A control valve is a device designed to regulate the flow rate or pressure of a fluid within a system. It has the capability to either open or close entirely or to partially adjust its position to regulate the flow or pressure. These valves are pivotal in numerous industrial processes, ensuring safe and efficient operations. They are extensively utilized across various sectors including oil & gas, chemical, power generation, and water treatment, among others. For enhanced flow control and to expand the flow regulation range, making flow alterations more adaptable, there are internal elements of a valve—known collectively as the valve trim—which come into contact with the process fluid and influence its flow. These elements include the stem, plug, seat, and cage. Both academic research and industrial feedback have shown that flow behaviours within the control valve are challenging to monitor and can lead to issues such as internal damage, thereby shortening the valve's service life. Consequently, the design and optimization of existing control valve models have been prominent research topics for years. With the aid of modern technology, especially Computational Fluid Dynamics (CFD), studying inherent flow characteristics has become feasible. Experts have highlighted that geometry, pressure, and flow are pivotal parameters in control valve design and operation. Notably, geometry can significantly influence other parameters. For instance, flow might increase or decrease based on pressure changes, driven by the complexity of the flow path. The underlying reasons for these flow parameter changes are often related to flow behaviours. Major control valve issues like cavitation and noise generation are directly linked to these flow behaviours. As a result, numerous researchers have employed experimental and numerical methods to study flow behaviours in control valves, aiming to address issues like cavitation and abnormal vibrations. Traditional control valve design strategies rely on experimental data collection, analysing historical databases of flow parameters acquired from flow meters and electronic devices, and then applying CFD techniques to evaluate performance and anticipate potential problems. In this research study, a comprehensive digital twin system for control valves was developed to minimise the predictive aspect of analyses through the physical and digital integration of control valves. The development of a digital twin aims to remove any assumptions in potential problems and maintenance.
| Date of Award | 21 May 2024 |
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| Original language | English |
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| Supervisor | Rakesh Mishra (Main Supervisor) & Hamid Alturbeh (Co-Supervisor) |
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