Turbine blade lower margin plate optimization design method and system, turbine stator and lower margin plate

Abstract

The invention discloses a turbine blade lower margin plate optimization design method and system, a turbine stator and a lower margin plate. The optimization design method comprises the following steps: S1, carrying out simulation calculation on a model flow field to obtain sealing performance expression parameters; s2, the design range of the axial protruding length of the exhaust edge of the lower margin plate relative to the tail edge of the turbine blade is set, and the design range of the fillet radius of the exhaust edge of the lower margin plate is obtained; s3, a test design method is used, the axial protruding length and the fillet radius serve as optimization variables, the sealing performance expression parameters serve as optimization targets, and multiple sets of axial protruding length-fillet radius data are obtained within the axial protruding length design range and the fillet radius design range; s4, obtaining a plurality of groups of sealing performance expression parameters corresponding to the plurality of groups of axial protruding length-fillet radius data; s5, according to the multiple sets of sealing performance expression parameters, the regression relation between the sealing performance expression parameters and the fillet radius and the axial protruding length is obtained; s6, according to the regression relation, the optimal solutions of the fillet radius and the axial protruding length are obtained.

Description

Technical Field

[0001] This invention relates to gas turbine design, specifically to a method for optimizing the design of the lower edge plate of a turbine blade, a system for optimizing the design of the lower edge plate of a turbine blade, a lower edge plate of a turbine stator, and a turbine stator. Background Technology

[0002] Gas turbines are widely used in national economic sectors such as energy, power, aerospace, and national defense. Turbines are evolving towards higher parameters, higher performance, and higher reliability. The continuously increasing turbine inlet temperature leads to interstage seal leakage, gas backflow, increased disk temperature, turbine disk overheating, and reduced turbine disk lifespan. To improve sealing performance and prevent gas backflow, increasing the amount of cooling gas in the interstage seals increases mainstream energy loss and reduces turbine efficiency. Using a grate-tooth seal structure increases the risk of rubbing. Summary of the Invention

[0003] The purpose of this invention is to provide a method and system for optimizing the design of the lower edge plate of a turbine blade, as well as a turbine stator and a lower edge plate, for improving interstage sealing performance.

[0004] In a first aspect, the present invention provides an optimization design method for the lower edge plate of a turbine blade. According to an embodiment of the present invention, the optimization design method includes steps S1, S2, S3, S4, S5, and S6; Step S1: Perform flow field simulation calculations on a model of the lower edge plate with turbine blades to obtain sealing performance parameters; Step S2: For the model, set the exhaust edge of the lower edge plate to axially protrude beyond the trailing edge of the turbine blade and obtain the design range of the axial protrusion length, and set a fillet on the exhaust edge of the lower edge plate and obtain the design range of the fillet radius; Step S3: Using a design of experiments method, set the axial protrusion length and the fillet radius as optimization variables, and set the sealing performance parameters of step S1 as the optimization target. In step S2, multiple sets of axial extension length-corner radius data are obtained within the design range of the axial extension length and the design range of the fillet radius. Step S4: Flow field simulation calculations are performed on the model with the multiple sets of axial extension length-corner radius data set in step S3 to obtain multiple sets of sealing performance parameters corresponding to the multiple sets of axial extension length-corner radius data. Step S5: Based on the multiple sets of sealing performance parameters corresponding to the multiple sets of axial extension length-corner radius data in step S4, the regression relationship between the sealing performance parameters and the fillet radius and the axial extension length is obtained. Step S6: Based on the regression relationship, the optimal solution for the fillet radius and the axial extension length is obtained.

[0005] In one or more embodiments, the sealing performance parameters of step S1 include gas backflow rate, disk temperature, and turbine stage efficiency.

[0006] In one or more embodiments, the model of step S1 further includes a turbine disk.

[0007] In one or more embodiments, step S1 further includes generating a mesh for the model, wherein the model located on the lower side of one-third or one-half of the leaf height generates an unstructured mesh.

[0008] In one or more embodiments, step S1 further includes setting the mesh density of the unstructured mesh to 0.001 and setting the minimum mesh quality of the unstructured mesh to be greater than 0.1.

[0009] In one or more embodiments, step S2 further includes setting the axial protrusion length design range to 0 mm to 2 mm and setting the fillet radius design range to 0.5 mm to 3 mm.

[0010] In one or more embodiments, step S3 further includes obtaining five sets of axial protrusion length-corner radius data using a Latin hypercube optimization algorithm.

[0011] Secondly, the present invention provides a turbine blade lower edge plate optimization design system. According to an embodiment of the present invention, the optimization design system is used to perform the above-described turbine blade lower edge plate optimization design method.

[0012] Thirdly, the present invention provides a turbine stator lower edge plate. According to an embodiment of the present invention, the exhaust edge of the lower edge plate is configured to extend axially out of the trailing edge of the turbine stator, and the length of the axial extension is 1.5 mm. The lower edge plate is provided with a rounded corner on the exhaust edge, and the radius of the rounded corner is 0.5 mm.

[0013] Fourthly, the present invention provides a turbine stator. According to an embodiment of the present invention, the turbine stator includes a turbine stator blade and a lower edge plate. The exhaust edge of the lower edge plate extends axially from the trailing edge of the turbine stator blade, and the length of the axial extension is 1.5 mm. The lower edge plate is provided with a rounded corner on the exhaust edge, and the radius of the rounded corner is 0.5 mm.

[0014] The embodiments of the present invention possess at least one of the following beneficial effects:

[0015] By setting the exhaust edge of the lower edge plate to extend axially beyond the trailing edge of the turbine blade, the barrier between the mainstream area and the disk cavity is increased. By optimizing the length of the axial extension of the exhaust edge of the lower edge plate relative to the trailing edge of the turbine blade and the radius of the radius of the exhaust edge, the pressure difference between the mainstream area and the disk cavity can be reduced, thereby improving the interstage sealing performance, reducing or even avoiding backflow of combustion gas, lowering the disk cavity temperature, and improving turbine stage efficiency. Attached Figure Description

[0016] The above and other features, properties and advantages of the present invention will become more apparent from the following description taken in conjunction with the accompanying drawings and embodiments, wherein:

[0017] Figure 1 A flowchart illustrating the optimization design method for the lower edge plate of a turbine blade;

[0018] Figure 2 This is a schematic diagram of the model;

[0019] Figure 3 This is a magnified view of the exhaust edge of the lower edge plate of the model;

[0020] Figure 4 A schematic diagram of the main and secondary flow fields of the optimized lower edge plate;

[0021] Figure 5 A schematic diagram of the main and secondary flow fields for optimizing the front lower edge plate.

[0022] Figure label:

[0023] 1- Turbine blade;

[0024] 2-Lower edge plate;

[0025] 3-model;

[0026] 4- Turbine disk;

[0027] 5-Disc cavity;

[0028] 6-Upper edge plate;

[0029] 7-Exhaust edge of the lower edge plate;

[0030] 8-Trail edge of turbine blade;

[0031] 9. Rounded corners. Detailed Implementation

[0032] The present invention will be further described below with reference to specific embodiments and accompanying drawings. More details are set forth in the following description in order to provide a full understanding of the present invention. However, the present invention can obviously be implemented in many other ways different from those described herein. Those skilled in the art can make similar extensions and derivations based on actual application situations without departing from the spirit of the present invention. Therefore, the scope of protection of the present invention should not be limited by the content of this specific embodiment.

[0033] It should be noted that these and other accompanying drawings are merely examples and are not drawn to scale, and should not be construed as limiting the scope of protection of the present invention.

[0034] like Figure 1As shown, the optimization design method for the lower edge plate of a turbine blade includes step S1. Performing flow field simulation calculations on model 3 of the lower edge plate 2 with turbine blade 1 to obtain sealing performance parameters. NX software can be used to create a model based on the actual structure, such as... Figure 2 Model 1 is shown. (As shown in the image) Figure 2 As shown, in addition to the lower edge plate 2 and turbine blade 1, model 3 may also include a turbine disk 4 to improve the realism of the flow field in the disk cavity 5. Figure 2 As shown, Model 3 may also include an upper edge plate 6 to improve the realism of the flow field in the mainstream region.

[0035] Step S1 may further include generating the mesh for Model 3, establishing the Computational Fluid Dynamics (CFD) mesh for Model 3. Specifically, the lower part of Model 3 located at one-third or one-half of the blade height can be generated as an unstructured mesh to simplify calculations and improve computational efficiency. The blade body, lower edge plate 2, and turbine disk 4 located at one-third or one-half of the turbine blade 1 height can be generated as unstructured meshes using ICEMCFD software. Step S1 may further include setting the mesh density of the unstructured mesh to 0.001 and setting the minimum mesh quality of the unstructured mesh to be greater than 0.1 to ensure computational convergence. Other main domain regions can be generated as structured meshes using AutoGrid software.

[0036] Step S1 may also include using CFX software to set the boundaries of the aforementioned mesh and perform full three-dimensional viscous flow field simulation calculations. Based on the simulation results, the velocity, pressure, flow direction, and temperature distribution of the gas can be obtained, along with a flow field distribution cloud map, further yielding sealing performance parameters. These sealing performance parameters are variables reflecting interstage sealing performance. The sealing performance parameters in Step S1 may include gas backflow rate, disk temperature, and turbine stage efficiency; these parameters can fully reflect interstage sealing performance. The gas backflow rate is the flow rate of the gas flowing into disk 5. The gas in disk 5 mainly originates from the mainstream gas and the disk sealing cold gas. The flow rate flowing into disk 5 is obtained by statistically analyzing the physical flow through the surface established in model 3. The gas backflow rate is obtained by subtracting the set disk sealing cold gas flow rate from the flow rate flowing into disk 5. The disk temperature is the temperature of disk 5, which can be taken as the static temperature at a fixed location within disk 5 and can be directly obtained through flow field simulation calculations. The turbine stage efficiency can be obtained by... The formula is derived from this, where LPT Shaft Power is the turbine stage shaft power, which can be directly obtained from flow field simulation calculations; W is the physical flow rate at the turbine blade outlet, which can also be directly obtained from flow field simulation calculations; and T... tThe total temperature at the turbine blade outlet is denoted as LPT, which can be directly obtained from flow field simulation calculations. The pressure ratio at the turbine stage is denoted as LPT, which can be further calculated from flow field simulation calculations. The specific heat ratio at the turbine blade outlet is denoted as k, which can be further calculated from flow field simulation calculations.

[0037] like Figure 1 As shown, the turbine blade lower edge plate optimization design method also includes step S2. For model 3, the exhaust edge 7 of the lower edge plate 2 is set to axially protrude from the trailing edge 8 of the turbine blade 1, and the axial protrusion length design range is obtained. A fillet 9 is set on the exhaust edge 7 of the lower edge plate 2, and the fillet radius design range is obtained. The exhaust edge 7 of the lower edge plate 2 is often ignored when improving interstage sealing performance. Setting the exhaust edge 7 of the lower edge plate 2 to axially protrude from the trailing edge 8 of the turbine blade 1 increases the barrier between the mainstream area and the disk cavity 5. By optimizing the axial protrusion length of the exhaust edge 7 of the lower edge plate 2 relative to the trailing edge 8 of the turbine blade 1 and the radius of the fillet 9 of the exhaust edge 7, the pressure difference between the mainstream area and the disk cavity 5 can be reduced, thereby improving the interstage sealing performance, reducing or even avoiding gas backflow, lowering the disk cavity temperature, and improving turbine stage efficiency. Furthermore, modifying the axial extension length of the exhaust edge 7 and the radius of the fillet 9 of the exhaust edge 7 on the lower edge plate 2 will not result in structural changes to the turbine blade 1. Structural modifications to the lower edge plate 2 are also simple, requiring only the extension of the exhaust edge 7 and modification of the grinding of the fillet 9, without increasing process difficulty or manufacturing costs. Moreover, it does not affect the use of other interstage sealing measures. The axial extension length of the exhaust edge 7 relative to the trailing edge 8 is... Figure 3 As shown in Figure 'a', the radius of the fillet 9 of the exhaust edge 7 is... Figure 3 The figure is shown as b. The axial extension length design range defines the range of values ​​for the axial extension length of the exhaust edge 7 relative to the trailing edge 8, and the fillet radius design range defines the range of values ​​for the radius of the fillet 9 of the exhaust edge 7. The axial extension length design range and the fillet radius design range can be determined based on factors such as structural strength, dimensional interference, and manufacturing process. In the embodiment where the turbine blade 1 is a stator blade, step S2 may further include setting the axial extension length design range to 0 mm to 2 mm, setting the fillet radius design range to 0.5 mm to 3 mm, the axial extension length of the exhaust edge 7 relative to the trailing edge 8 being greater than 0 mm and less than or equal to 2 mm, and the radius of the fillet 9 of the exhaust edge 7 being greater than or equal to 0.5 mm and less than or equal to 3 mm, to ensure the structural strength of the lower edge plate 2 and to avoid interference between the lower edge plate 2 and other structures.

[0038] like Figure 1As shown, the turbine blade lower edge plate optimization design method also includes step S3. Using the experimental design method, the axial extension length a and the fillet radius b are set as optimization variables, and the sealing performance parameters of step S1 are set as optimization targets. Multiple sets of axial extension length-fillet radius data are obtained within the design range of axial extension length and fillet radius in step S2. The Design of Experiment (DOE) method establishes an optimization matrix for the axial extension length *a* and the fillet radius *b* within the design range of the axial extension length and fillet radius in step S2. A surrogate model can be built in the ISight software, using the axial extension length *a* and fillet radius *b* as optimization variables and the sealing performance parameters from step S1 as optimization objectives. Multiple sets of axial extension length-fillet radius data are obtained, each set consisting of one axial extension length *a* and one fillet radius *b*. The DOE method ensures that the axial extension length *a* and fillet radius *b* traverse all results within the design range of the axial extension length and fillet radius, guaranteeing that the optimization results are within the interpolation results of the multiple sets of axial extension length-fillet radius data obtained in step S3, and avoiding extrapolation results with large errors. Step S3 may also include using the Latin hypercube optimization algorithm during optimization to obtain five sets of axial extension length-fillet radius data to improve fitting accuracy.

[0039] like Figure 1 As shown, the turbine blade lower edge plate optimization design method also includes step S4. Flow field simulation calculations are performed on model 3, which has multiple sets of axial extension length-corner radius data set in step S3, to obtain multiple sets of sealing performance parameters corresponding to these multiple sets of axial extension length-corner radius data. Model 3 is updated using each set of axial extension length-corner radius data obtained in step S3, and as described in step S1 above, the sealing performance parameters corresponding to each set of axial extension length-corner radius data are obtained, thereby obtaining multiple sets of sealing performance parameters corresponding to multiple sets of axial extension length-corner radius data.

[0040] like Figure 1 As shown, the turbine blade lower edge plate optimization design method also includes step S5. Based on the multiple sets of sealing performance parameters corresponding to the multiple sets of axial extension length-corner radius data in step S4, the regression relationship between the sealing performance parameters and the corner radius b and axial extension length a is obtained. The relationship between the sealing performance parameters and the changes in corner radius b and axial extension length a is obtained.

[0041] like Figure 1As shown, the turbine blade lower edge plate optimization design method further includes step S6. Based on the regression relationship, the optimal solutions for the fillet radius b and axial extension length a are obtained. In the aforementioned embodiment where the turbine blade 1 is a stator blade, the design range of the axial extension length is 0 mm to 2 mm, the design range of the fillet radius is 0.5 mm to 3 mm, the optimal value of the axial extension length a is obtained as 1.5 mm, and the optimal value of the fillet radius b is obtained as 0.5 mm. Figure 4 The flow fields of the main flow and secondary flow obtained by flow field simulation calculation of Model 3 are shown. Figure 5 The diagram shows the main and secondary flow fields obtained from flow field simulation calculations for Model 3 before optimization, i.e., the main and secondary flow fields obtained during step S1. Before optimization, the axial protrusion length *a* of Model 3 was 0, meaning the exhaust edge 7 and the trailing edge 8 were located in the same axial position. The fillet radius *b* of Model 3 before optimization was 2 mm. (Comparison) Figure 4 and Figure 5 After optimization, the mixing range of the mainstream and the sealing cold air in the disk cavity is significantly reduced, and the energy loss of the mainstream at the connection between turbine blade 1 and lower edge plate 2 is reduced. Furthermore, flow field simulation calculations were performed on model 3 with an axial extension length a of 1.5 mm and a corner radius b of 0.5 mm to obtain the gas backflow rate, disk cavity temperature, and turbine stage efficiency. Flow field simulation calculations were also performed on model 3 with an axial extension length a of 0 mm and a corner radius b of 2 mm to obtain the gas backflow rate, disk cavity temperature, and turbine stage efficiency, as shown in Table 1. Referring to Table 1, after optimization, the gas backflow rate is eliminated, the disk cavity temperature decreases by 19.2 K, and the turbine stage efficiency increases by 0.5%.

[0042] Table 1

[0043] Gas backflow flow Disk cavity temperature Turbine-stage efficiency a = 0, b = 2mm 0.007kg / s 751.0K 90.42％ a = 1.5 mm, b = 0.5 mm -0.001kg / s 731.8K 90.92％

[0044] A turbine blade lower edge plate optimization design system is provided. The design system executes the above-mentioned turbine blade lower edge plate optimization design method to obtain the optimal values ​​of fillet radius b and axial extension length a, thereby improving the interstage sealing performance, reducing or even avoiding gas backflow, lowering the disk cavity temperature, and improving turbine stage efficiency.

[0045] like Figure 2 and Figure 3 As shown, a turbine stator includes a turbine stator vane 1 and a lower edge plate 2. The exhaust edge 7 of the lower edge plate 2 extends axially from the trailing edge 8 of the turbine stator vane 1, and the axial extension length a of the exhaust edge 7 relative to the trailing edge 8 is 1.5 mm. The lower edge plate 2 is provided with a fillet 9 on the exhaust edge 7, and the fillet radius b of the fillet 9 is 0.5 mm. This can reduce the pressure difference between the mainstream area and the disk cavity 5, thereby improving the interstage sealing performance, reducing or even avoiding gas backflow, lowering the disk cavity temperature, and improving turbine stage efficiency.

[0046] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0047] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0048] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0049] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0050] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for optimizing the design of the lower edge plate of a turbine blade, characterized in that... include: Step S1. Perform flow field simulation calculations on the model of the lower edge plate with turbine blades to obtain sealing performance parameters; Step S2. For the model, set the exhaust edge of the lower edge plate to extend axially to the trailing edge of the turbine blade and obtain the design range of the axial extension length, and set a fillet on the exhaust edge of the lower edge plate and obtain the design range of the fillet radius. Step S3. Using experimental design methods, set the axial protrusion length and the fillet radius as optimization variables, set the sealing performance parameters of step S1 as optimization targets, and obtain multiple sets of axial protrusion length-fillet radius data within the design range of the axial protrusion length and the design range of the fillet radius in step S2; Step S4. Perform flow field simulation calculations on the model with the multiple sets of axial protrusion length-corner radius data set in step S3 to obtain multiple sets of sealing performance parameters corresponding to the multiple sets of axial protrusion length-corner radius data; Step S5. Based on the multiple sets of sealing performance parameters corresponding to the multiple sets of axial protrusion length-corner radius data in step S4, obtain the regression relationship between the sealing performance parameters and the corner radius and the axial protrusion length; as well as Step S6. Obtain the optimal solution for the fillet radius and the axial extension length based on the regression relationship.

2. The optimization design method according to claim 1, characterized in that: The sealing performance parameters in step S1 include gas backflow rate, disk temperature, and turbine stage efficiency.

3. The optimization design method according to claim 1, characterized in that: The model in step S1 also includes a turbine disk.

4. The optimization design method according to claim 1, characterized in that... Step S1 further includes: A mesh is generated for the model, wherein the model located on the lower side of one-third or one-half of the leaf height generates an unstructured mesh.

5. The optimization design method according to claim 4, characterized in that... Step S1 further includes: The unstructured mesh is set to a mesh density of 0.001, and the minimum mesh quality of the unstructured mesh is set to be greater than 0.

1.

6. The optimization design method according to claim 1, characterized in that... Step S2 further includes: The axial extension length is set to a design range of 0 mm to 2 mm, and the fillet radius is set to a design range of 0.5 mm to 3 mm.

7. The optimization design method according to claim 1, characterized in that... Step S3 further includes: Five sets of data on the axial protrusion length minus the fillet radius were obtained using the Latin hypercube optimization algorithm.

8. A turbine blade lower edge plate optimization design system, characterized in that... Used to perform the turbine blade lower edge plate optimization design method as described in any one of claims 1 to 7.

9. A turbine stator blade lower edge plate, characterized in that: The exhaust edge of the lower edge plate is configured to extend axially beyond the trailing edge of the turbine stator blade, and the length of the axial extension is 1.5 mm. The lower edge plate has a rounded corner on the exhaust edge, and the radius of the rounded corner is 0.5 mm.

10. A turbine stator, comprising turbine stator blades and a lower edge plate, characterized in that: The exhaust edge of the lower edge plate extends axially beyond the trailing edge of the turbine stator blade, and the length of the axial extension is 1.5 mm. The lower edge plate has a rounded corner on the exhaust edge, and the radius of the rounded corner is 0.5 mm.

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