Method for improving waste gas collection efficiency of arc-shaped top suction gas collection hood based on interface mass-energy ratio

Abstract

A method for improving waste gas collection efficiency of an arc-shaped top suction gas-collecting hood based on an interface mass-energy ratio comprises the following steps: constructing a physical geometric model of the 1: 1 arc-shaped top suction gas-collecting hood by adopting space claim based on an ANSYS 2024 R1 simulation platform; defining the ratio of turbulent kinetic energy to mass flux on the mass-energy ratio interface as an interface mass-energy ratio; sequentially setting a plurality of groups of comparison working conditions by taking the number of the outlet air pipes, the layout of the outlet air pipes and the size of the outlet air pipes as single variables to finish simulation; exporting result data, and drawing a scatter diagram of the collection efficiency, the vortex volume and the interface mass-energy ratio; and the number, layout and size of the outlet air pipes are optimized according to the result, and the collection efficiency is maximized. According to the method, the limitation of relying on subjective judgment in the traditional empirical design is overcome, so that the performance of the flow field has comparability, and a clear scientific basis and a diagnostic tool are provided for subsequent optimization.

Description

Technical Field

[0001] This invention belongs to the technical field of waste gas collection, and specifically relates to a method for improving the waste gas collection efficiency of an arc-shaped top suction hood based on the interface mass-energy ratio. Background Technology

[0002] As an important component of industrial ventilation systems, arc-shaped top-suction fume hoods are widely used in work environments that generate harmful pollutants, such as welding, spraying, and grinding. Their core function is to achieve efficient capture of polluting gases or particulate matter through negative pressure suction. However, in practical applications, the collection efficiency of fume hoods often falls short of expectations, and their performance is unstable, seriously affecting workplace air quality and environmental compliance.

[0003] Existing fume hood designs are mostly based on empirical formulas or simplified models, primarily configuring them according to macroscopic parameters such as total exhaust volume, hood opening size, and distance from the pollution source. These methods neglect the complexity of the actual flow field inside the hood, particularly failing to adequately consider the impact of airflow uniformity and stability on pollutant transport. Existing research shows that inappropriate structural design can induce turbulent flow fields within the fume hood, manifesting as airflow short-circuiting, localized backflow, and vortex shedding. These undesirable flow patterns directly lead to uneven velocity distribution and incomplete negative pressure coverage in the capture area, thus limiting the fume hood's capture efficiency and causing pollutant escape. More critically, there is currently no unified and effective quantitative indicator to correlate the flow field distribution characteristics of the fume hood with its collection efficiency. Traditional evaluations often rely on average wind speed or pressure distribution, but these parameters cannot reflect key factors affecting capture stability, such as turbulence intensity and flow separation. Therefore, even if the system meets the design airflow requirements, a phenomenon of "high energy consumption and low efficiency" may still occur. Furthermore, the lack of understanding of the intrinsic mechanism between flow structure and trapping performance during the optimization process often leaves structural improvements at the trial-and-error level, making it difficult to achieve precise control.

[0004] In summary, establishing a new criterion that can characterize the internal flow field state of a gas collection hood and is closely related to collection efficiency, thereby guiding structural design and performance evaluation, has become a pressing technical challenge in this field. This invention aims to address the limitations of existing arc-shaped top-suction gas collection hoods, which rely on empirical design due to a lack of precise quantification of harmful eddies during operation. By introducing scientific evaluation methods and optimization criteria, it promotes the design of gas collection systems towards greater precision and scientific rigor.

[0005] The invention disclosed in CN109622549B provides a method for improving the collection efficiency of a volatile organic compound (VOCs) waste gas collection system. Its core lies in using CFD numerical simulation to regulate and optimize the system structure. The method first establishes a refined CFD model of the waste gas collection system, analyzing the deviation between the airflow of each branch pipe and the designed airflow. To address the airflow imbalance problem, regulating valves are installed on branches with larger deviations, and the valve opening is optimized through iterative simulation to achieve airflow balance between branches. Simultaneously, an isosceles triangular plate structure is added to the hood opening. By adjusting the height and spatial distribution of the triangular plate from its base to its top edge, the flow field at the hood opening is further optimized, reducing eddies and resistance. By combining the regulating valve with the isosceles triangle plate, this invention effectively solves the problem of low gas collection efficiency caused by pressure imbalance in complex pipeline systems. However, while solving the original problem, this solution introduces new structural problems. The added triangle plate structure forms a new physical obstruction and local vortex zone at the hood opening. Although it may improve the overall flow direction, these additional components themselves become new sources of resistance and may lead to particulate matter accumulation under certain operating conditions.

[0006] The invention with publication number CN120654613A proposes a method for vortex suppression structure of servo valve flow channel based on CFD simulation. This method involves constructing a flow field simulation model and combining it with the Q criterion. A multi-criteria fusion algorithm, including criteria and composite tensors, is used to identify vortex core regions. Response surface methodology and genetic algorithms are then employed to perform multi-objective optimization of parameters such as guide vane tilt angle, radius of curvature, and porosity gradient, achieving a certain degree of vortex suppression and improved flow performance. However, this method has certain limitations. First, it relies on complex vortex identification criteria and high-precision CFD post-processing, requiring specialized software and substantial computational resources, making it difficult to quickly determine the presence of significant vortices in the early stages of engineering design or during field operation. Second, this scheme only optimizes specific structures and lacks a universal and concise quantitative index to characterize the intensity and impact of vortices, thus limiting its applicability and preventing unified evaluation across equipment and operating conditions. Summary of the Invention

[0007] This invention addresses the aforementioned problems by proposing a method for improving the exhaust gas collection efficiency of an arc-shaped top-suction hood based on the interfacial mass-energy ratio. The interfacial mass-energy ratio R = k / G, where k is the average turbulent kinetic energy and G is the mass flux. This ratio comprehensively characterizes the turbulence cost per unit of effective capture and is significantly positively correlated with eddy volume. By increasing the number of ducts or optimizing their layout to reduce the R value, eddies can be effectively suppressed and flow field uniformity improved, thereby enhancing collection efficiency.

[0008] The method for improving the exhaust gas collection efficiency of an arc-shaped top-suction hood based on the interface mass-energy ratio uses an arc-shaped top-suction hood with several outlet ducts arranged along the central axis at the top. The bottom of the side plate of the arc-shaped top-suction hood has a natural air inlet 2 facing the wind. The windward side of the arc-shaped top-suction hood has an inlet 1 connected to the external exhaust system. A preset horizontal section inside the arc-shaped top-suction hood is defined as the mass-energy ratio interface 4. The steps include: S1. Model building: Based on the ANSYS 2024 R1 simulation platform, a 1:1 physical geometric model of the arc-shaped top suction gas collection hood was constructed using Space Claim; S2. Simulation parameter settings: Use Fluent meshing to generate a mesh for the model and verify mesh independence; import the generated mesh into the Fluent module for calculation, and set the turbulence model, component transport model, and viscosity model; set the initial boundary conditions; define the ratio of turbulent kinetic energy to mass flux on interface 4 as the interface mass-energy ratio; S3. Simulation scheme: Steady-state flow field simulation is performed on the physical geometric model of the arc-shaped top suction and gas collection hood. The number of outlet ducts 3, the layout of outlet ducts 3, and the size of outlet ducts 3 are used as single variables. Several sets of comparative working conditions are set in sequence to complete the simulation. S4. Plotting Results: Export the result data and plot a scatter plot of collection efficiency, eddy volume and interfacial mass-energy ratio; S5. Optimization scheme: Optimize the number, layout and size of outlet duct 3 based on the change curves of collection efficiency, eddy volume and interface mass-energy ratio to maximize collection efficiency.

[0009] As a preferred option, the standard k-ε model is used for the turbulence model in step S2, and its energy conservation equation is as follows: Turbulent kinetic energy k-equation:

[0010] Equation for turbulent dissipation rate ε:

[0011] Where ρ is the fluid density, kg / m³; t is time, s; k is the kinetic energy per unit mass, J / kg; and ε is the turbulent diffusion rate, s⁻¹. It is the velocity in the i-direction, in m / s; It is the displacement in the i-direction, m; It is eddy viscosity. ; and This is the term that generates turbulent kinetic energy k; , and These are empirical parameters; The formula for calculating turbulent kinetic energy is:

[0012] In the formula, k is the turbulent kinetic energy, with the unit being m² / s²; u', v', and w' are the velocity fluctuation components of the fluid in the x, y, and z directions, respectively, with the unit being m / s. As a preferred option, the component transport equations of the component transport model are as follows:

[0013] in , , These are the components of the velocity vector. Let be the diffusion coefficient of pollutants at any point in space. To simplify calculations, the diffusion coefficients in the x, y, and z directions are assumed to be the same. For a two-component gas mixture, the component diffusion coefficients are estimated using the Maxwell-Gilliland empirical formula to estimate the pollutant diffusion coefficients in the air. It is the mass concentration of pollutants. The source term refers to the intensity of pollutant release at any point.

[0014] Preferably, the initial boundary conditions include inlet velocity, inlet mass flow rate, outlet pressure, temperature, and exhaust gas composition mass fraction, wherein the exhaust gas composition mass fraction is referenced to the exhaust gas composition escaping from the AO pool.

[0015] Preferably, S4 includes: S41. After the Fluent simulation converges, the velocity gradient tensor of each mesh in the physical model is extracted using Fluent's built-in post-processing function. Based on this, the symmetric part of the tensor, i.e., the strain rate tensor (S), and the antisymmetric part, i.e., the vorticity tensor (Ω), are calculated. Then, the field is calculated according to the definition of Q-Criterion:

[0016] Where ||Ω|| 2 Let ||S|| be the squared Frobenius norm of the vorticity tensor. 2 The Frobenius norm square of the strain rate tensor is used; finally, a threshold greater than zero is set to identify and visualize the vortex core region. The region with a positive Q value represents the rotation-dominated flow state, i.e., the vortex structure; the part with a Q value greater than 0 is the vortex-dominated region. The volume of the vortex-dominated region is calculated, and the correlation curve between the volume of the vortex-dominated region and the number of ducts is established. S42. Extract the average concentration and airflow data at the outlet of the gas collection hood from the Fluent simulation results to calculate the gas collection efficiency of the gas collection hood. The formula for calculating the gas collection efficiency of the gas collection hood is as follows:

[0017] In the formula, q represents the branch pipe air volume, with the unit being m³. 3 / h;c 出 The concentration of pollutants in the outlet branch pipe is expressed in g / m³. 2 ;m 入 The inlet mass flow rate is expressed in g / s. S43. Finally, using the interfacial mass-energy ratio as the abscissa and the collection efficiency and eddy volume as the ordinate, a scatter plot of the collection efficiency, eddy volume and interfacial mass-energy ratio for each set of comparative working conditions is drawn.

[0018] Preferably, the air inlet width of the arc-shaped top suction hood is 6 meters, the hood body length is 14 meters, the height is 1.5 meters, and the equation of the arc-shaped curved surface at the top is: .

[0019] As a preferred option, the mass-energy ratio interface 4 is set according to the position of the wind speed control of the gas collection hood.

[0020] Preferably, the mass-energy ratio interface 4 is 0.5m above the surface of the water where pollutants volatilize.

[0021] The innovative aspects of this invention include: 1. The "interface mass-energy ratio" is proposed and defined as the core criterion, which is to quantitatively evaluate the balance between ineffective disturbance and effective capture in the flow field by calculating the ratio of turbulent kinetic energy to exhaust gas mass flux at the key section of the gas collection hood.

[0022] 2. Establish a quantitative relationship model between the interface mass-energy ratio R and the collection efficiency η, determine the optimal range of R, and take adjusting the actual R value to the optimal range as the direct goal, guide the optimization design of the gas collection hood structural parameters in reverse, and form a scientific design method with clear objectives and predictable results.

[0023] The beneficial effects of this invention include: 1. It overcomes the limitations of relying on subjective judgment in traditional experience-based design, making the performance of the flow field comparable and providing clear scientific basis and diagnostic tools for subsequent optimization.

[0024] 2. The optimization design of the gas collection hood has been transformed from a blind trial-and-error mode of "trying to adjust the structure and observe the effect" to a scientific design process with the explicit goal of actively adjusting the R value to a specific optimal range. The design goal becomes clear and quantifiable, and the optimization results are highly predictable in the design and simulation stages, significantly shortening the development cycle and reducing trial-and-error costs. Attached Figure Description

[0025] Figure 1 This is a structural diagram of the arc-shaped top suction gas collection hood used in this invention.

[0026] Figure 2a This is a schematic diagram of the location of the outlet duct of the control group C-1 in this embodiment of the invention.

[0027] Figure 2b This is a schematic diagram of the location of the outlet duct of the control group C-2 in this embodiment of the invention.

[0028] Figure 3 This is a scatter plot of collection efficiency, interfacial mass-energy ratio, and eddy current volume in an embodiment of the present invention. Detailed Implementation

[0029] according to Figure 1 This invention relates to a method for improving the waste gas collection efficiency of an arc-shaped top-suction hood based on the interface mass-energy ratio. The arc-shaped top-suction hood features several outlet ducts 1 arranged along its central axis at its top. The bottom of the side panel of the arc-shaped top-suction hood has a natural air inlet 2 facing the wind. The windward side of the arc-shaped top-suction hood has a hood inlet 3 connected to an external exhaust system. The main structural dimensions of the arc-shaped top-suction hood are: length 14 meters, width 6 meters, and height 1.5 meters. The equation of its top arc-shaped curved surface is as follows: The preset horizontal section inside the arc-shaped top suction gas collection hood is defined as the mass-energy ratio interface 4. The mass-energy ratio interface 4 is set according to the position of the gas collection hood controlling the wind speed, and the height of the distance from the pollutant volatilization water surface is 0.5m.

[0030] The steps include: S1. Model building: Based on the ANSYS 2024 R1 simulation platform, a 1:1 physical geometric model of the arc-shaped top suction gas collection hood was constructed using Space Claim; S2. Simulation parameter settings: Use Fluent meshing to generate a mesh for the model and verify mesh independence; import the generated mesh into the Fluent module for calculation, and set the turbulence model, component transport model, and viscosity model; The turbulence model adopts the standard k-ε model, and its energy conservation equation is as follows: Turbulent kinetic energy k-equation:

[0031] Equation for turbulent dissipation rate ε:

[0032] Where ρ is the fluid density, kg / m³; t is time, s; k is the kinetic energy per unit mass, J / kg; and ε is the turbulent diffusion rate, s⁻¹. It is the velocity in the i-direction, in m / s; It is the displacement in the i-direction, m; It is eddy viscosity. ; and This is the term that generates turbulent kinetic energy k; , and These are empirical parameters; The formula for calculating turbulent kinetic energy is:

[0033] In the formula, k is the turbulent kinetic energy, with the unit being m² / s²; u', v', and w' are the velocity fluctuation components of the fluid in the x, y, and z directions, respectively, with the unit being m / s. The component transport equations in the component transport model are as follows:

[0034] in , , These are the components of the velocity vector. Let be the diffusion coefficient of pollutants at any point in space. To simplify calculations, the diffusion coefficients in the x, y, and z directions are assumed to be the same. For a two-component gas mixture, the component diffusion coefficients are estimated using the Maxwell-Gilliland empirical formula to estimate the pollutant diffusion coefficients in the air. This is the mass concentration of the pollutant. The diffusion coefficient of the pollutant in the air is calculated to be 6.97 × 10⁻⁶. -5 m 2 s -1 , The source term refers to the intensity of pollutant release at any point.

[0035] Set initial boundary conditions, including inlet velocity, inlet mass flow rate, outlet pressure, temperature, and mass fraction of exhaust gas components; where inlet 1 of the gas collection hood has a mass flow rate of 5.22 × 10⁻⁶ kg. s -1 Natural air inlet 2 is a velocity inlet with a velocity of 0.5 m / s; the outlet condition is set as a pressure outlet with a value of -50 Pa; the surface of the gas collection hood and pipeline is an insulated wall. The mass fraction of the exhaust gas composition is referenced to the exhaust gas composition of the AO pool; the ratio of turbulent kinetic energy to mass flux at the mass-energy ratio interface 4 is defined as the interface mass-energy ratio. S3. Simulation Scheme: Steady-state flow field simulation was performed on the physical geometric model of the arc-shaped top suction hood. While maintaining a constant total exhaust volume of 29.4 m³ / s, several sets of comparative operating conditions were sequentially set up, using the number of outlet ducts 3, the layout of outlet ducts 3, and the size of outlet ducts 3 as single variables, to complete the CFD simulation. The specific scheme is shown in Table 1: Table 1. CFD Simulation Comparison Scheme Design and Parameter Settings

[0036] The diagram showing the duct location in the duct layout scheme is as follows: Figures 2a-2b . Figure 2a For side 1, the horizontal distance between the duct position and the center axis of the arc-shaped top suction hood in the width direction is 1m, and the ducts are evenly arranged along the length direction of the suction hood. Figure 2b For side 2, the horizontal distance between the duct position and the center axis of the arc-shaped top suction hood in the width direction is 2m, and the ducts are evenly arranged along the length direction of the suction hood.

[0037] S4. Plotting Results: Export the results data and plot scatter plots of collection efficiency, eddy volume, and interfacial mass-energy ratio. The specific process is as follows: S41. After the Fluent simulation converges, the velocity gradient tensor of each mesh in the physical model is extracted using Fluent's built-in post-processing function. Based on this, the symmetric part of the tensor, i.e., the strain rate tensor (S), and the antisymmetric part, i.e., the vorticity tensor (Ω), are calculated. Then, the field is calculated according to the definition of Q-Criterion:

[0038] Where ||Ω|| 2 Let ||S|| be the squared Frobenius norm of the vorticity tensor. 2 The Frobenius norm square of the strain rate tensor is used; finally, a threshold greater than zero is set to identify and visualize the vortex core region. The region with a positive Q value represents the rotation-dominated flow state, i.e., the vortex structure; the part with a Q value greater than 0 is the vortex-dominated region. The volume of the vortex-dominated region is calculated, and the correlation curve between the volume of the vortex-dominated region and the number of ducts is established. S42. Extract the average concentration and airflow data at the outlet of the gas collection hood from the Fluent simulation results to calculate the gas collection efficiency of the gas collection hood. The formula for calculating the gas collection efficiency of the gas collection hood is as follows:

[0039] In the formula, q represents the branch pipe air volume, with the unit being m³.3 / h;c 出 The concentration of pollutants in the outlet branch pipe is expressed in g / m³. 2 ;m 入 The inlet mass flow rate is expressed in g / s. S43. Finally, using the interfacial mass-energy ratio as the abscissa and the collection efficiency and eddy volume as the ordinate, a scatter plot of the collection efficiency, eddy volume and interfacial mass-energy ratio for each set of comparative working conditions is drawn.

[0040] The results of changing the number of ducts in the fume hood from 4 to 10 are shown in Table 2: Table 2 Comparison of key performance indicators under different duct quantity schemes

[0041] The results of changing the duct size in Option B are shown in Table 3: Table 3 Comparison of key performance indicators under different duct size schemes

[0042] The results of changing the duct layout in Option C are shown in Table 4: Table 4 Comparison of key performance indicators under different duct layout schemes

[0043] S5. Based on simulation and experimental data, plot a scatter plot with the interface mass-energy ratio as the x-axis and the collection efficiency and eddy volume as the y-axis, as shown below. Figure 3 As shown, the summary analysis of all simulation schemes indicates that data points with high collection efficiency and small eddy volume are concentrated in the range of interfacial mass-energy ratio from 0.0366 to 0.0412. Based on this, the present invention will... The optimal interfacial mass-energy ratio operating range for the arc-shaped top-suction gas collection hood is defined as this range. When the value is within this range, the system can synergistically maximize collection efficiency and minimize eddy current size.

[0044] The interfacial mass-energy ratio of the unoptimized benchmark gas collection hood mentioned in the first step was calculated to be 0.04708, which is higher than the optimal range for the interfacial mass-energy ratio. Based on the relational model... Figure 3 When the interface mass-energy ratio is higher than the optimal range, it indicates that there is excess relative kinetic energy and insufficient mass flux at the pollution source interface. The most effective measure to reduce the interface mass-energy ratio of the gas collection hood is to increase the number of ducts to improve the uniformity of airflow distribution, thereby reducing disturbance at the pollutant transport interface. The number of ducts was increased from 4 to 6, 7, and 9, while keeping the total airflow, duct diameter, and symmetrical layout unchanged, so that the optimized interface mass-energy ratio fell within the optimal range.

[0045] The optimized gas collection hood model was re-simulated using CFD, and compared with the original baseline model. Key performance comparisons are shown in Table 5. Table 5: Comparison of performance of the gas collection hood before and after optimization

[0046] This embodiment demonstrates that by applying the interface mass-energy ratio-based optimization method described in this invention, and specifically adjusting the number of ducts from 4 to 9, the system's interface mass-energy ratio is adjusted to the optimal range. This optimization significantly improves the internal flow field structure of the gas collection hood and achieves outstanding performance enhancement: after optimization, the vortex volume within the gas collection hood is reduced by 2.15 m³. 3 Meanwhile, the collection efficiency of the gas collection hood was improved by 21.5%. The results fully verify the effectiveness and engineering practical value of the method proposed in this invention in optimizing the flow field, improving collection efficiency, and suppressing eddies.

Claims

1. A method for improving the waste gas collection efficiency of an arc-shaped top-suction hood based on the mass-energy ratio of the interface, wherein the arc-shaped top-suction hood has an inlet (1) on its windward side; a natural air inlet (2) is provided at the bottom of the side plate of the arc-shaped top-suction hood; several outlet ducts (3) are arranged along the central axis at the top of the arc-shaped top-suction hood and connected to an external exhaust system; a preset horizontal section inside the arc-shaped top-suction hood is defined as the mass-energy ratio interface (4), the steps of which include: S1. Model building: Based on the ANSYS 2024 R1 simulation platform, a 1:1 physical geometric model of the arc-shaped top suction gas collection hood was constructed using Space Claim; S2. Simulation parameter settings: Use Fluent meshing to mesh the model and verify mesh independence; import the mesh into the Fluent module for calculation, set the turbulence model, component transport model and viscosity model; set the initial boundary conditions; define the ratio of turbulent kinetic energy to mass flux on the mass-energy ratio interface (4) as the interface mass-energy ratio; S3. Simulation scheme: Steady-state flow field simulation is performed on the physical geometric model of the arc-shaped top suction hood. The number of outlet ducts (3), the layout of outlet ducts (3), and the size of outlet ducts (3) are used as single variables in sequence. Several sets of comparative working conditions are set in sequence to complete the simulation. S4. Plotting Results: Export the result data and plot a scatter plot of collection efficiency, eddy volume and interfacial mass-energy ratio; S5. Optimization scheme: Optimize the number of outlet ducts (3), the layout of outlet ducts (3), and the size of outlet ducts (3) based on the change curves of collection efficiency, eddy volume and interface mass-energy ratio to maximize collection efficiency.

2. The method according to claim 1, characterized in that: The S2 turbulence model uses the standard k-ε model, and its energy conservation equation is as follows: Turbulent kinetic energy k-equation: Equation for turbulent dissipation rate ε: Where ρ is the fluid density, kg / m³; t is time, s; k is the kinetic energy per unit mass, J / kg; and ε is the turbulent diffusion rate, s⁻¹. It is the velocity in the i-direction, in m / s; It is the displacement in the i-direction, m; It is eddy viscosity. ; and This is the term that generates turbulent kinetic energy k; , and These are empirical parameters; The formula for calculating turbulent kinetic energy is: In the formula, k is the turbulent kinetic energy, with the unit being m² / s²; u', v', and w' are the velocity pulsation components of the fluid in the x, y, and z directions, respectively, with the unit being m / s.

3. The method according to claim 1, characterized in that, The component transport equations in the component transport model are as follows: in , , These are the components of the velocity vector. Let be the diffusion coefficient of pollutants at any point in space. To simplify calculations, the diffusion coefficients in the x, y, and z directions are assumed to be the same. For binary gas mixtures, the component diffusion coefficients are estimated using the Maxwell-Gilliland empirical formula to estimate the pollutant diffusion coefficients in the air. It is the mass concentration of pollutants. The source term refers to the intensity of pollutant release at any point.

4. The method according to claim 1, characterized in that: The initial boundary conditions include inlet velocity, inlet mass flow rate, outlet pressure, temperature, and exhaust gas composition mass fraction, which is referenced to the exhaust gas composition escaping from the AO pool.

5. The method according to claim 1, characterized in that, S4 include: S41. After the Fluent simulation converges, the velocity gradient tensor of each mesh in the physical model is extracted using Fluent's built-in post-processing function. Based on this, the symmetric part of the tensor, i.e., the strain rate tensor (S), and the antisymmetric part, i.e., the vorticity tensor (Ω), are calculated. Then, the field is calculated according to the definition of Q-Criterion: Where ||Ω|| 2 Let |S|| be the squared Frobenius norm of the vorticity tensor. 2 The Frobenius norm square of the strain rate tensor is used; finally, a threshold greater than zero is set to identify and visualize the vortex core region. The region with a positive Q value represents the rotation-dominated flow state, i.e., the vortex structure; the part with a Q value greater than 0 is the vortex-dominated region. The volume of the vortex-dominated region is calculated, and the correlation curve between the volume of the vortex-dominated region and the number of ducts is established. S42. Extract the average concentration and airflow data at the outlet of the gas collection hood from the Fluent simulation results to calculate the gas collection efficiency of the gas collection hood. The formula for calculating the gas collection efficiency of the gas collection hood is as follows: In the formula, q represents the branch pipe air volume, with the unit being m³. 3 / h;c 出 The concentration of pollutants in the outlet branch pipe is expressed in g / m³. 2 m 入 The inlet mass flow rate is expressed in g / s. S43. Finally, using the interfacial mass-energy ratio as the abscissa and the collection efficiency and eddy volume as the ordinate, a scatter plot of the collection efficiency, eddy volume and interfacial mass-energy ratio for each set of comparative working conditions is drawn.

6. The method according to claim 1, characterized in that: The arc-shaped top-mounted air intake hood has a windward opening width of 6 meters, a body length of 14 meters, and a height of 1.5 meters. The equation of the arc-shaped curved surface at the top is as follows: .

7. The method according to claim 1, characterized in that: The mass-energy ratio interface (4) is set according to the wind speed position of the gas collection hood.

8. The method according to claim 57, characterized in that: The mass-energy ratio interface (4) is 0.5m above the surface of the pollutant volatilization water.

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