Aerosol flow simulation method and simulation device, electronic equipment and storage medium

Abstract

The present application relates to the technical field of heating-not-burning atomization equipment, and in particular to an aerosol flow simulation method and simulation device, electronic equipment and storage medium. The method comprises: simulating the physical properties and initial state of the particulate matter in the aerosol, as well as the flow information of the gaseous matter in the aerosol; establishing a discrete phase model of the particulate matter according to the physical properties and initial state of the particulate matter; wherein the discrete phase model is used to determine the movement information of the particulate matter over time; establishing a porous medium non-equilibrium state model of the aerosol according to the flow information of the gaseous matter; wherein the porous medium non-equilibrium state model is used to determine the migration information of the gaseous matter in the porous medium over time; coupling the discrete phase model and the porous medium non-equilibrium state model to determine the target concentration of each component in the aerosol. The present method can simulate the interaction between the particulate matter and the gaseous matter in the aerosol, and improve the accuracy of calculating the target concentration.

Description

Technical Field

[0001] The present application relates to the technical field of heat-not-burn atomization equipment, and in particular to an aerosol flow simulation method and simulation device, electronic equipment and storage medium. Background Art

[0002] Traditional simulations of the flow and diffusion of aerosols in the nozzles of heat-not-burn devices or in the aerosol-generating matrix inside are mostly based on the aerosol material composition mass transfer equation of the pure air model. However, since the aerosol composition generated by heating the aerosol-generating matrix is ​​relatively complex and has different phases, such as the presence of particles and gas, the aerosol material composition mass transfer equation does not take into account the transmission distribution of particles, and the simulation results are relatively rough and inaccurate.

[0003] Therefore, how to accurately simulate the flow of aerosol in heat-not-burn equipment is an urgent problem to be solved. Summary of the invention

[0004] Based on this, it is necessary to provide an aerosol flow simulation method and simulation device, electronic equipment and storage medium to address the above technical problems.

[0005] In a first aspect, the present application provides an aerosol flow simulation method, the method comprising:

[0006] Simulating the physical properties and initial state of the particulate matter in the aerosol, and the flow information of the gaseous matter in the aerosol; wherein the aerosol is generated by heating the aerosol generating matrix by the heating element of the heat-not-burn atomization device; the initial state includes at least one of the position, velocity and temperature of the particulate matter at the initial moment;

[0007] According to the physical properties and the initial state of the granular material, a discrete phase model of the granular material is established; wherein the discrete phase model is used to determine the movement information of the granular material changing with time;

[0008] According to the flow information of the gas phase substance, a porous medium non-equilibrium state model of the aerosol is established; wherein the porous medium non-equilibrium state model is used to determine the migration information of the gas phase substance in the porous medium that changes with time;

[0009] The discrete phase model and the porous medium non-equilibrium model are coupled to determine the target concentration of each component in the aerosol; wherein the components include the particulate matter and the gaseous matter.

[0010] In one embodiment, the step of establishing a discrete phase model of the particulate matter according to the physical properties and initial state of the particulate matter in the aerosol comprises:

[0011] The discrete phase model of the particle-phase material is determined according to the mass, velocity vector, fluid resistance and other forces of each particle-phase material in the aerosol; wherein the other forces include at least one of gravity, collision force and electromagnetic force.

[0012] In one embodiment, establishing a porous medium non-equilibrium state model of the aerosol according to the flow information of the aerosol includes:

[0013] The porous medium non-equilibrium model of the aerosol is determined according to the concentration of the i-th component, the generation / consumption rate of the i-th component, the flow velocity and the effective diffusion coefficient of the aerosol; wherein i is a positive integer.

[0014] In one embodiment, coupling the discrete phase model and the porous medium non-equilibrium model to determine the target concentration of each component in the aerosol includes:

[0015] A coupling equation is established according to the influence parameter of the mth particle-phase substance on the nth gas-phase substance, the concentration change value of the nth gas-phase substance and the coupling coefficient; wherein both m and n are positive integers; and the coupling coefficient indicates the interaction strength between the particle-phase substance and the gas-phase substance;

[0016] According to the coupled equation, the target concentration of each component in the aerosol is determined.

[0017] In one embodiment, the expression of the discrete phase model is as follows:

[0018] Among them, m p Indicates the mass of the particulate matter; u p indicates the velocity vector of the particle phase material; t indicates time; F drag Indicates the fluid resistance of the fluid to the particle phase; F other Indicate the other forces.

[0019] In one embodiment, the expression of the porous medium non-equilibrium model is as follows:

[0020] Among them, C i indicates the concentration of the i-th component; u indicates the flow rate of the aerosol; t indicates time; D eff indicates the effective diffusion coefficient; R i Indicates the generation / consumption rate of the ith component.

[0021] In one embodiment, the coupling coefficient includes a first coupling coefficient and a second coupling coefficient; the coupling equation is expressed as follows:

[0022] Among them, C n Indicates the target concentration of the nth component; α m indicates the first coupling coefficient; t indicates time; Φ m β indicates the influence parameter of the mth particle-phase substance on the nth gas-phase substance; n Indicates the second coupling coefficient; θ n Indicates the concentration change value of the nth gas-phase substance.

[0023] In a second aspect, the present application also provides an aerosol flow simulation device, the device comprising:

[0024] A simulation module, for simulating the physical properties and initial state of the particulate matter in the aerosol, and the flow information of the gaseous matter in the aerosol; wherein the aerosol is generated by heating the aerosol generating matrix by the heating element of the heat-not-burn atomization device; the initial state includes at least one of the position, velocity and temperature of the particulate matter at the initial moment;

[0025] A discrete phase module, used to establish a discrete phase model of the granular material according to the physical properties and the initial state of the granular material; wherein the discrete phase model is used to determine the motion information of the granular material changing with time;

[0026] A non-equilibrium state module, used to establish a porous medium non-equilibrium state model of the aerosol according to the flow information of the gas phase substance; wherein the porous medium non-equilibrium state model is used to determine the migration information of the gas phase substance in the porous medium that changes with time;

[0027] A coupling module is used to couple the discrete phase model and the porous medium non-equilibrium model to determine the target concentration of each component in the aerosol; wherein the components include the particulate matter and the gaseous matter.

[0028] In a third aspect, the present application further provides an electronic device, including:

[0029] a memory for storing a processor computer program;

[0030] Processor; wherein the processor is configured to: implement the method described in any embodiment of the present application when executing the computer program.

[0031] In a fourth aspect, the present application further provides a computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the method described in any embodiment of the present application is implemented.

[0032] In the above-mentioned aerosol flow simulation method, the motion information of the particulate matter in the aerosol changing with time is determined by the discrete phase model, so that the motion trajectory of the particulate matter can be accurately tracked and the deposition phenomenon over time can be simulated; the migration information of the gaseous matter in the porous medium with time can be determined by the porous medium non-equilibrium model, and the influence of diffusion, convection, adsorption and chemical reaction when the aerosol is transmitted in the porous medium can be fully considered; by coupling the discrete phase model and the porous medium non-equilibrium model, the interaction between the particulate matter and the gaseous matter in the aerosol can be accurately simulated, thereby improving the accuracy of calculating the target concentration of each component in the aerosol. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 is a schematic flow chart of an aerosol flow simulation method according to an exemplary embodiment;

[0034] Figure 2 is a schematic flow chart of an aerosol flow simulation method according to an exemplary embodiment;

[0035] Figure 3 is a schematic flow chart of an aerosol flow simulation method according to an exemplary embodiment;

[0036] Figure 4 is a structural block diagram of an aerosol flow simulation device according to an exemplary embodiment;

[0037] Figure 5 It is a diagram showing the internal structure of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0039] The terms "first", "second" and "third" in the embodiments of the present application are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, the features defined as "first", "second" and "third" may explicitly or implicitly include at least one of the features. In the description of the present application, "at least one" is used to indicate one or more; "multiple" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions. For example, a process, method, device, product or equipment that includes a series of steps or units is not limited to the listed steps or units, but optionally also includes steps or units that are not listed, or optionally also includes other steps or units inherent to these processes, methods, products or equipment.

[0040] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0041] The methods described in the embodiments of the present application can be applied to electronic devices; the electronic devices can be any mobile terminals or fixed terminals. The terminal can be a device that provides voice and / or data connectivity to a user. Exemplarily, the terminal can be an IoT terminal, such as a sensor device, a mobile phone (or a "cellular" phone, and a computer with an IoT terminal, for example, a fixed, portable, pocket-sized, handheld, computer-built-in, or vehicle-mounted device.

[0042] In some embodiments, Figure 1 As shown, a method for simulating an aerosol flow is provided, the method comprising the following steps:

[0043] S101, simulating the physical properties and initial state of the particulate matter in the aerosol, and the flow information of the gaseous matter in the aerosol; wherein the aerosol is generated by heating the aerosol generating matrix by a heating element of a heat-not-burn atomizing device; and the initial state includes at least one of the position, velocity and temperature of the particulate matter at the initial moment.

[0044] In the embodiment of the present application, the particulate matter refers to tiny solid particles or liquid particles suspended in the gas.

[0045] In the embodiments of the present application, the gas phase substance refers to a chemical substance existing in a gaseous state.

[0046] In some embodiments, the physical properties of the particulate matter may include, but are not limited to, at least one of particle mass, particle diameter, particle density, particle shape, particle thermal conductivity, particle specific heat capacity, and particle radiation emissivity.

[0047] In some embodiments, the initial state of the particulate matter may also include, but is not limited to, the particle distribution and particle quantity of the particulate matter at the initial moment.

[0048] In some embodiments, the flow information of the gas phase material may include, but is not limited to, at least one of fluid density, fluid dynamic viscosity, fluid thermal conductivity, fluid specific heat capacity, and fluid temperature distribution.

[0049] In some embodiments, the heating element may include but is not limited to one of metal foil, ceramic heating rod / tube, graphite heating rod and composite heating element.

[0050] In some embodiments, the heating method of the heating element may include but is not limited to one of resistance heating, induction heating, microwave heating and infrared heating.

[0051] In some embodiments, a geometric model is established based on the geometric dimensions, structural parameters and material properties of the aerosol generating matrix; wherein the structural parameters may include but are not limited to at least one of density, porosity, pore size distribution, connectivity, thermal conductivity, specific heat capacity and compressibility; the material properties may include but are not limited to the components of the aerosol generating matrix and the component characteristics corresponding to each component; the geometric model is input into a simulation module, and the simulation software is used to simulate the aerosol generated by heating the aerosol generating matrix, the physical properties of the particulate matter, the initial state and the flow information of the gaseous matter during the flow of the aerosol generating matrix and / or in the nozzle of the heat-not-burn atomization device; alternatively, the initial state of the particulate matter may also be set.

[0052] S102, establishing a discrete phase model of the granular material according to the physical properties and the initial state of the granular material; wherein the discrete phase model is used to determine the movement information of the granular material that changes with time.

[0053] In the embodiments of the present application, a discrete phase model (DPM) is a numerical method for simulating the motion of particles or droplets in a fluid. DPM can be used to analyze the trajectory, velocity distribution, concentration distribution of particles in a gas or liquid, and the interaction between particles and walls or other particles.

[0054] S103, establishing a porous medium non-equilibrium model of the aerosol according to the flow information of the gas phase substance; wherein the porous medium non-equilibrium model is used to determine the migration information of the gas phase substance in the porous medium that changes with time.

[0055] In some embodiments, a porous media model is a mathematical and physical framework for describing the flow behavior of a fluid through a solid material with a porous structure. The porous media model includes equilibrium and non-equilibrium states. Since the traditional equilibrium model is difficult to capture the non-uniformity of the temperature of each region after the aerosol generating substrate is heated, the embodiment of the present application can well simulate the mass transfer and heat transfer process of the aerosol through the porous medium (for example, the aerosol generating substrate or the nozzle, etc.) through the porous media non-equilibrium model.

[0056] In the embodiment of the present application, the migration information of the gas-phase substance may include but is not limited to at least one of the concentration, temperature, flow velocity, generation or consumption rate of the gas-phase substance.

[0057] S104, coupling the discrete phase model and the porous medium non-equilibrium model to determine the target concentration of each component in the aerosol; wherein the components include the particulate matter and the gaseous matter.

[0058] In some embodiments, the electronic device can couple the discrete phase model and the porous medium non-equilibrium model through coupling equations; the discrete phase model is used to describe the movement, behavior and trajectory of particulate matter in the aerosol, and the porous medium non-equilibrium model is used to describe the mass transfer and heat transfer process of the aerosol in the porous medium structure.

[0059] In the above-mentioned aerosol flow simulation method, the motion information of the particulate matter in the aerosol changing with time is determined by the discrete phase model, so that the motion trajectory of the particulate matter can be accurately tracked and the deposition phenomenon over time can be simulated; the migration information of the gaseous matter in the porous medium with time can be determined by the porous medium non-equilibrium model, and the influence of diffusion, convection, adsorption and chemical reaction when the aerosol is transmitted in the porous medium can be fully considered; by coupling the discrete phase model and the porous medium non-equilibrium model, the interaction between the particulate matter and the gaseous matter in the aerosol can be accurately simulated, thereby improving the accuracy of calculating the target concentration of each component in the aerosol.

[0060] In some embodiments, establishing a discrete phase model of the particulate matter according to the physical properties and initial state of the particulate matter in the aerosol includes:

[0061] The discrete phase model of the particle-phase material is determined according to the mass, velocity vector, fluid resistance and other forces of each particle-phase material in the aerosol; wherein the other forces include at least one of gravity, collision force and electromagnetic force.

[0062] In the embodiment of the present application, fluid resistance refers to the resistance caused by the fluid to the relative motion of the particle phase material. The fluid resistance can be calculated according to Stokes' law or Newton's resistance formula.

[0063] In some embodiments, other forces may also include but are not limited to Brownian force, lift, etc.

[0064] In some embodiments, the discrete phase model is expressed as follows:

[0065] Among them, m p Indicates the mass of the particulate matter; u p indicates the velocity vector of the particle phase material; t indicates time; F drag Indicates the fluid resistance of the fluid to the particle phase; F other Indicate the other forces.

[0066] In the embodiments of the present application, by solving the momentum balance equation of the particle-phase matter in the discrete phase model, the motion trajectory, velocity change, acceleration and other characteristics of the particle-phase matter in the aerosol in the flow field can be accurately described, and the characteristics of the particle-phase matter can be quantified, which helps to understand how the particle-phase matter responds to external forces (such as fluid resistance, gravity, lift, etc.), and more accurately reflects the transmission and distribution of the particle-phase matter in the aerosol.

[0067] In some embodiments, establishing a porous medium non-equilibrium state model of the aerosol according to the flow information of the aerosol includes:

[0068] The porous medium non-equilibrium model of the aerosol is determined according to the concentration of the i-th component, the generation / consumption rate of the i-th component, the flow velocity and the effective diffusion coefficient of the aerosol; wherein i is a positive integer.

[0069] In the embodiments of the present application, the concentration may indicate a molar concentration or a mass fraction.

[0070] In the embodiment of the present application, the effective diffusion coefficient can characterize the transmission resistance of the aerosol in the porous medium structure. The effective diffusion coefficient can include the molecular diffusion coefficient and the turbulent diffusion coefficient.

[0071] In the embodiment of the present application, the generation / consumption rate may represent the generation / consumption rate of the i-th component due to chemical reactions or other source items.

[0072] In some embodiments, the expression of the porous medium non-equilibrium model is as follows:

[0073] Among them, C iindicates the concentration of the i-th component; u indicates the flow rate of the aerosol; t indicates time; D eff indicates the effective diffusion coefficient; R i Indicates the generation / consumption rate of the ith component.

[0074] It should be noted that is the convection term, which can characterize the concentration change of the i-th component caused by convection; is the diffusion term, which can characterize the migration of the i-th component under the concentration gradient through diffusion; R i is the source term, which can include all factors that may change the concentration of the ith component, such as chemical reactions, phase changes (evaporation, condensation), deposition of particulate matter, etc.

[0075] In the embodiments of the present application, the non-equilibrium model of the porous medium can be used to accurately simulate the mass transfer and heat transfer process of the aerosol in the porous medium structure, and the efficiency and direction of the heat and mass transfer inside the porous medium can be quantified. The influencing factors such as convection diffusion, molecular diffusion and surface adsorption are fully considered, providing a theoretical basis for optimizing the conversion efficiency and utilization rate of the aerosol generation matrix.

[0076] In some embodiments, Figure 2 As shown, the discrete phase model and the porous medium non-equilibrium model are coupled to determine the target concentration of each component in the aerosol, including:

[0077] S1041, establishing a coupling equation according to the influence parameter of the mth particle-phase substance on the nth gas-phase substance, the concentration change value of the nth gas-phase substance and the coupling coefficient; wherein both m and n are positive integers; and the coupling coefficient indicates the interaction strength between the particle-phase substance and the gas-phase substance;

[0078] S1042: Determine the target concentration of each component in the aerosol according to the coupling equation.

[0079] In the embodiments of the present application, the influencing parameter may characterize the degree of influence of the adsorption reaction, absorption reaction, catalytic reaction or formation of condensation nuclei produced by the particle phase substance on the gas phase substance.

[0080] In the embodiment of the present application, the coupling coefficient indicates the interaction strength between the particle phase material and the gas phase material. The coupling coefficient can be determined based on multiple influencing variables, such as the particle size, chemical composition and morphological structure of the particle phase material itself, the volatility, solubility and molecular polarity of the gas phase material itself, the contact time and contact area between the particle phase material and the gas phase material, and the diffusion rate of the gas phase material to the surface of the particle phase material.

[0081] In some embodiments, the coupling coefficient includes a first coupling coefficient and a second coupling coefficient; the coupling equation is expressed as follows:

[0082] Among them, C n Indicates the target concentration of the nth component; α m indicates the first coupling coefficient; t indicates time; Φ m β indicates the influence parameter of the mth particle-phase substance on the nth gas-phase substance; n Indicates the second coupling coefficient; θ n Indicates the concentration change value of the nth gas-phase substance.

[0083] In the embodiment of the present application, by coupling the discrete phase model and the porous medium non-equilibrium model through coupling equations, the interaction between the particulate matter and the gas phase matter in the aerosol can be accurately simulated, thereby improving the accuracy of calculating the target concentration of each component in the aerosol.

[0084] The present application also provides an application scenario, which applies the above-mentioned aerosol flow simulation method. Specifically, Figure 3 As shown, the steps of the sol flow simulation method in this application scenario are as follows:

[0085] S301, simulate the physical properties and initial state of the particle phase matter in the aerosol, as well as the flow information of the gas phase matter in the aerosol.

[0086] In an optional embodiment, the aerosol is generated by heating the aerosol-generating substrate by a heating element of a heat-free atomization device; the initial state includes at least one of the position, velocity and temperature of the particulate matter at the initial moment.

[0087] S302, establishing a discrete phase model of the granular material according to the physical properties and initial state of the granular material.

[0088] In an optional embodiment, a discrete phase model of the particle matter is determined based on the mass, velocity vector, fluid resistance and other forces of each particle matter in the aerosol; wherein the other forces include at least one of gravity, collision force and electromagnetic force; the discrete phase model is used to determine the motion information of the particle matter changing with time.

[0089] S303, establishing a porous medium non-equilibrium model of aerosol according to the flow information of gas phase substances.

[0090] In an optional embodiment, a porous medium non-equilibrium model of aerosol is determined based on the concentration of the i-th component, the generation / consumption rate of the i-th component, the flow velocity of the aerosol and the effective diffusion coefficient; wherein i is a positive integer; the porous medium non-equilibrium model is used to determine the migration information of gas-phase substances in the porous medium that changes with time.

[0091] S304, coupling the discrete phase model and the porous medium non-equilibrium model to determine the target concentration of each component in the aerosol.

[0092] In an optional embodiment, a coupling equation is established based on the influence parameters of the mth particulate matter on the nth gaseous matter, the concentration change value of the nth gaseous matter and the coupling coefficient; wherein m and n are both positive integers; the coupling coefficient indicates the interaction strength between the particulate matter and the gaseous matter; based on the coupling equation, the target concentration of each component in the aerosol is determined.

[0093] In the above-mentioned aerosol flow simulation method, the motion information of the particulate matter in the aerosol changing with time is determined by the discrete phase model, so that the motion trajectory of the particulate matter can be accurately tracked and the deposition phenomenon over time can be simulated; the migration information of the gaseous matter in the porous medium with time can be determined by the porous medium non-equilibrium model, and the influence of diffusion, convection, adsorption and chemical reaction when the aerosol is transmitted in the porous medium can be fully considered; by coupling the discrete phase model and the porous medium non-equilibrium model, the interaction between the particulate matter and the gaseous matter in the aerosol can be accurately simulated, thereby improving the accuracy of calculating the target concentration of each component in the aerosol.

[0094] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0095] Based on the same inventive concept, the embodiment of the present application also provides an aerosol flow simulation device for implementing the aerosol flow simulation method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more aerosol flow simulation device embodiments provided below can refer to the limitations of the aerosol flow simulation method above, and will not be repeated here.

[0096] In one embodiment, Figure 4 As shown, an aerosol flow simulation device is provided, the device comprising:

[0097] The simulation module 10 is used to simulate the physical properties and initial state of the particulate matter in the aerosol, and the flow information of the gaseous matter in the aerosol; wherein the aerosol is generated by heating the aerosol generating matrix by the heating element of the heat-not-burn atomization device; the initial state includes at least one of the position, velocity and temperature of the particulate matter at the initial moment;

[0098] The discrete phase module 20 is used to establish a discrete phase model of the particle-phase material according to the physical properties and the initial state of the particle-phase material; wherein the discrete phase model is used to determine the movement information of the particle-phase material changing with time;

[0099] The non-equilibrium module 30 is used to establish a porous medium non-equilibrium model of the aerosol according to the flow information of the gas phase substance; wherein the porous medium non-equilibrium model is used to determine the migration information of the gas phase substance in the porous medium that changes with time;

[0100] The coupling module 40 is used to couple the discrete phase model and the porous medium non-equilibrium model to determine the target concentration of each component in the aerosol; wherein the components include the particulate matter and the gaseous matter.

[0101] In some embodiments, the discrete phase module 20 is used to determine the discrete phase model of the particulate matter based on the mass, velocity vector, fluid resistance and other forces of each particulate matter in the aerosol; wherein the other forces include at least one of gravity, collision force and electromagnetic force.

[0102] In some embodiments, the non-equilibrium module 30 is used to determine the porous medium non-equilibrium model of the aerosol based on the concentration of the i-th component, the generation / consumption rate of the i-th component, the flow velocity and the effective diffusion coefficient of the aerosol; wherein i is a positive integer.

[0103] In some embodiments, the coupling module 40 is used to perform the following steps:

[0104] A coupling equation is established according to the influence parameter of the mth particle-phase substance on the nth gas-phase substance, the concentration change value of the nth gas-phase substance and the coupling coefficient; wherein both m and n are positive integers; and the coupling coefficient indicates the interaction strength between the particle-phase substance and the gas-phase substance;

[0105] According to the coupled equation, the target concentration of each component in the aerosol is determined.

[0106] In some embodiments, the discrete phase model is expressed as follows:

[0107] Among them, m p Indicates the mass of the particulate matter; u p indicates the velocity vector of the particle phase material; t indicates time; F drag Indicates the fluid resistance of the fluid to the particle phase; F other Indicate the other forces.

[0108] In some embodiments, the expression of the porous medium non-equilibrium model is as follows:

[0109] Among them, C i indicates the concentration of the i-th component; u indicates the flow rate of the aerosol; t indicates time; D eff indicates the effective diffusion coefficient; R i Indicates the generation / consumption rate of the ith component.

[0110] In some embodiments, the coupling coefficient includes a first coupling coefficient and a second coupling coefficient; the coupling equation is expressed as follows:

[0111] Among them, C n Indicates the target concentration of the nth component; α m indicates the first coupling coefficient; t indicates time; Φ m β indicates the influence parameter of the mth particle-phase substance on the nth gas-phase substance; n Indicates the second coupling coefficient; θ n Indicates the concentration change value of the nth gas-phase substance.

[0112] Each module in the control device of the above-mentioned atomization device can be implemented in whole or in part by software, hardware or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of the processor in the electronic device in the form of hardware, or can be stored in the memory of the electronic device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0113] In one embodiment, an electronic device is provided. The electronic device may be a terminal, and its internal structure diagram may be as follows: Figure 5 As shown. The electronic device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the electronic device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a scatter plot detection method is implemented. The display screen of the electronic device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the electronic device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the housing of the electronic device, or an external keyboard, touchpad or mouse, etc.

[0114] Those skilled in the art will understand that Figure 5 The structure shown in the figure is merely a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the electronic device to which the scheme of the present application is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0115] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0116] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.) and / or features involved in this application are all information, data and / or features authorized by the user or fully authorized by all parties.

[0117] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0118] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0119] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. An aerosol flow simulation method, characterized in that: The method comprises: Simulating the physical properties and initial state of the particulate matter in the aerosol, and the flow information of the gaseous matter in the aerosol; wherein the aerosol is generated by heating the aerosol generating matrix by the heating element of the heat-not-burn atomization device; the initial state includes at least one of the position, velocity and temperature of the particulate matter at the initial moment; According to the physical properties and the initial state of the granular material, a discrete phase model of the granular material is established; wherein the discrete phase model is used to determine the movement information of the granular material changing with time; According to the flow information of the gas phase substance, a porous medium non-equilibrium state model of the aerosol is established; wherein the porous medium non-equilibrium state model is used to determine the migration information of the gas phase substance in the porous medium that changes with time; The discrete phase model and the porous medium non-equilibrium model are coupled to determine the target concentration of each component in the aerosol; wherein the components include the particulate matter and the gaseous matter.

2. The method according to claim 1, characterized in that The step of establishing a discrete phase model of the particle phase material according to the physical properties and initial state of the particle phase material in the aerosol comprises: The discrete phase model of the particle-phase material is determined according to the mass, velocity vector, fluid resistance and other forces of each particle-phase material in the aerosol; wherein the other forces include at least one of gravity, collision force and electromagnetic force.

3. The method according to claim 1, characterized in that The step of establishing a porous medium non-equilibrium model of the aerosol according to the flow information of the aerosol comprises: The porous medium non-equilibrium model of the aerosol is determined according to the concentration of the i-th component, the generation / consumption rate of the i-th component, the flow velocity and the effective diffusion coefficient of the aerosol; wherein i is a positive integer.

4. The method according to claim 1, characterized in that The coupling of the discrete phase model and the porous medium non-equilibrium model to determine the target concentration of each component in the aerosol includes: A coupling equation is established according to the influence parameter of the mth particle-phase substance on the nth gas-phase substance, the concentration change value of the nth gas-phase substance and the coupling coefficient; wherein both m and n are positive integers; and the coupling coefficient indicates the interaction strength between the particle-phase substance and the gas-phase substance; According to the coupled equation, the target concentration of each component in the aerosol is determined.

5. The method according to claim 2, characterized in that: The expression of the discrete phase model is as follows: Among them, m p Indicates the mass of the particulate matter; u p indicates the velocity vector of the particle phase material; t indicates time; F drag Indicates the fluid resistance of the fluid to the particle phase; F other Indicate the other forces.

6. The method according to claim 3, characterized in that The expression of the porous medium non-equilibrium model is as follows: Among them, C i indicates the concentration of the i-th component; u indicates the flow rate of the aerosol; t indicates time; D eff indicates the effective diffusion coefficient; R i Indicates the generation / consumption rate of the ith component.

7. The method according to claim 4, characterized in that The coupling coefficient includes a first coupling coefficient and a second coupling coefficient; the coupling equation is expressed as follows: Among them, C n Indicates the target concentration of the nth component; α m indicates the first coupling coefficient; t indicates time; Φ m β indicates the influence parameter of the mth particle-phase substance on the nth gas-phase substance; n Indicates the second coupling coefficient; θ n Indicates the concentration change value of the nth gas-phase substance.

8. An aerosol flow simulation device, characterized in that: The device comprises: A simulation module, for simulating the physical properties and initial state of the particulate matter in the aerosol, and the flow information of the gaseous matter in the aerosol; wherein the aerosol is generated by heating the aerosol generating matrix by the heating element of the heat-not-burn atomization device; the initial state includes at least one of the position, velocity and temperature of the particulate matter at the initial moment; A discrete phase module, used to establish a discrete phase model of the granular material according to the physical properties and the initial state of the granular material; wherein the discrete phase model is used to determine the motion information of the granular material changing with time; A non-equilibrium state module, used to establish a porous medium non-equilibrium state model of the aerosol according to the flow information of the gas phase substance; wherein the porous medium non-equilibrium state model is used to determine the migration information of the gas phase substance in the porous medium that changes with time; A coupling module is used to couple the discrete phase model and the porous medium non-equilibrium model to determine the target concentration of each component in the aerosol; wherein the components include the particulate matter and the gaseous matter.

9. An electronic device, characterized in that: include: a memory for storing a processor computer program; Processor; wherein the processor is configured to: implement the method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The readable storage medium stores a computer program, wherein the computer program implements the method according to any one of claims 1 to 7 when executed by a processor.

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