A fluid simulation method for optimizing performance of a desulfurization tower mist eliminator unit

Abstract

The application discloses a kind of fluid simulation methods for the performance optimization of desulfurization tower mist eliminator unit, comprising S1. Establish three-dimensional entity model before optimization;S2. Extract fluid domain and grid division, establish finite element model;S3. Set turbulence model, boundary condition and solving algorithm;S4. Steady iterative calculation, analysis flow field, velocity, pressure distribution and pressure drop law, obtain performance evaluation result;S5. According to the evaluation result optimization structure, determine the structure parameter and establish three-dimensional entity model after optimization;S6. Repeat steps S2 to S4 for simulation to the model after optimization, compare the results before and after optimization, determine the operating parameters and unit structure after optimization.The application can accurately evaluate the performance of mist eliminator, guide and verify the design of new spline curve blade structure, realize the whole process optimization from problem diagnosis to scheme verification.

Description

Technical Field

[0001] This invention relates to the field of industrial gas-liquid separation device optimization technology, specifically to a fluid simulation method for optimizing the performance of a desulfurization tower demister unit. Background Technology

[0002] In industrial settings such as wet flue gas desulfurization (WFGD) towers in thermal power plants, large-scale ventilation and dehumidification systems, seawater desalination plants, and chemical absorption towers, saturated wet gases often carry a large number of liquid droplets during flow. If these droplets are not removed in time, they can significantly impact equipment operation. Gas-liquid separation is a critical process in industrial equipment such as thermal power plants, chemical towers, and wet flue gas desulfurization systems. Currently, commonly used demisters include wire mesh demisters, baffle demisters, and blade demisters. Among these, blade demisters are the most widely used in wet flue gas desulfurization, steam dehumidification, and air-cooled islands due to their advantages of low pressure drop, easy maintenance, and modular structure. Existing research largely focuses on the local optimization of traditional baffle structures, with insufficient research on three-dimensional vortex-enhanced structures.

[0003] As industrial plants grow in scale and desulfurization efficiency requirements increase, the existing demister structure is gradually revealing the following problems: (1) Limited demisting efficiency: Before optimization, the flow channel of the straight blade is a two-dimensional curve, and the airflow has weak rotation ability in the flow channel, resulting in insufficient collection efficiency of small-diameter droplets (20-50μm) and easy secondary water carryover.

[0004] (2) High flow resistance and high energy consumption: Existing baffle structure relies on multiple rapid turns to achieve droplet separation, which increases pressure drop and affects the overall operating energy consumption of the system.

[0005] (3) The phenomenon of droplet re-entrainment is obvious: the liquid film on the blade surface is easily peeled off under the action of high-speed mainstream to form re-atomized droplets, which increases the water mist content at the outlet and cannot meet the strict emission standards.

[0006] (4) Lack of effective simulation methods for spiral three-dimensional flow fields: Before optimization, the demister is often analyzed based on two-dimensional or quasi-three-dimensional models, which is not suitable for complex three-dimensional spiral curved surface flow channels.

[0007] With the development of gas-liquid separation technology towards high efficiency, low resistance, and compactness, the construction of novel demister structures has become a research hotspot. Achieving stable helical rotation of the airflow within the flow channel generates higher radial centrifugal force, which helps enhance droplet migration towards the blade wall. However, the three-dimensional complexity of the flow field increases the difficulty of experimental analysis. Therefore, developing a high-precision fluid simulation method for desulfurization tower demisters to simulate the changes in flow field distribution, velocity, and pressure is of great significance.

[0008] Currently, there is a lack of systematic simulation methods for expressing flow field characteristics. Therefore, a complete simulation process is needed for structural optimization, performance prediction, and engineering applications to provide technical support for the structural optimization and development of desulfurization tower demisters. Summary of the Invention

[0009] The technical problem to be solved by this invention is to provide a fluid simulation method for optimizing the performance of a desulfurization tower demister unit. This method can not only accurately evaluate the performance of the demister, but also directly guide and verify the design of a novel spline curve blade structure with high efficiency and low resistance, realizing the optimization of the entire process from problem diagnosis to solution generation and verification.

[0010] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows.

[0011] A fluid simulation method for optimizing the performance of a desulfurization tower demister unit includes the following steps: S1. Based on the geometric parameters of the internal blades and the external cylinder dimensions of the demister unit before optimization, establish a three-dimensional solid model; S2. Extract the fluid domain, name it, and mesh it from the three-dimensional solid model to establish the finite element model of the demister unit; S3. In the fluid simulation software, set the turbulence model and boundary conditions of the finite element model, as well as the gas medium and solution algorithm in the demister unit, and set the simulation parameters; S4. Set the operating condition parameters and perform steady-state iterative calculations to analyze the flow field distribution, velocity distribution, pressure distribution and pressure drop law of the demister unit under different operating conditions before optimization, and obtain the demister performance evaluation results; S5. Based on the demisting performance evaluation results of step S4, optimize the structure of the demister unit, determine the optimized structural parameters, and establish the optimized three-dimensional solid model based on the structural parameters; The optimized structural parameters are a novel spline curve blade structure, in which the blade is composed of two three-dimensional spline curves, each spline curve is composed of two tangent sub-curves, and a smooth and continuous three-dimensional helical surface is formed by lofting and thickened into a solid helical blade. S6. Repeat steps S2 to S4 to perform flow field simulation on the optimized 3D solid model, compare the simulation results before and after optimization, and determine the optimized operating parameters and unit structure.

[0012] Preferably, in step S2, the fluid domain extraction uses SpaceClaim software, specifically including: importing a three-dimensional solid model and performing geometric repair to automatically repair gaps, overlapping surfaces, or damaged boundaries; selecting the "Extract" option under the "Preparation - Fluid Volume" function and clicking on the internal hollow area to generate the internal fluid volume; naming the fluid domain, including the inlet, outlet, blade wall, and shell wall areas.

[0013] Preferably, in step S2, the mesh generation uses the ANSYS Meshing module, with a minimum size of 2mm, a maximum size of 30mm, and a growth rate of 1.2. The mesh is locally refined in the blade edge, near-wall region, and transition zone according to the characteristics of the blade channel. At the same time, multiple expansion layer meshes are arranged on the shell wall to ensure boundary layer resolution.

[0014] Preferably, in step S3, the k-ω SST model is selected as the turbulence model to capture the strong rotating flow and secondary flow structure guided by the helical blades; the boundary conditions are set as follows: the inlet is a velocity inlet, the outlet is a pressure outlet and zero gauge pressure is taken, and no-slip boundary conditions are used for both the blades and the shell wall; the fluid medium is set as sulfur-dioxide, the density is defined using an ideal gas model, and the dynamic viscosity is set using empirical values.

[0015] Preferably, in step S4, the flow field distribution, pressure distribution, and velocity distribution data are extracted using the post-processing function of the fluid simulation software. The rotating flow structure formed in the channel is analyzed, and the variation law of the high-speed region and the recirculation region is observed to determine the trend of the guiding intensity increasing with the inlet velocity. By comparing the variation characteristics of the total pressure drop under different operating conditions, the influence of structural parameters on fluid resistance is evaluated. By calculating the centrifugal force field intensity and droplet offset trend of the blade channel, the improvement law of demisting efficiency is predicted.

[0016] Preferably, the two three-dimensional spline curves in the spline curve blade structure are both cubic B-spline curves, and are constructed by constraints on the start point, end point, connection point, and end tangent direction. Adjacent sub-curves smoothly transition tangentially at the connection point. The specific construction method is as follows: The first spline curve is located in the middle of the outer wall of the central column. The starting point of its first sub-curve is (X0, Y0, Z0), the tangent azimuth is 90°, and the pitch angle is 5°. The ending point of the second sub-curve is (X0, Y0+200, Z0-40), the tangent azimuth is 90°, and the pitch angle is -5°. The two sub-curves are tangent at the junction of (X0, Y0+116, Z0-20). The second spline curve is set according to the endpoint position of the first spline curve. The starting point coordinates of its first sub-curve are (X0-130, Y0, Z0+60), the tangent azimuth angle is -90°, and the pitch angle is 5°. The endpoint coordinates of the second sub-curve are (X0-130, Y0+200, Z0-100), the tangent azimuth angle is -90°, and the pitch angle is -5°. The two sub-curves are tangent at the connection point (X0-130, Y0+100, Z0-23.5).

[0017] Preferably, in step S5, the process of establishing the optimized three-dimensional solid model further includes: Construct the central column of the blade fan, and use the array command to expand the spiral blades around the constructed central column at equal intervals to form a complete demister blade fan; A demister sleeve is constructed using a two-stage blade arrangement, with the first-stage blades positioned at the inlet and the second-stage blades positioned at the outlet, forming an optimized three-dimensional solid model.

[0018] Preferably, in step S6, the simulation results before and after optimization are compared. By analyzing the rotating flow structure formed in the helical blade channel, the variation law of the high-speed zone and the recirculation zone, and the variation characteristics of the total pressure drop under different operating conditions, the influence of the blade helical shape, blade pitch and shell length on fluid resistance is evaluated, and finally the optimized operating condition parameters and unit structure are determined.

[0019] Due to the adoption of the above technical solutions, the technical progress achieved by this invention is as follows.

[0020] This invention forms a complete closed-loop optimization process: it establishes a complete closed-loop optimization method from "original structure modeling → simulation analysis → structural optimization → post-optimization simulation verification", which overcomes the shortcomings of existing technologies such as single structure simulation and lack of optimization verification, and improves the credibility and reliability of optimization results.

[0021] This invention can significantly improve the collection efficiency of small-diameter droplets: the three-dimensional helical blade structure constructed by spline curves enables the airflow to generate stable helical rotation in the flow channel, forming a higher radial centrifugal force, which enhances the migration of droplets to the blade wall and effectively improves the collection efficiency of small-diameter droplets of 20-50μm.

[0022] This invention can reduce pressure drop and energy consumption: by using a smooth and continuous three-dimensional helical surface to replace the traditional baffle structure, multiple sharp turns are avoided, flow resistance is reduced, and the system's pressure drop and operating energy consumption are reduced.

[0023] This invention can reduce droplet re-entrainment: the optimized spiral flow channel allows droplets to migrate more smoothly toward the wall, reducing the peeling and re-atomization of the liquid film under the action of high-speed mainstream, and reducing the water mist content at the outlet.

[0024] This invention provides a high-precision simulation method: taking into account the special characteristics of three-dimensional helical curved surface flow channels, the k-ω SST turbulence model is used to capture strong rotating flow and secondary flow structure. By locally refining the mesh in the blade edge and near-wall region, the boundary layer resolution is guaranteed and the simulation accuracy is improved.

[0025] The optimized demister unit provided by this invention has a compact structure and strong machinability: the blade surface constructed by spline curves is smooth and continuous, with good machinability; the two-stage blade fan is arranged in the cylinder to form a gradient swirling motion, with a compact structure, suitable for various industrial scenarios. Attached Figure Description

[0026] Figure 1 This is a flowchart of the present invention; Figure 2 This is a three-dimensional solid model of the demister before optimization according to the present invention; Figure 3 This is a finite element model diagram of the demister before optimization according to the present invention; Figure 4 This is a diagram showing the fluid domain extraction and inlet / outlet settings of the demister before optimization according to the present invention; Figure 5 The flow field distribution cloud map of the demister before optimization of the present invention is shown at a flow velocity of 6 m / s and a temperature of 600°C. Figure 6 The pressure distribution cloud map of the demister before optimization of the present invention is shown at a flow velocity of 6 m / s and a temperature of 600°C. Figure 7 The velocity distribution cloud map of the demister before optimization of the present invention is shown at a flow rate of 6 m / s and a temperature of 600°C. Figure 8 This is a spline curve diagram of the optimized demister blades according to the present invention. Figure 9 This is a three-dimensional spiral surface diagram of the optimized demister blades of the present invention; Figure 10 This is a diagram of the optimized demister blades of the present invention; Figure 11 This is an optimized 3D solid model diagram of the present invention; Figure 12 This is a finite element model diagram of the optimized demister of the present invention; Figure 13 This is a diagram showing the optimized fluid domain extraction and inlet / outlet setting of the demister according to the present invention. Figure 14 The flow field distribution cloud map of the optimized demister of the present invention under the conditions of flow velocity of 6m / s and 600℃. Figure 15 The pressure distribution cloud map of the optimized demister of the present invention under the conditions of flow velocity of 6m / s and 600℃. Figure 16 This is a velocity distribution cloud map of the optimized demister of the present invention under the conditions of a flow rate of 6 m / s and a temperature of 600°C. Detailed Implementation

[0027] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0028] A fluid simulation method for optimizing the performance of a desulfurization tower demister unit, combined with Figure 1 As shown, it includes the following steps: S1. Establish the 3D solid model before optimization.

[0029] Based on the geometric parameters of the internal blades and the external cylinder dimensions of the demister unit before optimization, a three-dimensional solid model of the entire demister is established in a three-dimensional modeling environment, such as... Figure 2 As shown. Simultaneously, inlet and outlet channels, along with necessary support structures, are constructed to ensure the channels are completely sealed and meet the requirements for subsequent fluid domain extraction.

[0030] S2. Fluid domain extraction and mesh generation.

[0031] The fluid domain is extracted, named, and meshed from the 3D solid model to establish the finite element model of the demister element. The specific process is as follows: Save the model as a STEP file and import it into SpaceClaim software. In the main interface, click "File - Open" to load the complete solid model of the demister. After importing, first use "Repair - Inspect" to check the geometry and automatically repair any gaps, overlapping surfaces, or damaged boundaries that may exist in the design.

[0032] Next, fluid domain extraction is performed. Under the "Preparation - Fluid Volume" function, select the "Extract" option, click on the internal hollow area, and generate the internal volume for fluid calculations. For the inlet and outlet channels, they must be kept connected to the internal fluid domain to ensure the fluid volume is continuous and complete. After extracting the internal fluid domain, name it, including areas such as inlet, outlet, blade wall, and shell wall, for example... Figure 3 and Figure 4 As shown, this provides explicit surface properties for setting boundary conditions in Fluent. After geometry processing is complete, save the model in Fluent-readable .agdb or .scdoc format.

[0033] Subsequently, the fluid domain was meshed within the ANSYS Meshing module, with a minimum mesh size of 2 mm, a maximum mesh size of 30 mm, and a growth rate of 1.2. Based on the characteristics of the blade passage, the mesh was locally refined at the blade edges, near-wall region, and transition zone. Simultaneously, multiple expansion layer meshes were arranged on the shell wall to ensure boundary layer resolution, ensuring the overall mesh quality met the requirements of numerical computation. A finite element model of the demister element was then established, as follows: Figure 3 As shown.

[0034] S3. Simulation parameter settings.

[0035] In the fluid simulation software, the turbulence model and boundary conditions of the finite element model, the gas medium in the demister element, and the solution algorithm are set, and the simulation parameters are configured. The specific process is as follows: After meshing, the fluid domain is imported into the Fluent solver environment for fluid dynamics analysis. In the solver settings, a pressure-based steady-state solver suitable for low-to-medium speed gas flow is selected, and a gravity model is enabled to simulate the flow behavior of the demister under actual installation conditions. The fluid medium is set to sulfur-dioxide, and its density is defined using Fluent's built-in ideal gas model. The dynamic viscosity is set using empirical values.

[0036] To accurately capture the strong rotating flow and secondary flow structure guided by the helical blades, the k-ω SST turbulence model was selected in the "Models-Viscous" panel to ensure accurate turbulence prediction in both the near-wall and free-flow regions. In the boundary condition definitions, the demister inlet was set as a velocity inlet, and the outlet was set as a pressure outlet with zero gauge pressure. No-slip boundary conditions were applied to both the blades and the shell wall. Regarding the inlet velocity settings, to study the impact of different operating conditions on the flow field characteristics, only the inlet velocity value was changed to create different simulation conditions, while keeping all other physical properties, turbulence parameters, and wall conditions consistent.

[0037] S4. Simulation analysis before optimization.

[0038] Operating parameters were set and steady-state iterative calculations were performed to analyze the flow field distribution, velocity distribution, pressure distribution, and pressure drop characteristics of the demister unit under different operating conditions before optimization, thereby obtaining the demister performance evaluation results. The specific process is as follows: Steady-state iterative calculations were performed by setting operating parameters. After all parameters were set, the flow field was initialized and iterative solutions were started. The velocity field, pressure field, and turbulent flow residuals were monitored as convergence criteria. The solution was applied until the overall residual converged to less than 1 × 10⁻⁶. -4 The calculation is considered to have reached a steady state when the net mass imbalance between inlet and outlet is less than 0.5% of the total mass flow rate at the inlet.

[0039] Key data such as flow field distribution, pressure distribution, and velocity distribution inside the demister before optimization were extracted using Fluent post-processing. The flow field distribution cloud maps, pressure distribution cloud maps, and velocity distribution cloud maps inside the demister before optimization are shown below. Figure 5 , Figure 6 , Figure 7 As shown. By analyzing the rotating flow structure formed in the channel and observing the variation patterns in the high-speed and recirculation regions, the trend of increasing flow intensity with increasing inlet velocity can be determined. By comparing the variation characteristics of total pressure drop under different operating conditions, the influence of structural parameters (such as blade pitch and shell length) on fluid resistance can be evaluated. At the same time, by calculating the centrifugal force field intensity and droplet offset trend in the blade channel, the improvement pattern of demisting efficiency can be predicted.

[0040] This implementation ultimately obtained the changes in flow behavior, pressure drop, and demisting performance of the demister before optimization under different flow rate conditions, providing a quantitative basis for structural optimization. As shown in Table 1 below, by comparing the outlet pressure and velocity at different flow rates, it can be clearly seen that as the flow rate increases, the outlet pressure and velocity gradually increase, which means that the pressure drop shows an upward trend. The increased centrifugal force leads to an increased tendency for small-diameter droplets to deviate. Therefore, the optimization objective is to improve the collection efficiency of small-diameter droplets while controlling the increase in pressure drop. The parameters that need to be optimized include the blade spiral morphology and blade pitch.

[0041] Table 1. Comparison of outlet pressure and velocity at different flow rates

[0042] S5. Structural optimization and modeling.

[0043] Based on the demisting performance evaluation results in step S4, the structure of the demister unit is optimized, the optimized structural parameters are determined, and an optimized three-dimensional solid model is established based on the structural parameters.

[0044] The optimized structural parameters result in a novel spline curve blade structure. The blade is composed of two three-dimensional spline curves, each consisting of two tangent sub-curves. Each spline curve is a cubic B-spline curve, constructed using constraints at the start point, end point, connection point, and end tangent direction. Adjacent sub-curves are tangent at the connection point. The specific construction process is as follows: First, two three-dimensional spline curves are constructed for the helical blade. These two spline curves, serving as the leading and trailing edges of the blade, determine the overall spatial torsional morphology and thickness variation of the blade. Each spline curve consists of two tangent sub-curves to ensure first-order continuity during spatial transitions, giving the blade surface good smoothness and machinability. Figure 8 As shown.

[0045] The first spline curve is placed in the middle of the outer wall of the central column. The starting point coordinates of its first sub-curve are set to (X0, Y0, Z0), and its tangent direction is defined as follows: an azimuth angle of 90° is selected to extend it along the positive Y-axis, and the pitch angle is set to 5° to achieve a slight upward tilt relative to the XY plane, thereby forming the initial rotational guidance effect of the blade. The ending coordinates of the second sub-curve are set to (X0, Y0+200, Z0-40). Its tangent direction remains unchanged at an azimuth angle of 90°, but the pitch angle is adjusted to -5°. The two sub-curves are tangent at the connection point (X0, Y0+116, Z0-20), causing the curve to bend downward in space to form a spiral-shaped spatial rotation segment.

[0046] The second spline curve is set based on the endpoint of the first spline curve. The starting point coordinates of its first sub-curve are (X0-130, Y0, Z0+60), and the tangent azimuth angle is set to -90°, allowing it to unfold along the negative Y-axis. The pitch angle is also set to 5° to maintain the upward trend of the surface. The endpoint coordinates of the second sub-curve are set to (X0-130, Y0+200, Z0-100), with its tangent direction maintaining an azimuth angle of -90° and a pitch angle of -5°. The two sub-curves are tangent at the connection point (X0-130, Y0+100, Z0-23.5), thus creating a mirror-like guiding effect in the spatial torsion direction of the two spline curves, providing a geometric basis for the formation of a continuous streamlined blade shape on the helical surface.

[0047] Secondly, after constructing the two spline curves mentioned above, the "Loft Surface" function in the 3D modeling software is used to generate a smooth and continuous 3D helical surface using the two spline curves as boundaries, such as... Figure 9 As shown, the surface exhibits a distinct three-dimensional torsional structure due to the angle setting and endpoint arrangement of the two curves, allowing the airflow to form a controlled swirling path. Subsequently, the surface is transformed into a solid helical blade with structural strength using the "thicken" command, with the thickening direction facing one side of the flow channel, so that the overall blade has both fluid guiding capability and the necessary mechanical strength.

[0048] Then, in the blade and fan structure, a central column with a diameter of 150mm and a height of 200mm is constructed, and single helical blades are arranged in an equiangular array around the axis of the column. Multiple identical blades are replicated in a circular array to form a complete helical blade and fan assembly, such as... Figure 10 As shown. The number of array blades can be designed to be 15 to 25 depending on the demisting efficiency requirements. This embodiment adopts a 20-blade array layout, which makes the airflow present a uniform swirling structure along the overall blade length direction, which is beneficial for droplets to undergo inertial deflection and impact the blade surface when flowing over the blades.

[0049] Finally, the outer cylinder adopts a straight-cylinder structure design with an outer diameter of 217mm, a wall thickness of 12mm, and a total length of 3120mm, to accommodate a two-stage helical fan. The first-stage fan is positioned 200mm from the inlet channel to guide the initial swirling flow. The second-stage fan is positioned 1000mm from the outlet to enhance the swirling flow and perform secondary demisting. The two-stage fan structure creates a gradient swirling motion inside the cylinder, which continuously deflects fine droplets from the mainstream path and causes them to collide with the blade surface. Through the above implementation steps, an optimized three-dimensional solid model is constructed, such as... Figure 11 As shown.

[0050] Through the above implementation steps, a novel spline curve-based demister blade structure is constructed, which features a continuous and smooth blade shape, significantly enhanced flow channel swirl, and a compact overall structure, thus helping to improve demister efficiency and reduce energy consumption.

[0051] S6. Optimized simulation verification.

[0052] Repeat steps S2 to S4 to perform flow field simulation on the optimized 3D solid model, compare the simulation results before and after optimization, and determine the optimized operating parameters and element structure. The specific process is as follows: Save the optimized 3D solid model as a STEP file and import it into SpaceClaim software. Perform fluid domain extraction and mesh generation using the same method as in step S2 to establish the optimized demister element finite element model. Name the fluid domains, including areas such as the inlet, outlet, blade wall, and shell wall. Figure 12 and Figure 13 As shown.

[0053] Subsequently, the simulation parameters were set in Fluent using the same method as in step S3. The k-ωSST model was still selected as the turbulence model, the boundary conditions were kept consistent with those in step S3, and the fluid medium was still set as sulfur-dioxide. Regarding the inlet velocity settings, in order to study the influence of different operating conditions on the flow field characteristics, only the inlet velocity value was changed to create different simulation operating conditions, while keeping all other physical property parameters, turbulence parameters, and wall conditions consistent.

[0054] After all parameter settings are completed, the flow field is initialized and iterative solution is started. The velocity field, pressure field and turbulent flow residual are monitored as convergence criteria. The calculation is considered to have reached steady state when the overall residual converges to the preset tolerance and the net mass imbalance meets the requirements.

[0055] Key data such as flow field distribution, pressure distribution, and velocity distribution inside the optimized demister unit were extracted using Fluent post-processing. The optimized flow field distribution cloud maps, pressure distribution cloud maps, and velocity distribution cloud maps inside the demister unit are shown below. Figure 14 , Figure 15 , Figure 16 As shown. By analyzing the rotating flow structure formed in the helical blade channel and observing the variation patterns in the high-speed and recirculation regions, the trend of helical flow guiding intensity increasing with inlet velocity can be determined. By comparing the variation characteristics of total pressure drop under different operating conditions, the influence of blade helical morphology, blade pitch, and shell length on fluid resistance can be evaluated. At the same time, by calculating the centrifugal force field intensity and droplet offset trend in the blade channel, the improvement pattern of demisting efficiency can be predicted.

[0056] Finally, by continuously comparing the simulation results before and after the optimization of the operating parameters and the demister structure, and based on the comparison of outlet pressure and velocity under different flow rates before and after optimization, as shown in Table 2, it can be found that the optimized spline curve blade structure has stronger swirling intensity, lower pressure drop loss, and higher demisting efficiency under the same operating conditions, especially with a significant improvement in the collection efficiency of small-diameter droplets. Through comprehensive analysis, the optimized operating parameters and unit structure were determined.

[0057] Table 2 Comparison of outlet pressure and velocity before and after optimization at different flow rates

[0058] The working principle of this invention is as follows: (1) Simulation-driven optimization principle: This invention establishes a closed-loop process of "original structure analysis → simulation optimization → post-optimization verification". By simulating the flow field of the structure before optimization, the flow field distribution, velocity distribution, pressure distribution, and pressure drop characteristics under different operating conditions are obtained, and the defogging performance is quantitatively evaluated. Based on the simulation results, the optimization objectives and parameters to be optimized are determined to guide structural optimization and avoid blind design. The optimized structure is then simulated again for verification. By comparing the simulation results before and after optimization, the credibility and reliability of the optimization effect are ensured.

[0059] (2) The principle of swirl enhancement in spline curve blade structure: The spline curve blade structure consists of two three-dimensional spline curves, each composed of two tangent sub-curves, ensuring first-order continuity. This design makes the blade surface smooth and continuous, without abrupt inflection points. When airflow passes through the blade channel, it is guided by the three-dimensional torsional shape of the blade, forming a stable helical rotating flow. The rotating airflow generates radial centrifugal force, causing denser droplets to migrate towards the blade wall, where they are captured and separated upon impact. Specific parameter settings of ±90° azimuth and ±5° pitch allow the blade to form a mirror-like spatial torsional structure, maximizing the swirling flow intensity.

[0060] (3) Gradient separation principle of two-stage blade fan: A two-stage bladed fan is arranged within the cylinder to create a gradient swirling motion. The first-stage bladed fan is located at the inlet, guiding the airflow through initial swirling and separating larger droplets. The second-stage bladed fan is located at the outlet, further enhancing the swirling and performing secondary separation of smaller droplets. This gradient design ensures separation efficiency while avoiding the excessive pressure drop caused by an overly strong single-stage swirling motion. The spacing between the two-stage bladed fan is optimized to create a stable swirling attenuation and re-enhancing process within the cylinder.

[0061] (4) High-precision simulation principle: To address the unique characteristics of the three-dimensional helical curved surface flow channel, a k-ω SST turbulence model is employed. This model combines the accuracy of the k-ω model in the near-wall region with the stability of the k-ε model in the free flow region, accurately capturing strong rotating flows and secondary flow structures. By locally refining the mesh at the blade edges and near-wall regions and arranging multi-layer expanded meshes, boundary layer resolution is ensured, improving simulation accuracy. Multi-condition simulation analysis of the flow field characteristics at different flow velocities provides a comprehensive basis for structural optimization.

[0062] Through the synergistic effect of the above working principles, this invention achieves efficient optimization and performance improvement of the desulfurization tower demister structure.

Claims

1. A fluid simulation method for optimizing the performance of a desulfurization tower demister unit, characterized in that: Includes the following steps: S1. Based on the geometric parameters of the internal blades and the external cylinder dimensions of the demister unit before optimization, establish a three-dimensional solid model; S2. Extract the fluid domain, name it, and mesh it from the three-dimensional solid model to establish the finite element model of the demister unit; S3. In the fluid simulation software, set the turbulence model and boundary conditions of the finite element model, as well as the gas medium and solution algorithm in the demister unit, and set the simulation parameters; S4. Set the operating condition parameters and perform steady-state iterative calculations to analyze the flow field distribution, velocity distribution, pressure distribution and pressure drop law of the demister unit under different operating conditions before optimization, and obtain the demister performance evaluation results; S5. Based on the demisting performance evaluation results of step S4, optimize the structure of the demister unit, determine the optimized structural parameters, and establish the optimized three-dimensional solid model based on the structural parameters; The optimized structural parameters are a novel spline curve blade structure, in which the blade is composed of two three-dimensional spline curves, each spline curve is composed of two tangent sub-curves, and a smooth and continuous three-dimensional helical surface is formed by lofting and thickened into a solid helical blade. The two three-dimensional spline curves in the spline curve blade structure are both cubic B-spline curves, and are constructed by constraints on the start point, end point, connection point, and end tangent direction. Adjacent sub-curves smoothly transition tangentially at the connection point. The specific construction method is as follows: The first spline curve is located in the middle of the outer wall of the central column. The starting point of its first sub-curve is (X0, Y0, Z0), the tangent azimuth is 90°, and the pitch angle is 5°. The ending point of the second sub-curve is (X0, Y0+200, Z0-40), the tangent azimuth is 90°, and the pitch angle is -5°. The two sub-curves are tangent at the junction of (X0, Y0+116, Z0-20). The second spline curve is set based on the endpoint position of the first spline curve. The starting point coordinates of its first sub-curve are (X0-130, Y0, Z0+60), the tangent azimuth angle is -90°, and the pitch angle is 5°. The endpoint coordinates of the second sub-curve are (X0-130, Y0+200, Z0-100), the tangent azimuth angle is -90°, and the pitch angle is -5°. The two sub-curves are tangent at the connection point (X0-130, Y0+100, Z0-23.5). S6. Repeat steps S2 to S4 to perform flow field simulation on the optimized 3D solid model, compare the simulation results before and after optimization, and determine the optimized operating parameters and unit structure.

2. The fluid simulation method for optimizing the performance of a desulfurization tower demister unit according to claim 1, characterized in that: In step S2, the fluid domain extraction uses SpaceClaim software, which specifically includes: importing a three-dimensional solid model and performing geometric repair to automatically repair gaps, overlapping surfaces, or damaged boundaries; selecting the "Extract" option under the "Preparation - Fluid Volume" function and clicking on the internal hollow area to generate the internal fluid volume; naming the fluid domain, including the inlet, outlet, blade wall, and shell wall areas.

3. The fluid simulation method for optimizing the performance of a desulfurization tower demister unit according to claim 1, characterized in that: In step S2, the mesh generation uses the ANSYS Meshing module, with a minimum size of 2mm, a maximum size of 30mm, and a growth rate of 1.

2. The mesh is locally refined in the blade edge, near-wall region, and transition zone according to the characteristics of the blade channel. At the same time, multiple expansion layer meshes are arranged on the shell wall to ensure boundary layer resolution.

4. The fluid simulation method for optimizing the performance of a desulfurization tower demister unit according to claim 1, characterized in that: In step S3, the k-ω SST model is selected as the turbulence model to capture the strong rotating flow and secondary flow structure guided by the helical blades; the boundary conditions are set as follows: the inlet is a velocity inlet, the outlet is a pressure outlet and zero gauge pressure is taken, and no-slip boundary conditions are used for both the blades and the shell wall; the fluid medium is set as sulfur-dioxide, the density is defined using an ideal gas model, and the dynamic viscosity is set using empirical values.

5. The fluid simulation method for optimizing the performance of a desulfurization tower demister unit according to claim 1, characterized in that: In step S4, the flow field distribution, pressure distribution, and velocity distribution data are extracted using the post-processing function of the fluid simulation software. The rotating flow structure formed in the channel is analyzed, the variation law of the high-speed region and the recirculation region is observed, and the trend of the guiding intensity increasing with the inlet velocity is determined. By comparing the variation characteristics of total pressure drop under different operating conditions, the influence of structural parameters on fluid resistance is evaluated. By calculating the centrifugal force field intensity and droplet offset trend in the blade channel, the improvement law of demisting efficiency is predicted.

6. The fluid simulation method for optimizing the performance of a desulfurization tower demister unit according to claim 1, characterized in that: In step S5, the process of establishing the optimized 3D solid model also includes: Construct the central column of the blade fan, and use the array command to expand the spiral blades around the constructed central column at equal intervals to form a complete demister blade fan; A demister sleeve is constructed using a two-stage blade arrangement, with the first-stage blades positioned at the inlet and the second-stage blades positioned at the outlet, forming an optimized three-dimensional solid model.

7. The fluid simulation method for optimizing the performance of a desulfurization tower demister unit according to claim 1, characterized in that: In step S6, the simulation results before and after optimization are compared. By analyzing the rotating flow structure formed in the helical blade channel, the variation law of the high-speed zone and the recirculation zone, and the variation characteristics of the total pressure drop under different operating conditions, the influence of the blade helical shape, blade pitch and shell length on fluid resistance is evaluated, and finally the optimized operating condition parameters and unit structure are determined.

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