top elevation of the bearing layer provided by geological exploration and the pile foundation drilling depth recorded in the on-site construction are input into the BIM model. The BIM model can integrate these data with the geometric shape, material properties and other information of the pile foundation to form a complete analysis basis.

[0106] The BIM model determines the relative position of the pile foundation and the bearing layer by analyzing the geometric relationship between the pile foundation hole depth and the top elevation of the bearing layer. Specifically, the rock embedding depth can be preliminarily calculated using the following formula:

[0107] ;

[0108] in, represents the rock embedding depth, Indicates the pile foundation hole depth. Indicates the top elevation of the bearing layer.

[0109] Step S7, using the preliminary rock-embedded depth as the basic input of the Monte Carlo simulation, defining the probability distribution of the pile foundation hole depth and the geological layer top surface depth, and modeling the pile foundation hole depth and the bearing layer depth based on these probability distributions.

[0110] Although the preliminary rock-embedded depth provides a basis for subsequent analysis, this estimate may not be completely accurate due to the uncertainties in the actual geological conditions and the construction process. Therefore, it is necessary to further use statistical methods such as Monte Carlo simulation to deal with these uncertainties in order to obtain a more reliable estimate of the rock-embedded depth.

[0111] In actual engineering, there is often uncertainty in the depth of pile foundation holes and the depth of the top surface of the geological layer. The depth of pile foundation holes may be affected by many factors such as on-site construction conditions, equipment accuracy, construction errors, etc., while the depth of the top surface of the geological layer depends on the accuracy of geological exploration and the natural changes of the site. Therefore, these parameters are regarded as random variables and their uncertainties are described by probability distribution.

[0112] Probability distribution of pile foundation hole depth: The probability distribution of pile foundation hole depth reflects the range of depths that the pile hole may reach under different construction conditions. This distribution may present a normal distribution, a uniform distribution, or other suitable statistical distribution forms, depending on the stability and accuracy of the construction. For example, if the construction error is small, the pile foundation hole depth may be close to the design value and present a narrow normal distribution; if the construction conditions are variable, it may present a wider distribution.

[0113] Probability distribution of top depth of geological layer: The probability distribution of top depth of geological layer indicates the depth variation of bearing layer at different locations. This distribution is based on the analysis results of geological exploration data and reflects the complexity and variation of geological layers. In areas with relatively stable geological conditions, the top depth of bearing layer may be close to the design value and present a narrow distribution; while in areas with complex geological conditions, the top depth distribution may be wide or even multi-peaked, reflecting the geological characteristics of different regions.

[0114] In the Monte Carlo simulation, modeling is performed based on the probability distribution of the pile foundation hole depth and the top depth of the geological layer in order to generate a large number of possible rock embedment depth scenarios. This process includes the following steps:

[0115] Probability distribution setting: Based on historical data, field survey results and expert opinions, define the probability distribution of pile foundation hole depth and geological layer top depth. Use statistical software or modeling tools in the BIM platform to set these distribution parameters, including mean, standard deviation, distribution type (such as normal, uniform, lognormal, etc.).

[0116] Random sampling: Monte Carlo simulation uses random sampling to extract a large number of samples from a defined probability distribution. These samples represent the possible values ​​of the pile foundation hole depth and the top depth of the bearing layer under different construction conditions.

[0117] Calculate the rock-embedded depth: For each random sample, calculate the corresponding rock-embedded depth. The specific calculation method can use the aforementioned geometric relationship formula:

[0118] ;

[0119] in, represents the rock-embedded depth corresponding to random sample i, , are the pile hole depth and the top surface depth of the bearing layer corresponding to random sample i respectively.

[0120] Step S8, performing multiple random samplings, using the randomly selected pile foundation hole depth and geological layer top surface depth in each simulation, recalculating and adjusting the preliminary rock-embedded depth to obtain a possible rock-embedded depth range.

[0121] In order to obtain a stable and representative estimate of the rock-embedded depth, multiple random samplings are required. The selection of the number of samples depends on the complexity of the simulation and the required accuracy. Generally speaking, the larger the number of samples, the more reliable the simulation results. In actual projects, thousands or even more samplings are performed to ensure the robustness of the results.

[0122] In each simulation, the system randomly extracts a set of data from the preset probability distribution of pile foundation borehole depth and geological layer top depth. These data reflect the pile foundation borehole depth and bearing layer position that the pile foundation may reach under certain conditions. Through this random sampling, various possible construction conditions and geological changes can be covered.

[0123] Through a large number of random sampling and recalculation, what is finally obtained is not a single rock-embedded depth value, but a possible rock-embedded depth range. This range reflects the variation of the rock-embedded depth of the pile foundation under different construction conditions and geological conditions.

[0124] Step S9, setting the optimization target in the BIM platform, generating multiple rock-embedded depth configuration schemes according to the possible rock-embedded depth range, using a genetic algorithm to evaluate the fitness of each rock-embedded depth scheme, determining the optimal scheme, and obtaining the final rock-embedded depth.

[0125] The BIM platform is not only a 3D modeling tool, it also has powerful analysis and optimization functions. In the design of the rock embedding depth of pile foundation, the setting of optimization target is the starting point of the whole optimization process. The optimization target is based on the specific needs and design requirements of the project, including multiple factors such as structural safety, economy and construction feasibility.

[0126] Structural safety: One of the optimization goals is to ensure that the pile foundation can meet the designed bearing capacity and stability requirements. This means that the rock embedment depth must be deep enough to ensure that the pile foundation can effectively transfer the load to the bearing layer and prevent structural problems such as settlement or tilting.

[0127] Economic efficiency: While ensuring safety, the optimization goal should also consider economic efficiency. For example, the deeper the rock embedding depth, the higher the required pile length and construction cost. Therefore, the optimization goal may include minimizing the rock embedding depth of the pile foundation to reduce construction costs while meeting the bearing capacity requirements.

[0128] Construction feasibility: The optimization goal also needs to consider the feasibility of construction. For example, the geological conditions, equipment capabilities, and construction technology at the construction site may affect the realization of the rock-embedded depth. Therefore, the optimization goal may include selecting a rock-embedded depth configuration that is easy to achieve in actual construction.

[0129] In the early Monte Carlo simulation, the possible rock-embedded depth range has been obtained, which reflects the possible rock-embedded depth distribution of pile foundations under different construction and geological conditions. Using this range, multiple rock-embedded depth configuration schemes can be generated in the BIM platform.

[0130] Generation of configuration schemes: Based on the possible range of rock-embedded depths, the BIM platform can automatically or manually generate multiple configuration schemes. These schemes may include different combinations of rock-embedded depths, pile lengths, and pile position arrangements. Each scheme corresponds to different construction conditions and economic costs.

[0131] Diversity of configurations: The generated configurations should cover a wide range of rock-embedded depth variations to ensure that the optimization process can explore a variety of possible design options. These options may include conservative designs (larger rock-embedded depth to ensure maximum safety) and aggressive designs (smaller rock-embedded depth to optimize cost).

[0132] Visualization in BIM platform: Each configuration scheme can be visualized in the BIM platform, and the spatial layout and geological adaptability of different rock embedment depth configurations can be intuitively viewed, so as to better understand and evaluate the advantages and disadvantages of each scheme.

[0133] Genetic algorithm is an optimization algorithm based on natural selection and genetic mechanism, which is particularly suitable for solving complex multi-objective optimization problems. In the optimization of pile foundation rock embedding depth, genetic algorithm simulates the biological evolution process and gradually optimizes the configuration scheme to find the optimal rock embedding depth scheme.

[0134] Generation of initial population: The genetic algorithm first considers the generated multiple rock-embedded depth configuration schemes as individuals in the initial population. Each individual represents a possible design scheme with a specific rock-embedded depth, pile length, and arrangement.

[0135] Definition of fitness function: The fitness function is a standard for measuring the pros and cons of each solution, which is set according to the optimization goal. The fitness function can comprehensively consider multiple factors such as structural safety (such as bearing capacity, safety factor, etc.), economy (such as material cost, construction cost, etc.) and construction feasibility (such as geological adaptability, construction difficulty, etc.). A solution with high fitness means it is closer to the optimization goal.

[0136] Genetic operations: Genetic algorithms simulate the biological evolution process through a series of selection, crossover and mutation operations, so that the solutions with higher fitness can preferentially pass on their "genes" to the next generation. The selection operation selects the best individuals into the next generation according to fitness; the crossover operation simulates the biological reproduction process and combines the characteristics of two solutions; the mutation operation introduces random changes to explore new design possibilities.

[0137] Iterative optimization: Through multiple iterations, the genetic algorithm gradually improves the overall fitness of the population and optimizes the rock embedding depth solution that is closer to the target. As the iterations proceed, the optimal solution gradually emerges and tends to be stable.

[0138] After multiple iterations and optimizations, the genetic algorithm will eventually converge to one or more optimal solutions, which represent the most suitable configuration of rock-embedded depth under the current optimization objectives and constraints.

[0139] Selection of the optimal solution: The BIM platform can automatically or manually select the optimal solution. The selection criteria are based on the maximum value of the fitness function or the balance point that reaches a certain design requirement. The optimal solution should achieve the best balance between structural safety, economy and construction feasibility.

[0140] Determination of the final rock-embedded depth: The rock-embedded depth in the optimal solution is the final designed rock-embedded depth. This depth will be used to guide the actual construction to ensure that the pile foundation design not only meets the structural requirements, but is also economically and constructively feasible.

[0141] Embodiment 2: The present invention also provides a BIM-assisted precast pile rock embedment depth analysis system, such as Figure 2As shown, it includes a three-dimensional modeling module, a finite element analysis module, a load solution module, a data extraction module, an estimation and judgment module, a deep calculation module, a simulation modeling module, an update calculation module and a deep optimization module.

[0142] Among them, the three-dimensional modeling module is used to construct a three-dimensional model of precast piles and geological layers in the BIM platform according to the design drawings and geological data to obtain a BIM model; the finite element analysis module is used to call the geometric and physical properties in the BIM model through the finite element analysis tool integrated in the BIM platform to generate a finite element model including precast piles, geological layers and boundary conditions; the load solution module is used to apply the load conditions of the precast piles in the finite element model, and solve the stress and displacement to obtain the solution results; the data extraction module is used to extract the stress distribution and the displacement of the pile bottom in the contact area between the pile foundation and the bearing layer from the solution results to obtain the finite element simulation data; the estimation and judgment module is used to use the linear interpolation method to make a preliminary estimate of the rock embedded depth of the finite element simulation data, and judge the pile foundation in the bearing layer according to the estimation results. whether the preliminary position meets the design requirements; a depth calculation module, which is used to combine the top surface elevation of the bearing layer with the pile foundation drilling depth through the BIM model to calculate the preliminary rock-embedded depth when the design requirements are met; a simulation modeling module, which is used to use the preliminary rock-embedded depth as the basic input of the Monte Carlo simulation, define the probability distribution of the pile foundation drilling depth and the top surface depth of the geological layer, and model the pile foundation drilling depth and the bearing layer depth according to the probability distribution; an update calculation module, which is used to recalculate and adjust the preliminary rock-embedded depth according to the pile foundation drilling depth and the top surface depth of the geological layer randomly extracted from the probability distribution, and obtain the rock-embedded depth range; a depth optimization module, which is used to use a genetic algorithm to evaluate the fitness of multiple rock-embedded depth configuration schemes generated according to the rock-embedded depth range, and select the optimal scheme to determine the final rock-embedded depth.

[0143] The specific implementation method of the above-mentioned BIM-assisted precast pile rock-embedded depth analysis system is the same as that of a BIM-assisted precast pile rock-embedded depth analysis method, and all further technical solutions in a BIM-assisted precast pile rock-embedded depth analysis method are fully introduced into a BIM-assisted precast pile rock-embedded depth analysis system.

[0144] Working principle: This invention can effectively improve the accuracy of pile foundation design by integrating design drawings and geological data in the BIM platform, constructing a three-dimensional model, and using finite element analysis tools to simulate and analyze the rock-embedded depth of prefabricated piles. The precise calculation and optimization of the rock-embedded depth ensures the reliable connection between the pile foundation and the bearing layer, thereby improving the safety and stability of the entire building structure and reducing the risk of building settlement and structural deformation.

[0145] In addition, the present invention generates multiple rock-embedded depth configuration schemes through optimization tools such as genetic algorithms in the BIM platform, and performs fitness evaluation and optimization on these schemes, so that the final rock-embedded depth design not only meets the structural requirements, but also takes into account the actual feasibility of construction. This process can effectively reduce the uncertainty in construction, optimize the construction plan, improve construction efficiency, and reduce rework and delays caused by improper design.

[0146] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0147] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0148] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0149] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0150] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A BIM-assisted precast pile rock embedment depth analysis method, characterized in that: The following steps are involved: Construct a 3D model of precast piles and geological layers in the BIM platform according to the design drawings and geological data to obtain a BIM model; The finite element analysis tool integrated in the BIM platform is used to call the geometric and physical properties in the BIM model to generate a finite element model including precast piles, geological layers and boundary conditions; Apply the load conditions of precast piles in the finite element model, solve the stress and displacement, and obtain the solution results; The stress distribution in the contact area between the pile foundation and the bearing layer and the displacement of the pile bottom are extracted from the solution results to obtain the finite element simulation data; The linear interpolation method is used to estimate the initial rock embedding depth of the finite element simulation data, and based on the estimation results, it is determined whether the initial position of the pile foundation in the bearing layer meets the design requirements; When the design requirements are met, the top elevation of the bearing layer and the pile foundation hole depth are combined through the BIM model to calculate the preliminary rock embedding depth; The preliminary rock-embedded depth is used as the basic input of the Monte Carlo simulation, the probability distribution of the pile foundation hole depth and the top depth of the geological layer is defined, and the pile foundation hole depth and the bearing layer depth are modeled according to the probability distribution; According to the pile foundation hole depth and the top surface depth of the geological layer randomly selected from the probability distribution, the preliminary rock-embedded depth is recalculated and adjusted to obtain the rock-embedded depth range; A genetic algorithm is used to evaluate the fitness of multiple rock-embedded depth configuration schemes generated according to the rock-embedded depth range, and the optimal scheme is selected to determine the final rock-embedded depth.

2. A BIM-assisted precast pile rock embedment depth analysis method according to claim 1, characterized in that: The geological data include the type, distribution, physical and mechanical properties of the strata, groundwater level and depth of the bearing layer.

3. A BIM-assisted precast pile rock embedment depth analysis method according to claim 1, characterized in that: The generation process of the finite element model is specifically as follows: Discretize the BIM model into finite elements according to the geometry of precast piles and geological layers; Use the physical property data in the BIM model to assign corresponding material properties to each unit; In the finite element model, boundary conditions are used to define the interaction between the structure and the external environment; Various loads are applied in the finite element model according to actual construction conditions and design requirements.

4. A BIM-assisted precast pile rock embedment depth analysis method according to claim 1, characterized in that: The load conditions include self-weight load, superstructure load, horizontal load and foundation reaction force.

5. The BIM-assisted precast pile rock embedment depth analysis method according to claim 1 is characterized in that: The specific process of solving stress and displacement is as follows: The finite element model is established as a set of linear or nonlinear equations to describe the mechanical equilibrium state of each unit under the external load, and the equation group is obtained; Solve the displacement of each node from the equation set to obtain the displacement result; Based on the stress-strain relationship, the stress distribution of each element is calculated from the displacement results.

6. The BIM-assisted precast pile rock embedment depth analysis method according to claim 1 is characterized in that: The stress in the contact area between the pile foundation and the bearing layer includes normal stress and shear stress.

7. The BIM-assisted precast pile rock embedment depth analysis method according to claim 1 is characterized in that: The displacement of the pile bottom includes vertical displacement and horizontal displacement.

8. The BIM-assisted precast pile rock embedment depth analysis method according to claim 1 is characterized in that: The preliminary rock-embedded depth is used as the basic input of the Monte Carlo simulation, the probability distribution of the pile foundation hole depth and the top surface depth of the geological layer is defined, and the pile foundation hole depth and the bearing layer depth are modeled according to the probability distribution, including: Define the probability distribution of pile foundation hole depth and top depth of geological layer based on historical data, field survey results and reference data; Monte Carlo simulation uses random sampling to draw multiple random samples from a probability distribution; For each random sample, the corresponding rock embedment depth is calculated.

9. The BIM-assisted precast pile rock embedment depth analysis method according to claim 1, characterized in that: The optimization objectives of selecting the best solution include structural safety, economy and construction feasibility.

10. A BIM-assisted precast pile rock embedment depth analysis system, characterized in that: The system is used to implement a BIM-assisted precast pile rock-embedded depth analysis method as described in any one of claims 1 to 9, comprising: A 3D modeling module is used to construct a 3D model of precast piles and geological layers in the BIM platform according to the design drawings and geological data to obtain a BIM model; Finite element analysis module, which is used to call the geometric and physical properties in the BIM model through the finite element analysis tool integrated in the BIM platform to generate a finite element model including precast piles, geological layers and boundary conditions; The load solving module is used to apply the load conditions of the precast piles in the finite element model, solve the stress and displacement, and obtain the solution results; The data extraction module is used to extract the stress distribution in the contact area between the pile foundation and the bearing layer and the displacement of the pile bottom from the solution results to obtain the finite element simulation data; The estimation and judgment module is used to estimate the initial rock embedding depth of the finite element simulation data using the linear interpolation method, and to determine whether the initial position of the pile foundation in the bearing layer meets the design requirements based on the estimation results; The depth calculation module is used to combine the top elevation of the bearing layer with the pile foundation hole depth through the BIM model to calculate the preliminary rock-embedded depth when the design requirements are met; The simulation modeling module is used to use the preliminary rock embedding depth as the basic input of the Monte Carlo simulation, define the probability distribution of the pile foundation hole depth and the top surface depth of the geological layer, and model the pile foundation hole depth and the bearing layer depth according to the probability distribution; An update calculation module is used to recalculate and adjust the preliminary rock-embedded depth according to the pile foundation hole depth and the top surface depth of the geological layer randomly extracted from the probability distribution to obtain the rock-embedded depth range; The depth optimization module is used to use a genetic algorithm to evaluate the fitness of multiple rock-embedded depth configuration schemes generated according to the rock-embedded depth range, and select the optimal scheme to determine the final rock-embedded depth.

Images