CN115659711A - Simulation method and device, electronic equipment and storage medium - Google Patents
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Abstract
The application provides a simulation method, a simulation device, electronic equipment and a storage medium, which relate to the technical field of engineering design, wherein at least one target simulation process parameter item is determined from all simulation process parameter items; generating a plurality of simulation process parameter sets by permutation and combination according to all the determined target simulation process parameter items and all the parameter values of each target simulation process parameter item; simulating the simulation target to obtain a simulation value corresponding to each simulation process parameter set; and determining whether the simulation values corresponding to the simulation process parameter sets meet optimization conditions or not according to the simulation values corresponding to each simulation process parameter set, and if the simulation values corresponding to the simulation process parameter sets meet the optimization conditions, determining the simulation process parameter sets as first optimization process parameter sets, so that the optimization process parameter sets can be determined while simulation is operated, and technicians are helped to determine process parameter values of industrial products, and industrial products with better performance can be obtained.
Description
Technical Field
The present application relates to the technical field of engineering design, and in particular, to a simulation method, apparatus, electronic device, and storage medium.
Background
Most of the current CAE (Computer Aided Engineering) software is in the form of general-purpose software, for example, providing a simulation application program for a simulation model, so that a design engineer focuses on considering design parameters of a product. In order to make CAE software truly used for guiding product design, many CAE manufacturers have developed multidisciplinary and multi-objective optimization software to obtain optimal product performance. The current optimization function and simulation are still relatively independent, and the existing simulation application program does not have the optimization function on the process parameters.
Disclosure of Invention
In view of the above, an object of the present application is to provide a simulation method, a simulation apparatus, an electronic device, and a storage medium, which obtain optimized process parameters while performing a simulation experiment to guide the design of an industrial product.
In a first aspect, the present application provides a simulation method, which includes obtaining all simulation process parameter items configured by a user in computer aided engineering software for a created industrial product model, and at least one parameter value of each simulation process parameter item, and obtaining a simulation target configured by the user in the computer aided engineering software for the industrial product model; determining at least one target simulation process parameter item in all simulation process parameter items; generating a plurality of simulation process parameter sets by permutation and combination according to all the determined target simulation process parameter items and all parameter values of each target simulation process parameter item, wherein each simulation process parameter value set comprises one parameter value of each target simulation process parameter item; the computer aided engineering software simulates a simulation target by taking a simulation environment configured for an industrial product model by a user and each simulation process parameter group as simulation conditions to obtain a simulation value corresponding to each simulation process parameter group; and determining whether the simulation value corresponding to the simulation process parameter group meets the optimization condition or not according to the simulation value corresponding to each simulation process parameter group, and if the simulation value corresponding to the simulation process parameter group meets the optimization condition, determining the simulation process parameter group as a first optimization process parameter group, wherein the first optimization process parameter group is used for determining the process parameter values of the industrial product corresponding to the industrial product model.
Preferably, for the simulation value corresponding to each simulation process parameter set, whether the simulation value corresponding to the simulation process parameter set meets the optimization condition is determined in the following manner: inputting a plurality of simulation process parameter sets as variables into a preset optimization algorithm model for solving, and taking a solving result as a standard simulation value; and determining whether the optimization condition is met according to the simulation values corresponding to the simulation process parameter set and the standard simulation values.
Preferably, the objective function of the optimization algorithm model is formed by weighted summation of each simulation function corresponding to the simulation process parameter item, and at least one objective simulation process parameter item is determined by the following method: for each simulation process parameter item, performing sensitivity analysis on the simulation process parameter item based on a target function to determine a sensitivity value of the simulation process parameter item; and determining the simulation process parameter item with the sensitivity value larger than the preset sensitivity value as a target simulation process parameter item.
Preferably, the number of the standard simulation values is one, and the step of determining whether the optimization condition is satisfied according to the simulation values corresponding to the simulation process parameter set and the standard simulation values includes: determining whether a simulation value corresponding to the set of simulation process parameters is equal to a standard simulation value; if the simulation value corresponding to the simulation process parameter group is equal to the standard simulation value, determining that the simulation value corresponding to the simulation process parameter group meets the optimization condition; and if the simulation value corresponding to the simulation process parameter group is not equal to the standard simulation value, determining that the simulation value corresponding to the simulation process parameter group does not meet the optimization condition.
Preferably, the number of the standard simulation values is multiple, and the step of determining whether the optimization condition is satisfied according to the simulation values corresponding to the simulation process parameter set and the standard simulation values includes: determining whether a simulation value corresponding to the simulation process parameter set is one of a plurality of standard simulation values; if the simulation value corresponding to the simulation process parameter group is one of the standard simulation values, determining that the simulation value corresponding to the simulation process parameter group meets the optimization condition, otherwise determining that the simulation value corresponding to the simulation process parameter group does not meet the optimization condition.
Preferably, the method further comprises the following steps: when the simulation values of all the simulation process parameter sets do not meet the optimization conditions, determining a second optimization process parameter set in all the simulation process parameter sets, wherein the second optimization process parameter set is used for determining process parameter values of the industrial product corresponding to the industrial product model; wherein the second optimized process parameter set is determined by: determining a difference value between a simulation value and a standard simulation value of each simulation process parameter set; and determining a second optimized process parameter set according to the difference value between the simulation value of each simulation process parameter set and the standard simulation value.
Preferably, the computer aided engineering software further comprises an optimized simulation configuration interface, a simulation process parameter item control corresponding to each simulation process parameter item configured for the industrial product model by the user is displayed in the optimized simulation configuration interface, and at least one target simulation process parameter item is determined by the following method: acquiring the selection operation of a user on a target simulation process parameter item control; and determining the simulation process parameter item corresponding to the target process parameter item control as a target simulation process parameter item.
In a second aspect, the present application provides a simulation apparatus, the apparatus comprising:
the acquisition module is used for acquiring all simulation process parameter items configured by a user in the computer aided engineering software for the created industrial product model and at least one parameter value of each simulation process parameter item, and acquiring a simulation target configured by the user in the computer aided engineering software for the industrial product model;
the determining module is used for determining at least one target simulation process parameter item in all the simulation process parameter items;
the combination module is used for generating a plurality of simulation process parameter sets by permutation and combination according to all the determined target simulation process parameter items and all parameter values of each target simulation process parameter item, and each simulation process parameter value set comprises one parameter value of each target simulation process parameter item;
the simulation module is used for enabling the computer aided engineering software to simulate a simulation target by taking a simulation environment configured for an industrial product model by a user and each simulation process parameter group as simulation conditions so as to obtain a simulation value corresponding to each simulation process parameter group;
and the verification module is used for determining whether the simulation value corresponding to each simulation process parameter group meets the optimization condition or not according to the simulation value corresponding to each simulation process parameter group, and if the simulation value corresponding to each simulation process parameter group meets the optimization condition, determining the simulation process parameter group as a first optimization process parameter group, wherein the first optimization process parameter group is used for determining the process parameter values of the industrial product corresponding to the industrial product model.
In a third aspect, the present application further provides an electronic device, including: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory communicating via the bus when the electronic device is operating, the machine-readable instructions when executed by the processor performing the steps of the emulation method as described above.
In a fourth aspect, the present application also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the simulation method as described above.
According to the simulation method, the simulation device, the electronic equipment and the storage medium, all simulation process parameter items configured for the created industrial product model by a user in computer aided engineering software and at least one parameter value of each simulation process parameter item are obtained, and a simulation target configured for the industrial product model by the user in the computer aided engineering software is obtained; determining at least one target simulation process parameter item in all simulation process parameter items; generating a plurality of simulation process parameter sets by permutation and combination according to all the determined target simulation process parameter items and all parameter values of each target simulation process parameter item, wherein each simulation process parameter value set comprises one parameter value of each target simulation process parameter item; enabling computer aided engineering software to take a simulation environment configured by a user for an industrial product model and each simulation process parameter group as simulation conditions, and simulating a simulation target to obtain a simulation value corresponding to each simulation process parameter group; and determining whether the simulation value corresponding to the simulation process parameter group meets the optimization condition or not according to the simulation value corresponding to each simulation process parameter group, and if the simulation value corresponding to the simulation process parameter group meets the optimization condition, determining the simulation process parameter group as a first optimization process parameter group, wherein the first optimization process parameter group is used for determining the process parameter values of the industrial product corresponding to the industrial product model. The method can determine the optimized process parameter group while running simulation aiming at the process product, and helps technicians to determine the process parameter values of the industrial product so as to obtain the industrial product with better performance.
In order to make the aforementioned objects, features and advantages of the present application comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 is a flowchart of existing CAE software simulation provided in an embodiment of the present application;
FIG. 2 is a flowchart of a simulation method according to an embodiment of the present disclosure;
FIG. 3 is a flowchart illustrating a process for determining target simulation process parameter items according to an embodiment of the present application;
FIG. 4 is a flowchart of a step of determining whether simulated values satisfy optimization conditions according to an embodiment of the present application;
FIG. 5 is a flowchart of another step of determining whether simulated values satisfy optimization criteria as provided by an embodiment of the present application;
FIG. 6 is a flowchart illustrating the operation of a simulation application according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of a simulation apparatus according to an embodiment of the present application;
fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. The components of the embodiments of the present application, as generally described and illustrated in the figures herein, could be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. Every other embodiment that one skilled in the art can obtain without inventive effort based on the embodiments of the present application falls within the scope of protection of the present application.
First, an application scenario to which the present application is applicable will be described. The application can be applied to simulation application programs in CAE (computer aided engineering).
The main idea behind CAE technology is to "try to let more audiences be able to touch and use the simulation, thus helping it to do work efficiently". The simulation software "application programming" is a main direction for the "popularization" of CAE technology, and the "application" is referred to as "simulation APP" in the industry. "simulation APP" provides an effective method that can greatly improve productivity for less variable, tedious, repetitive tasks. It may assist in assigning the work of running a CAE, collecting results, and performing basic result evaluations to users with lower skill levels, thus potentially really broadening the scope of application of CAE and driving the popularity of CAE.
One direction in which simulation software has developed is in conjunction with optimization techniques. The application of the target CAE software has one primary purpose, namely to simulate alternative experiments. The existing simulation operation flow is as follows: and establishing a CAE model according to the real object, and then executing CAE analysis to obtain simulation data. But this only serves to verify the validity of the design. In practice, the aim of improving the production efficiency and quality is achieved by guiding or modifying the product design through CAE simulation analysis. Therefore, the combination of multidisciplinary and multi-objective design space exploration and optimization and CAE simulation software is indispensable.
Based on this, the embodiment of the application provides a simulation method, a simulation device, an electronic device and a storage medium, which are suitable for a CAE-based simulation application program. The user herein refers to a technician using the simulation application.
Referring to fig. 1, fig. 1 is a flowchart illustrating a conventional simulation process performed by CAE software according to an embodiment of the present disclosure. The existing simulation comprises the following steps:
(1) The real physical model is modeled as a geometric model by a CAD tool. Geometric parameters of the physical model are required in this step, which is data that is of interest and can be mastered by design engineers.
(2) And (4) performing mesh generation on the geometric model through a mesh generation tool to obtain a mesh file which can be processed by a CAE algorithm. Mesh generation parameters are required in this step, which is data that is not of interest to design engineers.
(3) Aiming at a model needing simulation (comprising a geometric model and a grid in the steps (1) and (2)), setting physical properties of the model, including boundary/body conditions, material properties, statistical information and the like. Wherein the material properties are of interest and controllable by the design engineer and the boundary conditions, volume conditions, statistical information, etc. are of interest to the design engineer only in the part relevant to the process.
(4) And selecting proper solving parameters, including a series of numerical method parameters such as turbulence models, discrete formats, calculation parameters and the like. Neither of these parameters is of interest to the design engineer.
(5) And (5) solving and calculating.
(6) And extracting post-processing data and writing a calculation report, wherein the post-processing data comprises cloud pictures, streamlines, statistical data and the like. Where statistical data is of interest to design engineers and really plays an important role in product design. The cloud drawings and streamlines may assist.
Aiming at parameters concerned by a product design engineer, a simulation App concept is provided, namely parameters which are related to calculation and are not concerned by the design engineer are packaged to form software with relatively single function and solidified flow.
From the above flows, the simulation App can be regarded as deep packaging for the simulation flow and software, and has the advantages of simplifying parameter input and being more user-friendly. However, the running of the simulation App is still a complete CAE simulation process, design parameters can be verified and calculated, and the product design can be guided by combining the experience of a user. Referring to fig. 2 and fig. 6, fig. 2 is a flowchart of a simulation method provided in an embodiment of the present application, and fig. 6 is a flowchart of a work flow of a simulation application provided in the embodiment of the present application, where the simulation method provided in the embodiment of the present application includes:
s101, acquiring all simulation process parameter items configured for the created industrial product model by the user in the computer aided engineering software, at least one parameter value of each simulation process parameter item, and acquiring a simulation target configured for the industrial product model by the user in the computer aided engineering software.
Before step S101, the user has already created the industrial product model and configured all the simulation process parameter items and corresponding parameter values and simulation targets of the industrial product model.
The simulation process parameter items include geometric parameters, material properties, boundary conditions, volume conditions and the like. The geometric parameters are geometric descriptions of the CAE model, including length, width, height, diameter, etc. The material property is a description of a certain unit material of the CAE model, such as density, viscosity, etc. The boundary conditions include calculating speed, temperature, etc. on the boundary. The volume condition is a volume source term, such as a heat source, etc. For example, the industrial product model may be an automobile model, and the simulation process parameter items are parameter items such as material of an automobile tire, radius of the automobile tire, and the like. The parameter value can be 317mm of the radius of the automobile tire, or a range of 280mm-350mm, or the material of the automobile tire is rubber and the thickness is 13mm. The simulation target here may be the maximum driving speed or the minimum energy consumption of the automobile, etc.
Firstly, the configured simulation process parameter items are called through a multi-objective optimization algorithm model, and a corresponding expression function between each simulation process parameter item and a simulation target is determined. The expression function here may be preset in the database. And weighting based on the expression functions corresponding to all simulation process parameter items, and then taking the weighted expression functions as the target functions of the multi-target optimization algorithm model.
S102, determining at least one target simulation process parameter item in all simulation process parameter items.
Specifically, the computer aided engineering software further comprises an optimized simulation configuration interface, a simulation process parameter item control corresponding to each simulation process parameter item configured for the industrial product model by the user is displayed in the optimized simulation configuration interface, and at least one target simulation process parameter item is determined in the following manner:
acquiring the selection operation of a user on a target simulation process parameter item control;
and determining the simulation process parameter item corresponding to the target process parameter item control as a target simulation process parameter item.
In one aspect of the present application, the target simulation process parameter item is a process parameter item specified by a user, and the user considers that the simulation target has a significant influence, or a process parameter item specified by the user as needed. The simulation process parameter item control is generated based on the process parameter items configured by the user for the current CAE model.
Referring to FIG. 3, FIG. 3 is a flowchart illustrating a process for determining target simulation process parameter items according to an embodiment of the present disclosure. In another aspect of the present application, the objective function of the optimization algorithm model is formed by weighted summation of each simulation function corresponding to a simulation process parameter item, and at least one objective simulation process parameter item may be determined by:
s1020, for each simulation process parameter item, performing sensitivity analysis on the simulation process parameter item based on the objective function to determine a sensitivity value of the simulation process parameter item.
And S1022, determining the simulation process parameter item with the sensitivity value larger than the preset sensitivity value as a target simulation process parameter item.
In the scheme, the optimization algorithm model is used for screening simulation process parameter items so as to reduce the calculation amount of optimization. The optimization algorithm model is a multi-objective optimization algorithm model.
Taking the automobile model as an example, aiming at the radius of the automobile tire as a simulation process parameter item, the multi-objective optimization algorithm analyzes the influence degree of the radius of the automobile tire on the energy consumption of the automobile through different radius values of the automobile tire and respective corresponding simulation results (namely simulation targets). And finally, determining all simulation process parameter items with larger influence degrees on the energy consumption of the automobile as target simulation process parameter items.
S103, generating a plurality of simulation process parameter sets according to all the determined target simulation process parameter items and all parameter values of each target simulation process parameter item in a permutation and combination mode, wherein each simulation process parameter value set comprises one parameter value of each target simulation process parameter item.
In practical application, the number of the target simulation process parameter items is multiple, the parameter value of each target simulation process parameter item is uncertain, and the value range of the parameter value is generally configured by a user. Therefore, the multi-objective optimization algorithm can generate a plurality of simulation process parameter sets in a sampling mode.
Illustratively, the sampling values of the first target process parameter value are arranged from large to small respectively
. The sampling values of the second target process parameter values are respectively arranged from large to small
. The sampling values of the third target process parameter value are respectively arranged from large to small
. Wherein the content of the first and second substances,
、
the maximum and minimum values for the first target process parameter value,
、
the maximum and minimum values of the second target process parameter value,
、
the third target process parameter value is a maximum value and a minimum value. The simulation process parameter sets are respectively
，
，
，
And so on for a total of 64 sets of simulation process parameters.
And S104, enabling the computer aided engineering software to simulate the simulation target by taking the simulation environment configured by the user for the industrial product model and each simulation process parameter group as simulation conditions so as to obtain a simulation value corresponding to each simulation process parameter group.
The multi-objective optimization algorithm model sequentially sends each set of simulation process parameter sets to the simulation application program for simulation, so as to obtain a simulation result corresponding to each simulation process parameter set, wherein the simulation result can be an energy consumption value, a speed value and the like.
S105, determining whether the simulation value corresponding to each simulation process parameter group meets an optimization condition or not according to the simulation value corresponding to each simulation process parameter group, and if the simulation value corresponding to each simulation process parameter group meets the optimization condition, determining the simulation process parameter group as a first optimization process parameter group, wherein the first optimization process parameter group is used for determining process parameter values of industrial products corresponding to the industrial product model.
The technician may determine the process parameter set of the process product according to the optimized process parameter set, for example, the radius value of the tire determined in the simulation experiment in which the energy consumption is the minimum as the simulation target is used as the radius value of the tire of the actual automobile product corresponding to the automobile model.
Specifically, for the simulation value corresponding to each simulation process parameter set, whether the simulation value corresponding to the simulation process parameter set meets the optimization condition is determined in the following manner:
and inputting a plurality of simulation process parameter sets as variables into a preset optimization algorithm model for solving, and taking a solving result as a standard simulation value. And determining whether the optimization condition is met according to the simulation values corresponding to the simulation process parameter set and the standard simulation values.
In the step, the multi-objective optimization algorithm calculates the maximum value or the minimum value of the simulation result as the optimal simulation target based on the objective function.
And each time the multi-objective optimization algorithm model acquires the simulation result corresponding to one group of simulation process parameter sets, judging whether the simulation value corresponding to the current group of simulation process parameter sets is a standard simulation value.
Referring to fig. 4, fig. 4 is a flowchart illustrating a step of determining whether the simulated value satisfies the optimization condition according to an embodiment of the present application. In one embodiment of the present application, the number of the standard simulation values is one, and the step of determining whether the optimization condition is satisfied according to the simulation values corresponding to the simulation process parameter set and the standard simulation values includes:
s201, determining whether a simulation value corresponding to the simulation process parameter set is equal to a standard simulation value;
s202, if the simulation value corresponding to the simulation process parameter group is equal to the standard simulation value, determining that the simulation value corresponding to the simulation process parameter group meets the optimization condition;
s203, if the simulation value corresponding to the simulation process parameter set is not equal to the standard simulation value, determining that the simulation value corresponding to the simulation process parameter set does not meet the optimization condition.
Referring to fig. 5, fig. 5 is a flowchart illustrating another step of determining whether the simulated values satisfy the optimization condition according to an embodiment of the present application. In another aspect of the present application, the number of the standard simulation values is multiple, and the step of determining whether the optimization condition is satisfied according to the simulation values corresponding to the simulation process parameter set and the standard simulation values includes:
s301, determining whether a simulation value corresponding to the simulation process parameter set is one of a plurality of standard simulation values;
s302, if the simulation value corresponding to the simulation process parameter group is one of a plurality of standard simulation values, determining that the simulation value corresponding to the simulation process parameter group meets an optimization condition;
and S303, if not, determining that the simulation value corresponding to the simulation process parameter group does not meet the optimization condition.
It is understood that, for the multi-objective optimization problem, the number of the standard simulation values is plural, and the number of the first optimization process parameter set is also plural.
The simulation method provided by the embodiment of the application can determine the optimized process parameter group while running simulation aiming at the process product, and helps technicians to determine the process parameter values of the industrial product so as to obtain the industrial product with better performance.
In an embodiment of the application, if the simulation values of the simulation process parameter items configured by the user do not obtain the standard simulation values after simulation in the value range of the simulation values of the simulation process parameter items configured by the user, the method further includes determining a second optimized process parameter set in all the simulation process parameter sets when the simulation values of all the simulation process parameter sets do not satisfy the optimization condition, where the second optimized process parameter set is used to determine process parameter values of the industrial product corresponding to the industrial product model. Wherein the second optimized process parameter set is determined by:
a difference between the simulated values and the standard simulated values for each set of simulated process parameters is determined. And determining a second optimized process parameter set according to the difference value between the simulation value of each simulation process parameter set and the standard simulation value.
Here, the simulation process parameter group corresponding to the simulation value closest to the standard simulation value is used as the current optimal simulation process parameter group.
Furthermore, the method also includes generating a statistical table according to all simulation process parameter sets and simulation values corresponding to each simulation process parameter set, where each row in the statistical table includes one simulation process parameter set and the simulation values corresponding to the simulation process parameter set.
And highlighting the simulation process parameter set determined as the first optimization process parameter set or the second optimization process parameter set and the corresponding simulation value in the statistical table.
In the statistical data stage after the simulation is finished, all simulation process parameter sets and corresponding simulation values may be displayed in a tabular form, and the optimal simulation process parameter set may be highlighted, for example, by using a display font, a font size, a color, or the like different from those of other simulation process parameter sets. To assist the technician in viewing the data.
The simulation method can be realized through a simulation application program, the optimization algorithm is used as a scheduling layer, and the simulation algorithm is used as an execution layer. The scheduling layer repeatedly calls the execution layer for multiple times, and the execution layer feeds an optimization target result (namely a partial simulation statistical result) back to the scheduling layer. The multi-objective optimization algorithm can finish the simulation operation after considering that the optimal value is obtained.
Based on the same inventive concept, the embodiment of the present application further provides a simulation apparatus corresponding to the simulation method, and since the principle of solving the problem of the apparatus in the embodiment of the present application is similar to that of the simulation method in the embodiment of the present application, the implementation of the apparatus may refer to the implementation of the method, and repeated details are not repeated.
Referring to fig. 7, fig. 7 is a schematic structural diagram of a simulation apparatus according to an embodiment of the present disclosure. As shown in fig. 7, the simulation apparatus 700 includes:
an obtaining module 710, configured to obtain all simulation process parameter items configured by a user in computer aided engineering software for a created industrial product model, and at least one parameter value of each simulation process parameter item, and obtain a simulation target configured by the user in computer aided engineering software for the industrial product model;
a determining module 720, configured to determine at least one target simulation process parameter item among all simulation process parameter items;
the combination module 730 is used for generating a plurality of simulation process parameter sets by permutation and combination according to all the determined target simulation process parameter items and all the parameter values of each target simulation process parameter item, wherein each simulation process parameter value set comprises one parameter value of each target simulation process parameter item;
the simulation module 740 is configured to enable the computer aided engineering software to simulate the simulation target by using the simulation environment configured by the user for the industrial product model and each simulation process parameter group as a simulation condition, so as to obtain a simulation value corresponding to each simulation process parameter group;
the verification module 750 is configured to determine, for the simulation value corresponding to each simulation process parameter set, whether the simulation value corresponding to the simulation process parameter set meets an optimization condition, and if the simulation value corresponding to the simulation process parameter set meets the optimization condition, determine the simulation process parameter set as a first optimization process parameter set, where the first optimization process parameter set is used to determine process parameter values of an industrial product corresponding to the industrial product model.
In a preferred embodiment, for each simulation value corresponding to each simulation process parameter set, the verification module 750 determines whether the simulation value corresponding to the simulation process parameter set satisfies the optimization condition by: inputting a plurality of simulation process parameter sets as variables into a preset optimization algorithm model for solving, and taking a solving result as a standard simulation value; and determining whether the optimization condition is met according to the simulation values corresponding to the simulation process parameter set and the standard simulation values.
In a preferred embodiment, the objective function of the optimization algorithm model is formed by weighted summation of each simulation function corresponding to the simulation process parameter item, and the determining module 720 determines at least one objective simulation process parameter item by: for each simulation process parameter item, performing sensitivity analysis on the simulation process parameter item based on a target function to determine a sensitivity value of the simulation process parameter item; and determining the simulation process parameter item with the sensitivity value larger than the preset sensitivity value as a target simulation process parameter item.
In a preferred embodiment, the number of standard simulation values is one, and the verification module 750 is specifically configured to: determining whether a simulation value corresponding to the simulation process parameter set is equal to a standard simulation value; if the simulation value corresponding to the simulation process parameter group is equal to the standard simulation value, determining that the simulation value corresponding to the simulation process parameter group meets the optimization condition; and if the simulation value corresponding to the simulation process parameter group is not equal to the standard simulation value, determining that the simulation value corresponding to the simulation process parameter group does not meet the optimization condition.
In a preferred embodiment, the number of the standard simulation values is multiple, and the verification module 750 is specifically configured to: determining whether a simulation value corresponding to the simulation process parameter set is one of a plurality of standard simulation values; if the simulation value corresponding to the simulation process parameter group is one of the standard simulation values, determining that the simulation value corresponding to the simulation process parameter group meets the optimization condition, otherwise determining that the simulation value corresponding to the simulation process parameter group does not meet the optimization condition.
In a preferred embodiment, the verification module 750 is further configured to: when the simulation values of all the simulation process parameter sets do not meet the optimization conditions, determining a second optimization process parameter set in all the simulation process parameter sets, wherein the second optimization process parameter set is used for determining process parameter values of the industrial product corresponding to the industrial product model; wherein the second optimized process parameter set is determined by: determining a difference value between the simulation value of each simulation process parameter set and the standard simulation value; and determining a second optimized process parameter set according to the difference value between the simulation value of each simulation process parameter set and the standard simulation value.
In a preferred embodiment, the computer aided engineering software further includes an optimized simulation configuration interface, a simulation process parameter item control corresponding to each simulation process parameter item configured for the industrial product model by the user is displayed in the optimized simulation configuration interface, and the determining module 720 determines at least one target simulation process parameter item by: acquiring the selection operation of a user on a target simulation process parameter item control; and determining the simulation process parameter item corresponding to the target process parameter item control as a target simulation process parameter item.
Referring to fig. 8, fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure. As shown in fig. 8, the electronic device 800 includes a processor 810, a memory 820, and a bus 830.
The memory 820 stores machine-readable instructions executable by the processor 810, when the electronic device 800 runs, the processor 810 and the memory 820 communicate through the bus 830, and when the machine-readable instructions are executed by the processor 810, the steps of the simulation method in the method embodiment shown in fig. 1 may be executed.
An embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the step of the simulation method in the method embodiment shown in fig. 1 may be executed.
It can be clearly understood by those skilled in the art that, for convenience and simplicity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. The above-described apparatus embodiments are merely illustrative, and for example, the division of the units into only one type of logical function may be implemented in other ways, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed coupling or direct coupling or communication connection between each other may be through some communication interfaces, indirect coupling or communication connection between devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solutions of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present application, and are used for illustrating the technical solutions of the present application, but not limiting the same, and the scope of the present application is not limited thereto, and although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope disclosed in the present application; such modifications, changes or substitutions do not depart from the spirit and scope of the exemplary embodiments of the present application, and are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A method of simulation, the method comprising:
acquiring all simulation process parameter items configured by a user for a created industrial product model in computer aided engineering software and at least one parameter value of each simulation process parameter item, and acquiring a simulation target configured by the user for the industrial product model in the computer aided engineering software;
determining at least one target simulation process parameter item in all simulation process parameter items;
generating a plurality of simulation process parameter sets by permutation and combination according to all the determined target simulation process parameter items and all parameter values of each target simulation process parameter item, wherein each simulation process parameter value set comprises one parameter value of each target simulation process parameter item;
enabling computer aided engineering software to take a simulation environment configured by a user for an industrial product model and each simulation process parameter group as simulation conditions, and simulating the simulation target to obtain a simulation value corresponding to each simulation process parameter group;
and determining whether the simulation value corresponding to each simulation process parameter group meets an optimization condition or not according to the simulation value corresponding to each simulation process parameter group, and if the simulation value corresponding to each simulation process parameter group meets the optimization condition, determining the simulation process parameter group as a first optimization process parameter group, wherein the first optimization process parameter group is used for determining the process parameter values of the industrial product corresponding to the industrial product model.
2. The method of claim 1, wherein for the simulation value corresponding to each simulation process parameter set, determining whether the simulation value corresponding to the simulation process parameter set satisfies the optimization condition by:
inputting a plurality of simulation process parameter sets as variables into a preset optimization algorithm model for solving, and taking a solving result as a standard simulation value;
and determining whether the optimization condition is met according to the simulation values corresponding to the simulation process parameter set and the standard simulation values.
3. The method of claim 2, wherein the objective function of the optimization algorithm model is formed by a weighted summation of each simulation function corresponding to a simulation process parameter term, and at least one objective simulation process parameter term is determined by:
for each simulation process parameter item, performing sensitivity analysis on the simulation process parameter item based on the target function to determine a sensitivity value of the simulation process parameter item;
and determining the simulation process parameter item with the sensitivity value larger than the preset sensitivity value as a target simulation process parameter item.
4. The method according to claim 3, wherein the number of the standard simulation values is one, and the step of determining whether the optimization condition is satisfied according to the simulation values corresponding to the simulation process parameter set and the standard simulation values includes:
determining whether a simulation value corresponding to the simulation process parameter set is equal to a standard simulation value;
if the simulation value corresponding to the simulation process parameter group is equal to the standard simulation value, determining that the simulation value corresponding to the simulation process parameter group meets the optimization condition;
and if the simulation value corresponding to the simulation process parameter group is not equal to the standard simulation value, determining that the simulation value corresponding to the simulation process parameter group does not meet the optimization condition.
5. The method of claim 3, wherein the number of the standard simulation values is plural, and the step of determining whether the optimization condition is satisfied according to the simulation values corresponding to the simulation process parameter set and the standard simulation values includes:
determining whether a simulation value corresponding to the simulation process parameter set is one of a plurality of standard simulation values;
if the simulation value corresponding to the simulation process parameter group is one of the standard simulation values, determining that the simulation value corresponding to the simulation process parameter group meets the optimization condition, otherwise determining that the simulation value corresponding to the simulation process parameter group does not meet the optimization condition.
6. The method of claim 4, further comprising:
when the simulation values of all the simulation process parameter sets do not meet the optimization conditions, determining a second optimization process parameter set in all the simulation process parameter sets, wherein the second optimization process parameter set is used for determining the process parameter values of the industrial product corresponding to the industrial product model;
wherein the second optimized process parameter set is determined by:
determining a difference value between a simulation value and a standard simulation value of each simulation process parameter set;
and determining a second optimized process parameter set according to the difference value between the simulation value of each simulation process parameter set and the standard simulation value.
7. The method of claim 2, wherein the computer aided engineering software further comprises an optimized simulation configuration interface, wherein a simulation process parameter item control corresponding to each simulation process parameter item configured by the user for the industrial product model is displayed in the optimized simulation configuration interface, and at least one target simulation process parameter item is determined by:
acquiring the selection operation of a user on a target simulation process parameter item control;
and determining the simulation process parameter item corresponding to the target process parameter item control as a target simulation process parameter item.
8. A simulation apparatus, characterized in that the simulation apparatus comprises:
the system comprises an acquisition module, a simulation module and a simulation module, wherein the acquisition module is used for acquiring all simulation process parameter items configured for a created industrial product model by a user in computer aided engineering software, at least one parameter value of each simulation process parameter item and a simulation target configured for the industrial product model by the user in the computer aided engineering software;
the determining module is used for determining at least one target simulation process parameter item in all the simulation process parameter items;
the combination module is used for generating a plurality of simulation process parameter sets according to all the determined target simulation process parameter items and all the parameter values of each target simulation process parameter item in a permutation and combination mode, and each simulation process parameter value set comprises one parameter value of each target simulation process parameter item;
the simulation module is used for enabling the computer aided engineering software to simulate the simulation target by taking the simulation environment configured by the user for the industrial product model and each simulation process parameter group as simulation conditions so as to obtain a simulation value corresponding to each simulation process parameter group;
and the verification module is used for determining whether the simulation values corresponding to the simulation process parameter sets meet optimization conditions or not according to the simulation values corresponding to each simulation process parameter set, and if the simulation values corresponding to the simulation process parameter sets meet the optimization conditions, determining the simulation process parameter sets as first optimization process parameter sets which are used for determining process parameter values of the industrial products corresponding to the industrial product models.
9. An electronic device, comprising: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory communicating via the bus when the electronic device is operating, the processor executing the machine-readable instructions to perform the steps of the emulation method according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, performs the steps of the simulation method according to one of the claims 1 to 7.
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