Song Shin-Hyung
Department of Smart Automobile, Soonchunhyang University, Asan-si 31538, Korea.
Materials (Basel). 2021 Apr 6;14(7):1812. doi: 10.3390/ma14071812.
The alloy 304 stainless steel is used in a wide variety of industrial applications. It is frequently applied in tough environments, such as those involving high temperatures, low temperatures, and corrosive environments. Hence, research on the flow stress behavior of the alloy during deformation under tough environments is critically important to achieving the maximum effectiveness in the application of the alloy. This research presents a study on the flow stress of 304 stainless steel during hot deformation at the temperatures of 700 °C-900 °C under the strain rates ranging from 0.0002/s-0.02/s. For this study, hot tensile experiments are conducted, and the flow stress variations of the alloy are studied with respect to the variations in the strain rate and temperature. Next, the stress behavior was modeled by the traditional Arrhenius-type constitutive equation and random forest algorithm. Then, the flow stresses predicted by different methods were studied by comparing errors. The results showed that the flow stress was modeled more accurately by the random forest algorithm.
304 不锈钢合金被广泛应用于各种工业领域。它经常应用于恶劣环境中，例如涉及高温、低温和腐蚀性环境的场合。因此，研究该合金在恶劣环境下变形过程中的流变应力行为对于在合金应用中实现最大效能至关重要。本研究针对 304 不锈钢在 700℃至 900℃温度下、应变速率为 0.0002/s 至 0.02/s 范围内进行热变形时的流变应力展开了一项研究。为此项研究进行了热拉伸试验，并针对应变速率和温度的变化研究了该合金的流变应力变化。接下来，通过传统的阿累尼乌斯型本构方程和随机森林算法对流变应力行为进行建模。然后，通过比较误差来研究不同方法预测的流变应力。结果表明，随机森林算法对流变应力的建模更为准确。
