Dust removal equipment structure optimization method and device, equipment and storage medium

Abstract

The invention provides a dust removal equipment structure optimization method and device, equipment and a storage medium. The dust removal equipment structure optimization method comprises the following steps: establishing a fluid model based on an obtained dust removal equipment structure and a particle spraying position; performing grid division on the fluid model to obtain grids; setting inlet and outlet boundary conditions of dust removal equipment; selecting a turbulence model and a DPM model; calculating a turbulence model and a DPM model based on grids, boundary conditions and parameter setting to obtain a total particle generation number and an escape number; obtaining a dust removal rate based on the total particle generation number and the escape number; and optimizing the structure of the dust removal equipment based on the dust removal rate. The model is constructed to simulate the dust removal equipment, and the structure of the dust removal equipment is optimized according to the simulation result, so that the purposes of improving the dust removal efficiency and improving the yield of semiconductor products are achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of semiconductor dust removal, and in particular relates to a dust removal equipment structure optimization method, device, equipment and storage medium. Background Art

[0002] At present, with the development of mobile communications, intelligent automobiles, and miniaturization of various electronic devices, the demand for semiconductor manufacturing is increasing, the etching accuracy is constantly improving, and the diameter of the particles produced by etching will also decrease. In order to ensure the maintenance of the production environment and etching accuracy, it is particularly important to improve the efficiency of dust removal equipment. In semiconductor production, dust removal equipment needs to be operated continuously, and the structure of the dust removal equipment needs to be modified. Therefore, when the existing technology improves efficiency, it has the problem of high cost and low efficiency. Summary of the invention

[0003] In view of the problems existing in the prior art, the present invention provides a method, device, equipment and storage medium for optimizing the structure of a dust removal device, which at least partially solve the problems of high cost and low efficiency existing in the prior art.

[0004] In a first aspect, an embodiment of the present disclosure provides a method for optimizing the structure of a dust removal device, comprising: A fluid model is established based on the obtained dust removal equipment structure and particle injection position; Meshing the fluid model to obtain a mesh; Set the inlet and outlet boundary conditions of the dust removal equipment; Select turbulence model and DPM model; The turbulence model and DPM model are calculated based on the grid, boundary conditions and parameter settings to obtain the total number of particles generated and the number of escapes; The dust removal rate is obtained based on the total number of particles generated and the number of escaped particles; The structure of dust removal equipment is optimized based on the dust removal rate.

[0005] Optionally, the calculating of the turbulence model and the DPM model based on the grid, boundary conditions and parameter settings to obtain the total number of particles generated and the number of escapes includes: Set the residual curve and establish a monitoring curve based on the total mass flow rate of the flow field inlet and outlet; Set the total number of calculation steps, perform iterative solution based on the total number of calculation steps, and obtain the calculation result.

[0006] Optionally, the calculating of the turbulence model and the DPM model based on the grid, boundary conditions and parameter settings to obtain the total number of particles generated and the number of escapes includes: Whether the calculation process converges is determined based on the residual curve, calculation results, and mass flow rate at the inlet and outlet of the flow field. If the calculation process converges, the flow field parameter distribution results are obtained based on the calculation results. The total number of particles generated and the number of escapes are obtained based on the flow field parameter distribution results.

[0007] Optionally, the turbulence model and the DPM model are calculated based on the grid, boundary conditions and parameter settings to obtain the total number of particles generated and the number of escapes, including: if the calculation process does not converge, adjusting the grid, turbulence model and boundary conditions, and recalculating until the calculation process converges.

[0008] Optionally, the optimizing the dust removal equipment structure based on the dust removal rate includes: Different dust removal equipment structural parameters and boundary conditions are set, multiple calculation results are obtained based on different dust removal equipment structural parameters and boundary conditions, simulation results are obtained based on the calculation results, and multiple simulation results are compared to obtain the structural parameters with the highest dust removal rate to complete the optimization.

[0009] In a second aspect, the present disclosure also provides a dust removal equipment structure optimization device, including: A fluid module is used to establish a fluid model based on the acquired dust removal equipment structure and particle injection position; A grid module is used to grid the fluid model to obtain a grid; A setting module, used to set the inlet and outlet boundary conditions of the dust removal equipment; Selection module, used to select turbulence model and DPM model; The calculation module is used to calculate the turbulence model and DPM model based on the grid, boundary conditions and parameter settings to obtain the total number of particles generated and the number of escapes; The dust removal rate module is used to obtain the dust removal rate based on the total number of particles generated and the number of escaped particles; The optimization module is used to optimize the structure of the dust removal equipment based on the dust removal rate.

[0010] In a third aspect, an embodiment of the present disclosure further provides an electronic device, the electronic device comprising: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the dust removal equipment structure optimization method described in any one of the first aspects.

[0011] In a fourth aspect, an embodiment of the present disclosure further provides a computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable a computer to execute any of the dust removal equipment structure optimization methods described in the first aspect.

[0012] In a fifth aspect, an embodiment of the present disclosure further provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the dust removal equipment structure optimization method described in any one of the first aspects.

[0013] The present invention provides a dust removal equipment structure optimization method, device, equipment and storage medium. The dust removal equipment structure optimization method simulates the dust removal equipment by building a model, and optimizes the dust removal equipment structure according to the simulation results, so as to achieve the purpose of improving the dust removal efficiency and improving the yield of semiconductor products. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The above and other objects, features and advantages of the present disclosure will become more apparent through a more detailed description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, wherein like reference numerals generally represent like components throughout the exemplary embodiments of the present disclosure.

[0015] Figure 1 A flow chart of a dust removal equipment structure optimization method provided in an embodiment of the present disclosure; Figure 2 A principle block diagram of a dust removal equipment structure optimization device provided in an embodiment of the present disclosure; Figure 3 A functional block diagram of an electronic device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0016] The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0017] It should be clear that the following embodiments of the present disclosure are described by specific specific examples, and those skilled in the art can easily understand other advantages and effects of the present disclosure from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all of the embodiments. The present disclosure can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present disclosure. It should be noted that the following embodiments and features in the embodiments can be combined with each other in the absence of conflict. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present disclosure.

[0018] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein may be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on the present disclosure, it should be understood by those skilled in the art that an aspect described herein may be implemented independently of any other aspect, and two or more of these aspects may be combined in various ways. For example, any number of aspects described herein may be used to implement the device and / or practice the method. In addition, other structures and / or functionalities other than one or more of the aspects described herein may be used to implement this device and / or practice this method.

[0019] It should also be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present disclosure. The illustrations only show components related to the present disclosure rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0020] Additionally, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, it will be understood by those skilled in the art that the aspects described may be practiced without these specific details.

[0021] This embodiment discloses a method for optimizing the structure of a dust removal device, comprising: A fluid model is established based on the obtained dust removal equipment structure and particle injection position; Meshing the fluid model to obtain a mesh; Set the inlet and outlet boundary conditions of the dust removal equipment; Select turbulence model and DPM model; The turbulence model and DPM model are calculated based on the grid, boundary conditions and parameter settings to obtain the total number of particles generated and the number of escapes; The dust removal rate is obtained based on the total number of particles generated and the number of escaped particles; The structure of dust removal equipment is optimized based on the dust removal rate.

[0022] Optionally, the calculating of the turbulence model and the DPM model based on the grid, boundary conditions and parameter settings to obtain the total number of particles generated and the number of escapes includes: Set the residual curve and establish a monitoring curve based on the total mass flow rate of the flow field inlet and outlet; Set the total number of calculation steps, perform iterative solution based on the total number of calculation steps, and obtain the calculation result.

[0023] Optionally, the calculating of the turbulence model and the DPM model based on the grid, boundary conditions and parameter settings to obtain the total number of particles generated and the number of escapes includes: According to the residual curve, calculation results and mass flow rate at the inlet and outlet of the flow field, it is judged whether the calculation process converges. If the calculation process converges, the flow field parameter distribution results are obtained based on the calculation results. Based on the flow field parameter distribution results, the total number of particles generated and the number of escapes are obtained, and the total number of particles generated and the number of escapes are output.

[0024] Optionally, the turbulence model and the DPM model are calculated based on the grid, boundary conditions and parameter settings to obtain the total number of particles generated and the number of escapes, including: if the calculation process does not converge, adjusting the grid, turbulence model and boundary conditions, and recalculating until the calculation process converges.

[0025] Optionally, the optimizing the dust removal equipment structure based on the dust removal rate includes: Different dust removal equipment structural parameters and boundary conditions are set, multiple calculation results are obtained based on different dust removal equipment structural parameters and boundary conditions, simulation results are obtained based on the calculation results, and multiple simulation results are compared to obtain the structural parameters with the highest dust removal rate to complete the optimization.

[0026] In a specific application scenario, such as Figure 1 As shown, this embodiment discloses a method for optimizing the structure of dust removal equipment and determining the dust removal rate based on Fluent calculation, the method comprising: S1: Determine the structure of the dust removal equipment and the particle injection position, and establish a fluid model; use SpaceClaim to simplify the stp format model to obtain the structure of the dust removal equipment and the particle injection position; SpaceClaim is a powerful 3D solid direct modeling software, especially for engineering and industrial designers. It provides an intuitive and easy-to-use interface and Direct Modeling technology, allowing users to quickly create and modify complex 3D models without having to pay attention to the source of the model or the complexity of the establishment process.

[0027] S2: Meshing the fluid model of the dust removal equipment using Fluent Mesh; Fluent Solution is an important functional module in ANSYS Fluent software, mainly used for fluid dynamics simulation and computational fluid dynamics (CFD) analysis. Fluent Solution provides a variety of solver options and algorithms, suitable for a variety of complex flow simulation scenarios.

[0028] Main functions of Fluent Solution: Solver type: Fluent provides pressure-based solvers and density-based solvers. Pressure-based solvers are also called segregated solvers, which are suitable for steady-state and transient flow simulations; while density-based solvers are also called coupled solvers, which are suitable for simulations of high-speed flows and strongly coupled phenomena.

[0029] Algorithm selection: The pressure-based solver in Fluent uses a projection method to iteratively solve the governing equations to obtain a converged solution. The Segregated Algorithm solves the governing equations sequentially, while the Coupled Algorithm solves all equations simultaneously.

[0030] S3: Check the mesh and set the mesh parameters. Use the mesh checker to check the quality of the mesh elements and make sure there are no overstretched or distorted elements. Adjust mesh parameters such as element size and overlap area to optimize computational efficiency and accuracy.

[0031] S4: Select a turbulence model and a DPM model. In this embodiment, the turbulence model and the DPM model are bidirectionally coupled. Input parameters into the turbulence model and the DPM model to obtain an output result. Select a turbulence model to describe the turbulence characteristics of the fluid, and select a DPM model to simulate the movement and distribution of particles in the fluid.

[0032] The DPM model (Discrete Phase Model) is a model used to simulate the movement of particles in a fluid. It is mainly based on the Lagrangian method to describe the movement of particles, while the Euler method describes the movement of fluids. The DPM model is applicable to the case where the volume fraction of the particle phase is less than 10%. It does not consider the interaction between particles, but can consider the interaction between particles and fluids.

[0033] The basic principle of the DPM model: The DPM model simplifies moving particles into moving mass points, and ignores the flow details around the particles during the calculation process, such as vortex shedding, flow separation, boundary layer, etc. The governing equation of particle motion is based on Newton's second law, taking into account the interaction force between particles and fluid.

[0034] The DPM model (Discrete Phase Model) in Fluent is mainly used to simulate the movement and interaction of particles in the flow field, and is particularly suitable for situations where the volume fraction of the particle phase is less than 10%. The DPM model is based on the Lagrangian method to describe particle movement, while the Euler method describes fluid movement. This combination enables the DPM model to accurately simulate the behavior of particles in complex flow fields.

[0035] S5: Set inlet and outlet boundary conditions, analyze the flow area and perform volume extraction, name the inlet and outlet boundaries; for example, you can set the velocity, temperature and DPM wall boundary conditions at the inlet. Set the pressure conditions at the outlet. Set the initial velocity, temperature and mass flow rate of the particles for the particle injection port.

[0036] S6: Initialize the grid node calculation information, and import the grid into Fluent solution for calculation settings; S7: Set the residual curve, establish a monitoring curve according to the total mass flow rate of the flow field inlet and outlet, set the total number of calculation steps, and perform iterative solution to obtain the calculation results; such as setting the residual curve to monitor the convergence of the velocity and pressure fields. Establish a monitoring curve to monitor the mass flow rate of the flow field inlet and outlet. Set the total number of calculation steps, such as 5000 steps. Perform iterative calculation until the convergence condition is reached.

[0037] S8: According to the residual curve, calculation results and the mass flow rate at the inlet and outlet of the flow field, determine whether the calculation process converges. If converged, post-process the calculation results to obtain the flow field parameter distribution results, check the total number of particles generated and the number of escaped particles, and calculate the dust removal rate; if not converged, adjust the grid, turbulence model and boundary conditions, and recalculate until the calculation process converges; S9: Save the calculation results after the calculation converges; S10: Modify the structural parameters and boundary conditions of the dust removal equipment. After the modification is completed, repeat S1-S9 to obtain multiple simulation results, compare the multiple simulation results, obtain the structure and parameters with the highest dust removal rate, and complete the optimization method.

[0038] like Figure 2 As shown, this embodiment also discloses a dust removal equipment structure optimization device, including: A fluid module is used to establish a fluid model based on the acquired dust removal equipment structure and particle injection position; A grid module is used to grid the fluid model to obtain a grid; A setting module, used to set the inlet and outlet boundary conditions of the dust removal equipment; Selection module, used to select turbulence model and DPM model; The calculation module is used to calculate the turbulence model and DPM model based on the grid, boundary conditions and parameter settings to obtain the total number of particles generated and the number of escapes; The dust removal rate module is used to obtain the dust removal rate based on the total number of particles generated and the number of escaped particles; The optimization module is used to optimize the structure of the dust removal equipment based on the dust removal rate.

[0039] The electronic device disclosed in this embodiment includes a memory and a processor. The memory is used to store non-temporary computer-readable instructions. Specifically, the memory may include one or more computer program products, and the computer program product may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, a random access memory (RAM) and / or a cache memory (cache), etc. The non-volatile memory may include, for example, a read-only memory (ROM), a hard disk, a flash memory, etc.

[0040] The processor may be a central processing unit (CPU) or other forms of processing units with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In one embodiment of the present disclosure, the processor is used to run the computer-readable instructions stored in the memory, so that the electronic device performs all or part of the steps of the dust removal device structure optimization method of each embodiment of the present disclosure.

[0041] Those skilled in the art should be able to understand that in order to solve the technical problem of how to obtain a good user experience, the present embodiment may also include well-known structures such as a communication bus and an interface, and these well-known structures should also be included in the protection scope of the present disclosure.

[0042] like Figure 3 The present invention provides a schematic diagram of the structure of an electronic device according to an embodiment of the present invention, which is suitable for implementing the electronic device in the embodiment of the present invention. Figure 3 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0043] like Figure 3 As shown, the electronic device may include a processing device (such as a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) or a program loaded from a storage device into a random access memory (RAM). In the RAM, various programs and data required for the operation of the electronic device are also stored. The processing device, ROM, and RAM are connected to each other through a bus. The input / output (I / O) interface is also connected to the bus.

[0044] Typically, the following devices can be connected to the I / O interface: input devices such as sensors or visual information acquisition devices; output devices such as display screens; storage devices such as tapes, hard disks, etc.; and communication devices. The communication device allows the electronic device to communicate with other devices (such as edge computing devices) wirelessly or by wire to exchange data. Figure 3 An electronic device having various devices is shown, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead.

[0045] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device, or installed from a ROM. When the computer program is executed by a processing device, all or part of the steps of the dust removal equipment structure optimization method of the embodiment of the present disclosure are executed.

[0046] For detailed description of this embodiment, reference may be made to the corresponding descriptions in the aforementioned embodiments, which will not be repeated here.

[0047] The computer-readable storage medium disclosed in this embodiment stores non-transitory computer-readable instructions. When the non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the dust removal equipment structure optimization method of each embodiment of the present disclosure are executed.

[0048] The above-mentioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or mobile hard disk), media with built-in rewritable non-volatile memory (e.g., memory card) and media with built-in ROM (e.g., ROM box).

[0049] For detailed description of this embodiment, reference may be made to the corresponding descriptions in the aforementioned embodiments, which will not be repeated here.

[0050] The basic principles of the present disclosure are described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, effects, etc. mentioned in the present disclosure are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. are required by each embodiment of the present disclosure. In addition, the specific details disclosed above are only for the purpose of illustration and ease of understanding, and are not limitations. The above details do not limit the present disclosure to the necessity of adopting the above specific details to be implemented.

[0051] In the present disclosure, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. The block diagrams of the devices, devices, equipment, and systems involved in the present disclosure are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagram. As will be appreciated by those skilled in the art, these devices, devices, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open words, referring to "including but not limited to", and can be used interchangeably with them. The words "or" and "and" used here refer to the words "and / or" and can be used interchangeably with them, unless the context clearly indicates otherwise. The words "such as" used here refer to the phrase "such as but not limited to", and can be used interchangeably with them.

[0052] Additionally, as used herein, "or" used in a list of items beginning with "at least one" indicates a separate list, so that, for example, a list of "at least one of A, B, or C" means A or B or C, or AB or AC or BC, or ABC (i.e., A and B and C). Furthermore, the word "exemplary" does not mean that the example described is preferred or better than other examples.

[0053] It should also be noted that in the system and method of the present disclosure, each component or each step can be decomposed and / or recombined. Such decomposition and / or recombination should be regarded as equivalent solutions of the present disclosure.

[0054] Various changes, substitutions, and modifications of the techniques described herein may be made without departing from the teachings defined by the appended claims. Furthermore, the scope of the claims of the present disclosure is not limited to the specific aspects of the processes, machines, manufactures, compositions of events, means, methods, and actions described above. Currently existing or later to be developed processes, machines, manufactures, compositions of events, means, methods, or actions that perform substantially the same functions or achieve substantially the same results as the corresponding aspects described herein may be utilized. Thus, the appended claims include such processes, machines, manufactures, compositions of events, means, methods, or actions within their scope.

[0055] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the aspects shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

[0056] The above description has been given for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present disclosure to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations thereof.

Claims

1. A method for optimizing the structure of dust removal equipment, characterized in that: include: A fluid model is established based on the obtained dust removal equipment structure and particle injection position; Meshing the fluid model to obtain a mesh; Set the inlet and outlet boundary conditions of the dust removal equipment; Select turbulence model and DPM model; The turbulence model and DPM model are calculated based on the grid, boundary conditions and parameter settings to obtain the total number of particles generated and the number of escapes; The dust removal rate is obtained based on the total number of particles generated and the number of escaped particles; The structure of dust removal equipment is optimized based on the dust removal rate.

2. The dust removal equipment structure optimization method according to claim 1, characterized in that: The turbulence model and the DPM model are calculated based on the grid, boundary conditions and parameter settings to obtain the total number of particles generated and the number of escapes, including: Set the residual curve and establish a monitoring curve based on the total mass flow rate of the flow field inlet and outlet; Set the total number of calculation steps, perform iterative solution based on the total number of calculation steps, and obtain the calculation result.

3. The dust removal equipment structure optimization method according to claim 2, characterized in that: The turbulence model and the DPM model are calculated based on the grid, boundary conditions and parameter settings to obtain the total number of particles generated and the number of escapes, including: Whether the calculation process converges is determined based on the residual curve, calculation results, and mass flow rate at the inlet and outlet of the flow field. If the calculation process converges, the flow field parameter distribution results are obtained based on the calculation results. The total number of particles generated and the number of escapes are obtained based on the flow field parameter distribution results.

4. The dust removal equipment structure optimization method according to claim 3, characterized in that: The turbulence model and the DPM model are calculated based on the grid, boundary conditions and parameter settings to obtain the total number of particles generated and the number of escapes, including: if the calculation process does not converge, the grid, turbulence model and boundary conditions are adjusted, and the calculation is recalculated until the calculation process converges.

5. The dust removal equipment structure optimization method according to claim 4, characterized in that: The optimization of the dust removal equipment structure based on the dust removal rate includes: Different dust removal equipment structural parameters and boundary conditions are set, multiple calculation results are obtained based on the different dust removal equipment structural parameters and boundary conditions, simulation results are obtained based on the calculation results, and multiple simulation results are compared to obtain the structural parameters with the highest dust removal rate to complete the optimization.

6. A dust removal equipment structure optimization device, characterized in that: include: A fluid module is used to establish a fluid model based on the acquired dust removal equipment structure and particle injection position; A grid module is used to grid the fluid model to obtain a grid; A setting module, used to set the inlet and outlet boundary conditions of the dust removal equipment; Selection module, used to select turbulence model and DPM model; The calculation module is used to calculate the turbulence model and DPM model based on the grid, boundary conditions and parameter settings to obtain the total number of particles generated and the number of escapes; The dust removal rate module is used to obtain the dust removal rate based on the total number of particles generated and the number of escaped particles; The optimization module is used to optimize the dust removal equipment structure based on the dust removal rate.

7. The dust removal equipment structure optimization device according to claim 6, characterized in that: The turbulence model and the DPM model are calculated based on the grid, boundary conditions and parameter settings to obtain the total number of particles generated and the number of escapes, including: Set the residual curve and establish a monitoring curve based on the total mass flow rate of the flow field inlet and outlet; Set the total number of calculation steps, perform iterative solution based on the total number of calculation steps, and obtain the calculation result.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the dust removal equipment structure optimization method described in any one of claims 1-5.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the dust removal equipment structure optimization method described in any one of claims 1-5.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instruction is executed by a processor, the dust removal equipment structure optimization method described in any one of claims 1-5 is implemented.

Images