As an intelligent global optimization method, the genetic algorithm has tremendous potential
for improving flow behavior modeling and analysis. Based on flow stress-true strain curves …

The potentials of artificial neural network (ANN) modelling as a potent machine learning
approach for investigating the hot deformation behaviour of high-entropy alloys (HEAs) and …

The uniaxial warm tensile experiments were carried out in deformation temperatures (50–
250° C) and strain rates (0.005 to 0.0167 s− 1) to investigate the material workability and to …

In this work, hot compress tests were conducted at the strain rate range of 1–0.001 s− 1 and
the temperature range of 900–1050° C to unravel the hot deformation behavior of a powder …

Constitutive equations were recognized for AZ31B magnesium alloy at higher temperatures
and strain rates from conventional empirical models like the original Johnson–Cook (JC) …

Hot compression experiments are conducted to explore the deformation behaviors of 300M
steel under large strain, which can mimic the forging process of large components. It is found …

The hot deformation behavior of 30MnB5V steel was experimentally investigated and
theoretically analyzed using phenomenological constitutive models and an ensemble …

热冲压能够显著提升超高强钢板材成形性能, 减小变形抗力和回弹, 是实现汽车轻量化和关键
性能提升的重要途径. 近年来超高强钢热冲压技术发展迅猛, 市场需求巨大 …

The flow stress prediction of the 92W-5Co-3Ni alloy is performed using Machine Learning
models like Artificial Neural Networks (ANN), Random Forest (RF) and Deep Neural …

Hot stamping can significantly improve the formability of ultra-high strength steel sheets,
reduce deformation resistance and springback, which is an important way to achieve …