A high-precision airport pavement model parameterization fast generation method

Abstract

The application discloses a high-precision airport runway pavement model parameterization fast generation method and belongs to the technical field of building information modeling. In view of the problems of poor fault tolerance of existing pavement block modeling in dependence on a rule grid and height matching and lack of post-checking, a parameterization design platform and a building information modeling platform are cooperated, boundary, thickness partition and height text information in pavement drawings are fitted by a curved surface, vertex center points are clockwise sequenced and three-dimensional space nearest point matching is carried out, and the information is converted into a standardized space coordinate library; a rear section reads the coordinate library, recombines pavement block closed boundaries, calls original floor commands to generate pavement structure models in batches, and establishes an error identification rule library to reverse map and recheck. The application realizes automatic batch modeling of special-shaped boundaries and irregular block pavements, relaxes alignment constraints of height text labeling positions, improves data matching fault tolerance, ensures reliability of large-scale model generation, and is suitable for runway engineering design and construction stages.

Description

Technical Field

[0001] This invention belongs to the field of building information modeling technology, specifically relating to a high-precision method for rapid parametric generation of airport pavement models, applicable to pavement block-by-block batch modeling and data verification during the design and construction phases of airfield engineering. Background Technology

[0002] Airport pavement (including runways, taxiways, aprons, etc.) is typically constructed using concrete blocks, with joint lines in both the longitudinal and transverse directions to release temperature stress. Traditional airport pavement modeling has low precision requirements, generally only modeling sections based on different thicknesses, without the need for independent modeling of each pavement block. However, with the widespread application of Building Information Modeling (BIM) technology in civil aviation airports, many airports now use BIM models for quantity surveying and construction management. The precision of traditional block modeling is no longer sufficient, necessitating independent modeling of each pavement block, with the elevation of each corner point consistent with the block elevation map. For example, a 100,000-square-meter apron can have thousands to tens of thousands of pavement panels and tens of thousands of elevation data points. Manually modeling and adjusting the elevation of each block is time-consuming and labor-intensive, and prone to human error leading to discrepancies between the model and the drawings.

[0003] Chinese invention patent application CN113468637A discloses a BIM-based method for modeling airport pavements. The key technical point is to use the floor slab command in Revit to draw individual pavement block models, then copy and assemble them, and finally adjust the top elevation of each block sequentially. However, this method still relies heavily on manual modeling. Given the massive amount of data on pavement block elevations, the actual workload is enormous, making it difficult to meet project deadlines.

[0004] Chinese invention patent application CN119293911A discloses an automated modeling method for airport pavement blocks based on BIM technology. The technical solution uses Dynamo within the Revit single platform to convert CAD block elevation maps into pavement block models. This method first imports and decomposes a CAD drawing containing seam lines and elevation text into Revit. Then, in Dynamo, the elevation text is picked up and converted into numbers and coordinate points. The horizontal, vertical, and leftmost starting seam lines are picked up and converted into lines. The vertical starting point is obtained by intersecting the leftmost vertical starting line with the horizontal seam line. The starting points are then sorted by Y-value, and the horizontal lines are sorted from top to bottom. Ordered point groups are obtained by intersecting the ordered horizontal and vertical lines, and sorted from left to right within each group. Simultaneously, elevation coordinate points are filtered and reorganized based on their vertical distance to the horizontal lines, and sorted within each group by distance from the starting point. Since the elevation values ​​and text coordinate points initially follow the same order, the same sorting parameters are input to obtain ordered elevation number groups. Finally, the ordered point groups and ordered elevation numbers are combined to obtain the top corner coordinates. The bottom corner coordinates are obtained by copying downwards according to thickness. The four points on the top surface and the four points on the bottom surface are combined into a matrix of eight points and sorted clockwise. Eight-point adaptive families are placed in batches using the Adaptive Component.By Points node, generating pavement blocks in Revit.

[0005] As is well known to those skilled in the art, the Rhino / Grasshopper platform has advantages in NURBS surface fitting and complex geometric algorithm processing, while the Revit / Dynamo platform has advantages in structural model generation and engineering attribute management. Cross-platform data transfer through standardized data interfaces is a common practice in the field of Building Information Modeling (BIM). The "floor creation command" and "inject elevation control points" mentioned in this article correspond to the Floor.ByOutlineTypeAndLevel node in the Dynamo for Revit platform, used for batch generation of structural floor slabs, and the Floor.AddPoint node, used for adjusting the elevation distribution of the floor slab's top surface, respectively. Both nodes are parameterized driver interfaces for Revit's native structural floor slab objects and can be called without the need for additional custom family files.

[0006] However, the aforementioned existing technologies still have the following shortcomings: First, this method relies entirely on the regular intersection of horizontal and vertical seam lines in CAD drawings to generate grid points, and is only applicable to pavement areas with regular boundaries and standard rectangular blocks. For complex geometric shapes such as curved transition sections at the edge of the apron, fan-shaped radial blocks, or irregular boundaries, the seam line intersection method is difficult to apply directly and requires a lot of manual intervention for boundary correction. Second, the matching of elevation text and grid points relies on the "vertical distance from the point to the horizontal line" for filtering, which means that the elevation text must be roughly aligned with the horizontal line in the drawing. If the annotation position is offset from the grid point or the seam lines in the drawing are irregular, the method will fail. First, if the data is not fully integrated, matching is prone to failure or mismatch. Second, the method uses an 8-point adaptive family as the pavement block entity, with each block being an independent family instance. Although it can achieve shape expression, the adaptive family is not as convenient as Revit's native structural floor slab in terms of structural engineering quantity statistics, material list output, and subsequent operation and maintenance management. Moreover, placing a large number of family instances in batches has an adverse impact on the model file size and running performance. Third, the existing method only has a forward generation process and lacks a post-verification mechanism for the generated results. Once there are null values, bad points, or irregular blocks in the original data, the errors will be directly carried into the final model. In large-scale models, it is extremely difficult to manually check the error location block by block. Summary of the Invention

[0007] To address the aforementioned shortcomings of existing technologies, this invention provides a high-precision, parameterized, and rapid generation method for airport pavement models. This method employs a dual-platform collaboration between a parametric design platform and a building information modeling (BIM) platform. The front-end transforms the boundary, thickness partitioning, and elevation text information from pavement drawings into a structured 3D spatial coordinate library through surface fitting, vertex sorting, and 3D nearest point matching. The back-end reads this coordinate library, reconstructs the pavement block closure boundaries, calls native floor slab commands to batch generate pavement structure models, and establishes an error identification rule base for reverse mapping verification.

[0008] Specifically, the method of the present invention includes two interconnected stages: parametric fitting of the surface and construction of a standardized spatial coordinate library, and batch generation of pavement models and error verification.

[0009] In the stage of parametric fitting and standardized spatial coordinate library construction, the pavement block surfaces are first fitted based on the pavement database in the parametric design platform to obtain a pavement block surface reconstruction information library. Unlike existing technologies that rely on the intersection of horizontal and vertical seam lines to obtain regular grid points, this invention first imports drawings containing pavement block dimensions, pavement elevation, pavement type regions, and pavement field boundary information into the parametric design platform. Layers are merged according to pavement elevation, pavement boundary, pavement region, and pavement seam lines. After filtering out pavement boundary and pavement region information, pure planar pavement field surfaces are fitted according to different pavement thickness regions. The field planes of different regions are marked and grouped, thereby establishing a surface geometry foundation that can directly handle irregular boundaries and multi-thickness transition regions.

[0010] Subsequently, the vertex set of each segmented surface is deconstructed, and the vertexes are sorted clockwise by polar angle with the center point of each segmented surface as the center and a preset direction as the reference, resulting in an ordered vertex list. This sorting method does not depend on the horizontal and vertical axes of the global coordinate system, but rather on the local polar angle sorting based on the geometric center of the segment itself. Therefore, it can obtain the correct vertex order for subsequent closed boundary construction for curved boundaries, fan-shaped radial segments, or arbitrary polygonal segments, solving the problem of boundary closure failure caused by the disorder of vertices in irregular segments.

[0011] After obtaining the ordered vertex list, this invention further deconstructs the elevation text in the drawing into spatial points, that is, filters out the pavement elevation information, deconstructs the elevation text to obtain text values ​​and corresponding X-axis and Y-axis vector components in the working plane, and sets the Z-axis spatial vector component to a preset offset height. Combined with the X-axis and Y-axis vector components, the spatial points of the elevation text are reconstructed. Then, using each vertex in the ordered vertex list as the starting point and the spatial points of the elevation text as the ending point, a three-dimensional Euclidean distance is calculated to obtain a distance matrix. The distance matrix is ​​then processed in descending order by each vertex to obtain the nearest distance point index for each vertex. The text values ​​are then sorted according to this index to obtain elevation files that correspond one-to-one with the ordered vertex list. Finally, a standardized spatial coordinate library is fitted and output. Through three-dimensional spatial nearest point matching, the annotation position of the elevation text in the drawing does not need to be strictly aligned with the vertices of the pavement blocks. Even if there is an offset or irregular seam lines in the drawing, the elevation value can be automatically and accurately attached to the corresponding block vertex, significantly improving the fault tolerance and automation of data matching.

[0012] In the pavement model batch generation and error verification stage, the standardized spatial coordinate library mentioned above is read from the Building Information Modeling (BIM) platform, refitted into a list of spatial point coordinates, and the point coordinates in the list are read sequentially to construct closed pavement block boundary polylines. Then, the pavement structural model is generated in batches by calling the floor slab creation command according to pavement thickness partitions. Specifically, pavement type data is read, the elevation is set to the Wusong elevation system, and the Floor.ByOutlineTypeAndLevel command is called through surface contours and elevations to create pavement structural models in batches according to pavement thickness partitions. Unlike existing technologies that use 8-point adaptive families, this invention directly calls the Revit native structural floor slab command. The generated pavement panels have complete structural properties and can be directly used in quantity surveying, material list output, and subsequent operation and maintenance management, while avoiding the adverse effects of a large number of family instances on model file size and performance.

[0013] After generating pavement structure models in batches, elevation control points are further injected into the pavement structure models to make the top surface of the pavement structure models conform to the elevation distribution of the corresponding segmented pavement surfaces. This achieves accurate expression of surface elevation while maintaining the original floor slab engineering attributes. This post-injection method simplifies complex processes and eliminates the need to pre-create complex adaptive family files, enabling batch-generated flat pavement surfaces to conform to the actual surface elevation.

[0014] Furthermore, this invention establishes an error identification rule base, cleans the standardized spatial coordinate library while retaining the original index, identifies the serial numbers of the cleaned anomalies, and uses these anomaly serial numbers to back-map to the generated model components, thus locating the faulty pavement panels. This post-validation mechanism enables null values, bad spots, or irregular blocks in the original data to be automatically identified and located during the generation stage, eliminating the need for manual block-by-block checks and significantly improving the reliability of large-scale pavement model generation.

[0015] The beneficial effects of this invention are as follows: by replacing the intersection of seam lines with surface fitting, the problem of automated modeling of irregular boundaries and irregular blocks is solved; by replacing the vertical distance screening of horizontal lines with the nearest point matching in three-dimensional space, the strict alignment requirements for the position of elevation text annotations are relaxed, and the data fault tolerance is improved; by replacing the adaptive family with the native structural floor slab command, the complete engineering attributes of the floor slab are given while maintaining the lightweight of the model; and by establishing an error identification rule base, the posterior localization and reverse mapping verification of data anomalies are realized, ensuring the accuracy and reliability of models generated in large batches. Attached Figure Description

[0016] Figure 1 The overall system diagram shows the dual-platform collaborative architecture of the front-end "pavement segmentation surface fitting" module and the back-end "model generation and rule matching" module, as well as the elimination loop for erroneous components.

[0017] Figure 2 This is a schematic diagram of the pavement plan of an airport bay, showing a mixed distribution of curved boundaries, fan-shaped radial blocks, and standard rectangular blocks.

[0018] Figure 3 This is a schematic diagram of the pavement structure, showing the combination of a 42cm concrete surface layer, a 20cm water-stabilized upper base course, a 20cm water-stabilized lower base course, and a 50cm mountain stone cushion layer.

[0019] Figure 4 This is a schematic diagram of the Grasshopper battery pack output from a standardized spatial information database, showing the connection relationships between nodes for sorting around the center point, 3D distance calculation, elevation text deconstruction, and coordinate export.

[0020] Figure 5 This diagram illustrates the Dynamo node flow for reconstructing pavement block boundaries, showing the data flow of Excel data import, unit conversion, List.Clean cleaning, PolyCurve closure, and Floor.ByOutlineTypeAndLevel batch node generation. Detailed Implementation

[0021] The invention is described in detail below using an airport apron pavement project as an example. The total area of ​​the apron pavement is approximately 470,000 square meters. The pavement structure, from top to bottom, consists of a 42cm concrete surface layer, a 20cm cement-stabilized crushed stone upper base layer, a 20cm cement-stabilized crushed stone lower base layer, and a 50cm mountain stone subbase layer. The pavement is divided into multiple areas according to thickness and function, including a 42cm concrete pavement, a 28cm concrete pavement, a 12cm concrete pavement, and a transition pavement between 28cm and 42cm. The pavement boundaries include straight sections and curved transition sections, and the block form includes standard rectangular blocks and fan-shaped radial irregular blocks.

[0022] I. Parametric Fitting of Surfaces and Construction of Standardized Spatial Coordinate Library Import CAD drawings containing pavement block dimensions, pavement elevation, pavement type areas, and pavement site leveling boundary information into the Rhino platform. Organize the drawings by merging layers according to pavement elevation, pavement boundaries, pavement areas, and pavement joint lines, so that different types of spatial information belong to independent layers, which facilitates subsequent batch filtering and reading.

[0023] The geometric information in the pavement boundary and pavement region layers is filtered out, and pavement field surfaces are fitted in a pure plane according to different pavement thickness regions. Specifically, surface fitting is performed on the 42cm concrete pavement region, the 28cm concrete pavement region, the 12cm concrete pavement region, and the 28cm to 42cm transition pavement region to obtain the field planes of each region, denoted as 42cm-surface, 28cm-surface, 12cm-surface, and 28~42cm-surface. The surface of each region is offset by a preset distance to obtain the offset surface set used for subsequent vertex deconstruction, denoted as 42cm-surface-2, 28cm-surface-2, 12cm-surface-2, and 28~42cm-surface-2, to adapt to the spatial positioning requirements of the pavement structure layer.

[0024] The Grasshopper platform is invoked to identify the offset surface sets according to the above grouping, and non-surface items in the list are removed to ensure the consistency of the geometric type of the input data. Each filtered surface is deconstructed to obtain the vertex set of each surface. A control point list, list1, is created, ensuring that the order of the control points matches the order of the offset surface sets, and that the vertex sets of each surface are grouped separately into a list, list2.

[0025] The control points in list2 are then reordered. The center point of each set of surface vertices is calculated. Using this center point as the center and a preset direction as the reference, the vertices within the group are sorted clockwise by polar angle, forming a new ordered vertex list list3. This sorting process is based on the local geometric center of the block itself and does not depend on the horizontal and vertical axes of the global coordinate system. Therefore, for the curved transition sections and fan-shaped radial irregular blocks at the edge of the apron, the correct vertex order that can be used for subsequent closed boundary construction can be obtained.

[0026] Text objects in the track surface elevation information layer are filtered out. The elevation text in the drawing is deconstructed to obtain the numerical content of each text, forming a text value list (list4). Simultaneously, the X-axis and Y-axis vector components of each text object in the corresponding working plane are obtained, forming a vector component list (list5). The spatial coordinates of the elevation text are reconstructed, and the spatial vector component of the Z-axis is set to a preset offset height of 5. Combining this with the X-axis and Y-axis vector components in list5, a new set of spatial points for the elevation text is obtained through refitting.

[0027] Using each vertex in the ordered vertex list of list3 as the starting point A and each point in the elevation text spatial point set as the ending point B, calculate the three-dimensional spatial distance between the two points. According to the ordinary three-dimensional Euclidean distance formula, the distance d between point P1(x1, y1, z1) and point P2(x2, y2, z2) is: The calculation results form a distance list, list6. List6 is then sorted in descending order by each vertex to obtain the index or sequence number of the nearest point to each vertex within list6, forming an index list, list7. Using the data in list7 as indices, the text values ​​in list4 are sorted to obtain the elevation file, list8, which corresponds one-to-one with the ordered vertex list in list3.

[0028] The X-axis and Y-axis coordinates of spatial points are defined using the X-axis and Y-axis vector components in list5, respectively, and the Z-axis coordinates are defined using the elevation values ​​in list8. A new list of three-dimensional spatial coordinate points, list9, is then created through refitting. This list represents the three-dimensional spatial coordinates of each pavement segment. This list is then exported as a text file (text1) in an Excel-readable (x, y, z) coordinate format, while retaining the thickness partition type encoding. This serves as a standardized spatial coordinate library for the connection between the front and rear platforms.

[0029] II. Batch Generation and Error Verification of Pavement Models The Dynamo platform is invoked to construct file reading rules and read the data within text1. Since the coordinate data exported from the Rhino platform is usually in meters, while the Revit platform's internal coordinate system uses millimeters, a unit conversion is performed after the data is read, magnifying the coordinate values ​​by a factor of one thousand and refitting them into the Revit spatial point coordinate list list10.

[0030] The system reads the point coordinates in list10 sequentially, groups the vertex coordinates of the same pavement block, constructs a closed PolyCurve, and forms list11, which represents the pavement block boundary polyline. It then reads the pavement type data and thickness partition type code, sets the elevation to the Wusong elevation system, and uses the native floor slab creation command `Floor.ByOutlineTypeAndLevel` based on the surface profile and elevation to create pavement structure models in batches according to the partition types: 42cm concrete pavement, 28cm concrete pavement, 12cm concrete pavement, and 28cm to 42cm transition pavement. This process is data-driven and automatically matches the floor slab type, eliminating the need for manual selection of each block.

[0031] After generating pavement structure models in batches, elevation control points are further injected into each pavement structure model to make the top surface of the pavement structure model conform to the actual elevation distribution of the corresponding pavement surface blocks. This achieves accurate expression of surface elevation while maintaining the original structural floor slab engineering properties.

[0032] An error identification rule base was established, and list10 was traversed and cleaned. The `List.Clean` node was called to clean the spatial coordinate data, preserving the original index positions to maintain the correspondence between the list numbers before and after cleaning. The anomaly numbers were identified, specifically data items with empty Z-axis coordinates and list items with more than 4 vertices. Using the original anomaly number as an index, the generated model components were matched in reverse to automatically locate the erroneous path panels or irregularly shaped block components. The location results were output as a review report for manual verification and correction.

[0033] Through the above process, tens of thousands of pavement panels for the apron pavement project were generated in batches in a short period of time. The generated pavement panel models and block elevation maps maintained high precision and had complete structural engineering quantity statistics attributes, which can be directly used for digital construction management in the subsequent construction phase.

[0034] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for rapid parameterization and generation of high-precision airport pavement models, characterized in that, The method employs a dual-platform approach, combining a parametric design platform and a building information modeling (BIM) platform. The front-end transforms the boundary, thickness zoning, and elevation text information from pavement drawings into a structured 3D coordinate library through surface fitting, vertex sorting, and 3D nearest point matching. The back-end reads this coordinate library to reconstruct the closed boundaries of pavement blocks, calls native floor slab commands to batch generate pavement structural models, and establishes an error identification rule base for reverse mapping verification. The method includes the following steps: S1. Parametric Fitting of Surfaces and Construction of Standardized Spatial Coordinate Library: In the parametric design platform, the pavement block surfaces are fitted based on the pavement database to obtain a pavement block surface reconstruction information library; the vertex set of each pavement block surface is deconstructed and sorted clockwise with the center point of each pavement block surface as the center to obtain an ordered vertex list; the elevation text in the drawing is deconstructed into spatial points, the three-dimensional spatial distance between each vertex in the ordered vertex list and the set of spatial points of the elevation text is calculated, and the elevation value is matched for each vertex according to the nearest distance principle to generate and output a standardized spatial coordinate library that corresponds one-to-one with the ordered vertex list; S2. Batch generation and error verification of pavement models: Read the standardized spatial coordinate library in the building information modeling platform, reorganize the closed boundaries of pavement blocks in sequence, and call the floor slab creation command to generate pavement structure models in batches according to pavement thickness; establish an error identification rule library, locate abnormal items in spatial coordinate data, and back-map the abnormal item number to the generated model components to complete the error verification of pavement panels.

2. The method for rapid generation of high-precision airport pavement model parameters according to claim 1, characterized in that, In S1, the fitting of the pavement block surface based on the pavement database includes: The drawings containing pavement block dimensions, pavement elevation, pavement type area, and pavement site leveling boundary information are imported into the parametric design platform. Layers are merged according to pavement elevation, pavement boundary, pavement area, and pavement joint line. The pavement boundary and pavement area information are filtered out. Pure plane pavement site surface fitting is performed according to different pavement thickness areas, and the site pavement planes of different areas are marked and grouped. The different pavement thickness areas include 42cm concrete pavement, 28cm concrete pavement, 12cm concrete pavement, and 28~42cm transition pavement.

3. The method for rapid generation of high-precision airport pavement model parameters according to claim 1, characterized in that, In S1, the clockwise sorting based on the center point of each segmented surface includes: Obtain the vertex set of each segmented surface, calculate the center point of each segmented surface, and sort the vertex set clockwise with the center point as the center and the preset direction as the reference to form the ordered vertex list.

4. The method for rapid generation of high-precision airport pavement model parameters according to claim 1, characterized in that, In S1, the step of deconstructing the elevation text in the drawing into spatial points includes: The elevation information of the track surface is filtered out, the elevation text in the drawing is deconstructed, the text value and the corresponding X-axis and Y-axis vector components in the working plane are obtained, the Z-axis spatial vector component is set to a preset offset height, and the elevation text spatial points are reconstructed by combining the X-axis and Y-axis vector components.

5. The method for rapid generation of high-precision airport pavement model parameters according to claim 1, characterized in that, In S1, the calculation of three-dimensional spatial distance and matching of elevation values ​​according to the nearest distance principle includes: Starting from the vertices in the ordered vertex list and ending at the elevation text spatial points, calculate the three-dimensional Euclidean distance to obtain a distance matrix; sort the distance matrix in descending order by each vertex to obtain the nearest distance point index corresponding to each vertex; sort the text values ​​according to the index to obtain the elevation file that corresponds one-to-one with the ordered vertex list, and then fit it to obtain the standardized spatial coordinate library.

6. The method for rapid generation of high-precision airport pavement model parameters according to claim 1, characterized in that, In S2, the sequential reorganization of pavement block closure boundaries includes: The standardized spatial coordinate library is read from the building information modeling platform and refitted into a list of spatial point coordinates. The point coordinates in the list of spatial point coordinates are read in sequence to construct a closed pavement block boundary polyline.

7. The method for rapid generation of high-precision airport pavement model parameters according to claim 1 or 6, characterized in that, In S2, the step of batch generating pavement structure models by calling the floor slab creation command according to pavement thickness partitioning includes: Read the pavement type data, set the elevation to use the Wusong elevation system, and call the Floor.ByOutlineTypeAndLevel command through the surface profile and elevation to create pavement structure models in batches according to the pavement thickness.

8. The method for rapid generation of high-precision airport pavement model parameters according to claim 7, characterized in that, After generating pavement structure models in batches, elevation control points are injected into the pavement structure models so that the top surface of the pavement structure models conforms to the elevation distribution of the corresponding segmented pavement surfaces.

9. The method for rapid generation of high-precision airport pavement model parameters according to claim 1, characterized in that, In S2, establishing the error identification rule base includes: The standardized spatial coordinate library is cleaned while retaining the original index. The anomaly numbers that have been cleaned are identified and mapped back to the generated model components using the anomaly numbers to locate the error path panel.

10. The method for rapid generation of high-precision airport pavement model parameters according to claim 1, characterized in that, The parametric design platform mentioned in S1 is Rhino / Grasshopper, and the building information modeling platform mentioned in S2 is Revit / Dynamo.

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