A numerical simulation method for calculating performance of dust removal and denitration integrated filter material

Abstract

The application discloses a numerical simulation method for calculating the performance of dust removal and denitration integrated filter material, and belongs to the technical field of numerical simulation, which comprises the following steps: S1, obtaining the experimental result data of the performance of the integrated filter material; S2, simulating and calculating the relationship between the velocity and the pressure drop of the gas passing model based on the microstructure of the integrated filter material, obtaining the simulation parameters of the porous medium, and establishing a simplified model of the SCR fixed bed denitration reactor; S3, determining the specific parameter settings in the component transport and chemical reaction model, the porous medium model and the discrete phase model, and performing numerical simulation calculation, and comparing and analyzing the simulation results with the experimental results. The application uses the computational fluid dynamics (CFD) method, breaks through the limitation that the influence of particulate matter on the analysis accuracy of flue gas is large when the denitration efficiency is tested in the actual experiment, realizes the simulation calculation of the dust removal and denitration performances of the integrated filter material in the reactor at the same time, and guarantees the accuracy of the performance test of the integrated filter material.

Description

Technical Field

[0001] This invention relates to the field of numerical simulation, specifically to a numerical simulation method for calculating the performance of integrated dust removal and denitrification filter media. Background Technology

[0002] Air pollution mainly consists of fine particulate matter (PM) and toxic gases. Due to their small particle size, PM can remain suspended in the air for extended periods. Fine particulate matter smaller than PM2.5 is particularly easy to inhale into the lungs, leading to silicosis, pneumonia, and a range of other diseases. Toxic gases are primarily nitrogen oxides (NOx), a collective term for compounds composed of nitrogen and oxygen, with NO accounting for over 95% of the total. NOx is stable in the atmosphere and is toxic to both the atmospheric environment and human health. Integrated dust removal and denitrification filter media, by combining a denitrification catalyst with the dust removal filter media, can simultaneously remove PM and NOx within the dust collector filter bag. This shortens the process flow, reduces costs, and meets the treatment requirements for industrial flue gas (such as cement kilns, steel sintering, and coking).

[0003] However, in practical applications, dust-laden airflow can affect the accuracy of flue gas analysis, which reduces the accuracy of actual denitrification efficiency testing. The above problems urgently need to be solved. To this end, a numerical simulation method for calculating the performance of integrated dust removal and denitrification filter media is proposed. Summary of the Invention

[0004] The technical problem to be solved by this invention is: how to solve the impact of dust-laden airflow on the accuracy of flue gas analysis in practical applications, so as to improve the accuracy of actual denitrification efficiency testing, meet the requirements of energy conservation and emission reduction, and provide a numerical simulation method for calculating the performance of integrated dust removal and denitrification filter media.

[0005] The present invention solves the above-mentioned technical problems through the following technical solution, and the present invention includes the following steps:

[0006] S1: Obtain the experimental results data of the integrated filter media dust removal and denitrification performance that have been completed previously;

[0007] S2: Based on the microstructure simulation of integrated filter media, the relationship between gas velocity and pressure drop when passing through the model is calculated to obtain the simulation parameters of porous media and establish a simplified model of SCR fixed-bed denitrification reactor;

[0008] S3: Determine the specific parameter settings for the component transport and chemical reaction model, porous media model, and discrete phase model, and perform numerical simulation calculations. Compare and analyze the simulation results with experimental results.

[0009] Furthermore, in step S2, the integrated filter media follows the laws of conservation of mass, momentum, and energy in the numerical simulation of the flow field within the SCR fixed-bed denitrification reactor.

[0010] Furthermore, the expression for the law of conservation of mass is as follows:

[0011]

[0012] Where ρ is the fluid density; t is the flow time; u is the fluid velocity; and ▽ is the Hamiltonian operator.

[0013] The expression for the law of conservation of momentum is as follows:

[0014]

[0015] Where p is the pressure on the fluid element; τ is the viscous stress per unit volume of fluid; and f represents the force per unit mass of fluid.

[0016] The expression for the law of conservation of energy is as follows:

[0017]

[0018] Where p is the pressure on the fluid element; f is the force per unit mass of the fluid; e, u 2 / 2 represents the internal energy and kinetic energy per unit mass of fluid, respectively; k is the thermal conductivity coefficient; T is the temperature; and q is the heat transfer function per unit mass of fluid per unit time.

[0019] Furthermore, in step S2, the specific processing procedure is as follows:

[0020] S21: Medium Structure Simulation

[0021] The structure of the integrated filter media is simulated, including modeling of particle loading and distribution, and the movement of particles is calculated based on the DPM model of ANSYS-Fluent.

[0022] S22: Establishment of Gas Flow Model

[0023] Using the structural parameters of the medium, based on the fluid control equations, and employing the continuity equation, momentum equation, and energy equation, the initial and boundary conditions of the fluid control equations are set to describe the flow process state of the gas in the medium, and the relationship between the velocity and pressure drop when the gas passes through the integrated filter media model is calculated.

[0024] S23: Establishment of a simplified model for the SCR / VOC catalytic evaluation reactor device

[0025] The simplified SCR fixed-bed denitrification reactor was modeled using the 3D modeling software SpaceClaim, and the model dimensions were kept consistent with the experimental setup.

[0026] Furthermore, in step S3, a component transport and chemical reaction model is used to simulate the mixing degree of the SCR reaction gases and the reaction results, and the mass fraction Y of each substance is calculated using the convection-diffusion equation of the i-th substance. i The conservation equations are as follows:

[0027]

[0028] Among them, J i R is the diffusion flux of substance i; i It is the rate of formation of a chemical reaction; S i The generation rate for discrete phases and user-defined source terms;

[0029] The formula for calculating diffusion flux is as follows:

[0030]

[0031] Among them, Sc t It is the turbulent Schmidt number.

[0032] Furthermore, in step S3, the specific parameters that need to be determined in the component transport and chemical reaction model include: the proportion of NO gas, the proportion of HN3 gas, the proportion of O2 gas, the proportion of N2 gas, the gas composition in the simulated flue gas, and the SCR chemical reaction between nitrogen oxides and the denitrification catalyst.

[0033] Furthermore, in step S3, the simplified expression of the porous medium model is as follows:

[0034]

[0035] Among them, SS i is the momentum source term added to the i-th standard fluid flow equation; |v| is the magnitude of the velocity; α is the porosity coefficient; C2 is the inertial drag coefficient; μ is the dynamic viscosity.

[0036] Furthermore, in step S3, the specific parameters that need to be determined in the porous medium model include: the material of the porous medium, the setting of the calculation domain, the viscous drag coefficient, the inertial drag coefficient, the porosity, and whether the porous medium is anisotropic or isotropic.

[0037] Furthermore, in step S3, the specific parameters that need to be determined in the discrete phase model include the particle emission situation, initial velocity, particle type, and particle diameter. After inputting each parameter, the motion of the particles in the gas phase flow field is obtained through the discrete phase model.

[0038] Compared with the prior art, the present invention has the following advantages: The numerical simulation method for calculating the performance of integrated dust removal and denitrification filter media uses computational fluid dynamics (CFD) to overcome the limitation that particulate matter has a great influence on the accuracy of flue gas analysis when testing denitrification efficiency in actual experiments. It realizes the simultaneous simulation calculation of the dust removal and denitrification performance of the integrated filter media in the reactor, thus ensuring the accuracy of the integrated filter media performance test. Attached Figure Description

[0039] Figure 1 This is a flowchart illustrating the numerical simulation method for calculating the performance of integrated dust removal and denitrification filter media in Embodiment 1 of the present invention.

[0040] Figure 2 This is a simplified schematic diagram of the SCR fixed-bed reactor in Embodiment 2 of the present invention;

[0041] Figure 3(a) is a front view schematic diagram of the integrated filter material in Embodiment 2 of the present invention;

[0042] Figure 3(b) is a side view of the reactor model in Embodiment 2 of the present invention;

[0043] Figure 3(c) is a top view of the reactor model in Embodiment 2 of the present invention;

[0044] Figure 4 This is a pressure distribution diagram inside the pipes before and after the integrated filter media in Embodiment 2 of the present invention;

[0045] Figure 5 This is a velocity distribution diagram inside the pipes before and after the integrated filter media in Embodiment 2 of the present invention. Detailed Implementation

[0046] The embodiments of the present invention are described in detail below. These embodiments are implemented based on the technical solution of the present invention, and provide detailed implementation methods and specific operation processes. However, the scope of protection of the present invention is not limited to the following embodiments.

[0047] Example 1

[0048] like Figure 1 As shown in the figure, this embodiment provides a technical solution: a numerical simulation method for calculating the performance of integrated dust removal and denitrification filter media, the specific process of which is as follows:

[0049] Step 1: Obtain the experimental results data of the integrated filter media dust removal and denitrification performance that have been completed previously;

[0050] Step 2: Based on the microstructure simulation of the integrated filter media, calculate the relationship between gas velocity and pressure drop when the gas passes through the model, obtain the simulation parameters of the porous media, and establish a simplified model of the SCR fixed-bed denitrification reactor;

[0051] Step 3: Determine the specific parameter settings for the component transport and chemical reaction model, porous media model, and discrete phase model, and perform numerical simulation calculations. Compare and analyze the simulation results with experimental results.

[0052] In this embodiment, the microstructure simulation research approach is as follows: A geometric model is established; the dust removal performance is verified using the commercial software ANSYS-Fluent DPM model; boundary parameters are adjusted to obtain multiple sets of simulation data; the relationship between velocity and pressure drop is fitted; the data is compared with experimental data; and a basic database of filter media filtration efficiency and porous media parameters is obtained. The macroscopic simulation research on denitrification performance follows this approach: SCDM modeling simplifies the model; mesh generation is performed; the denitrification efficiency is studied using the component transport model of the commercial software ANSYS-Fluent; discrete equations are solved using the basic database of filtration efficiency and porous media parameters obtained from the microstructure simulation; the software is run to run the simulation data until convergence conditions are met to obtain the denitrification efficiency.

[0053] In step two, the fluid flow mainly follows three fundamental physical conservation laws: the law of conservation of mass, the law of conservation of momentum, and the law of conservation of energy. The numerical simulation of the flow field within the integrated filter media's NOx synergistic removal experimental device and detection system—specifically, the SCR fixed-bed denitrification reactor—must also incorporate these three conservation equations.

[0054] The expression for the mass conservation equation is shown in equation (1):

[0055]

[0056] Where ρ is the density of the fluid, with units of kg / m³. 3 ; t is the flow time in seconds; u is the fluid velocity in m / s; ▽ is the Hamiltonian operator.

[0057] The expression for the momentum conservation equation is shown in equation (2):

[0058]

[0059] Where p is the pressure on the fluid element; τ is the viscous stress on a unit volume of fluid; and f represents the force per unit mass of the fluid.

[0060] The energy conservation equation is derived from the first law of thermodynamics, and its expression is shown in equation (3):

[0061]

[0062] Where p is the pressure on the fluid element; f is the force per unit mass of the fluid; e, u 2 / 2 represents the internal energy and kinetic energy per unit mass of fluid, respectively, in J; k is the thermal conductivity coefficient, in W / (m²). 2·K); T is temperature in K; q is the heat transferred per unit mass of fluid per unit time.

[0063] In this embodiment, the specific process of step two is as follows:

[0064] 1. Media Structure Simulation: Using mathematical methods and tools, the structure of the integrated filter media is simulated, involving modeling of particle loading, distribution, and other aspects. The particle motion is calculated based on the ANSYS-Fluent DPM model.

[0065] 2. Gas flow model establishment: Using the medium structure parameters, based on the fluid control equations, the continuity equation, momentum equation, and energy equation are used to set the initial and boundary conditions of the fluid control equations to describe the relationship of the gas flow process in the medium and obtain the relationship between the model and the pressure drop.

[0066] 3. The simplified SCR reactor was modeled using the 3D modeling software SpaceClaim. The reactor was 70cm high, 7mm in diameter, and the porous medium was 2mm thick. The model dimensions were consistent with the experimental setup.

[0067] The following explains the relevant content of the component transport and chemical reaction model, porous media model, and discrete phase model in step three:

[0068] Component Transport and Chemical Reaction Model: In this embodiment of the SCR reaction, the fluid contains flue gas and SCR reaction gases. The degree of mixing of the SCR reaction gases and the chemical reaction results are required, which involves considering the mixing of substances in the flow. Specific parameters to be determined in the component transport and chemical reaction model include: the proportions of NO gas, HN3 gas, O2 gas, and N2 gas, simulating the gas composition in the flue gas and the SCR chemical reaction between nitrogen oxides and the denitrification catalyst. The component transport and chemical reaction model is used to simulate the degree of mixing of the SCR reaction gases and the reaction results. The mass fraction Y of each substance is calculated using the convection-diffusion equation for the i-th substance. i The conservation equations are as follows:

[0069]

[0070] Among them, J i R is the diffusion flux of substance i; i It is the rate of formation of a chemical reaction; S i The generation rate for discrete phases and user-defined source terms.

[0071] The method for calculating mass diffusion in turbulence is shown in the following formula:

[0072]

[0073] Among them, Sc t It is the turbulent Schmidt number, with a default value of 0.7.

[0074] Discrete Phase Model: ANSYS-Fluent can use the Discrete Phase Model (DPM) to calculate the motion and trajectory of particles dispersed in a flow field. Discrete phase calculations are performed from a Lagrangian perspective, meaning the calculation is performed on individual particles, unlike continuous phase calculations which are performed from an Eulerian perspective on spatial points. The DPM model is widely used in particle separation, aerosol dispersion, and coal combustion. The discrete phase model generally assumes a second volume fraction of less than 10-20% (but the particle mass carrying capacity can be greater than 10-20%). The DPM model requires settings for particle emission, initial velocity, particle type, and particle diameter. ANSYS-Fluent provides two particle diameter distributions: a Uniform distribution, where emitted particles are assumed to have the same diameter and velocity; and a Rosin-Rammler distribution, where particles have different diameters but the same velocity. For the Rosin-Rammler distribution, maximum, minimum, and average particle diameters need to be set. After inputting the parameters, the motion of particles in the gaseous flow field can be calculated.

[0075] The internal flow of the integrated denitrification filter media test platform is gas-liquid two-phase. Because the inlet particle concentration is relatively low and its effect on the continuous phase is negligible, according to the selection principle of simulation calculation model for two-phase flow and multiphase flow in ANSYS-Fluent, the discrete phase model (DPM) can be used to simulate the particle trajectory in this embodiment.

[0076] Porous media model: A porous media model uses a solid phase as the basic framework and non-framework components as pores. It is widely used to simulate the flow of porous components such as filter media, packing materials, and perforated plates. The modeling method for porous media involves adding a momentum source term to the standard fluid flow equations.

[0077]

[0078] Among them, SS i is the momentum source term added to the i-th (x, y, or z) standard fluid flow equation; |v| is the magnitude of the velocity; D and C are specified matrices.

[0079] The porous medium model can be simplified to the following expression:

[0080]

[0081] Where α is the porosity coefficient, in meters. 2C2 is the inertial drag coefficient, with units of m. -1 μ is the dynamic viscosity, measured in Pa·s.

[0082] In this embodiment, the specific parameters that need to be determined in the porous medium model include: the material of the porous medium, the setting of the computational domain, whether the porous medium is anisotropic or isotropic, the viscous drag coefficient, the inertial drag coefficient, and the porosity, etc.

[0083] Example 2

[0084] In this embodiment, the simplified SCR reactor was modeled using the 3D modeling software SpaceClaim. The reactor has a height of 70cm, a diameter of 7mm, and a porous media thickness of 2mm. The model dimensions are consistent with the experimental setup. Since the porous media model cannot achieve the desired dust filtration effect, to achieve this goal, the filter media fiber layer was simplified based on the approach described in the reference ("Research on Flow Field Characteristics and Filter Media Performance in Bag Filters," Liaoning University of Engineering and Technology, 2016, Chapter 4: Numerical Simulation of Dust Particle Filtration by Filter Media," pp. 24-25). It was assumed that the pore size and thickness of the filter media fiber layer were uniformly distributed, and the model was established as shown in Figures 3(b) and 3(c).

[0085] Based on the established model, the model was meshed using tetrahedral meshing software. Since the porous medium region is the key computational area, it was locally refined with a minimum mesh size of 0.01 mm. To conserve computational resources, the minimum mesh size for other regions was 0.04 mm, and the average mesh quality was 0.92, meeting the computational requirements.

[0086] Considering the fluid flow is laminar, for the porous medium model, the gas-solid drag is mainly viscous drag, and the inertial drag coefficient can be considered zero. Therefore, the expression for the porous medium becomes:

[0087]

[0088] In the formula, μ is the dynamic viscosity, Pa·s; 1 / α is the viscous drag coefficient, m -2 The pressure gradient generated by the momentum sink in the fluid is as follows:

[0089] Δp=S i Δn (9)

[0090] In the formula, Δn is the thickness of the porous medium.

[0091] This embodiment uses the microstructure of integrated filter media to simulate and calculate the relationship between airflow velocity and pressure drop when airflow passes through the model, and obtains porous media parameters to guide the denitrification reaction.

[0092] The specific details of the performance simulation of the integrated dust removal and denitrification filter media in this embodiment are as follows:

[0093] Based on the condition parameters of this embodiment, and from the material balance, the reaction rate constant is calculated as follows:

[0094]

[0095] In the formula: X is the NO conversion rate, %; Q is the gas flow rate, in L / min; W is the catalyst dosage, in g; W / Q is the mass of catalyst-treated gas per unit mass per minute.

[0096] The model's inlet and outlet are set as pressure-outlet and velocity-inlet, respectively.

[0097] The parameters of the discrete phase model are shown in Table 1.

[0098] Table 1 Parameter settings for the discrete phase model

[0099]

[0100]

[0101] The simulated flue gas composition was 500 ppm NO, 500 ppm NH3, 100 ppm SO2, and 5% O2 by volume, with N2 as the balance gas. The space velocity was 30,000 h⁻¹. -1 The denitrification activity of the catalyst was tested in the range of 100-300℃.

[0102] The simulation results are attached. Figure 4 , 5 As shown. From Figure 4 As can be seen from the static pressure distribution diagram of the pipeline before and after the integrated filter media, the reactor inlet section is darker in color, and the static pressure value inside the pipeline is very high, reaching about 50 Pa. The reactor outlet section is lighter in color, and the static pressure value inside the pipeline is small, almost zero. The static pressure value near the filter media is about 47 Pa. When the flue gas flows through the integrated filter media, the pressure inside the pipeline drops significantly.

[0103] from Figure 5As can be seen, the total number of injected particles is 500. Before reaching the integrated filter media, these particles maintain their original trajectory, moving in a straight line. When the particles reach the integrated filter media area, due to its trapping effect, a large number are intercepted, while only a small number pass through and reach the outlet. The trapping rate can be used to replace the filtration efficiency. Observations from the control panel show that the number of particles captured for 0.3μm, 0.5μm, and 1μm are 481, 494, and 498, respectively. The calculated filtration efficiencies of the integrated filter media for 0.3μm, 0.5μm, and 1μm particles are 96.2%, 98.8%, and 99.6%, respectively. The trapping rate for 3μm, 5μm, and 10μm particles is 100%, meaning the filtration efficiency of the integrated filter media is 100% for all of these particles. This indicates that the integrated filter media has a good interception effect on dust particles.

[0104] Based on the NO mass fraction distribution cloud maps obtained from experiments at 120℃, 160℃, 200℃, and 240℃, the inlet section of the reactor shows a very dark color, with an NO mass fraction of approximately 0.3%. During the diffusion of the mixed gas from the inlet to the outlet, the NO concentration remains essentially unchanged before contacting the integrated filter media. Upon contact with the integrated filter media, the NO distribution cloud map lightens in color, indicating a decrease in NO concentration. At T=120℃, after the reaction reaches stability, the NO mass fraction at the outlet stabilizes at approximately 0.232, allowing calculation of a denitrification efficiency of 22.7% for the integrated filter media at 120℃. Similarly, the NO conversion rates of the integrated filter media at 160℃, 200℃, and 240℃ are 34.2%, 55.1%, and 79.8%, respectively.

[0105] In summary, the numerical simulation method for calculating the performance of integrated dust removal and denitrification filter media in the above embodiments uses computational fluid dynamics (CFD) to overcome the limitation that particulate matter has a significant impact on the accuracy of flue gas analysis when testing denitrification efficiency in actual experiments. It enables simultaneous simulation calculation of both dust removal and denitrification performance of the integrated filter media in the reactor, ensuring the accuracy of integrated filter media performance testing.

[0106] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A numerical simulation method for calculating the performance of integrated dust removal and denitrification filter media, characterized in that, Includes the following steps: S1: Obtain the experimental results data of the integrated filter media dust removal and denitrification performance that have been completed previously; S2: Based on the microstructure simulation of integrated filter media, the relationship between gas velocity and pressure drop when passing through the model is calculated to obtain the simulation parameters of porous media and establish a simplified model of SCR fixed-bed denitrification reactor; S3: Determine the specific parameter settings for the component transport and chemical reaction model, porous media model, and discrete phase model, and perform numerical simulation calculations. Compare and analyze the simulation results with the experimental results. In step S2, the specific processing procedure is as follows: S21: Medium Structure Simulation The structure of the integrated filter media is simulated, including modeling of particle loading and distribution, and the movement of particles is calculated based on the DPM model of ANSYS-Fluent. S22: Establishment of Gas Flow Model Using the structural parameters of the medium, based on the fluid control equations, and employing the continuity equation, momentum equation, and energy equation, the initial and boundary conditions of the fluid control equations are set to describe the flow process state of the gas in the medium, and the relationship between the velocity and pressure drop when the gas passes through the integrated filter media model is calculated. S23: Establishment of a simplified model for the SCR / VOC catalytic evaluation reactor device The simplified SCR fixed-bed denitrification reactor was modeled using the 3D modeling software SpaceClaim, and the model dimensions were kept consistent with the experimental setup. In step S3, the specific parameters that need to be determined in the component transport and chemical reaction model include: NO gas ratio, HN3 gas ratio, O2 gas ratio, N2 gas ratio, simulating the gas composition in flue gas and the SCR chemical reaction between nitrogen oxides and denitrification catalyst; In step S3, the simplified expression of the porous medium model is as follows: ； in, This is the momentum source term added to the i-th standard fluid flow equation; It is the magnitude of the speed. The permeability coefficient of the porous structure; It is the coefficient of inertial drag; Dynamic viscosity; In step S3, the specific parameters that need to be determined in the discrete phase model include the particle emission situation, initial velocity, particle type, and particle diameter. After inputting each parameter, the motion of the particles in the gas phase flow field is obtained through the discrete phase model.

2. The numerical simulation method for calculating the performance of integrated dust removal and denitrification filter media according to claim 1, characterized in that, In step S2, the integrated filter media follows the laws of conservation of mass, momentum, and energy in the numerical simulation of the flow field within the SCR fixed-bed denitrification reactor.

3. The numerical simulation method for calculating the performance of integrated dust removal and denitrification filter media according to claim 2, characterized in that, The expression for the law of conservation of mass is as follows: ； in, It is the density of the fluid; For flowing time; It is the fluid velocity; For the Hamiltonian operator; The expression for the law of conservation of momentum is as follows: ； in, It is the pressure on a fluid micro-element; The viscous stress per unit volume of fluid; Represents the force per unit mass of a fluid; The expression for the law of conservation of energy is as follows: ； in, It is the pressure on a fluid micro-element; The force per unit mass of the fluid; , These are the internal energy and kinetic energy per unit mass of fluid, respectively. The thermal conductivity coefficient; For temperature; It is a function of the heat transferred per unit mass of fluid per unit time.

4. The numerical simulation method for calculating the performance of integrated dust removal and denitrification filter media according to claim 1, characterized in that, In step S3, a component transport and chemical reaction model is used to simulate the mixing degree of SCR reaction gases and the reaction results, utilizing the first The convection-diffusion equations for each substance are used to calculate the mass fraction Y of each substance. i The conservation equations are as follows: ； in, For matter The diffusion flux; It is the rate of formation of a chemical reaction; The generation rate for discrete phases and user-defined source terms; The formula for calculating diffusion flux is as follows: ； in, It is the turbulent Schmidt number.

5. The numerical simulation method for calculating the performance of integrated dust removal and denitrification filter media according to claim 1, characterized in that, In step S3, the specific parameters that need to be determined in the porous medium model include: the material of the porous medium, the setting of the calculation domain, the viscous drag coefficient, the inertial drag coefficient, the porosity, and whether the porous medium is anisotropic or isotropic.

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