Finite element post-processing data real-time rendering method, system and terminal

Abstract

The invention belongs to the field of computer graphics and finite element analysis post-processing, and particularly discloses a finite element post-processing data real-time rendering method and system and a terminal. According to the method and the device, through data division and compression, the amount of data needing to be processed and the calculation time in the rendering process are greatly reduced, the rendering speed of the large-scale finite element model is increased, efficient rendering of post-processing data of the large-scale finite element model is achieved, and through the regionalization processing and the self-adaptive detail control technology, the real-time performance of the large-scale finite element model is improved. The rendering precision is dynamically adjusted according to the visual angle of the user, consumption of memory and computing resources is reduced, and the overall performance of the system is improved. Compared with traditional CAE post-processing software, the interactive efficiency is improved by more than 30 times when the CAE post-processing software is used by a user, and the CAE post-processing software is smoother in performance.

Description

Technical Field

[0001] The present application belongs to the field of computer graphics and finite element analysis post-processing, and more specifically, to a real-time rendering method, system and terminal for finite element post-processing data, which can be widely used in post-processing rendering of large-scale finite element model data in the fields of engineering simulation, structural analysis, fluid mechanics, thermodynamics, etc. Background Art

[0002] Finite Element Analysis (FEA) is a numerical calculation method commonly used in engineering and physics. It is widely used in structural analysis, fluid mechanics, thermodynamics and other fields. Finite element post-processing is an important step in the finite element analysis process, which occurs after the solution calculation. The main purpose of post-processing is to visualize and analyze the calculation results so that users can understand and interpret the structural response. Among them, data visualization in the post-processing stage is an important part, and usually 3D rendering technology is needed to intuitively display the analysis results to users.

[0003] However, as the model complexity and data size increase, traditional rendering technology can no longer meet the needs of real-time interaction, especially in the post-processing of large-scale finite element models, where rendering performance issues are becoming increasingly prominent. Therefore, improving the rendering efficiency of finite element post-processing data has become an important technical challenge. Summary of the invention

[0004] In view of the defects of the prior art, the purpose of this application is to provide a real-time rendering method, system and terminal for finite element post-processing data, aiming to solve the problems in the prior art of slow rendering speed and poor real-time performance due to model complexity and huge data volume.

[0005] A first aspect of the present application relates to a real-time rendering method for finite element post-processing data, the real-time rendering method comprising: S1. Divide the result data set output by the finite element solution step according to the physical properties of the nodes or units to obtain several data subsets, and the data in the same data subset have the same physical properties; S2. adaptively compress each data subset separately to ensure that more details are retained in the key area, and obtain the compressed data subset; S3. Real-time regional rendering of each compressed data subset within the visible area under the current viewing angle.

[0006] In some implementations, step S1 is specifically: S11. Extract the physical characteristics of each node or unit from the finite element solution results; S12. The nodes or units that are spatially adjacent and whose physical characteristics are similar to each other exceeding a set threshold are classified into the same data subset; S13. Assign a unique identifier to each data subset, and store the data and attributes in each data subset in a corresponding data structure.

[0007] In some implementations, sub-step S12 is specifically: (1) Count the same physical characteristics of all nodes or units and obtain the maximum value of the physical characteristics and minimum value ; (2) Determine the range of physical properties of each data subset , ensuring that the range of physical properties in each data subset is the same:

[0008] (3) Determine the range of physical properties covered by each data subset ,in, Indicates the sequence number of the data subset, , Indicates the number of data subsets.

[0009] In some implementations, step S2 is specifically: S21. Determine compression requirement indicators: set compression requirement indicators according to the physical characteristics of each data subset, the maximum precision loss allowed by the user, the rendering frame rate, and the proportion of key data details to be retained; S22. Determine the optimal range of compression ratio: set the compression ratio range of each data subset with respect to the compression demand index, and the upper limit of the compression ratio of the key area is lower than the upper limit of the compression ratio of other areas; S23. Within the optimization range of the compression ratio, dynamically solving the optimal compression ratio of each data subset with the goal of measuring rendering quality while minimizing the amount of data transmission; S24. Adaptively compress each data subset using a dynamically calculated optimal compression ratio.

[0010] In some implementations, the calculation formula for measuring the rendering quality in step S23 is as follows:

[0011] in, Respectively, images Brightness, Respectively, images The contrast ratio, For images and images The covariance of the image is an uncompressed data subset, image A compressed subset of data.

[0012] In some implementations, step S3 is specifically as follows: S31. Using the frustum clipping algorithm, identify the visible area under the current viewing angle, send the compressed data subset of the visible area to the rendering queue, and remove the invisible area; S32. Obtain the distance between each object in the visible area and the camera. If it is greater than a set threshold, it is identified as a distant area; otherwise, it is identified as a near area; S33. Rendering a near area with a first precision and a far area with a second precision, wherein the first precision is higher than the second precision; S34. Cache the loaded compressed data subset in memory and perform incremental update rendering when the viewing angle changes.

[0013] A second aspect of the present application relates to a real-time rendering system for finite element post-processing data, the real-time rendering system comprising at least one processor and at least one memory; The at least one memory is used to store computer instructions; The at least one processor is used to execute at least part of the computer instructions to implement the real-time rendering method according to any embodiment of the present application.

[0014] In some embodiments, the at least one processor includes a CPU and a GPU; The CPU is used to partition and compress the data set and load the compressed data subset to the GPU; The GPU is used for real-time regional rendering of each compressed data subset within the visible area under the current viewing angle.

[0015] In some implementations, the CPU uses multi-threading technology to execute different tasks in parallel, wherein the main thread is responsible for user interaction and controlling the rendering process, and other threads are responsible for data parsing and model loading, so that the currently processed part is rendered simultaneously with data parsing.

[0016] A third aspect of the present application relates to an electronic device terminal, which is used to implement a finite element post-processing data real-time rendering system according to any one of the embodiments of the present application.

[0017] In general, the above technical solutions conceived by this application have the following beneficial effects compared with the prior art: This application proposes a real-time rendering method, system and terminal for finite element post-processing data. Through data division and compression, the amount of data to be processed and the computing time required in the rendering process are greatly reduced, the rendering speed of large-scale finite element models is improved, and efficient rendering of large-scale finite element model post-processing data is achieved. Through regional processing and adaptive detail control technology, the rendering accuracy is dynamically adjusted according to the user's perspective, the consumption of memory and computing resources is reduced, and the overall performance of the system is improved. Compared with traditional CAE (computer-aided engineering) post-processing software, the user interaction efficiency is improved by more than 30 times, and the performance is smoother. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a flow chart of a real-time rendering method for finite element post-processing data provided by this application.

[0019] Figure 2 This is a schematic diagram of the rendering effect of the filled area changing over time provided by this application.

[0020] Figure 3 This is a schematic diagram of the rendering effect of the flow path changing over time provided by this application.

[0021] Figure 4 This is a schematic diagram of the flow front temperature rendering results provided by this application.

[0022] Figure 5 This is a schematic diagram of the deformation rendering result provided by this application.

[0023] Figure 6 It is a structural schematic diagram of a finite element post-processing data real-time rendering system provided by this application. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0025] The term "and / or" in this article is a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The symbol " / " in this article indicates that the associated objects are in an or relationship, for example, A / B means A or B.

[0026] The terms "first" and "second" in the specification and claims herein are used to distinguish different objects rather than to describe a specific order of the objects. For example, a first response message and a second response message are used to distinguish different response messages rather than to describe a specific order of the response messages.

[0027] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0028] In the description of the embodiments of the present application, unless otherwise specified, "multiple" means two or more than two. For example, multiple processing units refer to two or more processing units, etc.; multiple elements refer to two or more elements, etc.

[0029] The embodiments of the present application are described below in conjunction with the drawings in the embodiments of the present application.

[0030] like Figure 1 As shown, the present application provides a real-time rendering method for finite element post-processing data, the real-time rendering method comprising: S1. The result data set output by the finite element solution step is divided according to the physical properties of the nodes or units to obtain several data subsets. The data in the same data subset have the same physical properties.

[0031] After the finite element analysis is solved and calculated, the result obtained is usually a large-scale data set, including node displacements, stress and strain fields, etc. In order to reduce the amount of data transmitted during the rendering process, this application adopts data partitioning and compression technology.

[0032] In some implementations, step S1 specifically includes: S11. Extract the physical properties of each node or unit from the finite element solution results.

[0033] The physical unit in finite element analysis refers to a single element obtained by discretizing a continuous structure. These units approximately describe the behavior of the actual structure by assuming an approximate solution. Each unit has its own specific shape and size, and they are only connected to each other at nodes. The type of unit can be different according to the needs of the analysis, such as beam elements, rod elements, plane elements, shell elements, and three-dimensional elements.

[0034] The physical properties of physical units in finite element analysis include but are not limited to: material properties (such as elastic modulus, Poisson's ratio, etc.), collective properties (such as area, length, etc.), degrees of freedom (such as displacement, temperature, electric potential, etc.), unit types (such as mechanical units, temperature field units, electric field units, etc.).

[0035] Nodes in finite element analysis are the points where physical units are connected. They are key locations in the finite element model. All physical units are connected through nodes. Degrees of freedom such as displacement, velocity, acceleration, etc. are defined at nodes.

[0036] The physical properties of nodes in finite element analysis include but are not limited to: degrees of freedom (such as displacement, rotation, temperature, pressure, etc.), velocity, acceleration, reaction force and load.

[0037] The present application arranges the data node numbers from small to large, and stores the traversed unit information and node information in an array.

[0038] S12. Nodes or units that are spatially adjacent and whose physical characteristics are similar to a set threshold are grouped into the same data subset.

[0039] The determination of whether nodes are adjacent is usually based on the unit connectivity and the geometric topology of the model. This method ensures the accuracy of the analysis and is consistent with the basic principles of finite element analysis.

[0040] The determination method based on unit connectivity is specifically: checking the unit connectivity matrix or adjacency matrix in the finite element model. If two nodes belong to at least one unit in common, then the two nodes are considered to be adjacent.

[0041] The determination method based on the geometric topological structure of the model is specifically: analyzing the topological structure of the grid to determine the connection relationship between nodes. In a regular grid, adjacent nodes are usually directly connected according to the arrangement order of the grid.

[0042] S13. Assign a unique identifier to each data subset, and store the data and attributes in each data subset in a corresponding data structure.

[0043] In some implementations, sub-step S12 is specifically: (1) Count the same physical characteristics of all nodes or units and obtain the maximum value of the physical characteristic and minimum value ; (2) Determine the range of physical properties of each data subset , ensuring that the range of physical properties in each data subset is the same:

[0044] (3) Determine the range of physical properties covered by each data subset ,in, Indicates the sequence number of the data subset, , Indicates the number of data subsets.

[0045] S2. Adaptively compress each data subset separately to ensure that more details are retained in the key area, and obtain the compressed data subset.

[0046] The finite element result data is compressed into a format suitable for transmission and rendering according to the compression algorithm. The compression degree is adaptively adjusted according to the characteristic changes of the data in different areas, ensuring that more details are retained in important areas and a higher compression ratio is performed in smooth areas. In an illustrated embodiment, a multi-resolution model is used to use geometric data with different levels of detail at different rendering levels.

[0047] In some implementations, step S2 is specifically: S21. Determine compression requirement indicators: set compression requirement indicators based on the physical characteristics of each data subset, the maximum precision loss allowed by the user, the rendering frame rate, and the proportion of details retained in key data.

[0048] In an illustrated embodiment, the maximum precision loss is quantified by RMSE (root mean square error); the rendering frame rate needs to meet the requirements of real-time interaction, usually above 20FPS; the key area refers to the area corresponding to high stress, and the proportion of retained details is above 80%.

[0049] S22. Determine the optimal range of compression ratio: set the compression ratio range of each data subset with respect to the compression demand index, and the upper limit of the compression ratio of the key area is lower than the upper limit of the compression ratio of other areas.

[0050] In an illustrated embodiment, experimental compression is performed from 1:5 to 1:20, and the compression ratio is dynamically adjusted according to different viewing angles or rendering frame rate requirements to find out the compression ratio range that meets the compression requirement index required by step S21.

[0051] S23. Within the optimization range of the compression ratio, the optimal compression ratio of each data subset is dynamically solved with the goal of minimizing the amount of data transmission while satisfying the quality of rendering.

[0052] This application takes the compression ratio as the variable to be optimized, and combines the rendering quality and the amount of data transmitted in a weighted form:

[0053] in, is the objective function used to evaluate the current compression ratio The combined effect of It is a rendering quality indicator, which usually increases with the compression rate; It is an indicator of the amount of data transmitted, reflecting the amount of data under the current compression ratio, and increases as the compression ratio increases; and are weight coefficients, which respectively control the importance of rendering quality and transmission data volume in optimization.

[0054] In some implementations, the calculation formula for measuring the rendering quality in step S23 is as follows:

[0055] in, Respectively, images Brightness, Respectively, images The contrast ratio, For images and images The covariance of the image is an uncompressed data subset, image A compressed subset of data.

[0056] The above indicators measure the local structural information of the image, so they are more effective for visual consistency evaluation. The closer the value is to 1, the better the image quality.

[0057] S24. Adaptively compress each data subset using a dynamically calculated optimal compression ratio.

[0058] Determines the best compression ratio by calculating the best rendering quality over a range of compression ratios.

[0059] The data in the data subset is extracted by using the optimal compression ratio, and the extracted data is stored in the corresponding data structure for rendering.

[0060] S3. Real-time regional rendering of each compressed data subset within the visible area under the current viewing angle.

[0061] This application performs regional processing on the data set and gives priority to the areas in the user's field of view during rendering. For invisible or less affected areas, a low-precision simplified model is used or the data of the area is lazily loaded in the background, which can significantly reduce the amount of calculation in the rendering stage and thus improve rendering efficiency.

[0062] In some implementations, step S3 is specifically as follows: S31. Using the frustum clipping algorithm, identify the visible area under the current viewing angle, send the compressed data subset of the visible area to the rendering queue, and remove the invisible area; S32. Obtain the distance between each object in the visible area and the camera. If it is greater than a set threshold, it is identified as a distant area; otherwise, it is identified as a near area; S33. Rendering a near area with a first precision and a far area with a second precision, wherein the first precision is higher than the second precision; S34. Cache the loaded compressed data subset in memory and perform incremental update rendering when the viewing angle changes.

[0063] By calculating the difference between the current view and the previous frame's view, only a subset of data in the changed area is updated, reducing unnecessary re-rendering.

[0064] In an illustrated embodiment, the rendering result cloud map is as follows: Figure 2-Figure 5 As shown. Among them, Figure 2 It indicates that during the filling process, the filling area of ​​the melt in the injection mold changes with time. Figure 3 It indicates that during the filling process, the flow path of the melt in the injection mold changes with time. Figure 4 It indicates the front temperature of the melt when it flows to the corresponding position during the filling process. Figure 5 It indicates the deformation of the injection molded part caused by the injection molding process after the filling, holding and cooling stages are completed. The cloud chart can show the warpage displacement at various locations.

[0065] The above method is particularly suitable for complex finite element models. It can efficiently process models with complex structures and large amounts of data and is widely used in engineering simulation, structural analysis, fluid mechanics and other fields. It can be easily integrated into existing finite element post-processing software and is compatible with a variety of hardware platforms, especially GPU acceleration devices, and has good scalability and application prospects.

[0066] like Figure 6 As shown, the present application provides a real-time rendering system for finite element post-processing data, the real-time rendering system comprising at least one processor and at least one memory; The at least one memory is used to store computer instructions; The at least one processor is used to execute at least part of the computer instructions to implement the real-time rendering method according to any embodiment of the present application.

[0067] In some embodiments, the at least one processor includes a CPU and a GPU; The CPU is used to partition and compress the data set and load the compressed data subset to the GPU; The GPU is used for real-time regional rendering of each compressed data subset within the visible area under the current viewing angle.

[0068] GPU is good at processing large-scale parallel tasks. This application reduces the CPU load by transferring the compressed data subset of finite element analysis to the GPU for graphics rendering. Combining the graphics rendering capabilities of modern GPUs, using graphics interfaces such as OpenGL, Vulkan or DirectX can achieve more efficient rendering calculations.

[0069] In some implementations, the CPU uses multi-threading technology to execute different tasks in parallel, wherein the main thread is responsible for user interaction and controlling the rendering process, and other threads are responsible for data parsing and model loading, so that the currently processed part is rendered simultaneously with data parsing.

[0070] This application avoids resource competition during the calculation process and improves the overall rendering response speed by allocating independent threads to different tasks; optimizes the collaborative work of data parsing and rendering, reduces rendering delays, and allows users to have a smoother interactive experience when performing model operations.

[0071] A third aspect of the present application relates to an electronic device terminal, which is used to implement a finite element post-processing data real-time rendering system according to any one of the embodiments of the present application.

[0072] Based on the method in the above embodiment, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program runs on a processor, the processor executes the method in the above embodiment.

[0073] Based on the method in the above embodiment, an embodiment of the present application provides a computer program product. When the computer program product runs on a processor, the processor executes the method in the above embodiment.

[0074] It is understandable that the processor in the embodiment of the present application may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. The general-purpose processor may be a microprocessor or any conventional processor.

[0075] The method steps in the embodiments of the present application can be implemented by hardware or by a processor executing software instructions. The software instructions can be composed of corresponding software modules, and the software modules can be stored in random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, mobile hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an ASIC.

[0076] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions may be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)), etc.

[0077] It should be understood that the various numerical numbers involved in the embodiments of the present application are only used for the convenience of description and are not used to limit the scope of the embodiments of the present application.

[0078] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A real-time rendering method for finite element post-processing data, characterized in that: include: S1. Divide the result data set output by the finite element solution step according to the physical properties of the nodes or units to obtain several data subsets, and the data in the same data subset have the same physical properties; S2. adaptively compress each data subset separately to ensure that more details are retained in the key area, and obtain the compressed data subset; S3. Real-time regional rendering of each compressed data subset within the visible area under the current viewing angle.

2. The real-time rendering method according to claim 1, characterized in that: Step S1 is specifically as follows: S11. Extract the physical characteristics of each node or unit from the finite element solution results; S12. The nodes or units that are spatially adjacent and whose physical characteristics are similar to each other exceeding a set threshold are classified into the same data subset; S13. Assign a unique identifier to each data subset, and store the data and attributes in each data subset in a corresponding data structure.

3. The real-time rendering method according to claim 2, characterized in that: Sub-step S12 is specifically as follows: (1) Count the same physical characteristics of all nodes or units and obtain the maximum value of the physical characteristic and minimum value ; (2) Determine the range of physical properties of each data subset , ensuring that the range of physical properties in each data subset is the same: (3) Determine the range of physical properties covered by each data subset ,in, Indicates the sequence number of the data subset, , Indicates the number of data subsets.

4. The real-time rendering method according to claim 1, characterized in that: Step S2 is specifically as follows: S21. Determine compression requirement indicators: set compression requirement indicators according to the physical characteristics of each data subset, the maximum precision loss allowed by the user, the rendering frame rate, and the proportion of key data details to be retained; S22. Determine the optimal range of compression ratio: set the compression ratio range of each data subset with respect to the compression demand index, and the upper limit of the compression ratio of the key area is lower than the upper limit of the compression ratio of other areas; S23. Within the optimization range of the compression ratio, dynamically solving the optimal compression ratio of each data subset with the goal of measuring rendering quality while minimizing the amount of data transmission; S24. Adaptively compress each data subset using a dynamically calculated optimal compression ratio.

5. The real-time rendering method according to claim 4, characterized in that: The calculation formula for measuring the rendering quality in step S23 is as follows: in, Respectively, images Brightness, Respectively, images The contrast ratio, For images and images The covariance of the image is an uncompressed data subset, image A compressed subset of data.

6. The real-time rendering method according to claim 1, characterized in that: Step S3 is as follows: S31. Using the frustum clipping algorithm, identify the visible area under the current viewing angle, send the compressed data subset of the visible area to the rendering queue, and remove the invisible area; S32. Obtain the distance between each object in the visible area and the camera. If it is greater than a set threshold, it is identified as a distant area; otherwise, it is identified as a near area; S33. Rendering a near area with a first precision and a far area with a second precision, wherein the first precision is higher than the second precision; S34. Cache the loaded compressed data subset in memory and perform incremental update rendering when the viewing angle changes.

7. A real-time rendering system for finite element post-processing data, characterized in that: comprising at least one processor and at least one memory; The at least one memory is used to store computer instructions; The at least one processor is used to execute at least part of the computer instructions to implement the real-time rendering method according to any one of claims 1 to 6.

8. The real-time rendering system according to claim 7, characterized in that: The at least one processor includes a CPU and a GPU; The CPU is used to partition and compress the data set and load the compressed data subset to the GPU; The GPU is used for real-time regional rendering of each compressed data subset within the visible area under the current viewing angle.

9. The real-time rendering system according to claim 8, characterized in that: The CPU uses multi-threading technology to execute different tasks in parallel, wherein the main thread is responsible for user interaction and controlling the rendering process, and other threads are responsible for data parsing and model loading, so that the currently processed part is rendered while the data is parsed.

10. An electronic equipment terminal, characterized in that: The electronic device terminal is used to implement the finite element post-processing data real-time rendering system as described in claim 9.

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