Bridge superstructure and substructure dual driving adaptive modeling method and system

Abstract

The application discloses a bridge superstructure and substructure double-driving adaptive modeling method and system, wherein the modeling method comprises the following steps: a dynamic local coordinate system is established based on a bridge span line and a route normal line, a space included angle theta is obtained, and a virtual cutting plane is constructed; a three-dimensional boolean difference set operation is performed on a standard beam segment and the virtual cutting plane, and a skew beam segment geometric model is generated; a planar projection contour polygon of each pier is extracted, the contour polygon is discretized into a sample point set, ray collision detection is performed, terrain elevation is obtained, and the elevation range and local terrain cross slope in the contour range are calculated; when the local terrain cross slope exceeds a preset threshold, adaptive calculation of a stepped foundation or a non-equal-height pier is triggered, and top and bottom surface elevations are output; a parameter topology dependency graph is established; when local changes occur in the bridge span line or the digital terrain model data, the parameter topology dependency graph is traversed, affected nodes are marked as dirty nodes, and only the incremental recalculation of branch links where the dirty nodes are located is performed.

Description

Technical Field

[0001] This invention relates to the field of building information modeling technology, and in particular to a dual-drive adaptive modeling method and system for the superstructure and superstructure of bridges. Background Technology

[0002] In highway, railway, and municipal bridge engineering, bridges are often built in areas with complex terrain and varied route conditions. Skew bridges and undulating terrain are extremely common design scenarios. Skew bridges are bridges whose span structure's arrangement axis (span line) has a non-orthogonal angular relationship with the longitudinal axis of the piers and abutments (route normal). The geometry of each beam end, diaphragm, and end of the superstructure must be specifically adjusted according to the skew angle.

[0003] Existing BIM software has two significant shortcomings when dealing with such complex situations: First, for the problem of skewed superstructures, it usually relies on manually rotating model components or pre-creating several sets of irregular template families according to angle classification. When the skewed angle exceeds the preset range or precise angle adaptation is required, this method is time-consuming, has geometric errors, and cannot cover the continuous angle range from 0° to 180°. Second, for the problem of terrain adaptation of the substructure, the elevation of the piers and abutments foundations needs to be manually entered by the designers after reading the topographic map. When the terrain is undulating and there are many piers, the workload is huge and there are many manual intervention steps. Data transfer is prone to errors, which seriously affects the design accuracy and efficiency.

[0004] Then, existing patents, such as CN115017569A, disclose a method, device, equipment, and medium for two-dimensional and three-dimensional linkage parametric modeling and drawing of bridges, including: S1, parametricizing bridge components and generating parametric bridge component definitions; S2, creating a three-dimensional bridge model based on the parametric bridge components; S3, generating two-dimensional bridge drawings based on the parametric bridge components and the three-dimensional bridge model; S4, linking and updating the three-dimensional bridge model and the two-dimensional bridge drawings, used for updating the two-dimensional bridge drawings in conjunction with changes in design parameters through the three-dimensional bridge model during bridge design; or, updating the three-dimensional bridge model in conjunction with changes in design parameters through the two-dimensional bridge drawings. Although the above patent has powerful verification and real-time dynamic update functions, when dealing with the relationship between the substructure and the terrain, it still relies on a single center point elevation reading method, failing to consider the local undulation characteristics of the terrain within the foundation projection outline. When the terrain has a lateral slope, a single elevation point cannot reflect the true spatial relationship between the foundation bottom surface and the terrain, easily leading to foundation suspension or over-excavation.

[0005] To address the aforementioned technical problems, this invention proposes a dual-drive adaptive modeling method and system for the superstructure and superstructure of bridges. Summary of the Invention

[0006] The purpose of this invention is to address the shortcomings of existing technologies by providing a dual-drive adaptive modeling method and system for the upper and lower structures of bridges, which solves the problems of geometric conflicts and elevation mismatch between the upper and lower structures of large skew bridges in complex terrain.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] A dual-drive adaptive modeling method for bridge superstructures includes:

[0009] A dynamic local coordinate system with the pier center point as the origin is established based on the span line and the route normal. The spatial angle θ between the span line and the route normal on the horizontal projection plane is obtained. A virtual cutting plane is constructed based on the spatial angle θ. A three-dimensional Boolean difference operation is performed between the standard beam segment and the virtual cutting plane to generate the geometric model of the skew beam segment.

[0010] Extract the planar projection contour polygon of each pier in the oblique coordinate system, discretize the contour polygon into a set of sampling points, perform ray collision detection with the digital terrain model along the gravity direction, obtain the terrain elevation of each sampling point, and calculate the elevation range and local terrain cross slope within the contour range based on the terrain elevation. When the local terrain cross slope exceeds the preset threshold, trigger the adaptive solution of stepped foundations or piers of unequal height, and output the top and bottom surface elevations.

[0011] A parametric topology dependency graph is established based on the spatial angle θ, the digital terrain model, and the geometric parameters of the upper and lower components. When the data of the cross line or the digital terrain model changes locally, the parametric topology dependency graph is traversed, the affected nodes are marked as dirty nodes, and only the branch links where the dirty nodes are located are incrementally recalculated to update the geometric model of the skew beam segment and the top and bottom surface elevations.

[0012] Furthermore, the establishment of a dynamic local coordinate system with the center point of the pier as the origin is specifically as follows: with the design point of the pier center as the origin O, the route normal direction as the positive X-axis direction, the span direction as the positive Y-axis direction, and the plumb line direction as the positive Z-axis direction, a local spatial rectangular coordinate system O-XYZ is established.

[0013] Furthermore, the construction of the virtual cutting plane specifically involves:

[0014] Let the normal vector n of the virtual cutting plane be expressed as:

[0015] n=(cosθ,sinθ,0);

[0016] If the virtual cutting plane passes through the end point P0(X0, Y0, Z0) of the beam segment, then the spatial equation of the virtual cutting plane is expressed as:

[0017] cosθ·(x-x0)+sinθ·(y-y0)=0;

[0018] Where n represents the normal vector of the cutting plane; x, y, z represent the coordinates of any point on the virtual cutting plane.

[0019] Furthermore, the three-dimensional Boolean difference operation specifically includes:

[0020] Retrieve the boundary representation model of the standard orthogonal beam segment, extract the spatial coordinates of all vertices in the boundary representation model, and construct the vertex matrix V;

[0021] Construct a rotation transformation matrix R(θ) based on the spatial angle θ, and obtain the transformed vertex matrix based on the vertex matrix V and the rotation transformation matrix R(θ); where the rotation transformation matrix R(θ) is expressed as:

[0022] ;

[0023] By performing a three-dimensional Boolean difference operation on the transformed vertex matrix using the virtual cutting plane, the geometry on the normal side of the virtual cutting plane is eliminated, generating the geometric model of the oblique beam segment.

[0024] Furthermore, the discretization of the contour polygon into a set of sampling points specifically involves:

[0025] Obtain the outer envelope projection polygon S of the substructure foundation on the horizontal projection plane. According to the preset sampling precision parameter d, discretize the internal region of the projection polygon S into a set P = {P1, P2, ..., P...} containing k sampling points. k}, where P i =(x i ,y i ), i∈1,2,…,k.

[0026] Furthermore, the ray collision detection specifically involves:

[0027] For any sampling point P in the set of sampling points P i A virtual ray is emitted along the direction of gravity, where the virtual ray is represented as:

[0028] R(t) = O i + tD;

[0029] O i = (x i , y i Z max );

[0030] D = (0, 0, -1);

[0031] Where R(t) represents the coordinates of a point on the ray at a distance t from the starting point; O it represents the origin of the ray; t represents the distance moved along the direction from the origin; D represents the direction vector; Z represents the direction vector. max This represents a preset constant greater than the maximum elevation of the digital terrain model; x i , y i This represents the planar coordinates of the i-th sampling point on the horizontal projection plane.

[0032] Furthermore, the specific steps for obtaining the terrain elevation of each sampling point are as follows:

[0033] The ray parameters of the virtual ray and the triangular facets in the digital terrain model are calculated and expressed as follows:

[0034] ;

[0035] E1=V 1- V0;

[0036] E2=V 2- V0;

[0037] Where V0, V1, and V2 represent the vertex coordinates of the triangular facet; E1 and E2 represent the two edge vectors of the triangular facet; u and v represent the centroid coordinates of the intersection point within the triangular facet; and t' represents the ray parameter.

[0038] Calculate sampling point P based on ray parameter t. i Terrain elevation Z i , is represented as:

[0039] Z i =Z max- t';

[0040] Traverse the set of sampling points P to obtain the set of terrain elevations H={Z1,Z2,...,Z...} within the projected polygon S. k}

[0041] Furthermore, the conditions for triggering the adaptive solution of stepped foundations or unequal-height piers also include:

[0042] The offset of the center of gravity of the cap beam exceeds the preset safe eccentricity limit, which is determined based on the flexural bearing capacity of the pier section.

[0043] Furthermore, the incremental recalculation specifically refers to:

[0044] Set the spatial angle θ and the digital terrain model as the root node, and set the geometric parameters of the upper and lower components as leaf nodes to construct a parameter dependency graph between the root node and the leaf nodes.

[0045] When the layout line or digital terrain model undergoes local changes, only the spatial angle θ node or digital terrain model node affected by the change is marked as a dirty node.

[0046] Traverse and recalculate all nodes on the directed edge path marked as dirty nodes, skipping unaffected nodes.

[0047] Correspondingly, a dual-drive adaptive modeling system for bridge superstructures is also provided, including:

[0048] The superstructure calculation module is used to establish a dynamic local coordinate system with the center point of the pier as the origin based on the span line and the route normal, obtain the spatial angle θ between the span line and the route normal on the horizontal projection plane, construct a virtual cutting plane based on the spatial angle θ, perform a three-dimensional Boolean difference operation on the standard beam segment and the virtual cutting plane, and generate a geometric model of the skew beam segment.

[0049] The substructure adaptive module is used to extract the planar projection contour polygons of each pier in the oblique coordinate system, discretize the contour polygons into a set of sampling points, perform ray collision detection with the digital terrain model along the gravity direction, obtain the terrain elevation of each sampling point, and calculate the elevation range and local terrain cross slope within the contour range based on the terrain elevation. When the local terrain cross slope exceeds the preset threshold, the adaptive solution of the stepped foundation or piers of unequal height is triggered, and the top and bottom surface elevations are output.

[0050] The upper and lower linkage incremental update module is used to establish a parameter topology dependency graph based on the spatial angle θ, digital terrain model, and geometric parameters of upper and lower components. When the layout line or digital terrain model data undergoes local changes, the parameter topology dependency graph is traversed, the affected nodes are marked as dirty nodes, and only the branch links where the dirty nodes are located are incrementally recalculated to update the geometric model of the skew beam segment and the top and bottom surface elevations.

[0051] Compared with the prior art, the beneficial effects of the present invention are:

[0052] 1. Break through the bottleneck of large oblique angle modeling: Introduce three-dimensional Boolean cutting matrix and geometric compensation function to make the geometric solution of beam end and diaphragm under continuous oblique angles from 0° to 180° mathematically rigorous, and completely abandon exhaustive templates.

[0053] 2. Resolve the coupling conflict between oblique intersections and undulating terrain: The projection profile and DTM ray collision detection technology are used to replace the traditional single-point elevation reading. It can automatically identify areas with steep cross slopes and adaptively generate piers of different heights or stepped foundations, avoiding foundation suspension or excessive excavation.

[0054] 3. Low-latency dynamic reconstruction: Introducing topology dependency graph technology for incremental updates significantly reduces the computational cost of full model recalculation when design changes occur, and improves the real-time interactive experience of forward design. Attached Figure Description

[0055] Figure 1 This is a flowchart of a dual-drive adaptive modeling method for the superstructure and superstructure of a bridge, provided in Embodiment 1.

[0056] Figure 2 This is a timing diagram of a dual-drive adaptive modeling method for the superstructure and superstructure of a bridge provided in Embodiment 1;

[0057] Figure 3 This is a flowchart of the precise solution for the oblique intersection of the superstructure provided in Example 1;

[0058] Figure 4 This is the adaptive flowchart of the lower structure provided in Embodiment 1. Detailed Implementation

[0059] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other.

[0060] Existing technologies for parametric bridge modeling typically treat the superstructure alignment calculation and the substructure terrain matching separately. When faced with complex conditions such as large-angle crossings (e.g., θ approaching an extreme value) and severe undulations in the transverse terrain, simple slant cutting and elevation readings can lead to large areas of the pier foundations being suspended or deeply buried on the transverse slope, and the asymmetric load eccentricity caused by the skew cannot be corrected in the terrain matching process.

[0061] The purpose of this invention is to address the shortcomings of existing technologies by providing a dual-drive adaptive modeling method and system for the superstructure and superstructure of bridges.

[0062] Example 1

[0063] This embodiment provides a dual-drive adaptive modeling method for the superstructure and superstructure of a bridge, such as... Figure 1-2 As shown, it includes:

[0064] A dynamic local coordinate system with the pier center point as the origin is established based on the span line and the route normal. The spatial angle θ between the span line and the route normal on the horizontal projection plane is obtained. A virtual cutting plane is constructed based on the spatial angle θ. A three-dimensional Boolean difference operation is performed between the standard beam segment and the virtual cutting plane to generate the geometric model of the skew beam segment.

[0065] Extract the planar projection contour polygon of each pier in the oblique coordinate system, discretize the contour polygon into a set of sampling points, perform ray collision detection with the digital terrain model along the gravity direction, obtain the terrain elevation of each sampling point, and calculate the elevation range and local terrain cross slope within the contour range based on the terrain elevation. When the local terrain cross slope exceeds the preset threshold, trigger the adaptive solution of stepped foundations or piers of unequal height, and output the top and bottom surface elevations.

[0066] A parametric topology dependency graph is established based on the spatial angle θ, the digital terrain model, and the geometric parameters of the upper and lower components. When the data of the cross line or the digital terrain model changes locally, the parametric topology dependency graph is traversed, the affected nodes are marked as dirty nodes, and only the branch links where the dirty nodes are located are incrementally recalculated to update the geometric model of the skew beam segment and the top and bottom surface elevations.

[0067] This embodiment includes three steps: accurate calculation of the upper structure based on the dynamic local coordinate system, adaptive lower structure based on DTM mesh collision and oblique projection, and incremental update of the upper and lower structures based on the topology dependency graph.

[0068] In the steps of accurately solving the oblique intersection of the superstructure based on the dynamic local coordinate system, such as Figure 3 As shown, specifically:

[0069] This embodiment takes a three-span prestressed concrete continuous box girder bridge as an example. The bridge crosses a road, and there is an oblique angle between the design centerline of the route and the centerline of the piers. The designers first imported the route design data into the BIM software, including the span layout and route normal information.

[0070] A dynamic local spatial rectangular coordinate system O-XYZ is established with the center design point of any bridge pier as the origin O, the direction of the route normal as the positive X-axis, the direction of the span line (the longitudinal axis of the bridge) as the positive Y-axis, and the direction of the plumb line (vertically upward) as the positive Z-axis. In this coordinate system, the angle between the span line and the route normal on the horizontal projection plane (i.e., the XY plane) is the spatial angle θ (0°≤θ≤180°), which is the oblique angle θ. In this embodiment, the oblique angle θ is preset to 35°.

[0071] Based on the oblique angle θ, the system dynamically generates a virtual cutting plane for the oblique cut beam end and end diaphragm, where the normal vector n of the virtual cutting plane is represented as:

[0072] n=(cosθ,sinθ,0)= (cos35°, sin35°,0)≈(0.8192, 0.5736, 0)

[0073] The normal vector is perpendicular to the XY plane, indicating that the virtual cutting plane is a vertical plane.

[0074] The virtual cutting plane passes through the end point P0(X0, Y0, Z0) of the beam segment. The coordinates of P0 are taken as the design coordinates of the center point of the end of the beam segment to be cut, for example, P0=(5000, 3000, 250). Then, the three-dimensional spatial equation of the virtual cutting plane is expressed as:

[0075] cosθ·(x-x0)+sinθ·(y-y0)=0

[0076] Right now:

[0077] 0.8192×(x-5000)+0.5736×(y-3000)=0

[0078] The system retrieves the boundary representation (B-rep) model of the standard orthogonal beam segment. The system extracts the spatial coordinates of all vertices in the boundary representation model, resulting in 48 vertices (each corner point and subdivision point of the standard hexahedral beam segment). These vertex coordinates are used to construct a vertex matrix V, which is a 48-row, 3-column matrix, with each row corresponding to the (x, y, z) coordinates of a vertex. The standard orthogonal beam segment refers to the original beam segment model that has not been cut and whose beam end plane is perpendicular to the route normal.

[0079] Based on the oblique angle θ = 35°, construct the rotation transformation matrix R(θ), which is expressed as:

[0080]

[0081] Multiplying the vertex matrix V by the rotation transformation matrix R(θ), i.e., V' = V × R(θ), where V is an n × 3 matrix and R(θ) is a 3 × 3 matrix, results in an n × 3 matrix, yielding the transformed vertex matrix V'. This matrix multiplication operation rotates a standard orthogonal beam segment from an orthogonal orientation to an oblique orientation consistent with the span direction, resulting in a spatial azimuth angle of 35° for the beam segment after rotation.

[0082] For the beam end cut surfaces and end diaphragms of precast beams or cast-in-place box girders, the system does not rely on a preset family library, but instead performs dynamic Boolean operations on standard beam segments based on a constructed three-dimensional Boolean cutting matrix M(θ). Subsequently, using the aforementioned virtual cutting plane equation, a three-dimensional Boolean difference operation is performed on the transformed vertex matrix V'. The specific process of the Boolean difference operation is as follows: traverse each vertex in V', determine which side of the virtual cutting plane the vertex is located on, substitute the vertex coordinates into the left side of the plane equation cosθ·(x-x0)+sinθ·(y-y0), if the calculation result is greater than 0, then the vertex is located on the positive side of the normal vector (i.e., the side that needs to be removed); if the calculation result is less than 0, then the vertex is located on the negative side of the normal vector (i.e., the side that needs to be retained). The system removes all vertices and their associated edges and faces located on the positive side of the normal vector, and reconstructs the boundary representation of the cut geometry, thereby automatically generating a geometric model of the skew beam segment at any angle θ. The beam end plane is perpendicular to the span direction and forms a 35° angle with the route normal direction. The position of the end diaphragm is adjusted accordingly, and the flange spread length is automatically adapted according to the geometric compensation function, realizing automatic updating of the spatial pose matrix under large skew angles and generating a stepless adaptive skew model instance.

[0083] In the step of adapting the lower structure based on DTM mesh collision and oblique projection, such as Figure 4 As shown, specifically:

[0084] In this embodiment, the terrain of the area where the bridge is located has a lateral slope. Assuming that the ground elevation changes from 215.6 meters on the left to 208.3 meters on the right, with a height difference of about 7.3 meters, and the foundation lateral width is 12 meters, the calculated local terrain lateral slope is about 60.8%.

[0085] The system obtains the outer envelope projection polygon S of the bridge pier cap on the horizontal projection plane (XY plane). Assuming the cap is a rectangle with a length of 8m and a width of 6m, its projection polygon S is also a rectangle, with the coordinates of its four vertices being (4800, 2800), (4800, 3400), (5600, 3400), and (5600, 2800).

[0086] According to the preset sampling precision parameter d (e.g., 0.5m, meaning one sampling point is taken for every 0.5m × 0.5m grid), the internal region of the projected polygon S is discretized into a set of sampling points. The area of ​​the projected polygon S is 48㎡ (8m × 6m), and the number of sampling points k≈48÷0.25=192, thus obtaining the sampling point set P={P1, P2,..., P... k}={P1, P2, ..., P 192}, where each sampling point P i The coordinates are (x i ,y i ).

[0087] For any sampling point P in the set of sampling points P i For example, take one of the sampling points P 50 =(5200, 3100), the system starts from point (5200, 3100, Z) max A virtual ray is emitted from point Z along a vertically downward (gravity) direction. max To be greater than the preset constant of the maximum elevation of the digital terrain model, the maximum elevation of the digital terrain model in this embodiment is 218.5m, and Z is taken as... max =300m (take a sufficiently large value to ensure the ray originates above the terrain). The parametric equation for the virtual ray is expressed as:

[0088] R(t) = O i + tD

[0089] The ray origin O i (5200, 3100, 300000), direction vector D=(0, 0, -1), t is a non-negative real parameter representing the distance moved along the direction vector from the ray starting point.

[0090] The system calculates the intersection of the virtual ray with the triangular facets in the digital terrain model (DTM) of the engineering area. The DTM is composed of a triangular mesh of irregular shapes (TIN), and each triangular facet is defined by three vertices V0, V1, and V2. In this embodiment, the coordinates of the three vertices of the triangular facet intersecting the ray are: V0 = (5198, 3098, 216200), V1 = (5202, 3098, 216500), and V2 = (5200, 3102, 216300). The edge vector E1 = V... 1- V0=(4, 0, 300), E2=V 2- V0=(2, 4, 100).

[0091] Next, the following system of linear equations is solved to obtain the ray parameters, expressed as:

[0092]

[0093] Where -D = (0, 0, 1), O i - V0=(2, 2, 83800), yielding ray parameters t'=83700, and barycentric coordinate parameters u=0.3, v=0.4. Since u≥0, v≥0, and u+v≤1, the intersection point is located inside the triangular facet. This intersection point is the spatial point where the ray penetrates the terrain surface, and its planar coordinates are related to the sampling point P. 50 Their plane coordinates are the same.

[0094] After solving for the intersection time t', the precise terrain elevation Z at the sampling point can be obtained. i =Z max- t'=300000-83700=216300, which is 216.3m.

[0095] Traverse all 192 sampling points in the sampling point set P to obtain the terrain elevation set H={Z1,Z2,...,Z...} within the projected polygon S. k}={Z1, Z2, ..., Z 192 The minimum elevation is 208.3m and the maximum elevation is 215.6m.

[0096] This embodiment differs from the conventional method of taking the elevation of a single center point. The system calculates the elevation range and terrain cross slope within the contour area, where the elevation range ΔH = max(H) - min(H) = 215.6 - 208.3 = 7.3m. Assuming the foundation's transverse width is W = 12m, and the local terrain cross slope i... t =ΔH / W=7.3 / 12≈0.608, or 60.8%.

[0097] Determine the cross slope of local terrain i t Does it exceed the preset threshold? If so, that is (If the preset threshold is 15%, then 60.8% is significantly greater than 15%). At the same time, if the cap beam is asymmetrical due to the oblique angle θ=35°, the offset of the cap beam's center of gravity is calculated to be 0.35m, and it is determined whether the offset of the cap beam's center of gravity exceeds the preset safe eccentricity limit (the preset safe eccentricity limit is determined based on the bending bearing capacity of the pier section, such as 0.25m). If so, that is, 0.35m>0.25m.

[0098] Furthermore, when the cap beam is asymmetrical due to the influence of the upper oblique angle θ, the system triggers the adaptive solution mechanism of stepped foundation or double column unequal height pier. Combined with the design foundation burial depth parameters, it automatically outputs the top and bottom elevations of each independent abutment / pile foundation and drives the generation of the substructure model. At this time, the system triggers the adaptive solution mechanism of stepped foundation or double column unequal height pier.

[0099] In this embodiment, the adaptive solution mechanism for the stepped foundation is as follows: the system divides the foundation along the slope into two independent parts: a left foundation and a right foundation. The left foundation corresponds to the side with higher terrain elevation, and the right foundation corresponds to the side with lower terrain elevation. The system calculates the average elevation of the sampling points within the projection area of ​​the left foundation to be 215.2m, and the average elevation of the sampling points within the projection area of ​​the right foundation to be 209.1m. The designed foundation depth is... =2.5m, then the bottom elevation of the left foundation is 215.2-2.5=212.7m, and the top elevation is 212.7+1.5=214.2m (foundation height 1.5m); the bottom elevation of the right foundation is 209.1-2.5=206.6m, and the top elevation is 206.6+1.5=208.1m. The system automatically outputs the above elevations and drives the generation of a three-dimensional geometric model of the stepped foundation, effectively avoiding the problem of large areas of the overall foundation being suspended or over-excavated on steep slopes.

[0100] In the above steps of incremental update based on the topological dependency graph, the specific steps are as follows:

[0101] In this embodiment, if the designer subsequently changes the oblique angle θ from 35° to 40°, the system needs to perform a corresponding update process to address this change.

[0102] The system first establishes a parameter topology dependency graph, with the spatial angle θ and the digital terrain model as root nodes, and the geometric parameters of the upper and lower components as leaf nodes. The leaf nodes include the beam end cutting surface position, end diaphragm geometry, and flange spread length of the upper structure, as well as the top and bottom elevations of the foundation cap, pile foundation elevation, and pier height of the lower structure. The system constructs directed edges between the root node and leaf nodes to represent the dependencies between parameters: when the θ node changes, all upper structure leaf nodes are affected; when the digital terrain model node changes, all lower structure leaf nodes are affected. Furthermore, since changes in θ affect the centroid offset of the cap beam, which in turn affects the triggering judgment of the stepped foundation, there is also an indirect dependency between the θ node and the lower structure leaf nodes.

[0103] When a local translation occurs in the span, causing the oblique angle θ to change from 35° to 40°, the system traverses the parameter topology dependency graph to identify the nodes affected by this change. The system marks the θ node as "dirty" and also marks all upper structure leaf nodes (beam end cut surface position, end diaphragm geometry, flange spread length) that depend on the θ node, as well as lower structure leaf nodes indirectly affected by θ (pile cap top and bottom elevation, pile foundation elevation, pier height) as "dirty".

[0104] The system only traverses and recalculates nodes on directed edge paths marked as "dirty." Specifically, based on the new "dirty" value of 40°, the system re-executes the 3D Boolean difference operation in step S1 to generate a new geometric model of the skew beam segment. Simultaneously, due to the change in "dirty" causing a change in the centroid offset of the cap beam, the system re-executes the trigger judgment and elevation calculation for the stepped foundation, outputting new top and bottom surface elevations. The system directly skips unaffected bridge spans and piers. In this embodiment, only the span containing the pier is affected; the parameters and models of the remaining bridge spans remain unchanged. The algorithm complexity for full model reconstruction is O(N), where N is the total number of bridge components, while the algorithm complexity for incremental recalculation is O(M), where M is the number of locally affected components. This achieves second-level reconstruction rather than full model reconstruction, ensuring low latency and data consistency in the global model update of complex bridges.

[0105] Compared with the prior art, the beneficial effects of this embodiment are:

[0106] 1. Break through the bottleneck of large oblique angle modeling: Introduce three-dimensional Boolean cutting matrix and geometric compensation function to make the geometric solution of beam end and diaphragm under continuous oblique angles from 0° to 180° mathematically rigorous, and completely abandon exhaustive templates.

[0107] 2. Resolve the coupling conflict between oblique intersections and undulating terrain: The projection profile and DTM ray collision detection technology are used to replace the traditional single-point elevation reading. It can automatically identify areas with steep cross slopes and adaptively generate piers of different heights or stepped foundations, avoiding foundation suspension or excessive excavation.

[0108] 3. Low-latency dynamic reconstruction: Introducing topology dependency graph technology for incremental updates significantly reduces the computational cost of full model recalculation when design changes occur, and improves the real-time interactive experience of forward design.

[0109] Example 2

[0110] This embodiment provides a dual-drive adaptive modeling system for the superstructure and superstructure of a bridge, including:

[0111] The superstructure calculation module is used to establish a dynamic local coordinate system with the center point of the pier as the origin based on the span line and the route normal, obtain the spatial angle θ between the span line and the route normal on the horizontal projection plane, construct a virtual cutting plane based on the spatial angle θ, perform a three-dimensional Boolean difference operation on the standard beam segment and the virtual cutting plane, and generate a geometric model of the skew beam segment.

[0112] The substructure adaptive module is used to extract the planar projection contour polygons of each pier in the oblique coordinate system, discretize the contour polygons into a set of sampling points, perform ray collision detection with the digital terrain model along the gravity direction, obtain the terrain elevation of each sampling point, and calculate the elevation range and local terrain cross slope within the contour range based on the terrain elevation. When the local terrain cross slope exceeds the preset threshold, the adaptive solution of the stepped foundation or piers of unequal height is triggered, and the top and bottom surface elevations are output.

[0113] The upper and lower linkage incremental update module is used to establish a parameter topology dependency graph based on the spatial angle θ, digital terrain model, and geometric parameters of upper and lower components. When the layout line or digital terrain model data undergoes local changes, the parameter topology dependency graph is traversed, the affected nodes are marked as dirty nodes, and only the branch links where the dirty nodes are located are incrementally recalculated to update the geometric model of the skew beam segment and the top and bottom surface elevations.

[0114] It should be noted that the dual-drive adaptive modeling system for the upper and lower structures of a bridge provided in this embodiment is similar to that in Embodiment 1, and will not be described in detail here.

[0115] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A dual-drive adaptive modeling method for the superstructure and superstructure of a bridge, characterized in that, include: A dynamic local coordinate system with the pier center point as the origin is established based on the span line and the route normal. The spatial angle θ between the span line and the route normal on the horizontal projection plane is obtained. A virtual cutting plane is constructed based on the spatial angle θ. A three-dimensional Boolean difference operation is performed between the standard beam segment and the virtual cutting plane to generate the geometric model of the skew beam segment. Extract the planar projection contour polygon of each pier in the oblique coordinate system, discretize the contour polygon into a set of sampling points, perform ray collision detection with the digital terrain model along the gravity direction, obtain the terrain elevation of each sampling point, and calculate the elevation range and local terrain cross slope within the contour range based on the terrain elevation. When the local terrain cross slope exceeds the preset threshold, trigger the adaptive solution of stepped foundations or piers of unequal height, and output the top and bottom surface elevations. A parametric topology dependency graph is established based on the spatial angle θ, the digital terrain model, and the geometric parameters of the upper and lower components. When the data of the cross line or the digital terrain model changes locally, the parametric topology dependency graph is traversed, the affected nodes are marked as dirty nodes, and only the branch links where the dirty nodes are located are incrementally recalculated to update the geometric model of the skew beam segment and the top and bottom surface elevations.

2. The dual-drive adaptive modeling method for bridge superstructure and superstructure according to claim 1, characterized in that, The establishment of a dynamic local coordinate system with the center point of the pier as the origin is specifically as follows: with the design point of the pier center as the origin O, the route normal direction as the positive X-axis, the span direction as the positive Y-axis, and the plumb line direction as the positive Z-axis, a local spatial rectangular coordinate system O-XYZ is established.

3. The dual-drive adaptive modeling method for bridge superstructure and superstructure according to claim 1, characterized in that, The construction of the virtual cutting plane specifically involves: Let the normal vector n of the virtual cutting plane be expressed as: n=(cosθ,sinθ,0); If the virtual cutting plane passes through the end point P0(X0, Y0, Z0) of the beam segment, then the spatial equation of the virtual cutting plane is expressed as: cosθ·(x-x0)+sinθ·(y-y0)=0; Where n represents the normal vector of the cutting plane; x, y, z represent the coordinates of any point on the virtual cutting plane.

4. The dual-drive adaptive modeling method for bridge superstructure and superstructure according to claim 1, characterized in that, The three-dimensional Boolean difference operation is specifically as follows: Retrieve the boundary representation model of the standard orthogonal beam segment, extract the spatial coordinates of all vertices in the boundary representation model, and construct the vertex matrix V; Construct a rotation transformation matrix R(θ) based on the spatial angle θ, and obtain the transformed vertex matrix based on the vertex matrix V and the rotation transformation matrix R(θ); where the rotation transformation matrix R(θ) is expressed as: ； By performing a three-dimensional Boolean difference operation on the transformed vertex matrix using the virtual cutting plane, the geometry on the normal side of the virtual cutting plane is eliminated, generating the geometric model of the oblique beam segment.

5. The dual-drive adaptive modeling method for bridge superstructure and superstructure according to claim 1, characterized in that, The specific steps of discretizing the contour polygon into a set of sampling points are as follows: Obtain the outer envelope projection polygon S of the substructure foundation on the horizontal projection plane. According to the preset sampling precision parameter d, discretize the internal region of the projection polygon S into a set P = {P1, P2, ..., P...} containing k sampling points. k }, where P i =(x i ,y i ), i∈1,2,…,k.

6. The dual-drive adaptive modeling method for bridge superstructure and superstructure according to claim 5, characterized in that, The specific steps of performing ray collision detection are as follows: For any sampling point P in the set of sampling points P i A virtual ray is emitted along the direction of gravity, where the virtual ray is represented as: R(t)=O i + tD; O i = (x i , y i , Z max ); D = (0, 0, -1)； Where R(t) represents the coordinates of a point on the ray at a distance t from the starting point; O i t represents the origin of the ray; t represents the distance moved along the direction from the origin; D represents the direction vector; Z represents the direction vector. max This represents a preset constant greater than the maximum elevation of the digital terrain model; x i , y i This represents the planar coordinates of the i-th sampling point on the horizontal projection plane.

7. The dual-drive adaptive modeling method for bridge superstructure and superstructure according to claim 6, characterized in that, The specific steps for obtaining the terrain elevation of each sampling point are as follows: The virtual ray and the triangular facets in the digital terrain model are calculated to solve for the ray parameters of the virtual ray and the triangular facets, which are expressed as follows: ； E1=V 1- V0; E2=V 2- V0; Where V0, V1, and V2 represent the vertex coordinates of the triangular facet; E1 and E2 represent the two edge vectors of the triangular facet; u and v represent the centroid coordinates of the intersection point within the triangular facet; and t' represents the ray parameter. Calculate sampling point P based on ray parameter t. i Terrain elevation Z i , is represented as: Z i =Z max- t’; Traverse the set of sampling points P to obtain the set of terrain elevations H={Z1,Z2,...,Z...} within the projected polygon S. k } 8. The dual-drive adaptive modeling method for bridge superstructure and superstructure according to claim 1, characterized in that, The conditions for triggering adaptive solutions for stepped foundations or unequal-height piers also include: The offset of the center of gravity of the cap beam exceeds the preset safe eccentricity limit, which is determined based on the flexural bearing capacity of the pier section.

9. The dual-drive adaptive modeling method for bridge superstructure and superstructure according to claim 1, characterized in that, The incremental recalculation specifically refers to: Set the spatial angle θ and the digital terrain model as the root node, and set the geometric parameters of the upper and lower components as leaf nodes to construct a parameter dependency graph between the root node and the leaf nodes. When the layout line or digital terrain model undergoes local changes, only the spatial angle θ node or digital terrain model node affected by the change is marked as a dirty node. Traverse and recalculate all nodes on the directed edge path marked as dirty nodes, skipping unaffected nodes.

10. A modeling system based on the dual-drive adaptive modeling method for bridge superstructures according to any one of claims 1-9, characterized in that, include: The superstructure calculation module is used to establish a dynamic local coordinate system with the center point of the pier as the origin based on the span line and the route normal, obtain the spatial angle θ between the span line and the route normal on the horizontal projection plane, construct a virtual cutting plane based on the spatial angle θ, perform a three-dimensional Boolean difference operation on the standard beam segment and the virtual cutting plane, and generate a geometric model of the skew beam segment. The substructure adaptive module is used to extract the planar projection contour polygons of each pier in the oblique coordinate system, discretize the contour polygons into a set of sampling points, perform ray collision detection with the digital terrain model along the gravity direction, obtain the terrain elevation of each sampling point, and calculate the elevation range and local terrain cross slope within the contour range based on the terrain elevation. When the local terrain cross slope exceeds the preset threshold, the adaptive solution of the stepped foundation or piers of unequal height is triggered, and the top and bottom surface elevations are output. The upper and lower linkage incremental update module is used to establish a parameter topology dependency graph based on the spatial angle θ, digital terrain model, and geometric parameters of upper and lower components. When the layout line or digital terrain model data undergoes local changes, the parameter topology dependency graph is traversed, the affected nodes are marked as dirty nodes, and only the branch links where the dirty nodes are located are incrementally recalculated to update the geometric model of the skew beam segment and the top and bottom surface elevations.

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