Design method of asymmetric guide vane diffuser for centrifugal compressor

Abstract

The invention provides a design method of an asymmetric guide vane diffuser for a centrifugal compressor, and belongs to the technical field of distributed new energy and aviation power. The method comprises the steps that the basic size and shape of the diffuser are determined based on the outlet airflow condition of the centrifugal compressor; according to the connecting mode of the diffuser and the volute, the design requirement of the asymmetric guide vane is determined; according to the number of the blades, the numbers and initial positions of the blades are determined, and according to airflow conditions and blade outlet boundary requirements, the angles and the positions of the blades are adjusted; based on the preliminary design, geometric parameters of the blade are calculated, and the geometric parameters comprise the trailing edge distance, the included angle and the mean camber line coordinate; and gradually optimizing the geometric parameters through an iterative calculation method. Through iterative optimization and CFD simulation, the aerodynamic performance of the diffuser can be remarkably improved, the flow loss is reduced, and the overall efficiency of a gas compressor is improved.

Description

Technical Field

[0001] The invention proposes a design method for an asymmetric guide vane diffuser for a centrifugal compressor, and belongs to the technical field of distributed new energy and aviation power. Background Art

[0002] Centrifugal compressors have the advantages of compact structure and large compression ratio. As a supercharging component, they can be widely used in gas turbine aircraft engines and other fields. When the airflow passes through the centrifugal compressor rotor blades to do work, it has a large kinetic energy. It is often necessary to use a diffuser to further decelerate and supercharge the airflow, and then the volute guides the airflow to the single-tube combustion chamber. The traditional diffuser blades are designed to be centrally symmetrical. After being connected to the volute, the boundary conditions of the blade outlets at different circumferential positions are not consistent, resulting in differences in the actual loads of the blades. Since the blades do not work at the optimal state point, it eventually causes problems such as increased flow losses inside the diffuser and limited pressure diffusion capacity. This proposal proposes a design method for an asymmetric guide vane diffuser. By designing the diffuser guide vanes asymmetrically, the aerodynamic loads of different guide vanes are reasonably distributed. Compared with the traditional axisymmetric uniformly distributed guide vane diffuser, the design method proposed in the present invention suppresses the flow separation inside the diffuser to a certain extent, reduces the flow loss, and has the potential to improve the stable working range of the centrifugal compressor. Summary of the invention

[0003] The present invention provides a design method for an asymmetric guide vane diffuser for a centrifugal compressor, which is used to solve the problems that the bladeless diffuser in the prior art is limited by the impeller outlet airflow angle and the traditional vaned diffuser is prone to stall due to the mismatch between the airflow and the blades.

[0004] The present invention proposes a design method for an asymmetric guide vane diffuser for a centrifugal compressor, the method comprising:

[0005] S1. Determine the basic size and shape of the diffuser based on the outlet airflow conditions of the centrifugal compressor; determine the design requirements of the asymmetric guide vanes based on the connection method between the diffuser and the volute;

[0006] S2. According to the number of blades, determine the number and initial position of the blades, and adjust the angle and position of the blades according to the airflow conditions and the blade outlet boundary requirements;

[0007] S3. Based on the preliminary design, calculate the geometric parameters of the blade, wherein the geometric parameters include the trailing edge distance, the included angle, and the coordinates of the mid-arc line; and gradually optimize the geometric parameters by an iterative calculation method;

[0008] S4. Perform flow field analysis on the optimized blades through numerical simulation software, evaluate the aerodynamic performance of the blades according to the numerical simulation results, and further optimize the design based on the evaluation results;

[0009] S5. Based on the final optimization results, develop detailed blade manufacturing drawings and processes, and manufacture and test the blades.

[0010] Furthermore, the S1 includes:

[0011] S11, collecting key parameters of the centrifugal compressor outlet through a sensor, wherein the key parameters include air flow velocity and air flow direction;

[0012] S12. Based on the collected airflow data and using the principles of gas dynamics, calculate the basic dimensions of the diffuser, wherein the basic dimensions include an inlet diameter, an outlet diameter, and a channel height;

[0013] S13. Analyze the relevant parameters of the connection structure between the diffuser and the volute, including the angle, curvature and sealing method of the connection, and clarify the design requirements of the asymmetric guide vanes, including the need to match the shape of the volute and reduce flow losses;

[0014] S14. According to the connection method between the diffuser and the volute and the airflow conditions, the number, distribution and basic shape of the asymmetric guide vanes are preliminarily set.

[0015] Furthermore, the S2 includes:

[0016] S21. Determine the number of blades according to the size and design requirements of the diffuser, and number the blades;

[0017] S22, preliminarily setting the position of the blade in the diffuser according to the geometric shape of the diffuser and the airflow conditions, wherein the position includes the leading edge and the trailing edge of the blade and the relative position between the blades;

[0018] S23. Based on the airflow conditions and the blade outlet boundary requirements, a preliminary simulation is performed using computational fluid dynamics software to analyze the effect of the blade angle on the airflow, and the blade angle is adjusted based on the analysis results;

[0019] S24. On the basis of adjusting the blade angle, the position of the blade in the diffuser is further optimized.

[0020] Furthermore, the S23 includes:

[0021] S231, constructing a three-dimensional geometric model through CAD software according to the actual size, blade shape and initially set position of the diffuser, and importing the geometric model into CFD software to set boundary conditions;

[0022] S232, meshing the constructed CFD model and verifying mesh independence;

[0023] S233, performing CFD simulation to analyze key parameters of airflow passing through the diffuser, wherein the key parameters include velocity field; and displaying the flow state of airflow between blades through visualization tools;

[0024] S234. Based on the preliminary simulation results, the main areas causing flow losses are identified, and the parameters of the blades are adjusted one by one through sensitivity analysis;

[0025] S235, and, after each adjustment, a new round of CFD simulation is performed, and the blade angle is gradually optimized through multiple iterations until the predetermined performance improvement target is achieved;

[0026] S236. During the optimization process, dynamic simulation is introduced to consider the influence of the unsteady effect of blade rotation or periodic changes on the airflow;

[0027] S237. After completing all iterative optimizations, conduct a comprehensive performance evaluation of the final diffuser design, verify the accuracy of the CFD simulation results, and make necessary fine-tuning based on the measured data.

[0028] Furthermore, the S3 includes:

[0029] S31, calculating the geometric parameters of the blade according to the initially designed blade shape and position, wherein the geometric parameters include the trailing edge distance, the included angle, and the mid-arc coordinates;

[0030] S32. Based on the principles of computational fluid dynamics, an iterative calculation model is established to gradually optimize the geometric parameters of the blades; by continuously adjusting the geometric parameters, the influence of the blades on the airflow is simulated and analyzed, and the blade design is optimized based on the simulation analysis results;

[0031] S33, substituting the optimized blade geometric parameters into the iterative calculation model for verification, and judging whether the optimization results meet the design requirements. If not, continue to perform optimization iterations until the best design effect is achieved.

[0032] Further, the S32 includes:

[0033] S321. Based on the preliminary design of the blade, a mathematical model including blade geometry, airflow boundary conditions and physical properties is established using CFD software;

[0034] S322. Based on the preset optimization goal and design requirements, set corresponding performance indicator thresholds as reference benchmarks for iterative optimization;

[0035] S323, inputting the preliminarily designed blade geometric parameters as initial values ​​into the iterative calculation model;

[0036] S324, automatically adjusting the blade geometric parameters in the iteration process by using a genetic algorithm; in each iteration, using CFD software to simulate and analyze the adjusted blade geometric parameters;

[0037] S325. In the iterative process, a prediction model between blade geometric parameters and performance indicators is established through a machine learning algorithm; and the model is continuously trained;

[0038] S326. Based on the simulation analysis results, determine whether the current geometric parameters meet the design requirements; if the performance indicators do not meet expectations, adjust the geometric parameters based on the sensitivity analysis results and the machine learning prediction model to enter the next round of iteration; repeat S324 to S326 until the performance indicators converge to the optimal solution or reach the preset upper limit of the number of iterations.

[0039] Furthermore, the S4 includes:

[0040] S41. Select numerical simulation software according to the complexity of the diffuser and the computing resources, and perform flow field analysis based on the selected numerical simulation software;

[0041] S42, setting parameters of numerical simulation according to actual operating conditions and design requirements of the diffuser, wherein the numerical simulation parameters include inlet conditions, outlet conditions, boundary conditions, and solution algorithms;

[0042] S43, running numerical simulation software to perform flow field analysis on the optimized blades to obtain flow conditions of the airflow inside the diffuser, wherein the flow conditions include velocity distribution, etc.;

[0043] S44. Evaluate the aerodynamic performance of the blade based on the numerical simulation results, and further optimize the design of the blade based on the evaluation results of the aerodynamic performance.

[0044] Furthermore, the S5 includes:

[0045] S51. Develop detailed manufacturing drawings based on the final optimized blade design, and determine the manufacturing process based on the material and shape characteristics of the blade, wherein the manufacturing process includes casting, forging, machining or 3D printing;

[0046] S52. Manufacture blades according to manufacturing drawings and process requirements, perform performance tests on the manufactured blades, and verify the design effects of the blades and evaluate performance stability based on the test data.

[0047] The present invention proposes a non-temporary computer-readable storage medium, on which a computer program is stored. The program is executed by a processor to implement a design method for an asymmetric guide vane diffuser for a centrifugal compressor as described in any one of the above.

[0048] A computer program product proposed by the present invention includes a computer program / instruction, which, when executed by a processor, implements a design method for an asymmetric guide vane diffuser for a centrifugal compressor as described in any one of the above.

[0049] The beneficial effects of the present invention are as follows: through iterative optimization and CFD simulation, the aerodynamic performance of the diffuser can be significantly improved, the flow loss can be reduced, and the overall efficiency of the compressor can be improved; the design is based on detailed airflow data and gas dynamics principles to ensure that the basic size and shape of the diffuser meet the actual working conditions, thereby enhancing its adaptability; the sensitivity analysis and machine learning models introduced in the design process make the adjustment of the blade geometric parameters more accurate and efficient, and respond quickly to changes in performance requirements; through the combination of numerical simulation and measured data, the reliability of the design results is ensured, and a scientific basis is provided for subsequent performance verification; detailed manufacturing drawings and process flows are formulated to ensure that the design scheme can be smoothly transformed into an actual product, thereby improving the controllability and efficiency of the manufacturing process; the optimization process and model established by this method can provide a reference for subsequent similar designs, form a replicable technology accumulation, and contribute to the sustainable development of related fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a schematic diagram of the double-outlet volute diffuser of the present invention;

[0051] Figure 2 is a schematic diagram of the asymmetric diffuser of the present invention;

[0052] Figure 3 This is a step diagram of the method described in the present invention. DETAILED DESCRIPTION

[0053] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0054] One embodiment of the present invention, as Figure 3 As shown, a design method for an asymmetric guide vane diffuser for a centrifugal compressor is characterized in that the method comprises:

[0055] S1. Determine the basic size and shape of the diffuser based on the outlet airflow conditions of the centrifugal compressor; determine the design requirements of the asymmetric guide vanes based on the connection method between the diffuser and the volute;

[0056] S2. According to the number of blades, determine the number and initial position of the blades, and adjust the angle and position of the blades according to the airflow conditions and the blade outlet boundary requirements;

[0057] S3. Based on the preliminary design, calculate the geometric parameters of the blade, wherein the geometric parameters include the trailing edge distance, the included angle, and the coordinates of the mid-arc line; and gradually optimize the geometric parameters by an iterative calculation method;

[0058] S4. Perform flow field analysis on the optimized blades through numerical simulation software, evaluate the aerodynamic performance of the blades according to the numerical simulation results, and further optimize the design based on the evaluation results;

[0059] S5. Based on the final optimization results, develop detailed blade manufacturing drawings and processes, and manufacture and test the blades.

[0060] For example: Take the double-outlet volute diffuser as an example. Figure 1 As shown, the diffuser outlet is connected to two centrally symmetrical volutes. The airflow from the centrifugal compressor enters the diffuser from the inlet, is guided by the asymmetric diffuser guide vanes, and then enters the volute. The following is the method for determining the geometry of the asymmetric diffuser.

[0061] by Figure 2 For example, on the XY plane, the diffuser inlet is circular, with a corresponding radius of r2; the leading edge of the diffuser guide vane is on a circle with a radius of r3; the interface between the diffuser and the volute is circular, with a corresponding radius of r5. In addition, the diffuser channel height is d. The angle between the absolute velocity direction of the airflow at the diffuser inlet and the radial direction is α2. According to the principles of gas dynamics, the angle α3 between the absolute velocity direction of the airflow at the leading edge of the blade and the radial direction is approximately equal to α2, that is, α3=α2 approximately.

[0062] The number of diffuser blades is generally 1 to 5 less than the number of compressor blades, and the greatest common divisor of the number of diffuser blades and the compressor blades must be 1. Figure 2 In the figure, 10 blades are used as an example. Since the two volutes are symmetrically distributed, after determining the positions of the five blades in the semicircle, the geometry of the entire circumference of the diffuser can be obtained by rotation and replication.

[0063] The five asymmetric blades V1 to V5 are numbered from 1 to 5, and the angle between the line connecting the leading edge of the blade and the coordinate origin O and OX is θ i For blade numbered i, the distance r between the trailing edge and the coordinate origin O is 4,i , the angle between the tangent line at the trailing edge and the radial direction α 4,i , mid-arc coordinates (XC,i ,Y C,i ), suction surface coordinates (X SS,i ,Y SS,i ), pressure surface coordinates (X PS,i ,Y PS,i ) are all θ i The function is:

[0064] (r 4,i ,α 4,i ,X C,i ,Y C,i ,X SS,i ,Y SS,i ,X PS,i ,Y PS,i )=f(θ i )

[0065] The determination method of each parameter is as follows:

[0066] 1. Specify r 4,i In general, r 4,i is a constant, that is, the trailing edge of the blade is on the same radius circle.

[0067] 2. Determine θ i In general, θ i+1 -θ i It decreases as i increases.

[0068] 3. Specify α 4,i In general, α 4,i With θ i There is a linear relationship.

[0069] 4. Determine the coordinates of the mid-arc. C,i The angle α between the tangent line at point C on the mid-arc and the radial direction C,i ,but:

[0070]

[0071] The coordinates of point C (X C,i ,Y C,i ):

[0072]

[0073]

[0074] Where R i The radius of the arc corresponding to the median arc in polar coordinates:

[0075]

[0076] 5. Determine the coordinates of the suction and pressure surfaces. The dimensionless relative offset of the diffuser blade profile is The suction surface coordinates (X SS,i ,Y SS,i ):

[0077]

[0078]

[0079] The pressure surface coordinates (X PS,i ,Y PS,i ):

[0080]

[0081]

[0082] The above determines the entire geometry of the asymmetric guide vane diffuser.

[0083] The working principle of the above technical solution is: according to the outlet airflow conditions of the centrifugal compressor (such as flow velocity, flow rate, pressure, etc.), the basic size (such as diameter, length, etc.) and overall shape of the diffuser are determined by using the principles of fluid mechanics and the working principle of the centrifugal compressor; considering the connection method between the diffuser and the volute (such as direct connection, transition section connection, etc.), and the asymmetry of the flow field inside the volute, the design requirements of the asymmetric guide vane are determined. According to the number of blades, the blades are numbered and the initial position of each blade is determined. The initial position is determined based on the overall size and shape of the diffuser and the principle of uniform distribution of the blades; according to the airflow conditions and the requirements of the blade outlet boundary (such as outlet flow velocity, outlet angle, etc.), the angle and position of the blade are adjusted, and based on the preliminary design, the geometric parameters of the blade are calculated, including the trailing edge distance, angle, and mid-arc coordinates. These parameters have an important influence on the aerodynamic performance of the blade; the geometric parameters of the blade are gradually optimized using an iterative calculation method. The optimized blade is analyzed for flow field using numerical simulation software (such as CFD software). Simulate the airflow conditions of the blades under actual working conditions, including flow velocity, pressure distribution, etc.; evaluate the aerodynamic performance of the blades based on the numerical simulation results. Evaluation indicators usually include flow efficiency, pressure loss, stability, etc.; based on the evaluation results, further optimize the design. Involves fine-tuning of the blade geometry parameters, or improvements to the overall structure of the diffuser; based on the final optimization results, develop detailed blade manufacturing drawings and processes. Including determining the blade material, processing method, quality inspection standards, etc.; manufacturing blades according to manufacturing drawings and processes, and conducting rigorous testing. Tests usually include performance tests (such as aerodynamic performance, mechanical properties, etc.) and durability tests (such as fatigue tests, corrosion resistance tests, etc.).

[0084] The effects of the above technical scheme are as follows: by determining the basic size and shape of the diffuser based on the outlet airflow conditions of the centrifugal compressor, the airflow distribution inside the diffuser can be ensured to be more reasonable; the design of the asymmetric guide vane can better adapt to the asymmetry of the flow field inside the volute, reducing the turbulence and loss of the airflow inside the diffuser; adjusting the blade angle and position according to the airflow conditions and the blade outlet boundary requirements can ensure that the blade guides the airflow in the best posture and improves the aerodynamic performance; optimizing the blade geometric parameters through iterative calculation methods can further reduce flow losses and improve the diffusion efficiency; the design of the asymmetric guide vane helps to reduce the airflow separation and vortex structure inside the diffuser, thereby improving the stability of the diffuser; through the flow field analysis of the blade by numerical simulation software, potential unstable factors can be discovered and resolved in time to ensure that the diffuser can operate stably under various working conditions; detailed blade manufacturing drawings and process formulation can be Ensure the manufacturing accuracy and quality of the blades, and reduce performance degradation or failures caused by manufacturing errors; strict control of the manufacturing and testing links can further verify the reliability and durability of the blades, and ensure that there will be no serious problems during long-term use; through numerical simulation software, flow field analysis and aerodynamic performance evaluation of the blades can be carried out, problems can be found and optimized in the early stage of design, thereby reducing the number of design iterations and reducing design costs; detailed blade manufacturing drawings and process formulation can guide the manufacturing process, improve manufacturing efficiency and reduce manufacturing costs; this design method can flexibly adjust the design parameters of the diffuser and blades according to different centrifugal compressor outlet airflow conditions and volute connection methods, and has strong adaptability; this asymmetric guide vane diffuser design method is not only suitable for traditional centrifugal compressors, but can also be applied to power systems in the fields of aviation, ships, etc., as well as equipment such as turbochargers, and has broad application prospects.

[0085] In one embodiment of the present invention, the S1 includes:

[0086] S11, collecting key parameters of the centrifugal compressor outlet through sensors, wherein the key parameters include air flow velocity, pressure, temperature and air flow direction;

[0087] S12, based on the collected airflow data and the centrifugal compressor outlet geometry, using the principles of gas dynamics, calculating the basic dimensions of the outlet diffuser, wherein the basic dimensions include the inlet diameter, the outlet diameter, and the channel height;

[0088] The inlet diameter D2 is calculated by the following formula:

[0089] D2=D exit_compressor ×f D

[0090] Among them, f D It represents the design coefficient, and its value is close to 1;

[0091] The outlet diameter D5 is calculated by the following formula:

[0092]

[0093] Among them, β2 and β5 represent the angles between the inlet and outlet airflow and the circumferential direction, respectively, and V2 and V5 represent the inlet and outlet airflow velocities, respectively.

[0094] The channel height H is consistent with the centrifugal compressor channel height.

[0095] S13. Analyze the relevant parameters of the connection structure between the diffuser and the volute, including the angle, curvature and sealing method of the connection, and clarify the design requirements of the asymmetric guide vanes, including the need to match the shape of the volute and reduce flow losses;

[0096] S14. According to the connection method between the diffuser and the volute and the airflow conditions, the number, distribution and basic shape of the asymmetric guide vanes are preliminarily set.

[0097] The working principle of the above technical solution is: through the sensor installed at the outlet of the centrifugal compressor, the key parameters of the airflow, including airflow velocity, pressure, temperature and airflow direction, are collected in real time. Based on the collected airflow data, the basic dimensions of the diffuser are calculated using the principles of gas dynamics. Including key parameters such as inlet diameter, outlet diameter, and channel height. During the calculation process, it is necessary to comprehensively consider the influence of parameters such as airflow velocity, pressure, and temperature on the performance of the diffuser to ensure that the diffuser can meet the outlet airflow conditions of the centrifugal compressor and achieve effective airflow deceleration and supercharging; the connection structure between the diffuser and the volute is analyzed in detail, including parameters such as the angle, curvature, and sealing method of the connection. At the same time, according to the shape of the volute and the airflow conditions, the design requirements of the asymmetric guide vanes are clarified, including the need to match the shape of the volute to reduce flow losses and improve the efficiency and stability of airflow through the diffuser; according to the connection method between the diffuser and the volute and the airflow conditions, the number, distribution, and basic shape of the asymmetric guide vanes are preliminarily set. At the same time, the basic shape of the asymmetric guide vanes also needs to be customized according to the shape of the volute and the airflow conditions to reduce flow losses and improve aerodynamic performance.

[0098] The effects of the above technical solution are as follows: the key parameters such as the airflow velocity, pressure, temperature and airflow direction at the outlet of the centrifugal compressor are collected in real time through high-precision sensors, ensuring the accuracy and timeliness of the data; the basic dimensions of the diffuser are calculated using the principles of gas dynamics, ensuring the scientificity and rationality of the diffuser design; through precise calculations, it can be ensured that the diffuser can meet the outlet airflow conditions of the centrifugal compressor and achieve effective deceleration and pressure increase of the airflow; the connection structure between the diffuser and the volute is analyzed in detail, including parameters such as the angle, curvature and sealing method of the connection, ensuring the stability and Reliability; Based on the shape of the volute and the airflow conditions, the design requirements of the asymmetric guide vanes are clarified, including matching the shape of the volute and reducing flow losses; Based on the connection method between the diffuser and the volute and the airflow conditions, the number, distribution and basic shape of the asymmetric guide vanes are preliminarily set; Through precise data collection and analysis, as well as calculations based on gas dynamics principles, problems can be discovered and optimized in the early stages of the design; The optimized diffuser and asymmetric guide vane design help to improve the efficiency and stability of the airflow through the diffuser; Through precise design and optimization, the diffuser can be ensured to operate stably under various operating conditions.

[0099] In one embodiment of the present invention, the S2 includes:

[0100] S21. Determine the number of blades according to the size and design requirements of the diffuser, and number the blades according to certain rules;

[0101] S22, preliminarily setting the position of the blade in the diffuser according to the geometric shape of the diffuser and the airflow conditions, wherein the position includes the leading edge and the trailing edge of the blade and the relative position between the blades;

[0102] S23. Based on the airflow conditions and blade outlet boundary requirements, a preliminary simulation is performed using computational fluid dynamics (CFD) software to analyze the effect of blade angle on airflow, and the blade angle is adjusted based on the analysis results.

[0103] S24. On the basis of adjusting the blade angle, the position of the blade in the diffuser is further optimized.

[0104] The working principle of the above technical solution is as follows: first determine the number of blades according to the size and design requirements of the diffuser. The selection of the number of blades needs to comprehensively consider the size of the diffuser, the airflow conditions and the expected diffusion efficiency. Too many blades may increase the flow resistance, while too few blades may not be able to effectively guide the airflow. After determining the number of blades, the blades are numbered according to certain rules, such as numbering them clockwise, so that each blade can be accurately identified and located; the position of the blades in the diffuser is preliminarily set according to the geometry and airflow conditions of the diffuser. Including the leading edge, trailing edge and relative position between the blades. The position of the blades needs to ensure that they can effectively guide the airflow while avoiding excessive flow resistance or vortex structure. The preliminary set position can be determined by empirical formula, analog design or preliminary simulation; based on the airflow conditions and the requirements of the blade outlet boundary, a preliminary simulation is performed using computational fluid dynamics (CFD) software. CFD software can simulate the flow of airflow in the diffuser, including the distribution of parameters such as velocity, pressure, and temperature. Through the simulation results, the influence of blade angle on airflow flow can be analyzed, including whether the airflow is smooth, whether there is a vortex structure, whether the flow loss is too large, etc. Based on the analysis results, the blade angle is adjusted to reduce flow losses and improve the efficiency of the diffuser. The blade angle can be adjusted by changing the inclination angle, torsion angle and other parameters of the blade; on the basis of adjusting the blade angle, the position of the blade in the diffuser is further optimized. This includes adjusting the leading edge and trailing edge positions of the blades and the relative positions between the blades. The purpose of the optimization is to ensure that the blades can better guide the airflow, reduce flow resistance, and improve the overall performance of the diffuser. The optimization process can be achieved through multiple simulations and iterations, and each iteration fine-tunes the blade position according to the simulation results until the best performance is achieved.

[0105] The effects of the above technical solution are as follows: according to the size and design requirements of the diffuser, the number of blades is accurately determined and numbered according to the rules, providing a clear and orderly basis for subsequent design and optimization work; the application of the numbering rules allows each blade to be accurately identified and located, avoiding confusion and errors in the design process; based on the geometric shape and airflow conditions of the diffuser, the blade position is preliminarily set to ensure the rationality and effectiveness of the blade layout; the preliminarily set position provides a starting point for subsequent optimization work, reducing the blindness and trial and error costs in the design process; using computational fluid dynamics (CFD) software for preliminary simulation, it is possible to accurately analyze the impact of blade angles on airflow; the simulation results provide detailed distribution information of airflow velocity, pressure, temperature and other parameters, It provides a scientific basis for adjusting the blade angle; based on the CFD simulation results, the blade angle is adjusted to reduce flow losses and improve diffusion efficiency; the adjusted blade angle can guide the airflow more effectively, reduce adverse factors such as vortices and turbulence, and improve the smoothness and stability of airflow; on the basis of adjusting the blade angle, the position of the blade in the diffuser is further optimized; the optimized blade position can better match the airflow conditions, ensure that the blade can better guide the airflow, reduce flow resistance, and improve the overall performance of the diffuser; by optimizing the number, position and angle of the blades, the energy consumption and cost of the diffuser during operation can be reduced; a more efficient diffuser can reduce energy waste, reduce operating costs, and at the same time improve the reliability and service life of the equipment.

[0106] In one embodiment of the present invention, the S23 includes:

[0107] S231, constructing a three-dimensional geometric model through CAD software according to the actual size, blade shape and initially set position of the diffuser, and importing the geometric model into CFD software to set boundary conditions;

[0108] S232, perform high-quality meshing on the constructed CFD model and verify mesh independence.

[0109] S233, performing CFD simulation to analyze key parameters of airflow passing through the diffuser, including velocity field, pressure field, and turbulence intensity; focusing on the influence of blade angle on airflow path, separation phenomenon, energy loss, and diffusion efficiency, and displaying the flow state of airflow between blades through visualization tools;

[0110] S234. Based on the preliminary simulation results, the main areas causing flow loss (such as airflow separation areas and high turbulence areas) are identified, and the parameters of the blades are adjusted one by one through sensitivity analysis. The parameters of the blades include the angle of attack and the installation angle.

[0111] S235, and, after each adjustment, a new round of CFD simulation is performed, and the blade angle is gradually optimized through multiple iterations until a predetermined performance improvement target is achieved; the improvement target includes significantly reducing the total pressure loss;

[0112] S236. During the optimization process, dynamic simulation is introduced to consider the influence of the unsteady effects of blade rotation or periodic changes on the airflow, so as to be closer to the actual application scenario. At the same time, for diffusers that may involve gas-liquid or gas-solid two-phase flow, it is also necessary to consider the influence of the presence of particles or droplets on the flow characteristics, and simulate through multiphase flow models to further refine the optimization strategy.

[0113] S237. After completing all iterative optimizations, conduct a comprehensive performance evaluation of the final diffuser design, including key indicators such as diffusion efficiency, flow stability, and pressure recovery capability. If necessary, verify the accuracy of the CFD simulation results through laboratory experiments or field tests, and make necessary fine-tuning based on the measured data.

[0114] The working principle of the above technical solution is: according to the actual size of the diffuser, the shape of the blades and the initially set position, an accurate three-dimensional geometric model is constructed using CAD software. This model is then imported into the CFD software for subsequent simulation analysis. In the CFD software, reasonable boundary conditions need to be set, including inlet airflow velocity, temperature, pressure distribution and outlet back pressure, etc. High-quality meshing of the constructed CFD model is the key to successful simulation. Special attention is paid to the blade surface and nearby areas, because the airflow flow in these areas is complex and requires higher calculation accuracy. Therefore, an encrypted grid strategy is adopted to improve the calculation accuracy of these areas. At the same time, grid independence verification is performed to ensure that the accuracy of the simulation results is not affected by the grid density. This is achieved by comparing the simulation results under different grid densities. When the result difference is within an acceptable range, the grid division can be considered reasonable; CFD simulation is performed to analyze the key parameters of the airflow passing through the diffuser. The key parameters include velocity field, pressure field and turbulence intensity, which can reflect the flow state and energy loss of the airflow in the diffuser. Focus on the influence of blade angle on airflow path, separation phenomenon, energy loss and diffusion efficiency. Through visualization tools such as streamlines, velocity cloud maps, and pressure cloud maps, the flow state of the airflow between the blades is intuitively displayed. Based on the preliminary simulation results, the main areas that cause flow losses, such as airflow separation areas and high turbulence areas, are identified. Through sensitivity analysis, the parameters of the blades, including the angle of attack and the installation angle, are adjusted one by one to improve the airflow and reduce energy loss. When adjusting the parameters, it is necessary to consider their impact on performance indicators such as diffusion efficiency and flow stability; after each adjustment of the blade parameters, a new round of CFD simulation is required to evaluate the optimization effect. Through multiple iterations, the blade angle is gradually optimized until the predetermined performance improvement target is achieved. During the iteration process, it is necessary to continuously compare the simulation results under different schemes to determine the optimal blade angle combination; during the optimization process, it is also necessary to consider the impact of the unsteady effects of blade rotation or periodic changes on the airflow. Therefore, dynamic simulation is introduced to be closer to the actual application scenario. For diffusers that may involve gas-liquid or gas-solid two-phase flow, it is also necessary to consider the impact of the presence of particles or droplets on the flow characteristics. Through simulation with multiphase flow model, the optimization strategy can be further refined and the accuracy of simulation results can be improved. After all iterative optimizations are completed, the final designed diffuser is comprehensively evaluated for performance. This includes key indicators such as diffusion efficiency, flow stability, and pressure recovery capability. If necessary, the accuracy of CFD simulation results is verified through laboratory experiments or field tests. Experimental data can provide strong support for fine-tuning design parameters to ensure that the performance of the diffuser in actual applications meets expectations.

[0115] The effects of the above technical solution are as follows: by constructing an accurate three-dimensional geometric model through CAD software, the actual size, blade shape and position of the diffuser can be truly reflected, providing an accurate basis for subsequent CFD simulation; high-quality meshing of the CFD model, especially the use of encrypted mesh strategies on the blade surface and nearby areas, can significantly improve the calculation accuracy and ensure the accuracy of the simulation results; mesh independence verification is performed to ensure that the accuracy of the simulation results is not affected by the mesh density, further improving the reliability of the design; through CFD simulation, key parameters such as the velocity field, pressure field and turbulence intensity of the airflow through the diffuser are analyzed, which can provide an in-depth understanding of the airflow flow state and provide a scientific basis for optimization; based on the preliminary simulation results, a sensitivity analysis of the blade angle is performed, and the blade parameters (such as angle of attack and installation angle) are adjusted one by one, which can significantly reduce flow losses and improve the diffusion efficiency; through multiple iterations , gradually optimize the blade angle until the predetermined performance improvement target is achieved (such as significantly reducing the total pressure loss) to ensure that the design effect meets expectations; introduce dynamic simulation to consider the impact of the unsteady effects of blade rotation or periodic changes on the airflow, which can be closer to the actual application scenario and improve the applicability of the design; for diffusers that may involve gas-liquid or gas-solid two-phase flow, simulation through a multiphase flow model can consider the impact of the presence of particles or droplets on the flow characteristics, further refine the optimization strategy, and improve the accuracy of the design; after completing all iterative optimizations, conduct a comprehensive performance evaluation of the final designed diffuser, including key indicators such as diffusion efficiency, flow stability, and pressure recovery capability, to ensure that the design meets actual needs; if necessary, verify the accuracy of the CFD simulation results through laboratory experiments or field tests, and make necessary fine-tuning based on the measured data to ensure the reliability and practicality of the design results.

[0116] In one embodiment of the present invention, S3 includes:

[0117] S31, calculating the geometric parameters of the blade according to the initially designed blade shape and position, wherein the geometric parameters include the trailing edge distance, the included angle, and the mid-arc coordinates;

[0118] S32. Based on the principles of computational fluid dynamics, an iterative calculation model is established to gradually optimize the geometric parameters of the blades; by continuously adjusting the geometric parameters, the influence of the blades on the airflow is simulated and analyzed, and the blade design is optimized based on the simulation analysis results;

[0119] S33, substituting the optimized blade geometric parameters into the iterative calculation model for verification, and judging whether the optimization results meet the design requirements. If not, continue to perform optimization iterations until the best design effect is achieved.

[0120] The working principle of the above technical solution is as follows: according to the preliminary designed blade shape and position, the geometric parameters of the blade need to be calculated first. The geometric parameters include but are not limited to the trailing edge distance, angle, and mid-arc coordinates. When calculating the parameters, it is necessary to ensure the accuracy and rationality of the parameter values ​​based on the design requirements and aerodynamic performance targets of the blade; an iterative calculation model is established based on the principle of computational fluid dynamics (CFD). The model can simulate the influence of the blade on the airflow and optimize the blade design based on the simulation analysis results. During the iterative calculation process, the geometric parameters of the blade (such as the trailing edge distance, angle, mid-arc coordinates, etc.) are continuously adjusted to observe and analyze the influence of these parameter changes on the airflow. Through multiple iterative calculations, the blade design is gradually optimized to achieve the best aerodynamic performance. Specifically, the iterative calculation model can simulate the flow of airflow on the blade surface, including key parameters such as velocity distribution, pressure distribution, and turbulence intensity. By analyzing the changes in these parameters, the advantages and disadvantages of the blade design can be evaluated and the subsequent optimization work can be guided. During the optimization process, factors such as the aerodynamic performance, structural strength, and manufacturing cost of the blade need to be comprehensively considered to ensure that the optimized blade design meets the performance requirements and is feasible. Substitute the optimized blade geometric parameters into the iterative calculation model for verification. The purpose of this step is to determine whether the optimization results meet the design requirements. If the aerodynamic performance of the optimized blade still does not meet the expected goals or there are other problems, it is necessary to continue the optimization iteration. By continuously adjusting the geometric parameters and repeating the iterative calculation process, the best design effect is achieved. During the verification process, it is necessary to pay attention to multiple performance indicators, such as diffusion efficiency, flow stability, pressure recovery capability, etc. These indicators can fully reflect the aerodynamic performance of the blade. At the same time, factors such as the reliability and durability of the blade in actual applications need to be considered to ensure that the design results meet the performance requirements and have good practicality and economy.

[0121] The effect of the above technical solution is: the geometric parameters of the blade shape and position of the preliminary design are calculated, including the trailing edge distance, angle, and mid-arc coordinates, etc., to ensure the accuracy of the blade design. Parameters are the basis of blade design and optimization, and accurate calculations provide reliable data support for subsequent optimization work; an iterative calculation model is established based on the principle of computational fluid dynamics to gradually optimize the geometric parameters of the blade. By continuously adjusting the geometric parameters and simulating and analyzing the influence of the blade on the airflow, the optimal blade design parameters can be found more accurately and the aerodynamic performance of the blade can be improved; through the iterative calculation model, the geometric parameters of the blade can be efficiently adjusted and simulated and analyzed. This iterative optimization method can quickly find the optimal solution, avoiding the time and cost waste caused by the traditional trial and error method; the optimized blade geometric parameters are substituted into the iterative calculation model for verification to determine whether the optimization results meet the design requirements. This verification method can ensure that the optimized blade design has good performance in practical applications; by optimizing the geometric parameters of the blade, the aerodynamic performance of the blade can be significantly improved, such as improving the diffusion efficiency and reducing the flow loss. Optimized blade design can enhance the stability of blades in airflow, reduce blade vibration and damage caused by airflow fluctuations or unstable factors, and improve the reliability and durability of the system; through iterative calculation and optimization verification, the blade design cycle can be significantly shortened, and the number of repeated modifications and tests in the design process can be reduced, thereby reducing design costs; optimized blade design can reduce material waste and processing difficulty, and reduce manufacturing costs. At the same time, the optimized blade shape and size are also more conducive to subsequent processing and assembly work.

[0122] In one embodiment of the present invention, the S32 includes:

[0123] S321. Based on the preliminary design of the blade, a mathematical model including blade geometry, airflow boundary conditions and physical properties is established using CFD software;

[0124] S322, based on preset optimization objectives, which include improving pressure diffusion efficiency, reducing total pressure loss, and optimizing airflow path, setting corresponding performance index thresholds according to design requirements as a reference benchmark for iterative optimization;

[0125] S323, inputting the preliminarily designed blade geometric parameters (such as trailing edge distance, angle, mid-arc coordinates, etc.) into the iterative calculation model as initial values;

[0126] S324. Automatically adjust blade geometry parameters during iterations using genetic algorithms. Use CFD software to simulate and analyze the adjusted blade geometry parameters in each iteration. Focus on the flow state of airflow on the blade surface, including separation, turbulence intensity, pressure distribution, etc., as well as the effects of these parameters on performance indicators such as diffusion efficiency and total pressure loss.

[0127] S325. In the iterative process, a prediction model between blade geometric parameters and performance indicators is established through a machine learning algorithm (such as a neural network, a random forest, etc.); and the model is continuously trained;

[0128] S326. Based on the simulation analysis results, determine whether the current geometric parameters meet the design requirements; if the performance indicators do not meet expectations, adjust the geometric parameters based on the sensitivity analysis results and the machine learning prediction model to enter the next round of iteration; repeat S324 to S326 until the performance indicators converge to the optimal solution or reach the preset upper limit of the number of iterations.

[0129] The working principle of the above technical solution is as follows: Based on the preliminary design of the blade, a mathematical model including blade geometry, airflow boundary conditions and physical properties is constructed using computational fluid dynamics (CFD) software. This model needs to be able to accurately describe the flow state of the airflow on the blade surface, including key parameters such as velocity, pressure, temperature and turbulence characteristics. Based on the preset optimization goals, such as improving the pressure diffusion efficiency, reducing the total pressure loss and optimizing the airflow path, the corresponding performance index thresholds are set according to the design requirements. These performance index thresholds will serve as a reference benchmark for iterative optimization to evaluate the pros and cons of the blade design after each iteration; the preliminary designed blade geometric parameters, such as trailing edge distance, angle, mid-arc coordinates, etc., are input into the iterative calculation model as initial values. The initial parameters will serve as the starting point of the optimization process, and the optimal solution will be gradually approached through subsequent iterative calculations; during the iteration process, the blade geometric parameters are automatically adjusted using a genetic algorithm. A genetic algorithm is an optimization algorithm based on natural selection and genetic mechanisms that can efficiently search for the optimal solution. In each iteration, the CFD software is used to simulate and analyze the adjusted blade geometric parameters, focusing on the flow state of the airflow on the blade surface, including separation phenomenon, turbulence intensity, pressure distribution, etc., as well as the impact of these parameters on performance indicators such as diffusion efficiency and total pressure loss; in the iteration process, a prediction model between blade geometric parameters and performance indicators is established through machine learning algorithms (such as neural networks, random forests, etc.). This prediction model can quickly predict performance indicators based on the current geometric parameters, thereby accelerating the optimization process. By continuously training the prediction model, its prediction accuracy is improved, so that it can predict performance indicators under different geometric parameter combinations more quickly and accurately during the iteration process; according to the simulation analysis results, it is judged whether the current geometric parameters meet the design requirements. If the performance indicators do not meet expectations, the geometric parameters are adjusted according to the sensitivity analysis results and the machine learning prediction model to enter the next round of iteration. Repeat steps S324 to S326 until the performance indicators converge to the optimal solution or reach the preset upper limit of the number of iterations. In the iteration process, by continuously adjusting and optimizing the geometric parameters, the optimal blade design is gradually approached.

[0130] The effects of the above technical solution are: by using CFD software to establish a mathematical model including blade geometry, airflow boundary conditions and physical properties, the flow state of airflow on the blade surface can be accurately described, including key parameters such as velocity, pressure, temperature and turbulence characteristics. This provides accurate basic data for subsequent iterative optimization; as a global optimization algorithm, the genetic algorithm can automatically adjust the geometric parameters of the blade during the iteration process without manual intervention, thereby improving the efficiency and accuracy of the optimization process; a prediction model between blade geometric parameters and performance indicators is established through a machine learning algorithm, and the model is continuously trained during the iteration process to improve the prediction accuracy. This enables faster and more accurate prediction of performance indicators under different geometric parameter combinations during the iteration process, thereby accelerating the optimization process; based on the preset optimization goals (such as improving the pressure diffusion efficiency, reducing the total pressure loss, and optimizing the airflow path, etc.), the corresponding performance indicator thresholds are set according to the design requirements. This makes the optimization process have clear goals and quantifiable evaluation criteria; in the iterative process, by continuously adjusting the geometric parameters and simulating and analyzing the changes in performance indicators until the performance indicators converge to the optimal solution or reach the preset upper limit of the number of iterations, the effectiveness and reliability of the optimization results are ensured; by optimizing the geometric parameters of the blades, the flow state of the airflow on the blade surface can be improved, such as reducing separation, reducing turbulence intensity, optimizing pressure distribution, etc., and improving the aerodynamic performance of the blades, such as improving the diffusion efficiency and reducing the total pressure loss; the optimized blade design can enhance the stability of the blades in the airflow, reduce the vibration and damage of the blades caused by airflow fluctuations or unstable factors, and improve the stability and reliability of the entire system; through an efficient iterative optimization process, the design cycle of the blades can be significantly shortened, the number of repeated modifications and tests in the design process can be reduced, and the design cost and time cost can be reduced; the optimized blade design can make more reasonable use of materials, reduce material waste and processing difficulty. This helps to reduce manufacturing costs and improve production efficiency.

[0131] In one embodiment of the present invention, the S4 includes:

[0132] S41. Select numerical simulation software according to the complexity of the diffuser and the computing resources, and perform flow field analysis based on the selected numerical simulation software;

[0133] S42, setting parameters of numerical simulation according to actual operating conditions and design requirements of the diffuser, wherein the numerical simulation parameters include inlet conditions, outlet conditions, boundary conditions, and solution algorithms;

[0134] S43, running numerical simulation software to perform flow field analysis on the optimized blades to obtain flow conditions of the airflow inside the diffuser, wherein the flow conditions include velocity distribution, pressure distribution, and vortex structure, etc.;

[0135] S44. Based on the numerical simulation results, evaluate the aerodynamic performance of the blades, analyze key indicators such as diffuser efficiency, and further optimize the design of the blades based on the evaluation results of the aerodynamic performance. Adjust the geometric parameters, shape or position of the blades; the loss of the diffuser is basically divided into two parts, namely friction loss and separation loss. Analogous to the diffuser, the efficiency η of the diffuser can be expressed by the following formula:

[0136]

[0137] Among them, V2 and V5 are the inlet and outlet velocities of the diffuser respectively.

[0138] The working principle of the above technical solution is: according to the complexity of the diffuser (such as the complexity of the geometric shape, the complexity of the flow characteristics, etc.) and the available computing resources (such as computing power, storage space, time limit, etc.), select the appropriate numerical simulation software. For example, suppose there is a diffuser with complex geometry and variable flow characteristics, and the computing resources are limited. In this case, ANSYS CFX or Fluent can be selected for simulation. Both software have the ability to handle complex geometries and flow characteristics, and provide a variety of optimization algorithms and parallel computing capabilities, which can reduce the demand for computing resources to a certain extent. At the same time, they both have powerful post-processing capabilities, which can easily analyze the simulation results and extract useful information. Ensure that the selected software can accurately simulate the flow conditions inside the diffuser; set the parameters of the numerical simulation according to the actual operating conditions of the diffuser (such as inlet flow velocity, pressure, temperature, etc.) and design requirements (such as expected diffusion efficiency, flow loss limitation, etc.); the parameters include inlet conditions, outlet conditions (such as outlet pressure, flow velocity, etc.), boundary conditions (such as wall conditions, boundaries of the flow area, etc.) and solution algorithms (such as numerical methods in computational fluid dynamics, such as finite volume method, finite difference method, etc.). The optimized blades are analyzed using numerical simulation software with set parameters. The simulation process calculates the flow of airflow inside the diffuser, including velocity distribution (i.e., the velocity and direction of the airflow at different locations), pressure distribution (i.e., the pressure value of the airflow at different locations), and vortex structure (such as the formation, development, and dissipation of vortices). Based on the numerical simulation results, the aerodynamic performance of the blades is evaluated. The key indicators of the blades’ pressure diffusion efficiency (i.e., the ratio of the pressure increase after the airflow passes through the blades to the input energy), flow losses (such as energy losses caused by friction, vortices, etc.), and stability (such as the adhesion of the airflow on the blades, whether separation occurs, etc.) are analyzed. Based on the evaluation results of aerodynamic performance, the blade design is further optimized. This may involve adjusting the blade’s geometric parameters (such as length, width, angle, etc.), shape (such as curvature, cross-sectional shape, etc.), or position (such as relative to the diffuser inlet or outlet).

[0139] The effect of the above technical solution is: by selecting appropriate numerical simulation software and performing flow field analysis based on the software, the flow conditions inside the diffuser can be accurately simulated. Including key flow characteristics such as velocity distribution, pressure distribution and vortex structure, it provides detailed data support for the design of the blade; based on the numerical simulation results, the efficiency of the diffuser can be accurately evaluated. It helps to find problems in the design and make targeted optimizations, thereby improving the design accuracy and efficiency of the blade; through numerical simulation, the design of the blade can be iterated and optimized multiple times in a virtual environment, thereby reducing the number of actual experiments, saving the cost of materials and equipment required for the experiment, shortening the R&D cycle, and improving the overall R&D efficiency; numerical simulation can predict and evaluate the performance of the blade in the design stage, so as to timely discover and solve potential problems, reduce the risk of failure caused by design defects, and improve the reliability and stability of the product; through numerical simulation and optimization, the aerodynamic performance of the blade can be significantly improved. This includes improving the efficiency of the diffuser, reducing flow losses and enhancing stability, thereby improving the performance of the entire diffuser; the optimized blade design can significantly improve the performance and quality of the product, thereby enhancing market competitiveness. This helps enterprises stand out in the fierce market competition and win more market share and customer trust; numerical simulation technology plays a vital role in the design and optimization of diffuser blades. With the continuous advancement of technology and the deepening of application, numerical simulation technology will continue to be improved and developed to provide support for technological innovation in more fields; the design and optimization of diffuser blades involves knowledge and technology of multiple disciplines, such as fluid mechanics, solid mechanics, computational mathematics, etc. Through the application of numerical simulation technology, it can promote the cross-integration and cooperation between these disciplines and jointly promote the development and innovation of related technologies. The above formula evaluates the pressure diffusion capacity of the blade by comparing the difference between the actual outlet pressure and the ideal outlet pressure; evaluates the energy loss of the blade during the flow process by calculating the total energy difference between the inlet and outlet; and evaluates whether the blade is stable during operation by measuring the degree of pressure fluctuation; the weight in the formula allows the importance of each indicator to be adjusted according to the needs of the specific application scenario, and a trade-off can be made between different design goals, such as pursuing high efficiency while taking into account the stability of the system; by quantifying multiple performance indicators, the evaluation results are more objective and comparable. This helps engineers quickly identify the advantages and disadvantages of the design and make targeted improvements; through specific numerical results, they can more intuitively understand how the design parameters affect the performance of the blade, thereby guiding subsequent design optimization. For example, if the flow loss is found to be too large, the geometric parameters, shape or position of the blade can be adjusted; unified evaluation criteria make it easier to compare different design schemes.This helps to select the best design from multiple alternatives; the formula not only takes into account the ideal state in theory, but also combines the performance data under actual operating conditions, making the evaluation results closer to practical applications; by providing a unified evaluation framework, it can help professionals from different backgrounds (such as mechanical engineers, fluid mechanics experts, etc.) to better collaborate and jointly optimize the design. By using the above formula for evaluation, it can effectively help designers make more scientific and reasonable decisions when optimizing blade performance. It can not only improve the efficiency of the diffuser, but also reduce flow losses and enhance the stability of the system, thereby improving the performance and reliability of the overall equipment. This is of great significance to improving the working efficiency and extending the service life of industrial equipment.

[0140] In one embodiment of the present invention, S5 includes:

[0141] S51. Develop detailed manufacturing drawings based on the final optimized blade design. The drawings should include information such as the blade's geometric size, shape, material, and manufacturing process. The manufacturing process is determined based on the blade's material and shape characteristics. The manufacturing process includes casting, forging, machining, or 3D printing.

[0142] S52. Manufacture blades according to manufacturing drawings and process requirements, perform performance tests on the manufactured blades, and verify the design effects of the blades and evaluate performance stability based on the test data.

[0143] The working principle of the above technical solution is as follows: According to the final optimized blade design, engineers will prepare detailed manufacturing drawings. These drawings are the basis for blade manufacturing, and contain key information such as the blade's geometric size, shape, material and manufacturing process; after the drawings are completed, engineers will determine the most suitable manufacturing process based on the material and shape characteristics of the blade. Manufacturing processes may include casting, forging, machining or 3D printing. The choice of these processes depends on factors such as the complexity of the blade, material properties, production efficiency and cost; according to the manufacturing drawings and process requirements, the manufacturing team will start manufacturing the blade. During the manufacturing process, the material quality, processing accuracy and process parameters will be strictly controlled to ensure that the quality of the blade meets the design requirements; after the blade is manufactured, performance testing will be carried out. Performance testing is a key step in verifying the effect of the blade design, including measuring the aerodynamic performance, mechanical properties and stability of the blade. The test data will be used to evaluate whether the performance of the blade meets expectations and to check whether there are any design or manufacturing defects.

[0144] The effect of the above technical solution is: according to the final optimized blade design, detailed manufacturing drawings are formulated to ensure the accuracy and consistency of the manufacturing process. The drawings contain key information such as the geometric size, shape, material and manufacturing process of the blade, providing clear work guidance and basis for the manufacturing team; according to the material and shape characteristics of the blade, the most suitable manufacturing process (such as casting, forging, machining or 3D printing) is determined. This customized manufacturing process selection can maximize the performance of the material while ensuring the shape and dimensional accuracy of the blade and improving the overall quality of the blade; performance testing of the manufactured blade is a key step in verifying the design effect of the blade. Through testing, you can intuitively understand the performance of the blade in the actual working environment, including key indicators such as aerodynamic performance, mechanical strength, and durability; based on the test data, the performance stability of the blade is evaluated. This helps to discover potential design or manufacturing defects, make timely adjustments and optimizations, and ensure the stability and reliability of the blade in long-term operation; through performance testing, it can be verified whether the design effect of the blade meets expectations. This helps to identify problems and optimize them in the design stage, avoiding unnecessary waste and losses in the subsequent manufacturing and use process; detailed manufacturing drawings and clear manufacturing processes help optimize the production process and reduce waste and loss in the production process. At the same time, choosing the right manufacturing process can also reduce manufacturing costs and improve production efficiency; through accurate manufacturing drawings and efficient manufacturing processes, the blade R&D and manufacturing cycle can be shortened, and the product launch speed can be accelerated. This is of great significance for seizing market opportunities and improving market competitiveness; high-quality blade products can enhance the brand image and reputation of the company. Through performance testing and stability evaluation, it can be ensured that the blade products perform well in actual applications and win the trust and praise of customers.

[0145] One embodiment of the present invention is a non-transitory computer-readable storage medium having a computer program stored thereon, the program being executed by a processor to implement a method for designing an asymmetric guide vane diffuser for a centrifugal compressor as described in any one of the above.

[0146] One embodiment of the present invention is a computer program product, comprising a computer program / instruction, which, when executed by a processor, implements a method for designing an asymmetric guide vane diffuser for a centrifugal compressor as described in any one of the above.

[0147] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A design method for an asymmetric guide vane diffuser for a centrifugal compressor, characterized in that: The method comprises: S1. Determine the basic size and shape of the diffuser based on the outlet airflow conditions of the centrifugal compressor; determine the design requirements of the asymmetric guide vanes based on the connection method between the diffuser and the volute; S2. According to the number of blades, determine the number and initial position of the blades, and adjust the angle and position of the blades according to the airflow conditions and the blade outlet boundary requirements; S3. Based on the preliminary design, calculate the geometric parameters of the blade, wherein the geometric parameters include the trailing edge distance, the included angle, and the coordinates of the mid-arc line; and gradually optimize the geometric parameters by an iterative calculation method; S4. Perform flow field analysis on the optimized blades through numerical simulation software, evaluate the aerodynamic performance of the blades according to the numerical simulation results, and further optimize the design based on the evaluation results; S5. Based on the final optimization results, develop detailed blade manufacturing drawings and processes, and manufacture and test the blades.

2. The method for designing an asymmetric guide vane diffuser for a centrifugal compressor according to claim 1, characterized in that: Said S1 comprises: S11, collecting key parameters of the centrifugal compressor outlet through a sensor, wherein the key parameters include air flow velocity and air flow direction; S12. Based on the collected airflow data and using the principles of gas dynamics, calculate the basic dimensions of the diffuser, wherein the basic dimensions include an inlet diameter, an outlet diameter, and a channel height; S13. Analyze the relevant parameters of the connection structure between the diffuser and the volute, including the angle, curvature and sealing method of the connection, and clarify the design requirements of the asymmetric guide vanes, including the need to match the shape of the volute and reduce flow losses; S14. According to the connection method between the diffuser and the volute and the airflow conditions, the number, distribution and basic shape of the asymmetric guide vanes are preliminarily set.

3. The method for designing an asymmetric guide vane diffuser for a centrifugal compressor according to claim 1, characterized in that: The S2 comprises: S21. Determine the number of blades according to the size and design requirements of the diffuser, and number the blades; S22, preliminarily setting the position of the blade in the diffuser according to the geometric shape of the diffuser and the airflow conditions, wherein the position includes the leading edge and the trailing edge of the blade and the relative position between the blades; S23. Based on the airflow conditions and the blade outlet boundary requirements, a preliminary simulation is performed using computational fluid dynamics software to analyze the effect of the blade angle on the airflow, and the blade angle is adjusted based on the analysis results; S24. On the basis of adjusting the blade angle, the position of the blade in the diffuser is further optimized.

4. The method for designing an asymmetric guide vane diffuser for a centrifugal compressor according to claim 3, characterized in that: The S23 comprises: S231, constructing a three-dimensional geometric model through CAD software according to the actual size, blade shape and initially set position of the diffuser, and importing the geometric model into CFD software to set boundary conditions; S232, meshing the constructed CFD model and verifying mesh independence; S233, performing CFD simulation to analyze key parameters of the airflow passing through the diffuser, wherein the key parameters include the velocity field; and displaying the flow state of the airflow between the blades through a visualization tool; S234. Based on the preliminary simulation results, the main areas causing flow losses are identified, and the parameters of the blades are adjusted one by one through sensitivity analysis; S235, and, after each adjustment, a new round of CFD simulation is performed, and the blade angle is gradually optimized through multiple iterations until the predetermined performance improvement target is achieved; S236. During the optimization process, dynamic simulation is introduced to consider the influence of the unsteady effect of blade rotation or periodic changes on the airflow; S237. After completing all iterative optimizations, conduct a comprehensive performance evaluation of the final diffuser design, verify the accuracy of the CFD simulation results, and make necessary fine-tuning based on the measured data.

5. The method for designing an asymmetric guide vane diffuser for a centrifugal compressor according to claim 1, characterized in that: The S3 includes: S31, calculating the geometric parameters of the blade according to the initially designed blade shape and position, wherein the geometric parameters include the trailing edge distance, the included angle, and the mid-arc coordinates; S32. Based on the principles of computational fluid dynamics, an iterative calculation model is established to gradually optimize the geometric parameters of the blades; by continuously adjusting the geometric parameters, the influence of the blades on the airflow is simulated and analyzed, and the blade design is optimized based on the simulation analysis results; S33, substituting the optimized blade geometric parameters into the iterative calculation model for verification, and judging whether the optimization results meet the design requirements. If not, continue to perform optimization iterations.

6. The method for designing an asymmetric guide vane diffuser for a centrifugal compressor according to claim 5, characterized in that: The S32 includes: S321. Based on the preliminary design of the blade, a mathematical model including blade geometry, airflow boundary conditions and physical properties is established using CFD software; S322. Based on the preset optimization goal and design requirements, set corresponding performance indicator thresholds as reference benchmarks for iterative optimization; S323, inputting the preliminarily designed blade geometric parameters as initial values ​​into the iterative calculation model; S324, automatically adjusting the blade geometric parameters in the iteration process by using a genetic algorithm; in each iteration, using CFD software to simulate and analyze the adjusted blade geometric parameters; S325. In the iterative process, a prediction model between blade geometric parameters and performance indicators is established through a machine learning algorithm; and the model is continuously trained; S326. Based on the simulation analysis results, determine whether the current geometric parameters meet the design requirements; if the performance indicators do not meet expectations, adjust the geometric parameters based on the sensitivity analysis results and the machine learning prediction model to enter the next round of iteration; repeat S324 to S326 until the performance indicators converge to the optimal solution or reach the preset upper limit of the number of iterations.

7. The method for designing an asymmetric guide vane diffuser for a centrifugal compressor according to claim 1, characterized in that: The S4 comprises: S41. Select numerical simulation software according to the complexity of the diffuser and the computing resources, and perform flow field analysis based on the selected numerical simulation software; S42, setting parameters of numerical simulation according to actual operating conditions and design requirements of the diffuser, wherein the numerical simulation parameters include inlet conditions, outlet conditions, boundary conditions, and solution algorithms; S43, running numerical simulation software to perform flow field analysis on the optimized blades to obtain flow conditions of the airflow inside the diffuser, wherein the flow conditions include velocity distribution, etc.; S44. Evaluate the aerodynamic performance of the blade based on the numerical simulation results, and further optimize the design of the blade based on the evaluation results of the aerodynamic performance.

8. The method for designing an asymmetric guide vane diffuser for a centrifugal compressor according to claim 1, characterized in that: The S5 comprises: S51. Develop detailed manufacturing drawings based on the final optimized blade design, and determine the manufacturing process based on the material and shape characteristics of the blade, where the manufacturing process includes casting, forging, machining or 3D printing; S52. Manufacture blades according to manufacturing drawings and process requirements, perform performance tests on the manufactured blades, and verify the design effects of the blades and evaluate performance stability based on the test data.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement a method for designing an asymmetric guide vane diffuser for a centrifugal compressor as described in any one of claims 1-8.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instruction is executed by a processor, a method for designing an asymmetric guide vane diffuser for a centrifugal compressor as described in any one of claims 1-8 is implemented.

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