Deep reinforcement learning (DRL) has emerged as a transformative approach in the realm of fluid dynamics, offering a data-driven framework to tackle the intrinsic complexities of active flow control.

Learning the basics can ease loop tuning frustration and ensure stability. During plant operations, it seems that tuning control loops is an ongoing task, which can be a continual frustration to ...