Simulation method of CFD-based vacuum recovery system of cigarette smoke

Abstract

The application discloses a simulation method of an AI smoke vacuum recovery system based on CFD, and comprises the following steps: according to an AI smoke vacuum recovery system to be simulated, a three-dimensional model of a calculation domain is established, and an interface between a heat source solid region and a fluid region in the calculation domain is coupled to obtain a three-dimensional model of the calculation domain after coupling; physical field data of the AI smoke vacuum recovery system to be simulated are collected, a solving model is determined, a source is defined, a heat source region condition, a fluid region condition, a boundary condition and a vacuum pressure at an outlet of the calculation domain are defined, and then a three-dimensional model of the calculation domain is divided into grids and imported into ANSYS Fluent software for CFD solving of a continuous phase; based on a result of the CFD solving, a recovery rate is obtained according to an expression of a smoke recovery rate, and whether the AI smoke vacuum recovery system to be simulated and the vacuum pressure at the outlet of the calculation domain defined are matched is determined according to the recovery rate, so that selection of a smoke recovery vacuum pump is carried out.

Description

Technical Field

[0001] This invention relates to the technical field of flue gas vacuum recovery simulation, and in particular to a simulation method for a CFD-based moxa smoke vacuum recovery system. Background Technology

[0002] The components of moxa smoke have extremely strong adsorption properties, adhering to room wall surfaces, seeping into clothing, and even lingering in the indoor air for a long time, posing a health hazard to both humans and furniture. Therefore, the recycling of moxa smoke has become a significant challenge in the promotion of moxibustion robots. However, the internal flow field of a vacuum moxa smoke recycling system is highly complex, involving heat transfer from the heat source, leading to uneven heating of the internal air and affecting the flow field, as well as the intense flow field movement caused by vacuum pressure. The combined effect of these two factors further complicates the flow field.

[0003] Simulating such a complex flow field is crucial for determining the appropriate pressure for moxibustion smoke recovery and for selecting the right structure. In actual experiments, using local measurement methods not only requires high precision in the measuring instruments, leading to high measurement costs, but also makes it difficult to fully understand the fluid movement within the system. This makes it impossible to accurately select and design the moxibustion smoke recovery system, and also makes it impossible to find the most suitable vacuum pressure.

[0004] However, CFD-based simulation of moxibustion smoke recovery utilizes computer-based methods to solve various conservation control partial differential equations for fluid flow. These equations reveal the distribution of physical quantities at different locations within the flow field. Therefore, CFD simulation is crucial for a complete representation of the vacuum recovery smoke flow field and even for the development of moxibustion robots. However, for the complex flow field simulation of moxibustion robots, if heat transfer is not considered or the heat transfer settings are incorrect, conventional CFD simulation methods cannot accurately simulate the flow conditions of the moxibustion smoke. Consequently, the matching between the vacuum pressure at the outlet and the moxibustion smoke vacuum recovery system cannot be accurately determined, making it impossible to accurately select the appropriate vacuum recovery pump for the system.

[0005] Therefore, whether a simulation method for a CFD-based vacuum recovery system of moxa smoke can be studied in order to select a vacuum recovery pump for the recovery system in moxibustion robots has become an urgent problem to be solved. Summary of the Invention

[0006] In view of this, the present invention provides a simulation method for a CFD-based vacuum recovery system for moxa smoke to solve the problems existing in the background art.

[0007] The technical solution provided by this invention is specifically a simulation method for a CFD-based vacuum recovery system for moxa smoke, which includes the following steps:

[0008] S1: Based on the vacuum recovery system of moxa smoke to be simulated, a three-dimensional model of the computational domain is established, and the interface between the heat source solid region and the fluid region in the computational domain is coupled to obtain the three-dimensional model of the computational domain after coupling.

[0009] S2: Collect the physical field data of the simulated moxa smoke vacuum recovery system, determine the solution model, define the source, define the heat source region conditions, fluid region conditions, boundary conditions, and define the vacuum pressure at the outlet of the computational domain. Then, divide the computational domain into three-dimensional model meshes and perform a mesh irrelevance test. After the mesh is verified to be irrelevance, import it into ANSYS Fluent software. First, perform CFD solution for the continuous phase in the Euler coordinate system, and then perform solution for the discrete phase in the Lagrange coordinate system.

[0010] S3: Based on the CFD solution, the recovery rate is calculated according to the expression of the flue gas recovery rate, and the recovery rate is used to determine whether the vacuum pressure at the outlet of the simulated smoke recovery system matches the vacuum pressure at the defined computational domain outlet.

[0011] Preferably, in step S1, a three-dimensional model of the computational domain is established based on the simulated moxa smoke vacuum recovery system, specifically as follows:

[0012] Structural data of the simulated moxa smoke vacuum recovery system were collected, and a three-dimensional model was established based on the structural data.

[0013] The interior of the three-dimensional model is filled with fluid and a heat source solid is established to form the established computational domain three-dimensional model;

[0014] The structural data includes the geometric dimensions and positional relationships of each component in the moxa smoke recovery system. The moxa smoke recovery system consists of a smoke recovery hood, a smoke recovery conduit, moxa sticks, and a vacuum recovery pump. The smoke recovery conduit is connected to the smoke recovery hood, and the vacuum recovery pump is connected to the end of the smoke recovery conduit. The moxa sticks extend vertically into the center of the smoke recovery hood from the top opening.

[0015] Further optimization, in step S1, the coupling treatment of the interface between the solid heat source region and the fluid region in the computational domain is specifically as follows: the solid heat source region and the fluid region are constructed into a single component using ANSYS Design Modeler software.

[0016] Further optimization, in step S2, the physical field data of the simulated moxa smoke vacuum recovery system includes: the average flow velocity, dynamic viscosity, density, and fixed size of the fluid inside the simulated moxa smoke vacuum recovery system; the thickness, temperature, and composition of the moxa stick heat source; the composition of the smoke generated by the moxa stick; the volume fraction, density, thermal conductivity, particle mass per second, particle size, and initial velocity of particles entering the fluid domain of the smoke particles in the system; the material of the smoke recovery hood and its density, thermal conductivity, and temperature; and the pressure of the vacuum pump.

[0017] Further preferably, the solution model includes: a continuous air phase turbulence model, an energy equation, and a force model of the discrete particle phase.

[0018] Further preferably, the air continuous phase turbulence model is a k-epsilon turbulence model, where k is the turbulent kinetic energy; ε is the turbulent dissipation rate; μ is the turbulent viscosity coefficient; ρ is the fluid density; and σ is the turbulent viscosity coefficient. k σ ε The Prandtl numbers are respectively associated with the turbulent kinetic energy k and the turbulent dissipation rate ε; and the transport equations for k and ε are respectively:

[0019]

[0020]

[0021] in:

[0022]

[0023] Further preferred, the energy equation is: the rate of increase of energy in the infinitesimal element is equal to the work done by all forces in the recovery system, including volume forces, surface forces, and the work done by the net mass of the fluid on the infinitesimal element; its expression is:

[0024]

[0025] In the formula, T represents temperature, k represents the heat transfer coefficient of the fluid, and c p For specific heat capacity, the four terms represent the rate of temperature change, convection term, diffusion term, and source term, respectively. The source term mainly represents the heat released from the flue gas source.

[0026] Further preferably, the force model of the discrete phase of the particles is the Stokes drag model, and the specific expression is as follows:

[0027]

[0028] In the formula, And λ is the mean free path of the molecule;

[0029] The virtual mass force refers to the additional force exerted on the particles by the airflow during the vacuum recovery process of the moxa smoke particles. This virtual mass force can be expressed as:

[0030]

[0031] In the formula, C is the virtual mass coefficient. vm It is 0.5;

[0032] The pressure gradient force, which is the additional force exerted on a particle by the air pressure gradient, is expressed as:

[0033]

[0034] The thermophoretic force, as an additional force, incorporates the thermophoretic effect on the particle, and its expression is:

[0035]

[0036] In the formula, D T,p This is the thermophoretic coefficient;

[0037] The force balance governing equations for the discrete phase are:

[0038]

[0039] In the formula, m p The mass of the particles; The velocity of the continuous phase; ρ is the particle velocity; ρ is the density of the continuous phase; ρ p The density of the particles; For additional force; For particle drag force; τ r denoted as the relaxation time of the particle.

[0040] Further optimization, in step S2, defining the heat source, defining the heat source region conditions, the fluid region conditions, and the boundary conditions specifically includes:

[0041] The source of the emission includes: the type of smoke particles, the velocity of the emission vector, the amount of smoke emitted per unit time, the initial temperature of the smoke particles, the particle size, and the material.

[0042] The conditions of the heat source region include: materials and temperature;

[0043] The fluid region conditions are an incompressible ideal gas;

[0044] The boundary conditions include the temperature and material of each boundary of the computational domain, wherein the boundary includes walls and phase inlets / outlets.

[0045] Further optimization involves step S3, where the recovery rate is calculated based on the CFD solution and the expression for the flue gas recovery rate. The recovery rate is then used to determine whether the vacuum pressure at the outlet of the simulated smoke recovery system matches the vacuum pressure at the defined computational domain outlet. Specifically:

[0046] Based on the CFD solution, the velocity changes of gas in various parts of the recovery system are analyzed by fluid velocity vector diagrams or velocity streamline diagrams, and discrete fitting curves of the relationship between velocity and displacement are generated.

[0047] The change in kinetic energy of the fluid at the wall can be obtained by measuring the change in dynamic pressure of the fluid at the wall surface;

[0048] The number of particles at various boundaries is obtained by tracking the discrete phase. The particle recovery rate is calculated according to the expression of the flue gas recovery rate. If the recovery rate is greater than or equal to the threshold, it is necessary to check whether the vacuum pressure at the outlet of the simulated smoke vacuum recovery system matches the vacuum pressure at the defined calculation domain. Otherwise, they do not match and the vacuum pressure at the outlet of the calculation domain needs to be reset.

[0049] The expression for the flue gas recovery rate is as follows:

[0050] In the formula, η is the recovery rate of the moxa smoke particles; N trap The number of particles captured at the vacuum pump of the recovery system is determined by setting the conditions for the discrete phase at the pressure outlet and at the other inlets and outlets. Specifically, the condition at the discrete phase pressure outlet is for capture, and the condition at the other inlets and outlets is for escape. Fluent calculations can then yield the number of smoke particles tracked under each condition; N occur The number of particles that enter the computational domain, i.e. the number of particles set at the source, is determined by the number of meshes involved on the source surface.

[0051] The present invention provides a CFD-based simulation method for a vacuum recovery system of moxa smoke. By coupling the interface between the fluid region and the solid heat source region in the computational domain of the simulated moxa smoke vacuum recovery system, the flow state of the smoke is accurately simulated. Appropriate solution models and boundary conditions are determined to obtain a CFD solution for the continuous phase. The results of the CFD solution are analyzed to obtain the recovery rate, thereby determining whether the vacuum pressure at the outlet of the simulated moxa smoke vacuum recovery system matches the vacuum pressure at the defined computational domain. When the vacuum pressure at the outlet matches, the selection of a vacuum pump for smoke recovery can be based on this vacuum pressure.

[0052] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit the disclosure of the present invention. Attached Figure Description

[0053] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0054] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0055] Figure 1 A flowchart illustrating a CFD-based simulation method for a vacuum recovery system of moxa smoke, as disclosed in this invention.

[0056] Figure 2 A simulation parameter setting framework diagram for a CFD-based vacuum recovery system for moxa smoke, provided in an embodiment of the present invention;

[0057] Figure 3 Three-dimensional model diagrams of two schemes in the moxa smoke vacuum recovery system;

[0058] Figure 4 This is a schematic diagram of the three-dimensional model of the computational domain in step S1;

[0059] Figure 5 This is a rendering of the 3D model of the computational domain in step S1.

[0060] Figure 6 The graphs show the recovery rates under various vacuum pressures from CFD simulations.

[0061] Figure 7 A vector diagram of the fluid velocity at section α under a vacuum pressure of 450 Pa within the moxa smoke vacuum recovery system;

[0062] Figure 8 The following are the discrete fitting curves and corresponding illustrations obtained after post-processing. Among them, (a) is the curve of fluid velocity and displacement under four vacuum levels, (b) is the illustration corresponding to (a), (c) is the curve of fluid velocity and displacement under another four vacuum levels, and (d) is the illustration corresponding to (c).

[0063] Figure 9 The following are the dynamic pressure distribution cloud maps of the fluid at the wall surface obtained after post-processing under various vacuum pressures: (a) is the dynamic pressure distribution cloud map of the fluid at the wall surface under a vacuum pressure of 330 Pa, (b) is the dynamic pressure distribution cloud map of the fluid at the wall surface under a vacuum pressure of 450 Pa, (c) is the dynamic pressure distribution cloud map of the fluid at the wall surface under a vacuum pressure of 560 Pa, and (d) is the dynamic pressure distribution cloud map of the fluid at the wall surface under a vacuum pressure of 660 Pa.

[0064] Figure 10 The figures show a comparison of the recovery results from the experiment and the CFD simulation analysis. (a) is the smoke recovery experiment under natural convection, (b) is the smoke recovery simulation under natural convection, (c) is the smoke recovery experiment under a vacuum pressure of 450 Pa, and (d) is the smoke recovery simulation under a vacuum pressure of 450 Pa. Detailed Implementation

[0065] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of methods consistent with some aspects of the invention as detailed in the appended claims.

[0066] To facilitate accurate determination of the matching between the vacuum pressure at the outlet of the moxa smoke vacuum recovery system and the system itself, and to facilitate accurate selection of the vacuum recovery pump, this implementation plan provides a CFD-based simulation method for the moxa smoke vacuum recovery system. (See [link to CFD simulation]). Figure 1 The simulation method includes the following steps:

[0067] S1: Based on the vacuum recovery system of the smoke to be simulated, a three-dimensional model of the computational domain is established, and the interface between the heat source solid region and the fluid region in the computational domain is coupled to accurately simulate the flow state of the smoke and obtain the three-dimensional model of the computational domain after coupling.

[0068] S2: Collect the physical field data of the simulated moxa smoke vacuum recovery system, determine the solution model, define the source, define the heat source region conditions, fluid region conditions, boundary conditions, and define the vacuum pressure at the outlet of the computational domain. Then, divide the computational domain into three-dimensional model meshes and perform a mesh irrelevance test. After the mesh is verified to be irrelevance, import it into ANSYS Fluent software. First, perform CFD solution for the continuous phase in the Euler coordinate system, and then perform solution for the discrete phase in the Lagrange coordinate system.

[0069] S3: Based on the CFD solution, the recovery rate is calculated according to the expression of the flue gas recovery rate, and the recovery rate is used to determine whether the vacuum pressure at the outlet of the simulated smoke recovery system matches the vacuum pressure at the defined computational domain outlet.

[0070] In step S1, a three-dimensional model of the computational domain is established based on the simulated moxa smoke vacuum recovery system, specifically as follows:

[0071] Structural data of the simulated moxa smoke vacuum recovery system were collected, and a three-dimensional model was built based on the structural data.

[0072] The interior of the three-dimensional model is filled with fluid and a heat source solid is established to form the established computational domain three-dimensional model;

[0073] The structural data includes the geometric dimensions and positional relationships of each component in the moxa smoke recovery system. The moxa smoke recovery system consists of a smoke recovery hood, a smoke recovery conduit, moxa sticks, and a vacuum recovery pump. The smoke recovery conduit is connected to the smoke recovery hood, and the vacuum recovery pump is connected to the end of the smoke recovery conduit. The moxa sticks extend vertically into the center of the smoke recovery hood from the top opening.

[0074] In step S1, the fluid region of the computational domain is determined by the structure of the vacuum recovery system. The internal space of the vacuum recovery system structure is filled to obtain the fluid region. The outlet of the fluid region is determined based on the location of the conduit where the vacuum pump is located, and the outlet surface is the suction surface of the vacuum pump at the conduit. The thickness of the heat source solid region of the computational domain is determined based on the thickness of the burning region of the moxa stick, and its positional relationship is determined by the position of the heat source of the moxa stick in the vacuum recovery system. In this embodiment, the position of the heat source of the moxa stick is as follows: Figure 4 , Figure 5 As shown. Those skilled in the art can establish a corresponding computational domain based on the specific structure of the moxibustion smoke recovery system, the location of the conduits, and the spatial position of the moxa stick heat source relative to the smoke recovery system. Figure 3 Two different structures of moxibustion smoke recovery systems are shown. One type places the duct on the same side as the air inlet, such as... Figure 3 (a), while another position is placed on the side next to it, such as Figure 3 (b)

[0075] The above-mentioned coupling processing of the interface between the heat source solid region and the fluid region in the computational domain specifically includes: constructing the fluid region and the heat source solid region as a single component in the ANSYS software—Design Modeler, that is, treating the two as a coupled relationship. Only through this coupling operation can the heat transfer inside the heat source solid be correctly simulated, thereby accurately simulating the flow state of the flue gas.

[0076] In step S2, the physical field data of the simulated moxa smoke vacuum recovery system include: the average flow velocity, dynamic viscosity, density, and fixed size of the fluid inside the simulated moxa smoke vacuum recovery system; the thickness, temperature, and composition of the moxa stick heat source; the composition of the smoke generated by the moxa stick; the volume fraction, density, thermal conductivity, particle mass per second, particle size, and initial velocity of particles entering the fluid domain of the smoke particles in the system; the material of the smoke recovery hood and its density, thermal conductivity, and temperature; and the pressure of the vacuum pump.

[0077] The physical field data collected above was simplified as follows: the moxa smoke particles were approximated as uniformly entering the internal space of the system; the recovery rate of the moxa smoke particles was approximated as the recovery rate of the smoke; the vacuum recovery hood and the recovery conduit were approximated as seamless; the actual pressure of the vacuum pump was approximated as the vacuum pressure of the cross section where the vacuum pump of the vacuum recovery system is located; the material of the solid heat source of the moxa stick was approximated as wood; and the material of the moxa smoke particles was approximated as wood.

[0078] The solution models include: the air continuous phase turbulence model, the energy equation, and the force model of the particle discrete phase.

[0079] Since the vacuum pressure values ​​used in the aforementioned vacuum recovery systems are all above 100 Pa, the fluid flow under this pressure is turbulent. Therefore, the continuous phase turbulence model under vacuum pressure in this implementation scheme is a feasible k-epsilon turbulence model. The selection of the above model is based on the specific pressure, choosing an appropriate turbulence model. For example, if a comparative experiment is to simulate the flow field motion under natural convection, a laminar flow model is selected for simulation. Since this implementation scheme is applicable to cases where the volume fraction of smoke particles in the flow field is within 12%, a discrete phase model is used for solution.

[0080] The relevant conditions of the heat source include: the type of smoke particles ejected, the ejection vector velocity, the ejection volume per unit time, the initial temperature of the smoke particles, the particle size, and the material. Those skilled in the art can set the above parameters accordingly based on different simulation scenarios. In this embodiment, the smoke particles enter the fluid region vertically downwards from the bottom surface of the heat source at a speed of 0.1 m / s in the form of surface generation. The material of the particles is wood, and they enter the fluid domain with a mass of 3.69e-6 kg per second. The particle size is 0.0002 mm, and the initial temperature of the particles is room temperature. The forces they experience include virtual mass force, thermophoretic force, pressure gradient force, and the drag equation is the strokes drag model.

[0081] The heat source area conditions include: material and temperature. In practice, the temperature can be set according to the actual burning of the moxa sticks using a temperature UDF program, so as to more closely simulate the combustion heat source with temperature change law. In this implementation plan, the material in the heat source area conditions is set to wood and the temperature is set to a constant of 600℃.

[0082] The conditions in the fluid region are those of an incompressible ideal gas. Since the pressure difference between the inlet and outlet of the vacuum recovery system to be analyzed in this embodiment is less than 20%, it can be approximated as an incompressible fluid for calculation, and the error is within the allowable range.

[0083] Boundary conditions define the temperature and material settings for each boundary of the computational domain, including walls and the inlets and outlets of each phase. In this implementation, the boundary conditions for the continuous phase (air) are: standard atmospheric pressure at the system inlet, open to the outside, and the difference between standard atmospheric pressure and vacuum pressure (i.e., the actual pressure) at the system outlet; both are at room temperature. The boundary conditions for the walls are: the recovery hood wall is made of wood, the duct wall is made of rubber, both are at room temperature, and there is no slippage. The boundary conditions for the discrete phase (smoke particles) are: escape at the system inlet, capture at the system outlet, and reflection at the walls.

[0084] Figure 2 The specific framework for the CFD simulation parameter settings of the moxa smoke vacuum recovery system in this embodiment is shown.

[0085] The vacuum pressure at the computational domain outlet was set to 330 Pa, 450 Pa, 560 Pa, and 660 Pa, and the flow field under these pressures was simulated. The results are as follows. Figure 8-9 .

[0086] After dividing the computational domain into a grid, the solution is performed. Specifically, since this implementation scheme uses a discrete phase model to simulate the recovery of internal smoke, and according to the diffusion law of smoke, the smoke is generated by the rising of heated air carrying smoke particles. Furthermore, the mass and volume of the discrete phase of the smoke particles are very small; only the influence of the continuous air phase needs to be considered, not the influence of the discrete smoke particles on the continuous air phase. Therefore, only a one-way coupling of these two phases needs to be calculated. To facilitate computational convergence, the continuous phase is first calculated in the Eulerian coordinate system, and then the discrete phase is calculated in the Lagrange coordinate system. The turbulence model used for the continuous air phase is a realizable k-epsilon model, which constrains the normal stress and uses the coefficient C in the turbulent viscosity. μ It is related to the strain rate and is not a constant. In the realizable k-epsilon model, k is the turbulent kinetic energy; ε is the turbulent dissipation rate; μ is the turbulent viscosity coefficient; ρ is the fluid density; and σ is the fluid density. k σ ε The Prandtl numbers are respectively associated with the turbulent kinetic energy k and the turbulent dissipation rate ε. The transport equations for k and ε are as follows:

[0087]

[0088]

[0089] in:

[0090]

[0091] Since this implementation plan involves heat exchange, it is necessary to consider using the energy equation. The energy equation states that the rate of increase of energy in the infinitesimal element is equal to the sum of all forces in the recovery system, including volume forces, surface forces, and the work done by the net mass of the fluid on the infinitesimal element. Its expression is:

[0092]

[0093] In the formula, T represents temperature, k represents the heat transfer coefficient of the fluid, and c p The specific heat capacity is represented by the four terms: the rate of temperature change, the convection term, the diffusion term, and the source term. The source term mainly represents the heat release from the smoke source. In the recovery system, all physical processes of the smoke can be represented by the source term, while the diffusion and convection terms represent the heat transfer between physical quantities in the smoke via conduction and convection, respectively.

[0094] The calculation model for the discrete phase of the moxa smoke particles is the Stokes drag model. Since the diameter of the moxa smoke particles falls within the range of submicron particles, the force model for the moxa smoke particles is the Stokes drag model, expressed as follows:

[0095]

[0096] In the formula, the parameter is the Cunningham correction factor for the Stokes drag formula, which is calculated as follows:

[0097]

[0098] Where λ is the mean free path of the molecule.

[0099] The virtual mass force refers to the additional force exerted on the particles by the airflow during the vacuum recovery process, caused by the accelerated movement of air. This virtual mass force can be expressed as:

[0100]

[0101] In the formula, C is the virtual mass coefficient. vm It is 0.5.

[0102] The pressure gradient force, which is the additional force exerted on the particle by the air pressure gradient, is expressed as:

[0103]

[0104] The thermophoretic force arises because a temperature gradient exists in the air of the vacuum recovery system. Small particles suspended in this space experience a force opposite to the direction of the temperature gradient. This phenomenon is called thermophoresis. ANSYS Fluent can incorporate the thermophoretic effect on particles into the additional force, expressed as follows:

[0105]

[0106] In the formula, D T,p For thermophoresis coefficients, the coefficients can be defined as constants, polynomials, or user-defined functions.

[0107] The force balance governing equations for the discrete phase can be written as:

[0108]

[0109] In the formula, m p The mass of the particles; The velocity of the continuous phase; ρ is the particle velocity; ρ is the density of the continuous phase; ρ p The density of the particles; For additional force; For particle drag force; τ r denoted as the relaxation time of the particle.

[0110] In step S3, based on the CFD solution, the recovery rate is calculated according to the expression of the flue gas recovery rate, and the recovery rate is used to determine whether the vacuum pressure at the outlet of the simulated smoke vacuum recovery system matches the vacuum pressure at the defined computational domain outlet. Specifically, based on the CFD solution, the velocity changes of the gas in various parts of the recovery system are analyzed by using a fluid velocity vector diagram or a velocity streamline diagram, and a discrete fitting curve of the relationship between velocity and displacement is generated.

[0111] The change in kinetic energy of the fluid at the wall can be obtained by measuring the change in dynamic pressure of the fluid at the wall surface;

[0112] The number of particles at various boundaries is obtained by tracking the discrete phase. The particle recovery rate is calculated according to the expression of the flue gas recovery rate. If the recovery rate is greater than or equal to the threshold, it is necessary to check whether the vacuum pressure at the outlet of the simulated smoke vacuum recovery system matches the vacuum pressure at the defined calculation domain. Otherwise, they do not match and the vacuum pressure at the outlet of the calculation domain needs to be reset.

[0113] Typically, the threshold is set to 98%. When the recovery rate is greater than 98%, the vacuum pressure at the outlet of the simulated moxa smoke vacuum recovery system matches the vacuum pressure at the defined calculation domain outlet. When the recovery rate is less than 98%, there is a mismatch, and the vacuum pressure at the outlet of the calculation domain can be reset. Step S2 is repeated for calculation until the recovery rate reaches 98%.

[0114] The post-processing analysis of the calculation results involves analyzing the velocity changes of the gas at various locations within the recovery system using fluid velocity vector diagrams or velocity streamline diagrams, generating discrete fitting curves showing the relationship between velocity and displacement; deriving the kinetic energy changes of the fluid at the wall surface by analyzing the dynamic pressure changes; and obtaining the number of particles at various boundaries by tracking the discrete phases, thus determining the flue gas particulate recovery rate. Detailed data on the flue gas recovery rates at vacuum pressures of 330 Pa, 450 Pa, 560 Pa, and 660 Pa used in this implementation scheme can be found in [link to relevant documentation]. Figure 6 .

[0115] The above method obtains the number of particles at various boundaries by tracking the discrete phase, thus yielding the smoke particle recovery rate. Specifically, it is first necessary to establish an evaluation index for the particle recovery rate within the smoke particle vacuum recovery system. In this implementation scheme, the size and mass of each smoke particle entering the computational domain are considered to be consistent. Therefore, the particle count is directly used as the numerical value for measuring the recovery rate, and its expression is as follows:

[0116]

[0117] In the formula, η is the recovery rate of the moxa smoke particles; N trap The number of particles captured at the vacuum pump of the recovery system is determined by setting the conditions for the discrete phase (Artemisia argyi particles) at the pressure outlet and at the other inlets and outlets. Specifically, the condition at the discrete phase pressure outlet is for capture, and the conditions at the other inlets and outlets are for escape. Fluent calculations can then obtain the number of Artemisia argyi particles tracked under each condition; N occur N represents the number of particles entering the computational domain, i.e., the number of particles set at the source. occur The value is determined by the number of grids involved in the source surface.

[0118] This implementation plan is obtained by visually adjusting the desired results. Figures 7-9 .in, Figure 7 This is a vector diagram of the fluid velocity at section α under a vacuum pressure of 450 Pa within the system. This diagram can accurately show the flow direction and velocity changes of the fluid in the flow field, and is more comprehensive and intuitive than traditional measurement methods. Figure 8 The discrete fitting curves obtained after post-processing the two sets of key data calculated are shown below, along with their graphical explanations. The first set of data represents the fluid velocity at eight equally spaced displacements within the system, from the bottom of the moxa stick at the moxibustion execution end to the outlet. The second set of data represents the velocity at nine points along the displacement path of the moxa smoke particles at the moxibustion execution end, as they are recovered from the bottom of the moxa stick and enter the inhalation tube. Figure 9The dynamic pressure change contour map of the fluid at the wall surface, calculated for this implementation scheme, reveals the location of the region with the strongest fluid kinetic energy, serving as a basis for structural optimization. The contour map shows that a blue area near the flue gas recovery hood outlet in the duct represents a region with relatively weak flue gas kinetic energy; beyond this area, the fluid kinetic energy rapidly increases. These two figures demonstrate that the greater the vacuum pressure supplied at the air pump, the greater the fluid kinetic energy; conversely, the greater the vacuum pressure supplied at the vacuum pump, the greater the fluid velocity.

[0119] Figure 10 (a) and Figure 10 (b) is a comparison of the flue gas flow test and CFD simulation recovery results under natural convection conditions. It can be found that by setting the three-dimensional model of the computational domain to fluid-structure interaction, the direction of the flue gas can be correctly simulated—escaping vertically upward along the moxa stick out of the recovery hood, and the amount of flue gas escape is almost consistent with the experiment. This proves that the fluid-structure interaction setting can accurately simulate the flow state of flue gas under the condition of having a heat source. Figure 10 (c) and Figure 10 (d) is a comparison of the flue gas flow test and CFD simulation recovery results under a vacuum pressure of 450Pa. It can be seen that the flue gas escape amount of the two is almost the same.

[0120] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the following claims.

[0121] It should be understood that the present invention is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A simulation method for a CFD-based vacuum smoke recovery system, characterized in that, Includes the following steps: S1: Based on the vacuum recovery system of moxa smoke to be simulated, a three-dimensional model of the computational domain is established, and the interface between the heat source solid region and the fluid region in the computational domain is coupled to obtain the three-dimensional model of the computational domain after coupling. S2: Collect the physical field data of the simulated moxa smoke vacuum recovery system, determine the solution model, define the source, define the heat source region conditions, fluid region conditions, boundary conditions, and define the vacuum pressure at the outlet of the computational domain. Then, divide the computational domain into three-dimensional model meshes and perform a mesh irrelevance test. After the mesh is verified to be irrelevance, import it into ANSYS Fluent software. First, perform CFD solution for the continuous phase in the Euler coordinate system, and then perform solution for the discrete phase in the Lagrange coordinate system. S3: Based on the solution results, the recovery rate is calculated according to the expression of the flue gas recovery rate, and the recovery rate is used to determine whether the vacuum pressure at the outlet of the simulated smoke recovery system matches the vacuum pressure at the defined calculation domain outlet. In step S1, a three-dimensional model of the computational domain is established based on the simulated moxa smoke vacuum recovery system, specifically as follows: Structural data of the simulated moxa smoke vacuum recovery system were collected, and a three-dimensional model was established based on the structural data. The interior of the three-dimensional model is filled with fluid and a heat source solid is established to form the established computational domain three-dimensional model; The structural data includes the geometric dimensions and positional relationships of each component in the moxa smoke recovery system. The moxa smoke recovery system consists of a smoke recovery hood, a smoke recovery conduit, moxa sticks, and a vacuum recovery pump. The smoke recovery conduit is connected to the smoke recovery hood, and the vacuum recovery pump is connected to the end of the smoke recovery conduit. The moxa sticks extend vertically into the center of the smoke recovery hood from the top opening.

2. The simulation method for the CFD-based vacuum smoke recovery system according to claim 1, characterized in that, In step S1, the coupling treatment of the interface between the solid heat source region and the fluid region in the computational domain is specifically as follows: the solid heat source region and the fluid region are constructed into a single component using ANSYS DesignModeler software.

3. The simulation method for the CFD-based vacuum smoke recovery system according to claim 1, characterized in that, In step S2, the physical field data of the simulated moxa smoke vacuum recovery system include: the average flow velocity, dynamic viscosity, density, and fixed size of the fluid inside the simulated moxa smoke vacuum recovery system; the thickness, temperature, and composition of the moxa stick heat source; the composition of the smoke generated by the moxa stick; the volume fraction, density, thermal conductivity, particle mass per second, particle size, and initial velocity of particles entering the fluid domain of the smoke particles in the system; the material of the smoke recovery hood and its density, thermal conductivity, and temperature; and the pressure of the vacuum pump.

4. The simulation method for the CFD-based vacuum recovery system of moxa smoke according to claim 1, characterized in that, The solution model includes: a continuous air turbulence model, an energy equation, and a force model for the discrete particle phase.

5. The simulation method for the CFD-based vacuum recovery system of moxa smoke according to claim 4, characterized in that, The continuous-phase air turbulence model is the k-epsilon turbulence model, where k is the turbulent kinetic energy; ε is the turbulent dissipation rate; and ρ is the fluid density. , The Prandtl numbers are respectively associated with the turbulent kinetic energy k and the turbulent dissipation rate ε; and the transport equations for k and ε are respectively: ； ； in: 。 6. The simulation method for the CFD-based vacuum recovery system of moxa smoke according to claim 4, characterized in that, The energy equation is as follows: the rate of increase of energy in the infinitesimal element is equal to the rate of increase of all forces in the recovery system, including volume forces, surface forces, and the work done by the net mass of the fluid on the infinitesimal element. Its expression is: ； In the formula, T represents temperature, k represents the heat transfer coefficient of the fluid, and c p For specific heat capacity, the four terms represent the rate of change of temperature, convection term, diffusion term, and source term, respectively. The source term represents the heat released by the smoke source.

7. The simulation method for the CFD-based vacuum recovery system of moxa smoke according to claim 4, characterized in that, The force model of the discrete phase of the particles is the Stokes drag model, and the specific expression is as follows: ； In the formula, ,and The mean free path of the molecules; The virtual mass force refers to the additional force exerted on the particles by the airflow during the vacuum recovery process of the moxa smoke particles. This virtual mass force can be expressed as: ； In the formula, is the virtual mass coefficient. It is 0.5; The pressure gradient force, which is the additional force exerted on a particle by the air pressure gradient, is expressed as: ； The thermophoretic force, as an additional force, incorporates the thermophoretic effect on the particle, and its expression is: ； In the formula, This is the thermophoretic coefficient; The force balance governing equations for the discrete phase are: ； In the formula, m p The mass of the particles; The velocity of the continuous phase; ρ is the particle velocity; ρ is the density of the continuous phase. The density of the particles; For additional force; For particle drag; denoted as the relaxation time of the particle.

8. The simulation method for the CFD-based vacuum smoke recovery system according to claim 1, characterized in that, In step S2, defining the heat source, defining the heat source region conditions, fluid region conditions, and boundary conditions specifically includes: The source of the emission includes: the type of smoke particles, the velocity of the emission vector, the amount of smoke emitted per unit time, the initial temperature of the smoke particles, the particle size, and the material. The conditions of the heat source region include: materials and temperature; The fluid region conditions are an incompressible ideal gas; The boundary conditions include the temperature and material of each boundary of the computational domain, wherein the boundary includes walls and phase inlets / outlets.

9. The simulation method for the CFD-based vacuum recovery system of moxa smoke according to claim 1, characterized in that, In step S3, based on the solution results, the recovery rate is calculated according to the expression for the flue gas recovery rate. Then, based on the recovery rate, it is determined whether the vacuum pressure at the outlet of the simulated smoke recovery system matches the vacuum pressure at the defined computational domain outlet. Specifically: Based on the solution results, the velocity changes of gas in various parts of the recovery system are analyzed by fluid velocity vector diagrams or velocity streamline diagrams, and discrete fitting curves of the relationship between velocity and displacement are generated. The change in kinetic energy of the fluid at the wall can be obtained by measuring the change in dynamic pressure of the fluid at the wall surface; The number of particles at various boundaries is obtained by tracking the discrete phase. The particle recovery rate is calculated according to the expression of the flue gas recovery rate. If the recovery rate is greater than or equal to the threshold, the vacuum pressure at the outlet of the simulated smoke recovery system matches the vacuum pressure at the defined calculation domain outlet. Otherwise, they do not match and the vacuum pressure at the outlet of the calculation domain needs to be reset. The expression for the flue gas recovery rate is as follows: ; In the formula, The recovery rate of Artemisia argyi smoke particles; The number of particles captured at the vacuum pump of the recovery system is obtained by setting the conditions of the discrete phase at the pressure outlet and the conditions at the other inlets and outlets. Specifically, the condition at the pressure outlet of the discrete phase is capture, and the condition at the other inlets and outlets is escape. Fluent calculation can obtain the number of smoke particles tracked under each condition. The number of particles that enter the computational domain, i.e. the number of particles set at the source, is determined by the number of meshes involved on the source surface.

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