在使用基因编程的水泥复合材料中的钢纤维拉出力数据驱动的配方
Ali Kooshkaki1, Seyed Ali Emamian2, Ramin Kazemi3
1Department of Civil Engineering, Hakim Sabzevari University, Sabzevar, Iran. alikooshkaki@gmail.com.
Scientific reports
|November 4, 2025
概括
这项研究使用基因表达编程 (GEP) 来预测水泥复合材料中的钢纤维拉出力. 开发的模型准确地预测了拉出力,为实验提供了一个可靠的,数据驱动的替代方案.
科学领域:
- 材料科学 材料科学 材料科学
- 土木工程 土木工程是指土木工程.
- 计算力学 计算力学 计算力学
背景情况:
- 钢纤维增强的水泥复合材料在建筑中至关重要.
- 预测钢纤维的拉出力对于结构完整性至关重要.
- 现有的方法通常依赖于广泛的实验测试.
研究的目的:
- 开发一个基于数据的模型来预测钢纤维拉出力.
- 为了制定一个准确和可解释的数学表达式的拉出力.
- 减少需要耗时和昂贵的实验程序的需求.
主要方法:
- 利用了一个包含437个实验结果的综合数据集.
- 采用基因表达编程 (GEP),是一种基因编程的变体.
- 进行了k倍交叉验证和SHAP灵敏度分析,用于模型验证.
主要成果:
- 实现了高预测准确度,R2为0.93.
- 确定了纤维拉伸强度和嵌入长度作为关键影响因素.
- 提出了一个新的,可解释的数学公式,用于拉出力.
结论:
- GEP模型提供了一种强大而准确的方法来预测拉出力.
- 衍生式为工程师和研究人员提供了一个有效的工具.
- 这种数据驱动的方法提高了复合材料的性能预测和配方.
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