QIN Guo-hua, GUO Yi-xiang, WANG Hua-min, HOU Yuan-jun, LOU Wei-da. MULTIPLE OBJECTIVE STRUCTURAL OPTIMIZATION ON “MACHINING DEFORMATION - FATIGUE LIFE” OF AERONAUTICAL MONOLITHIC COMPONENTS[J]. Engineering Mechanics, 2021, 38(8): 222-236. DOI: 10.6052/j.issn.1000-4750.2020.07.0517
Citation: QIN Guo-hua, GUO Yi-xiang, WANG Hua-min, HOU Yuan-jun, LOU Wei-da. MULTIPLE OBJECTIVE STRUCTURAL OPTIMIZATION ON “MACHINING DEFORMATION - FATIGUE LIFE” OF AERONAUTICAL MONOLITHIC COMPONENTS[J]. Engineering Mechanics, 2021, 38(8): 222-236. DOI: 10.6052/j.issn.1000-4750.2020.07.0517

MULTIPLE OBJECTIVE STRUCTURAL OPTIMIZATION ON “MACHINING DEFORMATION - FATIGUE LIFE” OF AERONAUTICAL MONOLITHIC COMPONENTS

  • In the process of blank manufacturing, the non-uniformity of mechanical properties of materials leads to residual stress in an aluminum alloy thick plate, so that in the subsequent high-speed cutting process, with the removal of a large number of materials, the release of residual stress causes deformation of the whole structure, which seriously affects the dimensional stability of the whole structure. Therefore, it is very important to study the relationship between part deformation and part structure to realize the high efficiency and precision of machining process. Firstly, the release of residual stress in an aluminum plate is reasonably equivalent to the application of external loads, and the deflection equation of machining deformation in the thickness direction of the aluminum plate is established by using the bending deformation formula of material mechanics. According to the actual measurement, the formula analytic value and the finite element simulation value of the machining deformation are in a good agreement with the actual measured value. In order to further analyze the relationship between part structure and its fatigue life, the nominal stress method is used to simplify the analysis by equating the minimum fatigue life of the part with the maximum stress of the part under fatigue loading. After static analysis of some typical structures, the neural network model with three web positions as input, and the maximum stress of the part and the maximum machining deformation as output is obtained. Finally, the neural network model is used to construct a multi-objective optimization problem that minimizes the maximum machining deformation and maximum fatigue stress, and the optimal solution obtained by solving the multi-objective problem with genetic algorithm is that the distance between the bottom of the three webs and the bottom of the part is 8.868 mm, 27.992 mm, 28.000 mm, respectively. At this moment, the maximum machining deformation of the part is 0.088 mm, the minimum random fatigue load life is 4.432×107.
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