Fluid-evacuation multi-mode simulation method and system for preventing and controlling harmful gas in high and large space with dense people

Abstract

The invention discloses a fluid-evacuation multi-modal simulation method and system for prevention and control of harmful gas in a high and large space with dense people, and relates to the technical field of hydrodynamics, and the method comprises the steps: building a fluid simulation model based on a fluid simulation tool, quantifying the diffusion velocity and range of the harmful gas, and obtaining a three-dimensional space-time evolution rule; an evacuation simulation model is constructed by using an AnyLogic tool, and a personnel evacuation path and time are dynamically generated; and real-time data interaction between the Star-CCM + and the AnyLogic is realized through a Java script, and an evacuation strategy is dynamically adjusted. According to the method, millisecond-level dynamic coupling of harmful gas diffusion and personnel evacuation is achieved, closed-loop feedback is formed through real-time data interaction, a high-precision modeling technology is adopted, the building streaming effect and personnel behavior response are accurately simulated, parameterized rapid switching is supported, quantitative decision support is provided, and simulation precision and response speed are improved.

Description

Technical Field

[0001] The present invention relates to the field of fluid dynamics technology, and in particular to a fluid-evacuation multimodal simulation method and system for preventing and controlling harmful gases in densely populated, large spaces. Background Art

[0002] As key technologies for disaster emergency management, fluid dynamics simulation and evacuation simulation have significant application value in fields such as rail transit. Terminals are typically densely populated, large spaces, where safety and emergency management capabilities are directly linked to operational efficiency. Current research focuses on optimization in a single area, such as fluid dynamics simulation or evacuation modeling. Cross-modal collaborative simulation technology is still immature, limiting the accuracy of dynamic analysis in complex scenarios.

[0003] Current research on the diffusion of harmful gases mostly uses CFD simulation technology (such as Fluent and OpenFOAM), focusing on analyzing the impact of ventilation systems on pollutant transport. Existing results are concentrated in closed spaces such as subways and tunnels, and lack targeted analysis of the unique risk characteristics of terminal buildings. The terminal building's cantilevered structure (average floor height 18-24 meters) causes the vertical diffusion rate of harmful gases to be 3-5 times faster than that of subway stations, while the population density in bottleneck areas such as waiting areas (4-6 people / ㎡) is significantly higher than that of conventional transportation hubs. In addition, although digital twin technology can construct high-precision fluid models, its multi-physics field coupling analysis mainly serves equipment operation and maintenance, and does not involve real-time decision support for personnel evacuation.

[0004] When it comes to evacuation modeling, traditional approaches rely on static scenario assumptions and empirical parameters. For example, cellular automaton-based models (such as PE-3D-SHEM) optimize stair evacuation efficiency through physical exertion parameters but fail to integrate dynamic environmental factors such as hazardous gas diffusion or air flow. While commercial software such as Pathfinder can simulate individual behavior, its evacuation path planning is still based on fixed environmental parameters and cannot reflect the real-time impact of hazardous gas flow fields on visibility and thermal comfort during terrorist attacks. Recent research has attempted to introduce deep reinforcement learning into evacuation decision-making, but this has been limited to theoretical verification and has yet to achieve data interoperability with fluid simulation.

[0005] The limitations of existing technologies are reflected in two aspects: First, single-domain models have difficulty capturing the coupled effects of fluid flow and evacuation. For example, the spread of fire smoke can significantly change the feasibility of evacuation routes, and traditional evacuation models do not integrate real-time fluid data, leading to biased risk assessments. Second, cross-platform collaboration is inefficient. Most studies use offline data exchange modes (such as PyroSim and Pathfinder co-simulation), and their periodic data transmission cannot meet the real-time requirements of emergency response. Summary of the Invention

[0006] In view of the above-mentioned problems, the present invention is proposed.

[0007] Therefore, the technical problems solved by the present invention are: the existing personnel evacuation modeling method has the problem that the single domain model is difficult to capture the coupling effect of fluid and evacuation, the cross-platform collaboration is inefficient, and how to dynamically adjust the personnel evacuation path and time when harmful gases diffuse.

[0008] To address the aforementioned technical problems, the present invention provides the following technical solutions: a multimodal fluid-evacuation simulation method for controlling hazardous gases in densely populated, large spaces. The method includes constructing a fluid simulation model using a fluid simulation tool to quantify the diffusion rate and range of hazardous gases and determine their three-dimensional spatiotemporal evolution patterns. An evacuation simulation model is constructed using AnyLogic to dynamically generate evacuation routes and times. JavaScript is used to implement real-time data interaction between Star-CCM+ and AnyLogic to dynamically adjust evacuation routes. The fluid simulation tools include Space Claim, which constructs a three-dimensional geometric model of the building structure, and Star-CCM+, which divides the unstructured grid into grids and sets encrypted grids and prism layers for ventilation openings and hazardous gas source areas.

[0009] As a preferred embodiment of the multimodal fluid evacuation simulation method for controlling hazardous gases in densely populated, large spaces described in the present invention, constructing a fluid simulation model includes using Space Claim to construct a three-dimensional geometric model of the terminal, including key features such as the building structure, vents, obstacles, and waiting passengers; using Star-CCM+ to divide the unstructured grid, setting prismatic layers in key areas, setting boundary conditions for vents and hazardous gas source areas, and configuring a turbulence model and component transport equations.

[0010] As a preferred solution of the fluid-evacuation multimodal simulation method for preventing and controlling harmful gases in densely populated large spaces described in the present invention, the unstructured grid includes discretizing the model using a polyhedron network, setting local encrypted grids in the harmful gas source area and ventilation holes to capture high gradient changes, and setting an encrypted prism layer to improve the boundary layer resolution.

[0011] As an optimal solution of the fluid-evacuation multimodal simulation method for preventing and controlling harmful gases in densely populated large spaces described in the present invention, the turbulence model and component transport equation include: the turbulence model uses the averaged flow equation to simulate turbulence, and uses the transport equation of turbulent kinetic energy k and dissipation rate ε to describe the turbulence evolution process; the component transport equation expresses the diffusion law of harmful gases in the air, the component mass conservation equation is the core control equation describing the material transport and reaction process in a multi-component system, and the component mass change rate is expressed as the sum of the net diffusion flux entering through the boundary and the source term generated by the chemical reaction of the component.

[0012] As a preferred embodiment of the multimodal fluid-evacuation simulation method for controlling hazardous gases in densely populated, large spaces described in the present invention, constructing an evacuation simulation model includes importing a terminal building plan into the evacuation simulation tool AnyLogic, setting the initial distribution of personnel based on the plan, simulating personnel evacuation behavior in combination with the behavioral rules of the social force personnel model, constructing an evacuation simulation model, triggering evacuation commands based on the diffusion of hazardous gases, and conducting an emergency evacuation simulation.

[0013] As a preferred embodiment of the multimodal fluid-evacuation simulation method for controlling hazardous gases in densely populated, large spaces, the real-time data interaction involves extracting hazardous gas concentration field data from Star-CCM+ using Java scripts and transmitting this data to the evacuation simulation tool AnyLogic via the MQTT protocol. AnyLogic then adjusts the evacuation path algorithm in real time based on the received data and feeds the evacuation results back to the fluid simulation model.

[0014] As a preferred solution of the fluid-evacuation multimodal simulation method for preventing and controlling harmful gases in densely populated large spaces described in the present invention, the extracted harmful gas concentration field data includes obtaining the harmful gas concentration field data of a specified area from a simulation model, extracting the concentration values ​​of three-dimensional grid points, intercepting two-dimensional slices, formatting the grid index and concentration values ​​into CSV rows, writing them into a file, and sending the slice data to a message queue through the publishing function of the MQTT protocol.

[0015] As a preferred solution for the multimodal fluid-evacuation simulation method for controlling hazardous gases in densely populated, large spaces, the MQTT protocol uses EMQX or Mosquitto as a message broker, Star-CCM+ as a publisher, and AnyLogic as a data subscriber; hazardous gas data is received via the AnyLogic evacuation simulation model.

[0016] As a preferred solution to the multimodal fluid-evacuation simulation method for controlling hazardous gases in densely populated, large spaces, the dynamic adjustment of evacuation paths involves dynamically calculating safe and dangerous areas based on hazardous gas concentration data received by AnyLogic, generating optimal evacuation paths using a shortest path algorithm, and adjusting path weights in real time based on congestion.

[0017] Another objective of this invention is to provide a multimodal fluid-evacuation simulation system for controlling hazardous gases in densely populated, large spaces. This system, enabled by JavaScript, enables real-time data interaction between Star-CCM+ and AnyLogic, dynamically adjusting evacuation routes. This system addresses the minute-level delays associated with one-way data transmission in current evacuation modeling.

[0018] As a preferred solution of the fluid-evacuation multimodal simulation system for preventing and controlling harmful gases in densely populated and large spaces described in the present invention, the system comprises a fluid simulation module, an evacuation simulation module, and a data interaction module; the fluid simulation module comprises a 3D geometric model construction module and an unstructured grid division module, the 3D geometric model construction module is used to construct a 3D geometric model of the terminal using Space Claim, including key features of the building structure, vents, obstacles, and waiting passengers, and import the complete geometric model into Star-CCM+ for fluid dynamics modeling, the unstructured grid division module 102 is used to divide the structured polyhedron grid used in Star-CCM+, set different encrypted grids and encrypted prism layers for key parts, set boundary conditions, select turbulence models and group transport equations to establish a harmful gas diffusion simulation model, output harmful gas concentration distribution data in real time by defining monitoring points and observation surfaces, and derive the fluid dynamics law of harmful gas diffusion through harmful gas diffusion fluid simulation using Star-CCM+; the evacuation simulation module is used to draw a terminal floor plan and set the initial distribution of personnel in AnyLogic, and construct The evacuation simulation model imports the behavioral rules of the social force personnel model, triggers evacuation instructions based on the harmful gas diffusion simulation results, and analyzes the personnel evacuation path selection and time distribution characteristics through simulation. The data interaction module is used to develop an MQTT real-time data interface based on Java script, establish a harmful gas diffusion data acquisition module, deploy an MQTT message broker for simulation platform data communication, use Star-CCM+ as the publisher to push harmful gas concentration field data, and use AnyLogic as the subscriber to receive data. The evacuation control module is developed in AnyLogic to dynamically adjust the evacuation path strategy based on the real-time harmful gas concentration. A parameterized configuration module is constructed to switch the harmful gas characteristics and building topology structure on demand, forming a closed-loop feedback system for harmful gas diffusion and personnel evacuation paths.

[0019] A computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement a fluid-evacuation multimodal simulation method for preventing and controlling harmful gases in a large and densely populated space.

[0020] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a fluid-evacuation multimodal simulation method for preventing and controlling harmful gases in a large, densely populated space.

[0021] Beneficial effects of the present invention: The present invention provides a fluid-evacuation multimodal simulation method for controlling harmful gases in densely populated, large spaces. The method constructs a fluid simulation model based on a fluid simulation tool, quantifies the diffusion rate and range of harmful gases, and obtains three-dimensional spatiotemporal evolution laws. The method can quantify the diffusion rate and impact range of harmful gases, accurately depict the three-dimensional spatiotemporal evolution laws of the harmful gas concentration field, and reduce data errors. An evacuation simulation model is constructed using the AnyLogic tool to dynamically generate personnel evacuation paths and times. The method can switch the physical properties of harmful gases and the building topology as needed, quickly generate matching emergency plans, and implement real-time data interaction between Star-CCM+ and AnyLogic through Java scripts. The evacuation path is dynamically adjusted, which has engineering implementation advantages, reduces the secondary pollution area, and supports dynamic optimization of emergency strategies. The present invention achieves better results in high-precision simulation evacuation modeling, dynamic coupling of real-time data, and flexible adaptation to multiple scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0023] Figure 1 This is an overall flow chart of a multimodal simulation method for fluid-evacuation for preventing and controlling harmful gases in crowded, large spaces, provided as a first embodiment of the present invention.

[0024] Figure 2 A schematic diagram of a three-dimensional geometric model of an airport terminal, providing a fluid-evacuation multimodal simulation method for preventing and controlling harmful gases in crowded, large spaces, provided as a first embodiment of the present invention.

[0025] Figure 3 Schematic diagram of Star-CCM+ model selection for a fluid-evacuation multimodal simulation method for preventing and controlling harmful gases in crowded and large spaces, provided as a first embodiment of the present invention.

[0026] Figure 4 Schematic diagram of an AnyLogic evacuation model for a multimodal fluid-evacuation simulation method for controlling hazardous gases in crowded, large spaces, according to the first embodiment of the present invention.

[0027] Figure 5 This is an overall flow chart of a fluid-evacuation multimodal simulation system for preventing and controlling harmful gases in crowded and large spaces, provided as a second embodiment of the present invention. DETAILED DESCRIPTION

[0028] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without creative work should fall within the scope of protection of the present invention.

[0029] Example 1, with reference to Figures 1-4 , which is an embodiment of the present invention, provides a multimodal simulation method for fluid-evacuation for preventing and controlling harmful gases in densely populated and large spaces, including:

[0030] S1: Build a fluid simulation model based on fluid simulation tools to quantify the diffusion rate and range of harmful gases and obtain the three-dimensional spatiotemporal evolution law.

[0031] Furthermore, building the fluid simulation model involves constructing a 3D geometric model of the terminal using Space Claim, including key features such as the building structure, vents, obstacles, and waiting passengers. Using Star-CCM+ to create an unstructured mesh, encrypting key areas with prismatic layers, setting boundary conditions for vents and hazardous gas source areas, and configuring a turbulence model and component transport equations.

[0032] The sample model is divided into two sections, one section is 160m long and 41.6m wide, and the other section is 76.8m long and 48.1m wide. It contains 12 commercial buildings and two elevators, 247 air-conditioning outlets, 8 air-conditioning return outlets and 1604 passengers. Figure 2 , Schematic diagram of the three-dimensional geometric model of the terminal.

[0033] Set the turbulence model and component transport equation, select the k-ε turbulence model for harmful gas diffusion fluid simulation, the specific model selection reference Figure 3 , Schematic diagram of Star-CCM+ model selection.

[0034] It should be noted that the unstructured grid includes the use of polyhedron networks to discretize the model, setting up local encrypted grids in the harmful gas source area and ventilation outlets to capture high gradient changes, and setting up encrypted prism layers to improve the boundary layer resolution.

[0035] It should also be noted that the turbulence model and component transport equation include: the turbulence model uses the averaged flow equation to simulate turbulence, and uses the transport equation of turbulent kinetic energy k and dissipation rate ε to describe the turbulence evolution process.

[0036] The component transport equation describes the diffusion law of harmful gases in the air. The component mass conservation equation is the core control equation describing the material transport and reaction process in a multi-component system. The component mass change rate is expressed as the sum of the net diffusion flux entering through the boundary and the source term generated by the chemical reaction of the component.

[0037] The turbulence model is expressed as:

[0038]

[0039] in: is the partial derivative with respect to time, is the partial derivative with respect to time, ρ is the density of the mixed fluid, k is the turbulent kinetic energy, is the divergence operator, u is the time-averaged velocity vector, μ is the fluid dynamic viscosity, μ t is the turbulent viscosity, σ k is the turbulent Prandtl number, is the spatial gradient of turbulent kinetic energy k, P k is the turbulent kinetic energy generation term, ρε is the turbulent kinetic energy dissipation term, ε is the turbulent kinetic energy dissipation rate, σ ε is the dissipation rate Prandtl number, is the spatial gradient of the dissipation rate ε, C ε1 、C ε2 is an empirical constant.

[0040] The component transport equation is expressed as:

[0041]

[0042] in, is the partial derivative with respect to time, is the partial derivative with respect to time, ρ is the density of the mixed fluid, Y s is the mass fraction of group s, v is the velocity vector, D s is the molecular diffusion coefficient of component s, S s is the mass source term caused by chemical reaction.

[0043] It should also be noted that by constructing a 3D geometric model of the terminal based on Space Claim and using Star-CCM+ to divide the unstructured grid and adopt polyhedron meshing, the flow effect of harmful gases in heterogeneous structures can be accurately simulated, providing a reliable geometric basis for quantifying the diffusion rate and impact range.

[0044] S2: Use AnyLogic to build an evacuation simulation model and dynamically generate evacuation routes and times.

[0045] Furthermore, building an evacuation simulation model involved importing the terminal building floor plan into the evacuation simulation tool AnyLogic, setting the initial distribution of personnel based on the floor plan, simulating personnel evacuation behavior by combining the behavioral rules of the social force personnel model, building an evacuation simulation model, triggering evacuation commands based on the diffusion of harmful gases, and conducting an emergency evacuation simulation.

[0046] It should be noted that the evacuation simulation model was constructed using AnyLogic tools, and a harmful gas stimulus response model was established to quantify the nonlinear relationship between cough frequency, visual field obstruction rate, and movement speed. This, combined with the fluid simulation model, can restore the coupling effect between the harmful gas diffusion process and the crowd's panic psychology, significantly reducing errors. Figure 4 Schematic diagram of the AnyLogic evacuation model. The upper part is the top view of the model, and the lower part is the evacuation simulation model.

[0047] It should also be noted that by constructing a high-precision evacuation simulation model in AnyLogic, dynamic simulation and optimization of personnel evacuation behavior under hazardous gas diffusion were achieved. The initial personnel distribution was set based on the terminal floor plan, and personnel movement was restored using the social force personnel model to trigger the evacuation mechanism. This effectively addressed technical issues such as insufficient consideration of environmental factors in evacuation simulation and oversimplified personnel behavior modeling. This model accurately predicted evacuation bottlenecks and optimized emergency response strategies, providing a scientific basis for decision-making in the prevention and control of hazardous gases in large spaces.

[0048] S3: Real-time data interaction between Star-CCM+ and AnyLogic was achieved through Java scripts to dynamically adjust evacuation routes.

[0049] Furthermore, real-time data interaction involves extracting hazardous gas concentration field data from Star-CCM+ using Java scripts and transmitting this data to the evacuation simulation tool AnyLogic via the MQTT protocol. AnyLogic then adjusts the evacuation path algorithm in real time based on the received data and feeds the evacuation results back to the fluid simulation model.

[0050] It should be noted that the extracted harmful gas concentration field data includes obtaining the harmful gas concentration field data of the specified area from the simulation model, extracting the concentration value of the three-dimensional grid point, intercepting the two-dimensional slice, formatting the grid index and concentration value into a CSV row, writing it to the file, and sending the slice data to the message queue through the publishing function of the MQTT protocol.

[0051] It should also be noted that the MQTT protocol includes using EMQX or Mosquitto as a message broker, Star-CCM+ as a publisher, and AnyLogic as a data subscriber; hazardous gas data is received through the AnyLogic evacuation simulation model.

[0052] It should also be noted that the dynamic adjustment of evacuation routes involves dynamically calculating safe and dangerous areas based on hazardous gas concentration data received by AnyLogic, generating the optimal evacuation route using a shortest path algorithm, and adjusting the path weights in real time based on congestion.

[0053] It should also be noted that a real-time, two-way data communication interface is constructed using Java script, enabling millisecond-level dynamic coupling of hazardous gas diffusion simulation and evacuation simulation. Compared to the minute-level delay (typically 5-10 minutes) caused by one-way data transmission in traditional independent simulation modes, this invention significantly reduces response latency, enabling a closed-loop feedback loop between changes in hazardous gas concentration fields and adjustments to evacuation routes, ensuring precise synchronization of emergency simulation results with the actual scenario timeline.

[0054] Example 2, reference Figure 5 , which is an embodiment of the present invention, provides a fluid-evacuation multimodal simulation system for preventing and controlling harmful gases in densely populated and large spaces, including a fluid simulation module 100, an evacuation simulation module 200, and a data interaction module 300.

[0055] Among them, S4: Fluid Simulation Module 100 includes a 3D Geometric Model Construction Module 101 and an Unstructured Grid Division Module 102. The 3D Geometric Model Construction Module 101 is used to use Space Claim to construct a 3D geometric model of the terminal, including key features such as building structure, vents, obstacles, and waiting passengers, and import the complete geometric model into Star-CCM+ for fluid dynamics modeling. The Unstructured Grid Division Module 102 is used to perform structured polyhedral grid division used in Star-CCM+, set different encrypted grids and encrypted prism layers for key parts, set boundary conditions, select turbulence models and group transport equations to establish a harmful gas diffusion simulation model, and output harmful gas concentration distribution data in real time by defining monitoring points and observation surfaces. The harmful gas diffusion fluid simulation is performed through Star-CCM+ to obtain the fluid dynamics law of harmful gas diffusion.

[0056] S5: Evacuation Simulation Module 200 is used to draw the terminal floor plan and set the initial personnel distribution in AnyLogic, construct an evacuation simulation model, import the behavioral rules of the social force personnel model, trigger evacuation instructions based on the harmful gas diffusion simulation results, and analyze the personnel evacuation path selection and time distribution characteristics through simulation.

[0057] S6: Data Interaction Module 300 is used to develop an MQTT real-time data interface based on Java script, establish a hazardous gas diffusion data collection module, deploy an MQTT message broker for simulation platform data communication, use Star-CCM+ as the publisher to push hazardous gas concentration field data, and use AnyLogic as the subscriber to receive data. An evacuation control module is developed in AnyLogic to dynamically adjust evacuation path strategies based on real-time hazardous gas concentrations. A parameterized configuration module is constructed to switch hazardous gas characteristics and building topology structures on demand, forming a closed-loop feedback system for hazardous gas diffusion and personnel evacuation paths.

[0058] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program code.

[0059] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0060] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0061] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having logic gate circuits for implementing logical functions on data signals, an application-specific integrated circuit having suitable combinational logic gate circuits, a programmable gate array (PGA), a field-programmable gate array (FPGA), etc. It should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention and are not intended to be limiting. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced with equivalents without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications should be encompassed by the claims of the present invention.

Claims

1. A multimodal simulation method for fluid-evacuation for preventing and controlling harmful gases in densely populated and large spaces, characterized in that: include: Build a fluid simulation model based on fluid simulation tools to quantify the diffusion rate and range of harmful gases and obtain the three-dimensional spatiotemporal evolution law; Using AnyLogic tools to build an evacuation simulation model, dynamically generating evacuation routes and times; Real-time data interaction between Star-CCM+ and AnyLogic was achieved through Java scripts, allowing for dynamic adjustment of evacuation routes. Fluid simulation tools include Space Claim and Star-CCM+. Space Claim is used to construct a three-dimensional geometric model of the building structure, while Star-CCM+ is used to divide the unstructured grid and set encrypted grids and encrypted prism layers for ventilation openings and harmful gas source areas.

2. The multimodal simulation method for fluid-evacuation for preventing and controlling harmful gases in densely populated, large spaces according to claim 1, characterized in that: The constructing of the fluid simulation model includes: A 3D geometric model of the terminal was constructed using Space Claim, including key features such as the building structure, vents, obstacles, and waiting passengers. Star-CCM+ was used to create an unstructured mesh, with prismatic layers added to key areas. Boundary conditions were set for vents and hazardous gas source areas, and a turbulence model and component transport equations were configured.

3. A multimodal simulation method for fluid-evacuation for preventing and controlling harmful gases in densely populated, large spaces according to claim 1 or 2, characterized in that: The unstructured grid includes, The model is discretized using a polyhedron network. Locally encrypted grids are set in the harmful gas source area and ventilation outlets to capture high gradient changes, and an encrypted prism layer is set to improve the boundary layer resolution.

4. The multimodal simulation method for fluid-evacuation for preventing and controlling harmful gases in densely populated, large spaces according to claim 2, characterized in that: The turbulence model and component transport equations include, The turbulence model uses the averaged flow equation to simulate turbulence and uses the transport equation of turbulent kinetic energy k and dissipation rate ε to describe the turbulence evolution process; The component transport equation describes the diffusion law of harmful gases in the air. The component mass conservation equation is the core control equation describing the material transport and reaction process in a multi-component system. The component mass change rate is expressed as the sum of the net diffusion flux entering through the boundary and the source term generated by the chemical reaction of the component.

5. The multimodal simulation method for fluid-evacuation for preventing and controlling harmful gases in a densely populated, large space as claimed in claim 4, characterized in that: The construction of the evacuation simulation model includes: The terminal building floor plan was imported into the evacuation simulation tool AnyLogic. The initial distribution of personnel was set based on the floor plan. Evacuation behavior was simulated using the behavioral rules of the social force personnel model. An evacuation simulation model was constructed, and evacuation commands were triggered based on the diffusion of hazardous gases to simulate emergency evacuations.

6. A multimodal simulation method for fluid-evacuation for preventing and controlling harmful gases in a densely populated, large space as claimed in claim 1 or 5, characterized in that: The real-time data interaction includes: Hazardous gas concentration field data extracted from Star-CCM+ using Java scripts was transmitted to the evacuation simulation tool AnyLogic via the MQTT protocol. AnyLogic adjusted the evacuation path algorithm in real time based on the received data and fed the evacuation results back to the fluid simulation model.

7. The multimodal simulation method for fluid-evacuation for preventing and controlling harmful gases in a densely populated, large space as claimed in claim 6, characterized in that: The extracted harmful gas concentration field data includes: Obtain the hazardous gas concentration field data for the specified area from the simulation model, extract the concentration values ​​at the 3D grid points, cut out the 2D slices, format the grid index and concentration values ​​into CSV rows, write them to a file, and send the slice data to the message queue through the MQTT protocol publishing function.

8. The multimodal simulation method for fluid-evacuation for preventing and controlling harmful gases in a densely populated, large space as claimed in claim 7, characterized in that: The MQTT protocol includes, Use EMQX or Mosquitto as the message broker, Star-CCM+ as the publisher, and AnyLogic as the data subscriber; receive hazardous gas data through the AnyLogic evacuation simulation model.

9. The multimodal simulation method for fluid-evacuation for preventing and controlling harmful gases in a densely populated, large space as claimed in claim 1, characterized in that: The dynamic adjustment of the evacuation path includes: Using the hazardous gas data received by AnyLogic, we dynamically calculated safe and dangerous areas for hazardous gas concentration distribution. We then used the shortest path algorithm to generate the optimal evacuation route, adjusting the path weights in real time based on congestion.

10. A multimodal simulation system for flow-evacuation to prevent and control harmful gases in densely populated, large spaces, characterized by: It includes a fluid simulation module (100), an evacuation simulation module (200), and a data interaction module (300); The fluid simulation module (100) includes a three-dimensional geometric model construction module (101) and an unstructured grid division module (102). The three-dimensional geometric model construction module (101) is used to use Space Claim to construct a three-dimensional geometric model of the terminal, including key features of the building structure, vents, obstacles, and waiting passengers, and import the complete geometric model into Star-CCM+ for fluid dynamics modeling. The unstructured grid division module (102) is used to divide the structured polyhedron grid used in Star-CCM+, set different encrypted grids and encrypted prism layers for key parts, set boundary conditions, select a turbulence model and a group transport equation to establish a harmful gas diffusion simulation model, and output harmful gas concentration distribution data in real time by defining monitoring points and observation surfaces. The harmful gas diffusion fluid simulation is performed by Star-CCM+ to obtain the fluid dynamics law of harmful gas diffusion. The evacuation simulation module (200) is used to draw a terminal floor plan and set the initial distribution of personnel in AnyLogic, build an evacuation simulation model, import the behavior rules of the social force personnel model, trigger the evacuation command based on the simulation results of harmful gas diffusion as a trigger condition, and analyze the personnel evacuation path selection and time distribution characteristics through simulation; The data interaction module (300) is used to develop an MQTT real-time data interface based on Java script, establish a harmful gas diffusion data acquisition module, deploy an MQTT message agent as simulation platform data communication, use Star-CCM+ as a publishing end to push harmful gas concentration field data, and use AnyLogic as a subscription end to receive data; develop an evacuation control module in AnyLogic, dynamically adjust the evacuation path strategy according to the real-time harmful gas concentration, build a parameterized configuration module, switch the harmful gas characteristics and building topology as needed, and form a closed-loop feedback system for harmful gas diffusion and personnel evacuation paths.

11. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of a fluid-evacuation multimodal simulation method for preventing and controlling harmful gases in a large and densely populated space according to any one of claims 1 to 9 are implemented.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a fluid-evacuation multimodal simulation method for preventing and controlling harmful gases in a large, densely populated space according to any one of claims 1 to 9 are implemented.

Images