An optimization method for a scheme of servoing internal support axial force exertion during foundation pit construction period

Abstract

The application discloses a kind of optimization methods for pit construction period servo inner support axial force exertion scheme, and the influence coefficient matrix of servo support axial force to displacement and bending moment is calculated by obtaining benchmark displacement, axial force and bending moment through traditional prestress design;Four kinds of servo optimization design working conditions are defined, and by combining support axial bearing capacity design value, enclosure structure bending resistance bearing capacity design value, traditional design axial force historical peak value and bending moment peak value, the safety constraint spectrum from conservative to aggressive is constructed;With the minimization of the maximum displacement of enclosure structure as the target, with each lane support axial force adjustment amount as the decision variable, a linear programming optimization model is constructed;Solving the model can obtain the optimal axial force adjustment target value under different working conditions;The application realizes the quantitative design of servo axial force, reveals the load redistribution mechanism of "decrease on the top and increase on the bottom", and significantly improves the deformation control efficiency compared with the traditional constant pressure maintaining mode.

Description

Technical Field

[0001] This invention relates to the field of geotechnical engineering foundation pit support design and active control technology, and in particular to an optimization method for the servo internal support axial force application scheme during foundation pit construction. Background Technology

[0002] Hydraulic servo support systems, due to their ability to actively and precisely apply and adjust support axial forces, have become an important technical means for controlling the deformation of deep and large foundation pits. However, current engineering applications of servo systems face the following prominent problems: 1) The design did not specify a specific usage plan, and the field mostly used simple control logic such as traditional "constant force" or "pressure holding", which downgraded the use of advanced equipment; 2) Lack of quantitative evaluation of the additional deformation control potential brought by introducing a servo system on the basis of existing traditional designs; 3) There is a lack of theoretically optimal axial force control schemes that match different engineering safety requirements.

[0003] Studies have shown that while a servo steel support system can effectively limit the maximum deformation of the wall when the axial force control threshold is too high, it can also lead to a significant increase in the bending moment of the wall at the support on the outside of the pit, posing a risk of bending failure of the retaining wall. This highlights the importance of scientifically setting servo control parameters.

[0004] The patent application filed by Shanghai Jiao Tong University, entitled "Method for Determining Axial Force of Servo Steel Support System with Maximum Displacement as Control Target" (CN108052782A), treats the servo as a hybrid spring model and obtains a support axial force design scheme under the design target by iterative calculation using the finite element difference method. The main point of this patent is that after determining the support axial force, during the construction stage, the construction process is optimized based on the difference between the load force of the construction structure and the design value to achieve a better control result than the design scheme.

[0005] Essentially, this is a "servo design" problem: given the decision to use servo hardware, how to scientifically set its control objectives to synergistically optimize the three core objectives of "deformation control", "support axial force safety" and "enclosure structure bending moment safety"; existing design methods or construction schemes lack a unified mathematical framework to solve this problem, which prevents the huge potential of servo systems from being fully and scientifically explored. Summary of the Invention

[0006] The purpose of this invention is to provide an optimized method for applying servo-driven internal support axial force during the construction of foundation pits.

[0007] The problem to be solved by this invention is to overcome the shortcomings of existing servo support axial force setting that relies on experience, cannot quantify and evaluate potential, and cannot flexibly adapt to different safety level requirements. This invention provides a theoretically rigorous, quantifiable, and adaptable method for optimizing the design and use of foundation pit servo support axial force.

[0008] An optimization method for applying servo-driven internal support axial force during foundation pit construction is proposed, and the technical solution adopted is as follows: Step 1: Benchmark Acquisition and Performance Metric Collection Through mechanical analysis of the entire construction process using traditional prestressed design, the baseline displacement distribution of the retaining structure, the baseline axial force and baseline bending moment distribution of each servo support are obtained under various construction conditions. At the same time, the mechanical performance indicators of the on-site servo system and construction materials are collected, including the design value of the axial bearing capacity of the support, the design value of the bending bearing capacity of the retaining structure, and the initial prestress value of the support.

[0009] Step 2: Constructing the Influence Coefficient Matrix The unit load method is used to calculate the influence coefficients of servo support axial force on displacement and bending moment. Displacement influence coefficient matrices and bending moment influence coefficient matrices are established to clarify the displacement increment caused by applying a unit force to the i-th support at the j-th displacement calculation point and the bending moment increment caused by applying a unit force at the k-th bending moment control section.

[0010] Step 3: Define multiple safety constraint operating conditions (construct performance spectrum) Based on a comparison of on-site material parameters and design specifications, four servo optimization design conditions are defined, forming a control performance spectrum ranging from absolutely safe and conservative to theoretically maximum potential: Condition A (with ample axial force): The upper limit of axial force is taken as the design value of the axial bearing capacity of the support, and the upper limit of bending moment is taken as the peak value of the traditional design bending moment; Condition B (with ample bending moment): The upper limit of axial force is taken as the historical peak value of axial force in traditional design, and the upper limit of bending moment is taken as the design value of the bending bearing capacity of the enclosure structure. Condition C (both have margin): The upper limit of axial force is taken as the design value of the axial bearing capacity of the support, and the upper limit of bending moment is taken as the design value of the bending bearing capacity of the enclosure structure. Condition D (Absolutely safe): The upper limit of axial force is taken as the historical peak value of axial force in traditional design, and the upper limit of bending moment is taken as the peak value of bending moment in traditional design; The lower limit of axial force for each working condition is taken as the initial prestress value of the support.

[0011] Step 4: Construction and Solution of Linear Programming Optimization Model Using the axial force adjustment of each installed internal support under this working condition as the decision variable, a linear programming model is constructed: Objective function: minimize the maximum calculated displacement of the enclosure structure; Constraints: including displacement-related constraints, as well as axial force safety constraints and bending moment safety constraints determined by the selected working condition. Solve the model to obtain the optimal servo support axial force adjustment amount and adjustment time.

[0012] Step 5: Comparison of Solution Output and Performance The target value for adjusting the axial force of each servo support is output as a loading command. At the same time, the calculation results under different working conditions are quantitatively compared with traditional prestressed design and common servo control modes to form a comparison spectrum of control performance and safety level, which assists in engineering decision-making.

[0013] Furthermore, the peak bending moment and the historical peak axial force of the traditional design are obtained through mechanical analysis of the entire construction process of the traditional prestressed design. They represent the maximum values ​​that the bending moment of the retaining structure and the axial force of each support have reached during the entire construction process, and are used as the baseline for safety constraints.

[0014] Furthermore, the method employs a step-by-step static optimization strategy; the continuous construction process of the foundation pit is discretized into multiple typical construction conditions, and the above optimization calculations are performed independently for each construction condition; finally, a complete set of servo support axial force optimization design schemes that are synchronized with the construction process and are divided into different conditions is output.

[0015] Furthermore, the standard form of the linear programming optimization model is as follows: An auxiliary variable u is introduced to represent the maximum displacement of the optimized enclosure structure; The constraints are specified as follows: Displacement-related constraints: Axial force safety constraints: Bending moment safety constraints: ; in This represents the prestress applied value for each support. and This represents the upper limit of axial force and bending moment, and its value is determined by the selected servo optimization design conditions.

[0016] Furthermore, the method also includes a performance comparison analysis step; the optimal displacement control effect calculated under different servo optimization design conditions is quantitatively compared with the displacement value of traditional prestressed design, as well as the displacement values ​​under common servo control modes such as constant pressure holding, natural growth followed by locking, and interval control, to form a comparison spectrum of control performance and safety level, which is used to support engineering decision-making.

[0017] The beneficial effects of this invention are: it establishes a quantitative theoretical framework for servo design; for the first time, it combines linear programming optimization with the definition of multiple safety constraint working conditions, providing a rigorous mathematical tool for the scientific setting of servo support axis force, and realizing a leap from empirical judgment to theoretical calculation; It achieves the integration of potential assessment and scheme generation: it can not only quantitatively calculate the theoretical optimal deformation control effect that the servo system can achieve under different safety constraints, i.e., potential assessment, but also simultaneously output the specific servo loading scheme to achieve the effect, i.e., scheme generation. It provides a complete decision-making spectrum: the four defined working conditions cover typical engineering requirements ranging from "absolute safety and conservatism" to "maximum theoretical potential". Designers can intuitively select and obtain the corresponding optimal design scheme according to the project's safety level requirements. The mechanism of collaborative optimization is revealed: the optimal solution often shows the redistribution law of axial force in the system. Theoretically, it reveals the mechanical essence of the servo system achieving global optimization under safety constraints through collaborative adjustment, which has guiding significance for engineering practice. Attached Figure Description

[0018] Figure 1 This is a flowchart of an optimization method for applying servo-driven internal support axial force during the construction phase of a foundation pit. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] In order to achieve the above objectives, Figure 1 A flowchart of an optimization method for applying servo-driven internal support axial force during the foundation pit construction period is presented.

[0021] In addition, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can represent three cases: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally indicates that the related objects before and after it are in an "or" relationship.

[0022] Example 1 The implementation of the method of the present invention follows Figure 1 The four stages shown: Phase 1: Complete the design and full-process numerical simulation of traditional prestressed foundation pit, extract benchmark state data and calculate influence coefficients; Phase 2: Based on the engineering safety requirements, select or define specific servo optimization design conditions (A, B, C, D). The third stage: For each construction condition, construct and solve the corresponding linear programming optimization model to obtain the optimal axial force adjustment scheme for each condition; Phase 4: Summarize and output a complete servo loading solution, and compare its performance with traditional designs and common patterns to support engineering decisions.

[0023] The four operating conditions are clearly located in a coordinate system composed of "axial force constraint level" and "bending moment constraint level", forming a complete safety control spectrum: Condition D (Absolutely Safe): Located in the lower left quadrant, both axial force and bending moment constraints use the most conservative "historical peak values," prohibiting the introduction of any new internal force risks. Its constraint expression is as follows: and ; Condition B (Moment Surplus): Located in the upper left quadrant, axial force constraints are conservative (historical peak value), but the bending moment is allowed to utilize the material's bending capacity to a surplus. Its constraint expression is as follows: and ; Condition A (Ample Axial Force): Located in the lower right quadrant, allowing for excess axial force utilizing material bearing capacity, but with conservative bending moment constraints (traditional peak value). Its constraint expression is as follows: and This working condition actively explores the support potential without introducing new bending moment risks, which has outstanding advantages in engineering practice and is the recommended preferred solution of this invention. Working condition C (with material surplus in both): Located in the upper right quadrant, it utilizes material surplus for both axial force and bending moment, resulting in the most relaxed constraints and the greatest theoretical potential; its constraint expression is as follows: and .

[0024] Taking the construction condition of excavation to the bottom of the pit in the embodiment as an example, the implementation process of the present invention will be described in detail.

[0025] Step S1: Defining Operating Conditions This embodiment focuses on analyzing working condition A (with ample axial force), whose specific safety constraints are: Upper limit of axial force: Design value of axial bearing capacity of the support , , ; Lower limit of axial force: Initial prestress value of the support , , ; Upper limit of bending moment: peak bending moment in traditional design .

[0026] Step S2: Baseline Acquisition Key benchmark data for the pit bottom working condition were obtained through traditional prestressed (Pre) design and finite element simulation of elastic foundation beams throughout the entire process: Reference displacement (3 calculation points): mm; Reference axial force (3 supports): kN; Reference bending moment (3 control sections): kN·m; Influence coefficient matrix (obtained using the unit load method): Displacement influence coefficient matrix : ; Bending moment influence coefficient matrix : ; Safety threshold parameters: Design value of support bearing capacity: kN; Initial prestress value: kN; Peak bending moment in traditional design: kN·m; Design values ​​of flexural bearing capacity of the building envelope: kN·m; Historical peak axial force in traditional design: kN.

[0027] Step S3: Model Building (Condition A) For the pit bottom working condition and the safety constraints of working condition A, the following linear programming model is constructed: Decision variables: , ; Objective function: ; Constraints: Displacement-related constraints: ; Axial force safety constraints: ; Bending moment safety constraints: .

[0028] Step S4: Solving and Output Solve the above model using a linear programming solver (such as MATLAB's linprog function) to obtain the optimal solution: kN, mm; Based on this, the target design value of the servo support axial force under working condition A is calculated: kN; Results analysis: Deformation control effect: After optimization, the maximum displacement was reduced from 18.3mm in the traditional design to 8.5mm, a reduction rate of 53.6%, and the deformation control effect was significant.

[0029] Axial force distribution characteristics: exhibits a typical "decreasing at the top and increasing at the bottom" pattern. The axial force of the upper support (S1) was reduced to near the initial prestress value (99.9 kN). The axial force of the central support (S2) is moderately reduced (270.3kN). The axial force of the lower support (S3) increased significantly to its design load capacity (800.0 kN). Mechanical Mechanism: This scheme actively reduces the axial force of the upper support, transferring more excavation load to the lower high-bearing-capacity support, thereby achieving optimized load redistribution. Under the premise of strictly ensuring that the bending moment does not exceed the traditional peak value, it suppresses the deformation of the retaining structure to the greatest extent.

[0030] Step S5: Performance Comparison Analysis Pre Traditional design (benchmark) 18.3 0% Traditional static design Mode E Constant pressure holding (locked at historical peak value) 16.4 10.4% Common patterns may increase bending moment Mode F Locked after natural growth 16.4 10.4% Common patterns Operating Condition D Absolutely safe (this invention) 17.8 2.7% Most conservative, with limited effectiveness Operating Condition B The bending moment has a margin of safety (this invention) 14.2 22.4% Utilizing the excess bending moment Operating Condition A There is excess axial force (in this invention) 8.5 53.6% Recommendation: Balance between safety and performance Operating Condition C Both have surplus (this invention). 7.9 56.8% Theoretical potential is the greatest To comprehensively evaluate the superiority of the method of the present invention, the modified control effects of various control strategies are compared and analyzed, as shown in the table above.

[0031] Common servo control modes (E, F) can only achieve an improvement of about 10.4%, and lack systematic safety constraints. The working condition spectrum defined in this invention clearly shows the trade-off between safety constraints and control performance. Working condition A (with ample axial force) achieves a significant reduction in deformation of 53.6% under the strict safety constraint of "bending moment not exceeding the traditional peak value". It achieves the best balance between safety and control performance and is the core recommended solution of this invention.

[0032] After installing S1 S1 120.5 3.2 Excavate to -0.25m S1 115.8 5.6 After installing S2 S1, S2 [118.2, 180.3] 4.8 Excavate to -0.50m S1, S2 [105.6, 220.5] 7.2 After installing S3 S1, S2, S3 [102.3, 195.8, 350.6] 6.5 Excavate to the bottom of the pit S1, S2, S3 [99.9, 270.3, 800.0] 8.5 This invention employs a "step-by-step static optimization" strategy, requiring the repeated execution of steps S1-S4 for each typical working condition throughout the construction process (e.g., after each support is installed, after each excavation step). The final output is a complete "Working Condition Servo Support Axial Force Optimization Design Table," as shown in the table above.

[0033] By inputting the design scheme shown in the table above into the servo control system, the following can be achieved: Precise control: In each construction condition, the servo system automatically operates according to preset parameters. The value applies or adjusts the support axial force; Safety Assurance: Since the solution is based on strict linear programming optimization and meets the safety constraints of working condition A (bending moment does not exceed the traditional peak value), the implementation process will theoretically not introduce new bending moment risks; The expected results are: the deformation control effect can be expected to reach the theoretical calculation value, which is significantly better than traditional design; System collaboration: Optimization schemes often exhibit a "reduction at the top and increase at the bottom" axial force redistribution pattern, which theoretically reveals the mechanical essence of servo systems achieving global optimization under safety constraints through collaborative adjustments.

[0034] This embodiment fully demonstrates the complete process of the method of the present invention, from data preparation, model building, optimization solution to result application; practice has proven that: The method is feasible: the linear programming model can be solved efficiently, yielding the theoretically optimal solution; Significant results: Compared with traditional design, deformation control is significantly improved (53.6%). Safety and controllability: Optimization is performed under clear hard safety constraints (such as the bending moment limit in condition A), and the results are reliable; Clear decision-making: By comparing the performance of four operating conditions, a clear scientific basis is provided for engineering decisions; Theoretical Innovation: For the first time, linear programming optimization is combined with the definition of multiple safety constraints, establishing a quantitative theoretical framework for servo design and realizing a leap from empirical judgment to theoretical calculation; This invention provides a complete theoretical framework and practical design tools for the scientific design of foundation pit servo support systems, filling the current technical gap of servo systems that "have hardware but lack theory".

[0035] Example 2 To facilitate understanding of the core optimization algorithm of this invention by professionals in the field of civil engineering, this embodiment elaborates on the mathematical expression, physical meaning, and solution principle of the linear programming model.

[0036] The linear programming optimization problem constructed in this invention can be expressed in the following standard form: in: The policy variable vector contains the axial force adjustment amounts for n supports. and auxiliary variables ; The coefficient vector of the standard function; , The equations and the equation constraint coefficient matrix; , The vector on the right-hand side of the equation and the equality are constrained. , Let be the lower and upper bound vectors of the policy variable.

[0037] For a foundation pit project with n supports, the decision variables are defined as: ; in The axial force adjustment for the support (unit: kN) can be positive (increase axial force) or negative (decrease axial force). As a helper variable, it represents the maximum displacement of the enclosure structure after optimization (unit: mm).

[0038] The objective function aims to minimize the maximum displacement of the enclosure structure, mathematically expressed as: ; The corresponding coefficient vector is: ; That is, only the auxiliary variable t is assigned a coefficient of 1, while the coefficients of other decision variables are 0.

[0039] Displacement correlation constraints ensure that the displacement of each calculation point after optimization does not exceed the maximum displacement u: ; in: The moment of influence coefficient for displacement; As a quasi-displacement vector; Let be a vector whose primes are all 1; let be the number of points to be shifted. This constraint can be expanded into m inequalities: .

[0040] Axial force safety constraints ensure that the adjusted support axial force is within a safe range: ; in: The initial prestress value (lower limit) of the i-th support; For the first The reference axial force supporting the track; The upper limit of the axial force of the i-th support is determined by the selected working condition; this constraint can be decomposed into 2n inequalities: (Lower bound constraint) (Upper limit constraint).

[0041] The bending moment safety constraint ensures that the bending moment of the adjusted enclosure structure is within a safe range: ; in: This is the bending moment influence coefficient matrix; The reference bending moment vector; This is the upper limit vector of bending moment, determined by the selected working condition; The number of sections controlled by bending moment; this constraint can be expanded into p inequalities: .

[0042] Combining the above constraints, we obtain the complete linear programming problem: in for identity matrix; for Zero-dimensional vector; It is a p-dimensional zero vector.

[0043] This invention employs the classic simplex method to solve linear programming problems. Its basic steps are as follows: Construction of initial basic feasible solutions: Introducing slack variables transforms inequality constraints into equality constraints. ; where s is the slack variable vector.

[0044] Optimality test: Calculate the test number If all If the current solution is the optimal solution, then the current solution is the optimal solution; otherwise, choose... The largest non-basic variable is added to the basis.

[0045] Basis transformation iteration: Determining the input variables and out-of-basic variables Update the basis matrix B and basic variables. Repeat the steps until the optimality condition is met and the result is obtained.

[0046] All formulas in this invention are dimensionless and calculated by taking their numerical values. Dimensionlessness can be achieved through various methods such as standardization, which will not be elaborated here. The formulas are derived from software simulations using a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas can be set by those skilled in the art according to the actual situation.

[0047] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An optimization method for applying servo-driven internal support axial force during foundation pit construction, characterized in that, Applied to deep foundation pit projects where hydraulic servo support systems have been determined to be used, the method is based on the mechanical analysis results of traditional prestressed design, constructs a linear programming model containing multi-dimensional safety constraints, quantitatively evaluates the deformation control potential of the servo system under different safety levels, and outputs the optimal axial force control scheme for each construction stage. The method specifically includes the following steps: S1. Reference State Construction: Based on the mechanical analysis of the entire construction process of traditional prestressed design, the reference state of the retaining structure under various construction conditions is established, and the reference displacement field of the retaining structure, the reference axial force of each servo support, and the reference bending moment distribution of the retaining structure are determined. S2. Performance Parameter Determination: Collect the mechanical performance parameters of the construction materials on site, and construct a performance index set for the servo system. The index set shall include at least the design value of the axial bearing capacity of each support, the design value of the bending bearing capacity of the retaining structure, and the initial prestress value of the support. S3. Analysis of influence coefficients: Using the unit load method, the mapping relationship between the servo support axial force and the structural response is established, and the displacement influence coefficient matrix and bending moment influence coefficient matrix are generated. S4. Definition of working condition spectrum: Based on the comparison between on-site material configuration parameters and design calculation indicators, at least four servo optimization design working conditions are defined by combining different axial force safety margins and bending moment safety margins, forming a safety performance spectrum covering conservative control to potential tapping. S5. Optimization Model Construction: For the selected servo design conditions, the axial force adjustment of the installed internal support is used as the decision variable, the maximum displacement of the enclosure structure is minimized as the objective function, and a linear programming mathematical model is constructed in combination with the safety constraints defined in the conditions. S6. Solving and Instruction Generation: Solve the linear programming model, output the optimal axial force adjustment amount and adjustment timing for each layer of support in each construction step, and generate a set of servo support axial force loading instructions synchronized with the construction process.

2. The optimization method for applying servo-driven internal support axial force during foundation pit construction, as described in claim 1, is characterized in that... The four servo optimization design conditions in step S4 are specifically defined as follows: Condition A is defined as an axial force surplus condition: its constraint is that the upper limit of axial force is taken as the design value of the axial bearing capacity of the support, and the upper limit of bending moment is taken as the peak value of the traditional design bending moment. Condition B is defined as a moment-surplus condition: its constraint conditions are that the upper limit of axial force is taken as the historical peak value of the traditional design axial force, and the upper limit of bending moment is taken as the design value of the bending bearing capacity of the enclosure structure. Condition C is defined as a double redundancy condition: its constraint conditions are that the upper limit of axial force is taken as the design value of the axial bearing capacity of the support, and the upper limit of bending moment is taken as the design value of the bending bearing capacity of the enclosure structure. Condition D is defined as an absolutely safe condition: its constraints are that the upper limit of axial force is taken as the historical peak value of axial force in traditional design, and the upper limit of bending moment is taken as the peak value of bending moment in traditional design. The lower limit of axial force for each working condition is taken as the initial prestress value of the support.

3. The optimization method for applying servo-driven internal support axial force during foundation pit construction, as described in claim 2, is characterized in that... The peak bending moment and historical peak axial force of the traditional design are the extreme values ​​reached by the bending moment of the retaining structure and the axial force of each support during the entire construction cycle in the mechanical simulation of the entire construction process based on the traditional prestressed design.

4. The optimization method for applying servo-driven internal support axial force during foundation pit construction, as described in claim 1, is characterized in that... The displacement influence coefficient matrix and bending moment influence coefficient matrix generated in S3 include: Based on the mechanical model corresponding to the traditional prestressed design, a unit force is applied to the i-th support, and the displacement increment caused by it at the j-th displacement calculation point is calculated. And the moment increment caused by the j-th moment control section. Thus, the displacement influence coefficient matrix is ​​constructed. and moment influence coefficient matrix .

5. The optimization method for applying servo-driven internal support axial force during foundation pit construction, as described in claim 1, is characterized in that... The construction of the linear programming mathematical model in S5 includes: Objective function: , where u is an auxiliary variable representing the maximum displacement of the enclosure structure after optimization; The constraints include: Displacement-related constraints: ; Axial force safety constraints: ; Bending moment safety constraints: ; in This is the displacement influence coefficient matrix. This refers to the axial force adjustment of each installed internal support under this working condition. This represents the baseline displacement distribution of the retaining structure under construction conditions. This represents the prestress applied value for each support. This is the loading command for the servo system under this construction condition. This is the moment influence coefficient matrix. The reference bending moment distribution of the enclosure structure, and This represents the upper limit of axial force and bending moment, and its value is determined by the selected servo optimization design conditions.

6. The optimization method for applying servo-driven internal support axial force during foundation pit construction, as described in claim 1, is characterized in that... The method adopts a step-by-step static optimization strategy, which discretizes the continuous foundation pit construction process into N typical construction conditions. Steps S1 to S5 are executed independently for each discrete construction condition, and finally a complete set of servo support axial force optimization design schemes for each construction condition is output.

7. The optimization method for applying servo-driven internal support axial force during foundation pit construction, as described in claim 1, is characterized in that... The method also includes a performance evaluation step: The calculated displacement control effect under different servo-optimized design conditions is quantitatively compared and analyzed with the displacement values ​​of traditional prestressed design, constant pressure holding mode, and natural growth locking mode. A comparison spectrum of control effectiveness and safety level is generated to guide engineering decision-making.

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