Reactor optimization method, system, equipment and medium based on numerical flow experiment

Abstract

The invention belongs to the technical field of reactor simulation, and provides a numerical flow experiment-based reactor optimization method, system, equipment and medium, and the method comprises the following steps: establishing a three-dimensional model of a reactor; carrying out regional division on the three-dimensional model to obtain a plurality of flow field numerical calculation domains; collecting actual working conditions, and setting boundary conditions according to the actual working conditions; determining a flow field calculation model; calculating the flow field based on the flow field calculation model and the boundary condition to obtain the three-dimensional distribution of the air flow structure; and judging whether the velocity uniformity and the pressure uniformity of the symmetry plane meet the index requirements of the reactor or not, if not, adjusting the length or / and the direction of the spoiler of the reactor, and returning to the step of establishing the three-dimensional model of the reactor. According to the invention, the reactor can be designed and optimized based on flow field uniformity with high efficiency and low cost.

Description

Technical Field

[0001] This invention relates to the fields of chemical process equipment and reaction engineering and numerical simulation technology, and particularly to reactor optimization methods, systems, equipment and media based on numerical flow experiments. Background Technology

[0002] Reactors are key equipment in process industries such as chemical, pharmaceutical, and energy sectors, suitable for homogeneous liquid-phase and multiphase reactions including liquid-liquid, gas-liquid, liquid-solid, and gas-liquid-solid processes. The uniformity of the flow field inside the reactor (flow field uniformity refers to the spatial distribution of reactant gases, such as velocity, pressure, and temperature) significantly affects the reactor's operational stability, efficiency, and service life. For example, excessively high local pressure can cause structural vibration or localized damage, leading to a reduced service life; significant differences in velocity distribution result in insufficient material residence time in high-velocity zones and minimal material participation in low-velocity zones, causing reduced reaction bed life and raw material waste.

[0003] Traditional reactor design relies heavily on engineers' experience and manual formulas, making it difficult to handle complex structures and novel processes. Conservative designs, such as poor inlet design or uneven catalyst loading, may fail to meet flow field uniformity requirements. Testing through experimental setups is costly, time-consuming, and makes it difficult to obtain detailed data across the entire equipment. Furthermore, while achieving uniform flow fields in small-scale laboratory settings is relatively easy due to the small diameter, scaling up to industrial-scale reactors dramatically increases the cross-sectional area. Minor flaws in the inlet distributor design are amplified, exponentially increasing the difficulty of maintaining flow field uniformity across the entire cross-section.

[0004] Therefore, there is an urgent need in this field for a reactor optimization design method that can overcome the above-mentioned shortcomings and achieve high efficiency and low cost. Summary of the Invention

[0005] In view of this, the present invention provides a reactor optimization method, system, equipment and medium based on numerical flow experiments to solve the technical defects of the prior art that rely on engineers' experience and manual formulas for reactor design, which are costly, time-consuming and cannot guarantee the uniformity of the flow field.

[0006] According to a first aspect of the present invention, a reactor optimization method based on numerical flow experiments is provided, comprising: Geometric modeling steps: Create a 3D model of the reactor; Steps for establishing the numerical computation domain of the flow field: Divide the three-dimensional model of the reactor into regions to obtain multiple numerical computation domains of the flow field; Boundary condition selection steps: Collect actual operating conditions, and set boundary conditions according to the actual operating conditions. The boundary conditions include one or more of the following: inlet parameters, outlet parameters, and wall conditions. The inlet parameters include one or more of the following: inlet velocity, inlet pressure, and inlet temperature. The outlet parameters include one or more of the following: outlet velocity, outlet pressure, and outlet temperature. The wall conditions include no-slip boundary conditions and / or thermal boundary conditions. Calculation configuration steps: Determine the flow field calculation model, which includes one or more of the following: numerical solver, turbulence model, material properties, and pseudo-transient calculation parameters; Performance extraction steps: Calculate the flow field based on the flow field calculation model and boundary conditions to obtain the three-dimensional distribution of airflow organization, which includes the velocity distribution and pressure distribution on the symmetry plane; Optimization steps: Determine whether the velocity uniformity and pressure uniformity of the symmetry plane meet the reactor's performance requirements. If the velocity uniformity and / or pressure uniformity of the symmetry plane do not meet the reactor's performance requirements, adjust the length and / or direction of the reactor's baffles and return to the geometric modeling step.

[0007] In one possible implementation, one or more catalyst layers are disposed within the cylinder.

[0008] In one possible implementation, the reactor includes an inlet shroud, a baffle shroud, and a cylindrical body, wherein one or more baffles are disposed inside the inlet shroud and the baffle shroud; the inlet shroud is connected to the air inlet, and the baffle shroud is connected to both the inlet shroud and the cylindrical body; the cylindrical body is connected to the air outlet.

[0009] In one possible implementation, the step of establishing the numerical computational domain for the flow field includes: The numerical computation domain of the flow field is established by mesh discretization modeling based on the three-dimensional model of the reactor.

[0010] In one possible implementation, the step of establishing the numerical computational domain for the flow field includes: The reactor's 3D model is divided into parts based on the length and orientation of the baffles, and a geometric topology is created. Mesh size and global parameters are defined to generate the mesh.

[0011] In one possible implementation, the computation configuration step includes one or more of the following steps: The numerical solver employs a pressure-based explicit steady-state solver. Pseudo-transient calculations are used to simulate compressible flow; Material selection: gas; The density of a gas is solved using the equation of state for an ideal body. The viscosity coefficient of a gas is expressed as a function of temperature.

[0012] In one possible implementation, the computation configuration step includes one or more of the following steps: Set one or more of the following for the flow field calculation model: initial flow field, convergence condition, time step, and total number of iterations.

[0013] In one possible implementation, the computation configuration step includes one or more of the following steps: The turbulence model adopted is a turbulence model based on Reynolds' time-averaged equation; The wall functions use the standard wall functions; The physical quantities of the flow field calculation model are differentiated using a second-order upwind scheme to ensure the solution of gradient changes along the grid using physical quantities. The gas is assumed to be an ideal gas, and the viscosity coefficient is solved using the Sutherland formula.

[0014] In one possible implementation, the computation configuration step includes one or more of the following steps: The turbulence model adopted is the RNG k-epsilon model; The numerical solver uses the SIMPLEC velocity-pressure coupling algorithm, and the gradient selection is based on the cell-level least squares method.

[0015] In one possible implementation, the performance extraction step is followed by: Set up monitoring points to collect data on the changes in pressure and velocity in the flow field over time; A monitor is constructed by selecting the plane of symmetry as the monitoring plane to monitor the weighted average value of the velocity on the plane of symmetry. Pressure and velocity contour maps of the symmetry plane are obtained based on monitoring points and monitors.

[0016] According to a second aspect of the present invention, a reactor optimization system based on numerical flow experiments is provided, comprising: The geometric modeling module is configured to create a three-dimensional model of the reactor; The computational domain partitioning module is configured to partition the 3D model of the reactor constructed by the geometric modeling module to obtain multiple numerical computational domains for the flow field. The calculation configuration module is configured to determine the flow field calculation model, which includes one or more of the following: a numerical solver, a turbulence model, material properties, and pseudo-transient calculation parameters. The data acquisition module is configured to collect data on actual operating conditions. The boundary condition configuration module is configured to set boundary conditions based on the actual operating conditions acquired by the acquisition module. The boundary conditions include one or more of inlet parameters, outlet parameters, and wall conditions. The inlet parameters include one or more of inlet velocity, inlet pressure, and inlet temperature. The outlet parameters include one or more of outlet velocity, outlet pressure, and outlet temperature. The wall conditions include no-slip boundary conditions and / or thermal boundary conditions. The performance extraction module is configured to calculate the flow field in the numerical calculation domain of the flow field of the calculation domain partitioning module based on the flow field calculation model determined by the calculation configuration module and the boundary conditions configured by the boundary condition configuration module, and obtain the three-dimensional distribution of airflow organization, which includes the velocity distribution and pressure distribution on the symmetry plane. The optimization module is configured to optimize the length and / or orientation of the reactor's baffles based on the velocity and pressure uniformity of the symmetry plane extracted by the performance extraction module, so that the velocity and pressure uniformity of the symmetry plane meets the reactor's performance requirements.

[0017] According to a third aspect of the present invention, a computing device is provided, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the reactor optimization method based on numerical flow experiments described above.

[0018] According to a fourth aspect of the present invention, a computer-readable storage medium is provided that stores computer-executable instructions, which, when executed by a processor, implement the steps of the reactor optimization method based on numerical flow experiments described above.

[0019] According to a fifth aspect of the present invention, a computer program is provided, wherein when the computer program is executed in a computer, the computer is instructed to perform the steps of the reactor optimization method based on numerical flow experiments described above.

[0020] This invention employs computational fluid dynamics numerical modeling, reducing physical experiments with numerical experiments, thereby lowering manpower, material resources, and time costs, and achieving higher computational accuracy than traditional empirical analysis. On the other hand, by optimizing the length and installation direction of the baffles inside the bend, the optimal rectifier optimization scheme is obtained, improving the uniformity of the flow field and helping to improve the reactor's catalytic efficiency and product quality. Attached Figure Description

[0021] Figure 1 This is a schematic flowchart of an embodiment of the reactor optimization method based on numerical flow experiments described in this invention; Figure 2This is a cross-sectional schematic diagram of an embodiment of a three-dimensional model of the reactor described in this invention; Figure 3 This is a schematic diagram of the symmetry plane mesh of the reactor in the reactor optimization method described in this invention; Figure 4 This is a detailed mesh diagram of the bend inlet of the reactor in the reactor optimization method described in this invention; Figure 5 This is a detailed mesh diagram of the reactor's flow plate in the reactor optimization method described in this invention; Figure 6 This is a velocity cloud diagram of the reactor in the reactor optimization method described in this invention; Figure 7 This is a pressure cloud map of the reactor in the reactor optimization method described in this invention; Figure 8 This is a schematic block diagram of an embodiment of the reactor optimization system based on numerical flow experiments described in this invention; Figure 9 This is a schematic block diagram of one embodiment of the computing device described in this invention; Figure 10 This is a schematic block diagram of another embodiment of the computing device described in this invention. Detailed Implementation

[0022] Numerous specific details are set forth in the following description to provide a full understanding of the invention. However, the invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0023] The terminology used in one or more embodiments of the present invention is for the purpose of describing particular embodiments only and is not intended to limit the scope of the invention. The singular forms “a” and “the” as used in one or more embodiments of the invention and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in one or more embodiments of the invention refers to and includes any or all possible combinations of one or more associated listed items.

[0024] It should be understood that although the terms first, second, etc., may be used to describe various information in one or more embodiments of the present invention, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, first may also be referred to as second without departing from the scope of one or more embodiments of the present invention, and similarly, second may also be referred to as first. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to a determination."

[0025] Figure 1 This is a schematic flowchart of an embodiment of the reactor optimization method based on numerical flow experiments described in this invention, as shown below. Figure 1 As shown, the reactor optimization method includes: Step S1: Establish a three-dimensional model of the reactor; Step S2: Divide the three-dimensional model of the reactor into regions to obtain multiple numerical calculation domains for the flow field. Step S3: Collect actual operating conditions, set boundary conditions according to the actual operating conditions, and obtain a boundary configuration file. The boundary conditions include one or more of the following: inlet parameters, outlet parameters, and wall conditions. The inlet parameters include one or more of the following: inlet velocity, inlet pressure, and inlet temperature. The outlet parameters include one or more of the following: outlet velocity, outlet pressure, and outlet temperature. The wall conditions include no-slip boundary conditions and / or thermal boundary conditions. Step S4: Determine the flow field calculation model, which includes one or more of the following: numerical solver, turbulence model, material properties, and pseudo-transient calculation parameters; Step S5: Calculate the flow field based on the flow field calculation model and boundary configuration conditions to obtain the three-dimensional distribution of airflow organization, which includes the velocity distribution and pressure distribution on the symmetry plane. Step S6: Determine whether the velocity uniformity and pressure uniformity of the symmetry plane meet the reactor's performance requirements. If the velocity uniformity and / or pressure uniformity of the symmetry plane do not meet the reactor's performance requirements, adjust the length and / or direction of the reactor's baffles and return to step S1.

[0026] This invention establishes a geometric model, divides the region, determines the flow field calculation settings and boundary conditions, calculates the flow field uniformity, and obtains the optimal rectifier design scheme by adjusting the length and direction of the rectifier to meet the reactor flow field uniformity index requirements. It can quickly calculate and analyze the internal flow field of the reactor, reduce the number of experiments, reduce development costs, and deeply reveal the internal mechanism of the reactor. It is applicable to the design and performance improvement of various reactors in chemical, pharmaceutical, energy and other fields.

[0027] The following details the steps of the reactor optimization method based on numerical flow experiments of this invention: Step S1: Geometric Modeling Steps like Figure 2As shown, the three-dimensional model 11 of the reactor includes an inlet shroud 111, a baffle shroud 112, and a cylindrical body 113. One or more baffles 114 are provided inside the inlet shroud and the baffle shroud. The inlet shroud is connected to the air inlet, and the baffle shroud is connected to both the inlet shroud and the cylindrical body. The cylindrical body is connected to the air outlet. Preferably, one or more catalyst layers 115 are provided inside the cylindrical body.

[0028] In one feasible embodiment, the spoiler 114 is a curved rectifier 1141 or / and a planar rectifier 1142.

[0029] The three-dimensional model of the reactor described above adopts a bent-pipe inlet without a pipe structure and uses a thin-walled metal structure design. The internal circulating medium is metallurgical flue gas. The left side of the reactor is the air inlet, and the right side is the flue gas fan outlet. The gas inlet and outlet are connected to different gas intake and return ports through pipes. The internal gas flow rate is controlled by the exhaust fan. After passing through the upper bend, the gas flows through the grid and two catalyst layers in sequence to the outlet. The specific flow rate is determined by the thickness of the catalyst layers.

[0030] The technical objective of this invention is to optimize the length and direction of the baffles so that the flow field inside the reactor is uniform and meets the required specifications.

[0031] In one feasible embodiment, step S1 includes: Step S11: Obtain the geometric parameters of the reactor's external model and establish a three-dimensional model of the reactor; Step S12: Create a fluid domain sketch on the reference plane of the 3D modeling software to create a 3D model of the fluid domain. Preferably, the 3D model of the fluid domain is stored as a model file. More preferably, the model configuration file is in STEP format, which facilitates subsequent import into the mesh discretization program for mesh generation.

[0032] Step S2: Establishment of the numerical computation domain for the flow field In one feasible embodiment, step S2 includes: The three-dimensional model of the reactor establishes the numerical computation domain of the flow field through mesh discretization modeling, specifically including: The reactor's 3D model is divided into parts based on the length and orientation of the baffles, and a geometric topology is created. Mesh size and global parameters are defined to generate the mesh.

[0033] In one feasible embodiment, step S2 includes: The 3D model of the reactor is imported into a mesh discretization program for mesh generation, including: The model file generated by parametric modeling in 3D modeling software is read in the mesh discretization program to establish the numerical calculation domain of the flow field. The meshing strategy is determined based on the spoiler structure to generate a discrete mesh that meets the computational quality requirements. The computational quality requirements include one or more of the following: mesh orthogonality quality not less than 0.15; aspect ratio not greater than 10; no negative volume elements.

[0034] In one feasible embodiment, the three-dimensional model of the reactor is divided into three numerical computational domains for the flow field: the inlet, the wall, and the outlet.

[0035] In one feasible embodiment, step S2 further includes: Create the geometric topology, including the points and curves necessary to represent the geometry; create the topology based on the entire geometric model.

[0036] In a preferred embodiment, such as Figures 3-5 As shown, step S2 includes: Define generalized global mesh parameters, which include one or more of mesh type, mesh growth ratio, and maximum allowable mesh cells; Define the global mesh size based on the maximum allowed mesh cell size; A robust octree algorithm is used to divide the tetrahedral mesh; To improve computational efficiency, the grid density is set according to the characteristic length of each section of the reactor. The grid density gradually increases from the fine grid on the wall to the inside of the reactor. The grid density on the wall is greater than that inside the reactor. The grid on the wall is the smallest and the grid inside the reactor is the largest. The grid size grows larger from the wall to the inside. Set the mesh size of the numerical computation domain for the flow field (set separate prismatic boundary layer meshes for special shapes and structures), set the maximum size of the inlet and outlet meshes and the maximum size of the meshes on the wall, and generate boundary layer prismatic meshes near the wall.

[0037] Preferably, step S2 further includes storing the three-dimensional model of the reactor after the flow field numerical calculation domain is divided as a geometric model. More preferably, the geometric model is saved in .tin format.

[0038] Step S3, Boundary condition selection steps: In one feasible embodiment, step S3 includes: The corresponding boundary conditions are determined based on the inlet, duct mass flow rate, outlet, and wall conditions, specifically including: The initial ambient pressure of the air inlet is determined based on external environmental conditions. For example, if the air inlet is exposed to the natural environment, atmospheric pressure can be used directly; if the air inlet is connected to other equipment (such as a fan or compressor), it needs to be set according to the equipment's outlet pressure; or relative pressure (based on atmospheric pressure) can be used as the initial ambient pressure of the air inlet. The inlet velocity is determined based on the mass flow rate of the pipeline. For example, the cross-sectional area of ​​the pipeline is obtained based on the mass flow rate of the material in the pipeline and the pipeline diameter, and the velocity of the material at the inlet is obtained by combining the material density. The boundary conditions of the outlet are determined based on the actual situation of the outlet. The boundary conditions of the outlet include one or more of the following: outlet velocity, outlet pressure, and outlet temperature. The boundary conditions of the wall are determined based on the wall material and thickness, and the boundary conditions of the wall include one or more of the following: wall roughness, wall temperature, and wall heat flux.

[0039] In one feasible embodiment, step S4 includes: Set the inlet section of the air intake fairing as a velocity inlet, and set the inlet velocity, turbulence intensity, and hydraulic diameter; The outlet section at the end of the cylinder is set as a pressure outlet, and its static pressure is set as standard atmospheric pressure. All solid walls (including the inner wall of the cylinder, the surface of the intake and the baffle shroud) are set as non-slip, heat-insulating wall boundary conditions, with the baffle shroud and the catalytic layer inside the cylinder being treated as internal walls.

[0040] Step S4: Calculate the configuration steps In one feasible implementation, step S4 includes: A pressure-based explicit steady-state solver is used to establish a turbulence model, and pseudo-transient calculations are set up to simulate compressible flow. The material is chosen as a gas, which is assumed to be an ideal gas, and its density can be solved by the ideal gas law. The gas viscosity coefficient is expressed as a function of temperature.

[0041] In one feasible implementation, step S4 includes: The numerical solver employs a pressure-based explicit steady-state solver. Pseudo-transient calculations are used to simulate compressible flow; Material selection: gas; The density of a gas is solved using the equation of state for an ideal body. The viscosity coefficient of a gas is expressed as a function of temperature.

[0042] In one feasible implementation, step S4 includes: Set the initial flow field, convergence conditions, time step, and total number of iterations for the flow field calculation model.

[0043] In one feasible implementation, step S4 includes: The turbulence model adopted is a turbulence model based on Reynolds' time-averaged equation; The wall functions use the standard wall functions; The physical quantities of the flow field calculation model are differentiated using a second-order upwind scheme to ensure the solution of gradient changes along the grid using physical quantities. The gas is assumed to be an ideal gas, and the viscosity coefficient is solved using the Sutherland formula.

[0044] In one feasible implementation, step S4 includes: The turbulence model adopted is the RNG k-epsilon model; The numerical solver uses the SIMPLEC velocity-pressure coupling algorithm, and the gradient selection is based on the cell-level least squares method.

[0045] Considering the engineering application requirements and computational demands of the model, a turbulence model based on the Reynolds time-averaged equation is adopted for solution. Since the exemplary embodiment of this invention addresses compressible flow problems, the energy equation needs to be enabled. The wall function is the standard wall function. Compared to the standard k-epsilon model, the RNG k-epsilon, by correcting the turbulent viscosity calculation, can more accurately simulate complex flows such as strong swirling and separated flows. The standard wall function can reduce the mesh accuracy requirements in the near-wall region of high Reynolds number flows (such as metallurgical flue gas), improving computational efficiency while maintaining accuracy, and is widely used in the computational analysis of curved fluid flows. The SIMPLEC velocity-pressure coupling algorithm is used for solution, and gradient selection is based on the element-wise least squares method. The differences of each physical quantity in the flow field equations adopt a second-order upwind scheme to ensure accurate solution of gradient variations along the mesh.

[0046] In one feasible embodiment, step S4 constructs the flow field calculation model using the following equation (1): (1) in, The density of the gas; for Velocity components in the direction (three-dimensional spatial coordinates, using) , , express, , P is the stress tensor. F represents the mass force per unit mass. for Mass force per unit mass in the direction of the mass; The viscosity coefficient of the airflow; for The mass force per unit volume in a given direction; , , , The symbol for Kronecker; The internal energy per unit mass of gas; for The influence of the environment on the heat flow of airflow in a specific direction.

[0047] In one feasible embodiment, the influence of flue gas particulate matter is ignored in the flow field calculation model. The flue gas flow inside the reactor is simulated using computational fluid dynamics methods, and its gas flow field can be analyzed using steady-state compressible flow. The flow field calculation model includes continuity equations, momentum equations, and energy equations. The continuity equation states that the mass of fluid flowing into or out of a space through its boundary within a certain time is equal to the change in mass within the space, which conforms to the mass conservation equation. The continuity equation can be constructed using the following equation (2): (2).

[0048] The momentum equation states that the rate of change of momentum of a fluid element within the control volume is equal to the sum of the mass forces and surface forces acting on that volume, which conforms to Newton's second law. The momentum equation is constructed using the following equation (3): (3) in, This represents the inertial force per unit volume. The stress tensor in the Navier-Stokes equations. Obtained through the following formula (4): (4) Among them, the Newtonian viscous stress formula applicable to supersonic flow, , , .

[0049] The energy equation states that the increase in internal energy of a fluid element is equal to the sum of the heat entering the element through thermal conduction, the heat generated within the element, and the work done by the surrounding fluid on the element. This conforms to the law of conservation of energy. The energy equation can be constructed using the following equation (5): (5) in, Work done by a fluid on an infinitesimal element, measured in joules. The heat transferred to the infinitesimal element is expressed in watts; the kinetic energy equation is constructed using the following equation (7): (7) The internal energy equation is constructed by the following equation (8): (8).

[0050] Step S5, Performance Extraction Step: In one feasible embodiment, step S5 includes: Initialize the flow field based on the initial flow field set in step S4; Choose the entry point as the computation source; Set the convergence residual values ​​and the total number of iterations for each parameter of the numerical solver, and begin iterative calculation.

[0051] In one feasible embodiment, step S5 further includes: Set up monitoring points to collect data on the changes in pressure and velocity in the flow field over time; A monitor is constructed by selecting the plane of symmetry as the monitoring plane to monitor the weighted average value of the velocity on the plane of symmetry. Pressure and velocity contour maps of the symmetry plane are obtained based on monitoring points and monitors.

[0052] This invention establishes a monitoring surface to observe the flow field results. The reactor's symmetry plane is defined as the weighted average of the velocities displayed on the monitor. To further analyze the airflow uniformity of the reactor's flow field, contour plots of the velocity and pressure fields are sequentially obtained through post-processing. The airflow uniformity of the reactor's flow field is then observed.

[0053] In a preferred embodiment, step S5 includes: The geometric parameters, key design variables, and solution parameters of the reactor are obtained. The geometric parameters include the external structural parameters of the reactor and the position of the monitoring surface. The key design variables include the length and installation direction of the baffles. The solution parameters include the convergence condition, time step, and total number of iterations. Adjust the geometric dimensions and monitoring surface positions of the flow field calculation model according to the reactor's geometric parameters; Run the flow field calculation model according to the solution parameters to obtain the pressure and velocity at the monitoring surface location; Obtain pressure contour maps and velocity contour maps; Pressure uniformity and velocity uniformity can be obtained based on pressure contour maps and velocity contour maps. For example, pressure uniformity and velocity uniformity can be obtained based on the differences in fluid velocity and pressure and / or the parallelism of streamlines at the same flow field location at the same time on the contour map.

[0054] Step S6, Optimization Steps: In one feasible embodiment, step S6 includes: Observe the airflow uniformity of the reactor flow field, and determine whether the velocity uniformity and pressure uniformity on the symmetry plane meet the reactor's performance requirements. These performance requirements are determined according to the reactor's operating standards. If the velocity uniformity and / or pressure uniformity of the symmetry plane does not meet the reactor's performance requirements, adjust the length and / or direction of the reactor bend baffles and return to step S1. For example, add baffles in areas of dense flow and adjust the direction to make the flow field turn uniformly, thereby improving uniformity.

[0055] In one feasible embodiment, step S6 includes: The data on the changes in pressure and velocity fields before and after optimization at the monitoring surface location were obtained respectively. The changes in velocity and pressure fields at the locations before and after optimization are displayed in the form of cloud maps. The uniformity of airflow in the flow field is observed, and the optimization results are compared to determine whether the rectifier plate adjustment is correct.

[0056] In one specific embodiment of the present invention, such as Figure 2 As shown, the reactor's turbulence-inducing plates include three sets of rectifiers: a curved rectifier, a first planar rectifier, and a second planar rectifier. The curved rectifier is located in the inlet expansion section of the inlet shroud; the first planar rectifier is located at the junction of the inlet shroud and the baffle shroud; and the second planar rectifier is located inside the baffle shroud. Two catalyst layers are provided inside the cylinder.

[0057] The reactor described above is optimized using the reactor optimization method based on numerical flow experiments according to this invention: The velocity contour maps and pressure contour maps obtained after steps S1-S5 are as follows: Figure 6 and Figure 7 As shown: from Figure 6 It can be seen that the fluid exhibits a high velocity near the inlet bend, while the velocity is low in most of the right vertical channel, and then increases significantly at the outlet. This is mainly due to the changes in the reactor and interface, resulting in an inversely proportional change in flow velocity, which ensures sufficient adsorption reaction time for the fluid in the catalyst layer. In the bend section of the bend structure, fluid separation occurs, leading to uneven velocity distribution, which may generate backflow and eddies, thus affecting flow stability. It can also be seen that the velocity is higher upstream of the rectifier plate, while the downstream velocity is lower due to the rectifier plate's influence, resulting in a jet structure along the rectifier plate edge. The velocity uniformity is significantly improved after the grid structure, with a clear velocity change before and after the catalyst layer, reflecting that the fluid can pass through the catalyst more uniformly and react fully.

[0058] from Figure 7 It can be seen that the pressure is generally higher at the inlet and above the bend, gradually decreasing along the flow direction. In the middle of the reactor, due to the influence of the catalyst layer and the grid, the pressure exhibits obvious stratification, gradually decreasing from top to bottom, with the lowest pressure at the outlet, maintaining airflow within the reactor. The pressure drop in the grid section is relatively small, mainly serving a rectifying function; the high catalyst layer thickness and low permeability result in a more significant pressure reduction. Additionally, flow separation at the trailing edge of the rectifier plate also causes some pressure reduction, but the effect is not significant.

[0059] from Figure 6 and Figure 7It can be seen that the bend in the channel causes fluid separation, leading to uneven flow velocity. In step S6, optimizing the length and direction of the rectifier plate can effectively improve the uniformity of the flow velocity and meet the reactor's performance requirements.

[0060] This invention acquires the reactor's geometric parameters, key design variable parameters, and solution parameters; adjusts the geometric dimensions and monitoring surface positions of a preset simulation model based on the reactor's geometric parameters; runs the simulation model according to the solution parameters to obtain pressure and velocity field changes at the monitoring surface positions before and after optimization; displays the velocity and pressure field changes at the positions before and after optimization in the form of cloud maps, observes the flow field uniformity, and compares the optimization results; optimizing the length and direction of the rectifier plate can effectively improve the flow velocity uniformity and meet the reactor's performance requirements.

[0061] Figure 8 This is a schematic block diagram of an embodiment of the reactor optimization system based on numerical flow experiments described in this invention, as shown below. Figure 8 As shown, the reactor optimization system 1 includes: Geometric modeling module 10 is configured to create a three-dimensional model of the reactor; The computational domain partitioning module 20 is configured to partition the three-dimensional model of the reactor constructed by the geometric modeling module to obtain multiple flow field numerical computational domains. The data acquisition module 30 is configured to collect data on actual operating conditions. The boundary condition configuration module 40 is configured to set boundary conditions based on the actual operating conditions collected by the acquisition module. The boundary conditions include one or more of inlet parameters, outlet parameters, and wall conditions. The inlet parameters include one or more of inlet velocity, inlet pressure, and inlet temperature. The outlet parameters include one or more of outlet velocity, outlet pressure, and outlet temperature. The wall conditions include no-slip boundary conditions and / or thermal boundary conditions. The calculation configuration module 50 is configured to determine the flow field calculation model, which includes one or more of the following: a numerical solver, a turbulence model, material properties, and pseudo-transient calculation parameters. The performance extraction module 60 is configured to calculate the flow field of the numerical calculation domain of the flow field of the calculation domain partitioning module based on the flow field calculation model determined by the calculation configuration module and the boundary conditions configured by the boundary condition configuration module, and obtain the three-dimensional distribution of airflow organization, which includes the velocity distribution and pressure distribution of the symmetry plane. The optimization module 70 is configured to optimize the length and / or direction of the reactor's baffles based on the velocity uniformity and pressure uniformity of the symmetry plane extracted by the performance extraction module, so that the velocity uniformity and pressure uniformity of the symmetry plane meet the reactor's performance requirements.

[0062] This invention alleviates the problems of discrete optimization processes, reliance on manual labor, and low efficiency in existing technologies, and achieves optimization of flow channel structure.

[0063] Figure 9 A schematic diagram of an application scenario of the reactor optimization method based on numerical flow experiments described in this invention is shown.

[0064] exist Figure 9 In the application scenario, the computing device 100 can construct a three-dimensional model 101 of the reactor based on the geometric parameters of each component. Then, the computing device 100 can perform mesh discretization modeling based on the three-dimensional model 101 to obtain a geometric model 102 of the reactor with a numerical computational domain for the flow field. Afterwards, the computing device 100 can configure the calculation and boundary conditions according to the actual operating conditions, obtaining a calculation configuration file 104 and a boundary condition configuration file 103, respectively. Finally, the computing device 100 can calculate the flow field 105 corresponding to the actual operating conditions based on the calculation configuration file 104 and the boundary condition configuration file 103, and optimize the reactor based on the velocity distribution and pressure distribution on the symmetry plane within the flow field.

[0065] It should be noted that the aforementioned computing device 100 can be either hardware or software. When the computing device 100 is hardware, it can be implemented as a distributed cluster consisting of multiple servers or terminal devices, or as a single server or a single terminal device. When the computing device 100 is software, it can be installed in the hardware devices listed above. It can be implemented as, for example, multiple software programs or software modules used to provide distributed services, or as a single software program or software module. No specific limitations are made here.

[0066] Figure 10 This diagram illustrates another application scenario of the reactor optimization method based on numerical flow experiments described in this invention.

[0067] exist Figure 10 In this application scenario, the components of the computing device 100 include, but are not limited to, a memory 110 and a processor 120. The processor 120 is connected to the memory 110 via a bus 130, and the database 150 is used to store data.

[0068] The computing device 100 also includes an access device 140, which enables the computing device 100 to communicate via one or more networks 160.

[0069] In one embodiment of the present invention, the above-mentioned components of the computing device 100 and Figure 10 Other components, not shown, can also be connected to each other, for example, via a bus. It should be understood that... Figure 10The illustrated block diagram of the computing device is for illustrative purposes only and is not intended to limit the scope of the invention. Those skilled in the art can add or replace other components as needed.

[0070] The computing device 100 can be any type of stationary or mobile computing device, including mobile computers or mobile computing devices (e.g., tablet computers, personal digital assistants, laptop computers, notebook computers, netbooks, etc.), mobile phones (e.g., smartphones), wearable computing devices (e.g., smartwatches, smart glasses, etc.) or other types of mobile devices, or stationary computing devices such as desktop computers or personal computers (PCs). The computing device 100 can also be a mobile or stationary server.

[0071] The processor 120 executes computer-executable instructions, which, when executed by the processor, implement the steps of the reactor optimization method based on numerical flow experiments described above. The above is a schematic representation of a computing device according to this embodiment. It should be noted that the technical solution of this computing device and the technical solution of the reactor optimization method based on numerical flow experiments described above belong to the same concept. Details not described in detail in the technical solution of the computing device can be found in the description of the technical solution of the reactor optimization method based on numerical flow experiments described above.

[0072] The present invention also provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the reactor optimization method based on numerical flow experiments described above.

[0073] The above is an illustrative scheme of the computer-readable storage medium described in this invention. It should be noted that the technical solution of this storage medium belongs to the same concept as the above-described reactor optimization method based on numerical flow experiments. Details not described in detail in the technical solution of the storage medium can be found in the description of the above-described reactor optimization method based on numerical flow experiments.

[0074] The present invention also provides a computer program, wherein when the computer program is executed in a computer, the computer is instructed to perform the steps of the reactor optimization method based on numerical flow experiments described above.

[0075] The above is an illustrative scheme of the computer program described in this invention. It should be noted that the technical solution of this computer program belongs to the same concept as the above-described reactor optimization method based on numerical flow experiments. Details not described in detail in the computer program's technical solution can be found in the description of the above-described reactor optimization method based on numerical flow experiments.

[0076] The foregoing has described specific embodiments of the invention. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired results. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0077] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the embodiments of the present invention.

[0078] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0079] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. The optional embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the embodiments of the present invention. These embodiments are selected and specifically described to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention.

Claims

1. A numerical flow experiment based reactor optimization method, characterized in that, The method comprises the following steps: a geometry modeling step: establishing a three-dimensional model of the reactor; a flow field numerical calculation domain establishing step: dividing the three-dimensional model of the reactor into regions to obtain a plurality of flow field numerical calculation domains; a boundary condition selecting step: collecting an actual working condition, and setting a boundary condition according to the actual working condition, wherein the boundary condition comprises one or more of an inlet parameter, an outlet parameter and a wall condition; the inlet parameter comprises one or more of an inlet velocity, an inlet pressure and an inlet temperature; the outlet parameter comprises one or more of an outlet velocity, an outlet pressure and an outlet temperature; and the wall condition comprises a no-slip boundary or / and a thermal boundary condition; a calculation configuration step: determining a flow field calculation model, wherein the flow field calculation model comprises one or more of a numerical solver, a turbulence model, material properties and pseudo-transient calculation parameters; a performance extracting step: calculating the flow field based on the flow field calculation model and the boundary condition to obtain a three-dimensional distribution of gas flow organization, wherein the three-dimensional distribution of gas flow organization comprises a symmetric plane velocity distribution and a symmetric plane pressure distribution; an optimization step: judging whether the symmetric plane velocity uniformity and the pressure uniformity meet the index requirements of the reactor; if the symmetric plane velocity uniformity or / and the pressure uniformity does not meet the index requirements of the reactor, adjusting the length or / and direction of the reactor spoiler, and returning to the geometry modeling step.

2. The reactor optimization method of claim 1, wherein, The reactor comprises an inlet fairing, a baffle fairing and a cylinder, one or more spoilers are arranged in the inlet fairing and the baffle fairing; the inlet fairing is in communication with an inlet; the baffle fairing is in communication with the inlet fairing and the cylinder respectively; the cylinder is in communication with an outlet, or / and, one or more catalyst layers are arranged in the cylinder.

3. The reactor optimization method of claim 1, wherein, The flow field numerical calculation domain establishing step comprises: establishing the flow field numerical calculation domain based on the three-dimensional model of the reactor through grid discrete modeling, or / and, the flow field numerical calculation domain establishing step comprises: dividing the three-dimensional model of the reactor as a whole according to the length and direction of the spoiler, creating a geometric topology structure, defining a grid size and global parameters, and generating a grid.

4. The reactor optimization method of claim 1, wherein, The calculation configuration step comprises one or more of the following steps: the numerical solver adopts a pressure-based explicit steady-state solver; pseudo-transient calculation is adopted to simulate compressible flow; the material is selected as a gas; the density of the gas is solved by an ideal body state equation; the gas viscosity coefficient is expressed as a function of temperature, or / and the calculation configuration step comprises one or more of the following steps: setting one or more of an initial flow field, a convergence condition, a time step and a total number of iterations of the flow field calculation model.

5. The reactor optimization method of claim 1, wherein, The calculation configuration step comprises one or more of the following steps: the turbulence model adopts a Reynolds time-averaged equation-based turbulence model; a standard wall function is adopted for a wall function; second-order upwind format is adopted for the difference of each physical quantity of the flow field calculation model to ensure the solution of the physical quantity along the grid gradient change; the gas is assumed to be an ideal gas, and the gas viscosity coefficient is solved by a Sutherland formula.

6. The reactor optimization method of claim 5, wherein, The calculation configuration step comprises one or more of the following steps: the turbulence model adopts an RNG k-epsilon model; The numerical solver adopts the SIMPLEC velocity-pressure coupling algorithm, and the gradient selection is based on the cell-based least square method.

7. The reactor optimization method of claim 1, wherein, The performance extraction step further comprises: setting monitoring points to collect the pressure and velocity of the flow field over time; selecting a symmetry plane as a monitoring plane to construct a monitor to monitor the weighted average value of the symmetry plane velocity; obtaining the pressure and velocity cloud maps of the symmetry plane based on the monitoring points and the monitor.

8. A numerical flow experiment based reactor optimization system, comprising: Comprise: a geometry modeling module configured to establish a three-dimensional model of the reactor; a computational domain division module configured to divide the three-dimensional model of the reactor established by the geometry modeling module into regions to obtain a plurality of flow field numerical calculation domains; a calculation configuration module configured to determine a flow field calculation model, the flow field calculation model comprising one or more of a numerical solver, a turbulence model, material properties, and pseudo-transient calculation parameters; an acquisition module configured to acquire actual working conditions; a boundary condition configuration module configured to set boundary conditions according to the actual working conditions acquired by the acquisition module, the boundary conditions comprising one or more of inlet parameters, outlet parameters, and wall conditions; the inlet parameters comprising one or more of inlet velocity, inlet pressure, and inlet temperature; the outlet parameters comprising one or more of outlet velocity, outlet pressure, and outlet temperature; and the wall conditions comprising no-slip boundary or / and thermal boundary conditions; a performance extraction module configured to perform calculation of the flow field of the flow field numerical calculation domain of the calculation domain division module based on the flow field calculation model determined by the calculation configuration module and the boundary conditions configured by the boundary condition configuration module, to obtain a three-dimensional distribution of gas flow organization, the three-dimensional distribution of gas flow organization comprising a symmetry plane velocity distribution and a symmetry plane pressure distribution; an optimization module configured to optimize the length or / and direction of the spoiler of the reactor based on the symmetry plane velocity uniformity and the pressure uniformity extracted by the performance extraction module, so that the symmetry plane velocity uniformity and the pressure uniformity meet the index requirements of the reactor.

9. A computing device, comprising: Comprise: a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions, which realize the steps of the reactor optimization method based on numerical flow experiment in any one of claims 1 to 7 when executed by the processor.

10. A computer-readable storage medium, characterized in that, The computer executable instructions are stored, which realize the steps of the reactor optimization method based on numerical flow experiment in any one of claims 1 to 7 when executed by the processor.

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