A foundation pit excavation deformation analysis method based on finite element model analysis

Abstract

The application provides a foundation pit excavation deformation analysis method based on finite element model analysis, and relates to the technical field of foundation pit deformation analysis, and comprises the following steps: establishing a foundation pit initial finite element model, dividing a grid and obtaining soil parameters of each unit; defining a plurality of continuous working conditions based on a construction plan, simulating a whole excavation process, calculating horizontal displacement, vertical settlement and support structure stress of activated units under each working condition, and forming a first prediction data set; in an actual excavation process, measured data of each activated unit under a corresponding working condition is obtained, compared with prediction data, and a relative error is calculated; if the error exceeds a threshold value, soil parameters are dynamically corrected through a back analysis algorithm, and a prediction model of the soil parameters changing with excavation depth is established; subsequent working condition parameters are predicted by using the updated parameters, a second prediction data set is obtained by re-performing finite element simulation, deformation characteristic values of each unit are calculated, and finally, dynamic evaluation and hierarchical early warning of foundation pit deformation risk are realized by using a risk level zoning method.

Description

Technical Field

[0001] This invention relates to the field of foundation pit deformation analysis technology, specifically a foundation pit excavation deformation analysis method based on finite element model analysis. Background Technology

[0002] With the rapid development of urban construction, foundation pit engineering is showing a trend of increasing scale and deepening excavation depth. Deformation control during foundation pit excavation is directly related to the safety of the project itself and the surrounding environment, and is a key and difficult issue in the field of geotechnical engineering. Traditional foundation pit deformation analysis often relies on empirical formulas or simplified calculation methods, which are difficult to accurately reflect the actual mechanical response under complex geological conditions and multi-process construction. This often leads to a large deviation between the predicted results and the actual monitoring data, and cannot provide accurate guidance for dynamic construction.

[0003] In the prior art, a method for studying foundation pit excavation deformation based on finite element model analysis, disclosed in CN116305412A, simulates and analyzes the foundation pit excavation process by establishing a three-dimensional finite element model, selecting a soil constitutive model, and substituting soil layer parameters. While this method can predict foundation pit deformation, its model parameters mainly rely on initial data from the geological survey report, lacking a mechanism for dynamic feedback and correction of model parameters based on on-site monitoring data during actual excavation. Furthermore, this prior art focuses on comparative analysis of different excavation methods, without explicitly proposing zonal inversion correction of the finite element model based on measured data, and using the corrected model for accurate prediction of subsequent working conditions and risk level classification. Therefore, there is room for further improvement in prediction accuracy and the refinement of risk control.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a method for analyzing the deformation of foundation pit excavation based on finite element model analysis, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: A method for analyzing the deformation of foundation pit excavation based on finite element model analysis, the specific steps of which include: Establish an initial finite element model of the target foundation pit, divide the model into multiple independent grid elements, and obtain the soil parameters corresponding to each independent grid element, including the initial void ratio, cohesion and internal friction angle of the soil. For each independent grid cell, define multiple continuous working conditions corresponding to the actual construction plan, simulate the entire process from the initial ground stress equilibrium to the completion of the foundation pit excavation, and use finite element numerical calculation to calculate the horizontal displacement value, vertical settlement value and support structure stress value of each activated independent grid cell under each working condition to form the first prediction dataset; During the actual excavation of the foundation pit, the actual horizontal displacement value, actual vertical settlement value, and actual support structure stress value of each activated independent grid cell under the current working conditions are obtained, and the relative error value is calculated in combination with the first prediction dataset. When the relative error value is greater than the preset error threshold, the soil parameters of each activated independent grid cell under the current working condition are updated by the inverse analysis algorithm, and a prediction model of the soil parameters changing with the excavation depth is established based on the soil parameter change data up to the current working condition. Based on the updated soil parameters and the prediction model, the soil parameter values ​​for each subsequent working condition are predicted. The predicted soil parameters are then used to perform finite element numerical simulations on the corresponding subsequent working conditions to obtain a second prediction dataset for each activated independent grid cell. Based on the second prediction dataset, the deformation characteristic values ​​of each activated independent grid cell are determined, and the deformation risk level of each activated independent grid cell is divided by the risk level partitioning method combined with a preset threshold.

[0007] Furthermore, based on the design drawings and engineering geological survey report of the target foundation pit, the geometric dimensions, soil layer distribution and support structure of the foundation pit are determined; an initial finite element model of the foundation pit excavation area is established using finite element preprocessing software, and the model is uniformly divided into multiple independent mesh elements of the same size. Each independent grid cell is assigned a unique cell number, which is sequentially numbered from the bottom to the top of the pit and from the center to the edge. This number is used to uniquely identify the spatial location of each independent grid cell. Multiple representative sampling points are set up within the foundation pit area. The arrangement of the representative sampling points follows the following principles: they are arranged at a first preset density in the central area of ​​the foundation pit, at a second preset density higher than the first preset density in the edge area of ​​the foundation pit, and additional sampling points are set up at the boundaries of different soil layers. For each representative sampling point, the initial void ratio of the soil was determined by the ring sampler method and the soil was tested according to the geotechnical test procedure. The cohesion and internal friction angle were determined by the direct shear test or triaxial compression test of the undisturbed soil sample. Based on the spatial coordinates of each sampling point and its corresponding soil parameter values, the Kriging interpolation algorithm is used to perform spatial interpolation calculations to obtain the soil parameter values ​​at the geometric center of each independent grid cell. The initial void ratio, cohesion, and internal friction angle of the soil obtained by interpolation are assigned to the corresponding independent mesh elements, thereby completing the parameter assignment of all independent mesh elements.

[0008] Furthermore, based on the excavation sequence, support installation sequence, and dewatering scheme determined in the construction organization design, multiple continuous working conditions corresponding to the actual construction plan are defined in the initial finite element model; each working condition is simulated sequentially according to the construction time sequence, the first working condition performs the initial ground stress balance calculation, and the subsequent working conditions sequentially simulate the earthwork excavation, support installation, and dewatering process. In the finite element numerical calculation of each working condition, the horizontal displacement value and vertical settlement value at the geometric center of each activated independent mesh element under the current working condition are extracted and recorded respectively, and the maximum principal stress value of the support structure element is taken as the stress value of the support structure. The horizontal displacement, vertical settlement, and support structure stress values ​​of all activated independent grid cells calculated for each working condition are integrated according to the cell number to form the first prediction dataset containing the complete simulation results of the construction process. The set of activated independent mesh elements changes with the working conditions. The activated independent mesh elements under each working condition refer to the soil elements and support structure elements that have not been excavated and removed and participate in the current mechanical calculation under the working condition in the finite element numerical simulation. Among them, the support structure elements refer to the independent mesh elements that are pre-established in the finite element model according to the form of the support structure and are used to simulate the mechanical behavior of the support structure. They exist in the model before the start of construction. The activated independent mesh elements are a subset dynamically determined from the set of independent mesh elements that includes all soil elements and support structure elements, based on the construction status of each working condition.

[0009] Furthermore, during the actual excavation of the foundation pit, according to the construction stages corresponding to the working conditions defined in step 2, actual monitoring data is collected through an on-site monitoring system. The actual monitoring system includes horizontal displacement monitoring points and vertical settlement monitoring points arranged at the geometric center of each activated independent grid unit, as well as stress sensors installed on the support structure and corresponding to the support structure units in the finite element model. Horizontal displacement is measured using a total station with polar coordinates, vertical settlement is measured using a level with a closed leveling route, and the stress of the support structure is collected using a vibrating wire stress gauge. The actual horizontal displacement, actual vertical settlement, and actual support structure stress values ​​collected from each monitoring point are mapped to the corresponding active independent mesh elements in the finite element model under the current working condition according to their spatial location. They are then categorized and integrated according to their corresponding independent mesh element numbers to form the first actual monitoring dataset, which is completely corresponding to the first prediction dataset in terms of spatial location and parameter type.

[0010] Furthermore, the first actual monitoring dataset and the first predicted dataset for each activated independent grid cell are compared parameter by parameter, and the relative error value is calculated for each activated independent grid cell. The formula used to calculate the relative error value is as follows: In the formula, Indicates the first The first activated independent grid cell The relative error values ​​of the deformation parameters, To activate the index of an independent grid cell; Indicates the first The activated independent grid cells in the first prediction dataset are the first... Deformation parameter values; Indicates the first The activated independent grid cell in the first actual monitoring dataset is the Deformation parameter values; An index for the types of deformation parameters; Specifically, when the activated independent grid cell is a soil cell, the deformation parameters include horizontal displacement and vertical settlement; when the activated independent grid cell is a support structure cell, the deformation parameters include horizontal displacement, vertical settlement, and support structure stress.

[0011] Based on the calculated relative error values ​​of each activated independent grid cell, a back analysis algorithm based on the least squares method is used to adjust the soil parameters in the model by region. The specific logic is as follows: Activated independent mesh elements whose relative error value for any deformation parameter is greater than a preset error threshold are marked as elements to be adjusted; The soil parameter vector is calibrated as Establish the objective function Its expression is as follows: In the formula, This is the soil parameter vector to be inverted, containing the soil void ratio, cohesion, and internal friction angle of all elements to be adjusted. The total number of units to be adjusted. The index of the unit to be adjusted; Indicates the first The arithmetic mean of the relative error values ​​of all deformation parameters of the unit to be adjusted; With minimizing the objective function as the optimization objective, the soil parameter vector of the unit to be adjusted is adjusted through an iterative algorithm. ; In each iteration, the updated soil parameters are used to recalculate the finite element model, obtain a new first prediction dataset and calculate the relative error value, until the relative error value of all activated independent mesh elements is less than the preset error threshold, and an updated finite element model is generated. Based on this, a predictive model for soil parameter changes with excavation depth is established using soil parameter change data up to the current working condition. Specifically, this involves collecting soil parameter values ​​updated by the back-analysis algorithm for each activated independent grid cell in the current and previous working conditions, and associating them with the excavation depth of the corresponding cell. Using a linear regression method, a linear prediction model is established for each soil parameter to be predicted, with the excavation depth as input and the corresponding predicted soil parameter value as output. The prediction model predicts soil parameters by analyzing a given excavation depth.

[0012] Furthermore, based on the updated finite element model and prediction model, the soil parameter values ​​in subsequent working conditions are predicted. Specifically, for each subsequent working condition, the current excavation depth is used as the input of the prediction model to calculate and output the corresponding predicted soil parameter values, including the predicted void ratio, predicted cohesion, and predicted internal friction angle. The predicted values ​​of soil parameters are updated to the active independent grid cells within the corresponding depth range. The numerical simulation of each subsequent construction condition after the current condition is performed to obtain the second prediction dataset of each active independent grid cell. The second prediction dataset is indexed by the condition and records the predicted values ​​of horizontal displacement, vertical settlement and support structure stress of each active independent grid cell under each subsequent condition. For each subsequent working condition, based on the second prediction dataset corresponding to that working condition, the deformation characteristic value of each activated independent grid cell under that working condition is determined according to the following formula: In the formula, Indicates the first under this working condition Deformation eigenvalues ​​of each activated independent mesh element; Indicates the first under this working condition The horizontal displacement prediction values ​​of each activated independent grid cell in the second prediction dataset; Indicates the first under this working condition Vertical settlement prediction values ​​for each activated independent grid cell in the second prediction dataset; Indicates the first under this working condition The predicted stress values ​​of the support structure in the second prediction dataset for each activated independent mesh cell; , and Assign a preset weight to the corresponding indicator, and satisfy the following conditions: ; Indicates product operation; It is a natural constant; When the activated independent mesh element is a soil element, the following conditions are met: , , .

[0013] Furthermore, for each subsequent working condition, based on the calculated deformation characteristic values ​​of each activated independent mesh element under that working condition, the deformation risk level is divided using a risk level zoning method, specifically as follows: Set the first threshold Second threshold ,and ; when At that time, the first Each activated independent grid cell is classified as a low-risk level; when At that time, the first Each activated independent grid cell is classified as a medium-risk level; when At that time, the first Each activated independent grid cell is classified as a high-risk level; Among them, threshold and The deformation control standards in the foundation pit engineering design specifications are determined by combining expert experience.

[0014] Compared with the prior art, the beneficial effects of the present invention are: This invention provides a reliable theoretical basis for foundation pit deformation analysis by establishing an initial finite element model and performing refined mesh generation; by defining continuous working conditions to simulate the complete construction process, it achieves dynamic simulation and prediction of the entire foundation pit excavation process; by acquiring actual deformation data through an on-site monitoring system and comparing it with the prediction results parameter by parameter, and by dynamically correcting soil parameters using a least squares-based back analysis algorithm, it significantly improves the accuracy and engineering applicability of the model; furthermore, based on the updated model, it accurately predicts subsequent working conditions and innovatively proposes a calculation formula for deformation characteristic values ​​and a risk level zoning method, realizing quantitative assessment and graded early warning of foundation pit deformation risk, providing a scientific basis and decision support for safety management during construction. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the overall method flow of the present invention; Figure 2 The graph shows the functional relationship between the predicted horizontal displacement, predicted vertical settlement, and deformation characteristic values. Figure 3 This is a graph showing the functional relationship between the predicted stress value and the deformation characteristic value of the support structure. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0017] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0018] Example: Please see Figures 1-3 The present invention provides a technical solution: A method for analyzing the deformation of foundation pit excavation based on finite element model analysis, the specific steps of which include: Step 1: Establish the initial finite element model of the target foundation pit, divide the model into multiple independent mesh elements, and obtain the soil parameters corresponding to each independent mesh element, including the initial void ratio, cohesion and internal friction angle of the soil. In this embodiment, based on the design drawings and engineering geological survey report of the target foundation pit, the geometric dimensions, soil layer distribution and support structure form of the foundation pit are determined; an initial finite element model of the foundation pit excavation area is established using finite element preprocessing software, and the model is uniformly divided into multiple independent mesh elements of the same size. Each independent grid cell is assigned a unique cell number, which is sequentially numbered from the bottom to the top of the pit and from the center to the edge. This number is used to uniquely identify the spatial location of each independent grid cell. Multiple representative sampling points are set up within the foundation pit area. The arrangement of the representative sampling points follows the following principles: they are arranged at a first preset density in the central area of ​​the foundation pit, at a second preset density higher than the first preset density in the edge area of ​​the foundation pit, and additional sampling points are set up at the boundaries of different soil layers. For each representative sampling point, the initial void ratio of the soil was determined by the ring sampler method and the soil was tested according to the geotechnical test procedure. The cohesion and internal friction angle were determined by the direct shear test or triaxial compression test of the undisturbed soil sample. Based on the spatial coordinates of each sampling point and its corresponding soil parameter values, the Kriging interpolation algorithm is used to perform spatial interpolation calculations to obtain the soil parameter values ​​at the geometric center of each independent grid cell. The initial void ratio, cohesion, and internal friction angle of the soil obtained by interpolation are assigned to the corresponding independent mesh elements, thereby completing the parameter assignment of all independent mesh elements.

[0019] In this embodiment, based on the foundation pit design drawings and survey report, a three-dimensional finite element model of the foundation pit excavation area is established using finite element preprocessing software. The model uses hexahedral elements for structured meshing, and the element size is uniformly determined to be 0.5 meters according to the geometric dimensions of the foundation pit and the calculation accuracy requirements to ensure the stability and efficiency of the calculation. Each element is assigned a unique number, and the numbering order is carried out layer by layer from the bottom of the foundation pit to the top surface. Within each layer, the numbering increases clockwise from the center of the foundation pit to the surrounding areas to ensure that the element position and number strictly correspond. The soil material constitutive model adopts the modified Cambridge model. Based on the soil layer distribution and physical and mechanical parameters in the survey report, the density, elastic modulus, and Poisson's ratio of each soil layer are set respectively. Through Kriging space interpolation, the initial void ratio, cohesion, and internal friction angle of the soil measured at the sampling points are accurately assigned to the geometric center of each element to complete the initialization of all model parameters, providing an accurate numerical basis for subsequent working condition simulation.

[0020] Step 2: Define multiple continuous working conditions corresponding to the actual construction plan for each independent grid cell, simulate the entire process from the initial ground stress equilibrium to the completion of the foundation pit excavation, and calculate the horizontal displacement value, vertical settlement value and support structure stress value of each activated independent grid cell under each working condition through finite element numerical calculation to form the first prediction dataset; In this embodiment, based on the excavation sequence, support installation sequence and dewatering scheme determined in the construction organization design, multiple continuous working conditions corresponding to the actual construction plan are defined in the initial finite element model; each working condition is simulated in sequence according to the construction time. The first working condition performs the initial ground stress balance calculation, and the subsequent working conditions simulate the earthwork excavation, support installation and dewatering process in sequence. In the finite element numerical calculation of each working condition, the horizontal displacement value and vertical settlement value at the geometric center of each activated independent mesh element under the current working condition are extracted and recorded respectively, and the maximum principal stress value of the support structure element is taken as the stress value of the support structure. The horizontal displacement, vertical settlement, and support structure stress values ​​of all activated independent grid cells calculated for each working condition are integrated according to the cell number to form the first prediction dataset containing the complete simulation results of the construction process. The set of activated independent mesh elements changes with the working conditions. The activated independent mesh elements under each working condition refer to the soil elements and support structure elements that have not been excavated and removed and participate in the current mechanical calculation under the working condition in the finite element numerical simulation. Among them, the support structure elements refer to the independent mesh elements that are pre-established in the finite element model according to the form of the support structure and are used to simulate the mechanical behavior of the support structure. They exist in the model before the start of construction. The activated independent mesh elements are a subset dynamically determined from the set of independent mesh elements that includes all soil elements and support structure elements, based on the construction status of each working condition.

[0021] During the excavation of the foundation pit, the geometry and stress state of the soil dynamically evolve with the excavation depth and construction procedures. The soil in the excavated area is removed and will no longer participate in subsequent mechanical calculations, while the soil in the unexcavated area continues to undergo stress adjustment and deformation accumulation. To accurately simulate this dynamic process, this invention introduces the concept of activated independent mesh elements in the constructed finite element model. These are defined as soil elements and support structure elements that have not been excavated and are participating in the current mechanical calculations under any working condition. The core of this definition is to realize the dynamic updating of the model's computational domain with the construction progress: each working condition only performs mechanical analysis on the currently existing soil and support structure, thereby truly reflecting the temporal changes in stress release, deformation development, and support stress during the excavation process. This avoids invalid calculations on the removed soil, ensuring the physical rationality and computational efficiency of the numerical simulation, and providing an accurate element-level data foundation for subsequent deformation prediction, parameter inversion, and risk assessment.

[0022] Step 3: During the actual excavation of the foundation pit, obtain the actual horizontal displacement value, actual vertical settlement value, and actual support structure stress value of each activated independent grid cell under the current working conditions, and calculate the relative error value in combination with the first prediction dataset; In this embodiment, during the actual excavation of the foundation pit, according to the construction stage corresponding to the working condition defined in step 2, actual monitoring data is collected through the on-site monitoring system. The actual monitoring system includes horizontal displacement monitoring points and vertical settlement monitoring points arranged at the geometric center of each activated independent grid unit, as well as stress sensors installed on the support structure and corresponding to the support structure units in the finite element model. Horizontal displacement is measured by polar coordinate method using a total station, vertical settlement is measured by closed leveling method using a level instrument, and support structure stress is collected by vibrating wire stress gauge. The actual horizontal displacement, actual vertical settlement, and actual support structure stress values ​​collected from each monitoring point are mapped to the corresponding active independent mesh elements in the finite element model under the current working condition according to their spatial location. They are then categorized and integrated according to their corresponding independent mesh element numbers to form the first actual monitoring dataset, which is completely corresponding to the first prediction dataset in terms of spatial location and parameter type.

[0023] The first actual monitoring dataset and the first predicted dataset of each activated independent grid cell are compared parameter by parameter, and the relative error value is calculated for each activated independent grid cell. The formula used to calculate the relative error value is as follows: In the formula, Indicates the first The first activated independent grid cell The relative error values ​​of the deformation parameters, To activate the index of an independent grid cell; Indicates the first The activated independent grid cells in the first prediction dataset are the first... Deformation parameter values; Indicates the first The activated independent grid cell in the first actual monitoring dataset is the Deformation parameter values; An index for the types of deformation parameters; Specifically, when the activated independent grid cell is a soil cell, the deformation parameters include horizontal displacement and vertical settlement; when the activated independent grid cell is a support structure cell, the deformation parameters include horizontal displacement, vertical settlement, and support structure stress.

[0024] For this formula, the dependent variable The larger the value, the more significant the first... The greater the deviation between the predicted deformation and the actual monitored value of each activated independent grid cell under a specific working condition, the lower the simulation accuracy of the model at that location and for that parameter, which may reflect significant differences between geological conditions, construction disturbances, or model parameters and actual conditions; conversely, if A smaller value indicates that the prediction matches the actual measurement well, the model has high reliability, and can be used to guide subsequent construction.

[0025] This part directly reflects the degree of deviation between the predicted value and the measured value. In actual engineering, this deviation may be due to the spatial variability of soil parameters, the difference between the construction process and the simulated working conditions, the simplification of the soil constitutive model, and monitoring errors, etc. The larger the value, the more significant the deviation between the local soil behavior and the simulation assumptions, which may be accompanied by actual situations such as soil stress release, abnormal stress on the support structure, or increased disturbance of the surrounding strata. Item indicates to Normalization was performed to eliminate the influence of parameter dimensions, forming a relative error, which can more objectively evaluate the model's adaptability to various deformation parameters.

[0026] This formula uses a relative error form, which is obtained by dividing by... Normalization avoids the problem of absolute error being affected by the range of parameter values, making deformation parameters of different positions and types comparable; taking the absolute value of the numerator ensures that the error is always positive, which facilitates subsequent threshold judgment and parameter inversion.

[0027] Step 4: When the relative error value is greater than the preset error threshold, update the soil parameters of each activated independent grid cell under the current working condition through the back analysis algorithm, and establish a prediction model of soil parameter changes with excavation depth based on the soil parameter change data up to the current working condition. In this embodiment, based on the calculated relative error values ​​of each activated independent grid cell, a back analysis algorithm based on the least squares method is used to adjust the soil parameters in the model by region. The specific logic is as follows: Activated independent mesh elements whose relative error value for any deformation parameter is greater than a preset error threshold are marked as elements to be adjusted; The soil parameter vector is calibrated as Establish the objective function Its expression is as follows: In the formula, This is the soil parameter vector to be inverted, containing the soil void ratio, cohesion, and internal friction angle of all elements to be adjusted. The total number of units to be adjusted. The index of the unit to be adjusted; Indicates the first The arithmetic mean of the relative error values ​​of all deformation parameters of the unit to be adjusted; With minimizing the objective function as the optimization objective, the soil parameter vector of the unit to be adjusted is adjusted through an iterative algorithm. ; In each iteration, the updated soil parameters are used to recalculate the finite element model, obtain a new first prediction dataset and calculate the relative error value, until the relative error value of all activated independent mesh elements is less than the preset error threshold, and an updated finite element model is generated. Based on this, a predictive model for soil parameter changes with excavation depth is established using soil parameter change data up to the current working condition. Specifically, this involves collecting soil parameter values ​​updated by the back-analysis algorithm for each activated independent grid cell in the current and previous working conditions, and associating them with the excavation depth of the corresponding cell. Using a linear regression method, a linear prediction model is established for each soil parameter to be predicted, with the excavation depth as input and the corresponding predicted soil parameter value as output. The prediction model predicts soil parameters by analyzing a given excavation depth.

[0028] In this embodiment, when the relative error value is greater than a preset error threshold, the measured values ​​of horizontal displacement, vertical settlement, and support structure stress of each activated independent grid unit are first compared with the predicted values ​​to identify the unit group with larger errors; specifically, the unit group with a relative error value exceeding the preset error threshold is identified. The elements are marked as elements to be adjusted, and their corresponding soil parameters in the current and previous working conditions are extracted; the objective function of the inverse analysis is constructed based on the least squares method. Iterative optimization using gradient descent method After each iteration, the updated parameters are substituted into the finite element model to recalculate the deformation under the current working condition, until the relative error of all activated elements is less than 1. Subsequently, using the current excavation depth as the horizontal axis and the optimized soil parameters of each unit as the vertical axis, linear regression models were established according to different parameter types. The resulting prediction models were used to describe the variation of soil parameters with excavation depth, providing a basis for parameter prediction in subsequent working conditions.

[0029] Step 5: Based on the updated soil parameters and the prediction model, predict the soil parameter values ​​for each subsequent working condition, and use the predicted soil parameters to perform finite element numerical simulations on the corresponding subsequent working conditions to obtain the second prediction dataset for each activated independent grid cell. In this embodiment, based on the updated finite element model and prediction model, the soil parameter values ​​in subsequent working conditions are predicted. Specifically, for each subsequent working condition, the current excavation depth is used as the input of the prediction model to calculate and output the corresponding predicted soil parameter values, including the predicted void ratio, predicted cohesion, and predicted internal friction angle. The predicted values ​​of soil parameters are updated to the active independent grid cells within the corresponding depth range. The numerical simulation of each subsequent construction condition after the current condition is performed to obtain the second prediction dataset of each active independent grid cell. The second prediction dataset is indexed by the condition and records the predicted values ​​of horizontal displacement, vertical settlement and support structure stress of each active independent grid cell under each subsequent condition. The second prediction dataset is a more accurate simulation result based on dynamically corrected soil parameters and prediction models. Compared with the initial prediction, it is closer to the actual response characteristics of the soil in the subsequent excavation process, and can more accurately predict the deformation and stress state in the pre-construction stage. The second prediction dataset provides a direct numerical basis for the subsequent calculation of deformation characteristic values, so that the calculation of deformation characteristic values ​​and the classification of risk levels are based on a newer and more reliable prediction foundation, thereby improving the timeliness and accuracy of early warning and realizing proactive and precise prevention and control of deformation risks in the subsequent construction stage of foundation pit engineering.

[0030] Step 6: Determine the deformation characteristic value of each activated independent grid cell based on the second prediction dataset, and use the risk level partitioning method combined with a preset threshold to classify the deformation risk level of each activated independent grid cell; In this embodiment, for each subsequent working condition, based on the second prediction dataset corresponding to that working condition, the deformation characteristic value of each activated independent grid cell under that working condition is determined according to the following formula: In the formula, Indicates the first under this working condition Deformation eigenvalues ​​of each activated independent mesh element; Indicates the first under this working condition The horizontal displacement prediction values ​​of each activated independent grid cell in the second prediction dataset; Indicates the first under this working condition Vertical settlement prediction values ​​for each activated independent grid cell in the second prediction dataset; Indicates the first under this working condition The predicted stress values ​​of the support structure in the second prediction dataset for each activated independent mesh cell; , and The preset weights for the corresponding indicators, and satisfy ; Indicates product operation; It is a natural constant; When the activated independent mesh element is a soil element, no support structure stress will be generated, therefore... The item will not participate in the calculation. Set to zero, satisfying , , .

[0031] set up The reason is that, in the analysis of foundation pit deformation, horizontal displacement is usually the most sensitive and intuitive precursor to instability, and has the most significant impact on the overall stability of the foundation pit and the surrounding environment; vertical displacement is the second most important, mainly reflecting the soil compression and bearing state; the stress of the support structure, as an indirect indicator, reflects the stress state of the structure, but it needs to be comprehensively evaluated in conjunction with displacement parameters.

[0032] For this formula, the dependent variable Used to characterize the The severity of deformation and risk level of each activated independent mesh element under the current working conditions. The larger the value, the more significant the deformation and stress state of the unit, and the higher the potential risk of instability or failure; conversely, The smaller the value, the more slight the deformation, the more reasonable the structural stress, and the more safe and controllable the condition.

[0033] When the absolute value of the predicted horizontal displacement When the pressure increases, it directly leads to the loosening of the soil on the sidewalls of the foundation pit and an increase in the lateral pressure on the support structure, significantly increasing the overall risk of instability. Therefore, by... The function reflects its diminishing marginal returns; when the absolute value of the vertical settlement prediction is... As the pit expands, it may cause the bottom of the pit to heave and the surrounding surface to subside. This project... The function reflects the effect of its nonlinear growth; stress concentration may lead to yielding or failure of support components. It uses a sigmoid function This is used to simulate its sensitive characteristics of slow low-stress change and sharp high-stress increase.

[0034] Table 1: Statistical Table of Deformation Characteristic Values Analysis of the second prediction data of the 15 groups of units in Table 1 shows that the numerical level of the deformation characteristic value of each unit steadily increases with the overall increase of the predicted horizontal displacement, vertical settlement and stress value of the support structure. This trend indicates that the deformation characteristic value calculation formula proposed in this invention can effectively integrate multi-dimensional deformation response and normalize it into a comprehensive risk assessment index. The change law of this index intuitively reflects the potential deformation accumulation effect and mechanical state evolution of the foundation pit soil and support structure system under different spatial locations or different construction stages.

[0035] Furthermore, by combining the risk level zoning method adopted in this invention, the deformation characteristic values ​​calculated by each unit can be compared with preset thresholds, thereby clearly dividing the entire grid unit of the foundation pit into three deformation risk levels: low, medium, and high. This analysis result not only realizes the quantitative assessment and spatial visualization of the overall and local risk status of the foundation pit, but more importantly, it provides a key decision-making basis for dynamic safety management during construction. Based on this zoning result, on-site management personnel can implement key monitoring and pre-reinforcement measures for high-risk areas and strengthen patrols for medium-risk areas, thereby achieving accurate early warning and graded prevention and control of foundation pit engineering risks, and improving the initiative and scientific nature of construction safety.

[0036] For each subsequent working condition, based on the calculated deformation characteristic values ​​of each activated independent mesh element under that working condition, the deformation risk level is divided using a risk level zoning method, specifically as follows: Set the first threshold Second threshold ,and ; when At that time, the first Each activated independent grid cell is classified as a low-risk level; when At that time, the first Each activated independent grid cell is classified as a medium-risk level; when At that time, the first Each activated independent grid cell is classified as a high-risk level; Among them, threshold and The deformation control standards in the foundation pit engineering design specifications are determined by combining expert experience.

[0037] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0038] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0039] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0040] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for analyzing the deformation of foundation pit excavation based on finite element model analysis, characterized in that, Specifically, it includes: Establish an initial finite element model of the target foundation pit, divide the model into multiple independent grid elements, and obtain the soil parameters corresponding to each independent grid element, including the initial void ratio, cohesion and internal friction angle of the soil. For each independent grid cell, define multiple continuous working conditions corresponding to the actual construction plan, simulate the entire process from the initial ground stress equilibrium to the completion of the foundation pit excavation, and use finite element numerical calculation to calculate the horizontal displacement value, vertical settlement value and support structure stress value of each activated independent grid cell under each working condition to form the first prediction dataset; During the actual excavation of the foundation pit, the actual horizontal displacement value, actual vertical settlement value, and actual support structure stress value of each activated independent grid cell under the current working conditions are obtained, and the relative error value is calculated in combination with the first prediction dataset. When the relative error value is greater than the preset error threshold, the soil parameters of each activated independent grid cell under the current working condition are updated by the inverse analysis algorithm, and a prediction model of the soil parameters changing with the excavation depth is established based on the soil parameter change data up to the current working condition. Based on the updated soil parameters and the prediction model, the soil parameter values ​​for each subsequent working condition are predicted. The predicted soil parameters are then used to perform finite element numerical simulations on the corresponding subsequent working conditions to obtain a second prediction dataset for each activated independent grid cell. Based on the second prediction dataset, the deformation characteristic values ​​of each activated independent grid cell are determined, and the deformation risk level of each activated independent grid cell is divided by the risk level partitioning method combined with a preset threshold.

2. The method for analyzing the deformation of foundation pit excavation based on finite element model analysis according to claim 1, characterized in that: Based on the design drawings and engineering geological survey report of the target foundation pit, determine the geometric dimensions, soil layer distribution and support structure of the foundation pit; The initial finite element model of the foundation pit excavation area was established using finite element preprocessing software, and the model was uniformly divided into multiple independent mesh elements of the same size. Each independent grid cell is assigned a unique cell number, which is sequentially numbered from the bottom to the top of the pit and from the center to the edge. This number is used to uniquely identify the spatial location of each independent grid cell. Multiple representative sampling points are set up within the foundation pit area. The arrangement of the representative sampling points follows the following principles: they are arranged at a first preset density in the central area of ​​the foundation pit, at a second preset density higher than the first preset density in the edge area of ​​the foundation pit, and additional sampling points are set up at the boundaries of different soil layers. For each representative sampling point, the initial void ratio of the soil was determined by the ring sampler method and the soil was tested according to the geotechnical test procedure. The cohesion and internal friction angle were determined by the direct shear test or triaxial compression test of the undisturbed soil sample. Based on the spatial coordinates of each sampling point and its corresponding soil parameter values, the Kriging interpolation algorithm is used to perform spatial interpolation calculations to obtain the soil parameter values ​​at the geometric center of each independent grid cell. The initial void ratio, cohesion, and internal friction angle of the soil obtained from interpolation are assigned to the corresponding independent mesh elements, thereby completing the parameter assignment for all independent mesh elements.

3. The method for analyzing the deformation of foundation pit excavation based on finite element model analysis according to claim 2, characterized in that: Based on the excavation sequence, support installation sequence, and dewatering scheme determined in the construction organization design, multiple continuous working conditions corresponding to the actual construction plan are defined in the initial finite element model. Each working condition is simulated in sequence according to the construction time. The first working condition performs the initial ground stress balance calculation, and the subsequent working conditions simulate the earthwork excavation, support installation, and dewatering process in sequence. In the finite element numerical calculation of each working condition, the horizontal displacement value and vertical settlement value at the geometric center of each activated independent mesh element under the current working condition are extracted and recorded respectively, and the maximum principal stress value of the support structure element is taken as the stress value of the support structure. The horizontal displacement, vertical settlement, and support structure stress values ​​of all activated independent grid cells calculated for each working condition are integrated according to the cell number to form the first prediction dataset containing the complete simulation results of the construction process. The set of activated independent mesh elements changes with the working conditions. The activated independent mesh elements under each working condition refer to the soil elements and support structure elements that have not been excavated and removed and participate in the current mechanical calculation under the working condition in the finite element numerical simulation. Among them, the support structure elements refer to the independent mesh elements that are pre-established in the finite element model according to the form of the support structure and are used to simulate the mechanical behavior of the support structure. They exist in the model before the start of construction. The activated independent mesh elements are a subset dynamically determined from the set of independent mesh elements that includes all soil elements and support structure elements, based on the construction status of each working condition.

4. The method for analyzing the deformation of foundation pit excavation based on finite element model analysis according to claim 1, characterized in that: During the actual excavation of the foundation pit, according to the construction stages corresponding to the working conditions defined in step 2, actual monitoring data is collected through the on-site monitoring system. The actual monitoring system includes horizontal displacement monitoring points and vertical settlement monitoring points arranged at the geometric center of each activated independent grid unit, as well as stress sensors installed on the support structure and corresponding to the support structure units in the finite element model. Horizontal displacement is measured using a total station with polar coordinates, vertical settlement is measured using a level with a closed leveling route, and the stress of the support structure is collected using a vibrating wire stress gauge. The actual horizontal displacement, actual vertical settlement, and actual support structure stress values ​​collected from each monitoring point are mapped to the corresponding active independent mesh elements in the finite element model under the current working condition according to their spatial location. They are then categorized and integrated according to their corresponding independent mesh element numbers to form the first actual monitoring dataset, which is completely corresponding to the first prediction dataset in terms of spatial location and parameter type.

5. The method for analyzing the deformation of foundation pit excavation based on finite element model analysis according to claim 4, characterized in that: The first actual monitoring dataset and the first predicted dataset for each activated independent grid cell are compared parameter by parameter. For each activated independent grid cell, the relative error value is calculated. The formula for calculating the relative error value is as follows: In the formula, Indicates the first The first activated independent grid cell The relative error values ​​of the deformation parameters, To activate the index of an independent grid cell; Indicates the first The activated independent grid cells in the first prediction dataset are the first... One deformation parameter value; Indicates the first The activated independent grid cell in the first actual monitoring dataset is the Deformation parameter values; An index for the types of deformation parameters; Specifically, when the activated independent grid cell is a soil cell, the deformation parameters include horizontal displacement and vertical settlement; when the activated independent grid cell is a support structure cell, the deformation parameters include horizontal displacement, vertical settlement, and support structure stress.

6. The method for analyzing the deformation of foundation pit excavation based on finite element model analysis according to claim 5, characterized in that: Based on the calculated relative error values ​​of each activated independent grid cell, a back analysis algorithm based on the least squares method is used to adjust the soil parameters in the model by region. The specific logic is as follows: Activated independent mesh elements whose relative error value for any deformation parameter is greater than a preset error threshold are marked as elements to be adjusted; The soil parameter vector is calibrated as Establish the objective function Its expression is as follows: In the formula, This is the soil parameter vector to be inverted, containing the soil void ratio, cohesion, and internal friction angle of all elements to be adjusted. The total number of units to be adjusted. The index of the unit to be adjusted; Indicates the first The arithmetic mean of the relative error values ​​of all deformation parameters of the unit to be adjusted; With minimizing the objective function as the optimization objective, the soil parameter vector of the unit to be adjusted is adjusted through an iterative algorithm. ; In each iteration, the updated soil parameters are used to recalculate the finite element model, obtain a new first prediction dataset and calculate the relative error value, until the relative error value of all activated independent mesh elements is less than the preset error threshold, and an updated finite element model is generated. Based on this, a predictive model for the change of soil parameters with excavation depth is established based on the soil parameter change data up to the current working condition. Specifically, the soil parameter values ​​of each activated independent grid cell updated by the back analysis algorithm in the current working condition and previous working conditions are collected and correlated with the excavation depth of the corresponding cell. Using the linear regression method, a linear prediction model is established for each soil parameter to be predicted, with the excavation depth as input and the predicted value of the corresponding soil parameter as output. The prediction model predicts the soil parameter by analyzing the given excavation depth.

7. The method for analyzing the deformation of foundation pit excavation based on finite element model analysis according to claim 6, characterized in that: Based on the updated finite element model and prediction model, the soil parameter values ​​in subsequent working conditions are predicted. Specifically, for each subsequent working condition, the current excavation depth is used as the input of the prediction model to calculate and output the corresponding predicted soil parameter values, including the predicted void ratio, predicted cohesion, and predicted internal friction angle. The predicted values ​​of soil parameters are updated to the active independent grid cells within the corresponding depth range. The numerical simulation of each subsequent construction condition after the current condition is performed to obtain the second prediction dataset of each active independent grid cell. The second prediction dataset is indexed by the condition and records the predicted values ​​of horizontal displacement, vertical settlement and support structure stress of each active independent grid cell under each subsequent condition. For each subsequent working condition, based on the second prediction dataset corresponding to that working condition, the deformation characteristic value of each activated independent grid cell under that working condition is determined according to the following formula: In the formula, Indicates the first under this working condition Deformation eigenvalues ​​of each activated independent mesh element; Indicates the first under this working condition The horizontal displacement prediction values ​​of each activated independent grid cell in the second prediction dataset; Indicates the first under this working condition Vertical settlement prediction values ​​for each activated independent grid cell in the second prediction dataset; Indicates the first under this working condition The predicted stress values ​​of the support structure in the second prediction dataset for each activated independent mesh cell; , and The preset weights for the corresponding indicators, and satisfy ; Indicates product operation; It is a natural constant; When the activated independent mesh element is a soil element, the following conditions are met: , , .

8. The method for analyzing the deformation of foundation pit excavation based on finite element model analysis according to claim 7, characterized in that: For each subsequent working condition, based on the calculated deformation characteristic values ​​of each activated independent mesh element under that working condition, the deformation risk level is divided using a risk level zoning method, specifically as follows: Set the first threshold Second threshold ,and ; when At that time, the first Each activated independent grid cell is classified as a low-risk level; when At that time, the first Each activated independent grid cell is classified as a medium-risk level; when At that time, the first Each activated independent grid cell is classified as a high-risk level; Among them, threshold and The deformation control standards in the foundation pit engineering design specifications are determined by combining expert experience.

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