The present invention discloses an aircraft parametric design method based on a state type function. A parameter set which describes an aircraft shape is extracted and input into an MATLAB, a constraint relationship among parameters in the parameter set is determined and coordinates of feature points on an aircraft are calculated by utilizing the MATLAB so as to form a coordinate file; then the coordinate file is read by utilizing an ANSYS to generate the aircraft shape and the aircraft shape is subjected to meshing by utilizing the ANSYS so as to form mesh data; and finally, the mesh data is read by utilizing the MATLAB to carry out stress estimation of an aerodynamic force and a thrust so as to finally obtain an aircraft model. The aircraft parametric design method has high design efficiency and a high fidelity and can be well used for analysis on stability and performance quality of the aircraft.

Aircraft parametric design method based on state type function

The present invention discloses an airfoil robust optimization design method based on a non-probability interval analysis model, and belongs to the technical field of optimization design. According tothe method disclosed by the present invention, an indefinite factor in airfoil design is fully considered, and in the case that a probability density of an indefinite parameter is unknown, quantifiedcharacterization of the indefinite parameter is implemented by using an interval vector. By means of a sample point experiment, a mapping relationship among an airfoil design variable, the indefiniteparameter and an aerodynamic coefficient is established. On this basis, upper and below interval boundaries of the airfoil aerodynamic coefficient are obtained by using a non-probability interval analysis model. Robust optimization model is established, then airfoil optimization design is implemented by using genetic algorithm. As numerical prediction indicates, on the premise of maintaining an airfoil lift coefficient and a geometric shape constraint, the method disclosed by the present invention reduces a resistance coefficient of a designed airfoil, reduces a variation range of the resistance coefficient and provides a new idea for airfoil optimization design.

Airfoil robust optimization design method based on non-probability interval analysis model

The invention provides an airfoil section represented by analytic functions and a generation method for the airfoil section and relates to a vane or an airfoil of turbomachinery and a manufacturing method for the vane or the airfoil A traditional airfoil section is manufactured by adopting a forward design method in common, ie, the airfoil section is determined firstly, and then, the shape of the airfoil section is approximately described by using a coordinate database, but a new airfoil section cannot be generated through changing coordinate data, ie, an inverse design cannot be realized The invention provides a method for generating the airfoil section by using the analytic functions All parameters in the functions are definite in geometrical significance, and the airfoil section or a family of airfoil sections can be generated according to an expected direction through adjusting parameter values, and even, the airfoil section of which the trailing edge has thickness can be generated, and therefore, the inverse design is realized Moreover, the shape of the airfoil section can be accurately reflected by a functional image, and errors cannot be generated Moreover, functional expressions are simpler than the database and are convenient in use A more complicated airfoil section can be generated by combining two analytic function expressions for upper and lower molded lines, and the analytic functions also can approach to those of the traditional airfoil section through adjusting the parameter values so as to obtain the approximate expression of the traditional airfoil section

Airfoil section represented by analytic functions and generation method for wing section

The invention discloses a phase unwrapping method based on a differential evolution (DE) algorithm. The core of the method is that a real phase is globally approached by use of a finite-term orthogonal polynomial (Zernike) and a coefficient to be determined is solved by use of the DE algorithm. For the purpose of preventing a final unwrapping result from being affected by data points polluted by big noise, a weight Zernike polynomial fitting method is employed. According to the invention, measured discrete data is fitted by taking the Zernike polynomial as a basis function, the accuracy of a fitting result is guaranteed, the coefficient to be determined is solved by performing dynamic random search by use of the DE algorithm, and the global convergence and robustness are quite high.

Phase unwrapping method based on differential evolution (DE) algorithm

The invention discloses a sorting method applied to a multi-target interval genetic algorithm. The method comprises: according to a design object, determining a design variable and a design target; searching for individuals meeting design requirements, and calculating the fitness, namely, a design target value, of a new individual with a computational fluid mechanics method; according to the design target value, sorting all the individuals by using hypervolume size and non-dominated sorting to generate a subpopulation I and a subpopulation II; in the subpopulation I, calculating the hypervolumes of all the individuals, performing sorting from big to small according to the hypervolume size in view of interval characteristics of solutions; in the subpopulation II, sorting all the individuals with the non-dominated sorting method to solve the multi-target problem; performing combined sorting on the subpopulation I and the subpopulation II; and generating a new population by utilizing selection operation: ending the design process until the new population meets the convergence standard. According to the method, the multi-target problem and the interval solution problem of the genetic algorithm are solved at the same time.

Sorting method applied to multi-target interval genetic algorithm

The invention provides a wing profile optimal design method of a parallel difference evolutionary algorithm based on open computing language (Open CL) The wing profile optimal design method is used for wing profile design A standard wing profile function and a profile function are selected, the profile function serves as a design variable, an optimization objective function is determined, steps of the difference evolutionary algorithm are divided into different stages according to processed data, and all stages are packaged in different cores for operating based on Open CL In population updating, mutation operators are used for generating test vectors and crossover operators are used for generating descendants; individuals in a population are restored to the wing profile shape and tested whether to meet geometric constraint; computational fluid dynamics (CFD) analysis is used for obtaining fitness of the individuals and seeking the optimum individual, and whether the optimum individual meets performance constraint is tested; and finally iteration is finished and the optimum result is copied back into a host internal storage The wing profile optimal design method achieves parallel processing of a wing profile design process, performs sufficient search in effective space, shortens design period, achieves cross-platform wing profile optimal design, and improves design efficiency

Wing profile optimal design method of parallel difference evolutionary algorithm based on open computing language (Open CL)

A Fast Calculation and Rendering Method for Infrared Characteristics of Hypersonic Vehicle

The invention discloses an aircraft aerodynamic configuration optimum design method based on the improved parallel DE algorithm. The method is used for achieving aircraft aerodynamic configuration optimum design. According to the method, different DE algorithm patterns are integrated in a pattern pool, and therefore the DE pattern selection range is expanded; besides, a dynamic parameter pattern is newly adopted, and more effective research on a large area of unknown solution spaces can be achieved through the pattern. In the iteration process, test vectors are generated through mutation operation and interlace operation; individual codes in a species group are reduced to corresponding aircraft configurations, the CFD computational analysis process is introduced to an individual fitness evaluation stage and serves as a basis for selection on a new generation of individuals, therefore, the design result analysis process and the parameter modification process can be effectively combined, and the design cycle is shortened; offspring groups are generated through selection operation. In view of the characteristic that the computing amount in the aircraft aerodynamic configuration design process is large, the parallel computing mechanism is introduced into the method, and therefore the method greatly shortens algorithm running time and improves design efficiency.

Ni Li

Papers

Wing profile optimal design method of parallel difference evolutionary algorithm based on open computing language (Open CL)

A Fast Calculation and Rendering Method for Infrared Characteristics of Hypersonic Vehicle

Aircraft aerodynamic configuration optimum design method based on improved parallel DE algorithm