Prediction method for crown porosity defect of oriented / single crystal crown working blade

Abstract

The invention discloses a method for predicting the crown porosity defect of a directional / single crystal working blade with a crown. The method comprises the following steps: establishing a three-dimensional parameterized model of the working blade with the crown; testing temperature change data of inner and outer surfaces of the blade shell; reversely calculating the heat exchange coefficient of the inner and outer surfaces of the blade shell; inputting a heat exchange coefficient, setting process parameters, and performing dynamic simulation; extracting temperature gradients and cooling rates at a plurality of points of the blade crown part from a simulation result; a geometric feature weighted optimization Niyama criterion is adopted to calculate a blade crown part looseness formation criterion value; intercepting the part of the blade crown part with the porosity simulation result smaller than the porosity formation criterion value from the simulated diagram; and obtaining a casting looseness actual measurement result, performing matching verification on the casting looseness actual measurement result and a simulation result, determining that the simulation result is effective when the goodness of fit is not less than 75%, and otherwise, performing correction. According to the method, geometric feature weighting factors are introduced, the solidification characteristics of the thin-wall blade crown structure are optimized, and the accuracy of blade crown porosity defect prediction is improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of precision casting of turbine blades of an aero-engine, and particularly relates to a method for predicting loose defects of a directional / single-crystal band crown working blade crown. BACKGROUND

[0002] Modern aero-engine turbine working blades generally adopt a design with a blade crown, and a continuous aerodynamic sealing ring is formed through the intermeshing of the blade crowns, which can effectively reduce tip leakage loss and significantly improve turbine efficiency, and has become an inevitable choice for advanced aero-engine design.

[0003] However, the design structure with a blade crown brings a casting process problem in the production of blades. Since there is a geometric mutation at the connection between the blade crown and the blade body, local heat dissipation direction is disordered in the directional solidification process, and a hot spot area is easily formed; at the same time, alloy liquid feeding between dendrites is blocked, so that the micro-shrinkage defect rate increases, resulting in an increase in the rejection rate of blades.

[0004] The traditional standard Niyama criterion has good applicability in predicting loose defects in most casting geometries, and can effectively guide process optimization. However, when applied to complex castings with sheet-like structures with mutations, such as turbine blades with blade crowns, the prediction accuracy of the criterion is obviously insufficient. This is mainly because: first, the heat flow distribution of the thin-walled mutation area presents a highly nonlinear characteristic, which leads to the failure of the simplified heat conduction model based on the traditional criterion; second, the local cooling rate of the solidification front is difficult to accurately characterize due to the rapid change of the geometric characteristics; third, the solidification shrinkage behavior of the thin-walled area is significantly different from that of the conventional area, and the standard Niyama criterion fails to fully consider the influence of this special solidification behavior.

[0005] At present, in the field of numerical simulation of loose defects, there is a problem of large error in the prediction results caused by distorted boundary conditions. Most conventional simulation methods use empirical heat transfer coefficients, but in the actual directional solidification process, the proportion of radiation heat transfer on the outer surface of the mold shell is difficult to accurately quantify, and the heat transfer coefficient on the inner surface of the mold shell presents dynamic change characteristics during pouring, thereby causing serious deviation between the simulation results of the temperature gradient and the actual working conditions. The reason for this is that the failure of the traditional criterion and the inaccuracy of the boundary conditions are mainly due to two aspects: first, the traditional criterion system fails to consider the influence of complex geometric characteristics; second, the traditional criterion system lacks boundary condition calibration based on actual temperature measurement data. Therefore, it is urgent to develop a method for predicting loose defects of a directional / single-crystal band crown working blade crown that can simultaneously satisfy the adaptability of geometric mutations, the authenticity of boundary conditions, and the accuracy of verification methods. SUMMARY

[0006] To solve the problems in the prior art, the application provides a prediction method for loose defects of a directional / single crystal band crown working blade, which comprises the following steps in sequence:

[0007] Step one: a three-dimensional parametric model of the band crown working blade is established through three-dimensional modeling software, the three-dimensional parametric model containing a blade crown-blade body transition structure feature; the three-dimensional parametric model of the band crown working blade is imported into ProCAST finite element simulation software, and mesh division is performed on the three-dimensional parametric model;

[0008] Step two: the temperature change data of the inner surface and the outer surface of the band crown working blade shell during the whole directional solidification process are tested on site during the directional solidification process of the band crown working blade;

[0009] Step three: based on the temperature change data of the inner surface and the outer surface of the band crown working blade shell during the whole directional solidification process obtained on site, the heat transfer coefficients of the inner surface and the outer surface of the band crown working blade shell during the whole directional solidification process are inversely calculated;

[0010] Step four: the heat transfer coefficients of the inner surface and the outer surface of the band crown working blade shell during the whole directional solidification process obtained by inverse calculation are input into the ProCAST finite element simulation software, and the material parameters and the directional solidification process parameters of the band crown working blade are set, and then the whole directional solidification process is dynamically simulated to obtain a dynamic simulation result;

[0011] Step five: the temperature gradient field data distribution map and the cooling rate field data distribution map of the blade crown part are obtained from the dynamic simulation result, and the temperature gradient and the cooling rate of several points of the blade crown part are extracted from the data distribution map;

[0012] Step six: based on the temperature gradient and the cooling rate of the several points of the blade crown part, the Niyama criterion is used to calculate the loose formation criterion value of the several points of the blade crown part by using the geometric feature weighted optimization, then the average value is taken, and the average value is taken as the loose formation criterion value of the blade crown part;

[0013] Step seven: the ProCAST finite element simulation software is used to calculate the loose defect simulation diagram of the band crown working blade based on the standard Niyama criterion, the part of the loose defect simulation result of the blade crown part in the simulation diagram is smaller than the calculated loose formation criterion value of the blade crown part, and the part is determined as a high-risk loose area;

[0014] Step 8: Use a micro-nano 3D CT analyzer to perform a 3D scan on the crowned working blade casting prepared on-site by the directional solidification process, obtain the measured results of the porosity defects of the crowned working blade casting, and verify the spatial matching degree between the measured results of the porosity defects of the crowned working blade casting and the simulation results of porosity defects in the high-risk porosity areas.

[0015] Step 9: When the agreement between the simulation results and the measured results is not less than 75%, the simulation results are valid. Save the simulation results and the calculated criterion value for the loosening of the leaf crown, which will be used for subsequent prediction of loosening defects in the leaf crown of the working leaf with the crown and optimization of the directional solidification process.

[0016] Step 10: When the agreement between the simulation results and the measured results is less than 75%, the parameters of the Niyama criterion with geometric feature weighting optimization need to be corrected. Based on the corrected Niyama criterion with geometric feature weighting optimization, repeat steps 6 to 8 until the agreement between the simulation results and the measured results is not less than 75%, thus completing the prediction of the loose canopy defect of the working leaf with crown.

[0017] Preferably, in step one, the crowned working blade includes a crown, a crown-blade transition structure, a blade, a rim plate, and a tenon; the three-dimensional parametric model includes the crown thickness, the crown cross-sectional area, the blade leading edge thickness at the connection with the crown, and the blade cross-sectional area at the connection with the crown.

[0018] In any of the above schemes, preferably, in step one, the grid unit size of the leaf crown region is no greater than 0.5 mm, the grid unit size of the leaf crown-blade transition structure is 1.5-1.75 times the grid unit size of the leaf crown region, the grid unit size of the blade region is 2-2.5 times the grid unit size of the leaf crown region, and the grid unit size of the edge plate region and the tenon region are both 5-10 times the grid unit size of the leaf crown region.

[0019] In any of the above schemes, it is preferred that, in step two, the entire process of directional solidification includes a pouring stage and a pulling stage; the temperature measurement area includes the leaf crown area located on the leaf basin side and the leaf back side of the crowned working blade shell, the leaf crown-leaf body transition structure, and the inner and outer surfaces of the leaf body area.

[0020] In any of the above schemes, the preferred method is that, in step three, the heat transfer coefficients of the inner and outer surfaces of the crowned working blade shell are calculated by inversion throughout the entire directional solidification process. The inversion calculation equation is: In the formula,

[0021] —Heat flow rate of the temperature measurement area, W / m 2 ;

[0022] —Heat transfer coefficient of the temperature measurement area, W / (m²) 2 ·K);

[0023] , —The temperature of the medium on both sides of the heat exchange interface, in K.

[0024] When the heat exchange interface is the outer surface of a shell with crowned working blades. The temperature of the air. The temperature of the shell with crowned blades; when the heat exchange interface is the inner surface of the shell with crowned blades, The temperature of the shell of the crowned working blade. The temperature of the molten metal.

[0025] In any of the above schemes, it is preferred that, in step four, the material parameters include elastic modulus, Poisson's ratio, and thermal conductivity; and the directional solidification process parameters include pouring temperature and drawing speed.

[0026] In any of the above schemes, it is preferred that, in step five, the temperature gradient and cooling rate at several points on the leaf crown are extracted from the data distribution map. The locations of the extraction points include the leaf crown area on the leaf basin side, the leaf crown area on the leaf back side, the leading edge of the leaf blade where it connects with the leaf crown, and the trailing edge of the leaf blade where it connects with the leaf crown. At least two points are extracted for each of the leaf crown area on the leaf basin side, the leaf crown area on the leaf back side, the leading edge of the leaf blade where it connects with the leaf crown, and the trailing edge of the leaf blade where it connects with the leaf crown.

[0027] In any of the above schemes, the preferred option is that, in step six, the Niyama criterion for geometric feature weighted optimization is: In the formula,

[0028] —The loose formation criterion value after geometric feature weighting optimization;

[0029] — Leaf crown thickness, mm;

[0030] —Thickness of the leading edge of the leaf blade where it connects to the leaf crown, mm;

[0031] —Cross-sectional area of ​​the leaf crown, mm 2 ;

[0032] —The cross-sectional area of ​​the leaf blade at the junction with the leaf crown, in mm 2 ;

[0033] —Temperature gradient, °C / mm;

[0034] —Cooling rate, °C / s;

[0035] — Correction factor, empirical value is 0.5-0.8.

[0036] In any of the above schemes, the preferred option is that, in step seven, the standard Niyama criterion is... In the formula,

[0037] —Standard criteria for the formation of looseness;

[0038] —Temperature gradient, °C / mm;

[0039] —Cooling rate, °C / s.

[0040] In any of the above schemes, it is preferable that, in step ten, the parameters of the Niyama criterion for geometric feature weighted optimization are modified, that is, the modification coefficients are adjusted. Make corrections by adjusting the correction factor within the empirical range of 0.5-0.8.

[0041] The method for predicting the looseness defect of the working blade with crown of the present invention includes the following four components: (1) a parameterized modeling module, configured to generate a crown-blade transition structure model with local densification grid; (2) a boundary condition inversion module, which generates heat transfer boundary conditions based on shell temperature measurement data and transforms the heat function h(T) in real time; (3) a looseness distribution prediction module, which calculates the geometric feature weighted Niyama criterion value and generates a looseness prediction distribution map; and (4) a micro-nano CT verification module, which performs a looseness distribution matching rate analysis between simulation results and measured results.

[0042] In this invention, the entire process of directional solidification includes pouring, filling, pulling, directional solidification and cooling. Pouring and filling can be combined into a pouring stage, and pulling, directional solidification and cooling can be combined into a pulling stage.

[0043] The method for predicting loose canopy defects in oriented / single-crystal crowned working blades of the present invention has the following beneficial effects:

[0044] (1) By introducing a geometric feature weighting factor, this invention optimizes the solidification characteristics of thin-walled leaf crown structures, significantly improving the prediction accuracy of loose defects in the leaf crown area, which has obvious advantages over traditional methods.

[0045] (2) After adopting the prediction method of the present invention, the optimization iteration cycle of directional solidification process parameters is significantly shortened and the efficiency is greatly improved. This is mainly due to the high efficiency of numerical simulation and the automatic identification of risk areas based on the porosity prediction results, thereby avoiding the repetition of the traditional long production-inspection process.

[0046] (3) After adopting the prediction method of the present invention, the number of trial castings in the process optimization process is significantly reduced, the scrap rate of the crown part and the overall inspection cost are greatly reduced, and the overall cost of quality control is effectively reduced.

[0047] (4) The present invention can simultaneously satisfy the following three advantages: First, it has good predictive adaptability to geometrically abrupt structures; second, it can truly reflect the boundary conditions of the directional solidification process; third, it has high-precision verification methods to ensure the accuracy and reliability of the prediction. Attached Figure Description

[0048] Figure 1 A flowchart of a preferred embodiment of the method for predicting loose crown defects in oriented / single-crystal crowned working blades according to the present invention;

[0049] Figure 2 for Figure 1 The illustrated embodiment shows the grid division diagrams of the leaf crown region, the leaf crown-leaf blade transition structure, and the leaf blade region;

[0050] Figure 3 for Figure 1 The temperature gradient field data distribution diagram of the leaf crown region in the illustrated embodiment;

[0051] Figure 4 for Figure 1 The cooling rate field data distribution diagram of the leaf crown region in the embodiment shown;

[0052] Figure 5 for Figure 1 The diagram shown illustrates the location of sampling points on the leaf crown in the illustrated embodiment.

[0053] Figure 6 for Figure 1 The illustrated embodiment shows a simulation diagram of loosening defects in the leaf crown region calculated based on the standard Niyama criterion;

[0054] Figure 7 for Figure 1 The diagram shows a comparison between the simulation results of the initial predicted porosity defects and the actual measured results of porosity defects in the castings in the embodiment shown, wherein: (a) a porosity defect distribution diagram of the crown part taken from the simulation diagram, and (b) a porosity defect distribution diagram of the castings in the field tested by a micro-nano three-dimensional CT analyzer.

[0055] Figure 8 for Figure 1The comparison diagram of the simulation results of the corrected predicted porosity defects and the measured results of porosity defects in the castings in the embodiment shown is as follows: (a) a porosity defect distribution diagram of the crown part taken from the simulation diagram, and (b) a porosity defect distribution diagram of the castings in the field tested by a micro-nano 3D CT analyzer. Detailed Implementation

[0056] To further understand the invention, the following detailed description of the invention will be provided in conjunction with specific embodiments.

[0057] like Figure 1 As shown, in a preferred embodiment of the method for predicting loose crown defects in oriented / single-crystal crowned working blades according to the present invention, the prediction method includes the following steps in sequence:

[0058] Step 1: Establish a 3D parametric model of the crowned working blade using 3D modeling software. This 3D parametric model includes the crown-blade transition structure features. Import the 3D parametric model of the crowned working blade into ProCAST finite element simulation software and perform mesh generation.

[0059] Step 2: At the site of the directional solidification process for the crowned working blade, test the temperature change data of the inner and outer surfaces of the shell of the crowned working blade throughout the entire directional solidification process;

[0060] Step 3: Based on the temperature change data of the inner and outer surfaces of the crowned working blade shell obtained from the field test throughout the entire directional solidification process, the heat transfer coefficients of the inner and outer surfaces of the crowned working blade shell throughout the entire directional solidification process are calculated by inversion.

[0061] Step 4: Input the heat transfer coefficients of the inner and outer surfaces of the crowned working blade shell obtained from the inversion calculation into the ProCAST finite element simulation software. At the same time, set the material parameters of the crowned working blade and the directional solidification process parameters. Then, perform dynamic simulation on the entire directional solidification process to obtain the dynamic simulation results.

[0062] Step 5: Obtain the temperature gradient field data distribution map and cooling rate field data distribution map of the leaf crown from the dynamic simulation results, and extract the temperature gradient and cooling rate at several points in the leaf crown from the data distribution map;

[0063] Step 6: Based on the temperature gradient and cooling rate at several points in the extracted leaf crown, the Niyama criterion with geometric feature weighting optimization is used to calculate the loosening formation criterion value at several points in the leaf crown, and then the average value is taken as the loosening formation criterion value of the leaf crown.

[0064] Step 7: Using ProCAST finite element simulation software, calculate the simulation image of the loosening defect of the working blade with crown based on the standard Niyama criterion. Extract the part of the simulation image where the simulation result of the loosening defect of the crown part is less than the calculated value of the loosening formation criterion for the crown part, and identify this part as a high-risk loosening area.

[0065] Step 8: Use a micro-nano 3D CT analyzer to perform a 3D scan on the crowned working blade casting prepared on-site by the directional solidification process, obtain the measured results of the porosity defects of the crowned working blade casting, and verify the spatial matching degree between the measured results of the porosity defects of the crowned working blade casting and the simulation results of porosity defects in the high-risk porosity areas.

[0066] Step 9: When the agreement between the simulation results and the measured results is not less than 75%, the simulation results are valid. Save the simulation results and the calculated criterion value for the loosening of the leaf crown, which will be used for subsequent prediction of loosening defects in the leaf crown of the working leaf with the crown and optimization of the directional solidification process.

[0067] Step 10: When the agreement between the simulation results and the measured results is less than 75%, the parameters of the Niyama criterion with geometric feature weighting optimization need to be corrected. Based on the corrected Niyama criterion with geometric feature weighting optimization, repeat steps 6 to 8 until the agreement between the simulation results and the measured results is not less than 75%, thus completing the prediction of the loose canopy defect of the working leaf with crown.

[0068] In step one, the crowned working blade includes a crown, a crown-blade transition structure, a blade, a fin plate, and a tenon; the three-dimensional parametric model includes the crown thickness, the crown cross-sectional area, the blade leading edge thickness at the connection with the crown, and the blade cross-sectional area at the connection with the crown.

[0069] The size of the grid unit in the leaf crown region is no greater than 0.5 mm. The size of the grid unit in the leaf crown-leaf body transition structure is 1.5-1.75 times the size of the grid unit in the leaf crown region. The size of the grid unit in the leaf body region is 2-2.5 times the size of the grid unit in the leaf crown region. The size of the grid unit in the edge plate region and the tenon region is 5-10 times the size of the grid unit in the leaf crown region.

[0070] In step two, the entire process of directional solidification includes a pouring stage and a pulling stage; the temperature measurement area includes the crown area located on the leaf basin side and the leaf back side of the working blade shell, the crown-leaf body transition structure, and the inner and outer surfaces of the leaf body area.

[0071] In step three, the heat transfer coefficients of the inner and outer surfaces of the crowned working blade shell are calculated through inversion throughout the entire directional solidification process. The inversion calculation equation is as follows: In the formula,

[0072] —Heat flow rate of the temperature measurement area, W / m 2 ;

[0073] —Heat transfer coefficient of the temperature measurement area, W / (m²) 2 ·K);

[0074] , —The temperature of the medium on both sides of the heat exchange interface, in K.

[0075] When the heat exchange interface is the outer surface of a shell with crowned working blades. The temperature of the air. The temperature of the shell with crowned blades; when the heat exchange interface is the inner surface of the shell with crowned blades, The temperature of the shell of the crowned working blade. The temperature of the molten metal.

[0076] In step four, the material parameters include elastic modulus, Poisson's ratio, and thermal conductivity; the directional solidification process parameters include pouring temperature and drawing speed.

[0077] In step five, the temperature gradient and cooling rate at several points in the leaf crown region are extracted from the data distribution map. The extraction points are located in the leaf crown region on the leaf basin side, the leaf crown region on the leaf back side, the leading edge of the leaf blade where it connects with the leaf crown, and the trailing edge of the leaf blade where it connects with the leaf crown. At least two points are extracted for each of the following leaf crown regions: the leaf crown region on the leaf basin side, the leaf crown region on the leaf back side, the leading edge of the leaf blade where it connects with the leaf crown, and the trailing edge of the leaf blade where it connects with the leaf crown.

[0078] In step six, the Niyama criterion for geometric feature weighted optimization is: In the formula,

[0079] —The loose formation criterion value after geometric feature weighting optimization;

[0080] — Leaf crown thickness, mm;

[0081] —Thickness of the leading edge of the leaf blade where it connects to the leaf crown, mm;

[0082] —Cross-sectional area of ​​the leaf crown, mm 2 ;

[0083] —The cross-sectional area of ​​the leaf blade at the junction with the leaf crown, in mm 2 ;

[0084] —Temperature gradient, °C / mm;

[0085] —Cooling rate, °C / s;

[0086] — Correction factor, empirical value is 0.5-0.8.

[0087] In step seven, the standard Niyama criterion is: In the formula,

[0088] —Standard criteria for the formation of looseness;

[0089] —Temperature gradient, °C / mm;

[0090] —Cooling rate, °C / s.

[0091] In step ten, the parameters of the Niyama criterion for geometric feature weighted optimization are modified, that is, the correction coefficients are adjusted. Make corrections by adjusting the correction factor within the empirical range of 0.5-0.8.

[0092] In this embodiment, the target predicted blade is a single-crystal blade of a low-pressure turbine of a certain type of aero-engine, and its material is DD6 high-temperature alloy. Blade crown structural parameters: blade crown thickness 1.2 mm, blade crown cross-sectional area 15.7 mm². 2 The leaf blade thickness at the junction with the crown is 2.8 mm, and the cross-sectional area at this junction is 20.3 mm². 2 The three-dimensional parametric model of the leaf was meshed, and the mesh morphology of the crown region, the crown-blade transition structure, and the blade region is as follows: Figure 2 As shown.

[0093] The boundary conditions obtained by inversion calculation based on the temperature measurement data of the inner and outer surfaces of the crowned working blade shell during the entire directional solidification process obtained from field tests are as follows: The set directional solidification process parameters are: drawing speed 4μm / s, shell preheating temperature 1520℃, and pouring temperature 1520℃.

[0094] Dynamic simulation of the entire directional solidification process was performed, and the dynamic simulation results were obtained. The temperature gradient field data distribution of the leaf crown is shown in the figure below. Figure 3 As shown, the distribution of cooling rate field data in the leaf crown region is as follows: Figure 4 As shown; nine points were extracted from the leaf crown area, and their locations are as follows. Figure 5 As shown.

[0095] Based on the temperature gradient and cooling rate at nine extraction points in the leaf crown, the Niyama criterion with geometric feature weighting optimization was used to calculate the loosening formation criterion value at each of the nine extraction points. The average value was then taken as the loosening formation criterion value for the leaf crown.

[0096] In the initial prediction, the correction coefficient k=0.6, and the median of empirical values ​​was used. The calculated criterion value for loosening of the leaf crown was 24. The calculation process is as follows:

[0097]

[0098] Using ProCAST finite element simulation software, the distribution of loose defects in the crowned working blade was calculated based on the standard Niyama criterion. Figure 6 As shown, the portion of the simulation result of loosening defects in the leaf crown is less than the criterion value for loosening formation in the leaf crown calculated during the initial prediction, and this portion is identified as a high-risk loosening area.

[0099] Comparison of the initial simulation results of porosity defects with the actual measured results of porosity defects in the castings. Figure 7 As shown in the figure, (a) is a distribution map of loose defects in the leaf crown area extracted from the simulation image, and (b) is a distribution map of loose defects in the field casting tested using a micro-nano 3D CT analyzer. It can be seen from the figure that the agreement between the simulation results and the measured results is only 50%. Therefore, it is necessary to correct the parameters of the geometrically weighted Niyama criterion. Based on the corrected geometrically weighted Niyama criterion, steps six to eight are repeated until the agreement between the simulation results and the measured results is not less than 75%, thus completing the prediction of loose defects in the leaf crown of the working blade.

[0100] The initial prediction correction factor was revised from 0.6 to 0.42, and the Niyama criterion for geometric feature weighted optimization was also revised. The calculated criterion value for porosity formation in the blade crown region was 12. A portion of the simulation results for porosity defects in the blade crown region that was lower than the revised criterion value was re-examined from the simulation image and identified as a high-risk porosity area. A comparison was made between the revised predicted porosity defect simulation results and the measured porosity defects in the cast parts. Figure 8 As shown, (a) is a distribution map of loose defects in the leaf crown area extracted from the simulation diagram, and (b) is a distribution map of loose defects in the field casting tested using a micro-nano 3D CT analyzer. It can be seen from the figures that the simulation results and the measured results have a 75% agreement, indicating that the simulation results are valid. The simulation results and the corrected criterion value for loose formation in the leaf crown area are saved for subsequent prediction of loose defects in the leaf crown area of ​​this crowned working blade and optimization of the directional solidification process.

[0101] The method for predicting loose defects in the crown of directional / single-crystal crowned working blades in this embodiment has the following beneficial effects: (1) By introducing a geometric feature weighting factor, the solidification characteristics of thin-walled crown structures are optimized, significantly improving the prediction accuracy of loose defects in the crown area. (2) The optimization iteration cycle of directional solidification process parameters is significantly shortened, and the efficiency is greatly improved. (3) The number of trial castings produced during the process optimization process is significantly reduced, and the scrap rate of the crown area and the overall inspection cost are significantly reduced, effectively reducing the comprehensive cost of quality control. (4) It can simultaneously meet the following advantages: it has good predictive adaptability to geometrically abrupt structures, can truly reflect the boundary conditions of the directional solidification process, and has high-precision verification methods to ensure the accuracy and reliability of the prediction.

[0102] Special Note: The technical solution of this invention involves numerous parameters, and the synergistic effects between these parameters must be comprehensively considered to achieve the beneficial effects and significant progress of this invention. Furthermore, the value ranges of each parameter in the technical solution were obtained through extensive experimentation. For each parameter and the combinations thereof, the inventors have recorded a large amount of experimental data; however, due to space limitations, the specific experimental data is not disclosed here.

[0103] It will be readily understood by those skilled in the art that this invention includes any combination of the inventive description and specific embodiments outlined in the foregoing specification and the various parts shown in the accompanying drawings. Due to space limitations and for the sake of brevity, not all of these combinations have been described in detail. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for predicting the loose crown defect in oriented / single-crystal crowned working blades, characterized in that: The prediction method includes the following steps in sequence. Step 1: Establish a 3D parametric model of the crowned working blade using 3D modeling software. This 3D parametric model includes the crown-blade transition structure features. Import the 3D parametric model of the crowned working blade into ProCAST finite element simulation software and perform mesh generation. Step 2: At the site of the directional solidification process for the crowned working blade, test the temperature change data of the inner and outer surfaces of the shell of the crowned working blade throughout the entire directional solidification process; Step 3: Based on the temperature change data of the inner and outer surfaces of the crowned working blade shell obtained from the field test throughout the entire directional solidification process, the heat transfer coefficients of the inner and outer surfaces of the crowned working blade shell throughout the entire directional solidification process are calculated by inversion. Step 4: Input the heat transfer coefficients of the inner and outer surfaces of the crowned working blade shell obtained from the inversion calculation into the ProCAST finite element simulation software. At the same time, set the material parameters of the crowned working blade and the directional solidification process parameters. Then, perform dynamic simulation on the entire directional solidification process to obtain the dynamic simulation results. Step 5: Obtain the temperature gradient field data distribution map and cooling rate field data distribution map of the leaf crown from the dynamic simulation results, and extract the temperature gradient and cooling rate at several points in the leaf crown from the data distribution map; Step 6: Based on the temperature gradient and cooling rate at several points in the extracted leaf crown, the Niyama criterion with geometric feature weighting optimization is used to calculate the loosening formation criterion value at several points in the leaf crown, and then the average value is taken as the loosening formation criterion value of the leaf crown. Step 7: Using ProCAST finite element simulation software, calculate the simulation image of the loosening defect of the working blade with crown based on the standard Niyama criterion. Extract the part of the simulation image where the simulation result of the loosening defect of the crown part is less than the calculated value of the loosening formation criterion for the crown part, and identify this part as a high-risk loosening area. Step 8: Use a micro-nano 3D CT analyzer to perform a 3D scan on the crowned working blade casting prepared on-site by the directional solidification process, obtain the measured results of the porosity defects of the crowned working blade casting, and verify the spatial matching degree between the measured results of the porosity defects of the crowned working blade casting and the simulation results of porosity defects in the high-risk porosity areas. Step 9: When the agreement between the simulation results and the measured results is not less than 75%, the simulation results are valid. Save the simulation results and the calculated criterion value for the loosening of the leaf crown, which will be used for subsequent prediction of loosening defects in the leaf crown of the working leaf with the crown and optimization of the directional solidification process. Step 10: When the agreement between the simulation results and the measured results is less than 75%, the parameters of the Niyama criterion with geometric feature weighting optimization need to be corrected. Based on the corrected Niyama criterion with geometric feature weighting optimization, repeat steps 6 to 8 until the agreement between the simulation results and the measured results is not less than 75%, thus completing the prediction of the loose canopy defect of the working leaf with crown.

2. The method for predicting loose crown defects in directional / single-crystal crowned working blades according to claim 1, characterized in that: In step one, the crowned working blade includes a crown, a crown-blade transition structure, a blade, a fin plate, and a tenon; the three-dimensional parametric model includes the crown thickness, the crown cross-sectional area, the blade leading edge thickness at the connection with the crown, and the blade cross-sectional area at the connection with the crown.

3. The method for predicting the loose crown defect of directional / single-crystal crowned working blades according to claim 2, characterized in that: In step one, the size of the grid unit in the leaf crown region is no greater than 0.5 mm, the size of the grid unit in the leaf crown-leaf body transition structure is 1.5-1.75 times the size of the grid unit in the leaf crown region, the size of the grid unit in the leaf body region is 2-2.5 times the size of the grid unit in the leaf crown region, and the size of the grid unit in the edge plate region and the tenon region is 5-10 times the size of the grid unit in the leaf crown region.

4. The method for predicting the loose crown defect of directional / single-crystal crowned working blades according to claim 3, characterized in that: In step two, the entire process of directional solidification includes a pouring stage and a pulling stage; the temperature measurement area includes the crown area located on the leaf basin side and the leaf back side of the working blade shell, the crown-leaf body transition structure, and the inner and outer surfaces of the leaf body area.

5. The method for predicting loose crown defects in directional / single-crystal crowned working blades according to claim 4, characterized in that: In step three, the heat transfer coefficients of the inner and outer surfaces of the crowned working blade shell are calculated through inversion throughout the entire directional solidification process. The inversion calculation equation is as follows: In the formula, —Heat flow rate of the temperature measurement area, W / m 2 ; —Heat transfer coefficient of the temperature measurement area, W / (m²) 2 ·K); , —The temperature of the medium on both sides of the heat exchange interface, in K; When the heat exchange interface is the outer surface of a shell with crowned working blades. The temperature of the air. The temperature of the shell with crowned blades; when the heat exchange interface is the inner surface of the shell with crowned blades, The temperature of the shell of the crowned working blade. The temperature of the molten metal.

6. The method for predicting the loose crown defect of directional / single-crystal crowned working blades according to claim 5, characterized in that: In step four, the material parameters include elastic modulus, Poisson's ratio, and thermal conductivity; the directional solidification process parameters include pouring temperature and drawing speed.

7. The method for predicting the loose crown defect of directional / single-crystal crowned working blades according to claim 6, characterized in that: In step five, the temperature gradient and cooling rate at several points in the leaf crown region are extracted from the data distribution map. The extraction points are located in the leaf crown region on the leaf basin side, the leaf crown region on the leaf back side, the leading edge of the leaf blade where it connects with the leaf crown, and the trailing edge of the leaf blade where it connects with the leaf crown. At least two points are extracted for each of the following leaf crown regions: the leaf crown region on the leaf basin side, the leaf crown region on the leaf back side, the leading edge of the leaf blade where it connects with the leaf crown, and the trailing edge of the leaf blade where it connects with the leaf crown.

8. The method for predicting the loose crown defect of directional / single-crystal crowned working blades according to claim 7, characterized in that: In step six, the Niyama criterion for geometric feature weighted optimization is: In the formula, —The loose formation criterion value after geometric feature weighting optimization; — Leaf crown thickness, mm; —Thickness of the leading edge of the leaf blade where it connects to the leaf crown, mm; —Cross-sectional area of ​​the leaf crown, mm 2 ; —The cross-sectional area of ​​the leaf blade at the junction with the leaf crown, in mm 2 ; —Temperature gradient, °C / mm; —Cooling rate, °C / s; — Correction factor, empirical value is 0.5-0.

8.

9. The method for predicting loose crown defects in directional / single-crystal crowned working blades according to claim 8, characterized in that: In step seven, the standard Niyama criterion is: In the formula, —Standard criteria for the formation of looseness; —Temperature gradient, °C / mm; —Cooling rate, °C / s.

10. The method for predicting the loose crown defect of directional / single-crystal crowned working blades according to claim 9, characterized in that: In step ten, the parameters of the Niyama criterion for geometric feature weighted optimization are modified, that is, the correction coefficients are adjusted. Make corrections by adjusting the correction factor within the empirical range of 0.5-0.8.

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