A virtual simulation experiment system based on multi-engine cooperation and a method thereof

Abstract

This invention discloses a virtual simulation experiment method and system based on multi-engine collaboration. The method is as follows: S1, the front-end interaction layer receives the simulation experiment task and parses the experiment mode classification; selects the corresponding learning mode according to the learning requirements, and then transmits the task data to the engine layer; S2, in the engine layer, based on the preset equipment association engine module, obtains the equipment required for the experiment through the equipment library information; and determines whether it is compliant; if compliant, at least two simulation engine modules are dynamically matched and linked through the collaborative engine association mapping mechanism, and then the results are calculated by the multi-disciplinary computing engine module and output in a unified data format; S3, the information collector receives the calculation results and scores or renders the experimental results. This method uses unified modeling and engine-based encapsulation to realize intelligent reasoning and animation rendering of virtual experimental scenarios in multiple disciplines such as chemistry and physics, thereby achieving an open, interactive, and verifiable virtual simulation experiment experience.

Description

Technical Field

[0001] This invention belongs to the field of educational informatization and virtual simulation technology, specifically relating to a virtual simulation experiment system and method based on multi-engine collaboration. Background Technology

[0002] With the popularization of virtual simulation experimental teaching, a large number of experimental teaching resources have migrated from real laboratories to online virtual environments. Most existing virtual experimental systems still adopt the "fixed animation + preset conditions" model: during the development phase, developers need to explicitly write corresponding trigger logic and animation scripts for each experimental step, each set of equipment, and each chemical reaction or physical process. When students perform operations such as dragging, connecting, heating, and mixing on the front end, the system only checks whether a certain pre-coded condition is met; once the condition is met, the corresponding animation clip is played.

[0003] This approach has significant drawbacks: First, the pairing relationships between experimental apparatus are often fixed in code or timeline scripts. Adding a new apparatus or a new combination requires modifying existing logic, making it difficult to reuse and maintain. Second, chemical reactions or changes in the state of matter lack a unified reasoning engine. Adding a new reaction or state change not only requires expanding data but also rewriting triggering conditions and animation call logic, resulting in high development costs and a high error rate. Third, the flow and propagation paths of gases, liquids, light, or current are often represented through fixed lines and pre-fabricated paths, making real-time analysis based on the actual apparatus structure built by learners impossible, lacking the ability to dynamically simulate real physical laws. Finally, quantitative calculations in physical processes such as mechanics, optics, thermodynamics, and electromagnetism are usually embedded in animation scripts, which are neither easy to maintain nor convenient for interdisciplinary expansion.

[0004] Chinese patent document CN109410343A discloses a method and system for biological experiments based on virtual reality. This invention relates to the field of virtual reality simulation. It generates biological structural model data by acquiring geometric feature data and experimental initialization structural data of organisms; it acquires biological behavioral and growth characteristics to generate biological perception model data; it acquires experimental settings such as light, water, temperature, wind, and soil parameters to generate an environmental model; and it dynamically synthesizes a virtual reality model of the organism using a 3D graphics engine based on the biological category, the biological structural model data, the biological perception model data, and the environmental model. This prior art achieves the generation of virtual reality biological experimental samples and simulates various special effects of real-world samples more realistically, resulting in highly reliable experimental results.

[0005] Chinese patent document CN117877333A discloses a virtual simulation-based experimental teaching method, server, and system. The virtual simulation-based experimental teaching method includes the following steps: S1, speech recognition: using a speech recognition engine to convert speech into text, integrating the speech recognition engine's API into the virtual simulation environment to receive, process, and understand students' spoken input, achieving real-time feedback. When students practice speaking, the system can instantly recognize the speech and provide grammar correction and pronunciation suggestions. This invention integrates three multimodal interaction technologies: speech recognition, gesture recognition, and facial expression recognition, enabling students to interact seamlessly with the virtual environment through speech, gestures, and facial expressions, providing a richer learning experience and allowing students to express and understand information more comprehensively in the virtual environment. However, the existing technology's definition of emotional states and expression mapping relies on knowledge from the fields of psychology and education, is highly subjective, and can easily lead to inaccurate adjustments to teaching strategies.

[0006] Therefore, existing technologies urgently need a new solution that can abstract the experimental process, unify the modeling of experimental logic, and drive the virtual experimental system with an "engine" rather than "script fragments," so that the animation module can focus on the form of expression, while the experimental logic is uniformly managed by a configurable, scalable, and reasonable engine. Summary of the Invention

[0007] The technical problem to be solved by the present invention is to provide a virtual simulation experiment system and method based on multi-engine collaboration. By unifying the modeling and engine-based encapsulation of the correlation of experimental equipment, experimental safety rules, chemical reactions and the three states of matter transformation, path connectivity and multi-disciplinary physical quantity calculation, intelligent reasoning and animation rendering of virtual experimental scenarios in chemistry, physics and other disciplines can be realized, thereby achieving an open, interactive and verifiable virtual simulation experiment experience.

[0008] To address the aforementioned technical problems, the first aspect of this invention is to provide a method for virtual simulation experiments based on multi-engine collaboration, specifically comprising the following steps:

[0009] S1: The front-end interaction layer receives simulation experiment tasks, parses the experiment mode classification, selects the corresponding learning mode according to the learning needs, and then transmits the task data to the engine layer.

[0010] S2: In the engine layer, the equipment required for the experiment is first obtained through the equipment library information based on the preset equipment association engine module; and the safety rule engine module determines whether it is compliant; if compliant, at least two simulation engine modules are dynamically matched and linked through the collaborative engine association mapping mechanism to obtain the experimental method, and then the results are calculated by the multidisciplinary computing engine module and output in a unified data format; if it is non-compliant, a safety warning is issued, operation is prohibited, and the process is returned to the front-end interaction layer.

[0011] S3: After receiving the calculation results, the information collector scores the experimental results or renders them into animations, thereby completing the simulation experiment task.

[0012] Preferably, in step S1, the mode selection stage is entered first, and a learning mode, assessment mode or free exploration mode is selected according to the learning needs;

[0013] If you choose the learning mode, you will be provided with step prompts and process guidance during the experiment, and the scoring engine will record the user's actions in real time to generate instant feedback;

[0014] If the evaluation mode is selected, all operation prompts will be hidden, and the system will automatically record the user's independent operation process to evaluate whether the user can complete the experiment without assistance.

[0015] If the free exploration mode is selected, it will not participate in the scoring, but will only be responsible for realistically simulating the experimental structure built by the user and the resulting experimental phenomena, so that learners can independently explore the diverse experimental results formed by different combinations of equipment and operation sequences.

[0016] Preferably, the simulation engine module in step S2 includes a matter reaction engine module, a matter conversion engine module, a matter collision engine module, a path transport engine module, a path analysis engine module, and an equivalent conversion engine module;

[0017] The material reaction engine module relies on an extended reaction library to process chemical reaction reasoning. The reaction library records the types of reactants, stoichiometric relationships, reaction conditions, and the morphology and visual characteristics of the products. The material reaction engine module infers the occurrence of the reaction and its visual manifestation based on the operation records and environmental conditions.

[0018] The material conversion engine module relies on a property library to determine phase transitions between solid, liquid, and gaseous states; the property library records physical property parameters such as melting point, boiling point, and vapor pressure; the material conversion engine module infers whether melting, boiling, evaporation, sublimation, or deposition has occurred based on temperature and pressure changes.

[0019] The material collision engine module is used to process experimental scenarios involving collision behavior and to infer the motion trend, possible fragmentation, or reaction results after the collision based on the collision model.

[0020] The path analysis engine module uses a graph structure to represent the connectivity between devices, with nodes representing device components and edges representing conduits, pipes, or direct connections. The path analysis engine module performs connectivity, reachability, and shortest path analysis for gas transport, liquid flow, and current conduction scenarios.

[0021] The path transmission engine module further deduces the flow direction, speed, and obstruction status of the fluid or medium based on the path structure given by the path analysis engine module.

[0022] The equivalent transformation engine is used to handle the equivalence of structure and dimensions, such as the equivalent simplification of circuit connection methods or the equivalent expression of structural topology under different construction methods, so that the system can maintain a consistent semantic interpretation under various assembly methods.

[0023] Preferably, the multidisciplinary computing engine module in step S2 adopts a modular design, including a mechanics calculation submodule, a thermal calculation submodule, an optical calculation submodule, and an electromagnetic calculation submodule, and uses a unified data format for output;

[0024] The mechanics calculation submodule calculates gravity, buoyancy, friction, tension, pressure, and the equilibrium state of an object;

[0025] The thermal calculation submodule calculates the temperature change pattern during heating and cooling processes;

[0026] The optical calculation submodule calculates reflection, refraction, critical angle, and optical path;

[0027] The electromagnetic calculation submodule calculates the current, magnetic field distribution, and direction of magnetic induction lines.

[0028] Preferably, in step S3, a scoring engine module is used to judge the correctness of the user's operation sequence, whether the timing is reasonable, and whether implicit scoring points are touched for scoring.

[0029] Preferably, in step S3, the animation call and rendering engine module calls the corresponding animation component according to the event and parameters to perform visual rendering of the engine layer output event.

[0030] A second aspect of this invention is to provide a virtual simulation experiment system based on multi-engine collaboration, comprising a front-end interaction layer, an engine layer, and a back-end display layer. The front-end interaction layer is used to select a practice mode, an assessment mode, or a free exploration mode according to learning needs. The engine layer includes multiple independently extended and collaboratively operating engine modules, which are linked through an event bus and employ a collaborative mapping mechanism to achieve cross-module collaboration using a unified data structure. The back-end display layer is used to score and visualize the events output by the engine layer, thereby achieving dynamic experimental effects of the simulation.

[0031] The above technical solution, with a multi-engine collaborative operation mechanism as the core, adopts a three-level structure of front-end interaction layer, engine layer and back-end display layer. The core concept of the system is to replace the traditional script-based logic with a unified event mechanism and an extensible rule system, so that the experimental logic can evolve in real time with the user's operation and cross-disciplinary reasoning can be completed automatically by multiple engines.

[0032] Preferably, the engine layer includes an instrument association engine module, a safety rule engine module, a matter reaction engine module, a matter conversion engine module, a matter collision engine module, a path transmission engine module, a path analysis engine module, an equivalent conversion engine module, and a multidisciplinary computing engine module;

[0033] The device association engine module records the interface type (such as bottle opening, conduit opening, fuel opening, etc.), the list of matching interfaces, and functional attributes of the devices based on the device library information. When the user performs a drag-and-drop matching operation, the device association engine module retrieves the interface matching rules, determines whether a legal combination can be formed, and updates the device topology map.

[0034] The safety rule engine module is based on the addition of hazard labels and hazard combination rules to the equipment attributes to identify hazardous situations such as high temperature, flammability, corrosiveness, and pressure vessels; if the operation violates the safety rules, the safety rule engine module will block subsequent reasoning and prompt the user.

[0035] The material reaction engine module relies on an extended reaction library to process chemical reaction reasoning. The reaction library records the types of reactants, stoichiometric relationships, reaction conditions, and the morphology and visual characteristics of the products. The material reaction engine module infers the occurrence of the reaction and its visual manifestation based on the operation records and environmental conditions.

[0036] The material conversion engine module relies on a property library to determine phase transitions between solid, liquid, and gaseous states; the property library records physical property parameters such as melting point, boiling point, and vapor pressure; the material conversion engine module infers whether melting, boiling, evaporation, sublimation, or deposition has occurred based on temperature and pressure changes.

[0037] The material collision engine module is used to process experimental scenarios involving collision behavior and to infer the motion trend, possible fragmentation, or reaction results after the collision based on the collision model.

[0038] The path analysis engine module uses a graph structure to represent the connectivity between devices, with nodes representing device components and edges representing conduits, pipes, or direct connections. The path analysis engine module performs connectivity, reachability, and shortest path analysis for gas transport, liquid flow, and current conduction scenarios.

[0039] The path transmission engine module further deduces the flow direction, speed, and obstruction status of the fluid or medium based on the path structure given by the path analysis engine module.

[0040] The equivalent transformation engine is used to handle the equivalence of structure and dimensions, such as the equivalent simplification of circuit connection methods or the equivalent expression of structural topology under different construction methods, so that the system can maintain a consistent semantic interpretation under multiple assembly methods.

[0041] The multidisciplinary computing engine module adopts a modular design, including a mechanics calculation submodule, a thermal calculation submodule, an optical calculation submodule, and an electromagnetic calculation submodule, and uses a unified data format for output;

[0042] The mechanics calculation submodule calculates gravity, buoyancy, friction, tension, pressure, and the equilibrium state of an object;

[0043] The thermal calculation submodule calculates the temperature change pattern during heating and cooling processes;

[0044] The optical calculation submodule calculates reflection, refraction, critical angle, and optical path;

[0045] The electromagnetic calculation submodule calculates the current, magnetic field distribution, and direction of magnetic induction lines.

[0046] Preferably, the backend display layer includes an information collector, a scoring engine module, and an animation invocation and rendering engine module. The information collector, as a global data center, records user operations, reasoning processes, changes in physical quantities, changes in material states, and changes in path structures. The scoring engine module, based on the data in the information collector, judges the correctness of the user's operation sequence, the reasonableness of the timing, and whether implicit scoring points are touched, and then scores accordingly. The animation invocation and rendering engine module calls the corresponding animation components according to the events and parameters, and performs visual rendering of the events output by the engine layer, thereby realizing the dynamic experimental effect of the simulation.

[0047] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0048] (1) This invention proposes an "adaptive experimental logic generation mechanism in free exploration mode". The system can combine various experimental equipment across disciplines without distinguishing between disciplines. The interaction between equipment no longer relies on traditional exhaustive rules or fixed animations, but is generated dynamically by multiple collaborative engines based on real-time status, thereby effectively avoiding the problems of incomplete exhaustive enumeration, rule omissions and difficulty in maintaining complex combinations.

[0049] (2) The present invention constructs a multi-engine architecture system with clear division of labor. Each engine works together through a unified scheduling mechanism, enabling the ultra-large-scale experimental logic to be decomposed, executed in parallel and automatically integrated.

[0050] (3) This invention proposes a "multi-mode experimental unified framework and logical decoupling mechanism". The system supports three experimental modes: practice mode, evaluation mode and exploration mode. The exploration mode gives users the greatest freedom and allows them to operate any experimental equipment. This completely decouples the logic layer from the animation rendering layer. The engine outputs events, and the animation module is only responsible for rendering. Attached Figure Description

[0051] Figure 1 This is a flowchart of the virtual simulation experiment method based on multi-engine collaboration of the present invention;

[0052] Figure 2 An example diagram showing the electromagnetic simulation effect obtained using the multi-engine collaborative virtual simulation experimental method of the present invention;

[0053] Figure 3 An example image showing the ray simulation effect obtained using the multi-engine collaborative virtual simulation experimental method of the present invention;

[0054] Figure 4 The diagram shows an example of the circuit simulation effect obtained using the multi-engine collaborative virtual simulation experimental method of the present invention.

[0055] Figure 5 An example image showing the chemical simulation effect obtained using the multi-engine collaborative virtual simulation experimental method of the present invention;

[0056] Figure 6 An example diagram showing the thermal simulation effect obtained using the multi-engine collaborative virtual simulation experimental method of the present invention;

[0057] Figure 7 The figure shows an example of the scoring effect obtained by using the virtual simulation experiment method based on multi-engine collaboration of the present invention. Detailed Implementation

[0058] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings. The following embodiments are only used to illustrate the technical solutions of the present invention more clearly, and should not be used to limit the scope of protection of the present invention.

[0059] Those skilled in the art will understand that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless defined as herein.

[0060] Example: Figure 1 As shown, this method for virtual simulation experiments based on multi-engine collaboration specifically includes the following steps:

[0061] S1: The front-end interaction layer receives simulation experiment tasks, parses the experiment mode classification, selects the corresponding learning mode according to the learning needs, and then transmits the task data to the engine layer.

[0062] In step S1, the mode selection stage is first entered, where students can choose a learning mode, assessment mode, or free exploration mode according to their learning needs.

[0063] If you choose the learning mode, you will be provided with step-by-step prompts and process guidance during the experiment. The scoring engine will record user actions in real time to generate instant feedback, and the scoring effect will be as follows: Figure 7 As shown;

[0064] If the evaluation mode is selected, all operation prompts will be hidden, and the system will automatically record the user's independent operation process to evaluate whether the user can complete the experiment without assistance.

[0065] If you choose the free exploration mode, you will not participate in the scoring. The mode will only be responsible for realistically simulating the experimental structure and phenomena built by the user, enabling learners to independently explore the diverse experimental results formed by different combinations of equipment and operation sequences; the scoring results will be displayed directly in the experimental scoring engine module.

[0066] S2: In the engine layer, the equipment required for the experiment is first obtained through the equipment library information based on the preset equipment association engine module; and the safety rule engine module determines whether it is compliant; if compliant, at least two simulation engine modules are dynamically matched and linked through the collaborative engine association mapping mechanism to obtain the experimental method, and then the results are calculated by the multidisciplinary computing engine module and output in a unified data format; if it is non-compliant, a safety warning is issued, operation is prohibited, and the process is returned to the front-end interaction layer.

[0067] The simulation engine module in step S2 includes a matter reaction engine module, a matter conversion engine module, a matter collision engine module, a path transport engine module, a path analysis engine module, and an equivalent conversion engine module.

[0068] The material reaction engine module relies on an extended reaction library to process chemical reaction reasoning. The reaction library records the types of reactants, stoichiometric relationships, reaction conditions, and the morphology and visual characteristics of the products. The material reaction engine module infers the occurrence of the reaction and its visual manifestation based on the operation records and environmental conditions.

[0069] The material conversion engine module relies on a property library to determine phase transitions between solid, liquid, and gaseous states; the property library records physical property parameters such as melting point, boiling point, and vapor pressure; the material conversion engine module infers whether melting, boiling, evaporation, sublimation, or deposition has occurred based on temperature and pressure changes.

[0070] The material collision engine module is used to process experimental scenarios involving collision behavior and to infer the motion trend, possible fragmentation, or reaction results after the collision based on the collision model.

[0071] The path analysis engine module uses a graph structure to represent the connectivity between devices, with nodes representing device components and edges representing conduits, pipes, or direct connections. The path analysis engine module performs connectivity, reachability, and shortest path analysis for gas transport, liquid flow, and current conduction scenarios.

[0072] The path transmission engine module further deduces the flow direction, speed, and obstruction status of the fluid or medium based on the path structure given by the path analysis engine module.

[0073] The equivalent transformation engine is used to handle the equivalence of structure and dimensions, such as the equivalent simplification of circuit connection methods or the equivalent expression of structural topology under different construction methods, so that the system can maintain a consistent semantic interpretation under multiple assembly methods.

[0074] In step S2, the multidisciplinary computing engine module adopts a modular design, including a mechanics computing submodule, a thermal computing submodule, an optical computing submodule, and an electromagnetic computing submodule, and uses a unified data format for output.

[0075] The mechanics calculation submodule calculates gravity, buoyancy, friction, tension, pressure, and the equilibrium state of an object;

[0076] The thermal calculation submodule calculates the temperature change pattern during heating and cooling processes;

[0077] The optical calculation submodule calculates reflection, refraction, critical angle, and optical path;

[0078] The electromagnetic calculation submodule calculates the current, magnetic field distribution, and direction of magnetic induction lines;

[0079] If the collaborative engine association mapping cannot be performed in step S2, the process will proceed directly to step S3 to render the animation by calling the rendering engine module.

[0080] S3: After receiving the calculation results, the information collector scores the experimental results or renders them into animations, thereby completing the simulation experiment task;

[0081] In step S3, the scoring engine module is used to judge the correctness of the user's operation sequence, whether the timing is reasonable, and whether implicit scoring points are touched, and to score accordingly.

[0082] In step S3, the animation call and rendering engine module calls the corresponding animation component based on the event and parameters to perform visual rendering of the engine layer output event.

[0083] This method introduces an instrument association engine, safety rule engine, material reaction engine, material conversion engine, material collision engine, path analysis engine, path transmission engine, equivalent transformation engine, and multidisciplinary computing engine into an integrated process where the engine automatically infers, judges, and triggers animations. This is supplemented by a unified animation calling and effect presentation mechanism, which transforms the traditional experiment process that relies on fixed scripts into an integrated process where the engine automatically infers, judges, and triggers animations. This results in a virtual simulation experiment system that is multidisciplinary, scalable, adaptive, and highly automated.

[0084] In some specific embodiments, before the experiment begins, the system first enters a mode selection phase, where users can choose between practice mode, assessment mode, or free exploration mode based on their learning needs. Practice mode provides step-by-step prompts and process guidance during the experiment, and the scoring engine module records user actions in real time to generate immediate feedback, as shown in the attached scoring effect diagram. Assessment mode hides all prompts, and the system automatically records the user's independent operation process to evaluate whether the user can complete the experiment without assistance. Free exploration mode does not participate in scoring; it only realistically simulates the experimental structure built by the user and the resulting experimental phenomena, enabling learners to independently explore the diverse experimental results caused by different combinations of equipment and operation sequences.

[0085] When a user enters the experimental operation phase, regardless of the mode used, all actions such as dragging, attaching, placing, connecting, heating, and igniting are transformed into standardized events by the front-end interaction layer and passed to the engine layer. From the moment an event enters the engine layer, the appliance association engine module begins to reason about each structural action, determining whether a valid combination relationship can be formed based on the appliance's interface type, structural attributes, and functional characteristics. Throughout the entire experimental setup process, the appliance association engine module continuously maintains its internal appliance topology graph, ensuring the system always has access to the latest state of the experimental structure.

[0086] The subsequent safety rules engine module determines whether the current operation and equipment characteristics involve risk sources such as high temperature, flammability, corrosiveness, pressurized containers, or open flames. If the safety rules do not meet the conditions, the system will block the subsequent reasoning process and prompt the user with the risk; only after the safety is verified can the experiment proceed to the collaborative mapping stage between engines.

[0087] The collaborative mapping mechanism is the key to the multi-engine architecture of this invention. In this stage, the system does not rely on manually preset subject classifications, but automatically derives the set of engine modules that should participate in the calculation based on user operations, instrument status, material properties, and environmental conditions. For example, when the operation involves material mixing, heating, or adding a catalyst, the material reaction engine module is automatically included in the calculation; when temperature increases or pressure changes may lead to adjustments in the phase state of matter, the material conversion engine module will automatically intervene; when instrument combinations form potential fluid pathways, the path analysis engine module and the path transport engine module will derive the pathway structure; when there are material collisions or structural equivalence issues, the material collision engine module and the equivalence conversion engine module are used to handle collision result reasoning and structural equivalence derivation, respectively.

[0088] After determining the set of participating engine modules in the collaborative mapping phase, the system enters the multidisciplinary computing engine module phase. This phase utilizes the joint operations of multiple computing sub-modules, including mechanics, optics, thermodynamics, electromagnetism, and chemistry, to achieve real-time calculations of interdisciplinary experimental phenomena. For example, in heating experiments, the thermodynamics calculation sub-module calculates the temperature change curve based on heating power, specific heat capacity, volume, and mass, and triggers the matter conversion engine module to determine phase transitions when the temperature reaches a critical condition; in optical experiments, the optical calculation sub-module derives the reflected and refracted light paths based on refractive index and incident angle; in electromagnetic experiments, the electromagnetic calculation sub-module calculates the distribution of magnetic induction lines based on changes in current, coil turns, and magnetic flux; and in mechanics experiments, it determines whether an object slides, tilts, or remains stationary through balance analysis of gravity, friction, buoyancy, and tension.

[0089] As the experiment progresses, all user actions, engine inference results, computational outputs, path structure changes, and material state changes are written into the information collector. The information collector, acting as a global data center, records the entire experiment in time-series format, ensuring that the scoring engine, animation call, and rendering engine modules can access a unified and complete experimental state. Based on this, the scoring engine module determines the correctness of the user action sequence, the reasonableness of the timing, and whether any implicit scoring points have been triggered. Figure 7 As shown, the animation call and rendering engine module calls the corresponding animation components based on events and parameters, so that phenomena such as flames, bubbles, light paths, liquid flow, magnetic field lines, and objects tipping over are presented to the user in a realistic and continuous dynamic form.

[0090] Through the aforementioned workflow, the system leverages the collaborative operation of multiple engine modules to achieve automatic reasoning of experimental logic without the need for pre-set scripts or subject classifications. This adapts to interdisciplinary, nonlinear, and complex combined experimental scenarios, significantly enhancing the intelligence and scalability of virtual simulation experiments. The final experimental results are shown in [link to documentation]. Figure 2-6 As shown.

[0091] like Figure 2 The image shown is a virtual simulation of the magnetic field interaction between a current-carrying solenoid and a U-shaped magnet or bar magnet. After identifying the experimental apparatus such as the solenoid, magnet, and small compass needle, the system automatically establishes the physical relationships between the current, magnetic field, and force through an apparatus correlation engine.

[0092] After the solenoid is energized, the electromagnetic calculation engine automatically deduces the magnetic field distribution generated by it based on the current direction and coil structure, and superimposes it with the magnetic field of the external magnet; the path analysis engine further analyzes the path of the magnetic field, causing the small magnetic needle to produce corresponding directional deflections at different spatial positions.

[0093] When the direction of the current, the position of the magnet, or the orientation of the magnetic poles is changed, the system can update the magnetic field distribution and the deflection of the magnetic needle in real time, thus fully presenting the dynamic process of the interaction between magnets in the electromagnetic experiment.

[0094] like Figure 3 The image shows a simulation of the optical path of a laser beam emitted from a laser pointer as it passes sequentially through various optical devices, including a convex lens, a concave lens, a semi-circular lens, a triangular lens, and a plane mirror. The system automatically distinguishes the geometric structure and optical properties of various optical components through a device identification module, and the optical computing engine calculates the light path in real time based on the laws of light propagation. During the experiment, the path analysis engine continuously extrapolates the propagation, refraction, reflection, and convergence or divergence paths of the laser at different media interfaces, allowing the changes in the optical path to be dynamically presented as the device type, position, and angle are adjusted, thus achieving a direct simulation of optical experimental phenomena.

[0095] like Figure 4 The image shown is a virtual simulation diagram of a hybrid circuit that supports the free connection of various electrical appliances. The system can automatically identify appliances such as ammeters, voltmeters, sliding rheostats, light bulbs, and fixed resistors, and construct the topological relationships between circuit nodes and branches through an appliance association engine.

[0096] When the user makes any connection or adjusts any parameter, the path analysis engine automatically infers the current flow direction and circuit path status, and the electromagnetic calculation engine performs dynamic calculations of parameters such as voltage, current and power based on the circuit model built in real time, so that the measurement instrument indication and bulb brightness changes can be fed back in real time.

[0097] This process eliminates the need for pre-setting calculation scripts for specific circuit configurations, significantly improving the flexibility and versatility of virtual circuit experiments.

[0098] like Figure 5The image shown is a virtual simulation of an oxygen production chemical experiment. After recognizing experimental equipment such as alcohol lamps, test tubes, reactants, rubber tubing, water tanks, and gas collecting bottles, the system establishes a correlation model between heating conditions and chemical reactions through a matter reaction engine and a matter conversion engine.

[0099] During the experiment, the system automatically determines whether the reaction conditions are met based on the heating status of the alcohol lamp. When the conditions are met, it drives a change in the state of matter, generating oxygen which is then transported to the water tank via a rubber tube. Simultaneously, the system uses a path analysis engine to simulate the gas transport path, dynamically presenting the process of gas displacement in the water within the gas collecting bottle and the phenomenon of bubble generation. When experimental conditions change, the system can synchronously update the reaction rate and generation effect, achieving continuous simulation of the entire chemical experiment process.

[0100] like Figure 6 The image shows a virtual simulation experiment of heating a liquid in a beaker and monitoring its temperature changes and material state evolution in real time. After identifying the beaker, heating source, and thermometer inserted into the beaker, the system establishes a correlation model between heating power, heat conduction path, and temperature measurement through an instrument association engine. During the experiment, the physics calculation engine continuously calculates the heat input and liquid temperature changes, and feeds the calculation results back to the thermometer display in real time. Simultaneously, the material conversion engine automatically determines the physical state of the liquid based on the temperature change results, causing the liquid to exhibit state changes such as liquid, vaporization, and steam generation when reaching different temperature ranges.

[0101] When the temperature changes or the heating conditions are adjusted, the system can update the temperature value, liquid state and visualization effect simultaneously, thereby realizing dynamic simulation and intuitive display of temperature evolution and phase change phenomena during liquid heating.

[0102] This virtual simulation experiment system based on multi-engine collaboration includes a front-end interaction layer, an engine layer, and a back-end display layer. The front-end interaction layer is used to select practice mode, assessment mode, or free exploration mode according to learning needs. The engine layer includes multiple independently extended and collaboratively operating engine modules. These modules are linked through an event bus and employ a collaborative mapping mechanism to achieve cross-module collaboration using a unified data structure. The back-end display layer is used to score and visualize the events output by the engine layer, thereby achieving dynamic experimental effects in the simulation. The core implementation steps of this invention are mainly reflected in three aspects: the construction of experimental equipment building modules, the establishment and collaboration of multiple scientific engines, and the implementation of data analysis and animation scheduling mechanisms between engines.

[0103] The engine layer includes an instrument association engine module, a safety rule engine module, a matter reaction engine module, a matter conversion engine module, a matter collision engine module, a path transmission engine module, a path analysis engine module, an equivalent conversion engine module, and a multidisciplinary computing engine module.

[0104] The device association engine module records the interface type (such as bottle opening, conduit opening, fuel opening, etc.), the list of matching interfaces, and functional attributes of the devices based on the device library information. When the user performs a drag-and-drop matching operation, the device association engine module retrieves the interface matching rules, determines whether a legal combination can be formed, and updates the device topology map.

[0105] The safety rule engine module is based on the addition of hazard labels and hazard combination rules to the equipment attributes to identify hazardous situations such as high temperature, flammability, corrosiveness, and pressure vessels; if the operation violates the safety rules, the safety rule engine module will block subsequent reasoning and prompt the user.

[0106] The material reaction engine module relies on an extended reaction library to process chemical reaction reasoning. The reaction library records the types of reactants, stoichiometric relationships, reaction conditions, and the morphology and visual characteristics of the products. The material reaction engine module infers the occurrence of the reaction and its visual manifestation based on the operation records and environmental conditions.

[0107] The material conversion engine module relies on a property library to determine phase transitions between solid, liquid, and gaseous states; the property library records physical property parameters such as melting point, boiling point, and vapor pressure; the material conversion engine module infers whether melting, boiling, evaporation, sublimation, or deposition has occurred based on temperature and pressure changes.

[0108] The material collision engine module is used to process experimental scenarios involving collision behavior and to infer the motion trend, possible fragmentation, or reaction results after the collision based on the collision model.

[0109] The path analysis engine module uses a graph structure to represent the connectivity between devices, with nodes representing device components and edges representing conduits, pipes, or direct connections. The path analysis engine module performs connectivity, reachability, and shortest path analysis for gas transport, liquid flow, and current conduction scenarios.

[0110] The path transmission engine module further deduces the flow direction, speed, and obstruction status of the fluid or medium based on the path structure given by the path analysis engine module.

[0111] The equivalent transformation engine is used to handle the equivalence of structure and dimensions, such as the equivalent simplification of circuit connection methods or the equivalent expression of structural topology under different construction methods, so that the system can maintain a consistent semantic interpretation under multiple assembly methods.

[0112] The multidisciplinary computing engine module adopts a modular design, including a mechanics calculation submodule, a thermal calculation submodule, an optical calculation submodule, and an electromagnetic calculation submodule, and uses a unified data format for output;

[0113] The mechanics calculation submodule calculates gravity, buoyancy, friction, tension, pressure, and the equilibrium state of an object;

[0114] The thermal calculation submodule calculates the temperature change pattern during heating and cooling processes;

[0115] The optical calculation submodule calculates reflection, refraction, critical angle, and optical path;

[0116] The electromagnetic calculation submodule calculates the current, magnetic field distribution, and direction of magnetic induction lines;

[0117] The backend display layer includes an information collector, a scoring engine module, and an animation invocation and rendering engine module. The information collector, acting as a global data center, records user operations, reasoning processes, changes in physical quantities, changes in material states, and changes in path structures. The scoring engine module, based on the data in the information collector, judges the correctness of the user's operation sequence, the reasonableness of the timing, and whether implicit scoring points are triggered, and then scores accordingly. The animation invocation and rendering engine module calls the corresponding animation components based on events and parameters, and performs visual rendering of the events output by the engine layer, thereby achieving the dynamic experimental effect of the simulation.

[0118] For those skilled in the art, the specific embodiments are merely exemplary descriptions of the present invention. Obviously, the specific implementation of the present invention is not limited to the above-described manner. Any non-substantial improvements made using the inventive concept and technical solution of the present invention, or the direct application of the inventive concept and technical solution to other situations without modification, are all within the protection scope of the present invention.

Claims

1. A method for virtual simulation experiments based on multi-engine collaboration, characterized in that, Specifically, the following steps are included: S1: The front-end interaction layer receives simulation experiment tasks, parses the experiment mode classification, selects the corresponding learning mode according to the learning needs, and then transmits the task data to the engine layer. S2: In the engine layer, the equipment required for the experiment is first obtained through the equipment library information based on the preset equipment association engine module; And it determines compliance based on the security rules engine module; If compliant, at least two simulation engine modules will be dynamically matched and linked through the collaborative engine association mapping mechanism to obtain the experimental method. The results will then be calculated by the multidisciplinary computing engine module and output in a unified data format. If a violation occurs, a security warning will be issued, the operation will be prohibited, and the system will return to the front-end interaction layer. S3: After receiving the calculation results, the information collector scores the experimental results or renders them into animations, thereby completing the simulation experiment task.

2. The method for virtual simulation experiments based on multi-engine collaboration according to claim 1, characterized in that, In step S1, the mode selection stage is first entered, where the learning mode, assessment mode, or free exploration mode is selected according to the learning needs. If you choose the learning mode, you will be provided with step prompts and process guidance during the experiment, and the scoring engine will record the user's actions in real time to generate instant feedback; If the evaluation mode is selected, all operation prompts will be hidden, and the system will automatically record the user's independent operation process to evaluate whether the user can complete the experiment without assistance. If the free exploration mode is selected, it will not participate in the scoring, but will only be responsible for realistically simulating the experimental structure built by the user and the resulting experimental phenomena, so that learners can independently explore the diverse experimental results formed by different combinations of equipment and operation sequences.

3. The method for virtual simulation experiments based on multi-engine collaboration according to claim 1, characterized in that, The simulation engine module in step S2 includes a matter reaction engine module, a matter conversion engine module, a matter collision engine module, a path transport engine module, a path analysis engine module, and an equivalent conversion engine module. The material reaction engine module relies on an extended reaction library to process chemical reaction reasoning. The reaction library records the types of reactants, stoichiometric relationships, reaction conditions, and the morphology and visual characteristics of the products. The material reaction engine module infers the occurrence of the reaction and its visual manifestation based on the operation records and environmental conditions. The material conversion engine module relies on a property library to determine phase transitions between solid, liquid, and gaseous states; the property library records physical property parameters such as melting point, boiling point, and vapor pressure; the material conversion engine module infers whether melting, boiling, evaporation, sublimation, or deposition has occurred based on temperature and pressure changes. The material collision engine module is used to process experimental scenarios involving collision behavior and to infer the motion trend, possible fragmentation, or reaction results after the collision based on the collision model. The path analysis engine module uses a graph structure to represent the connectivity between devices, with nodes representing device components and edges representing conduits, pipes, or direct connections. The path analysis engine module performs connectivity, reachability, and shortest path analysis for gas transport, liquid flow, and current conduction scenarios. The path transmission engine module further deduces the flow direction, speed, and obstruction status of the fluid or medium based on the path structure given by the path analysis engine module. The equivalent transformation engine is used to handle the equivalence of structure and dimensions, and to simplify or simplify the equivalent expression of structural topology under different construction methods, so that the system can maintain a consistent semantic interpretation under various assembly methods.

4. The method for virtual simulation experiments based on multi-engine collaboration according to claim 1, characterized in that, In step S2, the multidisciplinary computing engine module adopts a modular design, including a mechanics computing submodule, a thermal computing submodule, an optical computing submodule, and an electromagnetic computing submodule, and uses a unified data format for output. The mechanics calculation submodule calculates gravity, buoyancy, friction, tension, pressure, and the equilibrium state of an object; The thermal calculation submodule calculates the temperature change pattern during heating and cooling processes; The optical calculation submodule calculates reflection, refraction, critical angle, and optical path; The electromagnetic calculation submodule calculates the current, magnetic field distribution, and direction of magnetic induction lines.

5. The method for virtual simulation experiments based on multi-engine collaboration according to claim 1, characterized in that, In step S3, the scoring engine module is used to judge the correctness of the user's operation sequence, whether the timing is reasonable, and whether implicit scoring points are touched, and to score accordingly.

6. The method for virtual simulation experiments based on multi-engine collaboration according to claim 5, characterized in that, In step S3, the animation call and rendering engine module calls the corresponding animation component based on the event and parameters to perform visual rendering of the engine layer output event.

7. A virtual simulation experimental system based on multi-engine collaboration as described in any one of claims 1-5, characterized in that, It includes a front-end interaction layer, an engine layer, and a back-end display layer. The front-end interaction layer is used to select practice mode, assessment mode, or free exploration mode according to learning needs. The engine layer includes multiple independently extended and collaboratively running engine modules. The various engine modules are linked through an event bus and adopt a collaborative mapping mechanism to achieve cross-module collaboration with a unified data structure. The back-end display layer is used to score and visualize the events output by the engine layer, thereby realizing the dynamic experimental effect of the simulation.

8. The virtual simulation experiment system based on multi-engine collaboration according to claim 7, characterized in that, The engine layer includes an instrument association engine module, a safety rule engine module, a matter reaction engine module, a matter conversion engine module, a matter collision engine module, a path transmission engine module, a path analysis engine module, an equivalent conversion engine module, and a multidisciplinary computing engine module. The device association engine module records the interface type, list of matchable interfaces, and functional attributes of the devices based on the device library information. When the user performs a drag-and-drop matching operation, the device association engine module retrieves the interface matching rules, determines whether a legal combination can be formed, and updates the device topology map. The safety rule engine module is based on adding hazard labels and hazard combination rules to the equipment attributes to identify dangerous situations; If an operation violates security rules, the security rules engine module will block subsequent reasoning and prompt the user. The material reaction engine module relies on an extended reaction library to process chemical reaction reasoning. The reaction library records the types of reactants, stoichiometric relationships, reaction conditions, and the morphology and visual characteristics of the products. The material reaction engine module infers the occurrence of the reaction and its visual manifestation based on the operation records and environmental conditions. The material conversion engine module relies on a property library to determine phase transitions between solid, liquid, and gaseous states; the property library records physical property parameters such as melting point, boiling point, and vapor pressure; the material conversion engine module infers whether melting, boiling, evaporation, sublimation, or deposition has occurred based on temperature and pressure changes. The material collision engine module is used to process experimental scenarios involving collision behavior and to infer the motion trend, possible fragmentation, or reaction results after the collision based on the collision model. The path analysis engine module uses a graph structure to represent the connectivity between devices, with nodes representing device components and edges representing conduits, pipes, or direct connections. The path analysis engine module performs connectivity, reachability, and shortest path analysis for gas transport, liquid flow, and current conduction scenarios. The path transmission engine module further deduces the flow direction, speed, and obstruction status of the fluid or medium based on the path structure given by the path analysis engine module. The equivalent transformation engine is used to handle the equivalence of structure and dimension, and to simplify or simplify the equivalent expression of structural topology under different construction methods, so that the system can maintain a consistent semantic interpretation under multiple assembly methods. The multidisciplinary computing engine module adopts a modular design, including a mechanics calculation submodule, a thermal calculation submodule, an optical calculation submodule, and an electromagnetic calculation submodule, and uses a unified data format for output; The mechanics calculation submodule calculates gravity, buoyancy, friction, tension, pressure, and the equilibrium state of an object; The thermal calculation submodule calculates the temperature change pattern during heating and cooling processes; The optical calculation submodule calculates reflection, refraction, critical angle, and optical path; The electromagnetic calculation submodule calculates the current, magnetic field distribution, and direction of magnetic induction lines.

9. The virtual simulation experiment system based on multi-engine collaboration according to claim 7, characterized in that, The backend display layer includes an information collector, a scoring engine module, and an animation calling and rendering engine module. The information collector, as a global data center, records user operations, reasoning processes, changes in physical quantities, changes in material states, and changes in path structures. The scoring engine module, based on the data in the information collector, judges the correctness of the user's operation sequence, whether the timing is reasonable, and whether it touches on implicit scoring points to score the user. The animation call and rendering engine module calls the corresponding animation components based on the events and parameters, and performs visual rendering of the events output by the engine layer, thereby achieving the dynamic experimental effect of the simulation.

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