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Aero-Engine Blade Cryogenic Cooling Milling Deformation Simulation and Process Parameter Optimization
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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10254859/ https://www.ncbi.nlm.nih.gov/pubmed/37297206 http://dx.doi.org/10.3390/ma16114072 |
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author | Chen, Ting Xu, Yun Huang, Bo Shi, Yan Zhang, Jiahu Li, Lei Meng, Yaozhi Li, Xuqing |
author_facet | Chen, Ting Xu, Yun Huang, Bo Shi, Yan Zhang, Jiahu Li, Lei Meng, Yaozhi Li, Xuqing |
author_sort | Chen, Ting |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10254859 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102548592023-06-10 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 Materials (Basel) Article 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. MDPI 2023-05-30 /pmc/articles/PMC10254859/ /pubmed/37297206 http://dx.doi.org/10.3390/ma16114072 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Chen, Ting Xu, Yun Huang, Bo Shi, Yan Zhang, Jiahu Li, Lei Meng, Yaozhi Li, Xuqing Aero-Engine Blade Cryogenic Cooling Milling Deformation Simulation and Process Parameter Optimization |
title | Aero-Engine Blade Cryogenic Cooling Milling Deformation Simulation and Process Parameter Optimization |
title_full | Aero-Engine Blade Cryogenic Cooling Milling Deformation Simulation and Process Parameter Optimization |
title_fullStr | Aero-Engine Blade Cryogenic Cooling Milling Deformation Simulation and Process Parameter Optimization |
title_full_unstemmed | Aero-Engine Blade Cryogenic Cooling Milling Deformation Simulation and Process Parameter Optimization |
title_short | Aero-Engine Blade Cryogenic Cooling Milling Deformation Simulation and Process Parameter Optimization |
title_sort | aero-engine blade cryogenic cooling milling deformation simulation and process parameter optimization |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10254859/ https://www.ncbi.nlm.nih.gov/pubmed/37297206 http://dx.doi.org/10.3390/ma16114072 |
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