A physics-based machine-learning approach for modeling the temperature-dependent yield strengths of medium- or high-entropy alloys
A physics-based machine-learning approach for modeling the temperature-dependent yield strengths of medium- or high-entropy alloys
复制标题
一种基于物理学的机器学习方法，用于模拟中熵或高熵合金的温度相关屈服强度
DOI：
10.1016/j.apmt.2023.101747
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发表时间：
2023-04
影响因子：
8.3
通讯作者：
Baldur Steingrimsson;Xuesong Fan;R. Feng;P. Liaw
中科院分区：
文献类型：
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作者：
Baldur Steingrimsson;Xuesong Fan;R. Feng;P. Liaw
机器学习正在成为准确预测结构材料的温度相关屈服强度（YS）的强大工具，特别是对于多主元系统。然而，成功的机器学习预测依赖于合理的机器学习模型的使用。在这里，我们提出了一个全面的和最新的双线性对数模型，用于预测中熵或高熵合金（MEAs或HEAs）的温度依赖的YS。在该模型中，引入了断裂温度Tbreak，它可以指导具有吸引高温性能的mea或HEAs的设计。与假设的黑箱结构不同，我们的模型基于底层物理，以先验信息的形式结合在一起。采用了一种无约束全局优化技术，实现了低温和高温条件下模型参数的并行优化，结果表明，不同HEA成分的断裂温度和极限强度在整个YS范围内是一致的。对MEAs/HEAs与镍基高温合金的YS进行了高水平比较，发现所选的难熔HEAs具有优异的强度性能。为了可靠的运行，结构部件的温度，如由耐火合金制成的涡轮叶片，可能需要保持在45℃以下。一旦超过熔点，相变可能开始发生，合金可能开始失去结构完整性。
Machine learning is becoming a powerful tool to accurately predict temperature-dependent yield strengths (YS) of structural materials, particularly for multi-principal-element systems. However, successful machine-learning predictions depend on the use of reasonable machine-learning models. Here, we present a comprehensive and up-to-date overview of a bilinear log model for predicting temperature-dependent YS of medium-entropy or high-entropy alloys (MEAs or HEAs). In this model, a break temperature,Tbreak, is introduced, which can guide the design of MEAs or HEAs with attractive high-temperature properties. Unlike assuming black-box structures, our model is based on the underlying physics, incorporated in the form of a priori information. A technique for the unconstrained global optimization is employed to enable the concurrent optimization of model parameters over low- and high-temperature regimes, showing that the break temperature is consistent across the YS and ultimate strength for a variety of HEA compositions. A high-level comparison between YS of MEAs/HEAs and those of Nickel-based superalloys reveals superior strength properties of selected refractory HEAs. For reliable operations, the temperature of a structural component, such as a turbine blade, made from refractory alloys, may need to stay belowTbreak. Once aboveTbreak, phase transformations may start taking place, and the alloy may begin losing structural integrity.