A method for debugging non-uniform stress field of aero-engine turbine blade thermal mechanical fatigue test section

Abstract

The present application relates to a kind of aero-engine turbine blade thermal mechanical fatigue examination section non-uniform stress field debugging method, comprising (1) determining turbine blade three-dimensional model, turbine blade fixture three-dimensional model is established in computer software and is assembled, according to turbine blade stress field examination requirement to determine the range of stress of each examination point of examination section;(2) determine the parameter that influences examination section stress field distribution as variable, extract initial sample point and calculate to obtain the real response of these sample points and construct sample library;(3) according to the sample information in sample library, construct the proxy model between variable and response, utilize proxy model output the optimal parameter that influences examination section stress field distribution;(4) carry out test on fatigue testing machine, adjust fixture position and fatigue testing machine load, to obtain the test blade examination section stress field that meets the requirement.The present application reduces test cost by the method of adjusting and determining fixture position and testing machine load in finite element software.

Description

Technical Field

[0001] This invention belongs to the field of aerospace engine technology, specifically relating to a method for debugging the non-uniform stress field of the thermomechanical fatigue test section of an aero-engine turbine blade. Background Technology

[0002] During the service life of aero-engines, turbine blades experience alternating thermal and mechanical loads. Thermomechanical fatigue, caused by the superposition of temperature and stress cycles, is the primary failure mode. Compared to traditional isothermal low-cycle fatigue, creep, and creep-fatigue tests, thermomechanical fatigue can more accurately characterize the complex alternating multi-field coupled load characteristics of blades and the competition and synergy of various damage mechanisms, which is of great significance for turbine blade life assessment and fault analysis. To achieve an accurate description of the load conditions of turbine blades during service, thermomechanical fatigue testing requires high precision in the stress field. Inaccurate stress fields will affect the accuracy of test results, and consequently, the assessment of blade life. In existing technologies, adjusting the stress field of blades directly on a testing machine is extremely costly and inefficient, hindering the progress of turbine blade fatigue performance assessment.

[0003] The existing literature “Xu Hao, Li Zhenlei, Shi Duoqi, Wang Xiangping, Yang Xiaoguang. Study on biaxial bending vibration fatigue test of characteristic simulation part at the transition of leaf root edge plate [J]. Propulsion Technology, 2022, 43(01):254-260” uses finite element global modeling to perform prestressed modal analysis on the fixture system, but does not calculate the stress field and does not use a surrogate model to improve optimization efficiency. Summary of the Invention

[0004] To overcome the shortcomings of existing technologies, this invention provides a method for debugging the non-uniform stress field of the thermo-mechanical fatigue test section of aero-engine turbine blades. While fully reflecting the stress field distribution of the turbine blades during thermo-mechanical fatigue, the method reduces test costs by debugging and determining the fixture position and test machine load in finite element software, and improves debugging efficiency by establishing a proxy model, thus serving and supporting the thermo-mechanical fatigue test of aero-engine turbine blades.

[0005] Technical solution of the present invention:

[0006] A method for adjusting the non-uniform stress field of a cross-section for thermomechanical fatigue testing of an aero-engine turbine blade, characterized by comprising the following steps:

[0007] (1) Establish a three-dimensional model of the turbine blade fixture, including the upper clamp, lower clamp, upper chuck, upper fork, lower chuck, lower fork, front baffle, and rear baffle, and assemble it. Determine the range of stress at each test point of the turbine blade according to the turbine blade stress field test requirements.

[0008] (2) Determine the relative position of the fixture and the load of the fatigue testing machine as input variables. Within the range of values ​​of each input variable, use Latin hypercube sampling to extract initial sample points. Perform finite element simulation calculations on the fixture and blade assembly to obtain the stress value of the stress field of the test section corresponding to each sample point as the true response. Establish an automatic optimization calculation framework for the above process and perform repeated simulation calculations to build a sample library.

[0009] (3) Construct a proxy model between the parameters affecting the stress field distribution of the test section and the stress value of the test point of the stress field of the test section of the blade based on the sample information in the sample library. Use the proxy model to calculate and output the optimal parameters affecting the stress field distribution of the test section.

[0010] (4) Conduct the test on the fatigue testing machine. Adjust the relative position of the fixture and the load of the fatigue testing machine according to the results of step (3) to obtain the same stress field of the test blade test section that meets the requirements as the simulation results in step (3).

[0011] Further, in step (2), the input variables are: fatigue testing machine load P, relative distance L1 between the upper clamp and the upper fork, relative distance L2 between the upper fork and the upper clamp, relative distance L3 between the lower clamp and the lower fork, and relative distance L4 between the lower fork and the lower clamp.

[0012] Furthermore, the optimal parameters for determining the stress field distribution of the test section in step (3) are determined as follows: on the premise that the stress values ​​at each test point of the test section are within the stress field test requirements, the errors at each test point are combined using the coefficient allocation method to form a weighted total error, and a set of parameters that minimizes the weighted total error is selected.

[0013] Furthermore, in step (4), the determination of the load magnitude of the fatigue testing machine and the relative position of the fixture is optimized by performing finite element simulation on the turbine blade and establishing a proxy model in steps (2) and (3).

[0014] The advantages of this invention compared to existing technologies are as follows: This invention is a non-uniform stress field debugging method that, after determining the stress requirements at the test points of turbine blade characteristic structures, optimizes the fixture position and testing machine load through finite element simulation and surrogate modeling, ensuring that the stress field in the actual test meets the requirements. This invention, while fully reflecting the stress field distribution of turbine blades during thermomechanical fatigue, reduces testing costs by determining the fixture position and testing machine load through debugging in finite element software and optimization in a surrogate model. Currently, no related technologies have been reported, and this invention fills a gap in related research. Attached Figure Description

[0015] Figure 1This is the implementation process of a non-uniform stress field debugging method for thermomechanical fatigue testing section of aero-engine turbine blade according to the present invention;

[0016] Figure 2 This is a three-dimensional model of the blade and fixture assembly according to an embodiment of the present invention;

[0017] Figure 3 The turbine blades and their test point locations are shown in this embodiment of the invention.

[0018] Figure 4 The simulation results of the stress field of the test section and the stress value of the test point in this embodiment of the invention;

[0019] Figure 5 The relative positions and optimal parameters of the clamps in this embodiment of the invention are shown. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0021] like Figure 1 As shown, the present invention discloses a method for debugging a non-uniform stress field on a section for thermomechanical fatigue testing of aero-engine turbine blades. This method utilizes finite element simulation to save testing costs and employs a surrogate model to improve debugging efficiency, establishing an efficient non-uniform stress field debugging method. The implementation steps are as follows:

[0022] (1) Determine the three-dimensional model of the turbine blade. In computer software, establish and assemble the three-dimensional models of the turbine blade fixtures, including the upper clamp, lower clamp, upper chuck, upper fork, lower chuck, lower fork, front baffle, and rear baffle. Determine the range of stress at each test point of the turbine blade according to the turbine blade stress field test requirements.

[0023] (2) Using parameters such as the relative position of the fixture and the load of the fatigue testing machine that affect the stress field distribution of the test section as input variables, the initial sample points are extracted using Latin hypercube sampling within the range of each input variable value. The fixture and blade assembly is then calculated using finite element simulation software to obtain the stress value of the test section stress field corresponding to each sample point as the true response. An automatic optimization calculation framework is established for the above process, and the simulation is repeated 5000 times to build a sample library.

[0024] (3) Construct a proxy model between the parameters affecting the stress field distribution of the test section and the stress value of the test point of the test section of the blade based on the sample information in the sample library. The stress value error of each test point is combined with the coefficient allocation method to form a weighted total error as the optimization target. Under the premise that the stress values ​​of all test points meet the test requirements, output the relative position of the fixture and the load of the fatigue testing machine that minimizes the weighted total error as the optimal parameters.

[0025] (4) The blade fixture is processed according to the three-dimensional model, and the test is carried out on the fatigue testing machine. The position of the fixture and the load of the fatigue testing machine are adjusted according to the results of step (3) to obtain the same stress field of the test blade test section that meets the requirements as the simulation results in step (3).

[0026] The technical solution of the present invention, a method for debugging a non-uniform stress field of a thermomechanical fatigue test section of an aero-engine turbine blade, will be further described below with reference to the accompanying drawings.

[0027] (1) Determine the 3D model of the turbine blade: A 1:1 3D model is created based on the actual turbine blade of the engine. A 3D model of the upper clamp on the blade is drawn based on the blade profile design, and a 3D model of the lower clamp on the blade is drawn based on the tenon design. Other clamps that fix the upper clamp, lower clamp, and blade to the thermomechanical fatigue testing machine are also drawn, such as the upper chuck, upper fork, lower chuck, lower fork, front baffle, and rear baffle. After drawing, the blades are assembled in UG 3D modeling software according to the actual situation of the thermomechanical fatigue test. The blade and clamp assembly model is as follows: Figure 2 As shown. Based on the engine's operating requirements, the working stress range of the turbine blades is determined. According to the load conditions on the blades during engine operation, the section of the blade to be tested is selected as the middle section of the turbine blade, thus determining the turbine blade test points. The turbine blade thermomechanical fatigue test is conducted according to GJB 450A-2004 "General Requirements for Equipment Reliability Operation" to assess the turbine blade's thermomechanical fatigue capability. The locations of the turbine blade test points are shown below. Figure 3 As shown in Table 1, the assessment requirements are within ±10MPa.

[0028] Table 1 Stress Requirements for Test Points in Turbine Blade Thermomechanical Fatigue Test

[0029]

[0030] (2) Based on the blade clamp assembly results, the fatigue testing machine load P and the relative distances L1 between the upper clamp and the upper fork, L2 between the upper fork and the upper clamp, L3 between the lower clamp and the lower fork, and L4 between the lower fork and the lower clamp are selected as parameters affecting the stress field distribution of the test section. Latin hypercube sampling is performed on the above five parameters within the load range of the fatigue testing machine and the relative movement distance of the clamps. Finite element simulation calculations are performed in Ansys-Workbench software based on the sampling results. An automatic optimization calculation framework is established for the above process, and the stress value of the test point is extracted as the true response. The simulation is repeated 5000 times to build a sample library.

[0031] (3) Construct a surrogate model between the parameters affecting the stress field distribution of the test section and the stress value at the test point of the blade test section based on the sample information in the sample library; select the test point error coefficient according to the magnitude of the stress standard value, and the total weighted error y of the optimization objective can be expressed by the following formula:

[0032]

[0033] Where a1-a6 are the error coefficients for the six assessment points in this example, with values ​​of 0.1, 0.1, 0.2, 0.2, 0.1, and 0.3 respectively; σ i The standard value of stress at the test point; σ i The stress values ​​at the test points were obtained using the surrogate model. Calculations showed that when the load P was 27.3 kN, the relative distance L1 between the upper clamp and the upper fork was 0 mm, the relative distance L2 between the upper fork and the upper clamp was 23.35 mm, the relative distance L3 between the lower clamp and the lower fork was 0 mm, and the relative distance L4 between the lower fork and the lower clamp was 10.02 mm, the total weighted error y was minimized, and the stress value errors at each test point were all within ±10 MPa, meeting the experimental requirements. The simulated stress field of the test section and the stress values ​​at the test points are as follows: Figure 4 As shown, the relative positions of the corresponding fixtures are as follows: Figure 5 As shown.

[0034] (4) Manufacture turbine blades and fixtures, and conduct verification tests on a fatigue testing machine. The testing machine includes a loading, heating, air cooling, and sub-control system. The blades, upper clamp, upper fork, lower clamp, lower fork, front baffle, rear baffle, and lower fixture are assembled on the thermomechanical fatigue testing machine. The relative positions of the fixtures during assembly are determined based on the surrogate model calculation results from step (3). After assembly, the load on the thermomechanical fatigue testing machine is adjusted to match the optimization results from step (3), ensuring that the stress values ​​at all test points of the turbine blades meet the requirements of the thermomechanical fatigue test.

[0035] The examples provided above are merely for illustrating the purpose of this invention and are not intended to limit the scope of the invention. The scope of this invention is defined by the appended claims. All equivalent substitutions and modifications made without departing from the spirit and principles of this invention should be covered within the scope of this invention.

Claims

1. A method for adjusting the non-uniform stress field of a cross-section for thermomechanical fatigue testing of aero-engine turbine blades, characterized in that, Includes the following steps: (1) Establish a three-dimensional model of the turbine blade fixture, including the upper fixture, lower fixture, upper chuck, upper fork, lower chuck, lower fork, front baffle, and rear baffle. That is, perform a 1:1 three-dimensional modeling based on the actual turbine blade of the engine, draw the three-dimensional model of the upper fixture of the blade based on the blade profile design, draw the three-dimensional model of the lower fixture of the blade based on the tenon design, and assemble them. Determine the stress range of each test point of the turbine blade according to the stress field test requirements of the turbine blade. (2) Determine the relative position of the fixture and the load of the fatigue testing machine as input variables. Within the range of values ​​of each input variable, use Latin hypercube sampling to extract initial sample points. Perform finite element simulation calculation on the fixture and blade assembly to obtain the stress value of the stress field of the test section corresponding to each sample point as the real response. An automated optimization calculation framework was established for the above process, and a sample library was constructed by performing multiple repeated simulation calculations. (3) Construct a proxy model between the parameters affecting the stress field distribution of the test section and the stress value of the test point of the stress field of the test section of the blade based on the sample information in the sample library. Use the proxy model to calculate and output the optimal parameters affecting the stress field distribution of the test section. (4) Conduct the test on the fatigue testing machine. Adjust the relative position of the fixture and the load of the fatigue testing machine according to the results of step (3) to obtain the same stress field of the test blade test section that meets the requirements as the simulation results in step (3). The testing machine includes loading, heating, air cooling and sub-control system.

2. The method for adjusting the non-uniform stress field of the thermomechanical fatigue test section of an aero-engine turbine blade according to claim 1, characterized in that: In step (2), the input variables are: fatigue testing machine load P, relative distance L1 between the upper clamp and the upper fork, relative distance L2 between the upper fork and the upper clamp, relative distance L3 between the lower clamp and the lower fork, and relative distance L4 between the lower fork and the lower clamp.

3. The method for adjusting the non-uniform stress field of the thermomechanical fatigue test section of an aero-engine turbine blade according to claim 2, characterized in that: The basis for determining the optimal parameters affecting the stress field distribution of the test section in step (3) is as follows: under the premise that the stress values ​​of each test point of the test section are within the stress field test requirements, the errors of each test point are combined by the coefficient allocation method to form a weighted total error, and a set of parameters that minimizes the weighted total error is selected.

4. The method for adjusting the non-uniform stress field of the thermomechanical fatigue test section of an aero-engine turbine blade according to claim 3, characterized in that: In step (4), the load size of the fatigue testing machine and the relative position of the fixture are determined by optimizing the turbine blades by performing finite element simulation and establishing a proxy model in steps (2) and (3).

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