Hydrodynamic cavitation induced by different nozzle shapes in pressurized conduits, instrumented by optical detection, searching for pressure correlation

Hydrodynamic cavitation is a valuable technology for water treatment applications. It is well known that is capable of degrading molecules, inactivating microorganisms, reducing hardness, among other applications. However, this phenomenon must be controlled to ensure its adequate intensity. The aim of this study was to develop and test a nonintrusive optical system for cavitation detection and control in a modified Venturi tube. The experimental setup of a closed-loop piping system allowed a comprehensive analysis of the cavitation phenomenon, with precise control of flow rate and pressure conditions. Five different nozzle geometries were tested. The device was equipped with a light-emitting diode and a photosensor integrated into a nozzle. The average irradiance provided by the optical instrumentation effectively detected the presence of cavitation bubbles and the occurrence of single-phase flow. In addition, the study identified three robust correlations between dimensionless parameters, modeled using empirical equations that reliably fit the experimental data. These models and the optical detection system provide a consistent tool for identifying two-phase flow conditions in pipelines. The dimensionless ratio between the standard deviation of the pressure and the mean pressure in the section downstream of the nozzle increased with the flow rate and bubble density, reflecting the intensity of the cavitation-induced turbulence. Analysis of the results for the five nozzles led to the identification of the most efficient geometry in terms of pressure drop and cavitation intensity. [Display omitted] •Different nozzle geometries can change hydrodynamic cavitation effects.•Nonintrusive optical system used to detect and analyze hydrodynamic cavitation.•Standard deviation and mean pressure dimensionless ratio reflect turbulence.•Measuring and analysis of two-phase flow patterns.