多目标遗传算法校准使用DEM的彩色自压缩混凝土:一个集成的平行方法
Vahid Shafaie1, Majid Movahedi Rad2
1Department of Structural and Geotechnical Engineering, Széchenyi István University, 9026, Győr, Hungary.
Scientific reports
|February 20, 2024
概括
本研究介绍了一种用于模拟彩色自压缩混凝土 (CSCC) 的自动化方法,使用多目标优化和离散元素建模 (DEM). 该方法通过将色素效应集成到微参数中,准确地预测了具体的行为.
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:
- 数字模拟对于理解具体行为至关重要.
- 现有的方法在模拟复杂的混凝土特性 (如颜色效应) 时往往缺乏精度.
- 自压缩混凝土 (SCC) 在施工中具有优势,但需要精确的模拟来优化.
研究的目的:
- 开发和验证一种创新的,自动校准方法,用于彩色自紧缩混凝土 (CSCC) 模拟.
- 将多目标优化与离散元素建模 (DEM) 集成在一起,以提高混凝土模拟的准确性.
- 为了研究色素效应对CSCC微机械参数的影响.
主要方法:
- 使用MATLAB的遗传算法 (GA) 来实现微参数的多目标优化.
- 集成GA与PFC3D (离散元素建模软件) 进行CSCC行为模拟.
- 在 MATLAB 和 PFC 鱼脚本中开发了一个自动校准脚本,根据预定义的标准终止.
- 采用单轴压力 (UCS) 测试作为主要校准基础.
主要成果:
- 在CSCC的模拟和观察的宏观性质之间实现了高度对齐.
- 证明了自动校准方法的有效性,健身值始终超过0.94.4.
- 成功地将色素效应纳入DEM微参数,影响凝聚力系数.
结论:
- 开发的自动校准方法显著提高了CSCC数值模拟的准确性.
- 多目标优化对于在DEM中精确校准混凝土的微参数至关重要.
- 这项研究推进了先进的混凝土材料的模拟,包括着色剂的影响.
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