Modeling of Hydrodynamic Cavitation Reactors: Reflections on Present Status and Path Forward

Numerical simulation of cavitation-vortex interaction mechanism in an advanced rotational hydrodynamic cavitation reactor

Hydrodynamic cavitation (HC), a promising technology for enhancing processes, has shown distinct effectiveness and versatility in various chemical and environmental applications. The recently developed advanced rotational hydrodynamic cavitation reactors (ARHCRs), employing cavitation generation units (CGUs) to induce cavitation, have demonstrated greater suitability for industrial-scale applications than conventional devices. However, the intricate interplay between vortex and cavitation, along with its spatial-temporal evolution in the complex flow field of ARHCRs, remains inadequately elucidated. This study investigated the interaction mechanism between cavitation and vortex in a representative interaction-type ARHCR for the first time using the "simplified flow field strategy" and the Q-criterion. The findings reveal that the flow instability caused by CGUs leads to intricate helical and vortex flows, subsequently giving rise to both sheet and vortex cavitation. Subsequently, utilizing the Q-criterion, the vortex structures are identified to be concentrated inside and at CGU edges with evolution process of mergence and separation. These vortex structures directly influence the shape and dimensions of cavities, establishing a complex interaction with cavitation. Lastly, the vorticity transport equation analysis uncovered that the stretching and dilatation terms dominate the vorticity transport process. Simultaneously, the baroclinic term focuses on the vapor-liquid interface, characterized by significant alterations in density and pressure gradients. These findings contribute to a better comprehension of the cavitation-vortex interaction in ARHCRs.

Degradation of methyl orange using hydrodynamic Cavitation, H2O2, and photo-catalysis with TiO2-Coated glass Fibers: Key operating parameters and synergistic effects

Advanced oxidation processes (AOPs) are eco-friendly, and promising technology for treating dye containing wastewater. This study focuses on investigating the removal of methyl orange (MO), an azo dye, from a synthetic wastewater through the use of hydrodynamic cavitation (HC), both independently and in combination with hydrogen peroxide (H2O2), as an external oxidant, as well as photocatalysis (PC) employing catalyst coated on glass fibers tissue (GFT). The examination of various operating parameters, including the pressure drop and the concentration of H2O2, was systematically conducted to optimize the degradation of MO. A per-pass degradation modelwas used to interpret and describe the experimental data. The data revealed that exclusive employment of HC using a vortex-based cavitation device at 1.5 bar pressure drop, resulted in a degradation exceeding 96 % after 100 passes, equivalent to 230 min of treatment (cavitation yield of 3.6 mg/kJ for HC), with a COD mineralization surpassing 12 %. The presence of a small amount of H2O2 (0.01 %) significantly reduced the degradation time from 230 min to 36 min (16 passes), achieving a degradation of 99.8 % (cavitation yield of 6.77 mg/kJ for HC) with COD mineralization rate twice as much as HC alone, indicating a synergistic effect of 4.8. The degradation time was further reduced to 21 min by combining HC with PC using TiO2-coated glass fibers and H2O2, (cavitation yield of 11.83 mg/kJ for HC), resulting in an impressive synergistic effect of 9.2 and COD mineralization twice as high as the HC/H2O2 system. The results demonstrate that HC based hybrid AOPs can be very effective for treating and mineralizing azo dyes in water.

Integrated physicochemical processes to tackle high-COD wastewater from pharmaceutical industry

Wastewater decontamination in pharmaceuticals is crucial to prevent environmental and health risks from API residues and other contaminants. Advanced oxidation processes (AOPs) combined with cavitational treatments offer effective solutions. Challenges include designing reactors on a large scale and monitoring the effectiveness and synergies of the hybrid technology. In the present work, pilot-scale treatment of a real high COD (485 g/L) pharmaceutical wastewater (PW) was investigated using hydrodynamic cavitation (HC) operated individually at 330 L/h or in combination with oxidants and electrical discharge (ED) with cold plasma (15 kV and 48 kHz). The first approach consisted of PW cavitational treatment alone of 7 L of 1:100 diluted PW at a HC-induced pressure of 60 bar and a flow rate of 330 L/h. However, this strategy did not provide satisfactory results for COD (∼15% less), and only when HC treatment was extended to more than 30 min in a recirculation mode, encouraging results were obtained (∼45% COD reduction). Consequently, a hybrid approach combining HC with ED-cold plasma was chosen to treat this high-COD PW. Aiming to establish an efficient flow-through hybrid process, after optimising all cavitation and electrical discharge parameters (45 bar HC pressure and 10 kHz ED frequency), the best COD abatement of ∼50 % was recorded with a 1:50 diluted PW. However, a subsequent adsorption step over activated carbon was required to achieve an almost quantitative COD reduction (95%+). Our integrated physicochemical process proved to be extremely efficient in treating high-COD industrial wastewater and resulted in a remarkable reduction of the COD value. In addition, the residual surfactants content in the PW were also drastically reduced (98%+) when a small amount of oxidants was added in the hybrid HC/ED treatment.

ANN based surrogate model for key Physico-chemical effects of cavitation

Intense and localised physico-chemical effects realised by cavitation such as generation of hydroxyl radicals, high-speed jets, and very high energy dissipation rates are being harnessed for a wide range of applications from emulsions, crystallisation, reactions to water treatment and waste valorisation. Single cavity models are typically used to quantitatively estimate such localised effects of cavity collapse. However, these models demand significant computing resources for resolving fast dynamics and therefore are very difficult, if not impossible, to integrate with CFD based cavitation device or reactor scale models. This severely limits the utility of device/ reactor scale models in simulating key applications of interest. In this work, we present, for the first time, artificial neural network (ANN) based surrogate models which accurately represent complex physico-chemical effects of cavity collapse. Recently developed cavity dynamics model was used for generating training data set encompassing both acoustic and hydrodynamic cavitation. Appropriate methodology for training ANN was developed. A shallow three hidden layer dense ANN was found to be more effective for estimating three main effects of cavity collapse: jet velocity, •OH generation and localised energy dissipation rate. The performance of trained ANN was then evaluated by comparing the predictions with the totally unseen data obtained from the cavity dynamics model. The developed ANN was shown to simulate unseen data very well not just within the range of training data (interpolation) but also beyond (extrapolation). Algebraic equations representing ANN are included to facilitate incorporation in device/ reactor scale CFD models. The presented methodology and results will be useful for developing high-fidelity CFD models of cavitation devices/ reactors based on key physico-chemical effects of cavity collapse.

Intensifying extraction of biomolecules from macroalgae using vortex based hydrodynamic cavitation device

Macroalgae have a tremendous potential to become an important renewable resource for valuable biomolecules and chemicals. New and improved ways of cell disruption and of enhancing rate as well as yield of extraction of valuable products from macroalgae are needed to fully realise this potential. In this work, hydrodynamic cavitation (HC) was used for intensifying rate and yield of extraction of phycoerythrin, proteins and carbohydrates from marine macroalgae Palmaria palmata. We use vortex-based HC devices which do not use small restrictions like orifice-based HC devices or moving parts like rotor-stator based HC devices. A bench scale setup with a nominal slurry flow rate of 20 LPM was established. Dried and powdered macroalgae was used. Influence of key operating parameters like pressure drop and number of passes on extraction performance (the rate and yield) was measured. A simple, yet effective model was developed and used for interpreting and describing experimental data. The results indicate that there exists an optimum pressure drop across the device at which extraction performance is maximum. The extraction performance with HC was found to be significantly better than the stirred vessels. HC has resulted in 2 to 20 times improvement in the rate of extraction of phycoerythrin (R-PE), proteins and carbohydrates. Based on the results obtained in this work, pressure drop of 200 kPa and number of passes through the HC devices of about 100 were found to be most effective for HC-assisted intensified extraction from macroalgae. The presented results and model will be useful for harnessing vortex-based HC devices for intensifying the extraction of valuable products from macroalgae.