混凝土混合设计中的人工智能:全面审查
Doondy Priya Jagupilla1, Kameswara Rao Burugapalli2
1Department of Civil Engineering, KL Deemed to Be University, Vijayawada, India. 2401020014se@gmail.com.
Environmental science and pollution research international
|February 23, 2026
概括
人工智能 (AI) 和机器学习优化了混凝土混合设计,减少了试验和成本. 这些数据驱动的方法提高了混凝土的性能,并支持可持续的建筑实践.
科学领域:
- 土木工程 土木工程是指土木工程.
- 材料科学 材料科学 材料科学
- 计算机科学 计算机科学
背景情况:
- 传统的混凝土混合设计是经验性的,昂贵的,耗时的.
- 优化混凝土性能需要平衡性能,材料使用和成本.
- 人工智能的进步为混凝土混合设计提供了数据驱动的解决方案.
研究的目的:
- 在混凝土混合设计中审查人工智能和机器学习应用.
- 探索AI在预测具体性能和优化比例方面的作用.
- 突出AI在降低建筑成本和可持续性方面的潜力.
主要方法:
- 利用混凝土材料特性,混合比率和性能结果的历史数据集.
- 应用机器学习模型,如随机森林回归 (RF),用于性能预测.
- 采用优化框架来确定具有成本效益和可持续的混合设计.
主要成果:
- 人工智能模型准确地预测了具体的性能指标,例如28天的压力强度.
- 优化框架确定了符合特定强度要求的混合设计.
- 人工智能框架显示出降低实验室试验和相关成本的潜力.
结论:
- 基于人工智能的混凝土混合设计提供了更准确,更有效的方法.
- 这些方法可以降低成本,节省时间,并尽量减少资源密集型实验室试验.
- 人工智能有助于开发现代建筑的可持续和高性能混凝土.
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