Effect of Mass Transport by Convective Flow on the Distribution of Dissolved Carbon Monoxide in a Stirred Tank

The dissolved gas concentration in a stirred tank has significant importance in the chemical and biological processing industries as mass transfer from the injected gas to an aqueous solution must occur for the gas to be usable. As the solubility of the gas in the solution is low and there are no probes for measuring dissolved gas concentration, a volumetric mass transfer coefficient is selected as a criterion of design for the scale-up of stirred reactors. However, it is difficult to accurately predict the non-equilibrium state dissolved gas distribution using only the volumetric mass transfer coefficient. In this study, computational fluid dynamics (CFD)-based numerical analysis was conducted to systematically evaluated the effects of mass transport by convective flow on the distribution of dissolved carbon monoxide in a stirred tank. The dissolved carbon monoxide distribution and the volumetric mass transfer coefficient were compared at various rotational speeds of the impellers. At a rotational speed of 900 RPM, the Pearson correlation coefficient was about 0.52, which denotes a moderate correlation. In contrast, Pearson correlation coefficients less than 0.20 were obtained for speeds less than 700 RPM, indicating a weak correlation. By considering the dissolved carbon monoxide transport that occurs during convective flow in stirred tanks, we can provide more accurate information about the dissolved carbon monoxide distribution.

Gas Dispersion in Non-Newtonian Fluids with Mechanically Agitated Systems: A Review

Gas dispersion in non-Newtonian fluids is encountered in a broad range of chemical, biochemical, and food industries. Mechanically agitated vessels are commonly employed in these processes because they promote high degree of contact between the phases. However, mixing non-Newtonian fluids is a challenging task that requires comprehensive knowledge of the mixing flow to accurately design stirred vessels. Therefore, this review presents the developments accomplished by researchers in this field. The present work describes mixing and mass transfer variables, namely volumetric mass transfer coefficient, power consumption, gas holdup, bubble diameter, and cavern size. It presents empirical correlations for the mixing variables and discusses the effects of operating and design parameters on the mixing and mass transfer process. Furthermore, this paper demonstrates the advantages of employing computational fluid dynamics tools to shed light on the hydrodynamics of this complex flow. The literature review shows that knowledge gaps remain for gas dispersion in yield stress fluids and non-Newtonian fluids with viscoelastic effects. In addition, comprehensive studies accounting for the scale-up of these mixing processes still need to be accomplished. Hence, further investigation of the flow patterns under different process and design conditions are valuable to have an appropriate insight into this complex system.

High-fidelity profiling and modeling of heterogeneity in wastewater systems using milli-electrode array (MEA): Toward high-efficiency and energy-saving operation

High energy consumption is a critical problem for wastewater treatment systems currently monitored using conventional "single point" probes and operated with manual or automatic open-loop control strategies, exhibiting significant time lag. This challenge is addressed in this study by profiling the variation of three critical water quality parameters (conductivity, temperature and pH) along the depth of a reactor at high spatiotemporal resolution in a real-time mode using flat thin milli-electrode array (MEA) sensors. The profiling accurately captured the heterogeneous status of the reactor under transient shocks (conductivity and pH) and slow lingering shock (temperature), providing an effective dataset to optimize the chemical dosage and energy requirement of wastewater treatment systems. Transient shock models were developed to validate the MEA profiles and calculate mass transfer coefficients. Monte Carlo simulation revealed high-resolution MEA profiling combined with fast closed-loop control strategies can save 59.50% of energy consumption (Temperature and oxygen consumption controls) and 45.29% of chemical dosage, and reach 16.28% performance improvement over the benchmark (defined with ideal conditions), compared with traditional "single-point" sensors that could only monitor the entire system through a single process state. This study demonstrated the capability of MEA sensors to profile reactor heterogeneity, visualize the variation of water quality at high resolution, provide complete datasets for accurate control, and ultimately lead to energy-saving operation with high resilience.