结合有限元法和人工智能来评估PEEK复合材料在撞击条件下的肋骨重建过程中
Yomna H Shash1, Rana Hossam Elden2
1Biomedical Engineering Department, Faculty of Engineering, Helwan University, Cairo, Egypt. Yomna.abdelhamid@h-eng.helwan.edu.eg.
Journal of materials science. Materials in medicine
|December 23, 2025
概括
碳纤维增强PEEK (CFP) 和玻璃纤维增强PEEK (GFP) 复合材料显示为替代用于肋骨重建的有希望的替代品. 与有限元方法 (FEM) 模拟集成的AI模型准确地预测植入物性能,优化未来的设计.
科学领域:
- 生物材料科学 生物材料科学
- 机械工程 机械工程
- 计算机建模 计算建模
背景情况:
- 肋重建对于胸部功能和器官保护至关重要.
- 植入物虽然很常见,但存在一些局限性,导致人们在寻找替代品.
- 有限元法 (FEM) 和人工智能 (AI) 为植入物分析提供了先进的工具.
研究的目的:
- 评估聚乙基 (PEEK) 复合材料作为金属肋骨重建植入物的替代品.
- 开发人工智能模型来预测PEEK植入物的机械反应 (压力,应变,变形).
- 为了比较各种PEEK复合材料在模拟生理负荷下与的性能.
主要方法:
- 使用PEEK,碳纤维增强PEEK (CFP),玻璃纤维增强PEEK (GFP) 和酸PEEK (HAP) 植入物创建了定制的3D胸部模型.
- 在侧冲击和胸部力下进行FEM模拟,以收集机械反应数据.
- 机器学习和深度学习回归模型被训练并使用R2,MAE,MSE和RMSE等指标进行评估.
主要成果:
- 60%的CFP植入物显示出对肋骨和肺部的压力和压力最小.
- 纯PEEK和HAP 30%植入物显示了更高的压力和应变水平.
- 人工智能模型在预测机械反应方面实现了超过99.9%的准确性,证明了其高度可靠和高效.
结论:
- CFP (30%和60%) 和GFP (30%和60%) 复合材料是用于肋骨重建的的可行替代品.
- 整合FEM与AI显著优化了骨科植入物的评估和设计过程.
- 这种方法增强了用于重建外科手术的更安全,更有效的生物材料的开发.
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