使用EUCLID发现非关联的压力敏感可塑性模型
Haotian Xu1,2, Moritz Flaschel2, Laura De Lorenzis2
1Empa, Swiss Federal Laboratories for Material Science and Technology, Überlandstrasse 129, Dübendorf, 8600 Switzerland.
概括
这项研究扩展了EUCLID (高效无监督立法的识别和发现) 对于压力敏感的可塑性. 该框架准确地识别单个实验的材料模型,即使有噪音数据.
科学领域:
- 计算力学是计算力学.
- 材料科学是一种材料科学.
- 固体机械学 固体机械学
背景情况:
- 自动化材料模型发现对于预测材料行为至关重要.
- 现有的方法与复杂的可塑性模型 (如压力敏感模型) 斗争.
- 工程应用需要可解释的立宪法.
研究的目的:
- 扩大EUCLID框架对压力敏感可塑性模型的应用.
- 为了能够发现具有凸度和非关联流量规则的任意形状的收益率表面.
- 为了在模型准确性和简单性之间取得平衡.
主要方法:
- 使用数据驱动框架 (EUCLID),只需要全场移位和边界力数据.
- 使用富里埃数列来构建材料模型库,用于收益率表面和压力敏感项.
- 实施了促进稀疏性的规范化和凸度约束,以实现反向优化.
主要成果:
- 成功地将EUCLID扩展到具有非关联流规则的压力敏感可塑性.
- 使用杂的实验数据,从图书馆中展示了准确的材料模型选择.
- 学习的构成法则以可解释的数学表达式呈现.
结论:
- EUCLID为复杂材料模型的自动发现提供了一种有效的方法.
- 该框架准确地捕捉了压力灵敏度,屈服表面形状和流量规则.
- 这种方法为传统的参数识别技术提供了强大的替代方案.
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