Method for analyzing catalyst inlet flow field distribution characteristics for scr denitration

Abstract

The application discloses a catalyst inlet flow field distribution characteristic analysis method for SCR denitration, relates to the technical field of catalyst inlet flow field distribution analysis, and aims at solving the problem of uneven distribution of the catalyst inlet flow field. The physical model is constructed by boundary confirmation, deviation correction and physical property supplement, the problems of traditional parameter scattering distortion and model disconnection with the actual situation are solved, the parameter precision and model fitting degree are greatly improved, the calculation precision and efficiency are considered through grid independence and working condition comparison verification results, the problems of poor grid quality and convergence difficulty are avoided, and through space, cost and other constraint evaluation and sorting, the uneven flow field is effectively improved, the denitration efficiency is improved, and ammonia escape and catalyst wear are reduced.

Description

Technical Field

[0001] This invention relates to the field of catalyst inlet flow field distribution analysis technology, specifically to a method for analyzing the characteristics of catalyst inlet flow field distribution used in SCR denitrification. Background Technology

[0002] Current analysis of the catalyst inlet flow field in SCR denitrification systems suffers from several technical shortcomings: design parameter collection often relies on a single source (e.g., only referring to design drawings), failing to systematically integrate equipment resources and on-site measured data, and lacking multi-dimensional verification of completeness and rationality, easily leading to parameter distortion or omission; physical model construction often simplifies key structures such as guide vanes and rectifying components, failing to incorporate on-site measured data to correct deviations, resulting in low model-to-actual system fit; during flow field calculations, mesh generation lacks targeted partitioning and densification, control equations easily ignore turbulence characteristics or component transport processes, boundary conditions are subjectively set, and there is a lack of mesh independence and operational condition comparison verification, leading to insufficient reliability of calculation results; uniformity evaluation indicators are singular, optimization directions are general, making it difficult to accurately solve the problem of flow field non-uniformity, easily causing problems such as low denitrification efficiency, excessive ammonia slip, catalyst wear or blockage, affecting the stable operation of the system. Summary of the Invention

[0003] The purpose of this invention is to provide a method for analyzing the inlet flow field distribution characteristics of catalysts for SCR denitrification. This method constructs a physical model by confirming boundaries, correcting deviations, and supplementing physical properties, thus solving the problems of scattered and distorted parameters and model-actual discrepancies in traditional methods. This significantly improves parameter accuracy and model fit. The results are verified through mesh independence and operating condition comparison, balancing computational accuracy and efficiency while avoiding problems such as poor mesh quality and convergence difficulties. By evaluating and ranking based on constraints such as space and cost, the method effectively improves flow field uniformity, enhances denitrification efficiency, reduces ammonia slip and catalyst wear, and solves the problems in existing technologies.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] Methods for analyzing the catalyst inlet flow field distribution characteristics used in SCR denitrification include:

[0006] First, the design parameters of the SCR denitrification system are collected and verified. Based on these parameters, a physical model of the catalyst inlet region identical to that of the actual SCR denitrification system is constructed. The constructed physical model is discretized to generate grid cells suitable for flow field calculations. Governing equations are established based on the motion characteristics of the SCR denitrification catalyst inlet flow field. Furthermore, the boundary constraints and initial state parameters required for flow field calculations are confirmed. Numerical flow field calculations are performed based on the physical model, governing equations, and set conditions. Key characteristic parameters of the catalyst inlet flow field are extracted based on the numerical calculation results. The uniformity of the catalyst inlet flow field is evaluated based on the extracted flow field characteristics to determine if the flow field meets the catalyst operation requirements. Finally, the optimization direction of the catalyst inlet flow field is identified based on the key characteristic parameters and the uniformity evaluation results.

[0007] Preferably, the design parameters of the SCR denitrification system are collected and verified, including:

[0008] The design parameters include geometric parameters, process fluid parameters, equipment performance parameters, and system-related parameters.

[0009] Among them, geometric structural parameters include flue and reactor dimensions, flow guiding and rectifying components, catalyst inlet region and auxiliary structures; process fluid parameters include basic flue gas parameters, flue gas composition and fluid property related parameters; equipment performance parameters include catalyst performance and auxiliary equipment; system related parameters include unit foundation and connection relationships;

[0010] The design parameters were obtained from the design drawings, equipment resources, and on-site measured ports.

[0011] The collected design parameters are verified sequentially, including integrity verification, rationality verification, measurement accuracy verification, and cross-verification.

[0012] The design parameters are adjusted based on the verification results, and the final design parameters of the SCR denitrification system are obtained after the adjustment is completed.

[0013] Preferably, a physical model of the catalyst inlet region identical to that of the actual SCR denitrification system is constructed based on the obtained design parameters, including:

[0014] First, confirm the physical boundaries of the catalyst inlet region, including the longitudinal and lateral boundaries;

[0015] The three-dimensional morphology is reconstructed according to the design parameters. First, the main frame structure is constructed according to the design parameters. After the main frame structure is constructed, the structure of the guide vanes and rectifier components is reconstructed. Finally, the structure of the catalyst inlet area is constructed, which includes the inlet end face and the auxiliary structure of the inlet area.

[0016] The deviation of the catalyst inlet region after the three-dimensional morphology is restored is corrected. The deviation correction is as follows: based on the collected design parameters and field measurement data, the deviation of the structure of the catalyst inlet region after the three-dimensional morphology is restored is calculated. If there is a deviation in the catalyst inlet region after the three-dimensional morphology is restored, the deviation is corrected based on the field measurement data. After the deviation correction is completed, the geometric model of the catalyst inlet region is obtained.

[0017] The ensemble model is supplemented with physical properties, which include material properties and surface characteristics.

[0018] After the physical properties are supplemented, the physical model of the catalyst inlet region is obtained.

[0019] Preferably, the constructed physical model is discretized to generate mesh elements suitable for flow field calculations, including:

[0020] First, confirm the mesh type of the physical model. Mesh types include unstructured mesh, structured mesh, and hybrid mesh.

[0021] Next, the boundaries of the fluid region in the physical model are confirmed. Solid structures in the physical model are removed, including the baffle plate entity, the catalyst module body and the support beam. The cavity areas inside the flue, between the baffle plates and in front of the catalyst inlet are retained and marked as fluid flowable areas.

[0022] The fluid flowable region is divided into grid zones based on the confirmed grid type, including high grid density zones and low grid density zones. The high grid density zone includes the area near the catalyst inlet end face, the area around the guide vanes and porous rectifier plates, and the ammonia injection grid nozzle outlet area; the low grid density zone includes the straight section of the inlet flue and the non-critical area of ​​the reactor inner wall.

[0023] The fluid flowable region, after being divided into grids, is used to generate a grid using the grid generation tool of the flow field calculation software, and the generated grid is then refined in terms of surface and feature density.

[0024] The encrypted mesh is checked for multi-dimensional quality indicators, including mesh distortion, mesh aspect ratio, and mesh orthogonality. Based on the check results, meshes that do not meet the requirements are deleted or adjusted.

[0025] Finally, a complete physical model of the catalyst inlet flow field was obtained.

[0026] Preferably, the governing equations are established based on the motion characteristics of the SCR denitrification catalyst inlet flow field, including:

[0027] The flow characteristics of the catalyst inlet flow field are confirmed based on the design parameters, including flow pattern, medium characteristics and influencing factors;

[0028] Using the mass conservation and momentum conservation equations as the basic framework, the physical laws governing the flow characteristics of the catalyst inlet flow field are confirmed. The confirmation of physical laws includes establishing the continuity equation and the momentum equation, and supplementing it with a turbulence model, which is a k-ε two-equation model. The turbulence model is used to assist in the construction of the turbulence kinetic energy equation and the dissipation rate equation.

[0029] Further, the component transport equation and energy equation for the ammonia injection grid are supplemented;

[0030] Finally, all the constructed equations were verified. The verification was conducted to: verify whether the equations could capture key flow phenomena; and verify whether the equations conformed to the actual motion law of the catalyst inlet flow field.

[0031] After all verifications were successful, the governing equations for the inlet flow field of the SCR denitrification catalyst were obtained.

[0032] Preferably, the boundary constraints and initial state parameters required for the flow field calculation are confirmed, including:

[0033] First, the inlet boundary conditions are confirmed, including flow velocity, temperature, component concentration, and ammonia concentration. The flow velocity is confirmed based on the flue gas flow rate data provided in the SCR denitrification system design drawings, combined with the cross-sectional area of ​​the catalyst inlet region. The temperature is obtained from the design drawings as the design temperature value of the inlet flue gas of the SCR denitrification system. The component concentration is confirmed based on the specifications for flue gas components in the design parameters, determining the concentration of each major component in the inlet flue gas. The ammonia concentration is calculated based on the relationship between the ammonia injection rate and the flue gas flow rate, determining the mass fraction or mole fraction of ammonia at the inlet.

[0034] Next, the outlet boundary conditions are confirmed. The outlet boundary conditions include pressure and component concentration. The pressure is determined based on the resistance characteristics of the downstream equipment of the SCR denitrification system and the back pressure requirements during system operation. The component concentration is estimated based on the chemical reaction equilibrium principle and the simulation results of the inlet conditions and reaction process.

[0035] The wall boundary conditions are confirmed. The wall conditions include the no-slip condition of the solid wall and the wall roughness. The no-slip condition of the solid wall is to set the velocity component of the fluid at the wall to zero in both the direction perpendicular to the wall and the direction parallel to the wall for all solid walls in the catalyst inlet region. The wall roughness is to set the corresponding roughness parameters according to the actual roughness of the wall material.

[0036] The initial state parameters are confirmed, including the initial velocity distribution, initial temperature distribution, and initial component concentration distribution. The initial velocity distribution is initially set based on the inlet velocity and the geometry of the flow field region, using a simple linear or uniform distribution assumption to preliminarily determine the velocity values ​​of each grid cell in the flow field. The initial temperature distribution is set based on the inlet temperature and the adiabatic or heat dissipation conditions of the system. The initial component concentration distribution is set based on the concentrations of each component at the inlet and the initial assumptions about the mixing process.

[0037] Finally, all boundary constraints and initial state parameters were completed.

[0038] Preferably, numerical calculations of the flow field are performed based on the physical model, governing equations, and set conditions, including:

[0039] The discretized mesh file, governing equations, and fluid property parameters are used as the base data for import.

[0040] Next, configure the solver parameters, including solver type, coupling algorithm, and discretization scheme. The solver type is transient solver; the coupling algorithm is SIMPLE algorithm; the discretization scheme is as follows: the momentum equation and continuity equation use the second-order upwind scheme; the turbulence equation uses the first-order upwind scheme; and the multi-component transport equation uses the second-order central difference scheme.

[0041] After configuring the solver parameters, the iterative calculation parameters are set. The total number of iterations in the initial iteration phase is 500-1000 steps, and the total number of iterations in the later convergence phase is extended to 2000-5000 steps. Then, the convergence criteria are determined, and the residuals of the continuity equation and momentum equation are reduced to 10. -6 Below, the residuals of the k-equation and the ε-equation are reduced to 10. -4 Below, the residuals of the multi-component transport equations are reduced to 10. -5 the following;

[0042] After setting the iterative calculation parameters, start the numerical calculation of the flow field and monitor the flow field parameters in real time. Handle any anomalies based on the real-time monitoring results.

[0043] Finally, the numerical calculation results of the flow field were verified, including grid independence verification and working condition comparison verification. The flow field numerical calculation process was adjusted according to the verification results until all verifications were qualified.

[0044] Preferably, key characteristic parameters of the catalyst inlet flow field are extracted based on the numerical calculation results, including:

[0045] First, identify the parameter categories of the key characteristic parameters, including velocity characteristic parameters, pressure characteristic parameters, ammonia component concentration characteristic parameters, temperature characteristic parameters, and turbulence characteristic parameters;

[0046] Key characteristic parameters were extracted step-by-step according to parameter categories. Specifically, key characteristic parameters for velocity characteristics included the average flow velocity at the catalyst inlet face, velocity distribution extremes and deviations, velocity vector distribution, and velocity recovery downstream of the guide vane; key characteristic parameters for pressure characteristics included the average static pressure at the catalyst inlet face, flow field pressure loss, pressure distribution cloud map, and location of low-pressure zones; key characteristic parameters for ammonia component concentration characteristics included the average ammonia concentration at the catalyst inlet face, ammonia component concentration characteristic parameters, and location of the ammonia-fume mixing interface; key characteristic parameters for temperature characteristics included the average temperature at the catalyst inlet face, temperature distribution deviation, and local anomaly zones; and key characteristic parameters for turbulence characteristics included the average turbulent kinetic energy and dissipation rate at the catalyst inlet face, and turbulence distribution cloud map.

[0047] The extracted key characteristic parameters are then correlated with flow field characteristic phenomena, including eddy region phenomena, velocity gradient zone phenomena, and concentration stratification phenomena. The flow field characteristic phenomena are then correlated with the key characteristic parameters.

[0048] After correlation, the key characteristic parameters of the catalyst inlet flow field are obtained.

[0049] Preferably, based on the extracted flow field characteristics, the uniformity of the catalyst inlet flow field is evaluated to determine whether the flow field meets the catalyst operation requirements, including:

[0050] Before assessing the uniformity of the catalyst inlet flow field, the core assessment indicators should be confirmed, including flow rate uniformity, pressure uniformity, ammonia concentration uniformity, and temperature uniformity.

[0051] The core evaluation indicators are then evaluated using a dual-indicator approach, including both quantitative and visual indicators.

[0052] The acceptable threshold range of the indicators is confirmed according to the requirements of catalyst engineering;

[0053] The final overall evaluation framework for assessing the uniformity of the catalyst inlet flow field is obtained;

[0054] The core evaluation indicators are evaluated according to the overall evaluation framework. Among them, the flow rate uniformity evaluation is to determine whether the flue gas scouring is balanced; the pressure uniformity evaluation is to determine whether the resistance is too high due to too many guide plates or too low opening ratio of the rectifier plate; the ammonia concentration uniformity evaluation is to determine whether the denitrification reaction reactants are suitable; and the temperature uniformity evaluation is to determine whether the catalyst is in the active range.

[0055] The evaluation results are comprehensively judged, and the flow field is confirmed to meet the catalyst operation requirements based on the comprehensive judgment results. The judgment results are divided into qualified, basically qualified and unqualified.

[0056] The final result is an evaluation of the uniformity of the catalyst inlet flow field.

[0057] Preferably, based on key characteristic parameters and uniformity evaluation results, the optimization direction of the catalyst inlet flow field is identified, including:

[0058] First, confirm the data that are basically qualified and unqualified in the uniformity assessment results, and then associate the data with the key characteristic parameters to obtain the specific defect problem type.

[0059] Among them, the defect types include velocity dimension defects, ammonia concentration dimension defects, temperature dimension defects and pressure dimension defects;

[0060] By combining key characteristic parameters and physical model structure, the root causes of each defect type are analyzed, including causes of uneven velocity, uneven ammonia concentration, abnormal temperature, and excessive pressure loss.

[0061] Optimization plans are developed based on the root cause of each defect type.

[0062] Among them, the optimization directions for velocity uniformity include optimization of the guide vane system, flue structure, and overall component optimization; the optimization directions for ammonia concentration uniformity include optimization of the ammonia injection system, supplementation of the mixing structure, and adjustment of the ammonia injection amount; the optimization directions for temperature uniformity include optimization of insulation and sealing, airflow regulation, and heating assistance; and the optimization directions for pressure loss include optimization of resistance components, flow channel, and fan adaptation.

[0063] The proposed optimization schemes are evaluated for feasibility, including space constraints, cost constraints, and downtime constraints, and then the optimization schemes are prioritized.

[0064] The optimized schemes after priority ranking are visualized and reported, resulting in the final optimization direction of the catalyst inlet flow field.

[0065] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0066] 1. The catalyst inlet flow field distribution characteristic analysis method for SCR denitration provided by this invention refines the parameters into four categories, including geometric structure and process fluid, and obtains them from multiple channels such as design drawings, equipment resources, and on-site measurements. The deviations are corrected through four verifications, including completeness and rationality. At the same time, a physical model is constructed by boundary confirmation, deviation correction, and physical property supplementation, which solves the problems of scattered and distorted traditional parameters and the disconnect between the model and reality, and greatly improves the accuracy of parameters and the fit of the model.

[0067] 2. The catalyst inlet flow field distribution characteristic analysis method for SCR denitrification provided by this invention divides the grid density region according to the flow field complexity, and refines the grid in key areas to ensure accuracy; it configures an appropriate transient solver, SIMPLE algorithm and differentiated discretization format, and sets step-by-step iteration parameters and differentiated residual standards; it verifies the results by comparing grid independence with operating conditions, taking into account both computational accuracy and efficiency, and avoiding problems such as poor grid quality and difficulty in convergence.

[0068] 3. The catalyst inlet flow field distribution characteristic analysis method provided by this invention for SCR denitrification conducts quantitative and visual dual evaluation of core indicators such as flow rate and ammonia concentration, combines parameters and models to analyze the root causes of defects, formulates targeted multi-dimensional optimization schemes, and evaluates and ranks them through constraints such as space and cost, effectively improving the flow field uniformity, improving denitrification efficiency, and reducing ammonia escape and catalyst wear. Attached Figure Description

[0069] Figure 1 This is a schematic diagram of the catalyst inlet flow field distribution characteristics analysis steps of the present invention;

[0070] Figure 2 This is a schematic diagram of the catalyst inlet flow field distribution characteristics analysis process of the present invention. Detailed Implementation

[0071] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0072] To address the problems in existing technologies, such as the fragmented and unverified sources of design parameters for SCR denitrification systems, leading to incomplete or distorted data; large discrepancies between the constructed physical model and the actual data, which are not corrected; and the lack of partitioning, refinement, and quality checks in mesh discretization, ultimately affecting the accuracy of flow field calculations and hindering subsequent analysis and optimization, please refer to [the relevant documentation / reference]. Figure 1 and Figure 2 This embodiment provides the following technical solution:

[0073] Methods for analyzing the catalyst inlet flow field distribution characteristics used in SCR denitrification include:

[0074] First, the design parameters of the SCR denitrification system are collected and verified. Based on these parameters, a physical model of the catalyst inlet region identical to that of the actual SCR denitrification system is constructed. The constructed physical model is discretized to generate grid cells suitable for flow field calculations. Governing equations are established based on the motion characteristics of the SCR denitrification catalyst inlet flow field. Furthermore, the boundary constraints and initial state parameters required for flow field calculations are confirmed. Numerical flow field calculations are performed based on the physical model, governing equations, and set conditions. Key characteristic parameters of the catalyst inlet flow field are extracted based on the numerical calculation results. The uniformity of the catalyst inlet flow field is evaluated based on the extracted flow field characteristics to determine if the flow field meets the catalyst operation requirements. Finally, the optimization direction of the catalyst inlet flow field is identified based on the key characteristic parameters and the uniformity evaluation results.

[0075] Collect the design parameters of the SCR denitrification system and verify the design parameters, including:

[0076] The design parameters include geometric parameters, process fluid parameters, equipment performance parameters, and system-related parameters.

[0077] Among them, geometric structural parameters include flue and reactor dimensions, flow guiding and rectifying components, catalyst inlet region and auxiliary structures; process fluid parameters include basic flue gas parameters, flue gas composition and fluid property related parameters; equipment performance parameters include catalyst performance and auxiliary equipment; system related parameters include unit foundation and connection relationships;

[0078] The design parameters were obtained from the design drawings, equipment resources, and on-site measured ports.

[0079] The collected design parameters are verified sequentially, including integrity verification, rationality verification, measurement accuracy verification, and cross-verification.

[0080] The design parameters are adjusted based on the verification results, and the final design parameters of the SCR denitrification system are obtained after the adjustment is completed.

[0081] Specifically, the design parameters are refined into four categories: geometric structure, process fluid, equipment performance, and system correlation. Each category is further broken down into key sub-items, which can comprehensively cover the core parameters required for flow field analysis. This avoids deviations in subsequent model construction or flow field calculations due to parameter omissions, and provides complete data support for the analysis work. Parameters are obtained through three channels: design drawings, equipment resources, and field measurements. This approach can take into account both theoretical design and actual working conditions, and can also supplement data from multiple channels to reduce the limitations of single-channel data and improve parameter accuracy. Completeness, rationality, measurement accuracy, and cross-validation are carried out in sequence to screen out invalid and erroneous data at each level, avoiding the impact of parameter issues on the credibility of subsequent analysis results. Parameters are adjusted based on the validation results to specifically correct data deviations, ultimately obtaining accurate design parameters that highly match the actual system. This lays a high-quality data foundation for subsequent geometric model construction and flow field numerical calculations.

[0082] Based on the obtained design parameters, a physical model of the catalyst inlet region identical to that of the actual SCR denitrification system is constructed, including:

[0083] First, confirm the physical boundaries of the catalyst inlet region, including the longitudinal and lateral boundaries;

[0084] The three-dimensional morphology is reconstructed according to the design parameters. First, the main frame structure is constructed according to the design parameters. After the main frame structure is constructed, the structure of the guide vanes and rectifier components is reconstructed. Finally, the structure of the catalyst inlet area is constructed, which includes the inlet end face and the auxiliary structure of the inlet area.

[0085] The deviation of the catalyst inlet region after the three-dimensional morphology is restored is corrected. The deviation correction is as follows: based on the collected design parameters and field measurement data, the deviation of the structure of the catalyst inlet region after the three-dimensional morphology is restored is calculated. If there is a deviation in the catalyst inlet region after the three-dimensional morphology is restored, the deviation is corrected based on the field measurement data. After the deviation correction is completed, the geometric model of the catalyst inlet region is obtained.

[0086] The ensemble model is supplemented with physical properties, which include material properties and surface characteristics.

[0087] After the physical properties are supplemented, the physical model of the catalyst inlet region is obtained.

[0088] Specifically, first, clearly define the longitudinal and transverse physical boundaries to avoid range deviations caused by blurred boundaries during modeling. This establishes a precise range for subsequent 3D reconstruction, ensuring the model focuses solely on the core area of ​​the catalyst inlet, without redundancy or missing key spaces, thus laying a solid foundation for modeling accuracy. Modeling follows the sequence of "main framework - flow guiding / rectifying components - inlet area structure," first building the core skeleton, then adding key functional components, and finally perfecting the inlet end face and auxiliary structures. This ensures the stability of the main structure while not overlooking details that significantly affect the flow field, ensuring a high degree of consistency between the model structure and the actual system. By combining design parameters with on-site measured data to calculate deviations, the 3D reconstruction model is specifically corrected, eliminating "deviations between design drawings and on-site construction," preventing the theoretical model from becoming disconnected from the actual system, and significantly improving the model's realism. Supplementing material properties and surface characteristics gives the model not only geometric form but also actual physical behavior characteristics, providing an accurate physical basis for subsequent flow field calculations and avoiding calculation deviations caused by relying solely on geometric models.

[0089] The constructed physical model is discretized to generate mesh elements suitable for flow field calculations, including:

[0090] First, confirm the mesh type of the physical model. Mesh types include unstructured mesh, structured mesh, and hybrid mesh.

[0091] Next, the boundaries of the fluid region in the physical model are confirmed. Solid structures in the physical model are removed, including the baffle plate entity, the catalyst module body and the support beam. The cavity areas inside the flue, between the baffle plates and in front of the catalyst inlet are retained and marked as fluid flowable areas.

[0092] The fluid flowable region is divided into grid zones based on the confirmed grid type, including high grid density zones and low grid density zones. The high grid density zone includes the area near the catalyst inlet end face, the area around the guide vanes and porous rectifier plates, and the ammonia injection grid nozzle outlet area; the low grid density zone includes the straight section of the inlet flue and the non-critical area of ​​the reactor inner wall.

[0093] The fluid flowable region, after being divided into grids, is used to generate a grid using the grid generation tool of the flow field calculation software, and the generated grid is then refined in terms of surface and feature density.

[0094] The encrypted mesh is checked for multi-dimensional quality indicators, including mesh distortion, mesh aspect ratio, and mesh orthogonality. Based on the check results, meshes that do not meet the requirements are deleted or adjusted.

[0095] Finally, a complete physical model of the catalyst inlet flow field was obtained.

[0096] Specifically, first, identify the three mesh types: unstructured, structured, and hybrid. The appropriate type can be selected based on the complexity of the region, avoiding the limitations of a single mesh type. This ensures the feasibility of modeling complex regions while improving the efficiency of mesh generation in simpler regions. Solid structures such as guide vanes and catalyst modules are removed, retaining only flowable regions such as the interior of the flue. This avoids generating redundant meshes for solid regions, significantly reducing computational resource consumption. Simultaneously, the fluid extent is clearly defined to ensure that subsequent flow field calculations focus only on the effective region, avoiding computational biases caused by boundary confusion. The flowable region is divided into high and low... In the mesh density region, the mesh is densified in high-density areas with drastic flow field changes, such as the catalyst inlet face and the periphery of the guide vanes, to ensure computational accuracy. In low-density areas with stable flow fields, such as straight sections, the mesh is simplified to control the computational workload, achieving an optimal balance between "high accuracy in critical areas and high efficiency in non-critical areas". Surface densification and feature densification are used to enhance the mesh details in complex areas. Then, the mesh quality is checked using indicators such as distortion, aspect ratio, and orthogonality. Unqualified meshes are deleted or adjusted to avoid difficulties in convergence or distortion of results in flow field calculations due to poor mesh quality, thus laying a high-quality mesh foundation for subsequent numerical calculations.

[0097] To address the issues in existing SCR denitrification catalyst inlet flow field simulations, such as incomplete governing equations, inaccurate boundary condition settings, unreasonable mesh generation, and lack of verification methods, please refer to [the relevant documentation / reference]. Figure 1 and Figure 2 This embodiment provides the following technical solution:

[0098] Based on the motion characteristics of the inlet flow field of the SCR denitrification catalyst, the governing equations are established, including:

[0099] The flow characteristics of the catalyst inlet flow field are confirmed based on the design parameters, including flow pattern, medium characteristics and influencing factors;

[0100] Using the mass conservation and momentum conservation equations as the basic framework, the physical laws governing the flow characteristics of the catalyst inlet flow field are confirmed. The confirmation of physical laws includes establishing the continuity equation and the momentum equation, and supplementing it with a turbulence model, which is a k-ε two-equation model. The turbulence model is used to assist in the construction of the turbulence kinetic energy equation and the dissipation rate equation.

[0101] Further, the component transport equation and energy equation for the ammonia injection grid are supplemented;

[0102] Finally, all the constructed equations were verified. The verification was conducted to: verify whether the equations could capture key flow phenomena; and verify whether the equations conformed to the actual motion law of the catalyst inlet flow field.

[0103] After all verifications were successful, the governing equations for the inlet flow field of the SCR denitrification catalyst were obtained.

[0104] Specifically, the flow pattern, medium characteristics, and influencing factors are first confirmed based on the design parameters to avoid deviations caused by using general equations. This ensures that subsequent equation construction can accurately match the actual flow scenario of the catalyst inlet flow field, laying the foundation for calculation accuracy. Continuity and momentum equations are established based on mass and momentum conservation to ensure that the equations conform to the basic laws of fluid motion. A k-ε two-equation model is supplemented to accurately describe the complex turbulent motion around the guide vanes and ammonia injection grid through turbulent kinetic energy and dissipation rate equations, avoiding calculation distortions caused by simplifying the turbulence model. For the key requirements of SCR denitrification, component transport and energy equations are supplemented, covering both the core of fluid motion and the material and energy transfer processes related to the denitrification reaction, ensuring that the equations can support the coupled analysis of the flow field and reaction. Through dual verification of "capturing key flow phenomena" and "conforming to actual motion laws," invalid or highly biased equations can be screened out, avoiding unreliable flow field calculation results due to equation defects. Finally, control equations that highly fit the actual flow field are obtained.

[0105] Confirm the boundary constraints and initial state parameters required for the flow field calculation, including:

[0106] First, the inlet boundary conditions are confirmed, including flow velocity, temperature, component concentration, and ammonia concentration. The flow velocity is confirmed based on the flue gas flow rate data provided in the SCR denitrification system design drawings, combined with the cross-sectional area of ​​the catalyst inlet region. The temperature is obtained from the design drawings as the design temperature value of the inlet flue gas of the SCR denitrification system. The component concentration is confirmed based on the specifications for flue gas components in the design parameters, determining the concentration of each major component in the inlet flue gas. The ammonia concentration is calculated based on the relationship between the ammonia injection rate and the flue gas flow rate, determining the mass fraction or mole fraction of ammonia at the inlet.

[0107] Next, the outlet boundary conditions are confirmed. The outlet boundary conditions include pressure and component concentration. The pressure is determined based on the resistance characteristics of the downstream equipment of the SCR denitrification system and the back pressure requirements during system operation. The component concentration is estimated based on the chemical reaction equilibrium principle and the simulation results of the inlet conditions and reaction process.

[0108] The wall boundary conditions are confirmed. The wall conditions include the no-slip condition of the solid wall and the wall roughness. The no-slip condition of the solid wall is to set the velocity component of the fluid at the wall to zero in both the direction perpendicular to the wall and the direction parallel to the wall for all solid walls in the catalyst inlet region. The wall roughness is to set the corresponding roughness parameters according to the actual roughness of the wall material.

[0109] The initial state parameters are confirmed, including the initial velocity distribution, initial temperature distribution, and initial component concentration distribution. The initial velocity distribution is initially set based on the inlet velocity and the geometry of the flow field region, using a simple linear or uniform distribution assumption to preliminarily determine the velocity values ​​of each grid cell in the flow field. The initial temperature distribution is set based on the inlet temperature and the adiabatic or heat dissipation conditions of the system. The initial component concentration distribution is set based on the concentrations of each component at the inlet and the initial assumptions about the mixing process.

[0110] Finally, all boundary constraints and initial state parameters were completed.

[0111] Specifically, the inlet velocity is calculated by combining the flue gas flow rate and the inlet cross-sectional area, and the ammonia concentration is derived by combining the ammonia injection rate and the flue gas flow rate. The temperature and component concentration are directly anchored to the design drawings and parameter specifications, avoiding subjective assumptions and deviations. Each parameter has a clear engineering basis, ensuring that the inlet boundary conditions are highly consistent with the design conditions of the SCR system, providing accurate initial input for flow field calculations. The outlet pressure is determined by combining the resistance of downstream equipment and the system back pressure. The component concentration relies on the principle of reaction equilibrium and the prediction of the inlet-reaction process, breaking through the limitation of "isolated setting of outlet parameters". It fully considers the upstream and downstream correlation of the system, making the outlet boundary conditions match the actual discharge state of the fluid in actual operation, improving the system fit of the calculation results. The basic constraint of no slippage on the solid wall is clearly defined. At the same time, the roughness parameters are set according to the actual material conditions, which not only follows the basic laws of fluid mechanics, but also does not ignore the influence of wall roughness on the turbulent boundary layer, avoiding the distortion of flow field calculation caused by simplifying wall conditions. The initial velocity, temperature and concentration distribution are set by combining inlet conditions, geometry and system thermal state, and adopting simple and reasonable assumptions such as linear or uniform distribution. This not only fits the initial evolution trend of the flow field, but also avoids the difficulty of subsequent numerical calculation convergence due to unreasonable initial values, laying the foundation for the stable progress of flow field calculations.

[0112] Numerical calculations of the flow field are performed based on the physical model, governing equations, and set conditions, including:

[0113] The discretized mesh file, governing equations, and fluid property parameters are used as the base data for import.

[0114] Next, configure the solver parameters, including solver type, coupling algorithm, and discretization scheme. The solver type is transient solver; the coupling algorithm is SIMPLE algorithm; the discretization scheme is as follows: the momentum equation and continuity equation use the second-order upwind scheme; the turbulence equation uses the first-order upwind scheme; and the multi-component transport equation uses the second-order central difference scheme.

[0115] After configuring the solver parameters, the iterative calculation parameters are set. The total number of iterations in the initial iteration phase is 500-1000 steps, and the total number of iterations in the later convergence phase is extended to 2000-5000 steps. Then, the convergence criteria are determined, and the residuals of the continuity equation and momentum equation are reduced to 10. -6 Below, the residuals of the k-equation and the ε-equation are reduced to 10. -4 Below, the residuals of the multi-component transport equations are reduced to 10. -5 the following;

[0116] After setting the iterative calculation parameters, start the numerical calculation of the flow field and monitor the flow field parameters in real time. Handle any anomalies based on the real-time monitoring results.

[0117] Finally, the numerical calculation results of the flow field were verified, including grid independence verification and working condition comparison verification. The flow field numerical calculation process was adjusted according to the verification results until all verifications were qualified.

[0118] Specifically, discretized meshes, governing equations, and fluid property parameters are used as the basic data for import, ensuring that the computational input covers the core elements of geometry, physical laws, and medium characteristics. This avoids computational deviations due to missing or omitted data, providing a complete and accurate starting foundation for numerical calculations. The transient solver adapts to the dynamic characteristics of the flow field; the SIMPLE algorithm ensures the stability of the pressure-velocity coupled solution; and suitable discretization formats are selected for different equations, which not only meet the computational needs of various physical processes but also balance computational accuracy and solution stability. The initial iteration rapidly advances the flow field development, while the number of steps is extended in later stages to ensure convergence; and differentiated residuals are set according to the characteristics of the equations. To avoid insufficient convergence or overcomputation caused by a "one-size-fits-all" approach, a standard is adopted to balance efficiency and convergence quality. Flow field parameters are monitored in real time during calculations, and anomalies are handled promptly. This allows for the timely detection of issues such as residual oscillations and parameter mutations, preventing calculation failures or result distortions due to persistent anomalies. This ensures stable computational progress and reduces unnecessary computational energy consumption. Through grid independence verification and working condition comparison verification, calculation deviations are filtered and corrected layer by layer to ensure that the final results are not affected by computational conditions and closely match the actual flow field, providing reliable data support for subsequent flow field analysis. The parameter configuration and convergence control for the numerical flow field calculation are shown in the table below:

[0119]

[0120]

[0121]

[0122] To address the issues of uneven velocity, concentration, and temperature distribution in the inlet flow field of SCR denitrification catalysts in existing technologies, which lead to low denitrification efficiency, high ammonia slip, catalyst wear, and blockage, please refer to [the relevant documentation / reference]. Figure 1 and Figure 2 This embodiment provides the following technical solution:

[0123] Key characteristic parameters of the catalyst inlet flow field were extracted based on the numerical calculation results, including:

[0124] First, identify the parameter categories of the key characteristic parameters, including velocity characteristic parameters, pressure characteristic parameters, ammonia component concentration characteristic parameters, temperature characteristic parameters, and turbulence characteristic parameters;

[0125] Key characteristic parameters were extracted step-by-step according to parameter categories. Specifically, key characteristic parameters for velocity characteristics included the average flow velocity at the catalyst inlet face, velocity distribution extremes and deviations, velocity vector distribution, and velocity recovery downstream of the guide vane; key characteristic parameters for pressure characteristics included the average static pressure at the catalyst inlet face, flow field pressure loss, pressure distribution cloud map, and location of low-pressure zones; key characteristic parameters for ammonia component concentration characteristics included the average ammonia concentration at the catalyst inlet face, ammonia component concentration characteristic parameters, and location of the ammonia-fume mixing interface; key characteristic parameters for temperature characteristics included the average temperature at the catalyst inlet face, temperature distribution deviation, and local anomaly zones; and key characteristic parameters for turbulence characteristics included the average turbulent kinetic energy and dissipation rate at the catalyst inlet face, and turbulence distribution cloud map.

[0126] The extracted key characteristic parameters are then correlated with flow field characteristic phenomena, including eddy region phenomena, velocity gradient zone phenomena, and concentration stratification phenomena. The flow field characteristic phenomena are then correlated with the key characteristic parameters.

[0127] After correlation, the key characteristic parameters of the catalyst inlet flow field are obtained.

[0128] Specifically, five key parameters—velocity, pressure, ammonia concentration, temperature, and turbulence—are clearly defined. These parameters encompass not only fundamental fluid motion characteristics and core correlations in SCR denitrification, but also factors influencing complex flow fields. This comprehensive approach covers the core dimensions required for catalyst inlet flow field analysis, avoiding misjudgments of flow field characteristics due to missing parameters. When extracting parameters step-by-step by category, all parameters focus on key regions and core indicators at the catalyst inlet. This avoids redundant parameters wasting analytical effort and ensures that the extracted parameters directly reflect key influencing factors of catalyst operation, improving data extraction efficiency and accuracy. The extracted parameters are correlated with flow field characteristics such as eddy regions, velocity gradients, and concentration stratification, transforming isolated parameter data into "evidence" that can explain flow field problems. This avoids parameters remaining merely numerical, providing direct support for subsequent analysis of the causes of flow field anomalies. Ultimately, the extracted parameters can directly serve subsequent flow field uniformity assessment and optimization direction identification, forming a closed loop of "calculation-extraction-application." This ensures that the parameter extraction results have practical engineering guidance significance, rather than being purely theoretical data.

[0129] Based on the extracted flow field characteristics, the uniformity of the catalyst inlet flow field is evaluated to determine whether the flow field meets the catalyst's operational requirements, including:

[0130] Before assessing the uniformity of the catalyst inlet flow field, the core assessment indicators should be confirmed, including flow rate uniformity, pressure uniformity, ammonia concentration uniformity, and temperature uniformity.

[0131] The core evaluation indicators are then evaluated using a dual-indicator approach, including both quantitative and visual indicators.

[0132] The acceptable threshold range of the indicators is confirmed according to the requirements of catalyst engineering;

[0133] The final overall evaluation framework for assessing the uniformity of the catalyst inlet flow field is obtained;

[0134] The core evaluation indicators are evaluated according to the overall evaluation framework. Among them, the flow rate uniformity evaluation is to determine whether the flue gas scouring is balanced; the pressure uniformity evaluation is to determine whether the resistance is too high due to too many guide plates or too low opening ratio of the rectifier plate; the ammonia concentration uniformity evaluation is to determine whether the denitrification reaction reactants are suitable; and the temperature uniformity evaluation is to determine whether the catalyst is in the active range.

[0135] The evaluation results are comprehensively judged, and the flow field is confirmed to meet the catalyst operation requirements based on the comprehensive judgment results. The judgment results are divided into qualified, basically qualified and unqualified.

[0136] The final result is an evaluation of the uniformity of the catalyst inlet flow field.

[0137] Specifically, the study focuses on four uniformity indicators: flow rate, pressure, ammonia concentration, and temperature. These are all key factors directly affecting catalyst operation. Uneven flow rate leads to catalyst scouring imbalance, uneven ammonia concentration affects denitrification efficiency, and uneven temperature may exceed the catalyst's active range. This comprehensive approach covers the core dimensions of the flow field's influence on the catalyst, avoiding biased assessments due to omissions. Each core indicator is evaluated using a combination of quantitative and visual indicators. Quantitative indicators allow for precise comparison with acceptable thresholds, while visual indicators provide intuitive local anomalies. This avoids the limitations of relying solely on quantitative assessments to ignore local problems or solely on visual assessments to lack precise standards, thus improving assessment accuracy. Acceptable thresholds are determined based on catalyst engineering requirements, rather than using general standards. For example, temperature uniformity thresholds are used to anchor the catalyst's active range. The pressure uniformity threshold is correlated with the resistance bearing capacity of the guide vane / rectifier plate to ensure that the evaluation criteria are highly matched with actual operating requirements, avoiding the problem of "theoretically qualified but not engineering-compatible". First, an overall evaluation framework of "indicator confirmation - dual indicator setting - threshold clarification" is constructed, and then the evaluation is carried out item by item according to the framework. Each evaluation corresponds to a specific engineering problem, avoiding the confusion of the evaluation process. At the same time, the evaluation is not only "qualified", but also can preliminarily locate the cause of flow field problems and provide direction for subsequent optimization. The judgment results are divided into three levels: qualified, basically qualified, and unqualified. This is more practical than simple qualified / unqualified. For example, "basically qualified" can guide minor adjustments, while "unqualified" indicates that the guide structure needs to be reconstructed, avoiding excessive or insufficient rectification and improving the flexibility and accuracy of engineering decision-making.

[0138] Based on the key characteristic parameters and uniformity assessment results, the optimization directions for the catalyst inlet flow field are identified, including:

[0139] First, confirm the data that are basically qualified and unqualified in the uniformity assessment results, and then associate the data with the key characteristic parameters to obtain the specific defect problem type.

[0140] Among them, the defect types include velocity dimension defects, ammonia concentration dimension defects, temperature dimension defects and pressure dimension defects;

[0141] By combining key characteristic parameters and physical model structure, the root causes of each defect type are analyzed, including causes of uneven velocity, uneven ammonia concentration, abnormal temperature, and excessive pressure loss.

[0142] Optimization plans are developed based on the root cause of each defect type.

[0143] Among them, the optimization directions for velocity uniformity include optimization of the guide vane system, flue structure, and overall component optimization; the optimization directions for ammonia concentration uniformity include optimization of the ammonia injection system, supplementation of the mixing structure, and adjustment of the ammonia injection amount; the optimization directions for temperature uniformity include optimization of insulation and sealing, airflow regulation, and heating assistance; and the optimization directions for pressure loss include optimization of resistance components, flow channel, and fan adaptation.

[0144] The proposed optimization schemes are evaluated for feasibility, including space constraints, cost constraints, and downtime constraints, and then the optimization schemes are prioritized.

[0145] The optimized schemes after priority ranking are visualized and reported, resulting in the final optimization direction of the catalyst inlet flow field.

[0146] Specifically, the process begins by identifying "basically qualified / unqualified" data in the uniformity assessment, then correlating key characteristic parameters to pinpoint defect types. This avoids wasting effort on indiscriminate analysis, precisely focusing on the core issues affecting catalyst operation, providing clear targets for optimization. The root causes of defects are analyzed by combining key parameters with the physical model structure, rather than simply addressing surface phenomena. This ensures that optimization measures directly address the essence of the problem, avoiding haphazard, piecemeal rectification and improving optimization effectiveness. Dedicated optimization directions are developed based on defect dimensions, with specific implementation measures under each direction. This avoids vague and general optimization plans while precisely matching measures to actual defect types, enhancing the practicality of the solutions. Solutions are evaluated based on space, cost, and downtime constraints, then prioritized. This avoids developing impractical, theoretical solutions while helping the engineering team advance optimization according to urgency, balancing effectiveness with practical conditions. Visualized reports make optimization directions more intuitive, facilitating team understanding and implementation.

[0147] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0148] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention.

Claims

1. A method for analyzing the inlet flow field distribution characteristics of catalysts used in SCR denitrification, characterized in that, include: First, collect the design parameters of the SCR denitrification system and then verify the collected design parameters; Based on the obtained design parameters, a physical model of the catalyst inlet region identical to that of the actual SCR denitrification system is constructed; the constructed physical model is discretized to generate grid cells suitable for flow field calculation; the governing equations are established based on the motion law of the SCR denitrification catalyst inlet flow field; and the boundary constraints and initial state parameters required for flow field calculation are confirmed; the flow field is numerically calculated based on the physical model, governing equations, and set conditions. Key characteristic parameters of the catalyst inlet flow field are extracted based on the numerical calculation results of the flow field; the uniformity of the catalyst inlet flow field is evaluated based on the extracted flow field characteristics, and it is determined whether the flow field meets the catalyst operation requirements. Based on the key characteristic parameters and uniformity evaluation results, the optimization direction of the catalyst inlet flow field is identified; The numerical calculation of the flow field based on the physical model, governing equations, and set conditions includes: The discretized mesh file, governing equations, and fluid property parameters are used as the base data for import. Next, configure the solver parameters, including solver type, coupling algorithm, and discretization scheme. The solver type is transient solver; the coupling algorithm is SIMPLE algorithm; the discretization scheme is as follows: the momentum equation and continuity equation use the second-order upwind scheme; the turbulence equation uses the first-order upwind scheme; and the multi-component transport equation uses the second-order central difference scheme. After configuring the solver parameters, the iterative calculation parameters are set. The total number of iterations in the initial iteration phase is 500-1000 steps, and the total number of iterations in the later convergence phase is extended to 2000-5000 steps. Then, the convergence criteria are determined, and the residuals of the continuity equation and momentum equation are reduced to 10. -6 Below, the residuals of the k-equation and the ε-equation are reduced to 10. -4 Below, the residuals of the multi-component transport equations are reduced to 10. -5 the following; After setting the iterative calculation parameters, start the numerical calculation of the flow field and monitor the flow field parameters in real time. Handle any anomalies based on the real-time monitoring results. Finally, the numerical calculation results of the flow field were verified, including mesh independence verification and working condition comparison verification. The flow field numerical calculation process was adjusted according to the verification results until all verifications were qualified. Key characteristic parameters of the catalyst inlet flow field were extracted based on the numerical calculation results, including: First, identify the parameter categories of the key characteristic parameters, including velocity characteristic parameters, pressure characteristic parameters, ammonia component concentration characteristic parameters, temperature characteristic parameters, and turbulence characteristic parameters; Key characteristic parameters were extracted step-by-step according to parameter categories. Specifically, key characteristic parameters for velocity characteristics included the average flow velocity at the catalyst inlet face, velocity distribution extremes and deviations, velocity vector distribution, and velocity recovery downstream of the guide vane; key characteristic parameters for pressure characteristics included the average static pressure at the catalyst inlet face, flow field pressure loss, pressure distribution cloud map, and location of low-pressure zones; key characteristic parameters for ammonia component concentration characteristics included the average ammonia concentration at the catalyst inlet face, ammonia component concentration characteristic parameters, and location of the ammonia-fume mixing interface; key characteristic parameters for temperature characteristics included the average temperature at the catalyst inlet face, temperature distribution deviation, and local anomaly zones; and key characteristic parameters for turbulence characteristics included the average turbulent kinetic energy and dissipation rate at the catalyst inlet face, and turbulence distribution cloud map. The extracted key characteristic parameters are then correlated with flow field characteristic phenomena, including eddy region phenomena, velocity gradient zone phenomena, and concentration stratification phenomena. The flow field characteristic phenomena are then correlated with the key characteristic parameters. After correlation, the key characteristic parameters of the catalyst inlet flow field are obtained. Based on the extracted flow field characteristics, the uniformity of the catalyst inlet flow field is evaluated to determine whether the flow field meets the catalyst's operational requirements, including: Before assessing the uniformity of the catalyst inlet flow field, the core assessment indicators should be confirmed, including flow rate uniformity, pressure uniformity, ammonia concentration uniformity, and temperature uniformity. The core evaluation indicators are then evaluated using a dual-indicator approach, including both quantitative and visual indicators. The acceptable threshold range of the indicators is confirmed according to the requirements of catalyst engineering; The final overall evaluation framework for assessing the uniformity of the catalyst inlet flow field is obtained; The core evaluation indicators are evaluated according to the overall evaluation framework. Among them, the flow rate uniformity evaluation is to determine whether the flue gas scouring is balanced; the pressure uniformity evaluation is to determine whether the resistance is too high due to too many guide plates or too low opening ratio of the rectifier plate; the ammonia concentration uniformity evaluation is to determine whether the denitrification reaction reactants are suitable; and the temperature uniformity evaluation is to determine whether the catalyst is in the active range. The evaluation results are comprehensively judged, and the flow field is confirmed to meet the catalyst operation requirements based on the comprehensive judgment results. The judgment results are divided into qualified, basically qualified and unqualified. The final result is the evaluation of the uniformity of the catalyst inlet flow field; Based on the key characteristic parameters and uniformity assessment results, the optimization directions for the catalyst inlet flow field are identified, including: First, confirm the data that are basically qualified and unqualified in the uniformity assessment results, and then associate the data with the key characteristic parameters to obtain the specific defect problem type. Among them, the defect types include velocity dimension defects, ammonia concentration dimension defects, temperature dimension defects and pressure dimension defects; By combining key characteristic parameters and physical model structure, the root causes of each defect type are analyzed, including causes of uneven velocity, uneven ammonia concentration, abnormal temperature, and excessive pressure loss. Optimization plans are developed based on the root cause of each defect type. Among them, the optimization directions for velocity uniformity include optimization of the guide vane system, flue structure, and overall component optimization; the optimization directions for ammonia concentration uniformity include optimization of the ammonia injection system, supplementation of the mixing structure, and adjustment of the ammonia injection amount; the optimization directions for temperature uniformity include optimization of insulation and sealing, airflow regulation, and heating assistance; and the optimization directions for pressure loss include optimization of resistance components, flow channel, and fan adaptation. The proposed optimization schemes are evaluated for feasibility, including space constraints, cost constraints, and downtime constraints, and then the optimization schemes are prioritized. The optimized schemes after priority ranking are visualized and reported, resulting in the final optimization direction of the catalyst inlet flow field.

2. The method for analyzing the catalyst inlet flow field distribution characteristics for SCR denitrification according to claim 1, characterized in that, Collect the design parameters of the SCR denitrification system and verify the design parameters, including: The design parameters include geometric parameters, process fluid parameters, equipment performance parameters, and system-related parameters. Among them, geometric structural parameters include flue and reactor dimensions, flow guiding and rectifying components, catalyst inlet region and auxiliary structures; process fluid parameters include basic flue gas parameters, flue gas composition and fluid property related parameters; equipment performance parameters include catalyst performance and auxiliary equipment; system related parameters include unit foundation and connection relationships; The design parameters were obtained from the design drawings, equipment resources, and on-site measured ports. The collected design parameters are verified sequentially, including integrity verification, rationality verification, measurement accuracy verification, and cross-verification. The design parameters are adjusted based on the verification results, and the final design parameters of the SCR denitrification system are obtained after the adjustment is completed.

3. The method for analyzing the catalyst inlet flow field distribution characteristics for SCR denitrification according to claim 2, characterized in that, Based on the obtained design parameters, a physical model of the catalyst inlet region identical to that of the actual SCR denitrification system was constructed, including: First, confirm the physical boundaries of the catalyst inlet region, including the longitudinal and lateral boundaries; The three-dimensional morphology is reconstructed according to the design parameters. First, the main frame structure is constructed according to the design parameters. After the main frame structure is constructed, the structure of the guide vanes and rectifier components is reconstructed. Finally, the structure of the catalyst inlet area is constructed, which includes the inlet end face and the auxiliary structure of the inlet area. The deviation of the catalyst inlet region after the three-dimensional morphology is restored is corrected. The deviation correction is as follows: based on the collected design parameters and field measurement data, the deviation of the structure of the catalyst inlet region after the three-dimensional morphology is restored is calculated. If there is a deviation in the catalyst inlet region after the three-dimensional morphology is restored, the deviation is corrected based on the field measurement data. After the deviation correction is completed, the geometric model of the catalyst inlet region is obtained. The geometric model is supplemented with physical properties, including material properties and surface characteristics. After the physical properties are supplemented, the physical model of the catalyst inlet region is obtained.

4. The method for analyzing the catalyst inlet flow field distribution characteristics for SCR denitrification according to claim 3, characterized in that, The constructed physical model is discretized to generate mesh elements suitable for flow field calculations, including: First, confirm the mesh type of the physical model. Mesh types include unstructured mesh, structured mesh, and hybrid mesh. Next, the boundaries of the fluid region in the physical model are confirmed. Solid structures in the physical model are removed, including the baffle plate entity, the catalyst module body and the support beam. The cavity areas inside the flue, between the baffle plates and in front of the catalyst inlet are retained and marked as fluid flowable areas. The fluid flowable region is divided into grid zones based on the confirmed grid type, including high grid density zones and low grid density zones. The high grid density zone includes the area near the catalyst inlet end face, the area around the guide vanes and porous rectifier plates, and the ammonia injection grid nozzle outlet area; the low grid density zone includes the straight section of the inlet flue and the non-critical area of ​​the reactor inner wall. The fluid flowable region, after being divided into grids, is used to generate a grid using the grid generation tool of the flow field calculation software, and the generated grid is then refined in terms of surface and feature density. The encrypted mesh is checked for multi-dimensional quality indicators, including mesh distortion, mesh aspect ratio, and mesh orthogonality. Based on the check results, meshes that do not meet the requirements are deleted or adjusted. Finally, a complete physical model of the catalyst inlet flow field was obtained.

5. The method for analyzing the catalyst inlet flow field distribution characteristics for SCR denitrification according to claim 4, characterized in that, Based on the motion characteristics of the inlet flow field of the SCR denitrification catalyst, the governing equations are established, including: The flow characteristics of the catalyst inlet flow field are confirmed based on the design parameters, including flow pattern, medium characteristics and influencing factors; Using the mass conservation and momentum conservation equations as the basic framework, the physical laws governing the flow characteristics of the catalyst inlet flow field are confirmed. The confirmation of physical laws includes establishing the continuity equation and the momentum equation, and supplementing it with a turbulence model, which is a k-ε two-equation model. The turbulence model is used to assist in the construction of the turbulence kinetic energy equation and the dissipation rate equation. Further, the component transport equation and energy equation for the ammonia injection grid are supplemented; Finally, all the constructed equations were verified. The verification was conducted to: verify whether the equations could capture key flow phenomena; and verify whether the equations conformed to the actual motion law of the catalyst inlet flow field. After all verifications were successful, the governing equations for the inlet flow field of the SCR denitrification catalyst were obtained.

6. The method for analyzing the catalyst inlet flow field distribution characteristics for SCR denitrification according to claim 5, characterized in that, Confirm the boundary constraints and initial state parameters required for the flow field calculation, including: First, the inlet boundary conditions are confirmed, including flow velocity, temperature, component concentration, and ammonia concentration. The flow velocity is confirmed based on the flue gas flow rate data provided in the SCR denitrification system design drawings, combined with the cross-sectional area of ​​the catalyst inlet region. The temperature is obtained from the design drawings as the design temperature value of the inlet flue gas of the SCR denitrification system. The component concentration is confirmed based on the specifications for flue gas components in the design parameters, determining the concentration of each major component in the inlet flue gas. The ammonia concentration is calculated based on the relationship between the ammonia injection rate and the flue gas flow rate, determining the mass fraction or mole fraction of ammonia at the inlet. Next, the outlet boundary conditions are confirmed. The outlet boundary conditions include pressure and component concentration. The pressure is determined based on the resistance characteristics of the downstream equipment of the SCR denitrification system and the back pressure requirements during system operation. The component concentration is estimated based on the chemical reaction equilibrium principle and the simulation results of the inlet conditions and reaction process. The wall boundary conditions are confirmed. The wall conditions include the no-slip condition of the solid wall and the wall roughness. The no-slip condition of the solid wall is to set the velocity component of the fluid at the wall to zero in both the direction perpendicular to the wall and the direction parallel to the wall for all solid walls in the catalyst inlet region. The wall roughness is to set the corresponding roughness parameters according to the actual roughness of the wall material. The initial state parameters are confirmed, including the initial velocity distribution, initial temperature distribution, and initial component concentration distribution. The initial velocity distribution is initially set based on the inlet velocity and the geometry of the flow field region, using a simple linear or uniform distribution assumption to preliminarily determine the velocity values ​​of each grid cell in the flow field. The initial temperature distribution is set based on the inlet temperature and the adiabatic or heat dissipation conditions of the system. The initial component concentration distribution is set based on the concentrations of each component at the inlet and the initial assumptions about the mixing process. Finally, all boundary constraints and initial state parameters were completed.

Images