CN110727999A - Method for optimally designing wheel disc simulation piece based on stress and field intensity analysis - Google Patents
Method for optimally designing wheel disc simulation piece based on stress and field intensity analysis Download PDFInfo
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Abstract
The invention discloses a method for optimally designing a wheel disc simulation piece based on stress and field intensity analysis, and belongs to the technical field of structural design. The method takes the geometric dimension of the model part as a design variable, and the structural dimension of the simulation part is fit to reality through the restriction of actual conditions among related variables. And setting a main stress fitting deviation coefficient of the simulation piece and taking the main stress fitting deviation coefficient as an optimized objective function of the simulation piece by a method for eliminating the influence of the external load through a three-way main stress ratio, and estimating the main stress fitting degree of the simulation piece and the wheel disc. And then setting a stress gradient deviation coefficient as a target function of simulation piece optimization, finding a stress gradient path position by a three-dimensional stress gradient search method, and evaluating the fitting degree of the stress field of the simulation piece and the wheel disc. And comparing the model which accords with the fitting precision of the main stress and the stress gradient with the equivalent stress curve of the wheel disc to determine the simulation piece with the optimal geometric dimension.
Description
Technical Field
The invention relates to the technical field of structural design, in particular to a method for optimally designing a wheel disc simulation piece based on stress and field intensity analysis.
Background
The compressor is one of important components of the aero-engine, the low-pressure compressor wheel disc is a key component of the aero-engine, large-scale fatigue tests are difficult to perform due to the characteristics of high manufacturing cost, large volume and complex structure of the engine, and the fatigue life prediction precision is influenced. Therefore, in engineering, a simulation piece with lower manufacturing cost is usually used for replacing a real wheel disc to carry out a fatigue test, and the life evaluation is carried out by combining the real wheel disc.
In order to enable the path position of the main stress and the stress gradient received by the simulation piece to be well fitted with the path position of the main stress and the stress gradient of the wheel disc under the same condition in the process of carrying out related experiments, the simulation piece which is highly fitted with the main stress and the stress gradient in the related experiments with the wheel disc under the same condition needs to be designed, and related simulation analysis is carried out.
In the prior art, the size parameters of the part with larger influence relation are mostly quantitatively set to control the optimization process, and in addition, in the prior art, a method for optimizing by using a stress gradient method mostly adopts a two-dimensional model which can not well reflect the real stress field of the wheel disc. The invention adopts APDL language to assign values to all size parameters and carry out optimization calculation, thereby better realizing the optimization design of the parameters of the simulation piece. Meanwhile, the invention adopts a three-dimensional model, and can realize the calculation of the path of the stress gradient of the three-dimensional space so as to optimize and design the simulation piece. Meanwhile, the two methods are respectively set as the first optimization and the second optimization and simultaneously optimize and design the simulation piece, so that the analysis result of the simulation piece can better accord with the analysis result of a real wheel disc.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a method for optimally designing a wheel disc simulation piece based on stress and field intensity analysis.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows: a method for optimally designing a wheel disc simulation piece based on stress and field intensity analysis is disclosed, wherein the flow of the method is shown in figure 1, and the method comprises the following steps:
step 1: the design simulation piece is a cuboid with the length of H, the width of W and the thickness of T, a notch is designed in the middle of the cuboid, the opening radius of the notch is R, the opening depth is D, the opening size is G, and the inclination angle is BETA;
step 2: designing constraint conditions of structural parameters of the simulation piece;
step 2.1: and (3) constraining the relation between the width W of the test piece and the opening depth D:
D＜W；
reserving a certain ligament width between the opening depth and the width of the test piece, and defining an intermediate variable RD, so that:
D＝RD×(W-15)+3
and (3) determining RD as a design variable, ensuring that RD belongs to [0, 1], and ensuring the value range of the opening depth as follows:
D∈(3，W-12)；
step 2.2: the relationship between opening depth D, opening size G and notch radius R constrains:
the notch radius must not be greater than the smaller of the opening depth and half of the opening size, i.e. satisfies:
R≤min(D，G/2)
and in order to meet the processing precision of the simulated piece notch, the notch radius cannot be too small, namely:
R≥1
in order to ensure that the notch radius simultaneously meets two geometric dimension variable conditions of R ≤ min (D, G/2) and R ≥ 1, an intermediate variable notch radius ratio RR is defined so as to meet:
taking RR as a design variable, and making RR belong to [0, 1], so that the notch radius can meet the condition;
step 2.3: the relationship between the notch deflection angle BETA and the specimen thickness T, opening depth D constrains:
defining an intermediate variable RBET, let:
when the variable RBET belongs to the interval of [0, 1], the phenomenon that a notch cannot penetrate through a test piece is avoided.
And step 3: modeling finite elements of the simulation part;
and 4, step 4: carrying out a stress test on the wheel disc to obtain a three-dimensional main stress at the maximum stress point of the wheel disc;
and 5: fixing the lower plane of the model in the step 3, applying a pulling force on the upper plane, and carrying out stress analysis on the simulation piece;
step 6: introducing a main stress fitting deviation coefficient, and measuring the fitting degree of the three-dimensional main stress ratio of the simulation piece and the wheel disc through the main stress fitting precision;
step 6.1: the three-dimensional main stress is normalized by introducing a parameter stress ratio as a comparison quantity, and is defined as follows:
wherein s is1、s2And s3Respectively a first main stress, a second main stress and a third main stress at the maximum stress point, and the unit is MPa; rst21And rst31The ratio of the first main stress to the second main stress and the ratio of the first main stress to the third main stress at the maximum stress point are shown;
step 6.2: introducing a main stress fitting deviation coefficient to measure the degree of fitting of the three-dimensional main stress ratio of the simulation part and the wheel disc, and defining:
norm_str＝|rst21d-rst21s+rst31d-rst31s|
wherein norm _ str is a fitting deviation coefficient of the simulation piece and the three-dimensional main stress of the wheel disc; rst21dAnd rst31dRespectively the ratio of the first two principal stresses and the ratio of the first three principal stresses at the maximum stress point of the wheel disc; rst21sAnd rst31sRespectively representing the ratio of the first two principal stresses and the ratio of the first three principal stresses at the maximum stress point of the simulation piece;
the fitting degree of the simulation piece and the wheel disc can be roughly estimated according to the fitting deviation coefficient of the main stress, the smaller the deviation coefficient is, namely the norm _ str is used as a target function, the smaller the deviation coefficient is, the higher the fitting degree of the simulation piece and the wheel disc is, the fitting precision can be determined according to needs, and the convergence of the norm _ str of the target function is realized.
And 7: judging the fitting degree of the stress field of the simulation piece and the stress field of the real wheel disc by adopting a stress gradient fitting method and through the stress gradient fitting precision;
step 7.1: searching a maximum stress point N of the model, namely a dangerous point in the model, and enabling the origin of the working plane to coincide with the maximum stress point;
step 7.2: on a working plane, extracting a two-dimensional stress gradient path, wherein the two-dimensional stress gradient path is searched, the two-dimensional stress gradient path is obtained by taking a dangerous point N as a center and taking a certain tiny distance as a search radius, establishing an annular path, extracting stress values of all discrete positions on the annular path, finding out the minimum stress value and the position through comparison, marking the minimum stress value as a path point A, taking the dangerous point N as a vector starting point and the minimum stress path point A as a vector terminal point, and solving the vector direction, namely the stress gradient direction of the region;
step 7.3: continuously rotating the working plane by a certain angle, and continuously searching for a gradient path according to the mode of the step 7.2, wherein the smaller the rotation angle of the working plane is, the closer the formed surface is to the spherical surface, and the more accurate the obtained result is;
step 7.4: comparing all two-dimensional stress gradient paths on different working planes, and finding out one of the two-dimensional stress gradient paths with the highest stress reduction rate, namely the three-dimensional stress gradient path;
step 7.5: moving the origin of the working plane to the vector end point A of the searched three-dimensional stress gradient, and repeatedly executing the step 7.2 and the step 7.4 according to the method to obtain the three-dimensional stress gradient vector of each section, and connecting the vectors end to form the whole three-dimensional stress gradient path;
according to the principle of calculus, if the search radius is small enough, the end-to-end vector groups become stress gradient paths;
step 7.6: inserting the same number of interpolation points between every two path points, commonly referring the path points and the interpolation points as nodes, totaling m, and simultaneously obtaining stress values of the m nodes; in order to fit the stress field of the simulation piece and the stress field of the real wheel disc, the stress gradient path of the wheel disc and the stress gradient path of the simulation piece are also required to be configured in the same way, so that the stress gradient path of the wheel disc and the stress gradient path of the simulation piece have the same path length and the same interpolation point interval, the number of interpolation points is the same, and the stress values of m nodes on the gradient path of the wheel disc are extracted in advance;
step 7.7: comparing the stress values of the same path node on the stress gradient path of the simulation part with the stress values of m nodes on the stress gradient path of the wheel disc obtained in the step 7.6, and defining:
dgrap＝|Sdp-Ssp|
wherein dgrapThe difference between the stress of the wheel disc and the stress of the simulation piece at the path distance p is expressed in MPa; sdpThe equivalent stress value of the wheel disc at the position of the path distance p is expressed in MPa; sspThe equivalent stress value of the simulation piece at the path distance p and the position is in MPa;
step 7.8: and comparing the stress value of each interpolation point of the wheel disc and the simulation piece on the path to obtain the fitting degree of the whole stress curve:
wherein the content of the first and second substances,norm _ gra is a stress gradient fitting deviation coefficient of the simulation piece and the wheel disc; dgrapThe difference between the stress of the wheel disc and the stress of the simulation piece at the path distance p is expressed in MPa; m is the total number of interpolation points on the path;
the smaller the fitting deviation coefficient norm _ gra of the stress gradient is, the more sufficient the fitting of the stress gradient is, and accordingly norm _ gra is set as an objective function of the second optimization; the fitting accuracy can be determined as required, and the convergence of the objective function norm _ gra of the second optimization is realized.
And 8: if the fitting result obtained in the steps 6 and 7 does not meet the fitting precision, adjusting the structural size of the simulation piece in the step 1 by combining the constraint condition in the step 2;
step 8.1: according to the structural parameters of the simulation piece set in the step 1 and the structural parameter constraint conditions of the simulation piece set in the step 2 in the claim 1, the initial values and the optimization ranges of the variables are designed in a self-defined mode, and meanwhile, the optimization range of the opening size G is set;
step 8.2: and setting variables by using an APDL language of ANSYS software, so that the design variables are automatically changed within an optimization range for optimization.
And step 9: repeating the step 2 to the step 8 until a plurality of simulation pieces meeting the fitting precision of the main stress and the fitting precision of the stress gradient are obtained;
step 10: and (4) comparing the simulation piece optimized structure obtained in the step (9) with an equivalent stress generation distance-equivalent stress curve graph of the wheel disc, and selecting simulation piece data meeting the design criteria of the simulation piece.
The design criteria of the simulation piece are as follows: the ultimate purpose of the dummy design is to ensure that it has the same service life as the real component.
The simulation must satisfy the following conditions: the material and processing technique of the simulation piece are consistent with those of the wheel disc. The simulation piece can be subjected to a fatigue test on a fatigue testing machine, and the testing temperature is the same as the real wheel disc working temperature. The three-dimensional main stress of the stress concentration part of the simulation piece is similar to the three-dimensional main stress of the actual wheel disc. The stress gradient at the key part of the simulation piece and the maximum stress point of the wheel disc keeps the fitting performance.
Adopt the produced beneficial effect of above-mentioned technical scheme to lie in:
(1) the invention mainly adopts an optimized design module of ANSYS software for designing a simulation piece, and determines an optimized objective function value by setting the form of an optimized objective function and adjusting related geometric dimension variables;
(2) according to the method, two objective functions, namely a main stress fitting deviation coefficient and a stress gradient deviation coefficient, are set, the simulation piece and the wheel disc are effectively combined together under the same condition, and the optimal geometric size data of the simulation piece can be visually and clearly obtained;
(3) when fitting optimization is performed on a simulation piece, related geometric dimensions of the simulation piece form a variable group which is mutually restricted, and the structural dimension of the simulation piece is more in line with the reality through restriction of actual conditions among related variables;
(4) the method utilizes an ANSYS annular path to search the three-dimensional stress gradient, adopts parameterized programming in software, can run on any model, and has strong universality and reproducibility.
Drawings
FIG. 1 is a flow chart of a method for optimally designing a wheel disc simulation based on stress and field strength analysis according to the present invention;
FIG. 2 is a schematic structural diagram of a simulation of fatigue life of a wheel disc according to the present invention;
FIG. 3 is a schematic diagram of a three-dimensional stress gradient path for region search in an embodiment of the present invention;
(a) searching a maximum stress point diagram;
(b) searching a two-dimensional stress gradient path diagram at a dangerous point;
(c) searching a three-dimensional stress gradient path diagram at a dangerous point;
(d) searching a three-dimensional stress gradient path diagram in a region;
FIG. 4 is a graph of a 6mm stress gradient path of a disk in accordance with an embodiment of the present invention;
FIG. 5 is a graph of equivalent stress for a 6mm path of a wheel disc in an embodiment of the present invention;
FIG. 6 is a stress-fit plot of a wheel disc simulator in an embodiment of the present invention;
fig. 7 is an equivalent stress cloud diagram of an opening portion of a No. 350 simulation piece in an embodiment of the present invention.
In the drawings:
h-simulation piece length, W-simulation piece width, T-simulation piece thickness, R-simulation piece opening radius, D-simulation piece opening depth, G-simulation piece opening size and BETA-simulation piece notch deflection angle.
Detailed Description
The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
As shown in fig. 1, the method of the present embodiment is as follows.
Step 1: designing a simulation piece to be a cuboid with the length of H, the width of W and the thickness of T, wherein a notch is designed in the middle of the cuboid, the opening radius of the notch is R, the opening depth is D, the opening size is G, the inclination angle is BETA, and the structure of the simulation piece is schematically shown in figure 2;
step 2: designing constraint conditions of structural parameters of the simulation piece;
step 2.1: and (3) constraining the relation between the width W of the test piece and the opening depth D:
D＜W：
reserving a certain ligament width between the opening depth and the width of the test piece, and defining an intermediate variable RD, so that:
D＝RD×(W-15)+3
and (3) determining RD as a design variable, ensuring that RD belongs to [0, 1], and ensuring the value range of the opening depth as follows:
D∈(3，W-12)；
step 2.2: the relationship between opening depth D, opening size G and notch radius R constrains:
the notch radius must not be greater than the smaller of the opening depth and half of the opening size, i.e. satisfies:
R≤min(D，G/2)
and in order to meet the processing precision of the simulated piece notch, the notch radius cannot be too small, namely:
R≥1
in order to ensure that the notch radius simultaneously meets two geometric dimension variable conditions of R ≤ min (D, G/2) and R ≥ 1, an intermediate variable notch radius ratio RR is defined so as to meet:
taking RR as a design variable, and making RR belong to [0, 1], so that the notch radius can meet the condition;
step 2.3: the relationship between the notch deflection angle BETA and the specimen thickness T, opening depth D constrains:
defining an intermediate variable RBET, let:
when the variable RBET belongs to the interval of [0, 1], the phenomenon that a notch cannot penetrate through a test piece is avoided.
And step 3: modeling finite elements of the simulation part;
and 4, step 4: carrying out a stress test on the wheel disc to obtain a three-dimensional main stress at the maximum stress point of the wheel disc;
and 5: fixing the lower plane of the model in the step 3, applying a pulling force on the upper plane, and carrying out stress analysis on the simulation piece;
three analysis iteration modes are set by using ANSYS software, and respectively comprise: the method comprises the following steps of (1) selecting one of a zero-order method, a first-order optimization method and a random method for simulation optimization as required when analysis is carried out each time;
step 6: introducing a main stress fitting deviation coefficient, and measuring the fitting degree of the three-dimensional main stress ratio of the simulation piece and the wheel disc through the main stress fitting precision;
step 6.1: the three-dimensional main stress is normalized by introducing a parameter stress ratio as a comparison quantity, and is defined as follows:
wherein s is1、s2And s3Respectively a first main stress, a second main stress and a third main stress at the maximum stress point, and the unit is MPa; rst21And rst31The ratio of the first main stress to the second main stress and the ratio of the first main stress to the third main stress at the maximum stress point are shown;
step 6.2: introducing a main stress fitting deviation coefficient to measure the degree of fitting of the three-dimensional main stress ratio of the simulation part and the wheel disc, and defining:
norm_str＝|rst21d-rst21s|+|rst31d-rst31s|
wherein norm _ str is a fitting deviation coefficient of the simulation piece and the three-dimensional main stress of the wheel disc; rst21dAnd rst21dRespectively the ratio of the first two principal stresses and the ratio of the first three principal stresses at the maximum stress point of the wheel disc; rst21sAnd rst31sRespectively representing the ratio of the first two principal stresses and the ratio of the first three principal stresses at the maximum stress point of the simulation piece;
the fitting degree of the simulation piece and the wheel disc can be roughly estimated according to the fitting deviation coefficient of the main stress, the smaller the deviation coefficient is, namely the norm _ str is used as a target function, the smaller the deviation coefficient is, the higher the fitting degree of the simulation piece and the wheel disc is, the fitting precision can be determined according to needs, and the convergence of the norm _ str of the target function is realized.
And 7: judging the fitting degree of the stress field of the simulation piece and the stress field of the real wheel disc by adopting a stress gradient fitting method and through the stress gradient fitting precision;
step 7.1: searching a maximum stress point N of the model, namely a dangerous point in the model, as shown in fig. 3(a), and enabling the origin of the working plane to coincide with the maximum stress point;
step 7.2: on a working plane, extracting a two-dimensional stress gradient path, wherein the two-dimensional stress gradient path is established by taking a dangerous point N as a center and a certain tiny distance as a search radius, as shown in fig. 3(b), extracting stress values of all discrete positions on the annular path, finding out the minimum stress value and the position of the minimum stress value through comparison, marking the minimum stress value as a path point A, taking the dangerous point N as a vector starting point and the minimum stress path point A as a vector terminal point, and solving the vector direction, namely the stress gradient direction of the region;
step 7.3: continuously rotating the working plane by a certain angle, and continuously searching for a gradient path according to the mode of the step 7.2, wherein the smaller the rotation angle of the working plane is, the closer the formed surface is to the spherical surface, and as shown in fig. 3(c), the more accurate the obtained result is;
step 7.4: comparing all two-dimensional stress gradient paths on different working planes, and finding out one of the two-dimensional stress gradient paths with the highest stress reduction rate, namely the three-dimensional stress gradient path;
step 7.5: moving the origin of the working plane to the vector end point A of the searched three-dimensional stress gradient, and repeatedly executing the step 7.2 and the step 7.4 according to the method, so that the three-dimensional stress gradient vector of each section can be obtained, and the vectors are connected end to form the whole three-dimensional stress gradient path, as shown in fig. 3 (d);
according to the principle of calculus, if the search radius is small enough, the end-to-end vector groups become stress gradient paths, in actual calculation, the too small search radius can cause the number of iteration steps to be increased, the calculation time is greatly increased, and therefore the appropriate search radius is given by integrating the calculation accuracy and the calculation time.
As shown in fig. 3, in the present embodiment, 30 points with the fastest stress drop are searched for as path points with 0.2mm as the search radius, and fig. 3 shows the process of searching the three-dimensional stress gradient path in the area.
Step 7.6: inserting the same number of interpolation points between every two path points, commonly referring the path points and the interpolation points as nodes, totaling m, and simultaneously obtaining stress values of the m interpolation points; in order to fit the stress field of the simulation piece and the stress field of the real wheel disc, the stress gradient path of the wheel disc and the stress gradient path of the simulation piece also need to be configured in the same way, and stress values of m nodes on the gradient path of the wheel disc are extracted in advance;
the finite element algorithm can only obtain the stress value at the node, and for the stress value at any non-node position, the finite element software is obtained by an interpolation algorithm. In this embodiment, there are 20 interpolation points in every two path points. The total length of the path is 6mm and there are 600 interpolation points to provide the comparison.
Step 7.7: comparing the stress values of the same path node on the stress gradient path of the simulation part with the stress values of m nodes on the stress gradient path of the wheel disc obtained in the step 7.6, and defining:
dgrap＝|Sdp-Ssp|
wherein dgrapThe difference between the stress of the wheel disc and the stress of the simulation piece at the path distance p is expressed in MPa; sdpThe equivalent stress value of the wheel disc at the position of the path distance p is expressed in MPa; sspThe equivalent stress value of the simulation piece at the path distance p and the position is in MPa;
step 7.8: and comparing the stress value of each interpolation point of the wheel disc and the simulation piece on the path to obtain the fitting degree of the whole stress curve:
wherein norm _ gra is a stress gradient fitting deviation coefficient of the simulation piece and the wheel disc; dgrapThe difference between the stress of the wheel disc and the stress of the simulation piece at the path distance p is expressed in MPa; m is the total number of interpolation points on the path;
the smaller the fitting deviation coefficient norm _ gra of the stress gradient is, the more sufficient the fitting of the stress gradient is, and accordingly norm _ gra is set as an objective function of the second optimization; the fitting accuracy can be determined as required, and the convergence of the objective function norm _ gra of the second optimization is realized.
And 8: if the fitting result obtained in the steps 6 and 7 does not meet the fitting precision, adjusting the structural size of the simulation piece in the step 1 by combining the constraint condition in the step 2;
step 8.1: according to the structural parameters of the simulation piece set in the step 1 and the structural parameter constraint conditions of the simulation piece set in the step 2 in the claim 1, the initial values and the optimization ranges of the variables are designed in a self-defined mode, and meanwhile, the optimization range of the opening size G is set;
step 8.2: and setting variables by using an APDL language of ANSYS software, so that the design variables are automatically changed within an optimization range for optimization.
And step 9: repeating the step 2 to the step 8 until a plurality of simulation pieces meeting the fitting precision of the main stress and the fitting precision of the stress gradient are obtained;
step 10: and (4) comparing the simulation piece optimized structure obtained in the step (9) with an equivalent stress generation distance-equivalent stress curve graph of the wheel disc, and selecting simulation piece data meeting the design criteria of the simulation piece.
The design criteria of the simulation piece are as follows: the ultimate purpose of the dummy design is to ensure that it has the same service life as the real component.
The simulation must satisfy the following conditions: the material and processing technique of the simulation piece are consistent with those of the wheel disc. The simulation piece can be subjected to a fatigue test on a fatigue testing machine, and the testing temperature is the same as the real wheel disc working temperature. The three-dimensional main stress of the stress concentration part of the simulation piece is similar to the three-dimensional main stress of the actual wheel disc. The stress gradient at the key part of the simulation piece and the maximum stress point of the wheel disc keeps the fitting performance.
In this embodiment, the structure of the simulation piece is optimally designed, the software automatically records the results meeting the conditions according to the objective function, and the results are sorted and counted, and table 1 shows the optimal 10 simulation piece structures after fitting optimization of the principal stress.
Table 1 main stress ratio optimum 10 times results under simulation main stress fitting optimization conditions
The simulation piece simulates the first and second principal stresses better and simulates the third principal stress worse. In the elastic state, the three-way main stress ratio of the maximum equivalent stress node of the wheel disc is 1000: 119.40: 63.56, the first main stress is 15 times of the third main stress, and the fatigue crack is mainly influenced by the first main stress in large components, so that the fitting of the third main stress can be considered to be within the error range by combining table 4.
In this example, the stress gradient path length was set to 6mm, and fig. 4 shows the position of the stress gradient path of the disk. Along the stress gradient path, an equivalent stress curve can be obtained, such as the fastest stress drop curve of the dangerous part of the mortise of the wheel disc shown in FIG. 5. And (3) obtaining the stress value of each interpolation point on the gradient path from the path processing, and leading the equivalent stress value into a simulation part optimization program after special processing for fitting optimization as a judgment basis for judging the simulation part stress gradient fitting. According to fig. 5, the stress curve decreases as a linear function in the first half of the stress gradient path, and has a distinct inflection point at 0.8mm, and the stress decreasing rate becomes slower in the second half of the path, and the stress curve gradually becomes gentle.
The simulation piece model obtained by the optimization of the main stress utilizes the solving method of the three-dimensional stress gradient to respectively calculate the stress gradient, the results are sorted, and the table 7 lists the structural data of 10 simulation pieces with the best fitting optimization of the stress gradient.
TABLE 2 optimal 10-fold results of stress gradient under simulation stress gradient fitting optimization conditions
Therefore, in the model with better fitting degree of the stress gradient, a model with better fitting to the three-dimensional principal stress is not provided, which shows that the principal stress fitting and the stress gradient fitting need to be comprehensively selected according to specific conditions.
In the embodiment, 3000 sub-optimal fitting is performed on a simulation structure, four models are selected from 130 optimal models stored in ANSYS software for scheme comparison, wherein the model No. 52 is a stress gradient curve fitting optimal model, the model No. 100 is a main stress fitting optimal model, and the models No. 350 and No. 359 are intermediate models combining two factors, wherein the stress gradient curve fitting of the model No. 350 is better, and the main stress fitting of the model No. 359 is better. Fig. 6 is a comparison of stress fit curves for model nos. 52, 100, 350, 359 and the wheel discs, with the path distance of the stress gradient indicated on the abscissa and the stress variation along the stress gradient path for the four simulations indicated on the ordinate. As can be seen in fig. 6, the stress curve shapes of the simulations nos. 52, 100, 350 and 359 were substantially similar and slightly different from the stress curves of the wheel discs. At 0.8mm path distance, the stress curve deviation is larger and the other regions fit better.
The present embodiment selects the simulation 350 as the simulation of the roulette wheel. The dimensions of the simulation 350 were rounded and the principal stresses were compared to those of the disk, as shown in table 3:
table 3 stress parameter table for model No. 350
The first principal stress of the simulation piece is similar to that of the wheel disc, with a deviation of 1%, and the third principal stress has a larger deviation, but since the first principal stress plays a dominant role in the model, the influence of the third principal stress can be approximately ignored, and an equivalent stress cloud chart of the opening part of the simulation piece is shown in fig. 7.
Claims (6)
1. A method for optimally designing a wheel disc simulation piece based on stress and field intensity analysis is characterized by comprising the following steps:
step 1: the design simulation piece is a cuboid with the length of H, the width of W and the thickness of T, a notch is designed in the middle of the cuboid, the opening radius of the notch is R, the opening depth is D, the opening size is G, and the inclination angle is BETA;
step 2: designing constraint conditions of structural parameters of the simulation piece;
and step 3: modeling finite elements of the simulation part;
and 4, step 4: carrying out a stress test on the wheel disc to obtain a three-dimensional main stress at the maximum stress point of the wheel disc;
and 5: fixing the lower plane of the model in the step 3, applying a pulling force on the upper plane, and carrying out stress analysis on the simulation piece;
step 6: introducing a main stress fitting deviation coefficient, and measuring the fitting degree of the three-dimensional main stress ratio of the simulation piece and the wheel disc through the main stress fitting precision;
and 7: judging the fitting degree of the stress field of the simulation piece and the stress field of the real wheel disc by adopting a three-dimensional stress gradient fitting method and through the stress gradient fitting precision;
and 8: if the fitting result obtained in the steps 6 and 7 does not meet the fitting precision, adjusting the structural size of the simulation piece in the step 1 by combining the constraint condition in the step 2;
and step 9: repeating the step 2 to the step 8 until a plurality of simulation pieces meeting the fitting precision of the main stress and the fitting precision of the stress gradient are obtained;
step 10: and (4) comparing the simulation piece optimized structure obtained in the step (9) with an equivalent stress generation distance-equivalent stress curve graph of the wheel disc, and selecting simulation piece data meeting the design criteria of the simulation piece.
2. The method for optimizing design of wheel disc simulation based on stress and field strength analysis as claimed in claim 1, wherein the process of step 2 is as follows:
step 2.1: and (3) constraining the relation between the width W of the test piece and the opening depth D:
D＜W；
reserving a certain ligament width between the opening depth and the width of the test piece, and defining an intermediate variable RD, so that:
D＝RD×(W-15)+3
and (3) determining RD as a design variable, ensuring that RD belongs to [0, 1], and ensuring the value range of the opening depth as follows:
D∈(3，W-12)；
step 2.2: the relationship between opening depth D, opening size G and notch radius R constrains:
the notch radius must not be greater than the smaller of the opening depth and half of the opening size, i.e. satisfies:
R≤min(D，G/2)
and in order to meet the processing precision of the simulated piece notch, the notch radius cannot be too small, namely:
R≥1
in order to ensure that the notch radius simultaneously meets two geometric dimension variable conditions of R ≤ min (D, G/2) and R ≥ 1, an intermediate variable notch radius ratio RR is defined so as to meet:
taking RR as a design variable, and making RR belong to [0, 1], so that the notch radius can meet the condition;
step 2.3: the relationship between the notch deflection angle BETA and the specimen thickness T, opening depth D constrains:
defining an intermediate variable RBET, let:
when the variable RBET belongs to the interval of [0, 1], the phenomenon that a notch cannot penetrate through a test piece is avoided.
3. The method for optimizing design of wheel disc simulation based on stress and field strength analysis as claimed in claim 1, wherein the process of step 6 is as follows:
step 6.1: the three-dimensional main stress is normalized by introducing a parameter stress ratio as a comparison quantity, and is defined as follows:
wherein s is1、s2And s3Respectively a first main stress, a second main stress and a third main stress at the maximum stress point, and the unit is MPa; rst21And rst31The ratio of the first main stress to the second main stress and the ratio of the first main stress to the third main stress at the maximum stress point are shown;
step 6.2: introducing a main stress fitting deviation coefficient to measure the degree of fitting of the three-dimensional main stress ratio of the simulation part and the wheel disc, and defining:
norm_str＝|rst21d-rst21s|+|rst32d-rst31s|
wherein norm _ str is a fitting deviation coefficient of the simulation piece and the three-dimensional main stress of the wheel disc; rst21dAnd rst31dRespectively the ratio of the first two principal stresses and the ratio of the first three principal stresses at the maximum stress point of the wheel disc; rst21sAnd rst31sRespectively representing the ratio of the first two principal stresses and the ratio of the first three principal stresses at the maximum stress point of the simulation piece;
the fitting degree of the simulation piece and the wheel disc can be roughly estimated according to the fitting deviation coefficient of the main stress, the smaller the deviation coefficient is, namely the norm _ str is used as a target function, the smaller the deviation coefficient is, the higher the fitting degree of the simulation piece and the wheel disc is, the fitting precision can be determined according to needs, and the convergence of the norm _ str of the target function is realized.
4. The method for optimizing design of wheel disc simulation based on stress and field strength analysis as claimed in claim 1, wherein the process of step 7 is as follows:
step 7.1: searching a maximum stress point N of the model, namely a dangerous point in the model, and enabling the origin of the working plane to coincide with the maximum stress point;
step 7.2: on a working plane, extracting a two-dimensional stress gradient path, wherein the two-dimensional stress gradient path is searched, the two-dimensional stress gradient path is obtained by taking a dangerous point N as a center and taking a certain tiny distance as a search radius, establishing an annular path, extracting stress values of all discrete positions on the annular path, finding out the minimum stress value and the position through comparison, marking the minimum stress value as a path point A, taking the dangerous point N as a vector starting point and the minimum stress path point A as a vector terminal point, and solving the vector direction, namely the stress gradient direction of the region;
step 7.3: continuously rotating the working plane by a certain angle, and continuously searching for a gradient path according to the mode of the step 7.2, wherein the smaller the rotation angle of the working plane is, the closer the formed surface is to the spherical surface, and the more accurate the obtained result is;
step 7.4: comparing all two-dimensional stress gradient paths on different working planes, and finding out one of the two-dimensional stress gradient paths with the highest stress reduction rate, namely the three-dimensional stress gradient path;
step 7.5: moving the origin of the working plane to the vector end point A of the searched three-dimensional stress gradient, and repeatedly executing the step 7.2 and the step 7.4 according to the method to obtain the three-dimensional stress gradient vector of each section, and connecting the vectors end to form the whole three-dimensional stress gradient path;
according to the principle of calculus, if the search radius is small enough, the end-to-end vector groups become stress gradient paths;
step 7.6: inserting the same number of interpolation points between every two path points, commonly referring the path points and the interpolation points as nodes, totaling m, and simultaneously obtaining stress values of the m nodes; in order to fit the stress field of the simulation piece and the stress field of the real wheel disc, the stress gradient path of the wheel disc and the stress gradient path of the simulation piece also need to be configured in the same way, and stress values of m nodes on the gradient path of the wheel disc are extracted in advance;
step 7.7: comparing the stress values of the same path node on the stress gradient path of the simulation part with the stress values of m nodes on the stress gradient path of the wheel disc obtained in the step 7.6, and defining:
dgrap＝|Sdp-Ssp|
wherein dgrapThe difference between the stress of the wheel disc and the stress of the simulation piece at the path distance p is expressed in MPa; sdpThe equivalent stress value of the wheel disc at the position of the path distance p is expressed in MPa; sspThe equivalent stress value of the simulation piece at the path distance p and the position is in MPa;
step 7.8: and comparing the stress value of each interpolation point of the wheel disc and the simulation piece on the path to obtain the fitting degree of the whole stress curve:
wherein norm _ gra is a stress gradient fitting deviation coefficient of the simulation piece and the wheel disc; dgrapThe difference between the stress of the wheel disc and the stress of the simulation piece at the path distance p is expressed in MPa; m is the total number of interpolation points on the path;
the smaller the fitting deviation coefficient norm _ gra of the stress gradient is, the more sufficient the fitting of the stress gradient is, and accordingly norm _ gra is set as an objective function of the second optimization; the fitting accuracy can be determined as required, and the convergence of the objective function norm _ gra of the second optimization is realized.
5. The method for optimizing design of wheel disc simulation based on stress and field strength analysis as claimed in claim 1, wherein the process of step 8 is as follows:
step 8.1: according to the structural parameters of the simulation piece set in the step 1 and the structural parameter constraint conditions of the simulation piece set in the step 2 in the claim 1, the initial values and the optimization ranges of the variables are designed in a self-defined mode, and meanwhile, the optimization range of the opening size G is set;
step 8.2: and setting variables by using an APDL language of ANSYS software, so that the design variables are automatically changed within an optimization range for optimization.
6. The method of claim 4 for optimizing the design of a simulation of a wheel disc based on stress and field strength analysis, wherein the stress gradient path of the wheel disc and the stress gradient path of the simulation are configured identically in step 7.6 by having the same path length and the same interpolation point spacing and thus the same number of interpolation points.
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