Method for predicting high-cycle fatigue limit of stress concentration part of turbine blade

Abstract

The invention relates to a turbine blade stress concentration part high-cycle fatigue limit prediction method, and relates to the technical field of turbine blade fatigue life analysis, and the method comprises the steps: determining the root radius of a target stress concentration part according to the geometric parameters of the target stress concentration part in a simulation part; determining a target stress distribution function according to the root radius of the target stress concentration part, and determining a first maximum stress value of the target stress concentration part according to the target stress distribution function; determining a reference stress value of the target stress concentration part, and determining a stress concentration coefficient of the target stress concentration part according to the reference stress value and the first maximum stress value; and determining a second maximum stress value of the target stress concentration part according to the stress concentration coefficient, and predicting the fatigue limit of the stress concentration part simulation part according to the second maximum stress value. The accuracy of the fatigue limit value is improved.

Description

TECHNICAL FIELD

[0001] The embodiment of the present disclosure relates to the technical field of fatigue life analysis of turbine blades, in particular to a method for predicting high-cycle fatigue limit of stress concentration sites of turbine blades. BACKGROUND

[0002] In recent years, with the continuous improvement of the performance requirements of aero-engines, aero-engines with high rotational speed, high efficiency, large thrust-to-weight ratio and high reliability have become the development trend; at the same time, the turbine inlet temperature of the aero-engine has also been continuously improved.

[0003] As the core component of the aero-engine, the turbine blade is long-term served in the working environment of high temperature, high pressure and high speed, so it not only bears the centrifugal force load generated by rotation, the aerodynamic load generated by aerodynamic force and the thermal load generated by high temperature, but also bears the resonance, surge and flutter loads caused by forced vibration or self-excited vibration, so that the static and dynamic stress levels of the turbine blade are relatively high, which can easily cause high-cycle fatigue failure and seriously affect the safety of the aero-engine.

[0004] Statistical data shows that blade fracture is one of the most common failure reasons in aero-engine accidents; among them, about 70% of blade fracture accidents are caused by high-cycle fatigue failure induced by vibration, and high-cycle fatigue failure usually originates from the characteristic sites such as stress concentration sites of turbine blades; that is, because the stress concentration sites of turbine blades destroy the integrity of the turbine blade structure, often leading to the local stress level being significantly higher than that of the surrounding area (i.e. there is a stress concentration effect), which further reduces the high-cycle fatigue performance of the blade.

[0005] At present, a large number of high-cycle fatigue performance researches of turbine blades have been carried out in related technical solutions; however, these researches mainly focus on high-cycle fatigue tests of material level of nickel-based single crystal superalloys, and the structural level high-cycle fatigue researches of stress concentration sites (such as film hole, spoiler column and other characteristic sites) of turbine blades are relatively less, and the high-cycle fatigue damage failure mechanism of stress concentration sites has not been fully clarified. In addition, there is still a lack of high-cycle fatigue limit prediction method for the stress concentration sites of the blade, which further reduces the accuracy of the fatigue limit prediction results.

[0006] It should be noted that the information disclosed in the above background section is only used to strengthen the understanding of the background of the present disclosure, and therefore can include information that does not constitute prior art known to those of ordinary skill in the art. SUMMARY

[0007] The purpose of the present disclosure is to provide a method for predicting the high-cycle fatigue limit of stress concentration areas of turbine blades, thereby overcoming, at least to a certain extent, the problem of being unable to predict the fatigue limit of simulated parts of stress concentration areas due to limitations and defects of related technologies.

[0008] According to one aspect of the present disclosure, a method for predicting the high-cycle fatigue limit of a stress concentration portion of a turbine blade is provided. The method for predicting the high-cycle fatigue limit of a stress concentration portion of a turbine blade comprises:

[0009] determining a root radius of a target stress concentration location according to geometric parameters of the target stress concentration location in the stress concentration location simulation component;

[0010] determining a target stress distribution function according to a root radius of the stress concentration location, and determining a first maximum stress value of the target stress concentration location according to the target stress distribution function;

[0011] determining a reference stress value of the target stress concentration location, and determining a stress concentration factor of the target stress concentration location based on the reference stress value and the first maximum stress value;

[0012] A second maximum stress value of the target stress concentration location is determined according to the stress concentration coefficient, and a fatigue limit of the simulated component of the stress concentration location is predicted according to the second maximum stress value.

[0013] In an exemplary embodiment of the present disclosure, determining the root radius of the target stress concentration location according to geometric parameters of the target stress concentration location in the stress concentration location simulation part includes:

[0014] constructing a turbine blade geometric model of a single crystal turbine blade, and determining a stress concentration location simulation part based on the turbine blade geometric model;

[0015] Projecting the target stress concentration location in the stress concentration location simulation piece onto the surface of the stress concentration location simulation piece to obtain a stress concentration location projection result, and determining a semi-major axis and a semi-minor axis of the stress concentration location projection result;

[0016] The cosine value of the stress concentration portion angle of the target stress concentration portion is calculated, and the root radius of the target stress concentration portion is determined according to the semi-major axis, the semi-minor axis and the cosine value of the stress concentration portion angle.

[0017] In an exemplary embodiment of the present disclosure, determining a stress concentration location simulation component based on a turbine blade geometric model includes:

[0018] Performing a blade static frequency analysis on the turbine blade geometric model to obtain a static frequency analysis result, and performing a dynamic frequency analysis based on the static frequency analysis result to obtain a dynamic frequency analysis result;

[0019] constructing a dynamic frequency Campbell diagram according to the dynamic frequency analysis result, and analyzing the resonance margin of the turbine blade based on the dynamic frequency Campbell diagram;

[0020] determining a stress concentration location of the turbine blade at a dangerous order according to the resonance margin, and constructing a characteristic simulation part of the stress concentration location;

[0021] Analyzing the vibration characteristics of the characteristic simulation component to obtain a vibration characteristic analysis result, and verifying the validity and vibration intensity of the characteristic simulation component based on the vibration characteristic analysis result to obtain a validity verification result and a vibration intensity verification result;

[0022] When it is determined that the validity verification result and the vibration intensity verification result meet the preset conditions, the characteristic simulation part of the stress concentration part is used as the stress concentration part simulation part.

[0023] In an exemplary embodiment of the present disclosure, determining a target stress distribution function according to the root radius of the target stress concentration location includes:

[0024]

[0025] Among them, σ y (x) is the target stress distribution function, σ max is the maximum value in the stress distribution, a1, a2, a3, a4 are fitting coefficients, r n is the root radius of the stress concentration part; a is the semi-major axis of the projection result of the stress concentration part, b is the semi-minor axis of the projection result of the stress concentration part, x is the distance between the stress point and the root of the target stress concentration part, and y is the stress point.

[0026] In an exemplary embodiment of the present disclosure, determining the second maximum stress value of the target stress concentration location according to the stress concentration coefficient includes:

[0027] Determining the original point method critical distance of the target stress concentration location according to the material of the stress concentration location simulation component, and correcting the original point method critical distance according to the stress concentration coefficient to obtain a corrected point method critical distance;

[0028] The second maximum stress value of the target stress concentration location when it is in a critical state of fatigue failure is determined according to the corrected point method critical distance.

[0029] In an exemplary embodiment of the present disclosure, determining the second maximum stress value of the target stress concentration location according to the stress concentration coefficient further includes:

[0030] determining an original line method critical distance of the target stress concentration location according to the material of the stress concentration location simulation component, and correcting the original line method critical distance according to the stress concentration coefficient to obtain a corrected line method critical distance;

[0031] The second maximum stress value of the target stress concentration location when it is in a critical state of fatigue failure is determined according to the corrected line method critical distance.

[0032] In an exemplary embodiment of the present disclosure, predicting the fatigue limit of a simulated component at a stress concentration location according to the second maximum stress value includes:

[0033] The ratio of the second maximum stress value to the stress concentration factor is calculated, and the fatigue limit value of the stress concentration location simulation component is determined according to the ratio of the second maximum stress value to the stress concentration factor.

[0034] According to one aspect of the present disclosure, a device for predicting the high-cycle fatigue limit of a stress concentration portion of a turbine blade is provided. The device for predicting the high-cycle fatigue limit of a stress concentration portion of a turbine blade comprises:

[0035] A stress concentration location root radius determination module, configured to determine the root radius of the target stress concentration location according to the geometric parameters of the target stress concentration location in the stress concentration location simulation component;

[0036] a first stress value determination module, configured to determine a target stress distribution function according to a root radius of the target stress concentration location, and determine a first maximum stress value of the target stress concentration location according to the target stress distribution function;

[0037] a stress concentration coefficient determination module, configured to determine a reference stress value of the target stress concentration location, and determine the stress concentration coefficient of the target stress concentration location based on the reference stress value and the first maximum stress value;

[0038] A fatigue limit prediction module is used to determine the second maximum stress value of the target stress concentration location according to the stress concentration coefficient, and predict the fatigue limit of the simulated part of the stress concentration location according to the second maximum stress value.

[0039] The method for predicting the high-cycle fatigue limit of a stress concentration site of a turbine blade provided by the embodiment of the present disclosure, on one hand, determines the root radius of a target stress concentration site according to the geometric parameters of the target stress concentration site in a stress concentration site simulation piece; determines the target stress distribution function according to the root radius of the target stress concentration site, and determines the first maximum stress value of the target stress concentration site according to the target stress distribution function; determines the reference stress value of the target stress concentration site, and determines the stress concentration coefficient of the target stress concentration site according to the reference stress value and the first maximum stress value; determines the second maximum stress value of the target stress concentration site according to the stress concentration coefficient, and predicts the fatigue limit of the stress concentration site simulation piece according to the second maximum stress value, thereby realizing the prediction of the fatigue limit of the stress concentration site simulation piece, and solving the problem that the fatigue limit of the stress concentration site simulation piece cannot be predicted in the prior art; on the other hand, since the fatigue limit of the stress concentration site simulation piece can be predicted according to the corrected maximum stress (i.e., the second maximum stress value), the accuracy of the predicted fatigue limit value is improved.

[0040] It should be understood that the general description above and the following detailed description are only exemplary and explanatory, and cannot limit the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0041] The drawings incorporated into the specification and forming a part of the specification, show embodiments consistent with the present disclosure, and together with the specification, serve to explain the principles of the present disclosure. Obviously, the drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without creative labor.

[0042] Figure 1 A flowchart of a method for predicting the high-cycle fatigue limit of a stress concentration site of a turbine blade according to an example embodiment of the present disclosure is schematically shown.

[0043] Figure 2 An example diagram of a flat plate specimen with a stress concentration site according to an example embodiment of the present disclosure is schematically shown.

[0044] Figure 3 、 Figure 4 and Figure 5 An example diagram of a resulting stress concentration site simulation piece according to an example embodiment of the present disclosure is schematically shown.

[0045] Figure 6 、 Figure 7 and Figure 8 An example diagram of a vibration stress distribution extraction path of a stress concentration site simulation piece according to an example embodiment of the present disclosure is schematically shown.

[0046] Figure 9 、 Figure 10 as well as Figure 11 An example diagram schematically shows a comparison between vibration stress simulation results around a stress concentration location of a simulation component according to an example embodiment of the present disclosure and prediction results of various formulas.

[0047] Figure 12 A diagram schematically illustrates a scenario example of a specific selection process for calculating path length according to an exemplary embodiment of the present disclosure.

[0048] Figure 13 An example diagram schematically illustrates a second maximum stress value obtained based on a modified point method critical distance according to an example embodiment of the present disclosure.

[0049] Figure 14 An example diagram schematically illustrates a second maximum stress value obtained based on a modified line method critical distance according to an example embodiment of the present disclosure.

[0050] Figure 15 An example diagram schematically illustrates a comparison of prediction results of different fatigue limit quantitative characterization methods according to an example embodiment of the present disclosure.

[0051] Figure 16 An example diagram schematically illustrates a device for predicting the high-cycle fatigue limit of a stress concentration location on a turbine blade according to an example embodiment of the present disclosure. DETAILED DESCRIPTION

[0052] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the present disclosure will be more comprehensive and complete and will fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced while omitting one or more of the specific details, or that other methods, components, devices, steps, etc. may be employed. In other cases, well-known technical solutions are not shown or described in detail to avoid obscuring various aspects of the present disclosure.

[0053] In addition, the accompanying drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. Identical reference numerals in the figures denote identical or similar parts, and thus repetitive descriptions thereof will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities that do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0054] Existing fatigue life assessment methods for notched components include the nominal stress method, the local stress-strain method, and the stress field intensity method. However, these methods have the following drawbacks:

[0055] On the one hand, the traditional nominal stress method is mainly applicable to uniaxial fatigue loads and fails to fully consider the influence of multiaxial fatigue loads, especially multiaxial nonlinear fatigue loads; therefore, under the action of multiaxial fatigue loads, the traditional nominal stress method cannot accurately evaluate the fatigue performance of notched components.

[0056] On the other hand, the local stress-strain method is mainly used to solve low-cycle fatigue problems under high stress conditions. However, this method usually relies on the strain-life curve of the material, which is mostly obtained through fatigue tests with controlled strain. In addition, due to the relatively small amount of relevant research data and the fact that strain-life curves are more difficult to obtain than SN curves, these factors limit the widespread application of the local stress-strain method. Therefore, this method faces certain challenges in practical application, especially when material data are insufficient.

[0057] On the one hand, the stress field intensity method still faces the problem of complex calculation process in practical application, which to a certain extent limits its widespread application in the engineering field.

[0058] Based on this, the example embodiment of the present disclosure proposes a method for predicting the high-cycle fatigue limit of the stress concentration area of ​​a turbine blade, which can quantitatively characterize the fatigue limit of a simulated part of the stress concentration area based on the critical distance theory. This method not only considers the influence of fatigue stress concentration effect on crack initiation, but also considers the stress concentration size effect. It has been preliminarily applied in engineering practice and has achieved good prediction results.

[0059] In an exemplary embodiment, the method for predicting the high-cycle fatigue limit of the stress concentration portion of the turbine blade proposed in the exemplary embodiment of the present disclosure can be run on a terminal device, a server, a server cluster or a cloud server; of course, those skilled in the art can also run the method of the present disclosure on other platforms as needed, and this exemplary embodiment does not specifically limit this. Specifically, refer to Figure 1As shown, the method for predicting the high cycle fatigue limit of the stress concentration part of the turbine blade may include the following steps:

[0060] Step S110. Determine the root radius of the target stress concentration location according to the geometric parameters of the target stress concentration location in the stress concentration location simulation component;

[0061] Step S120: determining a target stress distribution function according to the root radius of the target stress concentration location, and determining a first maximum stress value of the target stress concentration location according to the target stress distribution function;

[0062] Step S130: determining a reference stress value of the target stress concentration location, and determining a stress concentration factor of the target stress concentration location based on the reference stress value and the first maximum stress value;

[0063] Step S140: Determine a second maximum stress value of the target stress concentration location according to the stress concentration coefficient, and predict the fatigue limit of the simulated component of the stress concentration location according to the second maximum stress value.

[0064] In the above-described method for predicting the high-cycle fatigue limit of a stress concentration site of a turbine blade, on the one hand, the root radius of the target stress concentration site is determined based on the geometric parameters of the target stress concentration site in the stress concentration site simulation; the target stress distribution function is determined based on the root radius of the target stress concentration site, and the first maximum stress value of the target stress concentration site is determined based on the target stress distribution function; the reference stress value of the target stress concentration site is determined, and the stress concentration coefficient of the target stress concentration site is determined based on the reference stress value and the first maximum stress value; the second maximum stress value of the target stress concentration site is determined based on the stress concentration coefficient, and the fatigue limit of the stress concentration site simulation is predicted based on the second maximum stress value, thereby realizing the prediction of the fatigue limit of the stress concentration site simulation and solving the problem in the prior art that the fatigue limit of the stress concentration site simulation cannot be predicted; on the other hand, since the fatigue limit of the stress concentration site simulation can be predicted based on the corrected maximum stress (i.e., the second maximum stress value), the accuracy of the predicted fatigue limit value is thereby improved.

[0065] Hereinafter, the method for predicting the high-cycle fatigue limit of the stress concentration portion of the turbine blade described in the exemplary embodiment of the present disclosure will be explained and illustrated in detail with reference to the accompanying drawings.

[0066] First, the application scenarios and technical implementation principles of the exemplary embodiments of the present disclosure are explained and illustrated. Specifically, turbine blades are one of the core rotating components of aircraft engines. Due to the complex and changeable service environment and working loads, the complex failure mechanism of turbine blades, and the anisotropy of single crystal materials, there are many uncertainties in the design, manufacturing, testing, use, and maintenance of turbine blades. As a result, the accuracy and efficiency of the high-cycle fatigue prediction model of turbine blades are difficult to guarantee. Therefore, in order to evaluate the high-cycle fatigue performance of stress concentration areas of turbine blades, conducting high-cycle fatigue tests based on stress concentration area simulations and selecting appropriate methods to quantitatively characterize the high-cycle fatigue limit are still the key points and difficulties that need to be overcome. Under this premise, the critical distance theory is a fatigue failure assessment method for notched components developed based on the theory of linear elastic fracture mechanics. It can be used to analyze the failure behavior of notched components under fatigue loading; therefore, it is very meaningful to use this method to predict the high-cycle fatigue limit of stress concentration area simulations of typical stress concentration areas of turbine blades.

[0067] In the process of fatigue limit prediction based on critical distance, first, the critical distance theory is derived through the theoretical model of an infinite plate with a through-crack; secondly, by analyzing the influence of the geometric structure difference between the stress concentration part simulation part and the flat part with stress concentration part on the stress distribution characteristics, the semi-major axis a, semi-minor axis b of the projected ellipse and the angle of the stress concentration part are used to make equivalent corrections to the geometric parameters of the stress concentration part in the classical model, and the accuracy of the Glinka-Newport formula, Creager-Paris formula, Xu formula and the stress distribution function expression proposed in this paper are compared. It is found that the function expression proposed in this paper has the highest fitting accuracy for the stress distribution at the root of the stress concentration part; further, considering the influence of the size and shape of the stress concentration part on the critical distance L, the stress concentration coefficient K is used to calculate the stress distribution at the root of the stress concentration part. t Correct the critical distance L of the point method and line method, and finally K t =1.6, K t =2.0 and K t =2.4 stress concentration part simulation parts after the correction of the point method critical distance are 0.0743mm, 0.0661mm, 0.055mm, and the line method critical distance are 0.2971mm, 0.2646mm, 0.2199mm respectively; further, based on the corrected critical distance, the fatigue limit prediction is performed using the point method, and the results show that when K t =1.6, K t =2.0 and K tThe high-cycle fatigue limit error of the stress concentration site simulation piece with a stress concentration site of 2.4 is 11.49%, 10.02%, and 5.7% respectively, the error of the fatigue limit predicted by using the line method is 14.92%, 13.25%, and 2.71% respectively, which are all lower than the allowable error range of 15%, and the critical distance theory shows an advantage in predicting the fatigue limit of the nickel-based single crystal alloy simulation piece.

[0068] Secondly, the stress distribution function involved in the example embodiments of the present disclosure is explained and described. Specifically, in the actual process of predicting the fatigue limit, in order to quantitatively characterize the high-cycle fatigue limit of the stress concentration site simulation piece, the stress distribution function in the stress gradient direction around the stress concentration site needs to be determined first. Meanwhile, under the condition of linear elasticity, the stress distribution function is proportional to the loading stress, that is, the stress distribution characteristics will not change with the size of the loading stress, but only be adjusted in proportion to the loading amplitude; further, considering that the excitation frequency of the high-cycle fatigue test is carried out at the first-order frequency of the simulation piece, therefore, by analyzing the vibration stress distribution around the stress concentration site of the stress concentration site simulation piece under the first-order mode, the maximum value of the vibration stress can be selected as the reference value, the stress distribution around the stress concentration site is normalized, and a general stress distribution function around the stress concentration site is established.

[0069] Further, in the actual application process, for the flat plate sample with a stress concentration site as shown in FIG. 1, there are three stress distribution functions at the notch root in the related technical solutions, which are respectively the Glinka-Newport formula as shown in formula (1), the Creager-Paris formula as shown in formula (2) and the Xu formula as shown in formula (3): Figure 2

[0070]

[0071]

[0072] wherein, K t is a stress concentration coefficient, α = 0.425 + 0.005K t ; r n is the root radius of the stress concentration site; x is the distance between the stress point y and the root of the stress concentration site; σ max is the maximum stress value at the root of the stress concentration site (i.e. the first maximum stress value); and has:

[0073]

[0074] β = 0.26(K t -1); formula (6)

[0075] ​Y = 1.216 + 0.3224K t Equation (8)

[0076] wherein, η is a distance coefficient, W is the distance from the stress concentration part to the edge of the plate, that is, the width of the stress concentration part, and D is the depth of the stress concentration part.

[0077] However, the stress distribution functions described above still have great limitations in use, and their fitting accuracy may vary greatly with the model, so there is a problem that the calculated maximum stress value is inaccurate. Based on this, considering the complexity of the geometry of the component with the stress concentration part, some researchers refer to the above several models and establish a stress function with higher precision, which can be shown in the following formula (9):

[0078]

[0079] wherein, a1-a5 are the fitting coefficients of the stress function.

[0080] Further, although the above stress function has a wide range of applications, it also has the disadvantage of large amount of calculation, which makes the obtained maximum stress value inaccurate. In view of the problems existing in the above stress function, an improved stress distribution function with high fitting accuracy and relatively simple calculation is needed. In the process of actual application, by observing all the above stress distribution functions, only one stress concentration part root radius is involved in the structural parameters; however, through analysis, it can be found that the actual angle of the hole type stress concentration part, the number of stress concentration parts and the distance therebetween will all affect the stress distribution. Based on this, for the stress concentration part simulation piece in the example embodiment of the present disclosure, since the stress concentration part is a slant hole at a certain angle with the plane where the turbine blade is located, and two stress concentration parts are distributed on each stress concentration part simulation piece, the structure is more complex than the above-mentioned single stress concentration part plate piece. Therefore, when using the stress representation formula of the stress concentration part root (formula (9)), it is necessary to analyze the influence of the geometric structure difference between the stress concentration part simulation piece and the single stress concentration part plate piece on the stress distribution characteristics, that is, it is necessary to further improve the stress distribution function on the basis of the above-mentioned formula (9). The improved stress distribution function (i.e. the target stress distribution function) will be explained and described in the following text, and will not be further described here.

[0081] In the following, the prediction method of the high-cycle fatigue limit of the turbine blade stress concentration part shown in Figure 1 will be further explained and described. Specifically:

[0082] In step S110 , the root radius of the target stress concentration location is determined according to the geometric parameters of the target stress concentration location in the stress concentration location simulation component.

[0083] Specifically, the specific process of determining the root radius of the target stress concentration part can be achieved in the following way: constructing a turbine blade geometric model of a single-crystal turbine blade, and determining a stress concentration part simulation part based on the turbine blade geometric model; projecting the target stress concentration part in the stress concentration part simulation part onto the surface of the stress concentration part simulation part to obtain the stress concentration part projection result, and determining the semi-major axis and semi-minor axis of the stress concentration part projection result; calculating the cosine value of the stress concentration part angle of the target stress concentration part, and determining the root radius of the target stress concentration part based on the semi-major axis, semi-minor axis and the cosine value of the stress concentration part angle. Among them, the specific determination process of the stress concentration part simulation part can be achieved in the following ways: performing a blade static frequency analysis on the turbine blade geometric model to obtain a static frequency analysis result, and performing a dynamic frequency analysis based on the static frequency analysis result to obtain a dynamic frequency analysis result; constructing a dynamic frequency Campbell diagram based on the dynamic frequency analysis result, and analyzing the resonance margin of the turbine blade based on the dynamic frequency Campbell diagram; determining the stress concentration part of the turbine blade at the dangerous order based on the resonance margin, and constructing a characteristic simulation part of the stress concentration part; analyzing the vibration characteristics of the characteristic simulation part to obtain a vibration characteristic analysis result, and verifying the validity and vibration intensity of the characteristic simulation part based on the vibration characteristic analysis result to obtain a validity verification result and a vibration intensity verification result; when it is determined that the validity verification result and the vibration intensity verification result meet the preset conditions, the characteristic simulation part of the stress concentration part is used as the stress concentration part simulation part; wherein the obtained stress concentration part simulation part can refer to Figure 3 、 Figure 4 as well as Figure 5 shown; among them, Figure 3 is the stress concentration factor K t =1.6 of the pore simulation, Figure 4 is the stress concentration factor K t =2.0 simulation parts, Figure 5 is the stress concentration factor K t =2.4 simulation parts; at the same time, the preset conditions recorded here may include but are not limited to: material consistency, geometric similarity, similar stress concentration degree, and consistent principal stress distribution gradient.

[0084] The following will further explain and illustrate the specific process of determining the root radius of the target stress concentration site. Specifically, in the process of actual application, based on a large number of experiments, it can be known that when the ratio between the spacing between the two stress concentration sites in the stress concentration site simulation and the radius of the stress concentration site is greater than 3.5, the stress concentration interference effect will basically not occur between the two stress concentration sites; and the ratio between the spacing between the two stress concentration sites and the radius of the stress concentration site involved in the exemplary embodiment of the present disclosure is greater than 4, so the influence of the porous interference effect can be ignored, but the distance W between the stress concentration site and the edge of the plate needs to be corrected to the average value of the spacing between the stress concentration sites plus the length of the stress concentration site from the edge of the plate. At the same time, considering that the inclination and yaw angles of the stress concentration site of the simulation make the structure an inclined hole at a certain angle to the plane where the turbine blade is located, and the directionality of the inclined hole destroys the symmetry of the stress concentration distribution, the stress gradient direction also changes accordingly, so it is necessary to make necessary corrections to the existing stress distribution function. The projection of the stress concentration part on the surface of the simulation part is an ellipse. The major and minor axis parameters of the ellipse (that is, the projection result of the stress concentration part) can be equivalently treated as the root radius of the stress concentration part.

[0085] Furthermore, assuming that the semi-major axis and semi-minor axis of the projection result of the stress concentration part are a and b respectively, in order to more accurately characterize the geometric characteristics of the stress concentration part, the root radius r of the stress concentration part in the formula can be n Redefine it as the radius of curvature of the tip of the major axis of the ellipse, that is, r n =b 2 / a. In addition, since the structure of the stress concentration part is in a multiaxial stress state during the high cycle fatigue test, and the long axis of the projection result of the stress concentration part is not perpendicular to the stress direction in the actual test, the stress concentration part simulation is geometrically corrected, and the radius of the redefined stress concentration part is divided by Right now

[0086]

[0087] in, is the yaw angle of the stress concentration part; wherein, the yaw angles of the three stress concentration part simulation parts used in the high cycle fatigue test of the exemplary embodiment of the present disclosure are The data is shown in Table 1 below, which shows the semi-major axis a, semi-minor axis b of the projected ellipse of the stress concentration part with different stress concentration degrees and the corresponding stress concentration part root radius r in the exemplary embodiment of the present disclosure. n The specific values ​​of can be shown in Table 2 below.

[0088] Table 1 Geometric parameters and stress concentration coefficients of the simulated parts at stress concentration locations

[0089]

[0090] Table 2 Geometric parameters of stress concentration site projection ellipse

[0091]

[0092]

[0093] In step S120, a target stress distribution function is determined according to the target stress concentration site root radius, and a first maximum stress value of the target stress concentration site is determined according to the target stress distribution function.

[0094] In the example embodiments of the present disclosure, the obtained target stress distribution function can be shown in the following formula (11):

[0095]

[0096] wherein σ y (x) is the target stress distribution function, σ 1 max is the maximum value in the stress distribution (i.e., the first maximum stress value), a1, a2, a3, a4 are fitting coefficients, r n is the target stress concentration site root radius; a is the semi-major axis of the stress concentration site projection result, b is the semi-minor axis of the stress concentration site projection result, x is the distance between the stress point and the root of the target stress concentration site, and y is the stress point. That is, in the actual application process, considering that the depth and width of the stress concentration site will both affect the stress distribution of the root, the ratio of the semi-major axis a and the semi-minor axis b of the stress concentration site projection ellipse is used to replace the constant value of x / r n .

[0097] Secondly, the first maximum stress value σ 1 max of the target stress concentration site is determined according to the target stress distribution function. Specifically, in the actual application process, in order to verify the accuracy of the stress distribution function of different stress concentration site roots, ANSYS Workbench software can be used to carry out harmonic response analysis on simulation pieces of different stress concentration degrees, to obtain the vibration stress distribution results of the stress concentration site simulation piece under the first-order resonance, and then to determine the first maximum stress value based on the vibration stress distribution results. At the same time, by analyzing the vibration stress nephogram around the stress concentration site, the stress extraction paths of the critical distance theory midpoint method and the line method are determined. The vibration stress distribution extraction paths of the stress concentration site simulation pieces of the three stress concentration coefficients are as shown in Figure 6 、 Figure 7 and Figure 8As shown by the arrow in ; Figure 6 K t =1.6, the vibration stress distribution extraction path of the stress concentration part simulation part, Figure 7 K t = 2.0, the vibration stress distribution extraction path of the stress concentration part simulation part, Figure 8 K t =2.4 vibration stress distribution extraction path of the stress concentration part simulation part.

[0098] The nonlinear curve fitting module in the Origin program was used to fit the simulation data based on the above function and obtain the final fitting coefficients. The coefficient results and the degree of fit are shown in Table 3.

[0099] Table 3 Fitting coefficients and fitting degree

[0100]

[0101]

[0102] At the same time, each parameter is substituted into each stress distribution function mentioned above to obtain the stress distribution function predicted by each formula. The vibration stress simulation results around the stress concentration part of the stress concentration part simulation part are compared with the prediction results of each formula. The results are as follows Figure 9 、 Figure 10 as well as Figure 11 shown; among them, Figure 9 K t =1.6 stress concentration part simulation stress result comparison chart, Figure 10 K t = 2.0 stress concentration part simulation stress result comparison chart, Figure 11 K t = 2.4 stress concentration part simulation stress results comparison chart. Figures 9-11 It can be seen that after the stress around the stress concentration part of the stress concentration part simulation part is normalized, the stress distribution function at the root of the stress concentration part shows a trend consistent with the finite element simulation results, that is, the normalized stress value decreases monotonically with the increase of the distance from the stress concentration part, and the slope also gradually decreases. However, the stress distribution functions at the root of the first three classic stress concentration parts all show a certain degree of "offset", which is quite different from the finite element simulation results of the actual stress distribution. t = 1.6, the predicted offset mainly occurs after 0.1mm, while for the other two stress concentration part simulations, the offset covers the entire distance within 0.5mm around the stress concentration part. 2 as well as Figure 4 Based on the comparative analysis, the function expression (i.e., the target stress distribution function) proposed in the present invention performs best in terms of stress distribution fitting accuracy at the root of the stress concentration part. It can be combined with the point method and line method in the critical distance theory to predict the high-cycle fatigue limit of the simulated parts at the stress concentration part.

[0103] In step S130 , a reference stress value of the target stress concentration location is determined, and a stress concentration coefficient of the target stress concentration location is determined based on the reference stress value and the first maximum stress value.

[0104] In this exemplary embodiment, first, the reference stress value σ of the target stress concentration location is determined. n ; Among them, the reference stress σ n There are many ways to select the base stress. Different base stress selection methods will significantly affect the calculation results of the stress concentration factor. Therefore, when using the stress concentration factor, the selection criteria of the base stress should be clear. Based on the theory of continuum elastic mechanics, the calculation of the stress concentration factor usually selects the nominal stress as the base stress σ n However, Neuber pointed out that when the root radius of the stress concentration part decreases, the stress concentration factor K calculated based on continuum elastic mechanics t The stress concentration at the root of the actual stress concentration site may be overestimated. This finding indicates that there is a large deviation between the theoretically calculated value and the experimental results. Therefore, the exemplary embodiment of the present disclosure comprehensively considers the actual engineering requirements of the aircraft engine turbine blade and the stress gradient around the stress concentration site, and selects the average stress value of the stress distribution curve in the direction of the main stress gradient as the reference stress. The specific calculation process can be shown in the following formula (12):

[0105]

[0106] Among them, a n is the selected calculation path length; at the same time, the specific selection process of the calculation path length can be referred to Figure 12 shown.

[0107] Secondly, the stress concentration coefficient of the target stress concentration part is determined according to the reference stress value and the first maximum stress value. Specifically, this can be achieved by the following methods: first, the principal stress gradient direction is determined according to the stress distribution around the target stress concentration part; secondly, the calculation path length a is determined. n and a n+1 , and calculate the path length a n and a n+1The corresponding nth reference stress value and n+1th reference stress value are calculated; then, the nth stress concentration coefficient corresponding to the nth reference stress value and the n+1th stress concentration coefficient corresponding to the n+1th reference stress value are calculated; further, the change rate between the nth stress concentration coefficient and the n+1th stress concentration coefficient is determined. If the change rate is less than a preset threshold of 0.5%, the nth stress concentration coefficient is used as the stress concentration coefficient of the target stress concentration location; otherwise, the calculation path length is reselected until the change rate is less than the preset threshold of 0.5%. The specific determination process of the stress concentration coefficient can be shown by the following formula (13):

[0108]

[0109] Among them, K t is the stress concentration factor, σ 1 max is the first maximum stress value, σ n is the baseline stress value.

[0110] In step S140, a second maximum stress value of the target stress concentration location is determined according to the stress concentration coefficient, and a fatigue limit of the simulated component of the stress concentration location is predicted according to the second maximum stress value.

[0111] In this example embodiment, first, the second maximum stress value is determined; specifically, the specific process of determining the second maximum stress value can be implemented based on the point method critical distance and / or the line method critical distance. Determining the second maximum stress value based on the point method critical distance can be implemented as follows: determining the original point method critical distance of the target stress concentration location based on the material of the stress concentration location simulation part, and correcting the original point method critical distance based on the stress concentration coefficient to obtain a corrected point method critical distance; determining the second maximum stress value of the target stress concentration location when it is in a critical state of fatigue failure based on the corrected point method critical distance. Further, determining the second maximum stress value based on the line method critical distance can be implemented as follows: determining the original line method critical distance of the target stress concentration location based on the material of the stress concentration location simulation part, and correcting the original line method critical distance based on the stress concentration coefficient to obtain a corrected line method critical distance; determining the second maximum stress value of the target stress concentration location when it is in a critical state of fatigue failure based on the corrected line method critical distance.

[0112] Secondly, the fatigue limit of the simulated component at the stress concentration location is predicted based on the second maximum stress value. Specifically, this can be achieved by calculating the ratio between the second maximum stress value and the stress concentration coefficient, and determining the fatigue limit value of the simulated component at the stress concentration location based on the ratio between the second maximum stress value and the stress concentration coefficient.

[0113] The following will further explain and illustrate the specific process of determining the second maximum stress value and the specific process of predicting the fatigue limit. Specifically, in the actual application process, first, by introducing the stress concentration factor K t The critical distance L of the point method and line method in the critical distance theory is corrected; the specific correction process can be shown in the following formula (14):

[0114]

[0115] Where, L * PM is the corrected point method critical distance, L * LM is the modified critical distance of the line method. At the same time, by introducing the stress concentration factor K t The correction method of the stress concentration part simulation parts with different stress concentration degrees can be shown in Table 4 below.

[0116] Table 4 Corrected critical distance

[0117]

[0118] Furthermore, the corrected point method critical distance L * PM Substituting into the point method expression in TCD theory shown in the following formula (15), the second maximum stress value can be obtained:

[0119] σ y (L * PM )=σ0; Formula (15)

[0120] From formula (15), we can know that when the simulated component at the stress concentration part is in the critical state of fatigue failure, the maximum stress value σ around the stress concentration part is determined as 2 max (i.e. the second maximum stress value). Due to the stress concentration factor K recorded in the exemplary embodiment of the present disclosure t The calculation formula is the ratio of maximum stress to nominal stress, so the maximum stress value σ around the stress concentration part can be used to calculate the max Divide by the stress concentration factor K tThe fatigue limit of the stress concentration part can be obtained by the ratio of , and the relative error δ can be calculated by combining the fatigue limit measured by the test. The specific formula can be shown as follows (16):

[0121]

[0122] Among them, Δσ e is the fatigue limit value measured by the test, Δσ p is the fatigue limit value predicted by the formula. At the same time, based on the point method after the correction of the critical distance and combined with the stress distribution function proposed in this paper, the corresponding normalized stress is calculated as its effective stress by firstly using the point method critical distance corresponding to the stress concentration part simulation parts with different stress concentration degrees. The results are as follows: Figure 13 As shown. Figure 13 It can be seen that K t The normalized stress of the simulated stress concentration part with K = 1.6 at its point method critical distance is 0.63233; t The normalized stress of the simulated stress concentration part with K = 2.0 at its point method critical distance is 0.60019; t The normalized stress of the simulated component at the stress concentration location with =2.4 at its point method critical distance is 0.61223.

[0123] The normalized stress is used as the effective stress at the critical distance of the stress concentration location simulation component of each stress concentration coefficient, and the maximum stress value at the root of the stress concentration location is calculated according to formula (13). The maximum stress value is divided by the stress concentration coefficient K. t The corresponding fatigue limit prediction values ​​are obtained, as shown in Table 5 below.

[0124] Table 5 Fatigue limit predicted by point method

[0125]

[0126] For three stress concentration location simulation parts with different stress concentration factors, the fatigue limit prediction errors of the point method after correcting the critical distance are 11.49%, 10.02%, and 5.7%, respectively, which are lower than the allowable error range of 15%. Therefore, the point method after correcting the critical distance is an effective fatigue limit prediction method.

[0127] Similarly, according to the above modified line method critical distance L * LM , and substituting it into the line method expression in TCD theory shown in the following formula (17), the second maximum stress value can be obtained:

[0128] σ y (L * LM )=σ0; Formula (17)

[0129] Based on the line method after the correction of the critical distance and combined with the stress distribution function proposed in this paper, the normalized average stress within the corresponding critical distance is calculated by the line method critical distance corresponding to the stress concentration part simulation parts with different stress concentration degrees, and it is used as the effective stress. The results are as follows Figure 14 As shown. Figure 14 It can be seen that K t The average normalized stress of the stress concentration part simulation part with K = 1.6 at its line method critical distance is 0.61430; t The average normalized stress of the stress concentration part simulation part with K = 2.0 at its line method critical distance is 0.58307; t = 2.4, the average normalized stress of the stress concentration part simulation piece at its line method critical distance is 0.56185. This average normalized stress is used as the effective stress of the stress concentration part simulation piece at the corresponding line method critical distance of each stress concentration coefficient. The maximum stress value at the root of the stress concentration part is calculated according to formula (15), and this maximum stress value is divided by the stress concentration coefficient K t The corresponding fatigue limit is obtained. The fatigue limit results of the simulated parts at the stress concentration location predicted by the modified critical distance posterior line method are shown in Table 6.

[0130] Table 6 Fatigue limit predicted by line method

[0131]

[0132] Table 6 shows that for the three stress concentration location simulation parts with different stress concentration factors, the fatigue limit prediction errors of the line method after correcting the critical distance are 14.92%, 13.25%, and 2.71%, respectively, which are lower than the allowable error range of 15%. Therefore, the line method after correcting the critical distance can be used as an effective fatigue limit prediction method.

[0133] Figure 15 The comparison of prediction results of different fatigue limit quantitative characterization methods is shown, including the point method and line method based on the improved critical distance theory and the fatigue limit prediction formula based on the Neuber and Peterson classic model. The horizontal axis in the figure is the fatigue limit measured by the test, and the vertical axis is the fatigue limit predicted by the formula, both in MPa. Figure 14 It can be seen that for the stress concentration factor K t = 1.6, the point method and line method in the critical distance theory have the highest prediction accuracy, and the data points are closest to the isovalue lines in the figure; for the stress concentration factor K t =2.0 and K t= 2.4, the prediction accuracy of both is within the 15% error band. However, the prediction results of the high-cycle fatigue limit of the stress concentration part of the turbine blade with three stress concentration levels by the line method are generally biased towards the dangerous side, and are all higher than the actual fatigue limit; in contrast, the point method is not very effective in predicting K t =1.6 stress concentration part of the simulated fatigue limit is too small, while for K t = = 2.0 and K t = = 2.4 stress concentration area simulation fatigue limit prediction is slightly higher. This prediction error may come from the fatigue crack growth threshold value ΔK of DD5 alloy used in this paper. th It is based on the approximate value of directionally solidified high-temperature alloys provided in the literature, and is not accurately measured by conducting surface crack threshold tests, which may lead to certain deviations in the calculation of the critical distance L, affecting the accuracy of the prediction results. In addition, the prediction results of the Neuber and Peterson classic model are generally conservative, significantly lower than the fatigue limit measured in the experiment, and exceed the 15% error band. Through analysis, it is believed that there are two main reasons for the large prediction error of this model: First, although this method takes into account the influence of the sensitivity of the stress concentration site on the fatigue performance of the stress concentration site, it is mainly based on the maximum stress value at the root of the stress concentration site, and does not fully consider the stress concentration coefficient K. t In addition, the complex stress field around the stress concentration area actually affects fatigue performance. Secondly, the material constant a used in the model is derived from an empirical formula rather than through precise experimental measurement. This may result in errors in applicability and accuracy for different types of materials, thus affecting the accuracy of the prediction results.

[0134] The following are embodiments of the apparatus disclosed herein, which can be used to implement the method embodiments disclosed herein. For details not disclosed in the apparatus embodiments disclosed herein, please refer to the method embodiments disclosed herein.

[0135] The exemplary embodiment of the present disclosure also provides a device for predicting the high cycle fatigue limit of a stress concentration portion of a turbine blade. Figure 16 As shown, the device for predicting the high-cycle fatigue limit of a stress concentration site of a turbine blade may include a stress concentration site root radius determination module 1610, a first stress value determination module 1620, a stress concentration coefficient determination module 1630, and a fatigue limit prediction module 1640. Among them:

[0136] The stress concentration location root radius determination module 1610 may be configured to determine the root radius of the target stress concentration location according to the geometric parameters of the target stress concentration location in the stress concentration location simulation component;

[0137] The first stress value determination module 1620 can be configured to determine a target stress distribution function according to the root radius of the target stress concentration site, and determine a first maximum stress value of the target stress concentration site according to the target stress distribution function.

[0138] The stress concentration coefficient determination module 1630 can be configured to determine a reference stress value of the target stress concentration site, and determine a stress concentration coefficient of the target stress concentration site according to the reference stress value and the first maximum stress value.

[0139] The fatigue limit prediction module 1640 can be configured to determine a second maximum stress value of the target stress concentration site according to the stress concentration coefficient, and predict a fatigue limit of the stress concentration site simulation according to the second maximum stress value.

[0140] In an example embodiment of the present disclosure, the root radius of the target stress concentration site is determined according to the geometric parameters of the target stress concentration site in the stress concentration site simulation, including: constructing a turbine blade geometric model of a single crystal turbine blade, and determining a stress concentration site simulation according to the turbine blade geometric model; projecting the target stress concentration site in the stress concentration site simulation on a surface of the stress concentration site simulation to obtain a stress concentration site projection result, and determining a major semi-axis and a minor semi-axis of the stress concentration site projection result; calculating a cosine value of a stress concentration site angle of the target stress concentration site, and determining the root radius of the target stress concentration site according to the major semi-axis, the minor semi-axis and the cosine value of the stress concentration site angle.

[0141] In an example embodiment of the present disclosure, the stress concentration site simulation is determined according to the turbine blade geometric model, including: performing a blade static frequency analysis on the turbine blade geometric model to obtain a static frequency analysis result, and performing a dynamic frequency analysis according to the static frequency analysis result to obtain a dynamic frequency analysis result; constructing a dynamic frequency Campbell diagram according to the dynamic frequency analysis result, and analyzing a resonance margin of the turbine blade based on the dynamic frequency Campbell diagram; determining a stress concentration site of the turbine blade under a dangerous order according to the resonance margin, and constructing a feature simulation of the stress concentration site; analyzing vibration characteristics of the feature simulation to obtain a vibration characteristic analysis result, and verifying effectiveness and vibration intensity of the feature simulation according to the vibration characteristic analysis result to obtain an effectiveness verification result and a vibration intensity verification result; when it is determined that the effectiveness verification result and the vibration intensity verification result satisfy a preset condition, taking the feature simulation of the stress concentration site as the stress concentration site simulation.

[0142] In an example embodiment of the present disclosure, the target stress distribution function is determined according to the root radius of the target stress concentration site, comprising:

[0143]

[0144] wherein σ y (x) is the target stress distribution function, σ max is the maximum value in the stress distribution, a1, a2, a3, a4 are fitting coefficients, r n is the root radius of the target stress concentration site; a is the semi-major axis of the projection result of the stress concentration site, b is the semi-minor axis of the projection result of the stress concentration site, x is the distance between the stress point and the root of the target stress concentration site, and y is the stress point.

[0145] In an example embodiment of the present disclosure, the second maximum stress value of the target stress concentration site is determined according to the stress concentration coefficient, comprising: determining the original point method critical distance of the target stress concentration site according to the material of the stress concentration site simulation piece, and correcting the original point method critical distance according to the stress concentration coefficient to obtain a corrected point method critical distance; and determining the second maximum stress value of the target stress concentration site when in a critical state of fatigue failure according to the corrected point method critical distance.

[0146] In an example embodiment of the present disclosure, the second maximum stress value of the target stress concentration site is determined according to the stress concentration coefficient, further comprising: determining the original line method critical distance of the target stress concentration site according to the material of the stress concentration site simulation piece, and correcting the original line method critical distance according to the stress concentration coefficient to obtain a corrected line method critical distance; and determining the second maximum stress value of the target stress concentration site when in a critical state of fatigue failure according to the corrected line method critical distance.

[0147] In an example embodiment of the present disclosure, the fatigue limit of the stress concentration site simulation piece is predicted according to the second maximum stress value, comprising: calculating the ratio between the second maximum stress value and the stress concentration coefficient, and determining the fatigue limit value of the stress concentration site simulation piece according to the ratio between the second maximum stress value and the stress concentration coefficient.

[0148] The specific details of each module in the above-described turbine blade stress concentration site high-cycle fatigue limit prediction device have been described in detail in the corresponding turbine blade stress concentration site high-cycle fatigue limit prediction method, and therefore will not be described here again.

[0149] It should be noted that, although several modules or units of the devices for action execution are mentioned in the above detailed description, such division is not mandatory. Indeed, according to an embodiment of the disclosure, the features and functionalities of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functionalities of one module or unit described above can be further divided into embodied by multiple modules or units.

[0150] Furthermore, although the various steps of the methods in the disclosure are described in a particular order in the drawings, this is not required or implied as to the particular order of execution of the steps, nor is it required that all of the steps shown be executed in order to achieve the desired result. Additionally or alternatively, certain steps can be omitted, multiple steps can be combined into one step, one step can be broken into multiple steps, etc.

[0151] Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the features of the disclosure as set forth herein. It is intended that the specification and examples be considered as exemplary only, with the true scope and spirit of the disclosure being indicated by the claims.

Claims

1. A method for predicting the high-cycle fatigue limit of a stress concentration area of ​​a turbine blade, characterized in that: include: determining a root radius of a target stress concentration location according to geometric parameters of the target stress concentration location in the stress concentration location simulation component; determining a target stress distribution function according to a root radius of the target stress concentration location, and determining a first maximum stress value of the target stress concentration location according to the target stress distribution function; determining a reference stress value of the target stress concentration location, and determining a stress concentration factor of the target stress concentration location based on the reference stress value and the first maximum stress value; The second maximum stress value of the target stress concentration location is determined according to the stress concentration coefficient, and the fatigue limit of the simulated component of the stress concentration location is predicted according to the second maximum stress value.

2. The method for predicting the high cycle fatigue limit of a stress concentration area of ​​a turbine blade according to claim 1, characterized in that: According to the geometric parameters of the target stress concentration location in the stress concentration location simulation part, the root radius of the target stress concentration location is determined, including: Constructing a turbine blade geometric model of a single crystal turbine blade, and determining a simulation part of a stress concentration location based on the turbine blade geometric model; Projecting the target stress concentration location in the stress concentration location simulation piece onto the surface of the stress concentration location simulation piece to obtain a stress concentration location projection result, and determining a semi-major axis and a semi-minor axis of the stress concentration location projection result; The cosine value of the angle of the target stress concentration location is calculated, and the root radius of the target stress concentration location is determined according to the semi-major axis, the semi-minor axis, and the cosine value of the angle of the stress concentration location.

3. The method for predicting the high cycle fatigue limit of a stress concentration area of ​​a turbine blade according to claim 2, characterized in that: Determining a stress concentration location simulation part according to the turbine blade geometric model includes: Performing a blade static frequency analysis on the turbine blade geometric model to obtain a static frequency analysis result, and performing a dynamic frequency analysis based on the static frequency analysis result to obtain a dynamic frequency analysis result; constructing a dynamic frequency Campbell diagram according to the dynamic frequency analysis result, and analyzing the resonance margin of the turbine blade based on the dynamic frequency Campbell diagram; determining a stress concentration location of the turbine blade at a dangerous order according to the resonance margin, and constructing a characteristic simulation part of the stress concentration location; Analyzing the vibration characteristics of the characteristic simulation component to obtain a vibration characteristic analysis result, and verifying the validity and vibration intensity of the characteristic simulation component based on the vibration characteristic analysis result to obtain a validity verification result and a vibration intensity verification result; When it is determined that the validity verification result and the vibration intensity verification result meet the preset conditions, the characteristic simulation part of the stress concentration part is used as the stress concentration part simulation part.

4. The method for predicting the high cycle fatigue limit of a stress concentration area of ​​a turbine blade according to claim 1, characterized in that: Determining a target stress distribution function according to the root radius of the target stress concentration location includes: Among them, σ y (x) is the target stress distribution function, σ max is the maximum value in the stress distribution, a1, a2, a3 and a4 are fitting coefficients, r n is the root radius of the stress concentration location; a is the semi-major axis of the projection result of the stress concentration location, b is the semi-minor axis of the projection result of the stress concentration location, x is the distance between the stress point and the root of the target stress concentration location, and y is the stress point.

5. The method for predicting the high cycle fatigue limit of a stress concentration portion of a turbine blade according to claim 1, characterized in that: Determining a second maximum stress value of the target stress concentration location according to the stress concentration coefficient includes: Determining the original point method critical distance of the target stress concentration location according to the material of the stress concentration location simulation component, and correcting the original point method critical distance according to the stress concentration coefficient to obtain a corrected point method critical distance; The second maximum stress value of the target stress concentration location when it is in a critical state of fatigue failure is determined according to the corrected point method critical distance.

6. The method for predicting the high cycle fatigue limit of a stress concentration area of ​​a turbine blade according to claim 1, characterized in that: Determining a second maximum stress value of the target stress concentration location according to the stress concentration coefficient also includes: determining an original line method critical distance of the target stress concentration location according to the material of the stress concentration location simulation component, and correcting the original line method critical distance according to the stress concentration coefficient to obtain a corrected line method critical distance; The second maximum stress value of the target stress concentration location when it is in a critical state of fatigue failure is determined according to the corrected line method critical distance.

7. The method for predicting the high cycle fatigue limit of a stress concentration portion of a turbine blade according to claim 1, characterized in that: The fatigue limit of the simulated component at the stress concentration location is predicted based on the second maximum stress value, including: The ratio of the second maximum stress value to the stress concentration factor is calculated, and the fatigue limit value of the stress concentration location simulation component is determined according to the ratio of the second maximum stress value to the stress concentration factor.

8. A device for predicting the high cycle fatigue limit of a stress concentration area of ​​a turbine blade, characterized in that: include: A stress concentration location root radius determination module, configured to determine the root radius of the target stress concentration location according to the geometric parameters of the target stress concentration location in the stress concentration location simulation component; a first stress value determination module, configured to determine a target stress distribution function according to a root radius of the target stress concentration location, and determine a first maximum stress value of the target stress concentration location according to the target stress distribution function; a stress concentration coefficient determination module, configured to determine a reference stress value of the target stress concentration location, and determine the stress concentration coefficient of the target stress concentration location based on the reference stress value and the first maximum stress value; A fatigue limit prediction module is used to determine the second maximum stress value of the target stress concentration location according to the stress concentration coefficient, and predict the fatigue limit of the simulated part of the stress concentration location according to the second maximum stress value.

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