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Aero-Engine Blade Cryogenic Cooling Milling Deformation Simulation and Process Parameter Optimization.
Chen, Ting; Xu, Yun; Huang, Bo; Shi, Yan; Zhang, Jiahu; Li, Lei; Meng, Yaozhi; Li, Xuqing.
Afiliação
  • Chen T; School of Mechanical Engineering, Sichuan University of Science and Engineering, Zigong 643000, China.
  • Xu Y; School of Mechanical Engineering, Sichuan University of Science and Engineering, Zigong 643000, China.
  • Huang B; School of Mechanical Engineering, Sichuan University of Science and Engineering, Zigong 643000, China.
  • Shi Y; School of Mechanical Engineering, Sichuan University of Science and Engineering, Zigong 643000, China.
  • Zhang J; School of Mechanical Engineering, Sichuan University of Science and Engineering, Zigong 643000, China.
  • Li L; School of Mechanical Engineering, Sichuan University of Science and Engineering, Zigong 643000, China.
  • Meng Y; School of Mechanical Engineering, Sichuan University of Science and Engineering, Zigong 643000, China.
  • Li X; School of Mechanical Engineering, Sichuan University of Science and Engineering, Zigong 643000, China.
Materials (Basel) ; 16(11)2023 May 30.
Article em En | MEDLINE | ID: mdl-37297206
ABSTRACT
For the machining of aero-engine blades, factors such as machining residual stress, milling force, and heat deformation can result in poor blade profile accuracy. To address this issue, simulations of blade milling were completed using DEFORM11.0 and ABAQUS2020 software to analyze blade deformation under heat-force fields. Process parameters such as spindle speed, feed per tooth, depth of cut, and jet temperature are used to design both a single-factor control and BBD test scheme to study the influence of jet temperature and multiple changes in process parameters on blade deformation. The multiple quadratic regression method was applied to establish a mathematical model correlating blade deformation with process parameters, and a preferred set of process parameters was obtained through the particle swarm algorithm. Results from the single-factor test indicated that blade deformation rates were reduced by more than 31.36% in low-temperature milling (-190 °C to -10 °C) compared with dry milling (10 °C to 20 °C). However, the margin of the blade profile exceeded the permissible range (±50 µm); therefore, the particle swarm optimization algorithm was used to optimize machining process parameters, resulting in a maximum deformation of 0.0396 mm when the blade temperature was -160 °C~-180 °C, meeting the allowable blade profile deformation error.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Materials (Basel) Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Materials (Basel) Ano de publicação: 2023 Tipo de documento: Article