Aero-Engine Blade Cryogenic Cooling Milling Deformation Simulation and Process Parameter Optimization.

Ting Chen, Yun Xu, Bo Huang, Yan Shi, Jiahu Zhang, Lei Li, Yaozhi Meng, Xuqing Li

Abstract read

In one paragraph

Article in Materials (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed

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1 citing paper in PubMed.

Optimization Method of Floating Fixture Layout for Distortion Control of Low-Stiffness Thin-Walled Beams.Materials (Basel, Switzerland) · 2024
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5 · Who and what money

Authors and funding

8 authors.

Ting ChenSchool of Mechanical Engineering, Sichuan University of Science and Engineering, Zigong 643000, China.

Yun XuSchool of Mechanical Engineering, Sichuan University of Science and Engineering, Zigong 643000, China.

Bo HuangSchool of Mechanical Engineering, Sichuan University of Science and Engineering, Zigong 643000, China.

Yan ShiSchool of Mechanical Engineering, Sichuan University of Science and Engineering, Zigong 643000, China.

Jiahu ZhangSchool of Mechanical Engineering, Sichuan University of Science and Engineering, Zigong 643000, China.

Lei LiSchool of Mechanical Engineering, Sichuan University of Science and Engineering, Zigong 643000, China.

Yaozhi MengSchool of Mechanical Engineering, Sichuan University of Science and Engineering, Zigong 643000, China.

Xuqing LiSchool of Mechanical Engineering, Sichuan University of Science and Engineering, Zigong 643000, China.

Funding

BoHuang 2021YFG0050YunXu 2019ZHGG0021

6 · The paper itself

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.

Indexed as

aero-engine bladecryogenic machiningparticle swarm algorithmsimulationstitanium

Identifiers

PMID37297206

DOI10.3390/ma16114072

PMCPMC10254859

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.