Simulation system and method

Abstract

The application provides a simulation system and method, wherein the system comprises: a simulation knowledge base module configured to construct a corresponding retrieval enhancement generated knowledge base based on at least one knowledge source; an agent module configured to obtain a simulation requirement, retrieve corresponding candidate knowledge from the retrieval enhancement generated knowledge base based on the simulation requirement, and generate a corresponding executable script; and a simulation interface module configured to call a target simulation software to execute the executable script and obtain a corresponding simulation result. Thus, the technical problems of low simulation precision or accuracy and low simulation efficiency in the prior art can be solved.

Description

Technical Field

[0001] This application relates to the field of computer technology, specifically to a simulation system and method. Background Technology

[0002] With the rapid development of computer technology, Computer-Aided Engineering (CAE) has become an indispensable part of modern industrial product development, widely used in fields such as machinery manufacturing, aerospace, automotive manufacturing, electronics, and energy equipment. Despite the increasingly powerful capabilities of CAE, it still faces a series of severe application challenges and bottlenecks in the simulation field. For example, current technologies still heavily rely on expert experience and manual operation. A complete simulation process involves many procedures and steps, such as geometry cleanup, mesh generation, material property definition, load and boundary condition setting, solution calculation, and post-processing result analysis, involving numerous complex decisions and operations. These decisions and operations are highly dependent on the individual experience and technical skill of the simulation engineer. Different simulation engineers facing the same simulation problem may produce vastly different simulation results due to differences in settings, making it difficult to guarantee the accuracy or precision of the simulation. Furthermore, the low efficiency of manual operation is a major source of simulation errors.

[0003] Therefore, there is an urgent need to propose a better simulation scheme. Summary of the Invention

[0004] In view of this, the embodiments of this application aim to provide a simulation system and method that can solve the technical problems of low simulation accuracy or precision and low simulation efficiency in the prior art.

[0005] Firstly, this application provides a simulation system, including: The simulation knowledge base module is used to construct a corresponding retrieval-enhanced knowledge base based on at least one knowledge source, wherein the retrieval-enhanced knowledge base includes at least one knowledge source. The intelligent agent module is used to acquire simulation requirements, retrieve corresponding candidate knowledge from the retrieval enhancement generation knowledge base based on the simulation requirements, and generate corresponding executable scripts. The executable scripts include at least the simulation requirements and the candidate knowledge. The simulation interface module is used to call the target simulation software to execute the executable script and obtain the corresponding simulation results. The target simulation software is one of the multiple simulation software programs that the simulation interface module interfaces with.

[0006] In some embodiments, the simulation interface module encapsulates multiple protocol interfaces. The simulation interface module is used to call the target simulation software to execute the executable script through the target protocol interface, and to monitor the execution status of the executable script. The target protocol interface and the target simulation software correspond one-to-one, and the execution state includes at least one of the following: waiting state, running state, interrupted state, and terminated state.

[0007] In some embodiments, the system further includes a simulation interaction module, wherein: The simulation interaction module is used to input multimodal requirement information corresponding to the simulation requirement in a preset interactive interface; The intelligent agent module is used to perform multimodal analysis on the multimodal requirement information to obtain the simulation requirements.

[0008] In some embodiments, The intelligent agent module is also used to receive the simulation results sent by the simulation interface module, and generate a corresponding simulation report based on the simulation results; The simulation interaction module is also used to display the simulation report in the preset interactive interface.

[0009] In some embodiments, the agent module is used for: The simulation results are analyzed to obtain the corresponding key information; The preset report module is invoked to generate a report on the key information, thus obtaining the simulation report.

[0010] In some embodiments, The simulation interaction module is also used to display the simulation results in the preset interactive interface.

[0011] In some embodiments, the multimodal requirement information includes at least one of text, image, voice, video, and captions.

[0012] In some embodiments, the simulation requirements include at least one of simulation problem analysis, simulation guidance, and simulation process execution.

[0013] In some embodiments, the retrieval enhancement knowledge base includes at least one of the following: a simulation problem library, an operation manual library, a simulation case library, a simulation specification library, and a simulation standard library.

[0014] Secondly, this application provides a simulation method applied to a simulation system, the simulation system including a simulation knowledge base module, an intelligent agent module, and a simulation interface module, the method comprising: The simulation knowledge base module constructs a corresponding retrieval-enhanced knowledge base based on at least one knowledge source, and the retrieval-enhanced knowledge base includes at least one knowledge source. The simulation requirements are obtained through the intelligent agent module, and corresponding candidate knowledge is retrieved from the retrieval enhancement generation knowledge base based on the simulation requirements. A corresponding executable script is generated, and the executable script includes at least the simulation requirements and the candidate knowledge. The target simulation software is called by the simulation interface module to execute the executable script and obtain the corresponding simulation results. The target simulation software is one of at least one simulation software that the simulation interface module interfaces with.

[0015] For any content not introduced or described in the embodiments of this application, please refer to the relevant descriptions in the foregoing system embodiments; they will not be repeated here.

[0016] Thirdly, this application provides a computer device that includes all or part of the simulation system provided in the first aspect above.

[0017] Fourthly, this application provides a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, implement the steps of the above-described simulation method.

[0018] The technical solution provided in this application embodiment can include the following beneficial effects: This application provides a simulation system comprising: a simulation knowledge base module for constructing a corresponding retrieval-enhanced generation knowledge base based on at least one knowledge source, the retrieval-enhanced generation knowledge base including at least one knowledge; an intelligent agent module for acquiring simulation requirements, retrieving corresponding candidate knowledge from the retrieval-enhanced generation knowledge base based on the simulation requirements, and generating a corresponding executable script, the executable script including at least the simulation requirements and the candidate knowledge; and a simulation interface module for calling a target simulation software to execute the executable script and obtain corresponding simulation results, the target simulation software being one of multiple simulation software interfaces connected to the simulation interface module. This allows for an automated simulation process, eliminating reliance on human experience and manual operation, thus improving the efficiency and convenience of simulation. It also solves the technical problems of low simulation accuracy or precision and low simulation efficiency in the prior art.

[0019] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0020] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings.

[0021] Figure 1 This is a schematic diagram of the structure of a simulation system provided in an embodiment of this application.

[0022] Figure 2 This is a schematic diagram of another simulation system provided in an embodiment of this application.

[0023] Figure 3 This is a functional schematic diagram of a simulation system provided in an embodiment of this application.

[0024] Figure 4 This is a flowchart illustrating a simulation method provided in an embodiment of this application.

[0025] Figure 5 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0026] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0027] Unless otherwise defined, the technical or scientific terms used in the embodiments of this specification shall have the ordinary meaning understood by one of ordinary skill in the art to which this specification pertains. The terms "first," "second," and similar terms used in the embodiments of this specification do not indicate any order, quantity, or importance, but are merely used to avoid confusion of constituent elements.

[0028] Unless the context otherwise requires, throughout this specification, "a plurality of" means "at least two," and "including" is interpreted as open-ended or encompassing, that is, "including, but not limited to." In the description of this specification, terms such as "one embodiment," "some embodiments," "exemplary embodiment," "example," "specific example," or "some examples" are intended to indicate that a particular feature, structure, material, or characteristic associated with that embodiment or example is included in at least one embodiment or example of this specification. The illustrative representations of the above terms do not necessarily refer to the same embodiment or example.

[0029] Exemplary embodiments of the present application will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this application will be thorough and complete, and will fully convey the scope of the present application to those skilled in the art.

[0030] In the process of submitting this application, the applicant also discovered that existing simulation knowledge bases face difficulties in knowledge accumulation and reuse. Specifically, much knowledge is scattered in the minds of simulation engineers, project reports, fragmented documents, or hidden databases, making it impossible to achieve systematic, structured, and digital effective knowledge management. This results in the inability to retrieve, access, and pass on this knowledge, hindering the transformation of corporate knowledge assets into core competitiveness. Existing simulation software is complex to operate and has a low degree of automation. For example, while mainstream commercial simulation software (such as ANSYS, Abaqus, and HyperWorks) offers powerful functions, its complex interface and steep learning curve make the threshold for simulation automation and process streamlining high, resulting in low levels of automation application. To address the above problems, this application proposes a simulation system and method.

[0031] Please see Figure 1 This is a schematic diagram of the structure of a simulation system provided in an embodiment of this application. For example... Figure 1 The simulation system 10 shown may include: a simulation knowledge base module 101, an agent module 102, and a simulation interface module 103. These modules support pairwise communication according to actual needs. For example, the simulation knowledge base module 101 and the agent module 102 support mutual communication or data transmission, and the agent module 102 and the simulation interface module 103 support mutual communication or data transmission.

[0032] The aforementioned simulation knowledge base module 101 is used to construct a corresponding retrieval-enhanced knowledge base based on at least one knowledge source, wherein the retrieval-enhanced knowledge base includes at least one knowledge source. The aforementioned intelligent agent module 102 is used to acquire simulation requirements, retrieve corresponding candidate knowledge from the retrieval enhancement generation knowledge base based on the simulation requirements, and generate a corresponding executable script, wherein the executable script includes at least the simulation requirements and the candidate knowledge; The simulation interface module 103 is used to call the target simulation software to execute the executable script and obtain the corresponding simulation results. The target simulation software is one of the multiple simulation software programs that the simulation interface module interfaces with.

[0033] The aforementioned simulation knowledge base module 101 can construct a dedicated, continuously updated Retrieval-augmented Generation (RAG) knowledge base based on at least one knowledge source, providing knowledge support for subsequent simulation systems. These knowledge sources include, but are not limited to, official Application Programming Interface (API) documentation and command manuals of mainstream commercial simulation software (such as ANSYS, Abaqus, HyperWorks, etc.); internally developed simulation standards and specifications (such as mesh quality standards and material library standards); validated typical failure case libraries and their solutions; best practice guidelines and simulation report templates; or other custom knowledge sources, for which this application does not impose further limitations. The aforementioned RAG knowledge base can include one or more pieces of knowledge, which can be organized and managed using techniques such as vectorization to facilitate efficient retrieval and accurate referencing by the subsequent intelligent agent module 102. The aforementioned RAG knowledge base can be categorized into any combination of one or more of the following knowledge bases: for example, simulation problem libraries, operation manual libraries, simulation case libraries, simulation specification libraries, simulation standard libraries, or other custom-type knowledge bases. The aforementioned simulation problem library mainly includes, but is not limited to, the causes and solutions for problems encountered during the implementation of various simulation software and simulation types. The aforementioned operation manual library mainly includes, but is not limited to, official guidance manuals for various simulation software. The aforementioned simulation case library mainly includes, but is not limited to, typical cases for different simulation types using various simulation software. The aforementioned simulation standard library mainly includes, but is not limited to, enterprise standards, industry standards, and national standards for different work types. The aforementioned simulation specification library mainly includes, but is not limited to, operational specifications and implementation steps for various simulation types within an enterprise.

[0034] The aforementioned intelligent agent module 102, also known as the large-model intelligent agent module, is a dedicated intelligent agent developed based on a large model. This large model is pre-defined by the system according to actual needs and can include, but is not limited to, convolutional neural network models, radial neural network models, deep learning models, or other machine learning models. It possesses two core capabilities: first, multimodal requirement parsing capability; and second, knowledge-enhanced script generation capability. In specific implementation, the intelligent agent module 102 utilizes the large model to parse and obtain the aforementioned simulation requirements. For example, it can parse the simulation requirements from user-submitted natural language text or uploaded specification documents and propose corresponding key parameters, such as simulation analysis type, materials, loads, boundary conditions, and target results. Further, based on the aforementioned simulation requirements, it retrieves and infers corresponding candidate knowledge from the aforementioned retrieval-enhanced knowledge base, and then generates corresponding executable scripts based on these candidate knowledge. For example, it combines retrieved API commands, parameter settings, process steps, and other knowledge into syntactically correct and logically complete executable scripts through code generation capabilities. This application does not limit the language format of the above-mentioned executable scripts, and each script corresponds to a specific simulation software. For example, the scripts may include, but are not limited to, Python, Tcl, JavaScript, or other custom language formats.

[0035] Please combine them together Figure 2 This is a schematic diagram of another simulation system provided in an embodiment of this application. For example... Figure 2 The simulation system shown may include Figure 1 The system shown may further include a simulation interaction module 104. This simulation interaction module 104 can provide a preset user interface (hereinafter referred to as the preset interface), where the user can input multimodal requirement information, such as a requirement description or specification document submitted in natural language. This application does not limit the specific form of the multimodal requirement information; it may include, but is not limited to, any combination of the following: text / document, image / picture, voice / audio, video, subtitles, or other custom forms. Furthermore, the simulation interaction module 104 can transmit the multimodal requirement information to the intelligent agent module 102. Correspondingly, the intelligent agent module 102 can perform multimodal requirement parsing on the multimodal information to derive the simulation requirements.

[0036] This application does not limit the classification / type of the above-mentioned simulation requirements. For example, they may include, but are not limited to, any combination of one or more of the following: simulation problem analysis, simulation guidance, simulation process execution, or other custom simulation requirements. The simulation problem analysis mentioned above can refer to problems encountered by the user during simulation analysis using the corresponding simulation software. The user can send the problem content to the intelligent agent module 102 through the corresponding simulation software for intelligent problem analysis and feedback of solutions. The simulation guidance mentioned above, also known as simulation method guidance, can refer to the user querying the specific methods of simulation operations through the intelligent agent module 102 during simulation analysis to guide subsequent simulation processes. The simulation process execution mentioned above, also known as simulation process automation, can refer to the user sending the simulation content requirements to the intelligent agent module 102 during simulation analysis. The intelligent agent module 102 generates corresponding scripts according to the simulation content requirements, directly driving the corresponding simulation software to generate simulation process steps and results. This application does not impose further limitations or details on this aspect.

[0037] The aforementioned simulation interface module 103, also known as the simulation software interface module, is primarily responsible for developing or providing a unified interface adapter library to interface with various simulation software. This interface adapter library may include one or more protocol interfaces, such as ANSYS's PyAnsys interface, Abaqus' Python interface, HyperWorks' Tcl / Tk interface, etc., with each protocol interface capable of interfaceing with one type of simulation software. The simulation interface module 103 can receive the executable script sent by the intelligent agent module 102, and execute the executable script by calling / driving the corresponding simulation software (e.g., the target simulation software corresponding to the target protocol interface) through the corresponding protocol interface. Simultaneously, it monitors the execution status of the executable script and obtains the final simulation results. The execution status can refer to the state describing the executable script during execution or operation, and may include, but is not limited to, any combination of one or more of the following states: such as waiting state, running state, interrupted state, and terminated state. This application does not further limit or elaborate on these states. Please refer to... Figure 3 This is a functional schematic diagram of a simulation system provided in an embodiment of this application. For example... Figure 3 In this application, the above-mentioned protocol interface is further divided into a script execution interface and a simulation software function interface. The target simulation software makes function calls to the intelligent agent module 102 through the simulation software function interface, and receives and executes the executable scripts generated by the intelligent agent module 102 through the script execution interface. This application will not make any further limitations or details in this regard.

[0038] The following describes some optional embodiments related to this application.

[0039] In some optional embodiments, the simulation interface module 103 can send the simulation results to the intelligent agent module 102. Correspondingly, after receiving the simulation results, the intelligent agent module 102 can generate a corresponding simulation report based on the simulation results. Specifically, the intelligent agent module 102 can first perform information parsing on the simulation results, extracting relevant key information such as materials, loads, boundary conditions, and target results. Then, it can call a preset report template to generate a report based on the key information, thus obtaining the corresponding simulation report. This application does not limit the preset report template; it can be pre-configured by the system according to actual conditions, such as a user-provided template based on personal preferences or a report template provided in the RAG knowledge base generated by the search enhancement method. This application does not impose further limitations or details on this.

[0040] In some alternative embodiments, the simulation interaction module 104 can display the simulation results and / or the simulation report in a preset interactive interface for users to view and use. This application does not impose any further limitations on this.

[0041] As can be seen, the simulation system described in this application can provide / form an automated simulation process of "requirement input - knowledge retrieval - script generation - automatic execution - result generation," significantly improving simulation efficiency, reducing human error, and ensuring the consistency and repeatability of simulation results. It supports the input of multimodal requirement information, flexibly adapting to the input habits of different users, and supports the direct import and execution of enterprise standard processes, expanding the system's application scenarios. The multimodal parsing capability based on a large language model enables intelligent conversion of simulation requirements, lowering the threshold for simulation operations and improving user experience. The aforementioned enhanced retrieval and generation of the RAG knowledge base integrates enterprise simulation knowledge assets, realizing the digital management and intelligent reuse of expert knowledge. The aforementioned simulation interface module is compatible with multiple simulation software, enabling cross-platform automated execution.

[0042] By implementing the embodiments of this application, this application provides a simulation system comprising: a simulation knowledge base module for constructing a corresponding retrieval-enhanced generative knowledge base based on at least one knowledge source, the retrieval-enhanced generative knowledge base including at least one knowledge; an intelligent agent module for acquiring simulation requirements, retrieving corresponding candidate knowledge from the retrieval-enhanced generative knowledge base based on the simulation requirements, and generating a corresponding executable script, the executable script including at least the simulation requirements and the candidate knowledge; and a simulation interface module for calling a target simulation software to execute the executable script and obtain corresponding simulation results, the target simulation software being one of multiple simulation software programs interfaced with the simulation interface module. This allows for an automated simulation process, eliminating reliance on human experience and manual operation, thus improving the efficiency and convenience of simulation. It also solves the technical problems of low simulation accuracy or precision and low simulation efficiency in existing technologies.

[0043] Based on the foregoing embodiments, please refer to Figure 4 This is a flowchart illustrating a simulation method provided in an embodiment of this application. Figure 4 The simulation method shown is applied to the aforementioned Figures 1-3 In the simulation system shown, the method includes the following implementation steps: S401. The simulation knowledge base module 101 constructs a corresponding retrieval enhancement generation knowledge base based on at least one knowledge source, wherein the retrieval enhancement generation knowledge base includes at least one knowledge source. S402. The simulation requirements are obtained through the intelligent agent module 102. Based on the simulation requirements, corresponding candidate knowledge is retrieved from the retrieval enhancement generation knowledge base, and a corresponding executable script is generated. The executable script includes at least the simulation requirements and the candidate knowledge. S403. The target simulation software is called through the simulation interface module 103 to execute the executable script and obtain the corresponding simulation results. The target simulation software is one of at least one simulation software that the simulation interface module 103 interfaces with.

[0044] In some embodiments, the simulation interface module 103 encapsulates multiple protocol interfaces, and the step of calling the target simulation software to execute the executable script includes: Based on the simulation interface module 103, the target simulation software is called through the target protocol interface to execute the executable script, and the execution status of the executable script is monitored. The target protocol interface and the target simulation software correspond one-to-one, and the execution state includes at least one of the following: waiting state, running state, interrupted state, and terminated state.

[0045] In some embodiments, obtaining simulation requirements includes: The simulation interaction module 104 inputs the multimodal requirement information corresponding to the simulation requirement into the preset interactive interface; The intelligent agent module 102 performs multimodal analysis on the multimodal requirement information to obtain the simulation requirements.

[0046] In some embodiments, the method further includes: The intelligent agent module 102 receives the simulation results sent by the simulation interface module 103 and generates a corresponding simulation report based on the simulation results. The simulation interaction module 104 displays the simulation report in the preset interaction interface.

[0047] In some embodiments, generating a corresponding simulation report based on the simulation results includes: The simulation results are analyzed to obtain the corresponding key information; The preset report module is invoked to generate a report on the key information, thus obtaining the simulation report.

[0048] In some embodiments, the method further includes: The simulation results are displayed in the preset interactive interface through the simulation interaction module 104.

[0049] In some embodiments, the multimodal requirement information includes at least one of text, image, voice, video, and captions.

[0050] In some embodiments, the simulation requirements include at least one of simulation problem analysis, simulation guidance, and simulation process execution.

[0051] In some embodiments, the retrieval enhancement knowledge base includes at least one of the following: a simulation problem library, an operation manual library, a simulation case library, a simulation specification library, and a simulation standard library.

[0052] For any content not introduced or described in the embodiments of this application, please refer to the relevant descriptions in the foregoing system embodiments; they will not be repeated here.

[0053] Please see Figure 5 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Figure 5 The computer device shown can be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness equipment, personal digital assistant, etc. This computer device may include the aforementioned simulation system.

[0054] Reference Figure 5The device 500 may include one or more of the following components: processing component 502, memory 504, power supply component 506, multimedia component 508, audio component 510, input / output interface 512, sensor component 514, and communication component 516.

[0055] Processing component 502 typically controls the overall operation of device 500, such as operations associated with display, telephone calls, data communication, camera operation, and recording. Processing component 502 may include one or more processors 520 to execute instructions to complete all or part of the steps of the simulation method described above. Furthermore, processing component 502 may include one or more modules to facilitate interaction between processing component 502 and other components. For example, processing component 502 may include a multimedia module to facilitate interaction between multimedia component 508 and processing component 502.

[0056] Memory 504 is configured to store various types of data to support the operation of device 500. Examples of this data include instructions for any application or method operating on device 500, contact data, phonebook data, messages, pictures, videos, etc. Memory 504 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0057] Power supply component 506 provides power to various components of device 500. Power supply component 506 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to device 500.

[0058] Multimedia component 508 includes a screen that provides an output interface between the device 500 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of the touch or swipe action but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 508 includes a front-facing camera and / or a rear-facing camera. When the device 500 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or the rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0059] Audio component 510 is configured to output and / or input audio signals. For example, audio component 510 includes a microphone (MIC) configured to receive external audio signals when device 500 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 504 or transmitted via communication component 516. In some embodiments, audio component 510 also includes a speaker for outputting audio signals.

[0060] Input / output interface 512 provides an interface between processing component 502 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, start buttons, and lock buttons.

[0061] Sensor assembly 514 includes one or more sensors for providing state assessments of various aspects of device 500. For example, sensor assembly 514 may detect the on / off state of device 500, the relative positioning of components such as the display and keypad of device 500, changes in the position of device 500 or a component of device 500, the presence or absence of user contact with device 500, the orientation or acceleration / deceleration of device 500, and temperature changes of device 500. Sensor assembly 514 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 514 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 514 may also include an accelerometer, a gyroscope, a magnetometer, a pressure sensor, or a temperature sensor.

[0062] Communication component 516 is configured to facilitate wired or wireless communication between device 500 and other devices. Device 500 can access wireless networks based on communication standards, such as WiFi, 2G, or 3G, or combinations thereof. In one exemplary embodiment, communication component 516 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 516 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0063] In an exemplary embodiment, device 500 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-described simulation method.

[0064] Understandably, the processor 520 in this application embodiment can be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method embodiment can be completed by integrated logic circuits in the processor's hardware or by software instructions. The processor described above can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0065] Understandably, the memory 504 in the embodiments of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct rambus RAM (DR RAM). It should be noted that the memory used in the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0066] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 504 including instructions, which can be executed by the processor 520 of the device 500 to complete the above-described upper-level emulation method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0067] The aforementioned device can be a standalone electronic device or a part of a standalone electronic device. For example, in one embodiment, the device can be an integrated circuit (IC) or a chip, wherein the integrated circuit can be a single IC or a collection of multiple ICs. The chip can include, but is not limited to, the following types: GPU (Graphics Processing Unit), CPU (Central Processing Unit), FPGA (Field Programmable Gate Array), DSP (Digital Signal Processor), ASIC (Application Specific Integrated Circuit), and SoC (System on Chip). The aforementioned integrated circuit or chip can be used to execute executable instructions (or code) to implement the aforementioned simulation method. These executable instructions can be stored in the integrated circuit or chip or obtained from other devices or equipment. For example, the integrated circuit or chip includes a processor, memory, and an interface for communicating with other devices. The executable instructions can be stored in the memory, and when the executable instructions are executed by the processor, the above simulation method can be implemented; or, the integrated circuit or chip can receive the executable instructions through the interface and transmit them to the processor for execution to implement the above simulation method.

[0068] This application embodiment can divide the computer device into functional modules according to the above method embodiment. For example, each function can be assigned to a separate module, or two or more functions can be integrated into a processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods. When dividing each functional module according to its corresponding function, the vehicle may include: a processing module and a communication module, etc.

[0069] It should be noted that all relevant content of each step involved in the above method embodiments can be referenced from the functional description of the corresponding functional module, and will not be repeated here. The computer device provided in this embodiment is used to execute the above simulation method, and therefore can achieve the same effect as the above implementation method.

[0070] In another exemplary embodiment, a computer program product is also provided, the computer program product comprising a computer program executable by a programmable device, the computer program having a code portion for performing the above-described simulation method when executed by the programmable device.

[0071] It should be noted that the descriptions of the above embodiments of storage media, methods, and devices are similar to those of the above system embodiments, and have similar beneficial effects as the method embodiments. For technical details not disclosed in the embodiments of storage media, methods, and devices of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0072] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of this application. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed in this application. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0073] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications or equivalent substitutions made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A simulation system, characterized in that, include: The simulation knowledge base module is used to construct a corresponding retrieval-enhanced knowledge base based on at least one knowledge source, wherein the retrieval-enhanced knowledge base includes at least one knowledge source. The intelligent agent module is used to acquire simulation requirements, retrieve corresponding candidate knowledge from the retrieval enhancement generation knowledge base based on the simulation requirements, and generate corresponding executable scripts. The executable scripts include at least the simulation requirements and the candidate knowledge. The simulation interface module is used to call the target simulation software to execute the executable script and obtain the corresponding simulation results. The target simulation software is one of the multiple simulation software programs that the simulation interface module interfaces with.

2. The system according to claim 1, characterized in that, The simulation interface module encapsulates multiple protocol interfaces. The simulation interface module is used to call the target simulation software to execute the executable script through the target protocol interface, and to monitor the execution status of the executable script. The target protocol interface and the target simulation software correspond one-to-one, and the execution state includes at least one of the following: waiting state, running state, interrupted state, and terminated state.

3. The system according to claim 1, characterized in that, The system also includes a simulation interaction module, wherein: The simulation interaction module is used to input multimodal requirement information corresponding to the simulation requirement in a preset interactive interface; The intelligent agent module is used to perform multimodal analysis on the multimodal requirement information to obtain the simulation requirements.

4. The system according to claim 3, characterized in that, The intelligent agent module is also used to receive the simulation results sent by the simulation interface module, and generate a corresponding simulation report based on the simulation results; The simulation interaction module is also used to display the simulation report in the preset interactive interface.

5. The system according to claim 4, characterized in that, The intelligent agent module is used for: The simulation results are analyzed to obtain the corresponding key information; The preset report module is invoked to generate a report on the key information, thus obtaining the simulation report.

6. The system according to claim 3, characterized in that, The simulation interaction module is also used to display the simulation results in the preset interactive interface.

7. The system according to claim 3, characterized in that, The multimodal requirement information includes at least one of the following: text, image, voice, video, and caption.

8. The system according to any one of claims 1-7, characterized in that, The simulation requirements include at least one of the following: simulation problem analysis, simulation guidance, and simulation process execution.

9. The system according to any one of claims 1-7, characterized in that, The enhanced retrieval knowledge base includes at least one of the following: a simulation problem library, an operation manual library, a simulation case library, a simulation specification library, and a simulation standard library.

10. A simulation method, characterized in that, Applied to a simulation system, the simulation system including a simulation knowledge base module, an intelligent agent module, and a simulation interface module, the method includes: The simulation knowledge base module constructs a corresponding retrieval-enhanced knowledge base based on at least one knowledge source, and the retrieval-enhanced knowledge base includes at least one knowledge source. The simulation requirements are obtained through the intelligent agent module, and corresponding candidate knowledge is retrieved from the retrieval enhancement generation knowledge base based on the simulation requirements. A corresponding executable script is generated, and the executable script includes at least the simulation requirements and the candidate knowledge. The target simulation software is called by the simulation interface module to execute the executable script and obtain the corresponding simulation results. The target simulation software is one of at least one simulation software that the simulation interface module interfaces with.

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