KR102640561B1 - Apparatus for simulating aerosol and method thereof - Google Patents

Abstract

An aerosol simulation device and method are provided. An aerosol simulation device according to some embodiments of the present disclosure includes a data input unit that receives simulation basic data including structural data of a target aerosol-generating article, and a model that constructs a CFD (Computational Fluid Dynamics) model based on the simulation basic data. It may include a simulation unit that simulates the heat transfer phenomenon and aerosol flow phenomenon that appear in the target aerosol-generating article using the configuration unit and the configured CFD model. This aerosol simulation device can reduce human and time costs invested in research and development of aerosol-generating products by providing simulation functions for heat transfer phenomena and aerosol flow phenomena inside the product through a CFD model.

Description

Aerosol simulation device and method {APPARATUS FOR SIMULATING AEROSOL AND METHOD THEREOF}

The present disclosure relates to an aerosol simulation device and method. More specifically, it relates to a device capable of simulating aerosol phenomena occurring within an aerosol-generating article and a method performed in the device.

In recent years, there has been an increasing demand for alternative methods to overcome the disadvantages of regular cigarettes. For example, demand is increasing for devices that generate aerosols by electrically heating cigarettes (e.g. electronic cigarette devices) and cigarette sticks with new structures applied to the devices. Accordingly, research and development on cigarette-type aerosol generating devices and cigarette sticks is being actively conducted.

Typically, research and development for cigarette sticks proceeds in the following order: requirement setting, design, manufacturing and verification. For example, in the case of research and development to improve the atomization amount of cigarette sticks, research and development may be conducted in the following order: setting a target atomization amount, designing the structure of the cigarette stick, manufacturing, and verifying the atomization amount through smoking experiments. However, this research and development process sometimes requires repetitive manufacturing and actual experiments, which can significantly increase the human and time costs invested in research and development. For example, defects in the design are discovered only in the final verification stage, which may frequently result in the design and manufacture of cigarette sticks again.

Therefore, in order to reduce human and time costs invested in research and development and enhance the efficiency of research and development, a method that can simulate various aerosol phenomena within cigarette sticks is urgently needed.

The technical problem to be solved through several embodiments of the present disclosure is to provide a device that can simulate the heat transfer phenomenon and aerosol flow phenomenon that appear in an aerosol-generating article and a method performed in the device.

The technical problems of the present disclosure are not limited to the technical problems mentioned above, and other technical problems not mentioned can be clearly understood by those skilled in the art from the description below.

In order to solve the above technical problem, an aerosol simulation device according to some embodiments of the present disclosure includes a data input unit that receives simulation basic data including structural data of a target aerosol-generating article, and a CFD (CFD) based on the simulation basic data. It may include a model component that configures a Computational Fluid Dynamics (Computational Fluid Dynamics) model and a simulation unit that simulates the heat transfer phenomenon and aerosol flow phenomenon that appear in the target aerosol-generating article using the configured CFD model.

In some embodiments, the model constructor includes a grid generator that generates a calculation grid based on the structural data, a governing equation setting unit that sets the governing equation of the CFD model, and initial conditions and boundary conditions of the CFD model. It may include a condition setting unit to set.

In some embodiments, the condition setting unit may set boundary conditions of the wall related to the flow of the aerosol based on the structural data.

In some embodiments, the simulation basic data further includes puff data, and the condition setting unit sets a flow boundary condition for the aerosol based on the puff data, wherein the flow boundary condition is set from the target aerosol-generating article. It may be a boundary condition set at the downstream end area where the aerosol is discharged.

In some embodiments, the simulation basic data further includes a temperature profile of a heater that heats the target aerosol-generating article, and the condition setting unit may set a thermal boundary condition based on the temperature profile.

In some embodiments, the simulation basic data further includes data regarding the heating structure of the heater, and the condition setting unit is a boundary area where heat is transferred from the heater to the target aerosol-generating article based on the heating structure of the heater. can be determined, and the thermal boundary condition can be set in the determined boundary area.

In some embodiments, the governing equation setting unit sets the first governing equation and the second governing equation as the governing equation of the CFD model, and the simulation unit calculates the set first governing equation and the second governing equation by linking them. Simulating the flow phenomenon of the aerosol and the heat transfer phenomenon, the first governing equation may be an equation related to the flow of the aerosol, and the second governing equation may be an equation related to heat transfer within the target aerosol-generating article.

In some embodiments, the simulation unit derives a temperature distribution within the target aerosol-generating article by calculating the set governing equation according to the set initial conditions and the set boundary conditions within the generated calculation grid, and the derived result. Based on this, areas of the calculation grid where the temperature is below the standard value can be detected.

In some embodiments, a visualization unit may be further included to visualize the results of the simulation.

The aerosol simulation method according to some embodiments of the present disclosure for solving the above-mentioned technical problems includes the step of receiving basic simulation data including structural data of a target aerosol-generating article in an aerosol simulation method performed on a computing device. , configuring a CFD (Computational Fluid Dynamics) model based on the simulation basic data, and simulating the heat transfer phenomenon and aerosol flow phenomenon that appear in the target aerosol-generating article using the constructed CFD model. .

A computer program according to some embodiments of the present disclosure for solving the above-mentioned technical problem includes the steps of combining with a computing device and receiving simulation basic data including structural data of a target aerosol-generating article, and adding the simulation basic data to the simulation basic data. Storing in a computer-readable recording medium to execute the steps of constructing a CFD (Computational Fluid Dynamics) model based on the CFD model and simulating the heat transfer phenomenon and aerosol flow phenomenon that appear in the target aerosol-generating article using the constructed CFD model. It can be.

According to some embodiments of the present disclosure described above, an aerosol phenomenon generated from a target aerosol-generating article can be simulated through a CFD model. Accordingly, design results can be easily verified without manufacturing and testing target aerosol-generating products, and human and time costs invested in research and development of aerosol-generating products can be greatly reduced.

In addition, by linking and solving the governing equations for aerosol flow and the governing equations for heat transfer, the heat transfer phenomenon and aerosol flow phenomenon that appear in the target aerosol-generating article can be accurately simulated.

Additionally, by linking and solving a plurality of governing equations for aerosol flow, heat transfer, chemical reaction, and material transfer, various aerosol phenomena within aerosol-generating articles can be accurately simulated.

Additionally, the density of the computational grid can be dynamically adjusted based on the degree of variation in simulation variable values. For example, the density of calculation grid areas where the degree of variation in simulation variable values is large may increase, and the density of calculation grid areas where the degree of variation is small may be reduced. Accordingly, the computing cost invested in unimportant calculation grid areas may be increased. This can be reduced, and the accuracy of simulation can be improved for important computational grid areas.

The effects according to the technical idea of the present disclosure are not limited to the effects mentioned above, and other effects not mentioned can be clearly understood by those skilled in the art from the description below.

1 is an exemplary configuration diagram showing an aerosol simulation device according to some embodiments of the present disclosure.
FIG. 2 is an exemplary diagram for explaining the operation of a grid generator according to some embodiments of the present disclosure.
FIG. 3 is an exemplary diagram illustrating the linkage between the operation of the governing equation setting unit and the governing equations according to some embodiments of the present disclosure.
4 and 5 are exemplary diagrams for explaining the operation of a condition setting unit according to some embodiments of the present disclosure.
FIGS. 6 and 7 are exemplary diagrams for explaining the operation of a simulation unit according to some embodiments of the present disclosure.
8 to 10 illustrate simulation results visualized by a visualization unit according to some embodiments of the present disclosure.
11 is an example flowchart illustrating an aerosol simulation method according to some embodiments of the present disclosure.
12 illustrates an example computing device that can implement a simulation device according to some embodiments of the present disclosure.

Hereinafter, preferred embodiments of the present disclosure will be described in detail with reference to the attached drawings. The advantages and features of the present disclosure and methods for achieving them will become clear by referring to the embodiments described in detail below along with the accompanying drawings. However, the technical idea of the present disclosure is not limited to the following embodiments and may be implemented in various different forms. The following examples are merely intended to complete the technical idea of the present disclosure and to be used in the technical field to which the present disclosure belongs. It is provided to fully inform those skilled in the art of the scope of the present disclosure, and the technical idea of the present disclosure is only defined by the scope of the claims.

When adding reference numerals to components in each drawing, it should be noted that identical components are given the same reference numerals as much as possible even if they are shown in different drawings. Additionally, in describing the present disclosure, if it is determined that a detailed description of a related known configuration or function may obscure the gist of the present disclosure, the detailed description will be omitted.

Unless otherwise defined, all terms (including technical and scientific terms) used in this specification may be used with meanings that can be commonly understood by those skilled in the art to which this disclosure pertains. Additionally, terms defined in commonly used dictionaries are not interpreted ideally or excessively unless clearly specifically defined. The terminology used herein is for the purpose of describing embodiments and is not intended to limit the disclosure. As used herein, singular forms also include plural forms, unless specifically stated otherwise in the context.

Additionally, in describing the components of the present disclosure, terms such as first, second, A, B, (a), and (b) may be used. These terms are only used to distinguish the component from other components, and the nature, order, or order of the component is not limited by the term. When a component is described as being “connected,” “coupled,” or “connected” to another component, that component may be directly connected or connected to that other component, but there is another component between each component. It will be understood that elements may be “connected,” “combined,” or “connected.”

As used in this disclosure, “comprises” and/or “comprising” refers to a referenced component, step, operation and/or element that includes one or more other components, steps, operations and/or elements. Does not exclude presence or addition.

Before describing various embodiments of the present disclosure, some terms used in the embodiments will be clarified.

In the following examples, “aerosol-forming substrate” may mean a material capable of forming an aerosol. Aerosols may contain volatile compounds. The aerosol-forming substrate may be solid or liquid. For example, the solid aerosol-forming substrate may include solid substances based on tobacco raw materials such as leaf tobacco, cut tobacco, reconstituted tobacco, etc., and the liquid aerosol-forming substrate may include nicotine, tobacco extract, humectants, and/or various flavors. It may include a liquid composition based on an agent. However, the scope of the present disclosure is not limited to the examples listed above.

In the following examples, “aerosol-generating article” may refer to an article capable of generating an aerosol. Aerosol-generating articles can include an aerosol-forming substrate. Representative examples of aerosol-generating articles include cigarette sticks, but the scope of the present disclosure is not limited to these examples.

In the following embodiments, “aerosol-generating device” may refer to a device that generates an aerosol using an aerosol-forming substrate or aerosol-generating article to generate an aerosol that can be inhaled directly through the user's mouth and into the user's lungs. The aerosol generating device may include, but is not limited to, a device that generates an aerosol through, for example, a cigarette stick.

In the following embodiments, “upstream” or “upstream direction” means a direction away from the smoker's mouth, and “downstream” or “downstream direction” means a direction closer to the smoker's mouth. can do. The terms upstream and downstream may be used to describe the relative positions of the elements that make up the smoking article. For example, in the aerosol-generating article 200 illustrated in FIG. 2 , the mouthpiece segment 240 is located downstream or in a downstream direction of the cooling segment 230, and the cooling segment 230 is positioned on the side of the mouthpiece segment 240. Located upstream or in the upstream direction.

In the following embodiments, “puff” refers to the user's inhalation, and inhalation may refer to the situation of pulling the product into the user's oral cavity, nasal cavity, or lungs through the user's mouth or nose. .

Hereinafter, several embodiments of the present disclosure will be described in detail with reference to the attached drawings.

1 is an exemplary configuration diagram showing an aerosol simulation device 100 according to some embodiments of the present disclosure.

The aerosol simulation device 100 may be a computing device capable of simulating aerosol phenomena generated from a target aerosol-generating article. Here, the target aerosol-generating article may mean an aerosol-generating article to be simulated. Additionally, the aerosol-generating article is an article that generates an aerosol through an aerosol-generating device, and may be, for example, a cigarette stick, but is not limited thereto. Additionally, the aerosol generating device may be, for example, a device that generates an aerosol by heating an inserted cigarette stick, but is not limited thereto. Hereinafter, for convenience of explanation, the aerosol simulation device 100 will be abbreviated as “simulation device” 100.

Simulation device 100 may be implemented with one or more computing devices. In other words, the simulation device 100 may be implemented as a single computing device or as a plurality of computing devices. For example, a first function of the simulation device 100 may be implemented in a first computing device, and a second function may be implemented in a second computing device. Alternatively, specific functions of the simulation device 100 may be implemented in a plurality of computing devices.

The computing device may be, for example, a laptop, desktop, laptop, etc., but is not limited thereto and may include all types of devices equipped with a computing function. Refer to FIG. 12 for an example of a computing device.

As shown in FIG. 1, the simulation device 100 according to the embodiment may include a data input unit 110, a model configuration unit 120, a simulation unit 130, a visualization unit 140, and a DB 150. You can. However, this is only a preferred embodiment for achieving the purpose of the present disclosure, and of course, some components may be added or omitted as needed. In addition, each component (e.g. 110) of the simulation device 100 shown in FIG. 1 represents functionally distinct functional elements, and a plurality of components (e.g. 110) are integrated with each other in the actual physical environment. Note that it can also be implemented as . Of course, in an actual physical environment, each of the components (e.g. 110) may be implemented in a subdivided form into a plurality of functional elements. Hereinafter, each component (e.g. 110) of the simulation device 100 will be described.

The data input unit 110 may receive basic simulation data regarding the target aerosol-generating product. Simulation basic data includes, for example, the type of aerosol-generating article, structural data of the aerosol-generating article, data on the materials (e.g. aerosol-forming substrate, wrapper, etc.) that make up the aerosol-generating article (hereinafter referred to as “material-related data”), and aerosol-generating article. It may include, but is not limited to, data related to the heater that heats the generated product (hereinafter referred to as “heater-related data”), puff data, and data related to simulation settings (hereinafter referred to as “setting-related data”). It may further include various data related to the simulation. Simulation basic data input through the data input unit 110 may be stored in the DB 150.

The structural data may include various data that can indicate or define the structure of the aerosol-generating article. For example, structural data includes modeling data (e.g. 2D modeling data, 3D modeling data) for the aerosol-generating article, regime data (e.g. length, diameter, internal structure, etc.) of the aerosol-generating article, and perforation structure formed in the aerosol-generating article (e.g. It may include data on perforation size, number, location, arrangement type, etc.) (hereinafter referred to as “perforation-related data”). It may include etc. However, it is not limited to this.

In addition, the material-related data includes, for example, the type, content, and physical properties (e.g. viscosity, porosity, water permeability, density) of the aerosol-forming base (e.g. nicotine, humectants such as glycerin/propylene glycol, tobacco substances such as cut grass/lamellae, etc.) etc.), the content and physical properties (e.g. porosity, water permeability, etc.) of the filter material (e.g. cellulose acetate fiber), and the specifications of the wrapper (e.g. thickness, length, etc.) and physical properties (e.g. porosity, thermal conductivity, etc.). However, it is not limited to this.

In addition, the heater-related data includes the temperature profile of the heater (e.g. heating temperature over time), data on the heating structure of the heater (e.g. heating method, heating position, shape, length, thickness, etc.), and the type of heater (e.g. internal heating type). , external heating type, electrical resistance heater, induction heating type heater), etc. However, it is not limited to this. The heating method of the heater may be divided into internal heating type and external heating type, but is not limited thereto.

Additionally, the puff data may include various data that can represent or define the user's puff. For example, puff data may include data on the number of puffs, puff intensity, puff interval, etc. However, it is not limited to this. For reference, the form of puff data may vary. For example, it may be defined in the form of volumetric flow rate over time (see 360 in FIG. 5).

In addition, the simulation setting-related data includes, for example, simulation execution time (or number of time steps), simulation accuracy, type of calculation grid or computation grid (e.g. 2D, 3D, aligned, unaligned), It may include the density of the calculation grid, the number of calculation cells, simulation target elements, type of governing equation, initial conditions, boundary conditions, area of interest, etc. However, it is not limited to this.

The simulation target elements refer to elements to be derived through simulation, such as temperature distribution, concentration distribution (e.g. concentration distribution of nicotine, moisturizer, etc.), velocity distribution (e.g. aerosol velocity distribution), and aerosol transfer amount (i.e. , atomization amount), suction resistance, etc., but is not limited thereto. The method of deriving the value of the target element through simulation will be described later.

Meanwhile, the data input unit 110 may use any method to receive basic simulation data. For example, the data input unit 110 may receive basic simulation data through a web interface (e.g. web GUI). Alternatively, the data input unit 110 may receive basic simulation data from a file stored in local storage. Of course, the data input unit 110 may also receive basic simulation data in the form of a file through a web interface.

In some embodiments, the data input unit 110 may provide a list of aerosol-generating products that can be simulated and allow the user to select a target aerosol-generating product. Then, the data input unit 110 can query the DB 150 to obtain basic simulation data for the target aerosol-generating product.

Next, the model configuration unit 120 may construct a CFD (Computational Fluid Dynamics) model for simulating the aerosol phenomenon of the target aerosol-generating article based on the input basic simulation data. A CFD model refers to a model for analyzing fluid phenomena. Anyone in the relevant technical field will be able to clearly understand the CFD model, so a detailed explanation thereof will be omitted.

As shown, the model configuration unit 120 may be configured to include a grid creation unit 121, a governing equation setting unit 122, and a condition setting unit 123. Hereinafter, the components of the model component 120 will be described.

The grid generator 121 may generate a calculation grid based on basic simulation data. A computational grid refers to a computational area in the form of a grid, and each computational cell that makes up the computational grid can be the minimum unit of simulation calculation. Therefore, as the number of calculation cells increases (i.e., as the calculation grid becomes denser), simulation accuracy increases, and computing costs for simulation may also increase. Conversely, as the number of calculation cells decreases (i.e., as the calculation grid becomes less dense), simulation accuracy decreases and computing costs can also be reduced. The computational grid may have the form of an ordered grid or an unaligned grid, and may be a two-dimensional grid or a three-dimensional grid. Anyone in the relevant technical field will be able to clearly understand the computational grid of a CFD model, so any further detailed explanation thereof will be omitted.

Specifically, the grid generator 121 may generate a calculation grid corresponding to the physical structure of the target aerosol-generating article based on structural data of the target aerosol-generating article. The grid generator 121 may generate the calculation grid further based on simulation setting-related data regarding the calculation grid (e.g. the shape of the calculation grid, the number of calculation cells, density, etc.). In order to provide easier understanding, further explanation will be made with reference to the example shown in FIG. 2.

FIG. 2 illustrates creating a calculation grid 300 for a target aerosol-generating article 200 composed of a plurality of segments 210 to 240, and the arrow shown in FIG. 2 represents the movement path of the aerosol (A). It is showing.

As shown in Figure 2, the target aerosol-generating article 200 is comprised of a front filter segment 210, an aerosol-forming substrate segment 220, a cooling segment 230, a mouthpiece segment 240, and a wrapper 250. Let's assume it has been done. Additionally, the front filter segment 210 is a cellulose acetate filter including a hollow channel, the aerosol-forming substrate segment 220 includes an aerosol-forming substrate, and the cooling segment 230 includes a hollow channel for cooling the aerosol. Let us assume that it is a paper tube filter and that the mouthpiece segment 240 is a cellulose acetate filter. In order not to obscure the subject matter of the present disclosure, detailed description of each segment 210 to 240 will be omitted. Additionally, assume that the target aerosol-generating article 200 is heated by the external heater 260 of an aerosol-generating device (not shown) to generate an aerosol.

In the above case, the grid generator 121 creates a calculation grid corresponding to the physical structure of the target aerosol-generating article 200 based on the structural data (e.g. 2D or 3D modeling data, system data) of the target aerosol-generating article 200. (300) can be generated. For example, the calculation grid 300 generated by the grid generator 121 may include calculation grid areas 310 to 340 corresponding to each segment 210 to 240 constituting the target aerosol-generating article 200. there is.

Description will be made again with reference to FIG. 1 .

In some embodiments, the grid generator 121 may adjust the number of calculation cells and/or the density of the calculation grid based on the computing performance and/or available computing resources of the simulation device 100. For example, when the available computing resources (or computing performance) are greater than the standard value, the grid generator 121 increases the number of calculation cells, such as by generating a three-dimensional calculation grid or a highly dense two-dimensional calculation grid. can be increased. In the opposite case, the grid generator 121 may reduce the number of calculation cells, such as by generating a two-dimensional calculation grid or a three-dimensional calculation grid with low density. In this case, the simulation can be efficiently performed considering the computing performance and/or available computing resources of the simulation device 100.

Additionally, in some embodiments, the grid generator 121 may increase the density (or the number of calculation cells) of the calculation grid area corresponding to the region of interest. For example, when the mouthpiece segment (e.g. 240) of the target aerosol-generating article (e.g. 200) is designated as the area of interest, the grid generator 121 creates a calculation grid area (e.g. 340) corresponding to the mouthpiece segment (e.g. 240). ) can increase the density. In this case, simulation accuracy for the region of interest can be improved.

Additionally, in some embodiments, the grid generator 121 determines the density (or the number of calculation cells) of the first calculation grid area (e.g. 320, 330, 340) that is highly correlated with the movement (flow) path of the aerosol. It is possible to increase and reduce the density of the second calculation grid area (e.g. 310) with low correlation. Here, the area highly correlated with the movement path of the aerosol may include, for example, the area that affects the generation of the aerosol, the movement path of the aerosol and the adjacent area, but is not limited thereto and may be defined in various ways. there is. For example, the grid generator 121 may generate a calculation grid such that the number of calculation cells included in the first calculation grid area is greater than the number of calculation cells included in the second calculation grid area. In these cases, simulation accuracy for the aerosol movement path and adjacent areas can be improved.

Additionally, in some embodiments, the grid generator 121 may dynamically adjust the density of the calculation grid (or the number of calculation cells) during simulation. For example, the grid generator 121 can adjust the number of calculation cells by dividing a specific calculation cell or merging a plurality of calculation cells. This embodiment will be further explained with reference to FIG. 6 later.

Next, the governing equation setting unit 122 may set the governing equation of the CFD model. The governing equation refers to an equation that defines fluid phenomena or describes the relationship with various variables (e.g. temperature, pressure, etc.) that affect fluid phenomena. Anyone working in the relevant technical field is already familiar with the concept of governing equations. Since there will be, the explanation for this will be omitted. Hereinafter, in order to provide easier understanding, the types and linkages of governing equations that can be applied to the CFD model according to the embodiment will be described with reference to FIG. 3.

As illustrated in FIG. 3, the governing equations include a flow equation 410 for simulating the flow phenomenon of aerosol and a heat transfer equation 420 for simulating the heat transfer phenomenon, in addition to the chemical reaction equation 430 and A mass transfer equation 440 may be further included. However, it is not limited to this. The chemical reaction equation 430 and the mass transfer equation 440 are used to more accurately simulate aerosol flow and heat transfer phenomena or physical and chemical phenomena (e.g. aerosol generation, material transfer, etc.) in addition to aerosol flow and heat transfer phenomena. It can be used for complex simulations up to. Hereinafter, the governing equations 410 to 440 illustrated in FIG. 3 will be described.

The flow equation 410 is an equation that describes the flow phenomenon of aerosol, for example, representing the relationship between aerosol velocity (u) and pressure (p), or at least one of aerosol velocity (u) and pressure (p) as a variable. It can be a formula with . As a more specific example, the flow equation 410 may include a mass conservation equation (or continuity equation) and a momentum equation such as the Navier-Stokes' equation. However, it is not limited to this.

An example of the mass conservation equation and momentum equation is described in Equation 1 and Equation 2 below. Equation 1 below is an equation derived from the law of conservation of mass, and Equation 2 below is an equation (or momentum conservation equation) derived from the law of momentum conservation and represents the relationship between fluid velocity, pressure, and viscosity, etc. am.

[Equation 1]

,

[Equation 2]

In Equations 1 and 2 above, i refers to the individual fluid material constituting the aerosol (eg, vaporized aerosol-forming substrate such as nicotine, glycerin, propylene glycol, tar, moisture, etc.), and eja refers to the individual fluid material. Refers to aerosol, which is a mixture. Here, the aerosol may include a mixture of aerosol and air. And, ρ _i means the fluid density of substance (i), n _i means the mass flux of substance (i), and ρ _eja means the density of aerosol (eja). , u means fluid velocity. And, p means the pressure, μ _eja means the viscosity of the aerosol (eja), and I means that the relevant term is in tensor form (or converted to tensor form). In the following description, for clarity of the present disclosure, descriptions of parameters (variables, constants, etc.) that overlap with the previously described equations will be omitted, and if parameters with the same symbol are used with different meanings, the related equations Let's explain it again. Additionally, some of the parameters of the equations mentioned in this disclosure may be calculated during a simulation process, and experimentally obtained values may be substituted for others.

For reference, Equation 2 above consists of two terms on the left side and two terms on the right side. The first term on the left side is a velocity change term over time, the second term on the left side is a convection term, and the first term on the right side is It is a pressure change term, and the second term on the right side is a fluid resistance term related to viscosity. In addition, if the number of substances (i) constituting the aerosol is set to be plural, Equation 1 may also be plural (similarly, the equations below may also be plural), and when performing the simulation, Equation 1 and 2 can be calculated in conjunction with each other.

On the other hand, in the structure of the target aerosol-generating article 200 illustrated in FIG. 2, the aerosol flow in the cooling segment 230 is bound to be different from the aerosol-generating substrate segment 220 or the mouthpiece segment 240. Aerosol flow in the cooling segment 230 is no different from gas movement in an unobstructed free-flow region, but the aerosol-forming substrate segment 220 or mouthpiece segment 240 contains porous material that impedes the flow of the aerosol ( e.g. filter material, tobacco material) are present. Therefore, in order to more accurately simulate aerosol flow in areas containing porous materials, such as the aerosol-forming substrate segment 220 or the mouthpiece segment 240, Darcy's law is added to the flow equation 410. It can be applied. Darcy's law is a law derived from an empirical formula obtained by observing the flow of fluid passing through a porous medium. Those working in the relevant technical field will already be familiar with Darcy's law, so a detailed explanation thereof will be omitted. do. When Darcy's law is applied, the above equations 1 and 2 can be transformed into the following equations 3 and 4.

[Equation 3]

,

[Equation 4]

In Equation 3, Q _i is a production term related to substance (i), which can mean the creation of gaseous substance (i) by evaporation (positive number form) or the exhaustion (negative form) of liquid substance (i). and can have units of mass flux. And, u _PM refers to the fluid velocity within the porous medium (PM), k _i refers to the permeability of the porous medium to material (i), and D _i refers to the permeability of material (i). It refers to the diffusion coefficient, and c _i refers to the concentration of substance (i).

Equation 4 can be understood as an equation that reflects the porosity of the porous medium in the velocity-related terms (eg velocity change term, convection term, etc.) of Equation 2, which is the momentum conservation equation, where k refers to the porous medium, and ϕ _k refers to the porosity of the porous medium (k), and K _eja refers to the permeability of the porous medium to aerosol (eja).

Next, the heat transfer equation 420 is an equation that describes the heat transfer inside the aerosol-generating article, for example, representing the relationship between the flow-related variables of the aerosol (e.g. velocity u, pressure p) and temperature (T), or It may be a formula that has at least one of flow-related variables (e.g. speed u, pressure p) and temperature (T) as variables. For example, heat transfer equation 420 may include an energy conservation equation. However, it is not limited to this.

An example of an energy conservation equation is shown in Equations 5 and 6 below. Equation 5 below represents the energy conservation equation applicable to the free flow region, and Equation 6 below represents the energy conservation equation applicable to the porous media region.

[Equation 5]

[Equation 6]

In equations 5 and 6 above, i refers to an individual fluid substance in the gas (vapor) phase (i.e., an aerosol-forming substrate in the gas phase), and j refers to an individual fluid substance in the liquid phase (i.e., an aerosol-forming substrate in the liquid phase), , tot refers to the entire substance including a plurality of individual substances (i, j). And, C _p,eja means the heat capacity (C _p ) of the aerosol (eja), T means the temperature, and h _i means the heat transfer coefficient of the substance (i). And, a refers to air, n _a refers to the mass flux of air (a), h _a refers to the heat transfer coefficient of air (a), and k _eja refers to the thermal conductivity of aerosol (eja). it means. And, eff refers to a state in which gas and liquid phases coexist in a porous medium (eg, a state in which liquid nicotine and gaseous nicotine coexist, gas aerosol and liquefied aerosol coexist), and C _p,eff is It refers to the heat capacity of the entire material (tot) in the mixed state (eff), n _j refers to the mass flux of material (j), h _j refers to the heat transfer coefficient of material (j), and k _eff,tot is It refers to the thermal conductivity of the entire material (tot) in the mixed state (eff). In addition, H _evap,i refers to the heat capacity of vaporization of substance (i), and q is a generation term related to temperature and can be set to 0 when no separate heating material is present in the aerosol-generating article.

Next, the chemical reaction equation 430 is an equation that describes the chemical reaction related to aerosol generation. For example, it represents the relationship between the chemical reaction rate (K) associated with the aerosol and the substance concentration (c) and temperature (T). , It may be a formula that has at least one of the chemical reaction rate (K), substance concentration (c), and temperature (T) as variables. For example, the chemical reaction equation 430 may include the Arrhenius equation, an evaporation amount calculation equation, and an ideal gas equation. However, it is not limited to this. Examples of the Arrhenius equation, evaporation amount calculation equation, and ideal gas equation are shown in Equations 7, 8, and 9 below, respectively.

[Equation 7]

,

[Equation 8]

[Equation 9]

In Equations 7 to 9, K _f means the reaction rate constant, A _f means the frequency factor, E _a means the activation energy, R means the gas constant, and α _i means the substance (i ), and E _0i refers to the initial activation energy of substance (i). And, EV _i and m _evap,i mean the evaporation amount of substance (i) (eg Kg/(m ³ *s) or mol/(m ³ *s)), and K _i is the evaporation rate of substance (i) It means a constant, C _sat,i means the saturation concentration of substance (i), and C _i means the concentration of substance (i). In addition, a _i is a factor that adjusts (controls) the saturation concentration (C _sat,i ) for substance (i) to suit the actual environment (or simulation purpose), and can be set to an appropriate value. The saturation concentration (C _sat,i ) can be calculated based on the saturation concentration (c _sat ) calculation formula in Equation 9, and Equations 7 to 9 can be calculated in conjunction.

For reference, the values of the frequency factor (A _f ) and reaction rate variable (α _i ) can be obtained experimentally, for example, through techniques such as TGA-DSC, TG-FTIR, GC-mass, and LC-mass. You can. In addition, the value of the reaction rate constant (K _f ) in Equation 7 can be applied (substituted) for the evaporation rate constant (K _i ) in Equation 8, and the saturation concentration (c _sat ) value in Equation 9 is Equation It can be applied (substituted) for a saturation concentration (C _sat ) of 8.

Next, the mass transfer equation 440 is an equation that describes the transfer of substances within the aerosol-generating article, for example, representing the relationship between the aerosol speed (u) and the transfer amount, or at least one of the aerosol speed (u) and the transfer amount. It can be a formula with one variable. For example, the mass transport equation 440 may include a species transport equation. However, it is not limited to this.

An example of the paper song equation is shown in Equations 10 and 11 below. Equation 10 below represents a transport equation that can be applied to the free flow region, and Equation 11 below represents a transport equation that can be applied to the porous media region.

[Equation 10]

[Equation 11]

In Equations 10 and 11, ξ _i is the transport amount of material (i), which may have units of mass flux or concentration, D _i means the diffusion coefficient of material (i), and D _eff,i is the porous medium. It refers to the diffusion coefficient of the substance (i) in a mixed state (eff) of liquid and gas phases. For the meaning of other parameters, refer to the preceding equation.

For reference, the velocity term (u _PM- related term) in Equation 11 can be understood as Darcy's law applied to the velocity term (u-related term) in Equation 10, and the diffusion term (De _ff,i) in Equation 11 (related clause) can be understood as modified to express the characteristics of a fluid consisting of a mixture of liquid and gas phases.

The governing equations described so far can be calculated in conjunction with each other as shown in FIG. 3. For example, when Equations 1 to 11 above are set as the governing equations of the CFD model, the velocity (u) value or pressure (p) value calculated through the flow equation (e.g. 410) such as Equations 1 to 4 is calculated as It can be applied (substituted) into a mass transfer equation (e.g. 440) such as Equation 10 or 11. As another example, the temperature (T) value calculated through the heat transfer equation (e.g. 420) such as Equation 5 or 6 may be applied (substituted) to the chemical reaction equation (e.g. 430) such as Equation 7 to 9. As another example, the material transfer amount (ξ) calculated through the material transfer equation (e.g. 440) such as Equation 10 or 11 is the concentration (C) value of the chemical reaction equation (e.g. 430) such as Equation 7 to 9. can affect. As another example, the temperature (T) value calculated through the heat transfer equation (e.g. 420) such as Equation 5 or 6 is the density (ρ) and viscosity (μ) of the flow equation (e.g. 410) such as Equation 1 to 4. ), diffusion coefficient (D), etc.

In this way, the values of variables calculated through a specific governing equation can be applied (substituted) or influenced by other governing equations, so that multiple governing equations can be calculated in conjunction with each other, thereby allowing the aerosol that appears in the target aerosol-generating article to be calculated. Not only flow and heat transfer phenomena, but also other complex physical and chemical phenomena (e.g. aerosol generation, material transport, etc.) can be accurately simulated. For example, the generation and flow of aerosols is a phenomenon in which chemical reactions, heat transfer, and fluid flow are complexly intertwined, and these phenomena can be accurately simulated by calculating multiple governing equations in conjunction. For reference, the variable values of a specific governing equation may be applied (substituted) to variables of another governing equation at the same time step, or may be applied (substituted) at the next time step.

Meanwhile, the governing equation setting unit 122 can set a formula directly input from the user as the governing equation of the CFD model, and can also automatically set the governing equation based on the simulation target elements. For example, when the simulation target element is the atomization amount, the governing equation setting unit 122 sets the flow equation 410, heat transfer equation 420, chemical reaction equation 430, and mass transfer equation 440 as the governing equations of the CFD model. It can be set to . As another example, when the simulation target element is suction resistance, the governing equation setting unit 122 may set only the flow equation 410 as the governing equation of the CFD model. As another example, when the simulation target element is temperature distribution, the governing equation setting unit 122 may set the flow equation 410 and the heat transfer equation 420 as the governing equations of the CFD model.

The description of other components of the simulation device 100 will continue with reference to FIG. 1 again.

The condition setting unit 123 may set initial conditions and/or boundary conditions of the CFD model. Initial conditions and/or boundary conditions are conditions set to accurately perform simulation, and can be used to solve the governing equations through numerical analysis techniques.

The initial conditions may include conditions for setting initial values of various simulation variables, and the condition setting unit 123 sets the initial conditions according to the simulation basic data and/or the input initial value (initial value pre-stored in DB 150). can be set. For example, if the simulation variables (e.g. variables of the governing equations) of the target aerosol-generating article include velocity (velocity of the aerosol), pressure, temperature, and concentration (e.g. concentration of constituent substances), as shown in FIG. 4 Likewise, the condition setting unit 123 may set initial conditions (e.g. 322, 342) for speed, pressure, temperature, and concentration for each calculation cell (e.g. 321, 341) constituting the calculation grid 300.

As a more specific example, the condition setting unit 123 may set initial conditions for material concentration based on material-related data (e.g. content data of constituent materials). For example, the condition setting unit 123 calculates the concentration value by dividing the content (e.g. filling amount) of the substance (e.g. tobacco material, moisturizer, etc.) by the volume of the part containing the substance (e.g. aerosol-forming base segment 260), and determines the concentration value. The value can be set as the initial condition. Additionally, the condition setting unit 123 can set initial conditions for speed, pressure, and temperature in the form of [speed = 0], [pressure = 1 atmosphere], and [temperature = room temperature]. This is because before smoking begins, the heater will not generate heat and there will be no flow of aerosol within the aerosol-generating article.

The boundary conditions may include various boundary conditions related to aerosol flow, heater heat, material transfer, etc., and the condition setting unit 123 sets the boundary conditions of the CFD model according to the simulation basic data or input boundary conditions. You can.

For example, the condition setting unit 123 may set flow boundary conditions for aerosol discharge (inhalation) based on puff data. Additionally, the condition setting unit 123 may set a wall boundary condition (e.g. non-slip) to limit or block the flow of aerosol based on the structural data. For example, the condition setting unit 123 may set a wall boundary condition to limit or block the movement of aerosol in a direction other than the downstream end of the target aerosol-generating article. In addition, the condition setting unit 123 can set thermal boundary conditions based on heater-related data, and boundary conditions regarding flow or mass transfer (e.g. wall boundary conditions) based on material-related data of the target aerosol-generating article 200. ) can be set. In addition, the condition setting unit 123 may set insulation boundary conditions based on material-related data (e.g. type of wrapper, physical properties, etc.). In order to provide easier understanding, an example of setting boundary conditions will be further explained with reference to FIG. 5.

Figure 5 shows an example of setting flow boundary conditions and thermal boundary conditions based on puff data 360 and the temperature profile 350 of the heater. For reference, Figure 5 shows as an example that puff data 360 is defined as a change in volumetric flow rate (Qv; ml/s) according to time (t), and the change in volumetric flow rate occurs after a specific time point (t1). What occurs in can be understood as simulating the generation of a puff after preheating is completed (at time t1).

As shown in FIG. 5, the condition setting unit 123 may set thermal boundary conditions based on the temperature profile 350 of the heater and data regarding the heating structure. For example, the condition setting unit 123 determines the boundary areas 370 and 380 through which heat is transferred from the heater to the target aerosol-generating article (e.g. 200) based on the heating structure of the heater, and sets the determined boundary areas 370 and 380. Boundary conditions according to the temperature profile 350 can be set. In this case, heating due to the heating structure and temperature profile of the heater can be accurately reflected in the CFD model.

For reference, in FIG. 6, since the heater (e.g. 260) that heats the target aerosol-generating article (e.g. 200) is an external heating type (see FIG. 2), the boundary areas 370 and 380 are of the target aerosol-generating article (e.g. 200). It is only shown as an example that it is formed on the outside, and if the heating structure of the heater is changed, the boundary area (e.g. 370, 380) related to heat transfer may be formed in a different location. For example, if the target heater is an internal heating type, the boundary area (e.g. 370, 380) may be formed inside the target aerosol-generating article.

Additionally, the condition setting unit 123 may set flow boundary conditions based on the puff data 360. For example, the condition setting unit 1230 may set a flow boundary condition in the downstream end area 390 where the aerosol is discharged by the puff. In this case, inhalation of aerosol by puff can be accurately reflected in the CFD model.

Description will be made again with reference to FIG. 1 .

As another example, the condition setting unit 123 may set a fluid boundary condition for perforation based on perforation-related data. At this time, the perforation-related data may include data on the location, number, and arrangement of perforations formed in the target aerosol-generating article, the volume flow rate of outside air flowing in through the perforation, and the temperature of outside air, and the flow boundary conditions are Based on the perforation-related data, it can be set in the boundary area where outside air flows in through the perforation. In this example, once the flow boundary conditions for the perforation are set, the aerosol phenomenon (e.g. aerosol flow phenomenon, heat transfer phenomenon) can be simulated by considering the flow rate and temperature of the external air flowing in through the perforation, and the simulation results are used to design the perforation. It can be used effectively.

Next, the simulation unit 130 can simulate the aerosol phenomenon for the target aerosol-generating article using the configured CFD model. Specifically, the simulation unit 130 converts the governing equations into algebraic equations through numerical analysis techniques (e.g. FDM, FEM, FVM, etc.), and solves the algebraic equations according to initial conditions and boundary conditions to determine simulation variables related to the aerosol phenomenon. The value of can be calculated. For example, as shown in FIG. 6, the simulation unit 130 simulates simulation variables (e.g. speed, pressure, temperature) over a plurality of time steps for each calculation cell (e.g. 321, 341) included in the calculation grid 300. , concentration, etc.) can be calculated repeatedly. According to this calculation process, various aerosol phenomena generated inside the target aerosol-generating article due to smoking can be accurately simulated.

As an example, the simulation unit 130 may simulate the aerosol flow phenomenon within the target aerosol-generating article by calculating the flow equation (e.g. 410). And as a result of the simulation, the pressure distribution and velocity distribution (e.g. aerosol velocity distribution) within the target aerosol-generating article can be derived. At this time, the simulation unit 130 provides a flow equation (e.g. equation) for the free-flow area for the calculation grid area (e.g. 330) corresponding to the free-flow area segment (e.g. cooling segment 230) of the target aerosol-generating article (e.g. 200). Calculations are performed according to 1 and 2), and for the calculation grid areas (e.g. 320, 340) corresponding to the porous medium area segments (e.g. aerosol-forming substrate segment 220, mouthpiece segment 240), the flow equation for the porous medium area is ( e.g. Calculations can be performed according to equations 3 and 4). In this example, the simulation unit 130 can derive pressure distribution after completion of smoking, pressure distribution at a specific point of smoking, pressure distribution change according to puff, pressure distribution change during smoking, pressure change over time at a specific location, etc. there is. Additionally, the simulation unit 130 may derive changes in aerosol movement speed and movement path according to the puff. In addition, the simulation unit 130 may derive the suction resistance for the entire target aerosol-generating article based on the pressure difference between both ends of the target aerosol-generating article (i.e., the difference in pressure values of the calculation grid area or calculation cell corresponding to both ends). You can. In a similar manner, the simulation unit 130 may derive the suction resistance for a portion of the target aerosol-generating article. For example, the simulation unit 130 creates a mouthpiece segment (e.g. 240) based on the difference in pressure values between the calculation grid areas (or calculation cells) corresponding to both ends of the mouthpiece segment (e.g. 240) constituting the target aerosol-generating article (e.g. 200). 240), the suction resistance can be derived.

As another example, the simulation unit 130 may simulate the aerosol flow phenomenon and heat transfer phenomenon within the target aerosol-generating article by calculating the flow equation (e.g. 410) and the heat transfer equation (e.g. 420) in connection. And as a result of the simulation, the pressure distribution, velocity distribution, and temperature distribution within the target aerosol-generating article can be derived. At this time, the simulation unit 130 generates a governing equation (e.g. equation) for the free-flow area for the calculation grid area (e.g. 330) corresponding to the free-flow area segment (e.g. cooling segment 230) of the target aerosol-generating article (e.g. 200). Perform calculations according to 1, 2, 5) and govern the porous media region for the calculation grid regions (e.g. 320, 340) corresponding to the porous media region segments (e.g. aerosol-forming substrate segment 220, mouthpiece segment 240). Calculations can be performed according to equations (e.g. Equations 3, 4, and 6). In this example, the simulation unit 130 can derive the temperature distribution after completion of smoking, the temperature distribution at a specific point of smoking, the temperature distribution change according to the puff, the temperature distribution change during smoking, the temperature change over time at a specific location, etc. there is.

As another example, the simulation unit 130 calculates the flow equation (e.g. 410), heat transfer equation (e.g. 420), chemical reaction equation (e.g. 430), and mass transfer equation (e.g. 440) to calculate the generation of aerosol, A variety of aerosol phenomena can be simulated, including flow, heat transfer, and mass transport. And as a result of the simulation, the pressure distribution, velocity distribution, temperature distribution, concentration distribution, chemical reaction rate, and amount of aerosol discharged to the outside can be derived within the target aerosol-generating article. At this time, the simulation unit 130 generates a governing equation (e.g. equation) for the free-flow area for the calculation grid area (e.g. 330) corresponding to the free-flow area segment (e.g. cooling segment 230) of the target aerosol-generating article (e.g. 200). Calculations are performed according to 1, 2, 5, 7 to 10), and for the porous media area segments (e.g. 320, 340) corresponding to the porous media area segments (e.g. aerosol-forming substrate segment 220, mouthpiece segment 240), Calculations can be performed according to the governing equations for the area (e.g. Equations 3, 4, 6, 7 to 9, 11). In this example, the simulation unit 130 synthesizes the aerosol transport amount of the calculation grid area corresponding to the downstream end area where aerosol is discharged from the target aerosol-generating article (i.e., calculates the aerosol transport amount of the calculation cell included in the calculation grid area). In total, the aerosol transfer amount (atomization amount) can be derived. For example, if the calculation grid is a 2D grid, the simulation unit 130 can synthesize the aerosol transport amount through the surface integral, and if the calculation grid is a 3D grid, the aerosol transport amount can be synthesized through the volume integral. . In addition, the simulation unit 130 can derive the concentration distribution change according to the puff, the concentration distribution change during smoking, the concentration change over time at a specific location, the concentration change for each substance, and the change in aerosol transfer amount according to the puff.

In some embodiments, as shown in FIG. 6, while the simulation unit 130 is calculating simulation variables over a plurality of time steps, the density of at least a portion of the calculation grid 300 is changed by the grid generator ( 121) can be dynamically adjusted. For example, the grid generator 121 may detect a calculation cell in which the value of a simulation variable (e.g. temperature, pressure, etc.) fluctuates more than a standard value, and divide the detected calculation cell into a plurality (i.e., increase density). You can do it). Alternatively, the grid generator 121 may detect a plurality of calculation cells in which the values of simulation variables (e.g. temperature, pressure, etc.) change below the standard value, and merge the detected plurality of calculation cells (i.e., density can be reduced). Areas of the computational grid where the values of simulation variables fluctuate significantly are likely to be important areas closely related to aerosol phenomena. Therefore, according to this embodiment, simulation accuracy for important calculation grid areas is improved, computing costs invested in unimportant calculation grid areas are reduced, and simulation can be performed more efficiently.

Additionally, in some embodiments, the simulation unit 130 may detect a dead zone within the target aerosol-generating article based on simulation results. Here, the dead zone may refer to an area that is not frequently used within the target aerosol-generating article during smoking. Specifically, the simulation unit 130 may detect areas (or calculation cells) in which the chemical reaction rate, temperature, or material concentration decrease is below the standard value in the entire calculation grid area as dead zones. The dead zone detected in this way can be effectively used to redesign the structure of aerosol-generating items, heaters, etc. In order to provide easier understanding, further explanation will be made with reference to the example shown in FIG. 7.

FIG. 7 illustrates simulation results 600 regarding the temperature distribution of the target aerosol-generating article 500 including the aerosol-forming substrate portion 520 and the filter portion 510. In particular, Figure 7 illustrates the temperature value of the calculation grid 600 visualized in the form of a heat map.

Referring to FIG. 7 , the simulation unit 130 may detect areas 610 and 620 in the calculation grid 600 where the temperature is below the reference value as dead zones. At this time, the reference value may be set to a different value for each calculation grid area or calculation cell. For example, the standard value of a calculation grid area located close to the heater may be set to a high value, and the standard value of a calculation grid area located far from the heater may be set to a low value. Alternatively, the standard value of the calculation grid area corresponding to the aerosol forming base unit 520 may be set to a high value, and the standard value of the calculation grid area corresponding to the filter unit 510 may be set to a low value.

The description of other components of the simulation device 100 will continue with reference to FIG. 1 again.

The visualization unit 140 may visualize simulation results for the target aerosol-generating article. For example, the visualization unit 140 may visualize simulation results (e.g. temperature distribution, velocity distribution, pressure distribution, concentration distribution, etc.) in the form of a heatmap on a 2D or 3D object representing the target aerosol-generating article (Figure 7 to 10). Additionally, the visualization unit 140 may display the movement path and/or direction of movement of the aerosol on the object, or may display the dead zone with emphasis.

As a more specific example, as shown in FIG. 8, the visualization unit 140 can generate visualization information 700 in which the temperature distribution inside the product is shown in the form of a heat map on a 2D object representing the target aerosol-generating product. there is. Of course, the visualization unit 140 can generate visualization information as shown in FIG. 8 for other simulation results (e.g. velocity distribution, concentration distribution, pressure distribution, etc.).

As another example, as shown in FIG. 9, the visualization unit 140 may generate visualization information 800 showing the temperature distribution inside the product in the form of a heat map on a 3D object representing the target aerosol-generating product. .

As another example, as shown in FIG. 10, the visualization unit 140 provides visualization information ( 900) can also be generated.

Additionally, although not shown, the visualization unit 140 may visualize the direction of movement of the aerosol in the form of an arrow. At this time, the visualization unit 140 can display the amount of movement of the aerosol through the thickness (or number) of the arrows, and can also display the moving speed through the color of the arrows.

Next, various data related to aerosol simulation may be stored in the DB 150. For example, the DB 150 may store basic simulation data according to the type of aerosol-generating article. Alternatively, the DB 150 may store simulation results according to the type of aerosol-generating article (or basic simulation data).

In some embodiments, the simulation unit 130 may determine whether simulation results corresponding to basic simulation data input before performing the simulation are stored in the DB 150. And, in response to the determination that it is saved, the simulation unit 130 may provide the pre-stored simulation result without performing the simulation. In this case, the effect of significantly reducing the computing cost performed for simulation can be achieved.

Meanwhile, according to some embodiments of the present disclosure, the simulation device 100 may provide an aerosol simulation service to the user. For example, the simulation device 100 may receive a simulation request from a user through a web interface or the like, and provide an aerosol simulation service in response to the request. At this time, the simulation device 100 may request a service usage fee from the user. Service usage fees may be calculated based on the computing resources invested in the simulation, but may be calculated in other ways. In some examples, a user may select simulation accuracy (or a service fee) when requesting a simulation. Then, the simulation device 100 can perform simulation by creating a calculation grid according to the selected accuracy (or service usage fee). For example, when the user selects high accuracy, the simulation device 100 can generate a dense calculation grid with a large number of calculation cells.

Each component (e.g. 110) in FIG. 1 may refer to software or hardware such as FPGA (Field Programmable Gate Array) or ASIC (Application-Specific Integrated Circuit). However, the above components are not limited to software or hardware, and may be configured to reside in an addressable storage medium, and may be configured to execute one or more processors. The functions provided within the above components may be implemented by more detailed components, or may be implemented as a single component that performs a specific function by combining multiple components.

So far, the configuration and operation of the simulation device 100 according to some embodiments of the present disclosure have been described with reference to FIGS. 1 to 10. According to the above, the aerosol phenomenon generated from the target aerosol-generating article can be accurately simulated through the CFD model. Accordingly, design results can be easily verified without manufacturing and testing target aerosol-generating products, and human and time costs invested in research and development of aerosol-generating products can be greatly reduced.

Hereinafter, an aerosol simulation method according to some embodiments of the present disclosure will be described in detail with reference to the drawings of FIG. 11 and below.

Each step of the method may be performed by a computing device. In other words, each step of the method may be implemented as one or more instructions executed by a processor of a computing device. All steps included in the method may be executed by one physical computing device, or may be distributed and executed by a plurality of physical computing devices. For example, the first steps of the method may be performed by a first computing device and the second steps of the method may be performed by a second computing device. Hereinafter, for convenience of understanding, the description will be continued assuming that each step of the method is performed by the simulation device 100 illustrated in FIG. 1. Therefore, when the subject of each operation is omitted in the description below, it can be understood as being performed by the above-exemplified device 100.

11 is an example flowchart illustrating an aerosol simulation method according to some embodiments of the present disclosure. However, this is only a preferred embodiment for achieving the purpose of the present disclosure, and of course, some steps may be added or deleted as needed.

As shown in FIG. 11, the aerosol simulation method may begin at step S100 of receiving basic simulation data regarding the target aerosol-generating article. For further information on this step, please refer to the description of the data input unit 110.

In step S200, a CFD model may be constructed based on the input basic simulation data. For example, the simulation device 100 may construct a CFD model by creating a calculation grid based on input basic simulation data, setting governing equations, and setting initial conditions and boundary conditions. For this step, please refer to the description of the model component 120 further.

In step S300, aerosol phenomena for the target aerosol-generating article may be simulated using the constructed CFD model. For example, the simulation device 100 may simulate the aerosol phenomenon by calculating the governing equations according to set initial conditions and boundary conditions and repeatedly calculating the governing equations according to a plurality of time steps. At this time, calculations for the governing equations can be performed in units of calculation cells that make up the calculation grid. As a more specific example, the simulation device 100 simulates the heat transfer phenomenon and aerosol flow phenomenon that appear in the target aerosol-generating article by repeatedly calculating the flow equation (e.g. 410) and the heat transfer equation (e.g. 420) according to a plurality of time steps. can do. For further information on this step, please refer to the description of the simulation unit 130.

In step S400, the simulation results can be visualized. For example, the simulation device 100 may visualize simulation results on a two-dimensional or three-dimensional object indicating a target aerosol-generating article. For example, the simulation device 100 may visualize the temperature distribution, pressure distribution, speed distribution, concentration distribution, etc. in the form of a heat map, display the movement path of the aerosol on the object, or highlight the dead zone. there is. However, the visualization method is not limited to this. For further information on this step, please refer to the description of the visualization unit 140.

For reference, steps S100 to S400 illustrated in FIG. 11 may be performed by the data input unit 110, the model construction unit 120, the simulation unit 130, and the visualization unit 140, respectively.

So far, the aerosol simulation method according to some embodiments of the present disclosure has been described with reference to FIG. 11. According to the above, the aerosol phenomenon generated from the target aerosol-generating article can be accurately simulated through the CFD model. Accordingly, design results can be easily verified without manufacturing and testing target aerosol-generating products, and human and time costs invested in research and development of aerosol-generating products can be greatly reduced.

Hereinafter, an exemplary computing device 1000 capable of implementing the simulation device 100 illustrated in FIG. 1 will be described.

FIG. 12 is an exemplary hardware configuration diagram showing the computing device 1000 of the present disclosure.

As shown in FIG. 12, the computing device 1000 includes one or more processors 1100, a bus 1300, a communication interface 1400, and a memory (loading) a computer program executed by the processor 1100. 1200) and a storage 1500 that stores a computer program 1600. However, only components related to the embodiment of the present disclosure are shown in FIG. 12. Accordingly, a person skilled in the art to which this disclosure pertains can recognize that other general-purpose components may be included in addition to the components shown in FIG. 12 . That is, the computing device 1000 may further include various components in addition to those shown in FIG. 12 .

The processor 1100 controls the overall operation of each component of the computing device 1000. The processor 1100 includes at least one of a Central Processing Unit (CPU), Micro Processor Unit (MPU), Micro Controller Unit (MCU), Graphic Processing Unit (GPU), or any type of processor well known in the art of the present disclosure. It can be configured to include. Additionally, the processor 1100 may perform an operation on at least one application or program to execute a method/operation according to embodiments of the present disclosure. Computing device 1000 may include one or more processors.

The memory 1200 stores various data, commands and/or information. Memory 1200 may load one or more programs 1600 from storage 1500 to execute methods/operations according to embodiments of the present disclosure. For example, when the computer program 1600 is loaded into the memory 1200, a module as shown in FIG. 1 may be implemented on the memory 1200. The memory 1200 may be implemented as a volatile memory such as RAM, but is not limited thereto.

Bus 1300 provides communication functions between components of computing device 1000. The bus 1300 may be implemented as various types of buses, such as an address bus, a data bus, and a control bus.

The communication interface 1400 supports wired and wireless Internet communication of the computing device 1000. Additionally, the communication interface 1400 may support various communication methods other than Internet communication. To this end, the communication interface 1400 may be configured to include a communication module well known in the technical field of the present disclosure. In some embodiments, communication interface 1400 may be omitted.

Storage 1500 may non-temporarily store one or more programs 1600. The storage 1500 is a non-volatile memory such as Read Only Memory (ROM), Erasable Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), flash memory, a hard disk, a removable disk, or a device well known in the art to which this disclosure pertains. It may be configured to include any known type of computer-readable recording medium.

The computer program 1600, when loaded into the memory 1200, may include one or more instructions that cause the processor 1100 to perform methods/operations according to various embodiments of the present disclosure. That is, the processor 1100 may perform a method/operation according to embodiments of the present disclosure by executing the one or more instructions.

For example, the computer program 1600 operates to receive simulation basic data including structural data of a target aerosol-generating article, configures a CFD model based on the input simulation basic data, and uses the constructed CFD model to target the target. It may include instructions to perform operations that simulate heat transfer phenomena and aerosol flow phenomena that occur in aerosol-generating articles. In this case, the simulation device 100 according to some embodiments of the present disclosure may be implemented through the computing device 1000.

The technical idea of the present disclosure described so far with reference to FIGS. 1 to 12 may be implemented as computer-readable code on a computer-readable medium. The computer-readable recording medium may be, for example, a removable recording medium (CD, DVD, Blu-ray disk, USB storage device, removable hard disk) or a fixed recording medium (ROM, RAM, computer-equipped hard disk). You can. The computer program recorded on the computer-readable recording medium can be transmitted to another computing device through a network such as the Internet, installed on the other computing device, and thus used on the other computing device.

In the above, even though all the components constituting the embodiments of the present disclosure have been described as being combined or operated in combination, the technical idea of the present disclosure is not necessarily limited to these embodiments. That is, within the scope of the purpose of the present disclosure, all of the components may be operated by selectively combining one or more of them.

Although operations are shown in the drawings in a specific order, it should not be understood that the operations must be performed in the specific order shown or sequential order or that all illustrated operations must be performed to obtain the desired results. In certain situations, multitasking and parallel processing may be advantageous. Moreover, the separation of the various components in the embodiments described above should not be construed as necessarily requiring such separation, and the program components and systems described may generally be integrated together into a single software product or packaged into multiple software products. You must understand that it exists.

Although embodiments of the present disclosure have been described above with reference to the attached drawings, those skilled in the art will understand that the present disclosure can be implemented in other specific forms without changing the technical idea or essential features. I can understand that there is. Therefore, the embodiments described above should be understood in all respects as illustrative and not restrictive. The scope of protection of this disclosure should be interpreted in accordance with the claims below, and all technical ideas within the equivalent scope should be interpreted as being included in the scope of rights of the technical ideas defined by this disclosure.

Claims (13)

A data input unit that receives simulation basic data including structural data of the target aerosol-generating article;
A model configuration unit that configures a CFD (Computational Fluid Dynamics) model based on the simulation basic data; and
It includes a simulation unit that simulates the heat transfer phenomenon and aerosol flow phenomenon that appear in the target aerosol-generating article using the configured CFD model,
The model component part is,
a grid generator that generates a calculation grid based on the structural data;
A governing equation setting unit that sets the governing equation of the CFD model; and
It includes a condition setting unit that sets initial conditions and boundary conditions of the CFD model,
The grid generator adjusts the density of the calculation grid area in response to the area of interest,
The governing equation setting unit sets the first governing equation and the second governing equation as the governing equation of the CFD model,
The simulation unit simulates the flow phenomenon of the aerosol and the heat transfer phenomenon by calculating in conjunction with the set first and second governing equations,
The first governing equation is an equation for the flow of the aerosol,
The second governing equation is an equation related to heat transfer within the target aerosol-generating article,
Aerosol simulation device. delete According to claim 1,
The simulation unit calculates the values of simulation variables related to the flow phenomenon of the aerosol according to the set governing equations, the set initial conditions, and the set boundary conditions, and calculates a plurality of calculation cells included in the generated calculation grid. Perform iterative calculations over time steps,
The grid generator detects a calculation cell in which the value of the simulation variable changes more than a standard value during the repetitive calculation, and divides the detected calculation cell into a plurality of cells.
Aerosol simulation device. According to claim 1,
The simulation unit calculates the values of simulation variables associated with the flow phenomenon of the aerosol according to the set governing equations, the set initial conditions, and the set boundary conditions, and performs a plurality of time steps for the calculation cells included in the generated calculation grid. Perform iterative calculations over,
The grid generator detects a plurality of calculation cells in which the value of the simulation variable changes below a standard value during the repetitive calculation, and merges the detected plurality of calculation cells.
Aerosol simulation device. According to claim 1,
The condition setting unit sets boundary conditions of the wall related to the flow of the aerosol based on the structural data,
Aerosol simulation device. According to claim 1,
The simulation basic data further includes puff data,
The condition setting unit sets flow boundary conditions for the aerosol based on the puff data,
The flow boundary condition is a boundary condition set at the downstream end area where the aerosol is discharged from the target aerosol-generating article,
Aerosol simulation device. According to claim 1,
The simulation basic data further includes a temperature profile of a heater that heats the target aerosol-generating article,
The condition setting unit sets thermal boundary conditions based on the temperature profile,
Aerosol simulation device. According to clause 7,
The simulation basic data further includes data regarding the heating structure of the heater,
The condition setting unit determines a boundary area where heat is transferred from the heater to the target aerosol-generating article based on the heating structure of the heater, and sets the thermal boundary condition in the determined boundary area,
Aerosol simulation device. delete According to claim 1,
The simulation unit,
Derive the temperature distribution within the target aerosol-generating article by calculating the set governing equation according to the set initial conditions and the set boundary conditions within the generated calculation grid,
Detecting a calculation grid area where the temperature is below the standard value based on the derived results,
Aerosol simulation device. According to claim 1,
Further comprising a visualization unit that visualizes the results of the simulation,
Aerosol simulation device. In an aerosol simulation method performed on a computing device,
Receiving basic simulation data including structural data of the target aerosol-generating article;
Constructing a CFD (Computational Fluid Dynamics) model based on the simulation basic data; and
Including the step of simulating heat transfer phenomena and aerosol flow phenomena appearing in the target aerosol-generating article using the configured CFD model,
The step of constructing the CFD model is,
generating a computational grid based on the structural data;
Setting the governing equations of the CFD model, and
It includes setting initial conditions and boundary conditions based on the simulation basic data,
In the step of generating the calculation grid, the density of the calculation grid area is adjusted according to the area of interest,
The step of setting the governing equation of the CFD model includes setting the first governing equation and the second governing equation as the governing equation of the CFD model,
The simulating step includes simulating the flow phenomenon of the aerosol and the heat transfer phenomenon by calculating in conjunction with the set first governing equation and the set second governing equation,
The first governing equation is an equation for the flow of the aerosol,
The second governing equation is an equation related to heat transfer within the target aerosol-generating article,
Aerosol simulation method. In a computer program combined with a computing device and stored on a computer-readable recording medium,
The computer program is,
Receiving basic simulation data including structural data of the target aerosol-generating article;
Constructing a CFD (Computational Fluid Dynamics) model based on the simulation basic data; and
Executing the step of simulating the heat transfer phenomenon and aerosol flow phenomenon that appear in the target aerosol-generating article using the configured CFD model,
The step of constructing the CFD model is,
generating a computational grid based on the structural data;
Setting the governing equations of the CFD model, and
It includes setting initial conditions and boundary conditions based on the simulation basic data,
In the step of generating the calculation grid, the density of the calculation grid area is adjusted according to the area of interest,
The step of setting the governing equation of the CFD model includes setting the first governing equation and the second governing equation as the governing equation of the CFD model,
The simulating step includes simulating the flow phenomenon of the aerosol and the heat transfer phenomenon by calculating in conjunction with the set first governing equation and the set second governing equation,
The first governing equation is an equation for the flow of the aerosol,
The second governing equation is an equation related to heat transfer within the target aerosol-generating article,
computer program.

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