A method and system for internal cooling of heavy-duty gas turbine turbine blades

Abstract

The present invention relates to the technical field of internal cooling of turbine blades, and in particular to a method and system for internal cooling of heavy-duty gas engine turbine blades. The method comprises: S1, modifying a Fourier heat transfer physical model by introducing a relaxation parameter to obtain a modified heat transfer physical model, and deriving a corresponding control equation; S2, discretizing the control equation and converting it into a discrete equation; S3, numerically simulating the internal cooling of the heavy-duty gas engine turbine blade based on the discrete equation; and S4, internally cooling the heavy-duty gas engine turbine blade based on the results of the numerical simulation. By using the present invention, heavy-duty gas engine turbine blades can be internally cooled based on accurate numerical simulation results.

Description

Technical Field

[0001] The present invention relates to the technical field of internal cooling of turbine blades, and in particular to a method and system for internal cooling of turbine blades of heavy-duty combustion engines. Background Art

[0002] In the field of power generation and drive, advanced heavy-duty gas turbines are undoubtedly the shining "crown jewel", carrying the core power of the industry. These high-performance gas turbine engines operate in extremely high temperature environments (between 1200 and 1500 degrees Celsius) in order to improve thermal efficiency and power output. With the rapid development of gas turbine technology, the inlet temperature of the turbine is also gradually rising, and with it the heat load borne by the turbine blades is increasing. In order to ensure the durability of the blades and extend their service life, strict control of the internal temperature tolerance level of the blade material and its changes has become a crucial technical challenge. It cannot be ignored that the actual working temperature of the blades far exceeds the maximum temperature that the metal can withstand. Therefore, how to efficiently and safely cool the blades has become the key to the stable operation of the gas turbine. Summary of the Invention

[0003] The present invention provides a method and system for internal cooling of heavy-duty gas turbine blades to address the problems of the prior art. The technical solution is as follows:

[0004] In one aspect, a method for internally cooling a heavy-duty gas turbine blade is provided, comprising:

[0005] S1. By introducing relaxation parameters, the Fourier heat transfer physical model is modified to obtain the modified heat transfer physical model, and the corresponding control equation is derived;

[0006] S2. discretizing the control equation and converting it into a discrete equation;

[0007] S3. performing a numerical simulation on the internal cooling of the heavy-duty gas engine turbine blade according to the discrete equation;

[0008] S4. Based on the results of the numerical simulation, the heavy-duty gas engine turbine blades are internally cooled.

[0009] Optionally, the modified heat transfer physical model is Among them, q represents tensor, t represents time, D represents thermal conductivity, T represents temperature, and λ is the introduced relaxation parameter. At this time, the propagation speed of the thermal signal is is a finite value, controlled by the relaxation parameter λ;

[0010] The control equation is: Where ρ represents the fluid density, represents the fluid velocity vector, k is the thermal conductivity, c p represents the specific heat capacity of the fluid, A new second-order time derivative term is added to the governing equation corresponding to the relative Fourier heat transfer physical model.

[0011] Optionally, the S2 specifically includes:

[0012] Expand the control equation at the nth time layer, and for the newly added second-order time derivative term in the control equation Use the central difference of the previous time layer to approximate the newly added second-order time derivative term The discretization of the previous time layer is: and is considered as the source term of the control equation, which is discretized as: Among them, the discretization method of the second-order time derivative term is: τ represents the time step.

[0013] Optionally, the S3 specifically includes:

[0014] Determine the internal cooling research area of ​​the heavy-duty gas turbine turbine blade, and mesh the research area using Fluent-Meshing's latest Poly-Hexcore mesh technology with local encryption;

[0015] According to the discretized control equation, a source term UDF plug-in is written for the divided grid using Fluent software to perform numerical simulation.

[0016] Optionally, the method of discretizing the control equation in S2 can analyze the error, and let Using Taylor's formula in mathematics, we get:

[0017]

[0018] Where f'(ξ) represents the derivative of f(ξ) with respect to t, and ξ represents t n-1 With t n For any value in , we can see from the formula that: for the second-order time derivative term, the value of the n-1 layer can be approximated to the value of the n layer, and the error is controllable.

[0019] In another aspect, a system for internally cooling a heavy-duty combustion engine turbine blade is provided, the system comprising:

[0020] A correction module is used to correct the Fourier heat transfer physical model by introducing relaxation parameters to obtain a corrected heat transfer physical model and derive the corresponding control equation;

[0021] A discretization module, used for discretizing the control equation and converting it into a discrete equation;

[0022] a numerical simulation module, configured to perform numerical simulation on the internal cooling of the turbine blade of the heavy-duty gas engine according to the discrete equation;

[0023] The internal cooling module is used to perform internal cooling on the turbine blades of the heavy-duty gas engine according to the results of numerical simulation.

[0024] Optionally, the modified heat transfer physical model is Among them, q represents tensor, t represents time, D represents thermal conductivity, T represents temperature, and λ is the introduced relaxation parameter. At this time, the propagation speed of the thermal signal is is a finite value, controlled by the relaxation parameter λ;

[0025] The control equation is: Where ρ represents the fluid density, represents the fluid velocity vector, k is the thermal conductivity, c p represents the specific heat capacity of the fluid, A new second-order time derivative term is added to the governing equation corresponding to the relative Fourier heat transfer physical model.

[0026] Optionally, the discretization module is specifically configured to:

[0027] Expand the control equation at the nth time layer, and for the newly added second-order time derivative term in the control equation Use the central difference of the previous time layer to approximate the newly added second-order time derivative term The discretization of the previous time layer is: and is considered as the source term of the control equation, which is discretized as: Among them, the discretization method of the second-order time derivative term is: τ represents the time step.

[0028] Optionally, the numerical simulation module is specifically used to:

[0029] Determine the internal cooling research area of ​​the heavy-duty gas turbine turbine blade, and mesh the research area using Fluent-Meshing's latest Poly-Hexcore mesh technology with local encryption;

[0030] According to the discretized control equation, a source term UDF plug-in is written for the divided grid using Fluent software to perform numerical simulation.

[0031] Optionally, the discretization module can discretize the control equation to analyze the error, so Using Taylor's formula in mathematics, we get:

[0032]

[0033] Where f'(ξ) represents the derivative of f(ξ) with respect to t, and ξ represents t n-1 With t n For any value in , we can see from the formula that: for the second-order time derivative term, the value of the n-1 layer can be approximated to the value of the n layer, and the error is controllable.

[0034] On the other hand, an electronic device is provided, comprising a processor and a memory, wherein the memory stores at least one instruction, and the at least one instruction is loaded and executed by the processor to implement the above-mentioned method for internal cooling of heavy-duty gas engine turbine blades.

[0035] On the other hand, a computer-readable storage medium is provided, wherein the storage medium stores at least one instruction, and the at least one instruction is loaded and executed by a processor to implement the above-mentioned method for internal cooling of a heavy-duty gas engine turbine blade.

[0036] The beneficial effects brought about by the technical solution provided by the present invention include at least:

[0037] By adopting the present invention, the internal cooling of the turbine blades of the heavy-duty gas engine can be performed according to the accurate numerical simulation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0039] Figure 1 This is a flow chart of a method for internally cooling a heavy-duty gas engine turbine blade provided by an embodiment of the present invention;

[0040] Figure 2 Schematic diagram of grid division for impingement cooling provided by an embodiment of the present invention;

[0041] Figure 3 Schematic diagram of grid division for column rib cooling provided by an embodiment of the present invention;

[0042] Figure 4 Schematic diagram of mesh division of a ribbed channel cooling grid provided by an embodiment of the present invention;

[0043] Figure 5This is a block diagram of a system for internal cooling of heavy-duty gas engine turbine blades provided by an embodiment of the present invention;

[0044] Figure 6 It is a structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0045] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0046] The embodiment of the present invention provides a method for internal cooling of a heavy-duty gas turbine blade. The method can be implemented by an electronic device, which can be a terminal or a server. Figure 1 A flow chart of a method for internally cooling a heavy-duty gas engine turbine blade is shown. The process flow of the method may include the following steps:

[0047] S1. By introducing relaxation parameters, the Fourier heat transfer physical model is modified to obtain the modified heat transfer physical model, and the corresponding control equation is derived;

[0048] Conduction, convection, and radiation are three forms of heat transfer. In the study of heat transfer problems, the most classic heat transfer physics model is the Fourier heat transfer physics model based on Fourier's law: q = -D▽T, where q represents a tensor, D represents thermal conductivity, and T represents temperature. Many numerical simulations involving heat transfer problems are based on the Fourier heat transfer physics model, and the internal cooling problem of blades is no exception. The corresponding governing equation is: Where ρ represents the fluid density, t represents the time, and T represents the temperature. represents the fluid velocity vector, k is the thermal conductivity, c p However, the study found that the governing equation derived from the classical Fourier law exhibits the paradox of infinite propagation speed of thermal signals, which is contrary to actual experience.

[0049] To this end, the embodiment of the present invention modifies the Fourier heat transfer physical model by introducing a relaxation parameter to obtain a modified heat transfer physical model, and derives the corresponding control equation. The modified heat transfer physical model is: Among them, q represents tensor, t represents time, D represents thermal conductivity, T represents temperature, and λ is the introduced relaxation parameter. At this time, the propagation speed of the thermal signal is is a finite value, controlled by the relaxation parameter λ;

[0050] The control equation is: Where ρ represents the fluid density, represents the fluid velocity vector, k is the thermal conductivity, c p represents the specific heat capacity of the fluid, A new second-order time derivative term is added to the governing equation corresponding to the relative Fourier heat transfer physical model.

[0051] S2. discretizing the control equation and converting it into a discrete equation;

[0052] The continuous control equations need to be converted into discrete equations through discretization methods. The choice of discretization method has a direct impact on the accuracy and efficiency of the simulation.

[0053] Optionally, the S2 specifically includes:

[0054] Expand the control equation at the nth time layer, and for the newly added second-order time derivative term in the control equation Use the central difference of the previous time layer to approximate the newly added second-order time derivative term The discretization of the previous time layer is: and is considered as the source term of the control equation, which is discretized as: Among them, the discretization method of the second-order time derivative term is: τ represents the time step.

[0055] The advantage of the above discretization method is that the newly added second-order time derivative term can be converted into a known source term, and the above method can analyze the error.

[0056] Optionally, the method of discretizing the control equation in S2 can analyze the error, and let Using Taylor's formula in mathematics, we get:

[0057]

[0058] Where f'(ξ) represents the derivative of f(ξ) with respect to t, and ξ represents t n-1 With t n For any value in , we can see from the formula that: for the second-order time derivative term, the value of the n-1 layer can be approximated to the value of the n layer, and the error is controllable.

[0059] During numerical simulations, the governing equations corresponding to the modified heat transfer physics model cannot be directly obtained using the commercial Fluent software. This embodiment of the present invention uses Taylor series expansion to analyze errors, using the second-order central difference at the previous moment to approximate the second-order derivative term at the current moment and treating it as a known source term. This method effectively controls errors and ensures the accuracy of the numerical simulation.

[0060] S3. performing a numerical simulation on the internal cooling of the heavy-duty gas engine turbine blade according to the discrete equation;

[0061] Optionally, the S3 specifically includes:

[0062] Determine the internal cooling research area of ​​the heavy-duty gas turbine turbine blade, and mesh the research area using Fluent-Meshing's latest Poly-Hexcore mesh technology with local encryption;

[0063] According to the discretized control equation, a source term UDF plug-in is written for the divided grid using Fluent software to perform numerical simulation.

[0064] Currently, turbine blade cooling technologies can be categorized as external or internal, depending on the cooling location. External cooling primarily includes film cooling and radiative cooling. Internal cooling primarily includes impingement cooling, rib cooling, and fin turbulence cooling. In blade internal cooling design, impingement cooling is widely used in the leading edge, where heat loads are most concentrated. This method uses ducts within the stator blades or flow channels within the rotor blades to direct cooling air through specific impingement holes, directly onto the blade's inner surface (target surface). This impingement jet approach significantly improves the local heat transfer coefficient, effectively addressing the high heat load at the leading edge. However, the trailing edge structure is relatively fragile and cannot withstand complex impingement cooling structures. Therefore, column-and-rib cooling solutions, namely rib-and-rib cooling and ribbed cooling, are commonly employed. These methods employ a series of column-and-rib structures, perpendicular to the cooling air flow direction, within the limited space at the blade's trailing edge to enhance cooling. These column-and-rib structures not only optimize the cooling air flow path but also increase the contact area with the blade surface, thereby improving cooling efficiency. Fins are added to the central portion of the blade to modify the cooling air's motion characteristics. These fins transform the originally laminar cooling air flow into turbulent flow, increasing flow instability and thus improving heat transfer efficiency. Furthermore, the addition of fins increases the fluid-solid heat transfer area, further enhancing the cooling effect. This meticulously designed cooling solution ensures that different areas of the blade are adequately cooled, guaranteeing long-term stable operation.

[0065] Fluent commercial software is often used for numerical simulation of internal cooling problems in turbine blades. However, the control equations corresponding to the modified heat transfer physics model become more complex, changing from parabolic to hyperbolic. A key issue, as well as the focus and difficulty of solving the problem, is that the core program within Fluent commercial software is not public, making direct discretization of it infeasible. However, Fluent provides users with custom functions that can be written in C language to extend Fluent's functionality, including source term UDFs. Therefore, in an embodiment of the present invention, a source term UDF plug-in is written in Fluent software for the divided grid based on the discretized control equations to perform numerical simulation. This method not only optimizes Fluent's built-in control equations, but also improves its applicability in specific application scenarios.

[0066] In the simulation of the internal cooling problem of turbine blades, mesh generation is a complex but crucial process, which directly affects the accuracy and computational efficiency of the simulation. In fluid simulation, there has always been a debate between hexahedron and tetrahedron meshes in various aspects of the simulation, but basically one consensus can be reached: that is, "hexahedron is better than tetrahedron in the solution process (although it is more difficult to divide)". The embodiment of the present invention prefers to use hexahedron meshes as much as possible in the calculation, which can not only effectively reduce the number of meshes, but also may reduce the impact of pseudo-diffusion. Therefore, the embodiment of the present invention does not use traditional structured meshes, but uses Fluent-Meshing's latest Poly-Hexcore mesh technology for local encryption. This mesh technology enables the hexahedron mesh and the polyhedron mesh to achieve common node connection (no interface surface). By increasing the proportion of hexahedral meshes, the Poly-Hexcore technology not only improves the accuracy of the mesh, but also optimizes the number of meshes and reduces the consumption of computing resources. This technology also specifically supports the division of boundary layer meshes, allowing the layered Poly mesh near the wall, the pure Poly mesh in the transition area, and the hexahedral mesh in the core area to work together to form an efficient calculation area filling strategy.

[0067] The following is a schematic diagram of the mesh generation for the three internal cooling methods:

[0068] like Figure 2 As shown in the figure, the impingement cooling grid is locally refined near the impingement hole, and three boundary layers are set on the relevant wall surfaces.

[0069] like Figure 3 As shown in the figure, the column-rib cooling grid is locally refined near the column rib, and a boundary layer is also set on the relevant wall surface.

[0070] like Figure 4As shown in the figure, the grid of the ribbed channel cooling grid near the ribs is divided regularly, the surface is mainly polygonal, and the internal grid is filled with hexahedral grids.

[0071] S4. Based on the results of the numerical simulation, the heavy-duty gas engine turbine blades are internally cooled.

[0072] The present invention uses a modified heat transfer model to numerically simulate heat transfer within turbine blades, better reproducing the actual heat transfer conditions. In steady-state studies, the numerical calculation results for the three cooling methods calculated using the modified heat transfer model were within ±10% of the experimental results. Furthermore, the present invention used the modified heat transfer model to conduct transient simulation experiments for the three cooling methods. The transient heat transfer data better matched the experimental results with the Fourier heat transfer model.

[0073] like Figure 5 As shown, an embodiment of the present invention further provides a system for internally cooling a heavy-duty gas engine turbine blade, the system comprising:

[0074] A correction module 510 is used to correct the Fourier heat transfer physical model by introducing a relaxation parameter to obtain a corrected heat transfer physical model and derive the corresponding control equation;

[0075] A discretization module 520 is used to discretize the control equation and convert it into a discrete equation;

[0076] A numerical simulation module 530 is used to perform numerical simulation on the internal cooling of the heavy-duty gas engine turbine blade according to the discrete equation;

[0077] The internal cooling module 540 is used to perform internal cooling on the heavy-duty gas engine turbine blades according to the results of the numerical simulation.

[0078] Optionally, the modified heat transfer physical model is Among them, q represents tensor, t represents time, D represents thermal conductivity, T represents temperature, and λ is the introduced relaxation parameter. At this time, the propagation speed of the thermal signal is is a finite value, controlled by the relaxation parameter λ;

[0079] The control equation is: Where ρ represents the fluid density, represents the fluid velocity vector, k is the thermal conductivity, c p represents the specific heat capacity of the fluid, A new second-order time derivative term is added to the governing equation corresponding to the relative Fourier heat transfer physical model.

[0080] Optionally, the discretization module is specifically configured to:

[0081] Expand the control equation at the nth time layer, and for the newly added second-order time derivative term in the control equation Use the central difference of the previous time layer to approximate the newly added second-order time derivative term The discretization of the previous time layer is: and is considered as the source term of the control equation, which is discretized as: Among them, the discretization method of the second-order time derivative term is: τ represents the time step.

[0082] Optionally, the numerical simulation module is specifically used to:

[0083] Determine the internal cooling research area of ​​the heavy-duty gas turbine turbine blade, and mesh the research area using Fluent-Meshing's latest Poly-Hexcore mesh technology with local encryption;

[0084] According to the discretized control equation, a source term UDF plug-in is written for the divided grid using Fluent software to perform numerical simulation.

[0085] Optionally, the discretization module can discretize the control equation to analyze the error, so Using Taylor's formula in mathematics, we get:

[0086]

[0087] Where f'(ξ) represents the derivative of f(ξ) with respect to t, and ξ represents t n-1 With t n For any value in , we can see from the formula that: for the second-order time derivative term, the value of the n-1 layer can be approximated to the value of the n layer, and the error is controllable.

[0088] An embodiment of the present invention provides a system for internally cooling a heavy-duty gas engine turbine blade. Its functional structure corresponds to a method for internally cooling a heavy-duty gas engine turbine blade provided by an embodiment of the present invention, and will not be described in detail here.

[0089] Figure 6This is a structural diagram of an electronic device 600 provided in an embodiment of the present invention. The electronic device 600 may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 601 and one or more memories 602, wherein the memory 602 stores at least one instruction, and the at least one instruction is loaded and executed by the processor 601 to implement the steps of the above-mentioned method for internal cooling of heavy-duty gas engine turbine blades.

[0090] In an exemplary embodiment, a computer-readable storage medium is also provided, such as a memory device including instructions. The instructions are executable by a processor in a terminal to implement the method for internally cooling a heavy-duty gas turbine turbine blade. For example, the computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, or optical data storage device.

[0091] Those skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware, or by a program to instruct the relevant hardware, and the program may be stored in a computer-readable storage medium, which may be a read-only memory, a disk, or an optical disk, etc.

[0092] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for internal cooling of a heavy-duty gas turbine blade, characterized in that: The method comprises: S1. By introducing relaxation parameters, the Fourier heat transfer physical model is modified to obtain the modified heat transfer physical model, and the corresponding control equation is derived; S2. discretizing the control equation and converting it into a discrete equation; S3. performing a numerical simulation on the internal cooling of the heavy-duty gas engine turbine blade according to the discrete equation; S4. performing internal cooling on the heavy-duty gas engine turbine blades according to the results of the numerical simulation; The modified heat transfer physical model is: Among them, q represents tensor, t represents time, D represents thermal conductivity, T represents temperature, and λ is the introduced relaxation parameter. At this time, the propagation speed of the thermal signal is is a finite value, controlled by the relaxation parameter λ; The control equation is: Where ρ represents the fluid density, represents the fluid velocity vector, c p represents the specific heat capacity of the fluid, A new second-order time derivative term is added to the governing equation corresponding to the relative Fourier heat transfer physical model.

2. The method according to claim 1, characterized in that Said S2 specifically includes: Expand the control equation at the nth time layer, and for the newly added second-order time derivative term in the control equation Use the central difference of the previous time layer to approximate the newly added second-order time derivative term The discretization of the previous time layer is: and is considered as the source term of the control equation, which is discretized as: Among them, the discretization method of the second-order time derivative term is: τ represents the time step.

3. The method according to claim 2, characterized in that Said S3 specifically includes: Determine the internal cooling research area of ​​the heavy-duty gas turbine turbine blade, and mesh the research area using Fluent-Meshing's latest Poly-Hexcore mesh technology with local encryption; According to the discretized control equation, a source term UDF plug-in is written for the divided grid using Fluent software to perform numerical simulation.

4. The method according to claim 2, characterized in that The method of discretizing the control equation in S2 can analyze the error, Using Taylor's formula in mathematics, we get: Where f'(ξ) represents the derivative of f(ξ) with respect to t, and ξ represents t n-1 With t n For any value in , O(τ) represents the infinitesimal of the same order of τ. From the formula, we can see that for the second-order time derivative term, the value of the n-1 layer can be approximated to the value of the n layer, and the error is controllable.

5. A system for internal cooling of heavy-duty gas turbine blades, characterized in that: The system comprises: A correction module is used to correct the Fourier heat transfer physical model by introducing relaxation parameters to obtain a corrected heat transfer physical model and derive the corresponding control equation; A discretization module, used for discretizing the control equation and converting it into a discrete equation; a numerical simulation module, configured to perform numerical simulation on the internal cooling of the turbine blade of the heavy-duty gas engine according to the discrete equation; An internal cooling module, configured to perform internal cooling on the turbine blades of the heavy-duty gas engine according to the results of the numerical simulation; The modified heat transfer physical model is: Among them, q represents tensor, t represents time, D represents thermal conductivity, T represents temperature, and λ is the introduced relaxation parameter. At this time, the propagation speed of the thermal signal is is a finite value, controlled by the relaxation parameter λ; The control equation is: Where ρ represents the fluid density, represents the fluid velocity vector, c p represents the specific heat capacity of the fluid, A new second-order time derivative term is added to the governing equation corresponding to the relative Fourier heat transfer physical model.

6. The system according to claim 5, characterized in that The discretization module is specifically used to: Expand the control equation at the nth time layer, and for the newly added second-order time derivative term in the control equation Use the central difference of the previous time layer to approximate the newly added second-order time derivative term The discretization of the previous time layer is: and is considered as the source term of the control equation, which is discretized as: Among them, the discretization method of the second-order time derivative term is: τ represents the time step.

7. The system according to claim 6, characterized in that The numerical simulation module is specifically used for: Determine the internal cooling research area of ​​the heavy-duty gas turbine turbine blade, and mesh the research area using Fluent-Meshing's latest Poly-Hexcore mesh technology with local encryption; According to the discretized control equation, a source term UDF plug-in is written for the divided grid using Fluent software to perform numerical simulation.

8. The system according to claim 6, wherein: The discretization module discretizes the control equation to analyze the error. Using Taylor's formula in mathematics, we get: Where f'(ξ) represents the derivative of f(ξ) with respect to t, and ξ represents t n-1 With t n For any value in , O(τ) represents the infinitesimal of the same order of τ. From the formula, we can see that for the second-order time derivative term, the value of the n-1 layer can be approximated to the value of the n layer, and the error is controllable.

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