Machine learning (ML) techniques are now widely being used in almost all areas of application. Six months back, CCTech Research started investigating how we may use ML in the area of Design of Mechanical Systems. One of the key application we were particularly interested is in Control Valve industry. simulationHub's Control Valve Performer app is already calculating valve performance within minutes compared to weeks in traditional CFD way. But one still yearns for a solution that could predict the flow performance in less than 5 seconds. The machine learning app developed by CCTech research team is now able to predict the value performance within seconds. Read more about the app, what went into creating the app and the app workflow.
Designing of control valves involves a lot of design parameters which needs to be considered to ensure safety and durability of the valve. One such prominent parameter is the Coefficient of Hydrodynamic Torque (Cdt). Control Valve Performer app by simulationHub now calculates and delivers the Cdt curve for all rotary motion valves. Here I am explaining all about this new feature and help make your valve design more efficient.
The heart of the control valve is the trim, especially the mating parts that throttle the stream to the demands of the controller. Each process is unique in nature and demands unique flow control characteristics. The synergy between what is demanded and what is supplied by the valve can be achieved by re-shaping the valve trim to get desired valve characteristics. Here I am sharing my experience of using simulationHub Control Valve Performer app with underlying CFD technology as a tool to evaluate the valve trim design of a lift valve.