CN115587480A - Digital simulation method and digital simulation device - Google Patents
Digital simulation method and digital simulation device Download PDFInfo
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- CN115587480A CN115587480A CN202211174878.8A CN202211174878A CN115587480A CN 115587480 A CN115587480 A CN 115587480A CN 202211174878 A CN202211174878 A CN 202211174878A CN 115587480 A CN115587480 A CN 115587480A
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Abstract
The invention provides a digital simulation method and a digital simulation device. The digital simulation method comprises the following steps: dividing a simulation analysis process into a plurality of nodes; respectively packaging each node into a functional module capable of being compiled and executed; setting a required parameter value at each node, and sequentially connecting the nodes in series according to a simulation analysis process; and starting a simulation analysis process, and sequentially executing according to the node sequence to realize the simulation analysis process.
Description
Technical Field
The present invention relates to the field of simulation, and in particular, to a digital simulation method and a digital simulation apparatus.
Background
In traditional production research and development, a test piece needs to pass through multiple trial productions and continuously iterate and circulate to solve the problems encountered in the product design and manufacturing process. In this conventional approach, the whole development life cycle is as long as several months or even several years, and each parameter change causes huge expense and time consumption. In contrast, the digital simulation reproduces the physical object in a digital mode, simulates the behavior of the object in a real environment, and performs virtual simulation on the product, the manufacturing process and even the whole factory, thereby improving the production efficiency of product research and development and manufacturing of manufacturing enterprises.
Disclosure of Invention
With the wide development of the digital simulation analysis work in enterprises, a large number of engineers participate in the digital simulation analysis work. In the analysis process, different analysis engineers often have different processing such as model simplification, grid division, boundary conditions and the like due to limitations of self-mastered related professional knowledge, differences of software mastering capability and different understanding degrees of products, and have larger randomness, so that different analysts have certain differences for the same problem analysis result, a product designer is caused to doubtful the analysis result, and the analysis result needs to be checked repeatedly under the condition, and a large amount of manpower and material resources are wasted. On the other hand, many repetitive tasks of the digital simulation analysis are time-consuming, such as modeling, grid division, loading, report output and the like, but the processes must be repeated for each analysis, and the repeated labor without added value causes waste of a large amount of manpower and material resources, so that the analysis efficiency is low, and the analysis cost is increased.
Meanwhile, the simulation analysis work needs to be carried out through the processes of CAD/CAE modeling, performance simulation analysis solving, result evaluation, report writing and the like, and various different tool software is used in the process, so that analysts frequently carry out data conversion, transmission and change, artificial errors are easily caused, and time is wasted.
Moreover, the traditional simulation analysis process has high requirements on analysts, and the substantial theoretical knowledge and skilled software operation are the basic literacy of the simulation analysts. How to enhance the usability of simulation software and how to precipitate, solidify and popularize a large amount of accumulated simulation models so as to promote enterprise research, development, innovation and digital transformation and upgrade are the problems which need to be solved in the future.
The present invention has been made in view of the above problems, and an object of the present invention is to solve at least one of the above problems and to provide a digital simulation method and a digital simulation apparatus capable of improving usability and analysis efficiency and improving result accuracy.
According to a first aspect of the present invention, there is provided a digital simulation method, comprising: dividing the simulation analysis process into a plurality of nodes; respectively packaging each node into a functional module capable of being compiled and executed; setting a required parameter value at each node, and sequentially connecting the nodes in series according to a simulation analysis process; and starting a simulation analysis process, and sequentially executing according to the node sequence to realize the simulation analysis process.
According to a second aspect of the present invention, there is provided a digital simulation apparatus comprising: the node module comprises a plurality of nodes, wherein the nodes are obtained by dividing a simulation analysis process and are respectively packaged into functional modules which can be compiled and executed, and required parameter values can be set in each node; the series module is used for sequentially connecting the nodes with the set parameter values in series according to a simulation analysis flow; and the execution module is used for sequentially executing the nodes which are connected in series according to the sequence of the nodes so as to realize the simulation analysis process.
In some embodiments, the nodes include at least one of simulation type nodes, simulation mechanism nodes, design digital-to-analog nodes, geometry processing nodes, material parameter nodes, boundary condition nodes, mesh partitioning nodes, computational nodes, simulation result nodes, data collection nodes, and optimization nodes.
In some embodiments, in the design model node, a digital model of an object to be simulated is directly introduced, or a model corresponding to the object is selected from a plurality of preset general models and adjusted.
In some embodiments, in the computing node, devices with different computational power are selected according to different computational power required by the simulation model.
In some embodiments, the nodes include a data acquisition node in which a measurement result actually measured by performing the same process as a simulation process on an object to be simulated is acquired, and an optimization node in which the measurement result is compared with a simulation result and each of the nodes is optimized in such a manner that the simulation result is close to the measurement result.
Effects of the invention
According to the present invention, it is possible to provide a digital simulation method and a digital simulation apparatus which can improve usability and analysis efficiency and improve result accuracy.
It should be understood that the statements made in this summary are not intended to limit the scope of the invention to the particular features or essential features of the embodiments, nor are they intended to limit the scope of the invention. Other features of the present invention will be readily apparent from the following description.
Drawings
The above and other features, advantages and aspects of embodiments of the present invention will become more apparent upon consideration of the following detailed description, taken in conjunction with the accompanying drawings. In the drawings, like or similar reference characters denote like or similar elements, and wherein:
FIG. 1 shows a schematic flow diagram of a digital simulation method of one embodiment of the present invention.
Fig. 2 schematically shows an example of a node flowchart of the digital simulation analysis according to the embodiment of the present invention.
FIG. 3 shows a schematic block diagram of a digitizing emulation apparatus of one embodiment of the present invention.
Detailed Description
Embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Hereinafter, the portions relating to the improvement points of the present invention will be mainly described in detail, and other portions may adopt various known configurations. Furthermore, while certain embodiments of the present invention have been illustrated in the accompanying drawings, it is to be understood that the invention may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more complete and thorough understanding of the invention. It should be understood that the drawings and the embodiments of the invention are for illustration purposes only and are not intended to limit the scope of the invention.
The terms "include" and variations thereof as used herein are inclusive and open-ended, i.e., "including but not limited to. The term "based on" is "based at least in part on". The term "one embodiment (implementation)" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment". Relevant definitions for other terms will be given in the following description.
As described above, in the current digital simulation, there are problems that a result difference is caused by a difference in process processing, time and labor are consumed for repetitive work, errors are easily caused and time is wasted in data processing between different tool software, and usability needs to be improved. In view of this, the embodiments of the present invention provide a solution that can improve usability and analysis efficiency, and improve result accuracy. In the scheme, the steps of the digital simulation are divided and packaged (solidified) into functional modules (node codes) which can be compiled and executed, and corresponding models, material data, algorithms and the like are called in each functional module to self-customize a simulation flow, so that the threshold of a simulation technology is reduced, and the analysis efficiency, the analysis accuracy and the usability are improved.
FIG. 1 shows a schematic flow diagram of a digital simulation method 100 of one embodiment of the present invention. As shown in FIG. 1, in a digital simulation method 100, a simulation analysis process is divided into a plurality of nodes (step S1). Specifically, for example, the division may be performed according to the simulation type. The simulation type is not particularly limited, and examples thereof include various types such as mechanical simulation, thermal simulation, and hydrodynamic simulation.
Regarding the division of the nodes, the nodes may be divided into various nodes according to the requirement of the simulation type, and in this embodiment, as shown in fig. 2, the nodes include at least one of a simulation type node, a simulation mechanism node, a design digital-analog node, a geometric processing node, a material parameter node, a boundary condition node, a mesh division node, a calculation node, a simulation result node, a data acquisition node, and an optimization node, for example.
After the nodes are divided, each node is respectively packaged into a functional module which can be compiled and executed (step S2). That is, each node is implemented in the form of a functional module, specifically, a function package to be implemented by the node is coded, and an attribute interface is opened. In the present embodiment, for example, the code may be coded using Abaqus as a software carrier and Python as a kernel script language, but the present invention is not limited thereto, and other software carriers and languages may be used and appropriately selected as necessary.
When simulation analysis is performed, a required parameter value is set at each node, and the nodes are connected in series in sequence according to a simulation analysis flow (step S3). Specifically, in the present embodiment, for example, a node as a function module may be opened in a window form, and a desired parameter value may be input or selected in a page. The serial connection of the nodes refers to the sequential connection of the nodes according to the data flow direction, and the front and back logic sequence of each node is limited. The concatenation of nodes may be performed by dragging the nodes in sequence or out of order and connecting them in logical order. Data streams between the nodes are transmitted through the connecting lines, so that a neural network system for calculating while walking is formed.
After the setting of the parameter values in the nodes and the serial connection of the nodes are completed, a simulation analysis process is started, and the simulation analysis process is sequentially executed according to the node sequence (step S4).
Fig. 2 schematically shows an example of a node flow diagram of the digital simulation analysis according to the embodiment of the present invention. The node flow is further explained with reference to fig. 2.
As shown in fig. 2, the simulation terminal serves as a starting point to start the simulation analysis process. The simulation terminal herein refers to a subject for performing simulation analysis, and a computer, for example, may be used.
After the simulation analysis is started in the simulation terminal, the type of the digital simulation to be carried out is selected in the simulation type node, and a required simulation mechanism is selected according to the simulation type. For simulation mechanisms, such as the presence of set deformations of C-beams, set deformations of composite materials, etc., there are multiple simulation mechanisms for each simulation type, which can be selected as desired.
In designing the digital-to-analog nodes, a specific digital model is set. Here, a digital model (for example, CAD model) of the object to be simulated may be directly introduced, or a model corresponding to the object may be selected from a plurality of general models set in advance and adjusted so that the shape, size, and the like of the model correspond to the object.
After the setting of the design digital-analog nodes is finished, the digital model is processed in the geometric processing nodes according to the requirements, and the digital model is simplified. Specifically, since various details are not very much focused in the simulation analysis, the digital model may be subjected to processing such as hole removal and corner rounding to simplify the model and reduce the processing load. The type of geometric processing is not limited, and for example, a common processing operation may be set in the geometric processing node, and an analyst may select the processing operation as needed. Further, since the attribute interface is opened to each node as described above, the addition, deletion, change, and the like of the processing operation in the geometric processing node can be performed as necessary. This improves the ease of use and the degree of freedom in design.
And aiming at the digital model subjected to the geometric processing, grids are divided in the grid division nodes. The mesh division method is not particularly limited, and may be selected from, for example, common methods for node consolidation, or may be directly input by an analyst a desired division size, a requirement, or the like.
In addition, in the material parameter node, a corresponding material attribute may be input in an attribute column included in the material parameter node, or an existing material attribute model may also be selected. The material parameters are parameters indicating the properties of the material itself, such as various mechanical and thermal performance parameters of the material, and as in the mesh division nodes, common combinations of parameters can be set, and addition, deletion, and modification can be performed through an open property interface.
In addition, in the boundary condition node, corresponding boundary conditions are set according to the requirements of simulation. The boundary condition is a condition for processing an object, and may be, for example, a three-point bend, a cantilever, or the like, and may be similarly cured to have a common condition, and may be added, deleted, changed, or the like through an open attribute interface.
After the setting in each node is completed, the simulation model is generated, and then the calculation is performed in the calculation node. Specifically, the devices with different computational power are selected according to the different computational power required by the simulation model. For example, a complex large-scale simulation model may be imported into a high-performance computing cluster node (HPC) for computation, while a simple small-scale model may be computed at the local edge. By selecting different computing resources according to the size of the simulation model in this way, the processing efficiency can be improved and the computing resources can be saved.
In the simulation result node, an analysis report is generated by processing, summarizing, and the like the simulation results obtained by the processing in the computation node.
In addition, a data acquisition node and an optimization node can be further included. In the data collection node, a measurement result actually measured by performing the same process as in the simulation process on the object is collected. In the optimization node, the measurement result is compared with the simulation result described above, and each node is optimized in such a manner that the simulation result is close to the measurement result. By carrying out reverse optimization in this way, the simulation model can be continuously iterated, the accuracy of the simulation model is improved, and automatic intelligent operation of CAD-CAE-CAO is realized.
As described above, in the present invention, by dividing the simulation analysis process into a plurality of nodes and respectively packaging each node into a functional module capable of being compiled and executed, an analyst can quickly perform the simulation analysis according to a standard workflow, and ensure the consistency of the result, so that the simulation operation can be efficiently, quickly and accurately performed, and a strong guarantee is provided for product research and development. Moreover, through standardization and normalization of simulation analysis work, the simulation analysis time can be effectively shortened, the analysis quality is improved, and the accuracy of an analysis result is ensured.
In addition, the simulation flow is executed to automatically obtain the analysis result and generate the final analysis report, and the conventional data conversion, transmission and modification are not needed, so that the accuracy of the result can be improved, and the time can be saved.
In addition, an analyst does not need to perform a large amount of repetitive work every time, and can complete the simulation analysis process by simply selecting and inputting simple attribute parameters and the like, so that the time can be saved, the analysis efficiency can be improved, and the analysis cost can be reduced. Meanwhile, the process is simplified, so that the usability is improved, and the threshold requirement on an analyst is reduced.
Furthermore, by reverse optimization and rapid updating of an iteration mechanism, efficient comparison analysis of engineering analysis results and actual results is achieved, model optimization correction efficiency is accelerated, and analysis efficiency and accuracy are further improved.
FIG. 3 shows a schematic block diagram of a digital simulation apparatus 300 according to an embodiment of the present invention. It is to be understood that the digital simulation apparatus 300 may include additional components than those shown or omit a portion of the components shown therein, and the present invention is not limited thereto.
As shown in fig. 3, the digital simulation apparatus 300 includes a node module 310, a series module 320, and an execution module 330. The node module 310 includes a plurality of nodes, which are obtained by dividing the simulation analysis process and are respectively packaged into functional modules that can be compiled and executed, and can set the required parameter values at each node. The series module 320 is configured to sequentially connect the nodes with the set parameter values in series according to the simulation analysis process. The execution module 330 executes in sequence in the order of the nodes being connected in series to implement the simulation analysis process. The specific configuration and processing of each block can be the same as those described above, and therefore, redundant description is omitted.
The preferred embodiments of the present invention have been described above in detail, but the present invention is not limited thereto. Various alterations, additions, deletions, or substitutions in the described embodiments may be made by those skilled in the art to which the invention pertains. In the above embodiment, although the steps, nodes, and the like are described in a certain order, the order is not necessarily limited to this order, and the order of the steps and nodes may be changed as long as no contradiction occurs. The technical scope of the present invention is defined by the claims, and the meaning equivalent to the description of the claims and all modifications within the scope thereof are also included.
Claims (10)
1. A digital simulation method, comprising:
dividing a simulation analysis process into a plurality of nodes;
respectively packaging each node into a functional module capable of being compiled and executed;
setting a required parameter value at each node, and sequentially connecting the nodes in series according to a simulation analysis process; and
and starting a simulation analysis process, and sequentially executing according to the node sequence to realize the simulation analysis process.
2. The digital simulation method according to claim 1,
the nodes comprise at least one of simulation type nodes, simulation mechanism nodes, design digital-analog nodes, geometric processing nodes, material parameter nodes, boundary condition nodes, grid division nodes, calculation nodes, simulation result nodes, data acquisition nodes and optimization nodes.
3. The digital simulation method of claim 2,
in the design digifax node, a digital model of an object to be simulated is directly introduced, or a model corresponding to the object is selected from a plurality of preset general models and adjusted.
4. The digital simulation method according to claim 2,
in the computing node, devices with different computing power are selected according to different computing power required by the simulation model.
5. The digital simulation method according to any one of claims 1 to 4,
the nodes comprise a data acquisition node and an optimization node,
the data acquisition node acquires a measurement result actually measured by performing the same process as a simulation process on an object to be simulated, and the optimization node compares the measurement result with a simulation result and optimizes each node so that the simulation result is close to the measurement result.
6. A digital simulation device is characterized by comprising:
the node module comprises a plurality of nodes, wherein the nodes are obtained by dividing a simulation analysis process and are respectively packaged into functional modules which can be compiled and executed, and required parameter values can be set in each node;
the series module is used for sequentially connecting the nodes with the set parameter values in series according to a simulation analysis process; and
and the execution module is used for sequentially executing the nodes which are connected in series according to the sequence so as to realize the simulation analysis process.
7. The digital simulation apparatus according to claim 6,
the nodes comprise at least one of simulation type nodes, simulation mechanism nodes, design digital-analog nodes, geometric processing nodes, material parameter nodes, boundary condition nodes, grid division nodes, calculation nodes, simulation result nodes, data acquisition nodes and optimization nodes.
8. The digital simulation apparatus according to claim 7,
in the design model node, a digital model of an object to be simulated is directly introduced, or a model corresponding to the object is selected from a plurality of preset general models and adjusted.
9. The digital simulation apparatus according to claim 7,
in the computing nodes, devices with different computing power are selected according to different computing power required by the simulation model.
10. The digital simulation apparatus according to any one of claims 6 to 9,
the nodes comprise a data acquisition node and an optimization node,
the data acquisition node acquires a measurement result actually measured by performing the same process as a simulation process on an object to be simulated, and the optimization node compares the measurement result with a simulation result and optimizes each node so that the simulation result is close to the measurement result.
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