Section generation method and device based on flow field data, equipment and storage medium

Abstract

The invention provides a section generation method and device based on flow field data, equipment and a storage medium, and can be applied to the technical field of fluid mechanics and the technical field of visualization. The method comprises the following steps: acquiring initial point cloud data at a target cutting position in a flow field scene, the initial point cloud data comprising spatial distribution information and physical state information of an initial point; performing sparse processing on the initial point cloud based on the physical state information to obtain a target point cloud; based on the spatial distribution information or the physical state information, boundary marking is carried out on the target point cloud, boundary points and non-boundary points are determined, and the boundary points represent target points, located at fluid and solid boundary positions in the flow field scene, in the target point cloud; and processing the boundary points and the non-boundary points by using a triangulation network growth algorithm and a surface rendering algorithm to obtain a rendering section, the rendering section including the boundary of the fluid and the solid in the flow field scene.

Description

Technical Field

[0001] The present disclosure relates to the technical fields of fluid mechanics and visualization, and more specifically, to a method, device, equipment and storage medium for generating a section based on flow field data. Background Art

[0002] At present, when it comes to the rapid integration and display of flow field data involving different grids, different calculation methods, and different simulation programs, it is necessary to perform visualization operations such as rapid segmentation, rendering, and display of the flow field point cloud. When it is necessary to display the cross-sectional data in a refined manner, the algorithms usually used are developed and optimized based on the characteristics of geospatial data, such as divide-and-conquer algorithms and triangulated network growth algorithms. Geospatial data has the characteristics of no complex voids inside and relatively uniform point cloud data, while flow field data has the characteristics of poor uniformity, high boundary layer density, and complex voids inside. Therefore, when point-to-surface generation of flow field point cloud data is performed based on existing algorithms, the cross-sectional display has low clarity and low efficiency. Summary of the invention

[0003] In view of this, the present disclosure provides a method, device, equipment and storage medium for generating a slice based on flow field data.

[0004] One aspect of the present disclosure provides a method for generating a section based on flow field data, comprising:

[0005] Acquire initial point cloud data located at a target cutting position in a flow field scene, wherein the initial point cloud data includes spatial distribution information and physical state information of the initial point; perform sparse processing on the initial point cloud based on the physical state information to obtain a target point cloud, wherein the initial point cloud includes multiple initial points, and the target point cloud includes multiple target points; perform boundary marking on the target point cloud based on the spatial distribution information or the physical state information, and determine boundary points and non-boundary points, wherein the boundary points represent target points in the target point cloud located at the boundary position between the fluid and the solid in the flow field scene, and the non-boundary points represent target points in the target point cloud located outside the boundary position between the fluid and the solid in the flow field scene; use a triangulated network growth algorithm and a surface rendering algorithm to process boundary points and non-boundary points to obtain a rendered section, wherein the rendered section includes the boundary between the fluid and the solid in the flow field scene.

[0006] According to an embodiment of the present disclosure, the physical state information includes first physical state information, and the first physical state information represents information of a decreasing state along the flow direction; wherein, using a triangulated network growth algorithm and a surface rendering algorithm to process boundary points and non-boundary points to obtain a rendering section includes:

[0007] Based on the sorting algorithm and the first physical state information, the boundary points and non-boundary points are sorted to obtain a sorted point cloud; based on the blocking algorithm, the sorted point cloud is blocked to obtain at least one block point cloud; the non-boundary points in the block point cloud are processed using the triangulated mesh growth algorithm to obtain the respective triangular meshes of at least one block point cloud; the triangular meshes of the respective block point clouds are rendered using the surface rendering algorithm to obtain a rendered section.

[0008] According to an embodiment of the present disclosure, the spatial distribution information includes point cloud density information; wherein, based on the spatial distribution information, the target point cloud is boundary marked, and the boundary points are determined, including: when the point cloud density information of the target point in the target point cloud is greater than a preset density threshold, the target point is boundary marked and the boundary points are determined.

[0009] According to an embodiment of the present disclosure, the physical state information also includes viscous fluid velocity information; wherein, based on the physical state information, the points in the target point cloud are marked with boundaries, and determining the boundary points includes: when the viscous fluid velocity information of the target point in the target point cloud is equal to a preset viscous velocity threshold, marking the boundary of the target point and determining the boundary point.

[0010] According to an embodiment of the present disclosure, the physical state information also includes temperature information; wherein, based on the physical state information, the target point cloud is boundary marked, and determining the boundary point also includes: when the temperature information of the target point in the target point cloud is greater than a preset temperature threshold, the target point is boundary marked and the boundary point is determined.

[0011] According to an embodiment of the present disclosure, the physical state information also includes flow velocity information; wherein, based on the physical state information, the target point cloud is boundary marked, and determining the boundary point includes: when the flow velocity information of the target point in the target point cloud is equal to the flow velocity threshold, the target point is boundary marked and the boundary point is determined.

[0012] According to an embodiment of the present disclosure, the initial point cloud is subjected to sparse processing based on the physical state information to obtain the target point cloud, including:

[0013] According to the physical state information of each of the multiple initial points in the initial point cloud, the physical state fluctuation level of each of the multiple local areas is determined; when the physical state fluctuation level of the local area is less than a preset gradient threshold, the local area is determined as a to-be-processed area; the multiple initial points located in the to-be-processed area are thinned to obtain a de-sparsed point cloud; according to the de-sparsed point cloud and the multiple initial points located in the local area that has not been de-sparsed, a target point cloud is obtained.

[0014] Another aspect of the present disclosure provides a section generation device based on flow field data, comprising:

[0015] An acquisition module is used to acquire initial point cloud data located at a target cutting position in a flow field scene, wherein the initial point cloud data includes spatial distribution information and physical state information of the initial point;

[0016] A processing module, used for performing sparse processing on the initial point cloud based on the physical state information to obtain a target point cloud, wherein the initial point cloud includes a plurality of initial points and the target point cloud includes a plurality of target points;

[0017] A marking module is used to mark the boundaries of the target point cloud based on the spatial distribution information or the physical state information, and determine the boundary points and non-boundary points, wherein the boundary points represent the target points in the target point cloud located at the boundary position between the fluid and the solid in the flow field scene, and the non-boundary points represent the target points in the target point cloud located outside the boundary position between the fluid and the solid in the flow field scene;

[0018] The rendering module is used to process boundary points and non-boundary points using a triangulated network growth algorithm and a surface rendering algorithm to obtain a rendering section, wherein the rendering section includes a boundary between a fluid and a solid in a flow field scene.

[0019] Another aspect of the present disclosure provides an electronic device, comprising:

[0020] one or more processors;

[0021] a memory for storing one or more programs,

[0022] When one or more programs are executed by one or more processors, the one or more processors implement the above-mentioned section generation method based on flow field data.

[0023] Another aspect of the present disclosure provides a computer-readable storage medium storing computer-executable instructions, which are used to implement the above-mentioned section generation method based on flow field data when executed.

[0024] According to the section generation method, device, equipment and storage medium based on flow field data provided by the present disclosure, the target point cloud is obtained by thinning the initial point cloud based on physical state information; the boundary of the target point cloud is marked based on spatial distribution information or physical state information to determine boundary points and non-boundary points; the boundary points and non-boundary points are processed using a triangulated network growth algorithm and a surface rendering algorithm to obtain a rendered section. Since the initial point cloud is thinned based on physical state information, the display of the flow rendering section can be accelerated without affecting the flow field display effect; secondly, based on the fusion of the spatial distribution information and physical state information of the target point, the accurate judgment of the flow field boundary is achieved. Under the premise of determining the flow field boundary, the rendering section is quickly generated based on the triangulated network growth algorithm and the surface rendering algorithm, which improves the efficiency and clarity of displaying the rendering section for the target cutting position. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The above and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0026] Figure 1 A flow chart of a method for generating a section based on flow field data according to an embodiment of the present disclosure is shown;

[0027] Figure 2 An example schematic diagram of generating a rendering slice according to an embodiment of the present disclosure is shown;

[0028] Figure 3 An example schematic diagram of determining boundary points according to an embodiment of the present disclosure is shown;

[0029] Figure 4 An example schematic diagram of determining a de-sparse point cloud according to an embodiment of the present disclosure is shown;

[0030] Figure 5 A block diagram of a slice generation device based on flow field data according to an embodiment of the present disclosure is shown; and

[0031] Figure 6 A block diagram of an electronic device suitable for implementing a slice generation method based on flow field data according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0032] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0033] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0034] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0035] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0036] In the process of realizing the present disclosure, it is found that when it comes to the rapid integrated display of flow field data involving different grids, different calculation methods, and different simulation programs, it is necessary to perform visualization operations such as rapid segmentation, rendering, display, and hiding of the spatial point cloud. When it is necessary to display the cross-sectional data in a refined manner, the algorithms usually used are developed and optimized based on the characteristics of geological measurement data, such as divide-and-conquer algorithms and triangulation network growth algorithms. Geological measurement data has the characteristics of no complex voids inside and relatively uniform point cloud data, while flow field data has the characteristics of poor uniformity, high boundary layer density, and complex voids inside. Therefore, when point-to-surface generation of flow field point cloud data is performed based on existing algorithms, the cross-sectional display clarity is low and the efficiency is low.

[0037] In view of this, the embodiments of the present disclosure provide a section generation method, device, equipment and storage medium based on flow field data. The method includes: obtaining initial point cloud data located at the target cutting position in the flow field scene, wherein the initial point cloud data includes the spatial distribution information and physical state information of the initial point; performing sparse processing on the initial point cloud based on the physical state information to obtain the target point cloud, wherein the initial point cloud includes multiple initial points and the target point cloud includes multiple target points; marking the boundaries of the target point cloud based on the spatial distribution information or the physical state information, and determining the boundary points and non-boundary points, wherein the boundary points represent the target points in the target point cloud located at the boundary position between the fluid and the solid in the flow field scene, and the non-boundary points represent the target points in the target point cloud located outside the boundary position between the fluid and the solid in the flow field scene; using the triangulated network growth algorithm and the surface rendering algorithm to process the boundary points and non-boundary points to obtain the rendered section, wherein the rendered section includes the boundary between the fluid and the solid in the flow field scene.

[0038] In the technical solution of the present disclosure, the user information (including but not limited to user personal information, user image information, user device information, such as location information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved are all information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with relevant laws, regulations and standards, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0039] Figure 1 A flow chart of a method for generating a slice based on flow field data according to an embodiment of the present disclosure is shown.

[0040] like Figure 1 As shown, the method 100 includes operations S110 to S140.

[0041] In operation S110, initial point cloud data located at a target cutting position in a flow field scene is acquired.

[0042] According to an embodiment of the present disclosure, the target cutting position represents the cutting position corresponding to the section to be rendered. The initial point represents the three-dimensional flow field point on the section at the target cutting position.

[0043] For example, in a certain flow field scene, the target cutting position is determined to be 30% with the initial position as a reference, cutting is performed based on the target cutting position of 30%, and initial point cloud data of multiple initial points located on the cutting surface at the target cutting position of 30% are obtained.

[0044] According to the embodiments of the present disclosure, the initial point cloud data has the characteristics of poor uniformity, high boundary layer density, low internal density, uneven grid distribution, and complex internal cavities. The initial point cloud data includes spatial distribution information and physical state information of the initial point. The spatial distribution information may include position information and spatial density distribution information, and the physical state information may include pressure information, flow rate information, temperature information, etc.

[0045] In operation S120, the initial point cloud is thinned based on the physical state information to obtain a target point cloud.

[0046] According to an embodiment of the present disclosure, the initial point cloud includes a plurality of initial points, and the target point cloud includes a plurality of target points.

[0047] According to the embodiments of the present disclosure, the physical state change levels of different location areas can be determined based on the physical state information of multiple initial points in the initial point cloud, and the initial point cloud can be thinned in the location area with low change level and high initial point density to obtain the target point cloud.

[0048] According to the embodiments of the present disclosure, relative to the initial point cloud, the target point cloud is obtained without affecting the overall physical state information, thereby improving the speed of the algorithm in processing the target point cloud.

[0049] In operation S130 , boundary marking is performed on the target point cloud based on the spatial distribution information or the physical state information to determine boundary points and non-boundary points.

[0050] According to an embodiment of the present disclosure, boundary points represent target points in the target point cloud located at the boundary between fluid and solid in the flow field scene, and non-boundary points represent target points in the target point cloud located outside the boundary between fluid and solid in the flow field scene.

[0051] According to an embodiment of the present disclosure, the boundary between the fluid region and the solid region in the flow field scene is a boundary layer.

[0052] According to an embodiment of the present disclosure, when the spatial distribution information or physical state information of the target point meets the boundary state condition of the boundary layer, the target point is boundary marked, the target point is determined to be a boundary point, and the target point in the target point cloud that has not been boundary marked is marked as a non-boundary point.

[0053] In operation S140 , the boundary points and non-boundary points are processed using a triangulated mesh growing algorithm and a surface rendering algorithm to obtain a rendering section.

[0054] According to an embodiment of the present disclosure, the triangulation network growth algorithm may be a Delaunay triangulation algorithm, and multiple boundary points and non-boundary points may be processed according to the Delaunay algorithm, a triangulation network may be generated according to the multiple non-boundary points, and partial edges may be generated at the multiple boundary points.

[0055] According to an embodiment of the present disclosure, a triangular mesh is a polygonal mesh composed entirely of triangles, and the triangles are constructed based on non-boundary points.

[0056] According to an embodiment of the present disclosure, a surface rendering algorithm is used to process a triangular mesh and a partial edge to obtain a rendering section corresponding to a target cutting position. The rendering section can display the boundary between a fluid and a solid in a flow field scene.

[0057] According to the embodiments of the present disclosure, since the initial point cloud is thinned based on the physical state information, the display of the flow rendering section can be accelerated without affecting the flow field display effect; secondly, based on the fusion of the spatial distribution information and physical state information of the target point, the flow field boundary is accurately judged, and under the premise that the flow field boundary is determined, the rendering section is quickly generated based on the triangulated network growth algorithm and the surface rendering algorithm, thereby improving the efficiency and clarity of displaying the rendering section for the target cutting position.

[0058] According to an embodiment of the present disclosure, the physical state information includes first physical state information, and the first physical state information represents information about a decreasing state along the flow direction, for example, speed information and pressure information.

[0059] According to an embodiment of the present disclosure, using a triangulated network growth algorithm and a surface rendering algorithm to process boundary points and non-boundary points to obtain a rendered section includes:

[0060] Based on the sorting algorithm and the first physical state information, the boundary points and non-boundary points are sorted to obtain a sorted point cloud; based on the blocking algorithm, the sorted point cloud is blocked to obtain at least one block point cloud; the non-boundary points in the block point cloud are processed using the triangulated mesh growth algorithm to obtain the respective triangular meshes of at least one block point cloud; the triangular meshes of the respective block point clouds are rendered using the surface rendering algorithm to obtain a rendered section.

[0061] According to an embodiment of the present disclosure, the sorted point cloud represents a set of a plurality of boundary points and a plurality of non-boundary points having a sorted relationship.

[0062] According to an embodiment of the present disclosure, in a flow field scene with complex flow directions, multiple boundary points and multiple non-boundary points may be sorted according to one or a combination of multiple first physical state information.

[0063] For example, the first physical state information is inlet pressure information. In a flow field scene with a single flow direction, a plurality of boundary points and a plurality of non-boundary points can be sorted using a sorting algorithm according to their respective inlet pressure information to obtain a sorted point cloud. The quick sorting algorithm can be a quick sorting algorithm.

[0064] According to an embodiment of the present disclosure, the number of blocks can be determined, and the sorted point cloud can be divided into blocks according to the number of blocks and the degree of change of the first physical state information of different local areas in the sorted point cloud to obtain multiple block point clouds. The degree of change of the first physical state information represents the fluctuation level of the first physical state information of the local area.

[0065] According to an embodiment of the present disclosure, a triangulated mesh growth algorithm is used to process non-boundary points in a block point cloud block by block to obtain a triangulated mesh of at least one block point cloud. For a certain block point cloud, a triangulated mesh is generated based on a plurality of non-boundary points in the block point cloud, and an edge partially located in a boundary layer is generated based on boundary points in the block point cloud.

[0066] According to an embodiment of the present disclosure, a surface rendering algorithm is used to render the triangular mesh of the block point cloud and the edges located at the boundary layer to obtain a rendering section containing the boundary between the fluid and the solid.

[0067] According to the embodiments of the present disclosure, the first physical state information is introduced, the boundary points and non-boundary points are sorted, and the sorted point cloud is obtained, thereby optimizing the sorting and blocking along the flow direction; then the triangulated network growth algorithm is used to process at least one block point cloud block by block to generate a triangular mesh, without the need to judge the complex topological relationship and the adjacent relationship of points, edges, and triangles, thereby greatly reducing the algorithm complexity, accelerating the generation speed of the triangular mesh, and improving the rendering efficiency.

[0068] Figure 2 An example schematic diagram of generating a rendering slice according to an embodiment of the present disclosure is shown.

[0069] like Figure 2 As shown, for the section 210 located at the target cutting position, the initial point cloud data on the section is obtained, and the flow field inlet and flow field outlet are displayed on the section, and the arrow indicates the flow direction in the flow field. The rendering section 220 is obtained only based on the spatial distribution information of the target point, and the rendering section 220 does not display the boundary; the physical state information is introduced to mark the accurate boundary points and non-boundary points, such as using the sorting algorithm to sort multiple boundary points and multiple non-boundary points according to the inlet pressure information of the boundary points and non-boundary points to obtain the sorted point cloud, and then the rendering section 230 is obtained according to the triangulation growth algorithm and the surface rendering algorithm, and the rendering section 230 can display the boundaries a, b, and c.

[0070] According to an embodiment of the present disclosure, the spatial distribution information includes point cloud density information; wherein, based on the spatial distribution information, the target point cloud is boundary marked, and determining the boundary points includes:

[0071] When the point cloud density information of the target point in the target point cloud is greater than a preset density threshold, the target point is boundary marked to determine the boundary point.

[0072] According to an embodiment of the present disclosure, the density information of target points located in different position areas in the target point cloud represents the density of the target points in the position area. The preset density threshold represents the minimum value of the point cloud density corresponding to the boundary area.

[0073] According to an embodiment of the present disclosure, when point cloud density information of a target point located in a certain position area in a target point cloud is greater than a preset density threshold, boundary marking is performed on the target point in this position area to determine the boundary point.

[0074] According to an embodiment of the present disclosure, the point cloud density information corresponding to the boundary area is greater than the point cloud density information of other areas.

[0075] According to an embodiment of the present disclosure, the physical state information further includes viscous fluid velocity information; wherein, based on the physical state information, the points in the target point cloud are marked with boundaries, and determining the boundary points includes:

[0076] When the viscous fluid velocity information of the target point in the target point cloud is equal to the preset viscous velocity threshold, the target point is marked as a boundary to determine the boundary point.

[0077] According to an embodiment of the present disclosure, when a fluid flows over a solid surface, a thin layer with gradually increasing thickness is formed on the solid surface due to the viscosity of the fluid. In the thin layer, the fluid velocity gradually increases in the direction perpendicular to the wall, and the area between the fluid and the wall is the boundary area. The preset viscosity velocity threshold represents the viscosity velocity value corresponding to the boundary area, for example, the preset viscosity velocity threshold can be 0.

[0078] According to an embodiment of the present disclosure, the viscous fluid velocity information represents the velocity of the target point.

[0079] According to an embodiment of the present disclosure, the physical state information further includes temperature information; wherein, based on the physical state information, the target point cloud is marked with a boundary, and determining the boundary point further includes:

[0080] When the temperature information of the target point in the target point cloud is greater than a preset temperature threshold, the target point is marked as a boundary to determine the boundary point.

[0081] According to an embodiment of the present disclosure, the preset temperature threshold is determined based on the temperature range corresponding to the boundary area. When the temperature information of the target point in the target point cloud is greater than the preset temperature threshold, the target point is marked as a boundary point to determine the boundary point.

[0082] According to an embodiment of the present disclosure, the physical state information further includes flow velocity information; wherein, based on the physical state information, the target point cloud is marked with a boundary, and determining the boundary point includes:

[0083] When the flow velocity information of the target point in the target point cloud is equal to the flow velocity threshold, the target point is marked as a boundary to determine the boundary point.

[0084] According to an embodiment of the present disclosure, the flow velocity threshold represents the velocity in the inlet and outlet directions of the flow field corresponding to the boundary area. For example, the flow velocity threshold is set to: 10 in the x direction, 0.5 in the y direction, and 0.5 in the z direction.

[0085] According to an embodiment of the present disclosure, the flow velocity information of the target point includes velocity information in the x-direction, the y-direction, and the z-direction. When the velocity information of the target point in the target point cloud in the x-direction, the y-direction, and the z-direction are all equal to the flow velocity threshold, the target point is marked as a boundary point to determine the boundary point.

[0086] Figure 3 An example schematic diagram of determining boundary points according to an embodiment of the present disclosure is shown.

[0087] like Figure 3As shown, a curve of fluid velocity variation is drawn according to the viscous fluid velocity information and position information of the target point in the target point cloud, and the preset viscous velocity threshold can be 0. For example, at point a, the viscous fluid velocity information of the target point located in the position area 310 in the target point cloud is greater than 0, and the target point in the position area 310 is determined as a non-boundary point, and the viscous fluid velocity information of the target point located in the position area 320 in the target point cloud is equal to 0, and the target point in the position area 320 is determined as a boundary point; a curve of point cloud density variation is drawn according to the point cloud density information and position information of the target point in the target point cloud, and the point cloud density information of the target point located in the position area 330 in the target point cloud is less than the preset density threshold, and the target point in the position area 330 is determined as a non-boundary point. For example, at point b, the point cloud density information of the target point located in the position area 340 in the target point cloud is greater than the preset density threshold, and the target point in the position area 340 is determined as a boundary point.

[0088] According to an embodiment of the present disclosure, the initial point cloud is subjected to sparse processing based on the physical state information to obtain the target point cloud, including:

[0089] According to the physical state information of each of the multiple initial points in the initial point cloud, the physical state fluctuation level of each of the multiple local areas is determined; when the physical state fluctuation level of the local area is less than a preset gradient threshold, the local area is determined as a to-be-processed area; the multiple initial points located in the to-be-processed area are thinned to obtain a de-sparsed point cloud; according to the de-sparsed point cloud and the multiple initial points located in the local area that has not been de-sparsed, a target point cloud is obtained.

[0090] For example, according to the outlet pressure information of each of the multiple initial points located in the multiple local areas in the initial point cloud, the outlet pressure state fluctuation level corresponding to each of the multiple local areas is obtained, and the outlet pressure state fluctuation level may be variance information.

[0091] According to an embodiment of the present disclosure, when the physical state fluctuation level of a local area is less than a preset gradient threshold, if the point cloud density information corresponding to the local area is large, the local area can be determined as a to-be-processed area. The to-be-processed area represents an area with a small physical state fluctuation level and large point cloud density information.

[0092] According to an embodiment of the present disclosure, performing sparse processing on multiple initial points in the area to be processed may include: randomly removing multiple initial points in the area to be processed. The multiple initial points in the area to be processed that are not removed are de-sparse point clouds. The point cloud density information of the sparse point cloud is relatively small.

[0093] According to the embodiments of the present disclosure, the target point cloud includes a de-thinned point cloud and a plurality of initial points located in a local area that has not been de-thinned. The preset gradient thresholds of different physical state information within a certain range are integrated, so that efficient thinning processing is performed in local areas with a small level of physical state fluctuation, which can achieve accelerated rendering of the section display without affecting the flow field section display effect.

[0094] Figure 4 An example schematic diagram of determining a de-sparse point cloud according to an embodiment of the present disclosure is shown.

[0095] like Figure 4 As shown, when the physical state fluctuation level of the local area is less than the preset gradient threshold, if the point cloud density information corresponding to the local area is large, the local area 410 can be determined as the area to be processed, and the area 420 is selected from the area to be processed, and multiple initial points located in the area 420 are removed to obtain the de-sparsed point cloud 430 corresponding to the area to be processed.

[0096] Based on the above-mentioned section generation method based on flow field data, the present disclosure also provides a section generation device based on flow field data. Figure 5 The device is described in detail.

[0097] Figure 5 A structural block diagram of a slice generation device based on flow field data according to an embodiment of the present disclosure is shown.

[0098] like Figure 5 As shown, the slice generation device 500 based on flow field data of this embodiment includes an acquisition module 510 , a processing module 520 , a marking module 530 and a rendering module 540 .

[0099] The acquisition module 510 is used to acquire the initial point cloud data at the target cutting position in the flow field scene, wherein the initial point cloud data includes the spatial distribution information and physical state information of the initial point. In one embodiment, the acquisition module 510 can be used to perform the operation S110 described above, which will not be repeated here.

[0100] The processing module 520 is used to perform sparse processing on the initial point cloud based on the physical state information to obtain a target point cloud, wherein the initial point cloud includes a plurality of initial points and the target point cloud includes a plurality of target points. In one embodiment, the processing module 520 can be used to perform the operation S120 described above, which will not be described in detail here.

[0101] The marking module 530 is used to mark the boundaries of the target point cloud based on the spatial distribution information or the physical state information, and determine the boundary points and non-boundary points, wherein the boundary points represent the target points in the target point cloud located at the boundary position between the fluid and the solid in the flow field scene, and the non-boundary points represent the target points in the target point cloud located outside the boundary position between the fluid and the solid in the flow field scene. In one embodiment, the marking module 530 can be used to perform the operation S130 described above, which will not be repeated here.

[0102] The rendering module 540 is used to process boundary points and non-boundary points using a triangulated network growth algorithm and a surface rendering algorithm to obtain a rendering section, wherein the rendering section includes a boundary between a fluid and a solid in the flow field scene. In one embodiment, the rendering module 540 can be used to perform the operation S140 described above, which will not be described in detail here.

[0103] According to an embodiment of the present disclosure, the rendering module 540 includes a first rendering sub-module, a second rendering sub-module, a third rendering sub-module, and a fourth rendering sub-module.

[0104] The first rendering submodule is used to sort the boundary points and non-boundary points based on the sorting algorithm and the first physical state information to obtain a sorted point cloud.

[0105] The second rendering submodule is used to divide the sorted point cloud into blocks based on a block algorithm to obtain at least one block point cloud.

[0106] The third rendering submodule is used to process non-boundary points in the block point cloud using a triangulated mesh growing algorithm to obtain a triangulated mesh of at least one block point cloud.

[0107] The fourth rendering submodule is used to render the triangular meshes of each block point cloud by using a surface rendering algorithm to obtain a rendering section.

[0108] According to an embodiment of the present disclosure, the marking module 530 includes a first marking submodule.

[0109] The first marking submodule is used to mark the boundary of the target point and determine the boundary point when the point cloud density information of the target point in the target point cloud is greater than a preset density threshold.

[0110] According to an embodiment of the present disclosure, the marking module 530 further includes a second marking submodule.

[0111] The second marking submodule is used to mark the boundary of the target point in the target point cloud and determine the boundary point when the viscous fluid velocity information of the target point is equal to a preset viscous velocity threshold.

[0112] According to an embodiment of the present disclosure, the marking module 530 further includes a third marking submodule.

[0113] The third marking submodule is used to mark the boundary of the target point and determine the boundary point when the temperature information of the target point in the target point cloud is greater than a preset temperature threshold.

[0114] According to an embodiment of the present disclosure, the marking module 530 further includes a fourth marking submodule.

[0115] The fourth marking submodule is used to mark the boundary of the target point and determine the boundary point when the flow velocity information of the target point in the target point cloud is equal to the flow velocity threshold.

[0116] According to an embodiment of the present disclosure, the processing module 520 further includes a first processing submodule, a second processing submodule, a third processing submodule and a fourth processing submodule.

[0117] The first processing submodule is used to determine the physical state fluctuation level of each of the multiple local areas according to the physical state information of each of the multiple initial points in the initial point cloud.

[0118] The second processing submodule is used to determine the local area as a to-be-processed area when the physical state fluctuation level of the local area is less than a preset gradient threshold.

[0119] The third processing submodule is used to perform sparse processing on a plurality of initial points located in the area to be processed to obtain a de-sparse point cloud.

[0120] The fourth processing submodule is used to obtain a target point cloud according to the de-sparse point cloud and a plurality of initial points located in a local area that has not been de-sparsely processed.

[0121] According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits, or at least part of the functions of any one of them can be implemented in one module. According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits can be split into multiple modules for implementation. According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits can be at least partially implemented as hardware circuits, such as field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), systems on chips, systems on substrates, systems on packages, application specific integrated circuits (ASICs), or can be implemented by hardware or firmware in any other reasonable way of integrating or packaging circuits, or can be implemented in any one of the three implementation methods of software, hardware, and firmware, or in any appropriate combination of any of them. Alternatively, according to the embodiments of the present invention, one or more of the modules, submodules, units, and subunits can be at least partially implemented as computer program modules, and when the computer program modules are run, the corresponding functions can be performed.

[0122] For example, any multiple of the acquisition module 510, the processing module 520, the marking module 530, and the rendering module 540 can be combined in one module / unit / sub-unit for implementation, or any one of the modules / units / sub-units can be split into multiple modules / units / sub-units. Alternatively, at least part of the functions of one or more of these modules / units / sub-units can be combined with at least part of the functions of other modules / units / sub-units and implemented in one module / unit / sub-unit. According to an embodiment of the present disclosure, at least one of the acquisition module 510, the processing module 520, the marking module 530, and the rendering module 540 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware, and firmware, or in any appropriate combination of any of them. Alternatively, at least one of the acquisition module 510 , the processing module 520 , the marking module 530 , and the rendering module 540 may be at least partially implemented as a computer program module, and when the computer program module is executed, a corresponding function may be performed.

[0123] Figure 6 A block diagram of an electronic device suitable for implementing a slice generation method based on flow field data according to an embodiment of the present invention is shown.

[0124] Figure 6 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0125] like Figure 6 As shown, a computer electronic device 600 according to an embodiment of the present invention includes a processor 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage part 608 into a random access memory (RAM) 603. The processor 601 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 601 may also include an onboard memory for caching purposes. The processor 601 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present invention.

[0126] In RAM 603, various programs and data required for the operation of electronic device 600 are stored. Processor 601, ROM 602 and RAM 603 are connected to each other via bus 604. Processor 601 performs various operations of the method flow according to the embodiment of the present invention by executing the programs in ROM 602 and / or RAM 603. It should be noted that the program can also be stored in one or more memories other than ROM 602 and RAM 603. Processor 601 can also perform various operations of the method flow according to the embodiment of the present invention by executing the programs stored in one or more memories.

[0127] Optionally, the electronic device 600 may further include an input / output (I / O) interface 605, which is also connected to the bus 604. The electronic device 600 may further include one or more of the following components connected to the input / output (I / O) interface 605: an input portion 606 including a keyboard, a mouse, etc.; an output portion 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 608 including a hard disk, etc.; and a communication portion 609 including a network interface card such as a LAN card, a modem, etc. The communication portion 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the input / output (I / O) interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed, so that a computer program read therefrom is installed into the storage portion 608 as needed.

[0128] Optionally, the method flow according to the embodiment of the present invention can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program contains a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 609, and / or installed from the removable medium 611. When the computer program is executed by the processor 601, the above-mentioned functions defined in the system of the embodiment of the present invention are executed. Optionally, the system, equipment, device, module, unit, etc. described above can be implemented by a computer program module.

[0129] The present invention also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiment; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the section generation method based on flow field data according to the embodiment of the present invention is implemented.

[0130] Optionally, the computer-readable storage medium may be a non-volatile computer-readable storage medium. For example, it may include, but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0131] For example, optionally, the computer-readable storage medium may include the ROM 602 and / or the RAM 603 described above and / or one or more memories other than the ROM 602 and the RAM 603 .

[0132] An embodiment of the present invention also includes a computer program product, which includes a computer program, which contains program code for executing the method provided by the embodiment of the present invention. When the computer program product runs on an electronic device, the program code is used to enable the electronic device to implement the section generation method based on flow field data provided by the embodiment of the present invention.

[0133] When the computer program is executed by the processor 601, the above functions defined in the system / device of the embodiment of the present invention are performed. Optionally, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0134] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 609, and / or installed from a removable medium 611. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0135] Optionally, the program code for executing the computer program provided by the embodiment of the present invention can be written in any combination of one or more programming languages, specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, such as Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., using an Internet service provider to connect through the Internet).

[0136] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions. It can be understood by those skilled in the art that the features recorded in the various embodiments of the present disclosure can be combined and / or combined in a variety of ways, even if such a combination or combination is not explicitly recorded in the present disclosure. In particular, without departing from the spirit and teaching of the present disclosure, the features described in the various embodiments of the present disclosure may be combined and / or combined in a variety of ways. All of these combinations and / or combinations fall within the scope of the present disclosure.

[0137] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Although the embodiments are described above, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A section generation method based on flow field data, characterized in that: The method comprises: Acquire initial point cloud data located at a target cutting position in a flow field scene, wherein the initial point cloud data includes spatial distribution information and physical state information of the initial point; Performing sparse processing on the initial point cloud based on the physical state information to obtain a target point cloud, wherein the initial point cloud includes a plurality of the initial points, and the target point cloud includes a plurality of the target points; Based on the spatial distribution information or the physical state information, the target point cloud is marked with boundaries to determine boundary points and non-boundary points, wherein the boundary points represent target points in the target point cloud located at the boundary position between the fluid and the solid in the flow field scene, and the non-boundary points represent target points in the target point cloud located outside the boundary position between the fluid and the solid in the flow field scene; The boundary points and the non-boundary points are processed by using a triangulated network growth algorithm and a surface rendering algorithm to obtain a rendering section, wherein the rendering section includes a boundary between a fluid and a solid in the flow field scene.

2. The method according to claim 1, characterized in that The physical state information includes first physical state information, wherein the first physical state information represents information of a decreasing state along the flow direction; The step of processing the boundary points and the non-boundary points using a triangulated network growth algorithm and a surface rendering algorithm to obtain a rendered section includes: Based on the sorting algorithm and the first physical state information, the boundary points and the non-boundary points are sorted to obtain a sorted point cloud; Divide the sorted point cloud into blocks based on a block algorithm to obtain at least one block point cloud; Processing the non-boundary points in the block point cloud using a triangulated mesh growing algorithm to obtain a triangulated mesh of at least one of the block point clouds; The triangular meshes of each of the block point clouds are rendered using a surface rendering algorithm to obtain the rendering section.

3. The method according to claim 1, characterized in that The spatial distribution information includes point cloud density information; Wherein, based on the spatial distribution information, the target point cloud is marked with boundaries, and determining the boundary points includes: When the point cloud density information of the target point in the target point cloud is greater than a preset density threshold, the target point is boundary marked to determine a boundary point.

4. The method according to claim 1, characterized in that: The physical state information also includes viscous fluid velocity information; Wherein, based on the physical state information, the points in the target point cloud are marked with boundaries, and determining the boundary points includes: When the viscous fluid velocity information of the target point in the target point cloud is equal to a preset viscous velocity threshold, the target point is boundary marked to determine a boundary point.

5. The method according to claim 1, characterized in that The physical state information also includes temperature information; Wherein, based on the physical state information, the target point cloud is marked with a boundary, and determining the boundary point further includes: When the temperature information of the target point in the target point cloud is greater than a preset temperature threshold, the target point is marked as a boundary to determine a boundary point.

6. The method according to claim 1, characterized in that The physical state information also includes flow velocity information; Wherein, based on the physical state information, marking the boundary of the target point cloud, and determining the boundary points includes: When the flow velocity information of the target point in the target point cloud is equal to the flow velocity threshold, the target point is boundary marked to determine the boundary point.

7. The method according to claim 1, characterized in that The initial point cloud is thinned based on the physical state information to obtain a target point cloud including: Determining physical state fluctuation levels of respective local areas according to the physical state information of respective initial points in the initial point cloud; When the physical state fluctuation level of the local area is less than a preset gradient threshold, determining the local area as an area to be processed; Performing a thinning process on the plurality of initial points located in the area to be processed to obtain a de-sparsed point cloud; The target point cloud is obtained according to the de-thinned point cloud and a plurality of the initial points located in a local area that has not been de-thinned.

8. A section generation device based on flow field data, comprising: An acquisition module, used to acquire initial point cloud data located at a target cutting position in a flow field scene, wherein the initial point cloud data includes spatial distribution information and physical state information of the initial point; A processing module, configured to perform a sparse processing on an initial point cloud based on the physical state information to obtain a target point cloud, wherein the initial point cloud includes a plurality of the initial points, and the target point cloud includes a plurality of the target points; A marking module, configured to mark the boundaries of the target point cloud based on the spatial distribution information or the physical state information, and determine boundary points and non-boundary points, wherein the boundary points represent target points in the target point cloud located at the boundary between the fluid and the solid in the flow field scene, and the non-boundary points represent target points in the target point cloud located outside the boundary between the fluid and the solid in the flow field scene; A rendering module is used to process the boundary points and the non-boundary points using a triangulated network growth algorithm and a surface rendering algorithm to obtain a rendering section, wherein the rendering section includes a boundary between a fluid and a solid in the flow field scene.

9. An electronic device, comprising: one or more processors; a memory for storing one or more programs, When one or more programs are executed by one or more processors, the one or more processors implement the method of any one of claims 1 to 7.

10. A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to implement the method of any one of claims 1 to 7.

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