数据驱动的高强钛合金高冲击韧性主控因素研究

Data-Driven Analysis of Dominant Factors for High Impact Toughness in High-Strength Titanium Alloys

  • 摘要: 冲击韧性是钛合金工程应用的关键指标,但与强度提升存在路径竞争。为揭示高强钛合金高冲击韧性的主控因素,基于公开文献建立了共188组样本的成分−热处理工艺−力学性能数据集,提出了一种以“专家模型”为核心的三层数据驱动集成模型架构。该架构解决了多类型数据混合训练导致的冲击韧性预测模型精度较低的问题,决定系数R2达到0.88。基于SHAP值识别出三项主控因素,即相稳定比率(铝当量/钼当量)、Mo含量、相稳定比率与平均原子半径的交互效应。定量给出Mo质量分数陷阱区间(2~4)及两个相稳定比率−平均原子半径优秀设计窗口((2~3/1.35~1.40)×10−10 m,以及(0~2/1.45~1.50)×10−10 m)。基于混淆矩阵的文献进一步验证了该主控因素的清晰边界。

     

    Abstract: Impact toughness is a critical indicator for the engineering application of titanium alloys, yet it often exhibits a trade-off relationship with strength enhancement. To uncover the dominant factors governing high impact toughness while maintaining strength, a dataset comprising 188 samples of composition, heat treatment processes, and mechanical properties was compiled from publicly available literature. A three-layer ensemble model architecture centered on “expert models” was proposed. This architecture effectively addressed the problem of low accuracy of impact toughness prediction, mostly caused by mixed-type data training, and achieved a coefficient of determination of 0.88. Three dominant factors were identified based on SHAP values, the phase stability ratio (aluminum equivalent/molybdenum equivalent), Mo content, and phase stability ratio’s interaction effect with the average atomic radius. Quantitatively, a Mo content trap range (2~4) and two optimal design windows for the phase stability ratio and average atomic radius((2~3/1.35~1.40)×10−10 m, and (0~2/1.45~1.50)×10−10 m) were delineated. Literature validation based on a confusion matrix further verified the clear boundary of these dominant factors.

     

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