Highly Accurate Aerodynamic Shape Opitmization With A Large Number Of Design Parameters Based On A New And Efficient Global Opitmization Algorithm

Aerodynamic configuration design is vital to the overall performance of an aircraft,and the modern aircraft design requires higher aerodynamic performance, shorterdesign cycle and lower design costs for aerodynamic configuration design. Aneffective approach to improve aerodynamic performance and design efficiency isaerodynamic configuration optimization, but such technique has not-yet played its fullpotential function as expected. Satisfactory aerodynamic configuration optimizationdepends on the following three essential requirements: a) the optimization methodsenable full search of the huge design space, to obtain the global optimal or nearlyglobal optimal configuration; b) the cost function solver is accurate enough todistinguish the slight change of aerodynamic features in the optimization process, withthe change of the cost function veritably reflecting the change of the physical quantity;and c) the parameterization can fully represent all the possible shapes, i.e. a largeeffective design space to include the optimal shape, requiring the sufficient designparameters, as more parameters can represent more shapes and more accurate shapes(GHM requirements). An optimization design method meeting all the threerequirements is possible to find the true global best shape. Aerodynamic configurationoptimization design has advanced substantially in respect of the three requirementsafter decades of development; however, it is still a long way to reach the ultimatetargets of a great many parameters, high accuracy and global search. Currently mostoptimization techniques can only meet one of the above three requirements, only a fewcan meet two requirements, and the optimization technique that meets all the threerequirements is not seen in China or the world now, which is the main reason why theeffect of the optimization techniques is far below expectation.Large need to the optimization techniques that meet the GHM requirements existsin the modern aircraft designing. The objects of the essay is to meet the need bysolving the difficulties exists in the development of GHM optimization technique，such as global search difficulty with many parameters，and develop a new optimizationsoftware platform to provide a new and advance tool to modern aircraft design.The characters of the main aerodynamic optimization techniques are analyzed inthe paper and the shortcomings of them are given. The Adjoint based optimizationtechnique successfully meets the two requirements of three： many parameters and highaccuracy? but the global search requirement is still not fulfilled. The technical analysisshows that the cost function are more probably to have more than one minimum as thenumber of the parameter increasing, and this is validated by the following study ofcurves and surfaces of aerodynamic characteristic-parameters of wing section，wing and aircraft. Now, most of the Adjoint based aerodynamic optimization technique wasperformed with the local optimization algorithm based on the sensitivity derivative,thus the optimization cannot get good results. This is the main reason why the effect ofthe Adjoint based optimization techniques is far below expectation and not widely usedin engineering. The global search technique with a large number of parameters will bedeveloped in the essay, and the new search algorithm will be used in the Adjoint basedoptimization technique to compose a new optimization technique that meets GHMrequirements.The main difficulty of the global search with a large number of parameters is thehuge increase of the calculation load of common global search algorithm which maysoon exceeds the ability of today and future hardware. Two guess is proposed in thepaper to solve the problem:1) through the relations between cost functions andparameters are complex, some regulations exists and this may be the key of the globalsearch algorithm with a large number of parameters.2) the optimization is just theprocedures to find and use the messages in the cost function and parameters. Thesensitivity derivative messages are not well used in Adjoint based optimization today，so we can improve the optimization technique by promote better usages of thesensitivity derivatives.Then the relations between the parameters and cost functions are studied again anda regulation is found: the cost function is single-extremum to the most of theparameters but multi-extremum to the other parameters. Thus the author successfullydeveloped a new optimization algorithm based on parameter classification(ParameterClassification Based Mixed Optimization，PCO). The design parameters are divided tosingle-extremum parameters and multi-extremum parameters, and then global searchalgorithm is used for multi-extremum parameters while local search algorithm is usedfor single-extremum parameters, thus the global optimization results can be found inacceptable computational load with more than100parameters. The new searchalgorithm is certificated with model functions, the results show that the newoptimization algorithm can improve the optimization efficiency and result greatly.The flow solver and its coupled Adjoint solver were developed in the paper withOsher flux difference splitting scheme, the finite volume method multi-block structuredgrid，based on Reynolds averaged Navier-Stokes equations. The Mpi parallelcomputation technique is used in the program to improve the computation speed. Theflow field of Rae2822，M6and etc wing section and wing is calculated and comparedwith the test results? the comparing results show that the accuracy of the flow solver issatisfied. The sensitivity derivatives of a wing section is calculated with Adjoint solverand compared with the results calculated by traditional method，the results also metquite well. The flow solver, adjoint solver, shape parameterization program、grid updatesoftware and PCO search program are composed to optimization software platformADJOPT. Wing section，wing and a large aircraft are optimized with this softwareplatform and the optimization results were compared with the results optimized withtraditional Adjoint based optimization technique. The results show that the ADJOPTreally have global search ability with many parameters. The drag reduction is morethan7times of the drag reduction of traditional Adjoint method.