Numerical Cavitation Model with thermodynamic effects for process intensification in a Venturi Reactors
Year: 2025
Type: article
Abstract: Process intensification through cavitation in Venturi reactors holds significantpotential for enhancing industrial efficiency. However, accurately predictingcavitation behavior under thermal conditions remains challenging. Thisstudy presents a novel numerical model implemented in the OpenFOAM environmentto simulate cavitation of high temperature water in Venturi reactors.The model employs a compressible Volume of Fluid (VOF) approach and incorporatesa modified Schnerr-Sauer cavitation model that accounts for thermaleffects by integrating energy equations and temperature-dependent fluidproperties. The model is validated against experimental data from Petkovˇsekand Dular [1], focused on temperature profiles and cavitation lengths at differentcavitation numbers. The simulations showed good agreement withexperimental observations, achieving Root Mean Square Error (RMSE) valuesof 0.0117K for case E1, 0.0202K for E2, and 0.0336K for E3. The modelaccurately predicted the intensity of thermal depression and the extent ofthe cavitation region. The study also examined unsteady behaviors such asre-entrant jet mechanisms, shedding frequencies and temperature depressionat different cavitation number. The developed model has proven reliable insimulating cavitation within thermal regimes, offering critical insights for optimizingVenturi reactor design and operation in high-temperature industrialprocesses. This research contributes to process intensification by delivering a validated numerical framework that deepens the understanding and predictivecapabilities of cavitation dynamics in high-temperature water systems.Additionally, the framework is designed to be integrated with optimizationalgorithms, offering a powerful tool for enhancing system performance andefficiency.
Source: Applied Thermal Engineering
Language: English
Subfield: Mechanics of Materials
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,660
Funders: Fondazione Cariplo, Univerza v Ljubljani
OpenAlex ID: W4408509183
