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 ...

In 2012, Automation World published an article looking at the decision factors faced when choosing electric or pneumatic actuators. More than a decade later, manufacturing engineers and OEMs still ...

Australian researchers are proposing a novel, learning-based H∞ control method to enhance the performance of vanadium redox flow batteries in DC microgrids. Vanadium redox flow batteries are one of ...

Just over a decade ago, an article titled, "Advanced Control Strategies Move into the Field" (Control, October 2008), highlighted three evolving trends in the process control world that would "make ...

Integrated slug-flow optimization can mitigate flow problems in a wide range of both offshore and onshore operating conditions. Slug flow is one of the most common flow states in horizontal and ...

Southwest Research Institute is now the home of a reciprocating compressor flow loop that is capable of recreating real-life gas pipeline pressures, temperatures and horsepower levels. The flow loop ...

This is Part 2 of a two-part articles discussing the challenges facing service providers as they transition from TDM-based legacy networks to packet-based networks capable of hosting next-generation ...