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Machining deformation prediction of large fan blades based on loading uneven residual stress

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Abstract

Fan blade is an important component of turbofan engine. It is a kind of curved thin-walled structural parts, which tends to have a certain amount of deformation after machining process. In order to predict the deformation of fan blade after machining process, the commercial simulation software Abaqus® is used to analyze the deformation of fan blade with titanium alloy through considering the effect of residual stress. The residual stresses on the surface and subsurface of the blade after milling and shot peening processes were measured and analyzed by experimental testing. Based on the measured residual stress data, the three-dimensional model of fan blade is segmented by the operation of extracting geometric features. Then, the residual stress values are discretized according to separation layers, and the discrete results are applied to the thin-walled blade by dividing layers and dividing regions. Finally, a finite element analysis (FEA) model for the deformation prediction of blade through considering the effect of residual stress is established. The simulation deformation is compared with the measured deformation, and the feasibility of the FEA model is verified. The study provides an effective analysis method for the deformation prediction of fan blade after milling and shot peening processes.

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Funding

This work was funded by the National Natural Science Foundation of China (Grant Nos. 51875472, 51905440, and 91860206), the National Science and Technology Major Project (Grant No. 2017-VII-0001-0094) and the National Key Research and Development Plan in Shaanxi Province of China (Grant No. 2019ZDLGY02-03).

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Correspondence to Changfeng Yao.

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Yao, C., Zhang, J., Cui, M. et al. Machining deformation prediction of large fan blades based on loading uneven residual stress. Int J Adv Manuf Technol 107, 4345–4356 (2020). https://doi.org/10.1007/s00170-020-05316-8

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  • DOI: https://doi.org/10.1007/s00170-020-05316-8

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