Simulation method, device and computer equipment based on atomic simulation case

Abstract

The present application relates to a simulation method, apparatus and computer equipment based on atomic simulation use cases, wherein the simulation method based on atomic simulation use cases includes: determining multiple execution units corresponding to the simulation task to be executed, and the atomic model corresponding to each execution unit, the simulation task includes simulation requirements of different types and different scenarios; determining the undirected matrix information corresponding to each atomic model; based on the undirected matrix information, searching and processing each execution unit through a graph search algorithm to obtain the simulation use case corresponding to the simulation task; based on the simulation use case, calling the corresponding execution unit to execute the simulation task. Through the present application, the problem of low configurability of simulation use cases is solved, and the configurability of simulation use cases is improved, so that simulation use cases can be quickly configured and optimized under multiple simulation types and multiple scenarios.

Description

Technical Field

[0001] The present application relates to the field of simulation technology, and in particular to a simulation method, apparatus and computer equipment based on atomic simulation use cases. Background Art

[0002] With the rapid development of artificial intelligence technology, intelligent simulation has become a frontier field of simulation, including the establishment of intelligent simulation platforms, the design of intelligent simulation languages, intelligent agent modeling, and the construction of intelligent simulation systems. In existing simulation systems, online collaborative simulation is usually performed based on product information and simulation templates, but the templated simulation process is difficult to cope with the simulation requirements of multiple simulation types and scenarios, resulting in low configurability of simulation use cases.

[0003] With regard to the problem of low configurability of simulation use cases in related technologies, no effective solution has been proposed so far. Summary of the invention

[0004] In this embodiment, a simulation method, apparatus, and computer device based on atomic simulation use cases are provided to solve the problem of low configurability of simulation use cases in related technologies.

[0005] In a first aspect, a simulation method based on an atomized simulation case is provided in this embodiment, and the method includes:

[0006] Determine a plurality of execution units corresponding to a simulation task to be executed, and an atomic model corresponding to each of the execution units; the simulation task includes simulation requirements of different types and scenarios;

[0007] Determining the undirected matrix information corresponding to each of the atomic models;

[0008] Based on the undirected matrix information, searching and processing each of the execution units is performed through a graph search algorithm to obtain a simulation case corresponding to the simulation task;

[0009] Based on the simulation use case, the corresponding execution unit is called to execute the simulation task.

[0010] In some embodiments, the determining of a plurality of execution units corresponding to the simulation task to be executed, and an atomic model corresponding to each of the execution units, comprises:

[0011] Selecting a plurality of execution units that match the simulation task to be executed;

[0012] Determining a plurality of attribute information of each of the execution units;

[0013] Based on each of the attribute information, the atomic model corresponding to the execution unit is established.

[0014] In some of the embodiments, after determining the atomic model corresponding to each of the execution units, the method further includes:

[0015] Establishing a coupling information library corresponding to each of the execution units; the coupling information library includes a coupling information matrix corresponding to each of the execution units;

[0016] The coupling information matrix includes a plurality of data flow information of the automation toolkit, and each of the data flow information is of an application class or a simulation standard interface file class.

[0017] In some of the embodiments, searching and processing each of the execution units by a graph search algorithm based on the undirected matrix information to obtain a simulation use case corresponding to the simulation task includes:

[0018] Based on the undirected matrix information, performing sorting and partitioning processing on each of the execution units;

[0019] Based on the sorting result and the partitioning result, searching and processing each of the execution units by a depth-first search algorithm to obtain multiple paths between different partitions;

[0020] A corresponding directional graph is generated according to each of the paths; information of the directional graph is the simulation use case corresponding to the simulation task.

[0021] In some embodiments, the sorting and partitioning of the execution units includes:

[0022] sorting the execution units according to the simulation level corresponding to each execution unit;

[0023] Partition processing is performed on each execution unit according to the simulation type and simulation tool corresponding to each execution unit.

[0024] In some of the embodiments, after searching and processing each of the execution units by a graph search algorithm based on the undirected matrix information to obtain a simulation case corresponding to the simulation task, the method further includes:

[0025] Acquire different versions of simulation engineering data corresponding to the simulation task, and construct a parameter identification vector corresponding to each of the simulation engineering data;

[0026] Based on the valid information in each of the parameter identification vectors, generating a decision vector corresponding to each of the parameter identification vectors;

[0027] When the distance value between each of the decision vectors does not exceed a preset threshold, the simulation process corresponding to the simulation case is simplified.

[0028] In some of the embodiments, before determining a plurality of execution units corresponding to the simulation task to be executed, the method further includes:

[0029] Obtaining the simulation task to be executed;

[0030] According to a preset task scheduling strategy, the simulation task to be executed is scheduled to the corresponding computing node; wherein the task scheduling strategy can be adjusted according to the system load size.

[0031] In a second aspect, a simulation device based on an atomic simulation case is provided in this embodiment, the device comprising: a selection module, a creation module, a search module and an execution module;

[0032] The selection module is used to determine a plurality of execution units corresponding to a simulation task to be executed, and an atomic model corresponding to each of the execution units; the simulation task includes simulation requirements of different types and scenarios;

[0033] The establishing module is used to determine the undirected matrix information corresponding to each of the atomic models;

[0034] The search module is used to search and process each of the execution units through a graph search algorithm based on the undirected matrix information to obtain a simulation case corresponding to the simulation task;

[0035] The execution module is used to call the corresponding execution unit to execute the simulation task based on the simulation use case.

[0036] In a third aspect, a computer device is provided in this embodiment, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the simulation method based on the atomic simulation use case described in the first aspect is implemented.

[0037] In a fourth aspect, a storage medium is provided in this embodiment, on which a computer program is stored, and when the program is executed by a processor, the simulation method based on the atomic simulation use case described in the first aspect above is implemented.

[0038] Compared with the related art, the simulation method, apparatus and computer equipment based on atomic simulation use cases provided in the present embodiment, by determining multiple execution units corresponding to the simulation task to be executed, and the atomic model corresponding to each execution unit, the simulation task includes simulation requirements of different types and different scenarios; determining the undirected matrix information corresponding to each atomic model; based on the undirected matrix information, searching and processing each execution unit through a graph search algorithm to obtain the simulation use case corresponding to the simulation task; based on the simulation use case, calling the corresponding execution unit to execute the simulation task, thereby solving the problem of low configurability of the simulation use case and improving the configurability of the simulation use case, so that the simulation use case can be quickly configured and optimized under multiple simulation types and multiple scenarios.

[0039] Details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0041] Figure 1 It is a hardware structure block diagram of a terminal device of a simulation method based on an atomic simulation use case provided in an embodiment of the present application;

[0042] Figure 2 is a flow chart of a simulation method based on an atomized simulation use case provided in one embodiment of the present application;

[0043] Figure 3 is a flowchart of a graph search processing process provided by an embodiment of the present application;

[0044] Figure 4 is a schematic diagram of a graph search processing process provided by an embodiment of the present application;

[0045] Figure 5 It is a flowchart of a simulation method based on an atomized simulation use case provided in a preferred embodiment of the present application;

[0046] Figure 6 It is a structural block diagram of a simulation device based on an atomic simulation use case provided in one embodiment of the present application.

[0047] In the figure: 102, processor; 104, memory; 106, transmission device; 108, input and output device; 10, selection module; 20, establishment module; 30, search module; 40, execution module. DETAILED DESCRIPTION

[0048] In order to more clearly understand the purpose, technical solutions and advantages of the present application, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments.

[0049] Unless otherwise defined, the technical terms or scientific terms involved in this application shall have the general meaning understood by people with general skills in the technical field to which this application belongs. The words "one", "a", "the", "these" and the like in this application do not indicate a quantitative limitation, and they may be singular or plural. The terms "include", "comprise", "have" and any variants thereof involved in this application are intended to cover non-exclusive inclusions; for example, a process, method and system, product or device comprising a series of steps or modules (units) is not limited to the listed steps or modules (units), but may include unlisted steps or modules (units), or may include other steps or modules (units) inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there may be three relationships, for example, "A and / or B" may mean: A exists alone, A and B exist at the same time, and B exists alone. Generally, the character " / " indicates that the objects associated with each other are in an "or" relationship. The terms "first", "second", "third", etc. in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

[0050] The method embodiment provided in this embodiment can be executed in a terminal, a computer or a similar computing device. For example, running on a terminal, Figure 1 is a hardware structure block diagram of a terminal of the simulation method based on the atomic simulation use case of this embodiment. Figure 1 As shown, the terminal may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 and a memory 104 for storing data, wherein the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA. The above terminal may also include a transmission device 106 and an input and output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is for illustration only and does not limit the structure of the above terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0051] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the simulation method based on the atomic simulation use case in the present embodiment. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, to implement the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0052] The transmission device 106 is used to receive or send data via a network. The above network includes a wireless network provided by a communication provider of the terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (Radio Frequency, referred to as RF) module, which is used to communicate with the Internet wirelessly.

[0053] In this embodiment, a simulation method based on an atomic simulation case is provided. Figure 2 is a flow chart of the simulation method based on the atomic simulation use case of this embodiment, such as Figure 2 As shown, the process includes the following steps:

[0054] Step S210, determining a plurality of execution units corresponding to a simulation task to be executed, and an atomic model corresponding to each execution unit; the simulation task includes simulation requirements of different types and scenarios;

[0055] Step S220, determining the undirected matrix information corresponding to each atomic model;

[0056] Step S230, based on the undirected matrix information, searching and processing each execution unit by using a graph search algorithm to obtain a simulation use case corresponding to the simulation task;

[0057] Step S240: Based on the simulation use case, call the corresponding execution unit to execute the simulation task.

[0058] Specifically, the simulation task elements input by the user are received through the web interface or the client interface, and the simulation task to be executed is determined according to the received simulation task elements. The simulation process in this embodiment can be implemented through the simulation platform, and supports multiple users to input simulation task information through interfaces on different user terminals at the same time. Among them, the definition of the simulation task is as follows:

[0059]

[0060] In formula (1), P represents the simulation task; S represents the simulation discipline, such as thermal, electrical, mechanical, optical and acoustic; TO represents the simulation tool, such as computer-aided engineering, computer-aided design, electronic design automation software, etc.; E represents the working condition information, that is, a specific condition or state of the actual physical system being simulated. Different simulation working conditions usually correspond to different simulation data, boundary conditions, initial conditions and other information; F represents engineering information. It should be noted that the simulation task includes simulation requirements of different types and scenarios. For example, the simulation task includes simulation requirements for different simulation disciplines and simulation requirements for different software platforms.

[0061] Furthermore, according to the preset task scheduling strategy, the simulation task to be executed is scheduled to the corresponding computing node, and multiple execution units corresponding to the simulation task to be executed are determined to obtain the task matrix set N=[N 1 ,N 2 , N 3 ,…,N i ] (i=1,2,…,k), N represents the set of all execution units of the simulation task, N i represents any execution unit; k represents the number of all execution units. The execution unit can process and calculate the input data according to specific simulation rules and algorithms to generate simulation results, that is, to generate corresponding outputs by simulating the behavior of a system or process, so as to facilitate the analysis, evaluation and optimization of the performance, reliability and effect of the system, such as logic simulation in electronic circuit design, flight simulation of aircraft, mechanical simulation of vehicles, modeling and simulation of social and economic systems, etc. Among them, the task matrix of a single execution unit is N i =[SLT TO PC SC A], S represents the identification information of the simulation discipline; L represents the identification information of the level where the execution unit is located; T represents the identification information of the simulation type; TO represents the identification information of the simulation tool; PC represents the identification information of the process category; SC represents the identification information of the process subcategory; A represents the identification information of the automation toolkit.

[0062] According to the multiple attribute information of each execution unit, the atomic model corresponding to the execution unit is established to obtain all atomic models that meet the conditions and realize the mapping between simulation requirements and execution units. The result is recorded as N′. The specific expression is as follows:

[0063]

[0064] In formula (2), S i Represents the identification information of the simulation discipline in the atomic model of the i-th execution unit; L i Indicates the identification information of the level where the row unit in the atomic model of the i-th execution unit is located; T i Identification information indicating the simulation type in the atomic model of the i-th execution unit; i Represents the identification information of the simulation tool in the atomic model of the i-th execution unit; PC i Indicates the identification information of the process category in the atomic model of the i-th execution unit; SC i Represents the identification information of the process subclass in the atomic model of the i-th execution unit; A i Represents the identification information of the automation toolkit in the atomic model of the ith execution unit; t represents the total number of execution units that meet the simulation requirements. At the same time, a coupling information library corresponding to each execution unit is established, and the coupling information library includes a coupling information matrix corresponding to each execution unit, and the coupling information matrix includes multiple data flow information of the automation toolkit, and the type of each data flow information is an application class or a simulation standard interface file class. It should be noted that after determining the simulation task to be executed according to the received simulation task elements, all execution units that meet the conditions can be obtained according to the simulation task. For example, according to the attribute information such as the simulation subject name corresponding to the simulation requirements in the simulation task, the execution units that meet the conditions are obtained.

[0065] After that, the undirected matrix information corresponding to each atomic model is determined, and based on the undirected matrix information, each execution unit is searched and processed through a graph search algorithm to obtain the simulation case corresponding to the simulation task, so as to complete the simulation case configuration, and then the corresponding execution unit can be called to execute the simulation task based on the simulation case, that is, there is no need to call all the execution units in the end, and the execution unit call is made based on the optimized simulation case configuration, which helps to improve the simulation efficiency. Among them, the graph search algorithm includes depth-first search, iterative deepening depth-first search, etc.

[0066] It should be noted that the system environment and conditions involved in the simulation use case include input data, initial state, external interference, interaction process, etc., which describe the execution steps and operation process of the simulation use case in detail, and define the operations and behaviors that the system should take during the simulation process. Since the simulation use case will determine the expected output and results after execution, such as the system's state transition, output data, performance indicators, etc., the system's performance, function, and quality can be evaluated and compared based on various indicators. In addition, the simulation use case in this embodiment can be used in different stages of system development, including verifying system design, testing system functions, evaluating performance, and optimizing system performance.

[0067] With the rapid development of artificial intelligence technology, intelligent simulation has become a frontier field of simulation, including the establishment of intelligent simulation platforms, the design of intelligent simulation languages, intelligent agent modeling, and the construction of intelligent simulation systems. In existing simulation systems, online collaborative simulation is usually performed based on product information and simulation templates, but the templated simulation process is difficult to cope with the simulation requirements of multiple simulation types and scenarios, resulting in low configurability of simulation use cases.

[0068] Compared with the prior art, the present application determines multiple execution units corresponding to the simulation task to be executed, and the atomic model corresponding to each execution unit, and the simulation task includes simulation requirements of different types and different scenarios; determines the undirected matrix information corresponding to each atomic model; based on the undirected matrix information, searches and processes each execution unit through a graph search algorithm to obtain a simulation use case corresponding to the simulation task; based on the simulation use case, calls the corresponding execution unit to execute the simulation task. Based on this, for simulation tasks that include simulation requirements of multiple types and scenarios, the corresponding execution units are atomized, that is, at the hardware simulation application level, it is proposed to use smaller granularity execution units, and the atomized execution units are processed through a graph search algorithm to obtain the corresponding simulation use cases, so that the automated simulation use cases are highly configurable, and the automated execution environment is set up quickly and efficiently, which solves the problem of low configurability of simulation use cases and improves the configurability of simulation use cases, so that simulation use cases can be quickly configured and optimized under multiple simulation types and multiple scenarios.

[0069] In some embodiments, determining a plurality of execution units corresponding to the simulation task to be executed and an atomic model corresponding to each execution unit in step S210 includes the following steps:

[0070] Step S211, selecting a plurality of execution units matching the simulation task to be executed;

[0071] Step S212, determining multiple attribute information of each execution unit;

[0072] Step S213: establishing an atomic model corresponding to the execution unit based on each attribute information.

[0073] Specifically, multiple execution units matching the simulation task to be executed are selected, and the task matrix set N of the execution units is [N 1 , N 2 , N 3 ,…,N i ] (i=1,2,…,k), N represents the set of all execution units of the simulation task, N i represents any execution unit; k represents the number of all execution units. Among them, according to the attribute information such as the simulation subject name corresponding to the simulation requirement in the simulation task, the execution unit that meets the conditions is obtained.

[0074] Furthermore, multiple attribute information of each execution unit is obtained, and an atomic model corresponding to the execution unit is established based on each attribute information. The task matrix of a single execution unit is N i =[SLT TO PC SC A], S represents the identification information of the simulation discipline; L represents the identification information of the level where the execution unit is located; T represents the identification information of the simulation type; TO represents the identification information of the simulation tool; PC represents the identification information of the process category; SC represents the identification information of the process subcategory, and the process subcategory refers to the sub-processing item under the process category. The process subcategory for different simulation business needs is different; A represents the identification information of the automation toolkit. Each execution unit is a software automation execution program of different software. This program corresponds to different business needs and is an automation solution toolkit for commercial software for secondary development. For example, the thermal pretreatment automation toolkit includes model preprocessing, material setting, boundary condition setting, meshing, etc.

[0075] Among them, the level where the execution unit is located affects the operation logic of the execution unit, and L has an update logic. The update logic is that when a new value is inserted into the level, the level value is increased by 1. The specific expression is as follows:

[0076]

[0077] In formula (3), I represents the added level value; F represents the level information with a value less than I; R represents the level information with a value greater than I; and L′ represents the new subject level set.

[0078] Through this embodiment, multiple execution units matching the simulation tasks to be executed are selected, multiple attribute information of each execution unit is determined, and based on each attribute information, an atomic model corresponding to the execution unit is established to facilitate the subsequent flexible configuration of simulation use cases, which helps to improve the configurability of the simulation use cases.

[0079] In some of the embodiments, after determining the atomic model corresponding to each execution unit, the following steps are further included:

[0080] Establishing a coupling information library corresponding to each execution unit; the coupling information library includes a coupling information matrix corresponding to each execution unit;

[0081] The coupling information matrix includes a plurality of data flow information of the automation toolkit, and the type of each data flow information is an application class or a simulation standard interface file class.

[0082] In this embodiment, the acceptance, processing, and sending protocol standards of the atomic model automation toolkit are defined. Specifically, a coupling information library corresponding to each execution unit is established, and the coupling information library describes the coupling relationship of each execution unit and is used to control the priority update of the execution unit. The coupling information library includes a coupling information matrix corresponding to each execution unit, and the expression of the coupling information matrix corresponding to each execution unit is as follows:

[0083]

[0084] In formula (4), A(I, P, O) represents the interface information of the atomic model automation toolkit; AI represents the input information of the execution unit automation toolkit; AP represents the processing information of the execution unit automation toolkit; AO represents the output information of the execution unit automation toolkit; i represents the value of the execution unit automation toolkit; and m represents the total number of execution unit automation toolkits.

[0085] Furthermore, for each data flow information of the automation toolkit, the type of each data flow information is defined as an application class or a simulation standard interface file class, that is, the types of the input information AI, the processing information AP, and the output information AO are defined as an application class or a simulation standard interface file class. The specific expression is as follows:

[0086] A(I,P,O)=[TC FC] (5)

[0087] In formula (5), TC represents the application class; FC represents the simulation standard interface file class. For example, when using the simulation standard interface file class, it is necessary to define initial condition parameters, boundary condition parameters, etc.

[0088] Through this embodiment, a coupling information library corresponding to each execution unit is established, and the coupling information library includes a coupling information matrix corresponding to each execution unit, and the coupling information matrix includes multiple data flow information of the automation toolkit. The type of each data flow information is an application class or a simulation standard interface file class, so as to improve the stability and reliability of the simulation system.

[0089] In some of the embodiments, Figure 3 As shown, in step S230, based on the undirected matrix information, each execution unit is searched and processed by a graph search algorithm to obtain a simulation case corresponding to the simulation task, including the following steps:

[0090] Step S231, sorting and partitioning each execution unit based on the undirected matrix information;

[0091] Step S232, based on the sorting result and the partitioning result, searching and processing each execution unit by a depth-first search algorithm to obtain multiple paths between different partitions;

[0092] Step S233, generating a corresponding directional graph according to each path; the information of the directional graph is a simulation use case corresponding to the simulation task.

[0093] Specifically, the undirected matrix information corresponding to each atomic model is established, where the single atomic model information is N i ′=[S i L i T i TO i PC i SC i A i ](i=1,2,…,m), for the i-th atomic model, S i Indicates the identification information of the simulation discipline; L i Indicates the identification information of the level where the execution unit is located; T i Identification information indicating the simulation type; TO i Indicates the identification information of the simulation tool; PC i Indicates the identification information of the process category; SC i Indicates the identification information of the process subclass; A i Represents the identification information of the automation toolkit.

[0094] Furthermore, if Figure 4 As shown in the figure, based on the undirected matrix information, each execution unit is sorted and partitioned, and based on the sorting results and partitioning results, each execution unit is searched through the depth first search algorithm (DFS) to obtain multiple paths between different partitions. After that, a corresponding directional graph is generated according to each path, and the information of the directional graph is the simulation use case corresponding to the simulation task.

[0095] Among them, the depth-first search algorithm is an algorithm used to traverse or search a tree or graph. The algorithm starts from the starting node and searches each branch as deeply as possible, that is, it searches every possible branch path until it cannot go deeper. Each node can only be visited once, and the result of each depth-first search must be a connected component of the graph.

[0096] It can be understood that the simulation process usually includes seven main process information of the execution unit, namely task input, preprocessing, solution processing, post-processing, report processing, design constraints and driver design. The partition path in this embodiment corresponds to the simulation process.

[0097] Through this embodiment, each execution unit is sorted and partitioned based on the undirected matrix information, and based on the sorting results and the partitioning results, each execution unit is searched through a depth-first search algorithm to obtain multiple paths between different partitions, and a corresponding directional graph is generated according to each path, so that the directional graph information can be obtained, and the simulation use case configuration can be realized quickly and efficiently.

[0098] In some embodiments, the sorting and partitioning of the execution units in step S231 includes the following steps:

[0099] According to the simulation level corresponding to each execution unit, each execution unit is sorted;

[0100] Each execution unit is partitioned according to the simulation type and simulation tool corresponding to each execution unit.

[0101] Specifically, before executing the graph search, the simulation level corresponding to each execution unit is obtained, that is, the level value of the simulation discipline where the execution unit is located. The level where the execution unit is located affects the running logic of the execution unit, so according to the simulation level corresponding to each execution unit, each execution unit is sorted and processed to obtain the corresponding sorting result. At the same time, the simulation type and simulation tool corresponding to each execution unit are obtained, and each execution unit is partitioned according to the simulation type and simulation tool corresponding to each execution unit, wherein the simulation tools include computer-aided engineering software, computer-aided design software, electronic design automation software, etc.

[0102] It can be understood that the simulation process usually contains seven main process information of the execution unit, namely user requirements, preprocessing, solution processing, post-processing, report processing, design constraints and driver design. The simulation types and simulation tools of different execution units are different. The partitioning results based on the simulation type and simulation tool can correspond to the simulation process.

[0103] Through this embodiment, each execution unit is sorted according to the simulation level corresponding to each execution unit, and each execution unit is partitioned according to the simulation type and simulation tool corresponding to each execution unit, which helps to improve the accuracy of subsequent graph search, thereby ensuring the intelligent generation of simulation use cases.

[0104] In some of the embodiments, after searching and processing each execution unit by a graph search algorithm based on the undirected matrix information to obtain a simulation case corresponding to the simulation task, the following steps are also included:

[0105] Acquire different versions of simulation engineering data corresponding to the simulation task, and construct a parameter identification vector corresponding to each simulation engineering data;

[0106] Based on the valid information in each parameter identification vector, a decision vector corresponding to each parameter identification vector is generated;

[0107] When the distance values ​​between the decision vectors do not exceed a preset threshold, the simulation process corresponding to the simulation case is simplified.

[0108] Specifically, different versions of simulation engineering data corresponding to the simulation task are obtained, and for each version of the simulation engineering data, a corresponding parameter identification vector is constructed. The vector contains simulation data structure information, material information, simulation component model information, initial conditions and boundary conditions information, etc. The specific expression is as follows:

[0109]

[0110] In formula (6), P represents the simulation data structure and material information of a single structure, x, y, and z are specific coordinates, mp represents the material property vector at the coordinate (x, y, z), m represents the total number of single structure parameter identification vectors; Mm represents the simulation component model; I represents the initial condition; E i represents the external input signal received at the beginning of the simulation; B represents the boundary condition; C represents the interaction rules between the system and the external environment; E b Represents the external input signal received during the simulation process; A represents the total parameter identification vector of the simulation engineering data; n is the total number of parameter identification vectors in the simulation engineering data.

[0111] Furthermore, according to the characteristic parameters of the simulation component model parameters, initial parameters, and boundary parameter settings, effective information in each parameter identification vector is extracted, and information screening is performed on each parameter identification vector to generate a new decision vector correspondingly, and the distance value between each decision vector is calculated. The distance calculation method includes but is not limited to Euclidean distance and Manhattan distance. The calculated distance value is compared with the preset threshold to evaluate the degree of vector difference between different versions. If the distance value between the decision vectors does not exceed the preset threshold, it indicates that the simulation process corresponding to the simulation case can be simplified to reduce the steps of the simulation execution unit and improve the simulation efficiency.

[0112] Exemplarily, the above-mentioned vector construction method is adopted to construct parameter identification vector A and parameter identification vector B for two different versions of simulation engineering data, respectively. According to the characteristic parameters set by the simulation component model parameters, initial parameters, and boundary parameters, effective information of vectors A and B is further extracted, and the initial vectors A and B are screened to generate new decision vectors a and b, respectively, and the standardized Euclidean distance between the decision vectors a and b is calculated. The specific calculation formula is as follows:

[0113]

[0114] In formula (7), x ai ,y ai and z ai is the parameter quantity in the decision vector a; x bi ,y bi and z bi is the parameter value in the decision vector b; D represents the distance value between the decision vectors a and b, which is used to judge the change of data information.

[0115] Through this embodiment, different versions of simulation engineering data corresponding to the simulation task are obtained, a parameter identification vector corresponding to each simulation engineering data is constructed, and a decision vector corresponding to each parameter identification vector is generated based on the valid information in each parameter identification vector. When the distance value between each decision vector does not exceed a preset threshold, the simulation process corresponding to the simulation use case is simplified, thereby reducing the steps of the simulation execution unit and improving the simulation efficiency.

[0116] In some of the embodiments, before determining a plurality of execution units corresponding to the simulation task to be executed, the following steps are also included:

[0117] Get the simulation task to be executed;

[0118] According to the preset task scheduling strategy, the simulation tasks to be executed are scheduled to the corresponding computing nodes; wherein the task scheduling strategy can be adjusted according to the system load size.

[0119] In this embodiment, the task scheduling strategy TS=[SL RU JL TP QW] is preset, where SL represents the system load, RU represents the resource utilization, JL represents the job queue length or waiting time, TP represents the priority, and QW represents the queue weight or quota. The scheduling strategy condition TS matrix can be customized to add new scheduling strategy dimensions, and set corresponding thresholds for each scheduling strategy dimension to implement task scheduling strategies for various complex scenarios. In addition, the task scheduling strategy can be adjusted according to the system load size. When the system load is higher or lower than the threshold corresponding to the task scheduling strategy, the task scheduling strategy can be triggered to adjust.

[0120] Specifically, obtain the simulation task to be executed, and schedule the simulation task to be executed to the corresponding computing node according to the preset task scheduling strategy. After the simulation task is scheduled to the corresponding computing node, the corresponding simulation execution unit can be called to execute the simulation task based on the mapping between the simulation requirements and the execution unit.

[0121] Through this embodiment, the simulation tasks to be executed are obtained, and according to the preset task scheduling strategy, the simulation tasks to be executed are scheduled to the corresponding computing nodes, wherein the task scheduling strategy can be adjusted according to the system load size, so that the task scheduling strategy can be optimized in time to improve the subsequent operation efficiency.

[0122] The present embodiment is described and illustrated below through preferred embodiments.

[0123] Figure 5 is a flow chart of a simulation method based on an atomized simulation use case of this preferred embodiment, such as Figure 5 As shown, the simulation method based on the atomic simulation use case includes the following steps:

[0124] Step S510, selecting a plurality of execution units matching the simulation task to be executed; the simulation task includes simulation requirements of different types and scenarios;

[0125] Step S520, determining multiple attribute information of each execution unit, and establishing an atomic model corresponding to the execution unit based on each attribute information;

[0126] Step S530, determining the undirected matrix information corresponding to each atomic model, and performing sorting and partitioning processing on each execution unit based on the undirected matrix information;

[0127] Step S540, based on the sorting result and the partitioning result, searching each execution unit by a depth-first search algorithm to obtain multiple paths between different partitions;

[0128] Step S550, generating a corresponding directional graph according to each path; the information of the directional graph is a simulation use case corresponding to the simulation task;

[0129] Step S560: Based on the simulation use case, call the corresponding execution unit to execute the simulation task.

[0130] Through this embodiment, multiple execution units matching the simulation task to be executed are selected, and the simulation task includes simulation requirements of different types and different scenarios; multiple attribute information of each execution unit is determined, and an atomic model corresponding to the execution unit is established based on each attribute information. Further, the undirected matrix information corresponding to each atomic model is determined, and each execution unit is sorted and partitioned based on the undirected matrix information, and each execution unit is searched and processed by a depth-first search algorithm based on the sorting result and the partitioning result, and multiple paths between different partitions are obtained, so that a corresponding directional graph can be generated according to each path. The information of the directional graph is a simulation use case corresponding to the simulation task, and the corresponding execution unit is called based on the simulation use case to execute the simulation task, which solves the problem of low configurability of the simulation use case, and improves the configurability of the simulation use case, and can quickly configure and optimize the simulation use case under multiple simulation types and multiple scenarios.

[0131] It should be noted that the steps shown in the above process or the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0132] In this embodiment, a simulation device based on an atomic simulation use case is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and will not be repeated hereafter. The terms "module", "unit", "sub-unit", etc. used below may implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation in hardware, or a combination of software and hardware, is also possible and conceivable.

[0133] Figure 6 is a structural block diagram of a simulation device based on an atomized simulation use case of this embodiment, such as Figure 6 As shown, the device includes: a selection module 10, a creation module 20, a search module 30 and an execution module 40;

[0134] The selection module 10 is used to determine a plurality of execution units corresponding to the simulation task to be executed, and an atomic model corresponding to each execution unit; the simulation task includes simulation requirements of different types and different scenarios;

[0135] Establishing module 20, for determining the undirected matrix information corresponding to each atomic model;

[0136] A search module 30 is used to search and process each execution unit through a graph search algorithm based on the undirected matrix information to obtain a simulation case corresponding to the simulation task;

[0137] The execution module 40 is used to call the corresponding execution unit to execute the simulation task based on the simulation use case.

[0138] Through the device provided in this embodiment, multiple execution units corresponding to the simulation task to be executed and the atomic model corresponding to each execution unit are determined, and the simulation task includes simulation requirements of different types and different scenarios; the undirected matrix information corresponding to each atomic model is determined; based on the undirected matrix information, each execution unit is searched and processed by a graph search algorithm to obtain a simulation use case corresponding to the simulation task; based on the simulation use case, the corresponding execution unit is called to execute the simulation task, which solves the problem of low configurability of the simulation use case and improves the configurability of the simulation use case, so that the simulation use case can be quickly configured and optimized under multiple simulation types and multiple scenarios.

[0139] In some of the embodiments, the selection module 10 is further used to select multiple execution units that match the simulation task to be executed; determine multiple attribute information of each execution unit; and establish an atomic model corresponding to the execution unit based on each attribute information.

[0140] In some of these embodiments, Figure 6 On the basis of, the device also includes a definition module for establishing a coupling information library corresponding to each execution unit; the coupling information library includes a coupling information matrix corresponding to each execution unit; wherein the coupling information matrix includes multiple data flow information of the automation toolkit, and the type of each data flow information is an application class or a simulation standard interface file class.

[0141] In some of the embodiments, the search module 30 is also used to sort and partition each execution unit based on the undirected matrix information; based on the sorting results and the partitioning results, each execution unit is searched by a depth-first search algorithm to obtain multiple paths between different partitions; a corresponding directional graph is generated according to each path; the information of the directional graph is a simulation use case corresponding to the simulation task.

[0142] In some of the embodiments, the search module 30 is further used to sort the execution units according to the simulation level corresponding to each execution unit; and to partition the execution units according to the simulation type and simulation tool corresponding to each execution unit.

[0143] In some of these embodiments, Figure 6 On the basis of, the device also includes a simplification module, which is used to obtain different versions of simulation engineering data corresponding to the simulation task, and construct a parameter identification vector corresponding to each simulation engineering data; based on the valid information in each parameter identification vector, a decision vector corresponding to each parameter identification vector is generated; when the distance value between each decision vector does not exceed a preset threshold, the simulation process corresponding to the simulation use case is simplified.

[0144] In some of these embodiments, Figure 6 On the basis of, the device also includes a scheduling module, which is used to obtain the simulation tasks to be executed; according to the preset task scheduling strategy, the simulation tasks to be executed are scheduled to the corresponding computing nodes; wherein the task scheduling strategy can be adjusted according to the system load size.

[0145] It should be noted that the above modules can be functional modules or program modules, and can be implemented by software or hardware. For modules implemented by hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0146] In this embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0147] Optionally, the computer device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0148] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0149] S1, determining multiple execution units corresponding to the simulation task to be executed, and the atomic model corresponding to each execution unit; the simulation task includes simulation requirements of different types and different scenarios;

[0150] S2, determining the undirected matrix information corresponding to each atomic model;

[0151] S3, based on the undirected matrix information, each execution unit is searched and processed by a graph search algorithm to obtain a simulation case corresponding to the simulation task;

[0152] S4, based on the simulation use case, calls the corresponding execution unit to execute the simulation task.

[0153] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementation modes, and will not be repeated in this embodiment.

[0154] In addition, in combination with the simulation method based on atomic simulation use cases provided in the above embodiments, a storage medium may also be provided in this embodiment to implement the method. The storage medium stores a computer program; when the computer program is executed by a processor, the simulation method based on atomic simulation use cases in any of the above embodiments is implemented.

[0155] It should be understood that the specific embodiments described herein are only used to explain the application, rather than to limit it. Based on the embodiments provided in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the protection scope of this application.

[0156] Obviously, the drawings are only some examples or embodiments of the present application. For ordinary technicians in the field, the present application can also be applied to other similar situations based on these drawings without creative work. In addition, it is understandable that although the work done in this development process may be complicated and lengthy, for ordinary technicians in the field, certain changes in design, manufacturing or production based on the technical content disclosed in this application are only conventional technical means and should not be regarded as insufficient content disclosed in this application.

[0157] The term "embodiment" in this application refers to a specific feature, structure or characteristic described in conjunction with the embodiment that can be included in at least one embodiment of the present application. The appearance of this phrase in various locations in the specification does not necessarily mean the same embodiment, nor does it mean that it is mutually exclusive with other embodiments and is independent or optional. It is clearly or implicitly understood by those of ordinary skill in the art that the embodiments described in this application can be combined with other embodiments without conflict.

[0158] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of patent protection. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the scope of protection of the present application. Therefore, the scope of protection of the present application shall be subject to the attached claims.

Claims

1. A simulation method based on atomic simulation use cases, characterized in that: The method comprises: Determine a plurality of execution units corresponding to a simulation task to be executed, and an atomic model corresponding to each of the execution units; the simulation task includes simulation requirements of different types and scenarios; The step of determining a plurality of execution units corresponding to the simulation task to be executed, and an atomic model corresponding to each of the execution units, comprises: selecting a plurality of the execution units matching the simulation task to be executed; determining a plurality of attribute information of each of the execution units; and establishing the atomic model corresponding to the execution unit based on each of the attribute information; Determining the undirected matrix information corresponding to each of the atomic models; Based on the undirected matrix information, searching and processing each of the execution units is performed through a graph search algorithm to obtain a simulation case corresponding to the simulation task; Wherein, based on the undirected matrix information, each of the execution units is searched and processed by a graph search algorithm to obtain a simulation use case corresponding to the simulation task, including: based on the undirected matrix information, each of the execution units is sorted and partitioned; based on the sorting result and the partitioning result, each of the execution units is searched and processed by a depth-first search algorithm to obtain multiple paths between different partitions; a corresponding directional graph is generated according to each of the paths; the information of the directional graph is the simulation use case corresponding to the simulation task; Based on the simulation use case, the corresponding execution unit is called to execute the simulation task.

2. The simulation method based on atomic simulation use case according to claim 1, characterized in that: After determining the atomic model corresponding to each of the execution units, the method further includes: Establishing a coupling information library corresponding to each of the execution units; the coupling information library includes a coupling information matrix corresponding to each of the execution units; The coupling information matrix includes a plurality of data flow information of the automation toolkit, and each of the data flow information is of an application class or a simulation standard interface file class.

3. The simulation method based on atomic simulation use case according to claim 1, characterized in that: The sorting and partitioning of the execution units includes: sorting the execution units according to the simulation level corresponding to each execution unit; Partition processing is performed on each execution unit according to the simulation type and simulation tool corresponding to each execution unit.

4. The simulation method based on atomic simulation use case according to claim 1, characterized in that: After searching and processing each of the execution units by a graph search algorithm based on the undirected matrix information to obtain a simulation case corresponding to the simulation task, the method further includes: Acquire different versions of simulation engineering data corresponding to the simulation task, and construct a parameter identification vector corresponding to each of the simulation engineering data; Based on the valid information in each of the parameter identification vectors, generating a decision vector corresponding to each of the parameter identification vectors; When the distance value between each of the decision vectors does not exceed a preset threshold, the simulation process corresponding to the simulation case is simplified.

5. The simulation method based on atomic simulation use case according to claim 1, characterized in that: Before determining a plurality of execution units corresponding to the simulation task to be executed, the method further includes: Obtaining the simulation task to be executed; According to a preset task scheduling strategy, the simulation task to be executed is scheduled to the corresponding computing node; wherein the task scheduling strategy can be adjusted according to the system load size.

6. A simulation device based on atomic simulation use cases, characterized in that: The device comprises: a selection module, a creation module, a search module and an execution module; The selection module is used to determine a plurality of execution units corresponding to a simulation task to be executed, and an atomic model corresponding to each of the execution units; the simulation task includes simulation requirements of different types and scenarios; The selection module is further used to select a plurality of execution units that match the simulation task to be executed; determine a plurality of attribute information of each execution unit; and establish the atomic model corresponding to the execution unit based on each attribute information; The establishing module is used to determine the undirected matrix information corresponding to each of the atomic models; The search module is used to search and process each of the execution units through a graph search algorithm based on the undirected matrix information to obtain a simulation case corresponding to the simulation task; The search module is further used to sort and partition each of the execution units based on the undirected matrix information; based on the sorting results and the partitioning results, search each of the execution units through a depth-first search algorithm to obtain multiple paths between different partitions; generate a corresponding directional graph according to each of the paths; the information of the directional graph is the simulation use case corresponding to the simulation task; The execution module is used to call the corresponding execution unit to execute the simulation task based on the simulation use case.

7. A computer device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps of the simulation method based on the atomic simulation use case described in any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the simulation method based on atomic simulation use cases described in any one of claims 1 to 5 are implemented.

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