CN112380794B - Multi-disciplinary parallel cooperation optimization design method for aviation turbine engine blade - Google Patents
Multi-disciplinary parallel cooperation optimization design method for aviation turbine engine blade Download PDFInfo
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Abstract
The invention relates to a multidisciplinary optimization design method for an aviation turbine engine blade, in particular to a multidisciplinary parallel cooperation optimization design method for an aviation turbine engine blade. The method solves the problems of large calculation amount, low optimization efficiency and difficult multidisciplinary integration when the traditional method is adopted to carry out multidisciplinary optimization design on the blades of the aviation turbine engine. The method is realized by adopting the following steps: the method comprises the following steps: generating a three-dimensional shape of the blade; step two: calculating aerodynamic force of the blade; calculating the deformation of the blade; step three: repeatedly executing the first step to the second step; step four: establishing a blade flow field reduced model; establishing a blade structure reduced model; step five: obtaining a fluid-solid coupling mixed model for blade structural analysis; obtaining a fluid-solid coupling mixed model for analyzing the blade flow field; step six: establishing a blade structure optimization subsystem; establishing a blade flow field optimization subsystem; step seven: and judging whether the calculation result meets the optimization target and the constraint condition.
Description
Technical Field
The invention relates to a multidisciplinary optimization design method for an aviation turbine engine blade, in particular to a multidisciplinary parallel cooperation optimization design method for an aviation turbine engine blade.
Background
When the multidisciplinary optimization design of the aviation turbine engine blade is carried out, how to calculate the optimal blade geometric parameters is a crucial problem. If the traditional method is adopted for the multidisciplinary optimization design of the blades of the aero-turbine engine, the traditional method is limited by the principle of the traditional method, the blade performance of each group of geometric parameters can be calculated only in an iterative coupling solution mode among multidisciplines, and accordingly the optimal blade parameters are searched, so that the calculation amount is large, the optimization efficiency is low, the multidisciplinary integration is difficult, and the multidisciplinary optimization design process of the blades of the aero-turbine engine is slow. Therefore, a multidisciplinary parallel collaborative optimization design method for the blades of the aero-turbine engine is needed to be invented, so that the problems of huge calculation amount, low optimization efficiency and difficult multidisciplinary integration when the traditional method is adopted to carry out multidisciplinary optimization design on the blades of the aero-turbine engine are solved.
Disclosure of Invention
The invention provides a multidisciplinary parallel cooperative optimization design method for an aviation turbine engine blade, which aims to solve the problems of huge calculation amount, low optimization efficiency and difficult multidisciplinary integration when a traditional method is adopted to carry out multidisciplinary optimization design on the aviation turbine engine blade.
The invention is realized by adopting the following technical scheme:
a multidisciplinary parallel cooperation optimization design method for an aviation turbine engine blade is realized by adopting the following steps:
the method comprises the following steps:
generating geometric parameters, deformation and aerodynamic force of the blades by using a random generator;
then, the coordinate (x) of the first point on the pressure surface of the blade is calculated according to the geometric parameters of the blade p1 ,y p1 ) Coordinate of last point on pressure side of blade (x) p2 ,y p2 ) Coordinate (x) of the first point on the suction surface of the blade s1 ,y s1 ) Coordinate (x) of last point on suction surface of blade s2 ,y s2 )；
Then, substituting the calculation result into the profile equation set of the pressure surface of the blade and the profile equation set of the suction surface of the blade, thereby calculating the profile parameter [ a ] of the pressure surface of the blade 0 a 1 a 2 a 3 a 4 a 5 ] T Profile parameter [ b ] of suction surface of blade 0 b 1 b 2 b 3 b 4 b 5 ] T ；
The set of profile equations for the pressure side of the blade is shown below:
the set of profile equations for the suction surface of the blade is shown below:
then, according to the profile parameter [ a ] of the pressure surface of the blade 0 a 1 a 2 a 3 a 4 a 5 ] T Profile parameter of suction surface of blade 0 b 1 b 2 b 3 b 4 b 5 ] T Obtaining the molded lines of a plurality of blade sections, and generating a three-dimensional blade shape according to the molded line basic stack of each blade section;
then, inputting the three-dimensional modeling and the deformation of the blade into a CFD model of the blade;
meanwhile, inputting the three-dimensional modeling of the blade and the aerodynamic force of the blade into a finite element model of the blade;
step two:
calculating blade aerodynamic force corresponding to blade geometric parameters and blade deformation by using a blade CFD model, and storing the calculation result in a database;
meanwhile, calculating blade geometric parameters and blade deformation corresponding to blade aerodynamic force by using a blade finite element model, and storing the calculation result into a database;
step three:
repeating the first step to the second step, thereby accumulating a certain amount of calculation results in the database;
step four:
establishing a blade flow field reduced model of the influence of blade geometric parameters and blade deformation on blade aerodynamic force, and identifying the blade flow field reduced model by using a calculation result in a database;
meanwhile, establishing a blade structure reduced model of which the blade geometric parameters and the blade aerodynamic force influence the blade deformation, and identifying the blade structure reduced model by using the calculation result in the database;
step five:
obtaining a fluid-solid coupling hybrid model of blade structure analysis by the following steps:
step a: a group of blade geometric parameters are given, blade aerodynamic force is calculated by utilizing a blade flow field reduced model, and the blade aerodynamic force is input into a blade finite element model;
step b: calculating blade deformation by using a blade finite element model, and inputting the blade deformation into a blade flow field reduced model;
step c: calculating blade aerodynamic force by using a blade flow field reduced model, and judging whether the blade aerodynamic force is matched with the blade deformation; if not, executing step b; if the blade flow field reduced model and the blade finite element model are matched, coupling of the blade flow field reduced model and the blade finite element model is achieved, and therefore a fluid-solid coupling mixed model for blade structure analysis is obtained;
meanwhile, a fluid-solid coupling hybrid model for blade flow field analysis is obtained through the following steps:
step a: a group of blade geometric parameters are given, blade deformation is calculated by utilizing a blade structure reduced model, and the blade deformation is input into a blade CFD model;
step b: calculating blade aerodynamic force by using a blade CFD model, and inputting the blade aerodynamic force into a blade structure reduced model;
step c: calculating the blade deformation by using the blade structure reduced model, and judging whether the blade deformation is matched with the blade aerodynamic force; if not, executing step b; if the blade structure reduced order model and the blade CFD model are matched, the blade structure reduced order model and the blade CFD model are coupled, and therefore a fluid-solid coupling mixed model for blade flow field analysis is obtained;
step six:
establishing a blade structure optimization subsystem based on a fluid-solid coupling hybrid model of blade structure analysis; in the blade structure optimization subsystem, a group of new blade geometric parameters are automatically generated by an optimization algorithm, then the current blade structure weight, the current blade service life, the current blade maximum equivalent stress and the current blade maximum deformation are calculated by utilizing a fluid-solid coupling hybrid model of blade structure analysis, and then the calculation result is uploaded to a collaborative optimization system;
meanwhile, a blade flow field optimization subsystem is established based on a fluid-solid coupling mixed model of blade flow field analysis; in the blade flow field optimization subsystem, a group of new blade geometric parameters are automatically generated by an optimization algorithm, then the current total blade pressure ratio, the current aerodynamic lift force of the blade airfoil profile and the current oscillation of the aerodynamic force of the blade are calculated by utilizing a fluid-solid coupling mixed model of the blade flow field analysis, and then the calculation result is uploaded to a cooperative optimization system;
step seven:
judging whether the calculation result meets an optimization target and a constraint condition by using a collaborative optimization system;
if the calculation result does not meet the optimization target and the constraint condition, executing a sixth step;
and if the calculation result meets the optimization target and the constraint condition, ending the optimization.
The blade geometrical parameters include: radius r of leading edge of blade 1 Trailing edge radius r of the blade 2 Angle of attack of blade i, bladeInlet structure angle beta 1 Blade outlet structure angle beta 2 Blade installation angle gamma, blade She Xianchang b, blade cascade distance t and blade inlet leading edge wedge angle beta q Blade outlet leading edge wedge angle beta h Diameter a of blade throat and maximum thickness C of blade max 。
And in the sixth step, a global optimized MIGA algorithm and a local gradient optimized NLPQL algorithm are used for generating new geometric parameters of the blade.
In the seventh step, the optimization objective is: 1) The weight of the blade structure is minimum; 2) The blade total pressure ratio is maximum; the constraint conditions are as follows: 1) The service life of the blade is more than 2e9 cycles; the maximum equivalent stress of the blade and the maximum deformation of the blade do not exceed specified values; 2) The aerodynamic lift of the blade airfoil is greater than a specified value; the oscillation of the aerodynamic force of the blade is less than a specified amplitude; 3) And the geometric parameters of the blades in the blade structure optimization subsystem are consistent with those of the blades in the blade flow field optimization subsystem.
Compared with the traditional method, the multidisciplinary parallel collaborative optimization design method for the blade of the aero-turbine engine is based on a brand-new principle, realizes the decoupling solution of each discipline of the multidisciplinary coupling problem, eliminates the multidisciplinary coupling iteration, simultaneously can consider the coupling effect among the disciplines, and further truly realizes the distributed parallel collaborative optimization of the multidisciplinary coupling problem, thereby remarkably reducing the calculated amount, remarkably improving the optimization efficiency, simplifying the multidisciplinary integration, and remarkably accelerating the multidisciplinary optimization design process of the blade of the aero-turbine engine.
The method effectively solves the problems of huge calculation amount, low optimization efficiency and difficult multidisciplinary integration when the traditional method is adopted to carry out multidisciplinary optimization design on the blade of the aero-turbine engine, and is suitable for the multidisciplinary optimization design of the blade of the aero-turbine engine.
Drawings
FIG. 1 is a schematic flow diagram of the present invention.
Detailed Description
A multidisciplinary parallel cooperation optimization design method for an aviation turbine engine blade is realized by adopting the following steps:
the method comprises the following steps:
generating geometric parameters, deformation and aerodynamic force of the blades by using a random generator;
then, the coordinates (x) of the first point on the pressure surface of the blade are calculated according to the geometrical parameters of the blade p1 ,y p1 ) Coordinate of last point on pressure side of blade (x) p2 ,y p2 ) Coordinate (x) of the first point on the suction surface of the blade s1 ,y s1 ) Coordinate (x) of last point on suction surface of blade s2 ,y s2 )；
Then, substituting the calculation result into the profile equation set of the pressure surface of the blade and the profile equation set of the suction surface of the blade, thereby calculating the profile parameter [ a ] of the pressure surface of the blade 0 a 1 a 2 a 3 a 4 a 5 ] T Profile parameter of suction surface of blade 0 b 1 b 2 b 3 b 4 b 5 ] T ；
The set of profile equations for the pressure side of the blade is shown below:
the set of profile equations for the suction surface of the blade is shown below:
then, according to the profile parameter [ a ] of the pressure surface of the blade 0 a 1 a 2 a 3 a 4 a 5 ] T Profile parameter [ b ] of suction surface of blade 0 b 1 b 2 b 3 b 4 b 5 ] T Obtaining the molded lines of a plurality of blade sections, and generating a three-dimensional blade shape according to the molded line basic stack of each blade section;
then, inputting the three-dimensional modeling and the deformation of the blade into a CFD model of the blade;
meanwhile, inputting the three-dimensional modeling of the blade and the aerodynamic force of the blade into a finite element model of the blade;
step two:
calculating blade aerodynamic force corresponding to blade geometric parameters and blade deformation by using a blade CFD model, and storing a calculation result into a database;
meanwhile, calculating blade geometric parameters and blade deformation corresponding to blade aerodynamic force by using a blade finite element model, and storing the calculation result into a database;
step three:
repeating the first step to the second step, thereby accumulating a certain amount of calculation results in the database;
step four:
establishing a blade flow field reduced model of the influence of blade geometric parameters and blade deformation on blade aerodynamic force, and identifying the blade flow field reduced model by using a calculation result in a database;
meanwhile, establishing a blade structure reduced model of which the blade geometric parameters and the blade aerodynamic force influence the blade deformation, and identifying the blade structure reduced model by using the calculation result in the database;
step five:
obtaining a fluid-solid coupling hybrid model of blade structure analysis by the following steps:
step a: a group of blade geometric parameters are given, blade aerodynamic force is calculated by utilizing a blade flow field reduced model, and the blade aerodynamic force is input into a blade finite element model;
step b: calculating blade deformation by using a blade finite element model, and inputting the blade deformation into a blade flow field reduced model;
step c: calculating blade aerodynamic force by using a blade flow field reduced model, and judging whether the blade aerodynamic force is matched with blade deformation; if not, executing step b; if the blade flow field reduced model and the blade finite element model are matched, the coupling of the blade flow field reduced model and the blade finite element model is realized, and thus a fluid-solid coupling mixed model for blade structure analysis is obtained;
meanwhile, a fluid-solid coupling hybrid model for blade flow field analysis is obtained through the following steps:
step a: a group of blade geometric parameters are given, blade deformation is calculated by utilizing a blade structure reduced model, and the blade deformation is input into a blade CFD model;
step b: calculating blade aerodynamic force by using a blade CFD model, and inputting the blade aerodynamic force into a blade structure reduced model;
step c: calculating the blade deformation by using the blade structure reduced model, and judging whether the blade deformation is matched with the blade aerodynamic force; if not, executing step b; if the blade structure reduced order model and the blade CFD model are matched, the blade structure reduced order model and the blade CFD model are coupled, and therefore a fluid-solid coupling mixed model for blade flow field analysis is obtained;
step six:
establishing a blade structure optimization subsystem based on a fluid-solid coupling mixed model of blade structure analysis; in the blade structure optimization subsystem, a group of new blade geometric parameters are automatically generated by an optimization algorithm, then the current blade structure weight, the current blade service life, the current blade maximum equivalent stress and the current blade maximum deformation are calculated by utilizing a fluid-solid coupling hybrid model of blade structure analysis, and then the calculation result is uploaded to a collaborative optimization system;
meanwhile, a blade flow field optimization subsystem is established based on a fluid-solid coupling mixed model of blade flow field analysis; in the blade flow field optimization subsystem, a group of new blade geometric parameters are automatically generated by an optimization algorithm, then the current total blade pressure ratio, the current aerodynamic lift force of the blade airfoil profile and the current oscillation of the aerodynamic force of the blade are calculated by utilizing a fluid-solid coupling mixed model of the blade flow field analysis, and then the calculation result is uploaded to a cooperative optimization system;
step seven:
judging whether the calculation result meets an optimization target and a constraint condition by using a collaborative optimization system;
if the calculation result does not meet the optimization target and the constraint condition, executing a sixth step;
and if the calculation result meets the optimization target and the constraint condition, ending the optimization.
The blade geometry parameters include: radius r of leading edge of blade 1 Trailing edge radius r of blade 2 Angle of attack i of blade, angle of structure beta of blade inlet 1 Blade outlet structure angle beta 2 Blade installation angle gamma, blade She Xianchang b, blade cascade distance t and blade inlet leading edge wedge angle beta q Blade outlet leading edge wedge angle beta h Diameter a of blade throat and maximum thickness C of blade max 。
And in the sixth step, a global optimized MIGA algorithm and a local gradient optimized NLPQL algorithm are used for generating new geometric parameters of the blade.
In the seventh step, the optimization objective is: 1) The weight of the blade structure is minimum; 2) The blade total pressure ratio is maximum; the constraint conditions are as follows: 1) The service life of the blade is more than 2e9 cycles; the maximum equivalent stress of the blade and the maximum deformation of the blade do not exceed specified values; 2) The aerodynamic lift of the blade airfoil is greater than a specified value; the oscillation of the aerodynamic force of the blade is less than a specified amplitude; 3) And the geometric parameters of the blades in the blade structure optimization subsystem are consistent with those of the blades in the blade flow field optimization subsystem.
While specific embodiments of the invention have been described above, it will be appreciated by those skilled in the art that these are by way of example only, and that the scope of the invention is defined by the appended claims. Various changes and modifications to these embodiments may be made by those skilled in the art without departing from the spirit and scope of the invention, and these changes and modifications are within the scope of the invention.
Claims (4)
1. A multidisciplinary parallel collaborative optimization design method for an aviation turbine engine blade is characterized by comprising the following steps: the method is realized by adopting the following steps:
the method comprises the following steps:
generating geometric parameters, deformation and aerodynamic force of the blades by using a random generator;
then, the coordinate (x) of the first point on the pressure surface of the blade is calculated according to the geometric parameters of the blade p1 ,y p1 ) Last on the pressure side of the bladeCoordinates of points (x) p2 ,y p2 ) Coordinate (x) of a first point on the suction surface of the blade s1 ,y s1 ) Coordinate of last point on suction surface of blade (x) s2 ,y s2 )；
Then, substituting the calculation result into the profile equation set of the pressure surface of the blade and the profile equation set of the suction surface of the blade, thereby calculating the profile parameter [ a ] of the pressure surface of the blade 0 a 1 a 2 a 3 a 4 a 5 ] T Profile parameter of suction surface of blade 0 b 1 b 2 b 3 b 4 b 5 ] T ；
The set of profile equations for the pressure side of the blade is shown below:
the set of profile equations for the suction surface of the blade is shown below:
then, according to the profile parameter [ a ] of the pressure surface of the blade 0 a 1 a 2 a 3 a 4 a 5 ] T Profile parameter of suction surface of blade 0 b 1 b 2 b 3 b 4 b 5 ] T Obtaining the molded lines of a plurality of blade sections, and generating a three-dimensional blade shape according to the molded line basic stack of each blade section;
then, inputting the three-dimensional modeling and the deformation of the blade into a CFD model of the blade;
meanwhile, inputting the three-dimensional modeling of the blade and the aerodynamic force of the blade into a finite element model of the blade;
step two:
calculating blade aerodynamic force corresponding to blade geometric parameters and blade deformation by using a blade CFD model, and storing the calculation result in a database;
meanwhile, calculating blade geometric parameters and blade deformation corresponding to blade aerodynamic force by using a blade finite element model, and storing the calculation result into a database;
step three:
repeating the first step to the second step, thereby accumulating a certain amount of calculation results in the database;
step four:
establishing a blade flow field reduced model of the influence of blade geometric parameters and blade deformation on blade aerodynamic force, and identifying the blade flow field reduced model by using a calculation result in a database;
meanwhile, establishing a blade structure reduced model of which the blade geometric parameters and blade aerodynamic force influence the blade deformation, and identifying the blade structure reduced model by using a calculation result in a database;
step five:
obtaining a fluid-solid coupling hybrid model of blade structure analysis by the following steps:
step a: a group of blade geometric parameters are given, blade aerodynamic force is calculated by utilizing a blade flow field reduced model, and the blade aerodynamic force is input into a blade finite element model;
step b: calculating blade deformation by using a blade finite element model, and inputting the blade deformation into a blade flow field reduced model;
step c: calculating blade aerodynamic force by using a blade flow field reduced model, and judging whether the blade aerodynamic force is matched with blade deformation; if not, executing step b; if the blade flow field reduced model and the blade finite element model are matched, coupling of the blade flow field reduced model and the blade finite element model is achieved, and therefore a fluid-solid coupling mixed model for blade structure analysis is obtained;
meanwhile, a fluid-solid coupling hybrid model for blade flow field analysis is obtained through the following steps:
step a: a group of blade geometric parameters are given, blade deformation is calculated by using a blade structure reduced model, and the blade deformation is input into a blade CFD model;
step b: calculating blade aerodynamic force by using a blade CFD model, and inputting the blade aerodynamic force into a blade structure reduced model;
step c: calculating the blade deformation by using the blade structure reduced model, and judging whether the blade deformation is matched with the blade aerodynamic force; if not, executing step b; if the blade structure reduced order model and the blade CFD model are matched, the blade structure reduced order model and the blade CFD model are coupled, and therefore a fluid-solid coupling mixed model for blade flow field analysis is obtained;
step six:
establishing a blade structure optimization subsystem based on a fluid-solid coupling hybrid model of blade structure analysis; in the blade structure optimization subsystem, a group of new blade geometric parameters are automatically generated by an optimization algorithm, then the current blade structure weight, the current blade service life, the current blade maximum equivalent stress and the current blade maximum deformation are calculated by utilizing a fluid-solid coupling hybrid model of blade structure analysis, and then the calculation result is uploaded to a collaborative optimization system;
meanwhile, a blade flow field optimization subsystem is established based on a fluid-solid coupling mixed model of blade flow field analysis; in the blade flow field optimization subsystem, a group of new blade geometric parameters are automatically generated by an optimization algorithm, then the current total blade pressure ratio, the current aerodynamic lift force of the blade airfoil profile and the current oscillation of the aerodynamic force of the blade are calculated by utilizing a fluid-solid coupling mixed model of the blade flow field analysis, and then the calculation result is uploaded to a cooperative optimization system;
step seven:
judging whether the calculation result meets an optimization target and a constraint condition by using a collaborative optimization system;
if the calculation result does not meet the optimization target and the constraint condition, executing a sixth step;
and if the calculation result meets the optimization target and the constraint condition, ending the optimization.
2. The multidisciplinary parallel collaborative optimization design method for an aircraft turbine engine blade according to claim 1, characterized in that: the blade geometrical parameters include: radius r of leading edge of blade 1 Trailing edge radius r of the blade 2 Angle of attack i of blade, angle of structure beta of blade inlet 1 Blade outlet structure angle beta 2 Blade installation angle gamma, blade She Xianchang b, blade cascade distance t and blade inlet leading edge wedge angle beta q Blade outlet leading edge wedge angle beta h Diameter a of blade throat and maximum thickness C of blade max 。
3. The multidisciplinary parallel collaborative optimization design method for an aircraft turbine engine blade according to claim 1, characterized in that: in the sixth step, a new blade geometric parameter is generated by using a global optimized MIGA algorithm and a local gradient optimized NLPQL algorithm.
4. The multidisciplinary parallel collaborative optimization design method for an aircraft turbine engine blade according to claim 1, characterized in that: in the seventh step, the optimization objective is: 1) The weight of the blade structure is minimum; 2) The blade total pressure ratio is maximum; the constraint conditions are as follows: 1) The service life of the blade is more than 2e9 cycles; the maximum equivalent stress of the blade and the maximum deformation of the blade do not exceed specified values; 2) The aerodynamic lift of the blade airfoil is greater than a specified value; the oscillation of the aerodynamic force of the blade is less than a specified amplitude; 3) And the geometric parameters of the blades in the blade structure optimization subsystem are consistent with those of the blades in the blade flow field optimization subsystem.
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