Numerical simulation and life prediction method of fatigue damage of water turbine blade and related device

Abstract

The application discloses a kind of water turbine blade fatigue damage numerical simulation and life prediction method and related device, comprising: obtaining the three-dimensional geometric model of water turbine blade and operating condition parameter;According to the three-dimensional geometric model of the water turbine blade and operating condition parameter, fluid-structure interaction model is established, and the fluid pressure fluctuation, cavitation impact stress and sand particle erosion load distribution on the surface of blade in the operation process are extracted;According to the fluid pressure fluctuation, cavitation impact stress and sand particle erosion load distribution on the surface of blade, the equivalent stress of blade is formed;Based on the equivalent stress and cycle number, fatigue damage evolution model is constructed;According to the fatigue damage evolution model and cumulative damage theory, the fatigue damage amount of blade under different operating time is calculated, and the life prediction result is output, and the method and related device can dynamically predict the fatigue life of water turbine blade.

Description

Technical Field

[0001] This invention belongs to the field of hydraulic machinery and hydropower engineering technology, and relates to a method and related device for numerical simulation of fatigue damage and life prediction of turbine blades. Background Technology

[0002] During long-term operation, turbine blades are subjected to complex external loads, including flow pulsation, cavitation impact, and particle erosion caused by sediment-laden water. These loads are random, coupled, and multi-scale, leading to a cumulative effect of fatigue damage on the blades. When the damage develops to a critical level, the blades may experience crack propagation or fracture, severely affecting the safe and stable operation of the unit. Therefore, accurately predicting the fatigue life of turbine blades under multi-source loads is a critical problem that the hydropower industry urgently needs to solve.

[0003] In existing research, most life prediction methods only consider a single load factor. For example, some studies calculate the dynamic stress distribution of blades based on fluid pulsating pressure and use linear fatigue damage models for life estimation; some studies only focus on the impact stress caused by cavitation collapse, ignoring the long-term cumulative effects of other loads; and some studies focus on surface damage caused by sand erosion, resulting in insufficient quantitative prediction of fatigue life. Although these methods can reflect the impact of a single factor on blade life to some extent, their prediction results are often significantly biased due to the lack of consideration for the superposition effect of multiple load sources, making it difficult to meet the needs of practical engineering applications.

[0004] Furthermore, traditional life prediction methods generally suffer from two limitations: first, the damage models used are mostly based on the linear accumulation assumption of a single stress cycle, failing to consider the nonlinear cumulative effects brought about by the complexity of the load spectrum; second, their computational efficiency is low, making it difficult to conduct rapid assessments under multiple operating conditions and the entire life cycle. Therefore, there is an urgent need for a numerical simulation method that can simultaneously consider multi-source loads such as flow pulsation, cavitation impact, and particle erosion, and combine fluid-structure interaction analysis with cumulative damage theory, thereby achieving dynamic prediction of the fatigue life of turbine blades and providing scientific support for power plant maintenance strategies and operation optimization. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method and related device for numerical simulation of fatigue damage and life prediction of turbine blades. This method and related device can dynamically predict the fatigue life of turbine blades.

[0006] To achieve the above objectives, this invention discloses a method for numerical simulation of fatigue damage and life prediction of turbine blades, comprising: Obtain the three-dimensional geometric model and operating parameters of the turbine blades; Based on the three-dimensional geometric model and operating parameters of the turbine blades, a fluid-structure interaction model is established to extract the fluid pressure pulsation, cavitation impact stress and sand erosion load distribution on the blade surface during operation. The equivalent stress of the blade is formed based on the fluid pressure pulsation, cavitation impact stress, and sand erosion load distribution on the blade surface. Based on the equivalent stress and the number of cycles, a fatigue damage evolution model is constructed; Based on the fatigue damage evolution model and cumulative damage theory, the fatigue damage of the blade at different operating times is calculated, and the life prediction results are output.

[0007] Furthermore, the fluid pressure pulsation is obtained through unsteady computational fluid dynamics methods, including fundamental frequency, harmonic frequency and high frequency pulsation components; the cavitation impact stress is obtained by simulating the bubble generation and collapse process using a cavitation model; and the sand erosion load is obtained through an impact model based on particle motion trajectory.

[0008] Furthermore, based on the fluid pressure pulsation, cavitation impact stress, and sand erosion load distribution on the blade surface, the equivalent stress of the blade is obtained using a linear or nonlinear superposition method.

[0009] Furthermore, the fatigue damage evolution model adopts a function form based on stress amplitude and cycle number, and the damage increment under different load conditions is calculated and superimposed.

[0010] Furthermore, the cumulative damage theory is Miner's linear cumulative damage criterion, or a nonlinear cumulative model is used to calculate the fatigue life consumption rate and determine the remaining life of the blade.

[0011] Furthermore, life prediction is performed under multiple operating conditions, including small opening operation, rated opening operation, and large opening operation. The fatigue damage results under different operating conditions are weighted and superimposed to form a comprehensive damage curve over the entire life cycle.

[0012] Furthermore, the life prediction results include the blade fatigue life curve, the correspondence between efficiency decay and life consumption, and the correspondence between maintenance cycle and life threshold.

[0013] This invention discloses a numerical simulation and life prediction system for fatigue damage of water turbine blades, comprising: The acquisition module is used to acquire the three-dimensional geometric model and operating parameters of the turbine blades; The first construction module is used to establish a fluid-structure interaction model based on the three-dimensional geometric model and operating parameters of the turbine blade, and to extract the fluid pressure pulsation, cavitation impact stress and sand erosion load distribution on the blade surface during operation. A forming module is used to form the equivalent stress of the blade based on the fluid pressure pulsation, cavitation impact stress and sand erosion load distribution on the blade surface; The second construction module is used to construct a fatigue damage evolution model based on the equivalent stress and the number of cycles. The prediction module is used to calculate the fatigue damage of the blade at different operating times based on the fatigue damage evolution model and cumulative damage theory, and output the life prediction results.

[0014] This invention discloses a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the numerical simulation and life prediction method for fatigue damage of water turbine blades.

[0015] The present invention discloses a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method for numerical simulation of fatigue damage and life prediction of turbine blades.

[0016] The present invention has the following beneficial effects: The numerical simulation and life prediction method and related device for turbine blade fatigue damage described in this invention, in practical operation, introduces comprehensive modeling of multi-source loads such as flow pulsation, cavitation impact, and sand erosion, and establishes a fatigue cumulative damage model within a fluid-structure interaction framework to achieve dynamic prediction of turbine blade fatigue life. Compared with existing techniques that only consider a single load or linear accumulation, this invention can more comprehensively reflect the damage evolution law under complex operating conditions, and the prediction results are more accurate. This invention can not only quantify blade life consumption, but also establish the correspondence between efficiency decay and maintenance cycle, providing a scientific basis and significant engineering value for hydropower station operation optimization and full life cycle management. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a graph showing the evolution of blade fatigue damage over operating time. Figure 3 This is a graph showing the decline in unit efficiency as fatigue damage progresses. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] In the description of this invention, it should be understood that the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0021] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0022] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Additionally, the character " / " in this invention generally indicates that the preceding and following objects have an "or" relationship.

[0023] It should be understood that although terms such as first, second, third, etc., may be used in the embodiments of the present invention to describe the preset range, these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from one another. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0024] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0026] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0027] Example 1 refer to Figure 1 The method for numerical simulation and life prediction of turbine blade fatigue damage according to the present invention includes the following steps: 1) Establishment of geometric modeling and fluid-structure interaction framework; A three-dimensional geometric model of the turbine blade is established, and a fluid domain and a structural domain are divided in the three-dimensional geometric model. The fluid domain adopts the incompressible Navier-Stokes equations, and the structural domain adopts the finite element equilibrium equations. The two are bidirectionally coupled through boundary conditions.

[0028] The incompressible Navier–Stokes equations are as follows:

[0029] The finite element equilibrium equation is as follows:

[0030] Where K is the stiffness matrix, {u} is the nodal displacement, and {F} is the external load vector, provided by the fluid pressure distribution.

[0031] 2) Extract multi-source loads; In fluid-structure interaction calculations, three typical loads are extracted from the blade surface: Dynamic load on the blade surface: The pressure time history p(t) on the blade surface was obtained through unsteady CFD calculation and Fourier decomposition was performed.

[0032] in, For the average pressure, A n For amplitude, f n This represents the pulsation frequency.

[0033] Cavitation impact load: The Zwart–Gerber–Belamri model was used to simulate bubble generation and collapse, and the peak impact stress was obtained.

[0034] Where R0 is the initial bubble radius, R is the instantaneous radius, and ρ is the fluid density.

[0035] Sand erosion load: Collision energy between particles and blade surface calculated using a discrete phase model.

[0036] Where, m p v represents the particle mass. p Let θ be the impact velocity and θ be the incident angle.

[0037] 3) Construct the equivalent stress history of multi-source loads; Convert the three types of loads into equivalent forces :

[0038] Where, σ p (t) represents the pulsating stress, σ c (t) represents the cavitation impact stress, σ e (t) represents the equivalent stress of particle erosion; α and β are weighting coefficients, determined by the principle of energy equivalence.

[0039] 4) Establish a fatigue damage model; Using a method combining S–N curves and Palmgren–Miner cumulative damage theory, the lifetime cycle number for a single stress amplitude σ is:

[0040] Where, σ a denoted as the material's fatigue strength limit, and m as a material constant.

[0041] The cumulative fatigue damage D is:

[0042] Where, n iN represents the actual number of load cycles. i This represents the lifespan under this stress level. When D ≥ 1, the blade is considered to have failed.

[0043] 5) Lifetime prediction and efficiency degradation curves; By weighting the cumulative damage under different operating conditions, the damage evolution curve over the entire life cycle of the blade is obtained:

[0044] Based on fluid-structure interaction efficiency, the functional relationship between efficiency and lifetime consumption can be established as follows:

[0045] Where η0 is the initial efficiency and γ is the efficiency decay coefficient.

[0046] 6) Reduced-order prediction using surrogate models; To improve computational efficiency, a surrogate model is used to fit the full-lifetime simulation results. The inputs are load parameters (flow rate, cavitation number, sediment concentration, etc.), and the outputs are the lifetime attrition rate and efficiency decay. The surrogate model can be a Kriging model, a radial basis function network, or a deep neural network, with the Kriging model being the preferred choice.

[0047] Example 2 This embodiment takes a 50MW axial-flow turbine unit as an example and uses the present invention to predict the fatigue life of blades under complex operating conditions.

[0048] The unit operates in a water flow environment with a sand concentration of 2 kg / m³, a rated flow rate of 180 m³ / s, and a rotational speed of 75 rpm. During operation, the blades are simultaneously subjected to multiple loads, including flow pulsation, cavitation impact, and sand erosion. Based on fluid-structure interaction calculations, the dynamic stress time history of the blade surface under typical operating conditions was obtained.

[0049] Subsequently, multi-source payload extraction was performed, including: The fundamental frequency of the flow pulse is 75 Hz, and the pressure amplitude is approximately 0.12 MPa; The peak local impact stress caused by cavitation collapse reached 0.35 MPa; The equivalent erosion stress caused by sand-containing particles on the suction surface of the blade is approximately 0.08 MPa.

[0050] The three types of loads were superimposed using the principle of energy equivalence to obtain the equivalent stress history of the blade.

[0051] Based on the S–N curve of the material (ZG0Cr13Ni5Mo stainless steel, fatigue strength limit σ) a =260MPa), and the damage attrition rate was calculated using Miner's cumulative damage model:

[0052] Where, n i N represents the actual number of load cycles. i This represents the lifespan at that stress level.

[0053] Calculation results show that under sand-laden and cavitation conditions, the cumulative damage to the blades reaches 0.72 after 5 years of operation, and the lifespan is consumed by more than 70%.

[0054] Further analysis of the efficiency decay law, including, for example Figure 1 As shown, the amount of fatigue damage to the blades gradually increases with operating time, with a slow initial increase, a significantly faster growth rate after 3 years, and nearing the lifespan limit after 5 years. Figure 2 As shown, the unit efficiency gradually decreases with the development of fatigue damage. The initial efficiency is 93%, which decreases by about 2.5% after 3 years and by about 4.2% after 5 years, reaching the preset maintenance threshold.

[0055] Based on the correlation between fatigue life consumption and efficiency decline, it is recommended to carry out maintenance or blade replacement after 4.5 to 5 years of operation to ensure the safe and economical operation of the unit.

[0056] Example 3 The numerical simulation and life prediction system for fatigue damage of turbine blades according to the present invention is characterized by comprising: The acquisition module is used to acquire the three-dimensional geometric model and operating parameters of the turbine blades; The first construction module is used to establish a fluid-structure interaction model based on the three-dimensional geometric model and operating parameters of the turbine blade, and to extract the fluid pressure pulsation, cavitation impact stress and sand erosion load distribution on the blade surface during operation. A forming module is used to form the equivalent stress of the blade based on the fluid pressure pulsation, cavitation impact stress and sand erosion load distribution on the blade surface; The second construction module is used to construct a fatigue damage evolution model based on the equivalent stress and the number of cycles. The prediction module is used to calculate the fatigue damage of the blade at different operating times based on the fatigue damage evolution model and cumulative damage theory, and output the life prediction results.

[0057] The module division in this embodiment is illustrative and represents only one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional modules in each embodiment of this application can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0058] Example 4 A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of a method for numerical simulation and life prediction of fatigue damage of a hydro-turbine blade. For example, the method includes: acquiring a three-dimensional geometric model and operating parameters of the hydro-turbine blade; establishing a fluid-structure interaction model based on the three-dimensional geometric model and operating parameters of the hydro-turbine blade, and extracting the distribution of fluid pressure pulsation, cavitation impact stress, and sand erosion load on the blade surface during operation; forming an equivalent stress of the blade based on the fluid pressure pulsation, cavitation impact stress, and sand erosion load distribution on the blade surface; constructing a fatigue damage evolution model based on the equivalent stress and the number of cycles; calculating the fatigue damage amount of the blade at different operating times based on the fatigue damage evolution model and cumulative damage theory, and outputting the life prediction result. The memory may include main memory, such as high-speed random access memory (RAM), or non-volatile memory, such as at least one disk storage device. The processor, network interface, and memory are interconnected via an internal bus, which may be an industry-standard architecture bus, a peripheral component interconnection standard bus, or an extended industry-standard architecture bus. The bus can be categorized as an address bus, data bus, or control bus. The memory stores programs; specifically, the program may include program code, which includes computer operation instructions. The memory may include main memory and non-volatile memory, and provides instructions and data to the processor.

[0059] Example 5 A computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of a numerical simulation and life prediction method for fatigue damage of a hydro-turbine blade. For example, the method includes: acquiring a three-dimensional geometric model and operating parameters of the hydro-turbine blade; establishing a fluid-structure interaction model based on the three-dimensional geometric model and operating parameters, and extracting the distribution of fluid pressure pulsation, cavitation impact stress, and sand erosion load on the blade surface during operation; forming an equivalent stress of the blade based on the fluid pressure pulsation, cavitation impact stress, and sand erosion load distribution on the blade surface; constructing a fatigue damage evolution model based on the equivalent stress and the number of cycles; calculating the fatigue damage amount of the blade at different operating times based on the fatigue damage evolution model and cumulative damage theory, and outputting the life prediction result. Specifically, the computer-readable storage medium includes, but is not limited to, volatile memory and / or non-volatile memory. The volatile memory may include random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include read-only memory (ROM), hard disk, flash memory, optical disk, magnetic disk, etc.

[0060] 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.

[0061] 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.

[0062] 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.

[0063] 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.

[0064] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and disclosure of the invention. This application is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the following claims.

[0065] It should be understood that the present invention is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

[0066] The above description is merely a preferred embodiment of the present invention and does not constitute any limitation on the present invention. Any simple modifications, alterations, or equivalent structural changes made to the above embodiments based on the technical essence of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for numerical simulation and life prediction of fatigue damage in hydraulic turbine blades, characterized in that, include: Obtain the three-dimensional geometric model and operating parameters of the turbine blades; Based on the three-dimensional geometric model and operating parameters of the turbine blades, a fluid-structure interaction model is established to extract the fluid pressure pulsation, cavitation impact stress and sand erosion load distribution on the blade surface during operation. The equivalent stress of the blade is formed based on the fluid pressure pulsation, cavitation impact stress, and sand erosion load distribution on the blade surface. Based on the equivalent stress and the number of cycles, a fatigue damage evolution model is constructed; Based on the fatigue damage evolution model and cumulative damage theory, the fatigue damage of the blade at different operating times is calculated, and the life prediction results are output.

2. The numerical simulation method for structural defects in turbine blades according to claim 1, characterized in that, The fluid pressure pulsation is obtained through unsteady computational fluid dynamics methods, including fundamental frequency, harmonic frequency and high frequency pulsation components; the cavitation impact stress is obtained by simulating the bubble generation and collapse process using a cavitation model; the sand erosion load is obtained through an impact model based on particle motion trajectory.

3. The numerical simulation method for structural defects in turbine blades according to claim 1, characterized in that, Based on the fluid pressure pulsation, cavitation impact stress, and sand erosion load distribution on the blade surface, the equivalent stress of the blade is obtained by using a linear or nonlinear superposition method.

4. The numerical simulation method for structural defects in turbine blades according to claim 1, characterized in that, The fatigue damage evolution model adopts a function form based on stress amplitude and cycle number, and the damage increment under different load conditions is calculated and superimposed.

5. The numerical simulation method for structural defects in turbine blades according to claim 1, characterized in that, The cumulative damage theory is Miner's linear cumulative damage criterion, or a nonlinear cumulative model is used to calculate the fatigue life consumption rate and determine the remaining life of the blade.

6. The numerical simulation method for structural defects in turbine blades according to claim 1, characterized in that, Life prediction is performed under multiple operating conditions, including small opening operation, rated opening operation, and large opening operation. The fatigue damage results under different operating conditions are weighted and superimposed to form a comprehensive damage curve over the entire life cycle.

7. The numerical simulation method for structural defects in turbine blades according to claim 1, characterized in that, The life prediction results include the blade fatigue life curve, the correspondence between efficiency decay and life consumption, and the correspondence between maintenance cycle and life threshold.

8. A numerical simulation and life prediction system for fatigue damage of hydraulic turbine blades, characterized in that, include: The acquisition module is used to acquire the three-dimensional geometric model and operating parameters of the turbine blades; The first construction module is used to establish a fluid-structure interaction model based on the three-dimensional geometric model and operating parameters of the turbine blade, and to extract the fluid pressure pulsation, cavitation impact stress and sand erosion load distribution on the blade surface during operation. A forming module is used to form the equivalent stress of the blade based on the fluid pressure pulsation, cavitation impact stress and sand erosion load distribution on the blade surface; The second construction module is used to construct a fatigue damage evolution model based on the equivalent stress and the number of cycles. The prediction module is used to calculate the fatigue damage of the blade at different operating times based on the fatigue damage evolution model and cumulative damage theory, and output the life prediction results.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the numerical simulation and life prediction method for fatigue damage of turbine blades as described in any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the numerical simulation and life prediction method for fatigue damage of turbine blades as described in any one of claims 1-7.

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