Performance improvement of the self-power control valve based on digital twin technology

Ju, Jinyong; Xie, Yudong; Han, Jiazhen; Wang, Yong; Wang, Haibo

doi:10.1016/j.energy.2024.131607

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Cited by 3 publications

References 21 publications

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NPP accident prevention: Integrated neural network for coupled multivariate time series prediction based on PSO and its application under uncertainty analysis for NPP data

Xiao,

Zhang,

Song

et al. 2024

Energy

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NPP accident prevention: Integrated neural network for coupled multivariate time series prediction based on PSO and its application under uncertainty analysis for NPP data

Xiao,

Zhang,

Song

et al. 2024

Energy

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Research and Design of Data Link Twin System

Han,

Lei,

Dai

et al. 2024

2024 3rd International Joint Conference on Information and Communication Engineering (JCICE)

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A Review of Safety Valves: Standards, Design, and Technological Advances in Industry

Cană,

Ripeanu,

Diniță

et al. 2025

Processes

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This review synthesizes insights from the literature and incorporates computational and experimental analyses to explore various types of safety valves and their applications across industries such as oil and gas, chemical manufacturing, and power generation. Key areas of focus include global regulatory standards from organizations like the American Society of Mechanical Engineers (ASME), International Organization for Standardization (ISO), Deutsches Institut für Normung (DIN), and American Petroleum Institute (API), which ensure stringent design and testing requirements. This paper examines the historical development of safety valves, recent technological advancements such as smart valves with integrated sensors, and predictive maintenance capabilities, along with ongoing challenges in high-pressure and corrosive environments. Additionally, it highlights the role of computational tools like CFD and FEA in optimizing valve designs and ensuring reliability under demanding conditions. By presenting a streamlined analysis of standards, innovations, and future directions, this review underscores the indispensable importance of safety valve technology in ensuring operational safety across various industrial applications.

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Performance improvement of the self-power control valve based on digital twin technology

Cited by 3 publications

References 21 publications

NPP accident prevention: Integrated neural network for coupled multivariate time series prediction based on PSO and its application under uncertainty analysis for NPP data

NPP accident prevention: Integrated neural network for coupled multivariate time series prediction based on PSO and its application under uncertainty analysis for NPP data

Research and Design of Data Link Twin System

A Review of Safety Valves: Standards, Design, and Technological Advances in Industry

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