1. A computational framework for electrification of liquid flows
- Author
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Mathieu Calero, Holger Grosshans, Miltiadis Papalexandris, and UCL - SST/IMMC/TFL - Thermodynamics and fluid mechanics
- Subjects
Hazard (logic) ,Electrical double layer ,Computer science ,General Chemical Engineering ,Energy Engineering and Power Technology ,Management Science and Operations Research ,01 natural sciences ,Explosion protection ,Industrial and Manufacturing Engineering ,010305 fluids & plasmas ,symbols.namesake ,Electrification ,0103 physical sciences ,Numerical simulations ,Turbulent flows ,Diffusion (business) ,010306 general physics ,Safety, Risk, Reliability and Quality ,Dielectric liquids ,Electrohydrodynamics ,Turbulence ,Reynolds number ,Mechanics ,Boundary layer ,Flow electrification ,Flow (mathematics) ,Control and Systems Engineering ,symbols ,Food Science - Abstract
Flow electrification constitutes a significant hazard to operational safety in industry and for this reason it has been studied in detail over the years. It is generally accepted that the impact of turbulence on the electrification of liquids is of paramount importance. More specifically, at sufficiently high Reynolds numbers and for low-conductivity liquids such as hydrocarbons, the thickness of the hydrodynamic boundary layer can become comparable to that of the electrical double layer. This can lead to increased charge diffusion towards the bulk of the flow and, subsequently, flow electrification. However, quantitative information of the underpinning mechanisms of this phenomenon is still lacking. In this paper we present a computational framework for the study of electrification of liquid flows via numerical simulations. In the first part of the paper, we present the governing equations and describe the proposed algorithm and its implementation in pafiX, which is a computational tool for the simulation of fluid flows related to explosion protection. In the second part, we present results from numerical tests that we performed in order to access the efficiency of the proposed computational framework.
- Published
- 2022
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