Single crystal blade and optimization design method of secondary orientation angle
By constructing a simulation model of a single-crystal blade and optimizing the secondary orientation angle design, the performance dispersion problem of single-crystal blades was solved, and the overall performance and reliability of the blades were improved.
Patent Information
- Application Number
- CN202411118768.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-14
- Publication Date
- 2026-03-03
AI Technical Summary
In the existing technology, there is no clear specification for the secondary orientation angle of single crystal blades, which leads to large performance dispersion and affects service life and structural reliability.
By constructing a blade simulation model, dividing stress concentration areas, calculating failure hazard points, establishing the relationship between orientation angle and failure parameters, performing weighted averaging, optimizing the secondary orientation angle design, and comprehensively considering temperature, material strength dispersion, and stress distribution.
This enables reliable evaluation and optimized design of the overall performance of single-crystal blades, reduces design variables, and improves the service life and structural reliability of the blades.
Smart Images
Figure CN121598515A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of aero-engines, and more specifically to the field of optimized design of single-crystal blades. Background Technology
[0002] Nickel-based single-crystal alloys have become the preferred material for modern aero-engine turbine blades due to their excellent performance under high temperature and high pressure environments. Unlike polycrystalline materials, single-crystal alloys exhibit anisotropic properties. The material properties change accordingly with variations in the orientation of the single crystal. A specific crystal orientation requires three angles for description: typically, the primary orientation angle, secondary orientation angle, and random angle are used to describe the crystal orientation of a single-crystal turbine blade.
[0003] Currently, in engineering practice, blades with a primary orientation angle smaller than a specific angle are generally considered qualified products. However, there are no clear regulations regarding the secondary orientation angle of blades, resulting in significant variations in blade performance and adversely affecting their service life and structural reliability.
[0004] Therefore, there is an urgent need for an optimized design method for the secondary orientation angle to improve the overall performance of the blade. Summary of the Invention
[0005] One objective of this invention is to provide an optimized design method for the secondary orientation angle of a single-crystal blade, which can select the optimal design range of the secondary orientation angle to obtain a reliable single-crystal blade.
[0006] The optimization design method for the secondary orientation angle of single-crystal blades to achieve the above objectives includes the following steps:
[0007] A blade simulation model was constructed, and the primary orientation angle, secondary orientation angle and random angle were used as design variables to carry out simulation calculations of the blade under service with different crystal orientations, and the blade simulation results were obtained.
[0008] The blade simulation results are divided into regions, and the failure risk points in different stress concentration regions are calculated.
[0009] Establish the response relationship between the primary orientation angle, the secondary orientation angle, the random angle, and the failure hazard point, and establish the overall failure parameters of the blade;
[0010] By taking the probability density function of the random angle and the probability density function of the first orientation angle as a weighted average with the response relationship, the relationship between the second orientation angle and the overall failure assessment parameters of the blade is obtained.
[0011] The design value of the secondary orientation angle of the blade is determined based on the relationship between the secondary orientation angle and the overall failure assessment parameters of the blade.
[0012] In one or more embodiments, the stress concentration region is a location on the blade where localized stress increases due to the blade's geometry.
[0013] In one or more embodiments, the stress concentration region includes the leading edge region of the blade root, the film pore region, the impact pore region, and the trailing edge slit region.
[0014] In one or more embodiments, the step of calculating the failure hazard point is as follows: using the temperature and yield strength of each node in the stress concentration region to calculate the material strength of each node; using the material strength and the local stress at each node to calculate the failure parameters at each node; and selecting the maximum failure parameter from among the failure parameters as the failure hazard point of the stress concentration region.
[0015] In one or more embodiments, the steps for calculating the overall failure parameters of the blade are as follows: using a neural network model, establishing the response relationship between the primary orientation angle, the secondary orientation angle, and the random angle and the maximum failure parameter of each stress concentration region; using the series model theory, establishing the response relationship between the overall failure parameters of the blade and the primary orientation angle, the secondary orientation angle, and the random angle.
[0016] In one or more embodiments, according to Obtain the overall failure assessment parameters R(θ,α,ρ), P of the blade. j (θ,α,ρ) is used to obtain the maximum failure parameters for each stress concentration region, where N is the number of stress concentration regions, θ is the primary orientation angle, α is the secondary orientation angle, and ρ is the random angle.
[0017] In one or more embodiments, the probability density function for the random angle is a uniformly distributed probability density function.
[0018] In one or more embodiments, the probability density function for the primary orientation angle is obtained based on blade casting statistics.
[0019] Another object of the present invention is to provide a single-crystal blade that is designed and obtained by the above method.
[0020] The above method comprehensively considers the maximum failure parameters of each stress concentration region, enabling a more complete assessment of the impact of orientation angle on the overall blade strength. By using the probability density function of the orientation angle, the method weighted averages the influence of the primary orientation angle and random angles on the overall blade failure parameters, fully considering the dispersion of orientation angles during blade casting. This yields a relationship between the secondary orientation angle and the overall blade failure assessment parameters, allowing for accurate optimization design of the secondary orientation angle. Attached Figure Description
[0021] The above and other features, properties and advantages of the present invention will become more apparent from the following description taken in conjunction with the accompanying drawings and embodiments, wherein:
[0022] Figure 1A-1B This is a structural diagram defining the orientation angle of a single-crystal blade;
[0023] Figure 2 This is a flowchart of a specific embodiment of the optimization method;
[0024] Figure 3 This is a flowchart of the optimization design method for the secondary orientation angle of a single-crystal blade. Detailed Implementation
[0025] The present invention will be further described below with reference to specific embodiments and accompanying drawings. More details are set forth in the following description in order to provide a full understanding of the present invention. However, the present invention can obviously be implemented in many other ways different from those described herein. Those skilled in the art can make similar extensions and derivations based on actual application situations without departing from the spirit of the present invention. Therefore, the scope of protection of the present invention should not be limited by the content of this specific embodiment.
[0026] It should be noted that these and other accompanying drawings are merely examples and are not drawn to scale, and should not be construed as limiting the scope of protection of the present invention.
[0027] like Figure 1A-1B As shown, the primary orientation angle θ is the angle between the crystal
[001] direction and the blade stacking direction, i.e., the reference direction RD; the secondary orientation angle α is the angle between the projection of the crystal
[100] direction onto the original plane and the engine main shaft; the random angle ρ indicates the rotational distribution of the reference direction in the crystal unit.
[0028] When analyzing the influence of crystal orientation on the static strength of turbine blades, the maximum equivalent stress in the stress concentration region is usually selected as the evaluation index. The location of the maximum equivalent stress is taken as the failure hazard point, and the variation law of the maximum equivalent stress under the individual action of the three orientation angles is studied. However, due to the influence of the temperature field during service, the internal and external temperature difference of the turbine blade is large, resulting in differences in material strength in different temperature regions, and the maximum stress that it can withstand is also different. The failure hazard point that only considers the maximum stress cannot represent the most dangerous local location.
[0029] On the other hand, due to the different stress states of various stress concentration areas on the blade, the variation law of different failure risk points of the blade with the orientation angle is also different. It is necessary to comprehensively consider the influence of various stress concentration areas on the blade and analyze the influence law of the orientation angle on the overall performance of the blade.
[0030] Furthermore, although crystal orientation is represented by three independent orientation angles, the effects of these three orientation angles on blade performance are not independent of each other. Considering only the influence of the secondary orientation angle while ignoring the coupling effect of the other two angles cannot fully reflect the variation law of blade performance.
[0031] Based on this, the present invention proposes an optimization design method for the secondary orientation angle of a single-crystal blade. It comprehensively considers the influence of temperature, stress distribution, and material strength dispersion on the local strength of the blade. Under the premise of accurately identifying the failure risk points in the stress concentration area, it comprehensively analyzes the variation law of multiple failure risk points with the orientation angle, fully reflects the influence law of the orientation angle on the overall performance of the blade, clarifies the coupling effect of multiple orientation angles, and accurately carries out the optimization design of the secondary orientation angle of the blade.
[0032] Combination Figure 2 and Figure 3 It is understood that this method includes the following steps. It should be noted that the order of the steps described below is for illustrative purposes only and is not necessarily limited to the order of steps.
[0033] S1. Construct a blade simulation model, using the primary orientation angle θ, secondary orientation angle α, and random angle ρ as design variables, and conduct simulation calculations of the blade under service conditions with different crystal orientations to obtain blade simulation results; S2. Divide the blade simulation results into regions and calculate the failure hazard points in different stress concentration regions j; S3. Establish the response relationship between the primary orientation angle, secondary orientation angle, and random angle and the failure hazard points, and establish the overall failure parameters of the blade; S4. Perform a weighted average of the probability density functions for the random angle and the probability density functions for the primary orientation angle on the response relationship to obtain the relationship between the secondary orientation angle and the overall failure assessment parameters of the blade; S5. Determine the design value of the secondary orientation angle of the blade based on the relationship between the secondary orientation angle and the overall failure assessment parameters of the blade.
[0034] Specifically, in step S2, the stress concentration area refers to the location on the blade where localized stress increases due to its geometry, and is divided into regions such as the leading edge region of the blade root, the film cooling pore region, the impact pore region, and the trailing edge slit region. Those skilled in the art will understand that the divided regions include, but are not limited to, the specific embodiments described above.
[0035] Based on the finite element mesh of the single-crystal turbine blade model, the temperature T of node i in any of the stress concentration regions mentioned above is extracted. i and yield strength σ i The yield strength of nickel-based single crystal materials can be calculated based on data from the material mechanical properties handbook, at temperature T. i The material yield strength below Material properties typically exhibit a certain degree of dispersion, and the yield strength of a material at various temperatures can follow a certain probability density distribution. This indicates that the local stress is σ. i The failure parameters at that time are When the local stress σ i When the value is -∞, the failure parameter is P. i =1. With constant temperature and material strength dispersion, the failure parameter gradually decreases with increasing local stress. Even with the same local stress, changes in temperature and material dispersion will affect the probability density distribution. This causes changes in the failure parameters. Therefore, the failure parameter P i It is an evaluation index that can comprehensively consider local stress, temperature, and material properties to determine the location of failure hazards. The larger the failure parameter, the more dangerous the location is.
[0036] After obtaining the failure parameters at all nodes i within the stress concentration region, the maximum value of the failure parameters within the stress concentration region is selected as the failure hazard point of the stress concentration region. Where n is the total number of mesh nodes in the stress concentration region.
[0037] The location corresponding to the maximum failure parameter is taken as the failure hazard point P in that region. Compared with using the maximum stress as the evaluation index for the failure hazard point, the failure parameter proposed in this method comprehensively considers the combined effects of material property changes caused by temperature, the dispersion of material strength, and the local stress of the blade. The failure hazard point determined by the maximum failure parameter is more representative of the dangerous location of the stress concentration area.
[0038] Continuing with step S3, the primary orientation angle θ, secondary orientation angle α, and random angle ρ are used as design variables to analyze the maximum failure parameters in each stress concentration region of the blade. Using a neural network model, the response relationships between the three orientation angles and the maximum failure parameters in each stress concentration region are established. The maximum failure parameters in each stress concentration region are calculated for a given orientation angle (θ, α, ρ). Based on the theory of the cascade model, the overall failure parameters of the blade are established. Where P j Let be the minimum failure parameter at stress concentration region j, and N be the number of stress concentration regions considered.
[0039] Failure parameter P of any stress concentration region j Changes in P will cause changes in the overall failure parameter R(θ,α,ρ) of the blade. j The larger the value, the larger the corresponding R(θ,α,ρ) value, indicating that the orientation is more dangerous. This formula can be used to transform the influence of the orientation angle on various stress concentration locations into its influence on the overall blade strength.
[0040] Let f(θ) be the probability density function of the primary orientation angle of the blade, and f(ρ) be the probability density function of a random angle. Then, for a given secondary orientation angle α, the overall failure parameter R(α) of the blade can be expressed as: Where θ c ρ c These are the upper limits of the range of change for the first orientation angle and the random angle, respectively.
[0041] In some embodiments, the probability density function for the first orientation angle is obtained based on blade casting statistics, and the probability density function for the random angle is a uniformly distributed probability density function.
[0042] This formula uses a probability density function to weighted average the influence of the primary orientation angle and random angle on the overall failure parameter R(θ,α,ρ) of the blade. It takes into account the actual orientation distribution of the blade, effectively reduces the number of influencing variables, and clarifies the relationship between the secondary orientation angle and the overall failure parameter of the blade.
[0043] The final relationship between the secondary orientation angle and the overall blade failure assessment parameters, R(α), takes into account the influence of the temperature field, stress field, and material strength dispersion in the stress concentration region on the failure hazard location, the combined influence of multiple failure hazard locations under different crystal orientations on the overall blade strength, and the probability distribution of the primary orientation angle and random angle of the cast blade. A larger R(α) value indicates that the secondary orientation angle is more detrimental to the blade strength. Therefore, the optimal value of the secondary orientation angle can be determined based on the minimum value of R(α).
[0044] The method is illustrated below with a specific embodiment.
[0045] Using the primary orientation angle θ, secondary orientation angle α, and random angle ρ as design variables, finite element simulation calculations were carried out on single-crystal turbine blades under service conditions at different orientation angles. The simulation results were obtained, and the nodal stresses and temperatures of stress concentration areas such as the leading edge of the blade root, film cooling holes, impact holes, and trailing edge slits of the single-crystal turbine blades were extracted.
[0046] For example, the stress concentration region J at the leading edge of the blade root of a single-crystal turbine blade. Y For example, extract the stress concentration region J at the leading edge of the leaf root. Y The data at node i, temperature T i =850℃, yield strength calculated
[0047] If we assume that the yield strength of the material follows a normal distribution with a standard deviation of 50 MPa, then the material strength distribution at node i can be expressed as follows: Combined with the local stress σ at node i i =850 MPa, the failure parameters of this node can be calculated as follows:
[0048] For example, if the region has 163 grid nodes, the failure parameters at each of the 163 nodes are calculated, and the maximum value is selected as the failure parameter P for the stress concentration region. j =0.352, designated as a potential failure point. The node temperature corresponding to this potential failure point is 900℃, and the stress is 830MPa. Although the stress of 830MPa at this point is less than the stress value of 850MPa at node i mentioned above, the higher temperature at this point causes a significant decrease in material properties, thus making it a potential failure point in this stress concentration region.
[0049] Using a neural network model, the orientation angle (θ, α, ρ) and the maximum failure parameter P for each stress concentration region were established. j The response relationship between (θ, α, ρ) is established. Based on this response relationship, given the orientation angle (θ, α, ρ), the maximum failure parameter P for each stress concentration region is obtained. j (θ,α,ρ), and based on the series model theory, calculate the overall failure parameter R(θ,α,ρ) of the blade. By P j (θ,α,ρ) is used to obtain R(θ,α,ρ), and the response relationship between R(θ,α,ρ) and the orientation angle is established. N is the number of stress concentration regions considered.
[0050] The overall failure parameters of the blade are influenced by the primary orientation angle, secondary orientation angle, and random angle. For each fixed set of primary and secondary orientation angles, the failure parameters change with the random angle. The influence of the random angle is obtained by weighted averaging using the probability density function f(ρ) of the random angle.
[0051] Similarly, when the secondary orientation angle remains constant, the influence of the primary orientation angle is obtained by weighted averaging through the probability density function f(θ) of the primary orientation angle.
[0052] In general engineering, the primary orientation angle is controlled. Therefore, the probability density function of the primary orientation angle can be obtained by statistically analyzing the distribution of the primary orientation angle in actual cast blades. Treating random angles as uniformly distributed probability density functions, and substituting them into the above formula, the blade failure parameters for different secondary orientation angles can be calculated.
[0053] Based on the established relationship between the secondary orientation angle and the failure parameters, the design value of the blade's secondary orientation angle is determined based on the minimum R(α).
[0054] Compared to traditional methods that use maximum stress as the assessment index for failure risk points, the above method comprehensively considers failure parameters influenced by local stress distribution, temperature field, and material strength dispersion. Based on the analysis of stress values at individual key points on the blade, this method comprehensively considers the maximum failure parameters of various stress concentration regions, thus providing a more comprehensive assessment of the impact of orientation angle on the overall blade strength. Furthermore, by using the probability density function of the orientation angle, this method weighted averages the influence of primary orientation angle and random angle on the overall blade failure parameters. This not only fully considers the dispersion of orientation angle during blade casting but also effectively reduces the number of influencing variables and clarifies the influence of secondary orientation angle on the overall blade failure parameters.
[0055] Based on the above description, it can also be understood that a single-crystal blade obtained using the above method has better overall performance.
[0056] This application uses specific terms to describe embodiments of the application. Terms such as "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic associated with at least one embodiment of the application. Therefore, it should be emphasized and noted that references to "an embodiment," "one embodiment," or "an alternative embodiment" in different locations throughout this specification do not necessarily refer to the same embodiment. Furthermore, certain features, structures, or characteristics in one or more embodiments of the application can be appropriately combined.
[0057] While the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the invention. Any variations and modifications can be made by those skilled in the art without departing from the spirit and scope of the invention. Therefore, any modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention, without departing from the scope of the invention, fall within the protection scope defined by the claims of the present invention.
Claims
1. A method for optimizing the secondary orientation angle of a single-crystal blade, characterized in that, Includes the following steps: A blade simulation model was constructed, and the primary orientation angle, secondary orientation angle and random angle were used as design variables to carry out simulation calculations of the blade under service with different crystal orientations, and the blade simulation results were obtained. The blade simulation results are divided into regions, and the failure risk points in different stress concentration regions are calculated. Establish the response relationship between the primary orientation angle, the secondary orientation angle, the random angle, and the failure hazard point, and establish the overall failure parameters of the blade; By taking the probability density function of the random angle and the probability density function of the first orientation angle as a weighted average with the response relationship, the relationship between the second orientation angle and the overall failure assessment parameters of the blade is obtained. The design value of the secondary orientation angle of the blade is determined based on the relationship between the secondary orientation angle and the overall failure assessment parameters of the blade.
2. The method for optimizing the secondary orientation angle of a single-crystal blade as described in claim 1, characterized in that, Stress concentration areas are the locations on the blade where localized stress increases due to the blade's geometry.
3. The method for optimizing the secondary orientation angle of a single-crystal blade as described in claim 2, characterized in that, The stress concentration areas include the leading edge region of the leaf root, the film pore region, the impact pore region, and the trailing edge split region.
4. The method for optimizing the secondary orientation angle of a single-crystal blade as described in claim 1, characterized in that, The steps for calculating the failure risk points are as follows: The material strength of each node is calculated using the temperature and yield strength at each node within the stress concentration region. Using the material strength and the local stress at each node, calculate the failure parameters at each node; Among the various failure parameters, the largest failure parameter is selected as the failure hazard point of the stress concentration region.
5. The method for optimizing the secondary orientation angle of a single-crystal blade as described in claim 1, characterized in that, The steps for calculating the overall failure parameters of the blade are as follows: Using a neural network model, the response relationship between the primary orientation angle, the secondary orientation angle, and the random angle and the maximum failure parameter of each stress concentration region was established. Using the series model theory, the response relationship between the overall failure parameters of the blade and the primary orientation angle, secondary orientation angle and random angle is established.
6. The method for optimizing the secondary orientation angle of a single-crystal blade as described in claim 5, characterized in that, according to Obtain the overall failure assessment parameters R(θ,α,ρ), P of the blade. j (θ,α,ρ) represents the maximum failure parameters for each stress concentration region, where N is the number of stress concentration regions, θ is the primary orientation angle, α is the secondary orientation angle, and ρ is the random angle.
7. The method for optimizing the secondary orientation angle of a single-crystal blade as described in claim 1, characterized in that, The probability density function of the random angle is a uniform probability density function.
8. The method for optimizing the secondary orientation angle of a single-crystal blade as described in claim 1, characterized in that, The probability density function for the first orientation angle is obtained from blade casting statistics.
9. A single-crystal blade, characterized in that, It is designed and obtained by the method described in any one of claims 1-8.