Hydrodynamic cavitation is a promising technology for several applications, like disinfection, sludge treatment, biodiesel production, degradation of organic emerging pollutants as pharmaceutical, and dye degradation. Due to local saturation conditions, cavitating liquid exhibits generation, growth, and subsequent collapse of vapor-filled cavities. The cavities' collapse brings very high pressure and temperature; this last aspect is essential in some chemical processes because it induces the decomposition of water molecules into species with a high oxidation potential, which can react with organic substances. Properly exploiting this process requires a highly accurate prediction of pressure peak values. To this purpose, we implemented a multi-phase Eulerian–Lagrangian code to solve the fluid-dynamic problem, coupled with the Rayleigh–Plesset equation, to capture the evolution of bubbles with the required accuracy. The algorithm was validated against experimental data acquired with optical techniques for different cavitation-shedding mechanisms. Then, we used the developed tool to investigate the decoloration of organic substances from a cavitation Venturi tube operating at different pressure. We compared the obtained results with the experimental observation to assess the reliability of the developed code as a predictive tool for cavitation and the possibility of using the code itself to assess scale-up criteria for possible industrial applications.
Eulerian–Lagrangian modeling of phase transition for application to cavitation-driven chemical processes
Also at: Consiglio Nazionale delle Ricerche, Istituto di Scienze e Tecnologie per l'Energia e la Mobilità Sostenibili (STEMS), Via G. Marconi 4, 80125 Napoli, Italy.
Note: This paper is part of the special topic, Cavitation.
Francesco Duronio, Andrea Di Mascio, Angelo De Vita, Valentina Innocenzi, Marina Prisciandaro; Eulerian–Lagrangian modeling of phase transition for application to cavitation-driven chemical processes. Physics of Fluids 1 May 2023; 35 (5): 053305. https://doi.org/10.1063/5.0145568
Download citation file: