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<p>Low energy laser shock peening (LE-LSP) represents a sophisticated surface reinforcement technique for superalloy compressor blades. The accurate prediction of residual stress in LE-LSP is the basis for developing blade reinforcement processes. This study presents an innovative approach for predicting the residual stress induced by LE-LSP, utilizing the inherent strain theory combined with the finite element method (FEM). A large-scale LE-LSP simulation was conducted, and the impact of process parameters on the residual stress distribution was investigated. The analysis revealed that the coupling of tensile and compressive strains within the surface layer results in a distinctive spoon-shaped residual stress profile. Experimental validation was performed on superalloy samples and TC17 titanium alloy, demonstrating that the proposed prediction model achieved an accuracy over 80% for superalloys. Furthermore, the model was extended to predict residual stress in TC17, achieving over 85% accuracy and confirming the generalizability of the proposed strategy. This study provides a theoretical basis and methodological reference for the residual stress prediction and process optimization in superalloys induced by LE-LSP.</p>

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Prediction of residual stress in superalloys by low energy laser shock peening based on inherent strain theory and finite element method

  • 期刊论文

  • 发表日期：

    2025年5月29日

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  • Yilong Cao,
  • Changfeng Yao,
  • Liang Tan,
  • Qihui Cheng,
  • Tao Fan

摘要

Low energy laser shock peening (LE-LSP) represents a sophisticated surface reinforcement technique for superalloy compressor blades. The accurate prediction of residual stress in LE-LSP is the basis for developing blade reinforcement processes. This study presents an innovative approach for predicting the residual stress induced by LE-LSP, utilizing the inherent strain theory combined with the finite element method (FEM). A large-scale LE-LSP simulation was conducted, and the impact of process parameters on the residual stress distribution was investigated. The analysis revealed that the coupling of tensile and compressive strains within the surface layer results in a distinctive spoon-shaped residual stress profile. Experimental validation was performed on superalloy samples and TC17 titanium alloy, demonstrating that the proposed prediction model achieved an accuracy over 80% for superalloys. Furthermore, the model was extended to predict residual stress in TC17, achieving over 85% accuracy and confirming the generalizability of the proposed strategy. This study provides a theoretical basis and methodological reference for the residual stress prediction and process optimization in superalloys induced by LE-LSP.