The Digital Twin Realization of an Ejector for Multiphase Flows

Giovanni Mazzuto, Filippo Emanuele Ciarapica, Marco Ortenzi and Maurizio Bevilacqua
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Giovanni Mazzuto: Dipartimento Ingegneria Industriale e Scienze Matematiche, Faculty of Engineering, Università Politecnica delle Marche, 60131 Ancona, Italy
Filippo Emanuele Ciarapica: Dipartimento Ingegneria Industriale e Scienze Matematiche, Faculty of Engineering, Università Politecnica delle Marche, 60131 Ancona, Italy
Marco Ortenzi: Dipartimento Ingegneria Industriale e Scienze Matematiche, Faculty of Engineering, Università Politecnica delle Marche, 60131 Ancona, Italy
Maurizio Bevilacqua: Dipartimento Ingegneria Industriale e Scienze Matematiche, Faculty of Engineering, Università Politecnica delle Marche, 60131 Ancona, Italy

Energies, 2021, vol. 14, issue 17, 1-23

Abstract: Despite the extensive use of ejectors in the process industry, it is complex to predict suction and motive fluids mixture characteristics, especially with multiphase flows, even if, in most cases, mixture pressure control is necessary to satisfy process requirements or to avoid performance problems. The realization of an ejector model can allow the operators to overcome these difficulties to have real-time control of the system performance. In this context, this work proposes a framework for developing a Digital Twin of an ejector installed in an experimental plant able to predict the future state of an item and the impact of negative scenarios and faults diagnosis. ANNs have been identified as the most used tool for simulating the multiphase flow ejector. Nevertheless, the complexity in defining their structure and the computational effort to train and use them are not suitable for realizing standalone applications onboard the ejector. The proposed paper shows how Swarm Intelligence algorithms require a low computational complexity and overperform prediction error and computational effort. Specifically, the Grey Wolf optimizer proves to be the best one among those analyzed.

Keywords: ejector; multiphase flow; Swarm Intelligence algorithms (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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