Low-cycle fatigue life prediction method and system suitable for directionally solidified turbine blade

Abstract

The invention discloses a low-cycle fatigue life prediction method and system suitable for a directional solidification turbine blade, and relates to the technical field of gas turbine key component life determination, and the method comprises the steps: obtaining to-be-measured data of the directional solidification turbine blade; the data to be measured comprises elastic modulus and low-cycle fatigue performance data; calculating an orientation factor based on the elastic modulus; determining effective strain energy density based on the low-cycle fatigue performance data; and calculating the predicted low-cycle fatigue life of the directionally solidified turbine blade based on the orientation factor and the effective strain energy density. The method can improve the prediction precision of the low-cycle fatigue life of the directional solidification turbine blade.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of gas turbine key component life determination, in particular to a low-cycle fatigue life prediction method and system suitable for directional solidification turbine blades. BACKGROUND

[0002] Under the background of accelerating global energy transformation, gas turbines have become the core equipment for coordinating power grid peak shaving demand and renewable energy fluctuation due to their high efficiency, flexibility and low carbon. Especially in the current situation of large-scale access of renewable energy and continuous rise of power system peak shaving demand, the importance of heavy-duty gas turbines is increasingly prominent. Among the many key structural components of heavy-duty gas turbines, the turbine blade at the hot end is in the most severe service environment. This component is subjected to high temperature, high pressure, strong oxidation and cyclic loading for a long time, and its mechanical properties and service life are directly related to the thermal efficiency, power output and operation reliability of the whole system. To adapt to this extreme service condition, turbine blade materials are required to have excellent high-temperature mechanical properties, high creep fatigue strength and good oxidation and corrosion resistance. Based on these requirements, turbine blade materials have gradually changed from traditional cast polycrystalline alloys to advanced directional solidification alloys or single crystal alloys. Compared with traditional cast polycrystalline alloys, directional solidification alloys are solidified along the maximum principal stress direction (usually

[001] crystal direction), effectively eliminating transverse grain boundaries, significantly improving the fatigue resistance and creep fracture strength of the material at high temperature, and prolonging the service life of the component. Directional solidification has become the mainstream material for current gas turbine hot-end components. However, although directional solidification improves the overall high-temperature mechanical properties of the material, the unique structure also causes significant crystal anisotropy. That is, under the same loading conditions and environmental conditions, the fatigue response of the material differs significantly due to different crystal orientations. This anisotropic behavior poses a great challenge to fatigue life assessment and service reliability prediction, especially under low-cycle fatigue conditions, where the life difference between different crystal orientations can be more than one order of magnitude. At this time, if the traditional evaluation method based on isotropic assumption is still used, it will lead to serious misjudgment of the fatigue life.

[0003] Therefore, how to introduce the influence of anisotropy on material performance into the fatigue life prediction model becomes a key problem for constructing a life assessment method suitable for directionally solidified alloys. Current research shows that there is a clear physical correlation between the elastic modulus and the crystal orientation. Based on this, domestic and foreign scholars have proposed the orientation factor method, which uses elastic modulus to represent different crystal orientations of the material, and then introduces the influence of anisotropy on life into the life prediction model. However, the current mainstream anisotropic material life prediction model constructed by using the orientation factor method is mostly based on empirical formula, and lacks clear physical meaning support. And when facing advanced materials with very small plastic component in macroscopic strain and only local plastic strain response, such models often fail to accurately capture the mechanism of dominant fatigue damage, resulting in low prediction accuracy of low cycle fatigue life of directionally solidified turbine blades. SUMMARY

[0004] The purpose of the present application is to provide a low cycle fatigue life prediction method and system suitable for directionally solidified turbine blades, which can improve the prediction accuracy of low cycle fatigue life of directionally solidified turbine blades.

[0005] To achieve the above-mentioned purpose, the present application provides the following solutions.

[0006] In a first aspect, the present application provides a low cycle fatigue life prediction method suitable for directionally solidified turbine blades, comprising: obtaining test data of a directionally solidified turbine blade; the test data includes elastic modulus and low cycle fatigue performance data; the elastic modulus includes: elastic modulus in crystal direction and elastic modulus in crystal direction; , and respectively represent the smallest integer that is relatively prime to the component of any lattice vector along this direction on the cell base vector , and ; calculating an orientation factor based on the elastic modulus; determining an effective strain energy density based on the low cycle fatigue performance data; calculating the predicted low cycle fatigue life of the directionally solidified turbine blade based on the orientation factor and the effective strain energy density.

[0007] In a second aspect, the present application provides a low cycle fatigue life prediction system suitable for directionally solidified turbine blades, comprising the following modules.

[0008] The acquisition module is configured to obtain test data of a directionally solidified turbine blade; the test data includes elastic modulus and low cycle fatigue performance data; the elastic modulus includes: elastic modulus in crystal direction and elastic modulus in crystal direction; , and respectively represent the minimum integers relatively prime to the components of any lattice vector along the direction in the cell base vectors , and .

[0009] an orientation factor calculation module, configured to calculate an orientation factor based on the elastic modulus.

[0010] an effective strain energy density determination module, configured to determine an effective strain energy density based on the low cycle fatigue performance data.

[0011] a low cycle fatigue life prediction module, configured to calculate a predicted low cycle fatigue life of the directionally solidified turbine blade based on the orientation factor and the effective strain energy density.

[0012] According to the specific embodiments provided in the application, the application has the following technical effects.

[0013] The application combines the advantages of the orientation factor method and the effective strain energy density model, is based on the theoretical basis that there is a clear physical relationship between the elastic modulus and the crystal orientation, uses the elastic modulus to construct the orientation factor (which has crystal direction and crystal direction) representing anisotropy, and introduces it into the effective strain energy density as a damage parameter to predict the low cycle fatigue life, and establishes a low cycle fatigue life prediction method with clear physical meaning, less data requirement, and suitable for practical engineering application. The method can effectively reflect the influence of the anisotropy of different crystal orientations of the directionally solidified material on the fatigue life, thereby realizing unified, accurate and reliable prediction of the low cycle fatigue life of different orientations of the directionally solidified turbine blade. BRIEF DESCRIPTION OF DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the application or the related art, the following will briefly introduce the drawings needed to be used in the embodiments. Obviously, the drawings in the following description only constitute some embodiments of the application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0015] Figure 1 It is a flowchart of a low cycle fatigue life prediction method suitable for a directionally solidified turbine blade in the application.

[0016] Figure 2 It is a detailed flowchart of a low cycle fatigue life prediction method suitable for a directionally solidified turbine blade provided in Embodiment One in the application.

[0017] Figure 3A schematic diagram of effective strain energy density for typical low cycle fatigue hysteresis loop in Example 1.

[0018] Figure 4 A schematic diagram of comparison between predicted low cycle fatigue life and experimental life for UGTC47 alloy in Example 1 using effective strain energy density model.

[0019] Figure 5 A schematic diagram of comparison between predicted low cycle fatigue life and experimental life for UGTC47 alloy in Example 1 using the method of the present application.

[0020] Figure 6 A schematic diagram of functional modules of a low cycle fatigue life prediction system for directional solidification turbine blade provided in another embodiment of the present application. DETAILED DESCRIPTION

[0021] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0022] In order to make the above objectives, characteristics and advantages of the present application more apparent, the present application will be further described in detail below with reference to the drawings and specific embodiments.

[0023] In an exemplary embodiment, as shown in Figure 1 , a low cycle fatigue life prediction method for directional solidification turbine blade is provided, which is executed by a computer device, specifically, can be executed by a terminal or a server, or can be executed by a terminal and a server together, in the embodiments of the present application, the method is applied to the server as an example, and includes the following steps S1 to S8.

[0024] Step S1: obtaining measured data of the directional solidification turbine blade; the measured data includes elastic modulus and low cycle fatigue performance data; the elastic modulus includes elastic modulus in direction and elastic modulus in direction. , and respectively represent the smallest integer proportional to any lattice vector in the direction and the component on the cell base vector , and .

[0025] Specifically, high temperature tensile data and low cycle fatigue performance data of the directional solidification turbine blade in typical characteristic orientations are collected.

[0026] High-temperature tensile and strain-controlled low-cycle fatigue performance tests were conducted on directionally solidified turbine blade material samples to obtain tensile and low-cycle fatigue performance data at typical characteristic orientations, namely

[001] crystal orientation and non-

[001] crystal orientation (i.e. Crystal orientation), high-temperature tensile data are elastic modulus. Low-cycle fatigue performance data include steady-cycle hysteresis loops and low-cycle fatigue stress-life curves.

[0027] Step S2: Calculate the orientation factor based on the elastic modulus.

[0028] The formula for calculating the orientation factor is as follows.

[0029] .

[0030] in, Orientation factor; In order to be in Elastic modulus in the crystal direction In order to be in Elastic modulus in the crystallographic direction.

[0031] Specifically, in order to reflect the influence of anisotropic characteristics caused by different crystal orientations of materials on fatigue life, researchers found that, according to the theory of anisotropic elasticity, for nickel-based directionally solidified alloys used in the directionally solidified turbine blades of gas turbines, since their microcrystalline structure belongs to a face-centered cubic structure, i.e., a face-centered cubic lattice (FCC), the elastic modulus in the

[001] crystal direction can be used theoretically. Poisson's ratio in the

[001] crystal orientation and shear modulus in the

[001] crystal direction , deduced Crystal Orientation elastic modulus The derived formula is defined as follows.

[0032] .

[0033] Using the above formula, the elastic modulus under any crystal orientation can be accurately derived for a directionally solidified turbine blade under the condition of knowing the relevant parameters of the

[001] crystal orientation, thus establishing a quantitative relationship between crystal orientation and elastic modulus. Since the anisotropic characteristics of materials originate from the differences in crystal orientation, this theory provides a solid theoretical basis for using elastic modulus to characterize the influence of material anisotropy on fatigue life.

[0034] An orientation factor that reflects the effects of anisotropy is constructed based on the ratio of elastic moduli of typical characteristic orientations. to provide a basis for subsequent correction of the life prediction model.

[0035] Step S3: determining the effective strain energy density based on the low-cycle fatigue performance data.

[0036] As a specific embodiment, step S3 includes steps S31-S34.

[0037] Step S31: determining the total elastic strain range and the total plastic strain range based on the stable cycle hysteresis loop.

[0038] Step S32: determining the total stress and the effective stress based on the low-cycle fatigue stress-life curve.

[0039] Step S33: calculating the effective elastic strain range based on the total elastic strain range, the total stress and the effective stress.

[0040] The formula for calculating the effective elastic strain range is as follows.

[0041] .

[0042] wherein, is the effective elastic strain range; is the effective stress; is the total stress; is the total elastic strain range.

[0043] Specifically, the low-cycle fatigue stress-life curve is constructed according to the results of the low-cycle fatigue performance test of the directional solidification material sample obtained in step S1. When the fatigue life remains basically unchanged with the decrease of the stress, the stress at this time is the fatigue limit stress. In order to facilitate calculation, the stress when the fatigue life reaches times is defined as the fatigue limit stress. The stress exceeding the fatigue limit stress is defined as the effective stress . Through the hysteresis loop analysis of the material, the effective elastic strain range is determined.

[0044] Step S34: calculating the effective strain energy density based on the total plastic strain range, the effective elastic strain range and the effective stress.

[0045] The formula for calculating the effective strain energy density is as follows.

[0046] .

[0047] wherein, is the effective strain energy density; is the effective stress; is the effective elastic strain range; is the total plastic strain range.

[0048] Step S4: Calculate the predicted low-cycle fatigue life of the directionally solidified turbine blade based on the orientation factor and the effective strain energy density.

[0049] The formula for calculating the predicted low-cycle fatigue life of the directionally solidified turbine blade is as follows.

[0050] .

[0051] wherein, is the predicted low-cycle fatigue life of the directionally solidified turbine blade; is the orientation factor; is the effective strain energy density; , and are fitting parameters.

[0052] Example One This example is directed to the low-cycle fatigue life prediction of anisotropic directionally solidified turbine blades. The nickel-based high-temperature alloy UGTC47 material is selected as the research object, and the material is prepared by the directional solidification process. The test object is a standard smooth cylindrical sample. Key parameters are obtained through high-temperature tensile and strain-controlled low-cycle fatigue tests, and the method described in this application is used for life prediction at different orientations. As shown in FIG. 1, the specific steps are as follows. Figure 2

[0053] Step one, respectively, carry out the high-temperature tensile test and fatigue test of the material.

[0054] For UGTC47 alloy smooth samples, follow the relevant provisions of the national standard GB / T 228.2-2015 "Metallic Materials Tensile Test Part 2 High Temperature Test Method", respectively, carry out high-temperature tensile test on UGTC47 material longitudinal (L direction), that is,

[001] crystal direction and transverse (T direction) (that is, non-

[001] crystal direction) samples, the test temperature is 750℃, and the elastic modulus of UGTC47 alloy L direction and T direction two characteristic orientation smooth samples are obtained after the test, as shown in Table 1.

[0055] Table 1 Elastic modulus of UGTC47 alloy characteristic orientation smooth samples at 750℃

[0056] The low-cycle fatigue test of UGTC47 alloy follows the relevant provisions of the national standard GB / T 15248-2008 "Metallic Materials Axial Constant Amplitude Low Cycle Fatigue Test Method". The control mode adopts strain control, the test temperature is set to 750℃, the strain ratio is , and the strain rate is 0.001 (mm / mm) / s. The corresponding fatigue life of the samples of two characteristic orientations at different experimental strain levels is obtained, as shown in Table 2. ​

[0057] Table 2 Low cycle fatigue life of UGTC47 alloy smooth samples with characteristic orientation at 750℃

[0058] Step two, according to the high temperature tensile test, the orientation factor of the orientation to be measured is constructed.

[0059] The low cycle fatigue life prediction method of the present application is used to evaluate the unified parameters of the low cycle fatigue life of UGTC47 alloy with different orientations. First, the orientation factor of the typical characteristic orientation to be evaluated of the material needs to be determined. According to the results of the high temperature tensile test of the UGTC47 alloy material sample in step one, the L direction of the material, i.e. the

[001] crystal direction, is set as the reference direction, and the orientation factor is calculated by using the ratio of the elastic modulus. The orientation factor parameter of the L direction of the UGTC47 alloy material sample is 1, and the orientation factor parameter of the T direction is .

[0060] Step three, according to the fatigue test, the S-N curve is established, and the fatigue limit stress value of the material is obtained.

[0061] In order to facilitate calculation, the stress when the fatigue life reaches cycle times is defined as the fatigue limit stress. According to the results of the low cycle fatigue performance test of the UGTC47 directional solidification turbine blade sample in step one, the stress-life curve is constructed, the logarithmic linear regression is used for fitting, and the fatigue limit stress value of the UGTC47 alloy material at 107 cycle times is obtained by extrapolation. The part of the stress exceeding the fatigue limit stress is identified as the effective stress .

[0062] Step four, according to the fatigue test and the fatigue limit stress value, the effective strain energy density of the material is calculated.

[0063] According to the results of the low cycle fatigue performance test of the UGTC47 directional solidification material sample in step one, and the calculation formula of the effective elastic strain range, the effective stress and the effective elastic strain range of the sample with different orientations under different test strain conditions are calculated, as shown in Table 3.

[0064] Table 3 Effective stress and elastic strain of UGTC47 alloy smooth samples with characteristic orientation at 750℃

[0065] According to the contents of Table 2 and Table 3, the effective strain energy density is calculated, and a typical low cycle fatigue hysteresis loop effective strain energy density schematic diagram is also drawn, as shown in Figure 3 , the horizontal coordinate represents the strain, and the vertical coordinate represents the stress, effective strain energy density, effective elastic strain range, total plastic strain range, total strain range, stress maximum, stress minimum, the entire red closed loop depicts a complete loading-unloading-reverse loading-unloading cycle experienced by the material, and the green part in the figure is the strain energy density part above the limit stress, that is, the effective strain energy density.

[0066] Step five, using the orientation factor and the effective strain energy density, the low cycle fatigue life of different orientations of the material is predicted.

[0067] In order to verify the superiority and accuracy of the low cycle fatigue life prediction method proposed in the application, the low cycle fatigue life of the UGTC47 alloy material smooth specimen of different characteristic orientations is predicted by using the effective strain energy density model and the orientation factor and effective strain energy density based method proposed in the application respectively, and the above two methods are evaluated after prediction. When evaluating, the two methods require unified model parameters for prediction of different orientations.

[0068] Figure 4 The results of evaluating the low cycle fatigue life of the UGTC47 alloy material smooth specimen of different characteristic orientations by using the effective strain energy density model are given. It can be seen that, since the original model does not consider the influence of the anisotropy characteristics of different crystal orientations on the low cycle fatigue life of the material, the distribution of the predicted life L and T data points of the UGTC47 material is obviously dispersed, and the prediction life deviation is large.

[0069] Figure 5 The results of evaluating the low cycle fatigue life of the UGTC47 alloy material smooth specimen of different characteristic orientations by using the effective strain energy density model are given. It can be seen that, since the original model does not consider the influence of the anisotropy characteristics of different crystal orientations on the low cycle fatigue life of the material, the distribution of the predicted life L and T data points of the UGTC47 material is obviously dispersed, and the prediction life deviation is large.

[0070] In summary, the anisotropic low cycle fatigue life evaluation method proposed in the application introduces the crystal orientation factor to correct the effective strain energy density model, and constructs a unified parameter life prediction model under different orientations, which shows good fitting accuracy and engineering practicability under the typical characteristic orientations of the UGTC47 alloy, and can be widely applied to the field of low cycle fatigue life evaluation of anisotropic directionally solidified alloy materials.

[0071] The low cycle fatigue life prediction method suitable for directionally solidified turbine blades proposed in the application has the following beneficial effects.

[0072] (1) The method of the present application can solve the problem of difficulty in evaluating the low-cycle fatigue life of anisotropic directionally solidified materials in different crystal orientations. The principle is to create an orientation factor to represent the anisotropic characteristics of the directionally solidified material based on the physical relationship between the elastic modulus and the crystal orientation, and to predict the low-cycle fatigue life in combination with the effective strain energy density.

[0073] (2) The advantage of the present application is that the fatigue life of directionally solidified materials in different orientations can be predicted based on the material parameters of the characteristic orientation and the effective strain energy density, which is simple in form, easy to obtain parameters, and has high prediction accuracy.

[0074] (3) The method of the present application can be used for precise evaluation of the multi-directional life of gas turbine turbine blades, providing theoretical support for the long-life safe operation and reliability of the structure. At the same time, the method has good universality and can be applied to other materials and structures with similar characteristics under service conditions, and has significant engineering application value.

[0075] Based on the same inventive concept, the embodiments of the present application also provide a low-cycle fatigue life prediction system suitable for directionally solidified turbine blades. The implementation scheme for solving the problem provided by the system is similar to the implementation scheme described in the above method, so the specific limitations in one or more low-cycle fatigue life prediction system embodiments suitable for directionally solidified turbine blades provided below can be referred to the limitations of the low-cycle fatigue life prediction method suitable for directionally solidified turbine blades described above, which will not be repeated here.

[0076] In one exemplary embodiment, as shown in Figure 6 , a low-cycle fatigue life prediction system suitable for directionally solidified turbine blades is provided, which includes: An acquisition module is configured to acquire test data of the directionally solidified turbine blade; the test data includes elastic modulus and low-cycle fatigue performance data; the elastic modulus includes elastic modulus in the crystal direction and elastic modulus in the crystal direction; , and respectively represent the smallest integer that is relatively prime to the component of any lattice vector along the direction on the cell base vector , and .

[0077] An orientation factor calculation module is configured to calculate the orientation factor based on the elastic modulus.

[0078] An effective strain energy density determination module is configured to determine the effective strain energy density based on the low-cycle fatigue performance data.

[0079] A low cycle fatigue life prediction module for calculating a predicted low cycle fatigue life of a directionally solidified turbine blade based on an orientation factor and an effective strain energy density.

[0080] The technical features of the above embodiments can be combined in any manner. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described; however, as long as the combinations of the technical features do not contradict each other, they should be considered to be within the scope of the present disclosure.

[0081] The principles and implementation manners of the present application are described herein by using specific examples, and the above embodiments are only used to help understand the method of the present application and its core idea; meanwhile, for those skilled in the art, the specific implementation manners and application range can be changed according to the idea of the present application. In conclusion, the content of the present disclosure should not be understood as a limitation to the present application.

Claims

1. A method for predicting the low-cycle fatigue life of directionally solidified turbine blades, characterized in that, The method for determining the low-cycle fatigue life of directionally solidified turbine blades includes: Acquire test data for directional solidification turbine blades; the test data includes elastic modulus and low-cycle fatigue performance data; the elastic modulus includes: in Elastic modulus in the crystallographic direction and in Elastic modulus in the crystal orientation; , and These represent the basis vectors of any lattice vector along this direction in the unit cell. , and The smallest integer whose components are proportional and coprime; The orientation factor is calculated based on the elastic modulus; The effective strain energy density is determined based on the low-cycle fatigue performance data. Based on the orientation factor and the effective strain energy density, the predicted low-cycle fatigue life of the directional solidified turbine blade is calculated.

2. The method for predicting the low-cycle fatigue life of directionally solidified turbine blades according to claim 1, characterized in that, The formula for calculating the orientation factor is: ； in, Orientation factor; In order to be in Elastic modulus in the crystal orientation; In order to be in Elastic modulus in the crystallographic direction.

3. The method for predicting the low-cycle fatigue life of directionally solidified turbine blades according to claim 1, characterized in that, The low-cycle fatigue performance data includes steady-cycle hysteresis loops and low-cycle fatigue stress-life curves. Specifically, determining the effective strain energy density based on the low-cycle fatigue performance data includes: Based on the stable cycle hysteresis loop, the total elastic strain range and the total plastic strain range are determined; Based on the low-cycle fatigue stress-life curve, the total stress and effective stress are determined. Calculate the effective elastic strain range based on the total elastic strain range, the total stress, and the effective stress. The effective strain energy density is calculated based on the total plastic strain range, the effective elastic strain range, and the effective stress.

4. The method for predicting the low-cycle fatigue life of directionally solidified turbine blades according to claim 3, characterized in that, The formula for calculating the effective elastic strain range is as follows: ； in, The effective elastic strain range; Effective stress; The total stress; This represents the total elastic strain range.

5. The method for predicting the low-cycle fatigue life of directionally solidified turbine blades according to claim 3, characterized in that, The formula for calculating the effective strain energy density is as follows: ； in, Effective strain energy density; Effective stress; The effective elastic strain range; This represents the total plastic strain range.

6. The method for predicting the low-cycle fatigue life of directionally solidified turbine blades according to claim 1, characterized in that, The formula for calculating the predicted low-cycle fatigue life of the directionally solidified turbine blade is as follows: ； in, Predicting low-cycle fatigue life for directional solidification turbine blades; Orientation factor; Effective strain energy density; , and All of these are fitting parameters.

7. A low-cycle fatigue life prediction system suitable for directional solidification turbine blades, characterized in that, The low-cycle fatigue life prediction system for directional solidification turbine blades includes: The acquisition module is used to acquire the test data of the directional solidification turbine blade; the test data includes elastic modulus and low-cycle fatigue performance data; the elastic modulus includes: in Elastic modulus in the crystallographic direction and in Elastic modulus in the crystal orientation; , and These represent the basis vectors of any lattice vector along this direction in the unit cell. , and The smallest integer whose components are proportional and coprime; An orientation factor calculation module is used to calculate the orientation factor based on the elastic modulus. An effective strain energy density determination module is used to determine the effective strain energy density based on the low-cycle fatigue performance data. The low-cycle fatigue life prediction module is used to calculate the predicted low-cycle fatigue life of the directional solidified turbine blade based on the orientation factor and the effective strain energy density.

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