Local flow analysis and management for digital twins of control valves

Qingyun Bu, Aliyu Aliyu, Rakesh Mishra

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Since about 2002, Industry 4.0, and Digital Twin (DT) research as we know it today, enjoyed increasing attention in academia and industry. The research on the DTs of control valves is currently not as mature as in other critical fields. It is however of utmost importance given the role control valves play in the process, nuclear, and petroleum industries. As a common and essential part of the pipeline system, valves are used to regulate fluid flow within pipelines to achieve a desired flow condition. However, the local flow characteristics within the valve domain are difficult to determine experimentally because of complex geometry and inaccessibility of the flow domain. The application of DT technology in pipelines allows real-time fluid flow data transmission both at global and local levels, and performance monitoring of the system as well as for predicting remaining useful life. Big data analytics and machine learning can be leveraged to improve valve system performance prediction as well as to improve safety. This paper describes initial work carried out on developing a control valve digital twin which incorporates tools for monitoring local flow conditions in the control valve. Computational Fluid Dynamics (CFD) is used to determine the internal characteristics of the fluid inside the valve, and the data are analysed and managed through the development of a DT of the valve system.
Original languageEnglish
Title of host publicationInternational Conference on Maintenance and Intelligent Asset Management (ICMIAM), 2021
Number of pages6
ISBN (Electronic)9781665466714
ISBN (Print)9781665466721
Publication statusPublished - 12 Dec 2021
EventInternational Conference on Maintenance and Intelligent Asset Management - Federation University Ballarat , Ballarat, Australia
Duration: 12 Dec 202115 Dec 2021


ConferenceInternational Conference on Maintenance and Intelligent Asset Management
Abbreviated titleICMIAM2021
Internet address


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