Diversion tunnel intelligent design method based on multi-module collaborative optimization

Abstract

The invention relates to an intelligent diversion tunnel design method based on multi-module collaborative optimization, which solves the problem of a linear serial mode of a traditional diversion tunnel design process, breaks through the limitation of artificial experience and finds a global or approximately global structural economic optimal solution. Establishing a model basis library, inputting engineering boundary conditions, and standardizing data; the intelligent hydraulic calculation and section optimization module is used for performing hydraulic simulation calculation to generate a plurality of section design schemes; the preliminary support design module is used for matching an initial support design scheme with known sections and geological conditions; the structural calculation module is used for calculating, checking and optimizing mechanical safety and economical efficiency by integrating the design schemes of the section and the preliminary support; the economic comparison module quantifies the economic cost of each design scheme and provides a target function value; and through an intelligent closed-loop mode, closed-loop processing is carried out on the calculation module by adopting modes of design, verification, feedback, optimization and result output in sequence.

Description

Technical Field

[0001] This application relates to the field of design, specifically to an intelligent design method for diversion tunnels based on multi-module collaborative optimization. Background Technology

[0002] Existing technologies primarily employ a sequential design approach. When structural calculations or economic comparisons yield unsatisfactory results, manual adjustments to hydraulic parameters are required, necessitating a restart of the calculations. This results in long iteration cycles, limited design space exploration, and low iteration efficiency. Designers often rely on experience to propose limited alternatives for comparison, making it difficult to achieve global optimization across parameter spaces such as hydraulics, tunnel diameter, lining thickness, and support density, easily leading to local optima. Support design and parameter selection heavily depend on engineer experience, lacking standardization and automation. Furthermore, the four modules—hydraulics, structure, support, and economics—are relatively independent, lacking a unified optimization objective for automatic trade-offs. Summary of the Invention

[0003] The present invention aims to overcome at least one of the defects of the prior art and provide an intelligent design method for diversion tunnels based on multi-module collaborative optimization, thereby solving the problem of the linear serial mode of the traditional diversion tunnel design process.

[0004] This paper presents an intelligent design method for diversion tunnels that enables automatic iteration and collaborative optimization of multiple modules, including hydraulics, structure, support, and economy. Under the premise of meeting all constraints, only a few necessary parameters need to be input to find a technically feasible and economically optimal design scheme and quickly complete the automatic design to form the design result.

[0005] Specifically, a method for intelligent design of diversion tunnels based on multi-module collaborative optimization is provided, the method comprising:

[0006] Establish a model reference library, including budget quotas, national and industry standards, and historical engineering cases;

[0007] Input the engineering boundary conditions, including hydrological conditions, geological conditions, topographic and layout conditions;

[0008] The intelligent hydraulics calculation and cross-section optimization module generates multiple cross-section design schemes that conform to the specifications based on the aforementioned database and input engineering boundary conditions.

[0009] The preliminary support design module matches initial support design schemes for known cross sections and geological conditions using a database.

[0010] The structural calculation module integrates the design schemes of the cross-section and preliminary support, and performs mechanical safety and economic verification and optimization.

[0011] The economic comparison module quantifies the economic cost of each design scheme and provides the objective function value.

[0012] Through the intelligent closed-loop mode, the intelligent hydraulics calculation and cross-section optimization module, the preliminary support design module, the structural calculation module, and the economic comparison module in the calculation module are processed in a closed loop in sequence using the methods of design, verification, feedback, optimization, and output results.

[0013] The main advantages of this invention are as follows:

[0014] Global optimality: Searching in multiple parameter spaces breaks the limitations of human experience and makes it easier to find the global or near-global economic optimal solution.

[0015] Revolutionary improvement in design efficiency: The traditional manual iteration process, which takes weeks, is shortened to automatic calculations in hours or even minutes, greatly improving design efficiency and analysis depth.

[0016] True multidisciplinary collaboration: Hydraulic requirements, structural safety, support measures, and project costs are placed under the same optimization framework for real-time weighing, realizing the transformation from "serial design" to "parallel optimization".

[0017] Intelligent support design: By solidifying expert experience through a rule base, support design moves from experience-based judgment to quantitative intelligent matching, improving the scientific nature and consistency of the design.

[0018] Enhanced decision support: The solution clearly demonstrates the trade-offs between "cost-safety-risk," supporting scientific decision-making. Attached Figure Description

[0019] Figure 1 This is a flowchart of an intelligent design method for diversion tunnels based on multi-module collaborative optimization according to the present invention. Detailed Implementation

[0020] The accompanying drawings are for illustrative purposes only and should not be construed as limiting the invention. To better illustrate the following embodiments, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product dimensions; it is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0021] This application provides an intelligent design method for diversion tunnels based on multi-module collaborative optimization, such as... Figure 1 As shown, the method includes:

[0022] S100: Establish a model reference library, including budget quotas, national and industry standards, and historical engineering cases;

[0023] This database supports accurate calculations in the economic comparison module, ensuring the standardization and timeliness of cost estimates.

[0024] Specifically, in some embodiments, the method for establishing the model reference library includes:

[0025] S50: Establish a parameter database based on budget quotas to support the calculation of the economic comparison module, including material unit price database, machinery shift cost database, labor unit price database, and quota sub-item database;

[0026] in:

[0027] Material Unit Price Database: Stores the latest market prices and information prices of major building materials such as cement, steel bars, sand and gravel aggregates, admixtures, and structural steel.

[0028] Machinery Shift Fee Database: Stores the usage fees for construction machinery such as excavators, drilling machines, shotcrete machines, and concrete pumps.

[0029] Labor unit price database: Stores the comprehensive labor unit price for different types of work, such as excavator, support worker, and formwork worker.

[0030] Quota Sub-item Library: Based on the current national and industry budget quotas, such as the "Regulations and Calculation Standards for the Compilation of Design Estimates for Hydropower Projects", this library stores the comprehensive unit price or basic price of labor, materials and machinery consumption for tasks such as "rock excavation", "concrete lining", "anchor bolt installation", "reinforcing steel installation", and "shotcrete".

[0031] S51: Establish a knowledge base of design rules and parameters based on national and industry standards, including a sub-base of hydraulic design rules and a sub-base of structural and support design rules;

[0032] The hydraulic design rules sub-library is based on the "Code for Design of Hydraulic Tunnels" (NB / T 10391-2020, SL 279-2016), and specifically includes:

[0033] Criteria for determining whether a flow is pressurized or unpressurized;

[0034] Recommended ranges for the optimal hydraulic aspect ratio for different cross-sectional shapes, including archway shape, circular shape, and horseshoe shape;

[0035] Maximum or minimum allowable flow velocity limits, including limits for preventing erosion and sedimentation;

[0036] Constraints on the connection between inlet and outlet water surfaces;

[0037] The structure and support design rules sub-library is comprehensively referenced from the "Code for Design of Hydraulic Tunnels" and the "Technical Specification for Rock and Soil Anchor and Shotcrete Support Engineering" (GB 50086-2015). This library makes the engineers' regulatory knowledge explicit and coded, ensuring that every solution generated during the optimization process automatically meets the most basic mandatory regulatory requirements. It is the fundamental guarantee of compliance in "intelligent design," including:

[0038] The table of surrounding rock classification and corresponding recommended values ​​of physical and mechanical parameters includes the following: the surrounding rock classification is such as I to V, and the recommended values ​​of physical and mechanical parameters include deformation modulus, cohesion, and internal friction angle.

[0039] A preliminary support parameter recommendation table for each level of surrounding rock, including anchor bolt type, length, spacing, shotcrete layer thickness, and steel arch frame specifications and spacing;

[0040] The structural safety criterion rules transform the allowable safety factor values ​​in the specifications into hard constraints for the optimization algorithm. These allowable values ​​include the lining safety factor, the compressive strength safety factor, and the surrounding rock stability safety factor.

[0041] The rules for load combination and partial factors clarify the load combination methods and corresponding structural importance coefficients and partial factors under different working conditions such as construction period, operation period, and maintenance period;

[0042] S52: Establish a reference model library based on historical engineering cases, providing initial historical experience data for designers to use as a reference, including a library of typical engineering drawings, a library of engineering feature parameters, and experience-related models.

[0043] By providing high-quality initial historical experience data, the optimization process avoids blindly searching within the ineffective design space, accelerates the exploration process, and provides designers with intuitive analogies.

[0044] Specifically, the typical engineering drawing library collects typical cross-sections, longitudinal sections, and support layout diagrams of existing diversion tunnels with different surrounding rock conditions and different flow rates and heads.

[0045] The library stores drawings in CAD format. For engineering drawings stored in this CAD library, this system uses Python and an open-source CAD parsing framework to automatically parse them. By extracting key design information such as geometric entities, layer attributes, text annotations, and block references, and converting it into structured data, such as JSON or Python dictionary / list objects, a standardized information model that is machine-readable and programmable is constructed. This model provides accurate and traceable geometric and semantic data support for subsequent processing, realizing the connection between design information and "structured data," and laying the data foundation for fully automated design and optimization decisions.

[0046] Specifically, the engineering feature parameter library is created by automatically parsing historical engineering case documents to extract key design parameters and empirical data. Parameter categories include, but are not limited to: structural geometric parameters (such as tunnel diameter and cross-sectional dimensions), hydraulic parameters (such as design flow rate and local head loss coefficient), geological parameters (such as surrounding rock grade, support type and parameters), and economic indicators (such as unit cost and material consumption). The original parameters are stored in Word format. The system uses Python combined with an open-source document parsing library (such as openpyxl) to intelligently identify and structure the document content, converting it into standardized, programmable data structures (such as JSON or database records). This constructs a high-quality empirical dataset that supports intelligent reasoning and optimization design.

[0047] Specifically, the experience-based correlation model is based on an established library of engineering drawings and engineering feature parameters. This system utilizes Pandas data analysis and mining tools in Python to conduct in-depth correlation analysis on multidimensional information from historical projects. By systematically mining the statistical relationships and potential patterns between engineering features (such as surrounding rock grade and tunnel diameter) and engineering costs (such as initial support costs), an intelligent mapping model from key design parameters to economic indicators is constructed. This model can quickly output the corresponding suggested initial support cost range based on the input surrounding rock grade and tunnel diameter parameters, providing efficient initial screening and economic pre-assessment capabilities for subsequent optimization algorithms, thereby significantly improving the efficiency and scientific rigor of scheme comparison and iterative optimization.

[0048] S102: Input engineering boundary conditions, including hydrological conditions, geological conditions, topographic and layout conditions;

[0049] Specifically, in some embodiments, the input engineering boundary conditions are used to input variables, including

[0050] Hydrological conditions include the tunnel's design flood flow rate Q (m³ / s) and the relationship between the upstream and downstream water levels at the tunnel's inlet and outlet;

[0051] Geological conditions include the grade and length of the surrounding rock along the tunnel route, and the groundwater activity.

[0052] The terrain and layout conditions include the tunnel inlet floor elevation Z_in (m), the outlet floor elevation Z_out (m), the total tunnel axis length L (m), and the planar layout parameters include the number of turns n, the turning radius R_i (m) at each turn, and the turning angle.

[0053] The proposed solution integrates four core calculation modules: intelligent hydraulics calculation and cross-section optimization, preliminary support design, structural calculation, and economic comparison. These modules are no longer simply sequential but form a collaborative workflow with dynamic feedback mechanisms within a unified framework. The four modules form an intelligent closed-loop model of "design-verification-feedback-optimization-output results." The intelligent hydraulics calculation and cross-section optimization module provides a reasonable "skeleton" and cross-section parameters; the preliminary support design module provides the "initial framework" for the cross-section; the structural calculation module performs "pressure testing and fine-tuning"; and the economic comparison module provides the "price tag." Any non-compliance at any stage triggers feedback adjustments, ultimately delivering a reasonable result to the next module. This results in a complete design scheme that is technically compliant and economically cost-effective.

[0054] Each module performs calculations, verifications, and adjustments under the guidance of the standardized knowledge base and design rules, ultimately outputting the technically and economically optimal solution that satisfies all constraints. The specific methods for each module are as follows.

[0055] S104: Intelligent hydraulics calculation and cross-section optimization module, which generates multiple cross-section design schemes based on the aforementioned database and input engineering boundary conditions;

[0056] Based on the model library and input engineering boundary conditions, this solution generates multiple feasible structural cross-section prototypes, providing initial input for subsequent modules.

[0057] Specifically, in some embodiments, the intelligent hydraulics calculation and cross-section optimization module includes:

[0058] S10: Parametric cross-section generator, which generates multiple types of diversion tunnel cross-sections based on the input engineering boundary design variables, boundary conditions and the experience association model created by the historical engineering cases;

[0059] The boundary conditions include flow rate and longitudinal slope. The generated cross-sections of various types of diversion tunnels should meet the basic structural requirements of the "Design Code for Hydraulic Tunnels". The types include archway shape and circular shape.

[0060] S11: Rapid simulation of hydraulic characteristics, the design scheme of the diversion tunnel section is verified by calling the embedded professional hydraulic calculation model;

[0061] For each automatically generated diversion tunnel cross-section design scheme, the system will call the embedded professional hydraulic calculation model for simulation verification. This calculation, developed using Python, strictly adheres to the relevant provisions of the "Hydraulic Design Manual" and is specifically designed with algorithms tailored to the complex flow conditions unique to diversion tunnels. The model can handle the hydraulic characteristics of the diversion tunnel under both design and flood season conditions, and accurately calculates based on the actual flow regime within the tunnel, including unpressurized flow, semi-pressurized flow, and pressurized flow, using corresponding governing equations and calculation methods to ensure that the cross-section design meets hydraulic safety and performance requirements under various operating conditions.

[0062] Specifically, in some embodiments, the verification includes:

[0063] Flow capacity under design flow rate, velocity distribution inside the tunnel, and water surface line;

[0064] Head loss along the process and local head loss, including the turning parameters of the input engineering boundary;

[0065] The flow patterns of inlet and outlet water, including whether flooding, precipitation, or backwater occurs.

[0066] S12: Constraint check and screening, based on the upper limit of flow velocity, flow regime requirements, and discharge capacity margin, eliminate infeasible diversion tunnel sections;

[0067] The termination rules include limits on flow velocity, flow regime requirements, and discharge capacity margin.

[0068] S13: Preliminary optimization and ranking. The feasible diversion tunnel sections are ranked based on the premise of meeting the discharge capacity and the conditions of minimizing the net area and the head loss. 2-3 diversion tunnel section schemes are recommended to the front end.

[0069] S14: Outputs the geometric parameters of the recommended diversion tunnel cross-section, the discharge capacity curve, the calculated flow velocity, and the head loss value;

[0070] S106: Preliminary support design module, which matches the initial support design scheme based on the database and known cross-sections and geological conditions;

[0071] By leveraging standards and empirical knowledge, a compliant and economical initial support scheme can be quickly matched for a given cross-section and geological conditions, serving as the starting point for detailed structural calculations.

[0072] Specifically, in some embodiments, the preliminary support design module includes:

[0073] S20: Multi-source information fusion, receiving cross-sectional geometric information of the diversion tunnel and surrounding rock classification and segmentation information;

[0074] S21: Rule reasoning and parameter matching, using a production rule system for automatic matching;

[0075] Specifically, in some embodiments, the “Structure and Support Design Rules Sub-Library” is invoked, and a generative rule system is used for automatic matching. For example, when the surrounding rock level is III and the tunnel diameter is greater than 12m, the initial support is recommended as follows: system anchor bolts Φ25@1.5m, L=3.0m; sprayed C25 concrete, 12cm thick; and if necessary, a grid steel frame @1.2m is installed.

[0076] S22: Empirical model calibration, which involves fine-tuning the parameters recommended by the standard by finding support cases with similar conditions;

[0077] S23: Output results, including preliminary support parameter tables for each section of the tunnel. This includes anchor bolts, shotcrete, and steel arch / grid arch.

[0078] Accurate mechanical safety and economic verification and optimization of the "section + preliminary support" combination are key to determining the safety and economy of the final solution.

[0079] S108: Structural calculation module, which integrates the design scheme of cross section and preliminary support, and performs mechanical safety and economic verification and optimization;

[0080] Specifically, in some embodiments, the structure calculation module includes:

[0081] S30: Automatic construction of numerical models, generating stratum models, support structure models, lining models, and load models;

[0082] The geological model is based on the surrounding rock parameters, the support structure model treats anchor bolts as rod elements, and the shotcrete and steel arch as beam or shell elements. The lining model parameterizes the thickness t, and the loads include ground stress, groundwater pressure, and the lining's self-weight.

[0083] S31: Calculate the safety factor for each part; perform numerical calculations to automatically extract the range of the plastic zone and displacement field of the surrounding rock. Calculate the internal forces (M, N) of the initial support and secondary lining. Automatically calculate the safety factor for each part based on the "Structural Safety Criterion Rules" in the database.

[0084] S32: Develop a closed-loop feedback optimization mechanism based on the safety system, including setting a safety factor standard value. If the safety factor is greater than the standard value, reduce the lining thickness or lower the support parameters. If the safety factor is less than the standard value, increase the lining thickness or strengthen the support parameters. Repeat the calculation until the safety factor falls within the range of the safety factor standard value.

[0085] Specifically, when the safety factor is excessively high, such as more than 1.3 times the standard value, "economic optimization" is triggered. At this time, the lining thickness is appropriately reduced or the support parameters are lowered, such as increasing the anchor spacing, and the calculation is repeated until the safety factor is close to the standard allowable value.

[0086] When the safety factor does not meet the specifications, the "safety enhancement" is triggered. At this time, the lining thickness is automatically increased or the support parameters are strengthened, such as increasing the density of anchor bolts or adding steel arches, and the calculation is repeated until the requirements are met.

[0087] S33: Perform reinforcement calculations and reinforcement selection design for the lining;

[0088] This design is based on the "Code for Design of Hydraulic Concrete Structures" and the internal force results calculated numerically.

[0089] S34: Output the optimized final lining thickness and reinforcement diagram, the final support parameters after adjustment and confirmation, and a summary report of safety factors under various working conditions.

[0090] S110: Economic comparison module, which quantifies the economic cost of each design scheme and provides the objective function value;

[0091] Specifically, in some embodiments, the economic comparison module includes:

[0092] S40: Extraction and calculation of engineering quantities, including the extraction and calculation of excavation quantities, concrete quantities, support material quantities, and steel reinforcement quantities;

[0093] The excavation work volume is automatically calculated based on the final cross-section and axis length from the structural calculation module. The concrete work volume is calculated based on the final lining thickness and length optimized by the structural calculation module. The support material work volume is calculated based on the final support parameters confirmed by the structural calculation module, including the number of anchor bolts, the area of ​​the shotcrete layer, and the weight of the steel arch frame. The reinforcement work volume is calculated based on the reinforcement results from the structural calculation module.

[0094] S41: Real-time cost calculation, using the quota or comprehensive unit price method to calculate the cost of sub-items, the cost of temporary items, and the total investment of the scheme;

[0095] Specifically, the costs of each sub-project include rock excavation, concrete lining, support works, and steel reinforcement installation.

[0096] The cost of the measures includes construction ventilation, lighting, drainage, etc., and can be estimated using empirical coefficients.

[0097] The total investment of the plan, i.e. the objective function value, is: C_total = Σ(itemized costs) + measures costs.

[0098] S42: Preparation for cost sensitivity analysis, by recording the cost composition ratio of different design schemes;

[0099] Cost breakdown ratios, such as excavation ratio, lining ratio, and support ratio, provide in-depth insights for comparing multiple options and making decisions.

[0100] S43: Output the engineering quantity calculation process, the total investment of the optimized structure, and the proportion of each component.

[0101] S112: Through intelligent closed-loop mode, the intelligent hydraulics calculation and cross-section optimization module, support preliminary design module, structural calculation module, and economic comparison module in the calculation module are processed in a closed loop in sequence by design, verification, feedback, optimization, and output results.

[0102] This solution enables multidisciplinary collaboration during the design phase, placing hydraulic requirements, structural safety, support measures, and project costs under the same optimization framework for real-time optimization and balancing, thus achieving a shift from "serial design" to "parallel optimization."

[0103] In some embodiments, the results are visualized to generate intelligent parametric drawings, including:

[0104] Input-driven, by interfacing with the output parameters of the computing module, one-click image generation is achieved;

[0105] The massive amounts of data and final solutions generated by the collaborative optimization engine are transformed into multi-dimensional results that engineers and decision-makers can intuitively understand, efficiently review, and conveniently utilize. It is not just a "graphics generation tool," but a comprehensive decision support platform that integrates intelligent mapping, dynamic reporting, and solution comparison.

[0106] Output parameters include cross-sectional geometry, support parameters, reinforcement information, and axis layout.

[0107] Specifically, the types of drawings include:

[0108] Plan layout: includes tunnel axis, entrance and exit locations, turning points, geological sections, control point coordinates and elevations;

[0109] Longitudinal profile: includes tunnel longitudinal slope, geological columnar section, support type segmentation, and key control elevation;

[0110] Cross-sectional view: generated according to different surrounding rock segments and support designs, including the excavation outline, initial support (anchor bolts, steel mesh, steel arch frame schematic), secondary lining outline and thickness;

[0111] Lining reinforcement drawings: including reinforcement layout, reinforcement table, and quantity table.

[0112] In some embodiments, the method also includes generating structured computation reports and solution reports:

[0113] Standardized Report: A standardized report is generated by acquiring input, process data and results from the calculation module. The report includes a design overview, hydraulic calculations, geological and support design, structural calculations, quantities and estimates, and a summary of the main technical and economic indicators of the scheme.

[0114] Radar charts or parallel coordinate graphs can be used to visually compare the key indicators of each option, including total investment, safety factor, excavation volume, and estimated construction period.

[0115] The report also includes:

[0116] Design Overview: Project background, design basis (referenced standards), and main boundary conditions.

[0117] The hydraulic calculation chapter includes hydraulic calculation models, hydraulic elements (velocity, water depth, head loss) under design flow rate, discharge capacity curves, and flow regime analysis conclusions.

[0118] Geological and Support Design Chapter: Surrounding Rock Segmentation and Parameter Table, Support Design Parameter Table for Each Segment and Selection Basis.

[0119] Structural Calculation Section: Brief description of the calculation model (simplified model diagram may be attached), load combination, internal force calculation results (bending moment and axial force diagrams of key sections), summary table of safety factors, and reinforcement calculation results.

[0120] The section on quantities and estimates includes a detailed bill of quantities (excavation, concrete, anchor bolts, reinforcement, shotcrete, etc.) and an investment estimate table.

[0121] Summary table of key technical and economic indicators: The key indicators of the final plan are presented in a one-page format, including tunnel diameter, length, lining thickness, total excavation volume, total concrete volume, and total investment.

[0122] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the technical solution of the present invention, and are not intended to limit the specific implementation of the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the claims of the present invention should be included within the protection scope of the claims of the present invention.

Claims

1. A smart design method for diversion tunnels based on multi-module collaborative optimization, characterized in that, The method includes: Establish a model reference library, including budget quotas, national and industry standards, and historical engineering cases; Input the engineering boundary conditions, including hydrological conditions, geological conditions, topographic and layout conditions; The intelligent hydraulics calculation and cross-section optimization module generates multiple cross-section design schemes based on the aforementioned database and input engineering boundary conditions. The preliminary support design module matches initial support design schemes for known cross sections and geological conditions using a database. The structural calculation module integrates the design schemes of the cross-section and preliminary support, and performs mechanical safety and economic verification and optimization. The economic comparison module quantifies the economic cost of each design scheme and provides the objective function value. Through the intelligent closed-loop mode, the intelligent hydraulics calculation and cross-section optimization module, the preliminary support design module, the structural calculation module, and the economic comparison module in the calculation module are processed in a closed loop in sequence using the methods of design, verification, feedback, optimization, and output results.

2. The intelligent design method for diversion tunnels based on multi-module collaborative optimization according to claim 1, characterized in that, The intelligent hydraulics calculation and cross-section optimization module includes: S10: Parametric cross-section generator, which generates multiple types of diversion tunnel cross-sections based on the input engineering boundary design variables, boundary conditions and the experience association model created by the historical engineering cases; S11: Rapid simulation of hydraulic characteristics, the design scheme of the diversion tunnel section is verified by calling the embedded professional hydraulic calculation model; S12: Constraint check and screening, based on the upper limit of flow velocity, flow regime requirements, and discharge capacity margin, eliminate infeasible diversion tunnel sections; S13: Preliminary optimization and ranking. The feasible diversion tunnel sections are ranked based on the premise of meeting the discharge capacity and the conditions of minimizing the net area and the head loss. 2-3 diversion tunnel section schemes are recommended to the front end. S14: Outputs the geometric parameters of the recommended diversion tunnel cross-section, the discharge capacity curve, the calculated flow velocity, and the head loss value.

3. The intelligent design method for diversion tunnels based on multi-module collaborative optimization according to claim 2, characterized in that, The verification includes: Flow capacity under design flow rate, velocity distribution inside the tunnel, and water surface line; Head loss along the route and local head loss; Flow patterns and water levels at inlet and outlet.

4. The intelligent design method for diversion tunnels based on multi-module collaborative optimization according to claim 1, characterized in that, The preliminary design module for the support system includes: S20: Multi-source information fusion, receiving cross-sectional geometric information of the diversion tunnel and surrounding rock classification and segmentation information; S21: Rule reasoning and parameter matching, using a production rule system for automatic matching; S22: Empirical model calibration, which involves fine-tuning the parameters recommended by the standard by finding support cases with similar conditions; S23: Output results, including preliminary support parameter tables for each section of the tunnel.

5. The intelligent design method for diversion tunnels based on multi-module collaborative optimization according to claim 1, characterized in that, The structural calculation module includes: S30: Automatic construction of numerical models, generating stratum models, support structure models, lining models, and load models; S31: Calculate the safety factor for each part; S32: Develop a closed-loop feedback optimization mechanism based on the safety system, including setting a safety factor standard value. If the safety factor is greater than the standard value, reduce the lining thickness or lower the support parameters. If the safety factor is less than the standard value, increase the lining thickness or strengthen the support parameters. Repeat the calculation until the safety factor falls within the range of the safety factor standard value. S33: Perform reinforcement calculations and reinforcement selection design for the lining; S34: Output the optimized final lining thickness and reinforcement diagram, the final support parameters after adjustment and confirmation, and a summary report of safety factors under various working conditions.

6. The intelligent design method for diversion tunnels based on multi-module collaborative optimization according to claim 1, characterized in that, The economic comparison module includes: S40: Extraction and calculation of engineering quantities, including the extraction and calculation of excavation quantities, concrete quantities, support material quantities, and steel reinforcement quantities; S41: Real-time cost calculation, using the quota or comprehensive unit price method to calculate the cost of sub-items, the cost of temporary items, and the total investment of the scheme; S42: Preparation for cost sensitivity analysis, by recording the cost composition ratio of different design schemes; S43: Output the engineering quantity calculation process, the total investment of the optimized structure, and the proportion of each component.

7. The intelligent design method for diversion tunnels based on multi-module collaborative optimization according to claim 1, characterized in that, The method for establishing the model database includes: S50: Establish a parameter database based on budget quotas to support the calculation of the economic comparison module, including material unit price database, machinery shift cost database, labor unit price database, and quota sub-item database; S51: Establish a knowledge base of design rules and parameters based on national and industry standards, including a sub-base of hydraulic design rules and a sub-base of structural and support design rules; The hydraulic design rules sub-library includes: Criteria for determining whether a flow is pressurized or unpressurized; Recommended ranges for the optimal hydraulic aspect ratio for different cross-sectional shapes; Maximum or minimum allowable flow rate limits; Constraints on the connection between inlet and outlet water surfaces; The structure and support design rules sub-library includes: Table of surrounding rock classification and corresponding recommended values ​​for physical and mechanical parameters; Recommended preliminary support parameters for each level of surrounding rock; Structural safety criteria rules; Load combination and partial factor rules; S52: Establish a reference model library based on historical engineering cases, providing initial historical experience data for designers to use as a reference, including a library of typical engineering drawings, a library of engineering feature parameters, and experience-related models.

8. The intelligent design method for diversion tunnels based on multi-module collaborative optimization according to claim 1, characterized in that, The input engineering boundary conditions are used to input variables, including Hydrological conditions include design flood discharge and upstream and downstream water level relationships; Geological conditions include the grade and length of the surrounding rock along the tunnel route, and the groundwater activity. The terrain and layout conditions include the elevation of the tunnel inlet floor, the elevation of the tunnel outlet floor, the total length of the tunnel axis, and the plan layout parameters include the number of turns, the turning radius and the turning angle at each turn.

9. The intelligent design method for diversion tunnels based on multi-module collaborative optimization according to claim 1, characterized in that, The results are visualized and output to generate intelligent parametric drawings, including: Input-driven, by interfacing with the output parameters of the computing module, one-click image generation is achieved; Drawing types include: Plan layout: includes tunnel axis, entrance and exit locations, turning points, geological sections, control point coordinates and elevations; Longitudinal profile: includes tunnel longitudinal slope, geological columnar section, support type segmentation, and key control elevation; Cross-sectional view: generated according to different surrounding rock segments and support designs, including the cut outline, initial support, secondary lining outline and thickness; Lining reinforcement drawings: including reinforcement layout, reinforcement table, and quantity table.

10. The intelligent design method for diversion tunnels based on multi-module collaborative optimization according to claim 1, characterized in that, It also includes generating structured calculation reports and solution reports: Standardized Report: A standardized report is generated by acquiring input, process data and results from the calculation module. The report includes a design overview, hydraulic calculations, geological and support design, structural calculations, engineering quantities and estimates, and a summary of the main technical and economic indicators of the scheme. The summary table of the main technical and economic indicators of the scheme presents the key indicators of the final scheme in a one-page format, including tunnel diameter, length, lining thickness, total excavation volume, total concrete volume and total investment. Radar charts or parallel coordinate graphs: Visualize and compare the key indicators of each option, including total investment, safety factor, excavation volume, and estimated construction period.

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