Rapid modeling method for updating highway tunnel lining type based on Dynamo parameterization

Abstract

The invention discloses a rapid modeling method for updating a highway tunnel lining type based on Dynamo parameterization, and belongs to the technical field of highway tunnel BIM modeling. According to the method, three-dimensional modeling of a center line is realized through Dynamo; and establishing a group template of a standard outline template and a standard lining type component. And then reading an information table of'starting and ending point mileage stake numbers-lining types' of starting points and ending points of different lining types in the whole mileage range of the tunnel, matching corresponding lining type names, and placing a family template generation model of standard lining type components along a center line. And matching lining type component information matched with the tunnel mileage position. And modifying the parameters of the placed standard lining type template family instance into a specified lining type to obtain a tunnel model with accurate tunnel contour shape and component parameters. And finally integrating the model and automatically counting the model engineering quantity. The method solves the problem of parametric modeling of a complex highway tunnel structure.

Description

Technical Field

[0001] This invention belongs to the field of highway tunnel BIM modeling technology, and in particular relates to a rapid modeling method for updating highway tunnel lining types based on Dynamo parametric updates. Background Technology

[0002] In recent years, the introduction of BIM technology and parametric design tools has provided new solutions for tunnel engineering. For example, establishing a parametric family library through Revit enables rapid modeling of some components, and combining it with Dynamo for data-driven design can improve model generation efficiency. However, existing technologies still have significant limitations: Insufficient parameterization depth: Most family libraries only support fixed cross-section forms and cannot dynamically adjust key parameters such as lining thickness and support density according to changes in surrounding rock grade or alignment, still requiring manual intervention. Fragmented multi-source data: Design data (such as route coordinates and lining parameters) and construction data (such as schedules and resource allocation) are scattered across different platforms, lacking an effective linkage mechanism, making it difficult to achieve collaborative management of the "design-construction" two-stage process. Limited level of intelligence: The design model cannot reflect over-excavation and under-excavation during construction, and cannot adaptively optimize by combining real-time geological monitoring data or construction feedback, resulting in a disconnect between the model and actual working conditions.

[0003] In conclusion, although BIM technology has improved the informatization level of tunnel engineering to some extent, its shortcomings in dynamic parametric modeling, multi-disciplinary collaboration, and intelligent decision support still restrict further improvements in construction efficiency and cost control accuracy. Therefore, a systematic approach that deeply integrates parametric design, automated quantity surveying, and dynamic optimization algorithms is urgently needed to achieve efficient and accurate management of tunnel engineering. Summary of the Invention

[0004] The purpose of this invention is to provide a rapid modeling method for updating highway tunnel lining types based on Dynamo parametric updates, solving the problem of parametric modeling of complex highway tunnel structures and achieving dynamic coupling between surrounding rock parameters and support design. It also constructs a technical framework for BIM-driven forward design of tunnel engineering, develops a point cloud-driven model correction engine, and provides an automatic compensation mechanism between construction point clouds and design models. This provides a high-precision 3D information model foundation for smart construction site development.

[0005] The objective of this invention can be achieved through the following technical solutions: A rapid modeling method for updating highway tunnel lining types based on Dynamo parameterization includes the following steps: S1. Input horizontal curve parameters and vertical curve parameters, dynamically optimize curve parameters through iterative adjustment algorithm, generate Dynamo parametric curve and establish a three-dimensional model of tunnel centerline; S2. Construct an information table of "start and end point mileage station number - lining type" and an information table of "lining type - component parameters". Using the standard section clearance cross section, the vehicle cross passage clearance cross section, the pedestrian cross passage clearance cross section, and the emergency parking lane tunnel clearance cross section as the outline reference, establish a standard outline template and a parameterized family template of standard lining type components. S3. According to the "start and end point mileage station number - lining type" information table, the tunnel centerline is segmented and placed along the centerline at a set interval. S4. Group and map component parameters by lining type through the List.GroupByKey node, batch modify family template instance parameters to match the lining type of each mileage section, and generate an accurate tunnel model. S5. Link the models of each mileage segment in mileage order, and integrate the main tunnel, pedestrian tunnel, vehicular tunnel and emergency parking lane; S6. Perform engineering quantity statistics on the integrated model and develop a point cloud-driven model correction engine to achieve construction deviation compensation.

[0006] As a further aspect of the present invention, the iterative adjustment algorithm in step S1 includes: The least squares optimization model is used to dynamically calibrate the curve parameters; The objective function of the least squares optimization model is expressed as: in: , For calculated values; , These are measured values; The number of sample points; The solution is obtained using the Levenberg-Marquardt algorithm, with the following constraints: Radius constraint: Transition curve constraints: , Indicates the length of the transition curve; Curvature continuity constraint: , This represents the radius of two adjacent circular arc segments; Indicates curvature; This indicates a limit on the maximum curvature change.

[0007] As a further aspect of the present invention, the establishment of the parameterized family template in step S2 includes setting the center position, angle, radius, lining thickness, and anchor length of the tunnel outline as type parameters. Three types of parameterized family libraries are constructed: the main structure family library, including portals, initial support, secondary lining, invert arches, and central partition walls; the support structure family library, including anchor bolts, steel arch frames, and pipe sheds; and the ancillary facilities family library, including ventilation ducts and lighting systems.

[0008] As a further aspect of the present invention, when placing the family template instance in step S3: the longitudinal slope angle is calculated by the Z-coordinate difference of each pile coordinate. Rotate family instances to match the slope; Use the Curve.TrimByParameter node to segment the centerline according to the lining type and start and end station numbers.

[0009] As a further aspect of the present invention, the parameter grouping mapping in step S4 includes: generating a dictionary using the List.GroupByKey node with the lining type as the key and the component parameter as the value; batch modifying the family instance parameters through the Element.SetParameterByName node; and using the Geometry.Morph node to achieve a smooth transition for the variable cross-section segment.

[0010] As a further aspect of the present invention, the point cloud-driven model correction engine in step S6 includes: Point cloud registration was performed using feature-enhanced registration and a hierarchical ICP algorithm. The objective function of the hierarchical ICP algorithm is: ; Deviation Compensation Decision: Based on Error Field Dynamically adjust lining thickness Outer contour according to renew; Compensation amount calculation model: The coefficients are obtained through machine learning training.

[0011] As a further aspect of the present invention, the quantity statistics are achieved in the following way: the geometric volume of the component is calculated using the Solid.Volume node; a detailed table containing volume, length, and component type is dynamically generated using the Schedule.AddField node, and associated with the P6 construction schedule plan.

[0012] As a further aspect of the present invention, the deviation compensation strategy includes: increasing the thickness of shotcrete during local over-excavation. ; Adjust the excavation outline when there is local under-excavation; The design centerline is shifted during overall offset.

[0013] The present invention also discloses an electronic device including a memory and a processor, comprising the steps of the above method.

[0014] The beneficial effects of this invention are: This method addresses the technical pain points of traditional tunnel modeling, such as low efficiency, poor accuracy, and weak collaboration. It achieves a closed-loop data process throughout the design-modeling-construction phase, features real-time parameter updates, supports multiple tunnel types, significantly shortens modeling time, and provides an efficient and reliable digital solution for complex tunnel engineering. Attached Figure Description

[0015] The invention will now be further described with reference to the accompanying drawings.

[0016] Figure 1 This is a roadmap of the highway tunnel modeling technology of the present invention; Figure 2 This is a flowchart of the point cloud-driven construction deviation compensation method of the present invention. Figure 3 This is a schematic diagram of the three-dimensional tunnel model of the present invention; Figure 4 This is a schematic diagram of the modified lining type lining component parameters of the present invention; Figure 5 This is a schematic diagram of the integrated tunnel model of the present invention. Detailed Implementation

[0017] 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.

[0018] A rapid modeling method for updating highway tunnel lining types based on Dynamo parameterization includes the following steps: S1. Input horizontal curve parameters and vertical curve parameters, dynamically optimize curve parameters through iterative adjustment algorithm, and output Dynamo parametric curve; associate route data with the parametric family library of tunnels in Revit to realize tunnel centerline modeling; Specifically, it includes the following steps: S11. Calculation of horizontal curve coordinates (based on the improved intersection method) S111, Input parameters: The intersection sequence is JD1(X1,Y1), JD2(X2,Y2), ..., JDn(Xn,Yn); The radius R of the circular curve; The lengths of the transition curves are Ls1 and Ls2. S112. Calculate the tangent length (including transition curve correction). in The turning angle at the intersection; S113. Calculate the coordinates of the transition curve (cyclotron integral). Use Fresnel integration to solve for the coordinates of the transition curve points: S114, Coordinate transformation to global coordinate system local coordinates Rotation direction angle Angle transformation to global coordinates Then translate it back to the original point.

[0019] The direction angle of the line connecting the intersection points is calculated as follows: in and These are the differences between the current intersection point and the previous intersection point.

[0020] S12, Calculation of vertical curve elevation S121. Calculate the slopes g1 and g2 of the two straight segments respectively. S122. Calculate the actual length of the vertical curve based on the vertical curve radius and the slope difference: S123. Calculate the elevation based on the position before and after.

[0021] S13, Error Adjustment Optimization There are systematic errors in the design parameters (radius / length of the transition curve) and the station-by-station coordinates. A least-squares optimization model is constructed to address these errors. The Levenberg-Marquardt algorithm is used to solve the problem, balancing accuracy and stability. The mathematical description and solution method of the error squared optimization model (least squares) can be divided into three main parts: objective function, constraints, and optimization algorithm.

[0022] The objective function (least square error function) requires that the calculated points... As close as possible to the actual measurement point .

[0023] expression: in: , : Calculated value; , Measured value; Number of sample points.

[0024] Constraints: The constraints include radius constraints, transition curve constraints, and curvature continuity constraints.

[0025] 1. Radius constraint: 2. Transition curve constraint: This indicates the length of the transition curve.

[0026] The length of the transition curve must be within a certain range to ensure a smooth transition when the curve enters or exits the circular arc segment.

[0027] 3. Curvature continuity constraint: The radius of two adjacent circular arc segments; Curvature; The curvature variation between adjacent segments must not be too large, limiting the maximum curvature variation. .

[0028] Optimization Algorithm: Levenberg-Marquardt Optimization Steps Levenberg-Marquardt is a numerical optimization method for nonlinear least squares problems, falling between the Gauss-Newton method and gradient descent, and is suitable for fitting problems containing nonlinear models.

[0029] Its core formula is expressed as: Meaning of each symbol: Jacobian matrix: Represents the partial derivatives of the residuals with respect to the variables. The residual vector represents the error between the calculated and measured values. Damping factor: Used to adjust the stability and convergence speed of the algorithm. identity matrix Variable update step size Working mechanism: when When the size is small, the algorithm is close to the Gauss-Newton method (fast convergence, but unstable); when When the value is large, it tends to be similar to gradient descent (stable, but converges slowly). Dynamic adjustment A balance can be struck between the two, improving optimization efficiency.

[0030] Generate the horizontal design line and output an Excel file containing the coordinates of each pile at one-meter intervals on the left and right sides. Compare the straight-curve table and design drawing data to check the error of the tunnel centerline curve parameters, ensuring the calibration error is controlled within ±0.01m. The input horizontal curve data includes the intersection point name, coordinates (X / Y), transition curve length, circular curve radius, and tangent length parameters. The input longitudinal curve data includes the elevation of the slope change point, the vertical curve radius, and the vertical curve radius parameter to obtain the curve's Z coordinate; The output file data for each station coordinate point includes the station number of the left and right lines, X coordinate, Y coordinate, design elevation, and azimuth.

[0031] The Data.ImportExcel node is used to read the X, Y, and Z coordinates of the exported stake-by-stake coordinate points. The List.RestofItems node is used to skip the header row of the Excel table, keeping only the data rows. The NurbsCurve.ByPoints node is used to create Dynamo spline curves from the point coordinates. The CurveByPoints.ByReferencePoints node is used to convert the spline curves into 3D curves in Revit, which are then imported into the Revit family for massing and serve as the positioning reference for all component family instances. The centerline of the emergency parking lane is cut using the Curve.TrimByParameter node, with the start and end stake numbers of the emergency parking lane entered.

[0032] S2. Organize the "Start and End Mileage Station Number - Lining Type" information table corresponding to different lining types from the tunnel start to the end point in the design and construction drawings, and the "Lining Type - Component Parameter" information table for all lining types. Use the standard section clearance cross section, the vehicular cross passage clearance cross section, the pedestrian cross passage clearance cross section, and the emergency parking lane tunnel clearance cross section as the tunnel outline reference; use the tunnel structural component parameters of any lining type as the tunnel structural component reference, and establish a standard outline template and a family template for standard lining type components.

[0033] Specifically: The starting and ending chainages corresponding to different lining types throughout the entire tunnel's length were compiled into an Excel spreadsheet titled "Starting and Ending Chainage - Lining Type". All lining types and their corresponding component parameters were also compiled into an Excel spreadsheet titled "Lining Type - Component Parameters". The spreadsheet includes information on the applicable cross-section, surrounding rock grade, lining type, anchor bolt length and spacing, steel mesh layout spacing, steel arch frame model and spacing (cm), initial support shotcrete, secondary lining cast-in-place concrete, and invert arch concrete material and thickness (cm), as well as material properties.

[0034] In addition, data and parameters for the standard section clearance cross-section, vehicular cross-section clearance cross-section, pedestrian cross-section clearance cross-section, and emergency parking lane tunnel clearance cross-section were obtained from the construction plan and construction drawings. A metric contour model was then created as a contour template. Using any type of tunnel lining structural component as a template, the tunnel lining and support structure were decomposed into modular component standard family templates. The established metric conventional model or metric volume model was then parameterized. Specifically, the center position, angle, and radius of the tunnel's arcs were set as type parameters when editing the contour. The lining concrete thickness, system anchor length, and locking anchor length were also set as type parameters to facilitate subsequent parametric adjustments of the lining type template parameters.

[0035] The parametric family of highway tunnels includes the parametric family of the main tunnel structure, the parametric family of the support structure, and the parametric family of the ancillary facilities. The main structure family consists of family components of different lining types, including portals, initial support and secondary lining, invert arches, and central partition walls. The support structure family includes components such as anchor bolts, steel arch frames, pipe roofs, pre-conduit pipes, and steel mesh. The ancillary facilities family includes components such as ventilation ducts, lighting systems, and fire-fighting equipment.

[0036] Finally, in the family parameter attributes, set the center position, angle, height, radius of the standard section's net cross-sectional profile, and the material and size parameters of the structural components as type parameters to establish a reusable parametric family library. In the project template's type attributes, create new identification data: sub-item ID, sub-item name, mileage station number, component name, surrounding rock grade, lining thickness, and reinforcement spacing.

[0037] S3. Read the "Start and End Mileage Station Number - Lining Type" information table for the start and end points of different lining types within the entire tunnel mileage range, match the lining type name that is appropriate for the tunnel mileage location, segment the tunnel centerline by mileage station number, and generate a model by placing the family template of standard lining type components along the centerline. The specific steps are as follows: (1) Read the Excel information table "Start and End Mileage Station Numbers - Lining Type" Use the `Data.ImportExcel` node to read the surrounding rock grade, mileage station number, lining type, and component parameters from the Excel spreadsheet. Use the `List.RestOfItems` node to skip the header row and keep only the data rows. Input the tunnel starting station number, and read the starting and ending station numbers of N different lining types sequentially. Use the `Curve.TrimByParameter` node to extract curves by mileage station number to obtain the tunnel centerline model for the corresponding mileage segment of the N lining types. Use the `Curve.Length` node to measure the curve length to verify correctness.

[0038] (2) Load the parametric family template of standard lining type components. Load the corresponding family components into the Revit project template, and use Family Types to load the parametric family template of the standard lining type components into the Dynamo file.

[0039] (3) Place parametric family template instances of standard lining type components along the centerline to generate the model; Using the FamilyInstance.ByPoint node, standard lining type structural family templates are placed in batches along the centerline at a set interval of 1m. The main structural components, ancillary facilities, and ventilation and lighting system components are then arranged to generate tunnel models for the mileage sections of N different lining types. Figure 3 As shown.

[0040] (4) Adjust the longitudinal slope angle The longitudinal slope angle is calculated based on the Z-coordinate difference of each pile point, and the family instance is rotated to match the tunnel slope. The longitudinal slope angle is set as a parameter of the family instance. (5) Use a Custom Node to encapsulate steps (3) to (5) into a custom node.

[0041] S4, such as Figure 4 As shown, the List.GroupByKey node is used to aggregate multiple columns of parameters, realizing the grouping and mapping of lining types and parameters, and matching the lining type component information that is appropriate for the tunnel mileage location. By modifying the parameters of the placed standard lining type template family instance to the specified lining type, a tunnel model with accurate N lining types and component parameters for the mileage segment is obtained. Specifically: (1) Data input and preprocessing Tunnel component parameters are entered through an Excel spreadsheet titled "Lining Type - Component Parameters." The raw data, including lining type and component parameter columns, is imported from Excel using the Data.ImportExcel node. The List.RestOfItems node is used to skip the header row, retaining only the data rows. Component parameter information for N lining types is then retrieved.

[0042] (2) Grouped by lining type In Dynamo, use the List.GroupByKey node to group data by "key" and aggregate the corresponding "value" into a list.

[0043] Input data structure: Keys input is the lining type column. Values ​​input is the associated component parameter column. Output: Grouped dictionary structure data.

[0044] (3) Parameter matching and driving The List.Map node is used to iterate through each lining type group. The corresponding parameter list is extracted from the dictionary, and the corresponding component parameters are matched based on the lining type at different tunnel mileage locations. Using the grouped dictionary structure, parameter values ​​can be directly extracted by lining type. The Element.SetParameterByName node is used to batch assign the read parameter values ​​to Revit family instance parameters, enabling automatic batch modification of metric general model or metric volume model parameters in standard family templates (ensuring parameter names strictly match the type parameter names defined in the family). Based on the data, one-click model creation dynamically adjusts the tunnel cross-section shape, main structure, lining structure, and auxiliary facility model shape, size, and material updates. The structural component parameters, sub-item project names, and start and end mileage stations corresponding to the lining type are obtained. Structural component parameters include, but are not limited to, the material, component length, thickness, outline radius, unit project name, and sub-item name from S2.

[0045] Modify the lining structure outline in the lining type template by modifying the type parameters in the family type. The thickness is achieved by modifying the type parameter D. The marker center is visible, and the option to keep concentric when changing the radius is checked.

[0046] Furthermore, by adjusting the instance parameter settings of the standard section's clearance cross-sectional profile, different cross-sectional forms are dynamically generated by inputting parameters such as center position, angle, height, and radius. The Geometry.Transform node is used to enable real-time modification of the cross-sectional shape, supporting rapid response to design changes. Variable cross-section sections use the Geometry.Morph node to achieve smooth transitions, avoiding geometric conflicts in the model. Variable cross-section sections commonly appear at opening transition sections and emergency stopping lanes.

[0047] S5. Link the tunnel models of each mileage segment in Revit according to their mileage, and complete the integration of the main tunnel, pedestrian cross passages, vehicular cross passages, and emergency stopping lanes into a single model. Figure 5 As shown.

[0048] S6, such as Figure 2 As shown, a point cloud-driven model correction engine was developed; laser scanning point cloud data was imported, and the design model was compared with the actual point cloud; compensation lining thickness parameters were automatically generated; and dynamically adjusted concrete volume and other engineering quantity statistics were output. Specifically, it includes the following steps: 1. During the data acquisition phase, a terrestrial laser scanner is used to collect point clouds of the construction surface, and the point cloud model is accurately registered with the design model. The point cloud density requirement is ≥500 points / m². 2 .

[0049] (1) Feature enhancement and registration to extract key structural feature points such as the crown and the center of the inverted arch; (2) The hierarchical registration strategy adopts global coarse registration (feature point matching) and local fine registration (full point cloud ICP).

[0050] The ICP (Iterative Closest Point) algorithm optimizes the objective function: in: Point cloud coordinates; : Design the nearest point in the model; Rotation matrix; Translation vector 2. Error Analysis Stage (1) Use the original point cloud to input the point cloud data registration module; (2) Use the Revit model input design model registration module; (3) The registration module error field is obtained by using the registered point cloud.

[0051] Error calculation model: Over-digging : under-dig in: This is the design value; These are measured values.

[0052] (4) Calculate the error distribution δ(x, y, z) between the point cloud and the model through the error field, and pass it to the compensation decision engine.

[0053] Intelligent decision-making algorithms: The coefficients are trained using machine learning.

[0054] 3. During the model update phase, the model automatically modifies the type parameters and key parameters of the parametric family by obtaining the lining thickness family instance parameters, calculating the compensation value, and completing the geometric reconstruction of the model.

[0055] The geometric update principle ensures that the inner contour of the design clearance remains unchanged, while the outer contour shifts. Dynamic adjustment of lining thickness: in For design values, To update the value.

[0056] 4. Real-time recalculation of project quantities Concrete volume compensation: Further, the automatic quantity linkage steps for the model are as follows: Using the Revit schedule, the Element.GetParameterValueByName node is used to extract component volume, length, and concrete strength parameters. The Element.Geometry and Solid.Volume nodes are used to directly calculate the concrete volume using geometry. The List.Sum node is used to sum the volumes of similar components to generate the total volume. The Schedule.ByName node is used to call a predefined schedule template in Revit. The Schedule.AddField node is used to dynamically add statistical fields for volume, length, and component type. The ScheduleExportOptions node is used to export the schedule to an Excel file, generating a quantity list and material statistics report. The quantities of each tunnel component, concrete volume, and steel usage are statistically analyzed and linked to the P6 construction schedule to provide data support for resource allocation and reduce manual quantity calculation time.

[0057] In summary, this invention provides a rapid modeling method for updating highway tunnel lining types based on Dynamo parametric methods. The main technical approach is as follows: Figure 1 As shown: Read the data from the Excel file of each station coordinate point, create a Dynamo spline curve (CurbsCurve) using the point coordinates, extract the curve by the station number, place a point family conventional model along the curve, rotate the family instance, adjust the longitudinal slope angle, and finally integrate the model.

[0058] The above description is merely an example and illustration of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the invention or exceed the scope defined in the claims, all of which should fall within the protection scope of the present invention.

Claims

1. A rapid modeling method for updating the type of highway tunnel lining based on Dynamo parameterization, characterized in that, The method comprises the following steps: S1, inputting the parameters of the horizontal curve and the longitudinal curve, dynamically optimizing the curve parameters through an iterative adjustment algorithm, generating a Dynamo parameterized curve, and establishing a three-dimensional model of the tunnel center line; S2, constructing an information table of "starting and ending point mileage pile number-lining type" and an information table of "lining type-component parameter", taking the standard section clearance cross section, the vehicle cross passage clearance cross section, the pedestrian cross passage clearance cross section, and the emergency parking belt tunnel clearance cross section as the contour reference, and establishing the parameterized family template of the standard contour template and the standard lining type component; S3, segmenting the tunnel center line according to the information table of "starting and ending point mileage pile number-lining type", and placing the family template instance of the standard lining type component along the center line at a set interval; S4, grouping and mapping the component parameters according to the lining type through a List.GroupByKey node, batch modifying the family template instance parameters to match the lining type of each mileage section, and generating an accurate tunnel model; S5, linking the models of each mileage section in the order of the mileage, and integrating the main hole, the pedestrian cross hole, the vehicle cross hole, and the emergency parking belt; S6, performing engineering quantity statistics on the integrated model, and developing a point cloud driven model correction engine to realize construction deviation compensation.

2. The quick modeling method for updating the type of highway tunnel lining based on Dynamo parameterization according to claim 1, characterized in that, The iterative adjustment algorithm in step S1 comprises: adopting a least square optimization model to dynamically calibrate the curve parameters; the objective function of the least square optimization model is expressed as: wherein: , is the calculated value; , is the measured value; is the number of sample points; the solution is obtained through a Levenberg-Marquardt algorithm, and the constraint conditions comprise: Radius constraint: Ease curve constraint: , denotes the length of the ease curve; Curvature continuity constraint: , denotes the radius of the two adjacent circular arc segments; denotes the curvature; denotes the limit of maximum curvature variation.

3. The quick modeling method for updating the type of highway tunnel lining based on Dynamo parameterization according to claim 1, characterized in that, the establishment of the parameterized family template in step S2 comprises: setting the center position, angle, radius of the tunnel contour, and the lining thickness and anchor rod length as type parameters; three types of parameterized family libraries are constructed: a main structure family library comprising a portal, primary support, secondary lining, inverted arch, and mid-partition wall; a support structure family library comprising an anchor rod, steel arch, and pipe shed; and an accessory facility family library comprising a ventilation pipe and lighting system.

4. The quick modeling method for updating the type of highway tunnel lining based on Dynamo parameterization according to claim 1, characterized in that, When placing the family template instance in step S3: Calculate the longitudinal slope angle by computing the difference in Z coordinates between the stake points Rotate the family instance to match the slope The Curve.TrimByParameter node is used to segment and intercept the center line according to the starting and ending pile numbers of the lining type.

5. The quick modeling method for updating the type of highway tunnel lining based on Dynamo parameterization according to claim 1, characterized in that, The parameter grouping and mapping in step S4 comprises: using the List.GroupByKey node to generate a dictionary with the lining type as the key and the component parameter as the value; and batch modifying the family instance parameters through the Element.SetParameterByName node, and realizing smooth transition of the variable cross section section through the Geometry.Morph node.

6. The quick modeling method for updating the type of highway tunnel lining based on Dynamo parameterization according to claim 1, characterized in that, The point cloud driven model correction engine in step S6 comprises: Point cloud registration, feature enhancement registration and hierarchical ICP algorithm are adopted, and the objective function of the hierarchical ICP algorithm is: ; Bias compensation decision: based on error field Dynamic adjustment of lining thickness , the outer contour according to Update; Compensation amount calculation model: The coefficients are obtained by machine learning training.

7. The quick modeling method for updating the type of highway tunnel lining based on Dynamo parameterization according to claim 1, characterized in that, the engineering quantity statistics are realized through the following ways: calculating the geometric volume of the component using the Solid.Volume node; and dynamically generating a detailed table containing the volume, length, and component type through the Schedule.AddField node, and associating the P6 construction progress plan.

8. The quick modeling method for updating the highway tunnel lining type based on Dynamo parameterization according to claim 6, characterized in that, The bias compensation strategy includes: increasing the thickness of the shotcrete when locally over-excavating ; adjusting the excavation contour line when local underexcavation occurs; translating the design center line when overall deviation occurs. 9.An electronic device comprising a memory and a processor, the memory storing a computer program, wherein, The processor executes the computer program to realize the steps of the method in any one of claims 1-9.

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