The Taylor–Couette reactor (TCR) is becoming an increasingly significant topic in chemical industry. This study investigates the micromixing performance of a ribbed TCR with axial flow in the Villermaux–Dushman reaction system. The local micromixing mechanism of the ribbed TCR was analyzed, and the volume-averaged energy dissipation rate was calculated using CFD. The effects of operating parameters and rib structural parameters on micromixing performance were investigated. The results show that the introduction of ribs eliminates the high shear region between the vortex pairs, resulting in the strong micromixing region being situated on the inner and outer cylinder wall surfaces and the ribbed surface region. Smaller rib spacing, larger rib width, and rib height can strengthen micromixing and result in a smaller segregation index. Micromixing times of ribbed TCRs were calculated using the incorporation model, tm, in the range of 2.0 × 10−5 to 8.0 × 10−3. The results show that ribbed TCRs require a lower energy consumption to achieve a lower tm than other rotating reactors. A correlation equation between tm and five parameters was developed, with a correlation coefficient of 0.951. The accuracy of the volume-averaged energy dissipation rate obtained via CFD was verified through experimental analysis. The correlation between the micromixing time and the volume-averaged energy dissipation rate was established in a form that satisfies Kolmogorov’s turbulence theory for tm. To convert the volume-averaged energy dissipation rate into a local energy dissipation rate, a factor ϕ was introduced and solved using the engulfing diffusion model. This study provides insights into the design and optimization of ribbed TCRs.
This paper investigates the flow structure and flow pattern transition within a conical ribbed Taylor–Couette reactor (TCR), which is 4 mm in gap width and 200 mm in height, via particle image velocimetry (PIV) and numerical simulation methods. The effect of various parameters on the vortex structure and on flow transition, including the structural parameters of the ribs (rib spacing and rib width) and the operating parameters (Taylor number and axial Reynolds number), were investigated. Without axial flow, the ribbed TCR can control the flow structure while maintaining the symmetry of the flow field. Under certain conditions, a Taylor vortex pair can form between the ribs, with the down vortex rotating clockwise and the up vortex rotating counterclockwise. The axial dimension of the Taylor vortex can be controlled by adjusting the rib spacing, which can be summarized into four different conditions according to the size of the rib spacing. With axial flow, the axial Reynolds number greatly impacts the Taylor vortex structure within the ribbed TCR, and as the axial Reynolds number increases, the up vortex appears to be compressed and the down vortex appears to be stretched. The double vortex flow pattern between the ribs is eventually transformed into a single vortex. The critical axial Reynolds number for flow pattern transition is defined and correlated with the Taylor number and rib spacing. The results show that the critical axial Reynolds number is positively proportional to the Taylor number and is inversely proportional to rib spacing. The empirical correlation equation developed in this study shows strong predictive power and is validated using the experimental results. Overall, this study provides a comprehensive understanding of the flow structure and pattern transition within a ribbed TCR and lays the foundation for the further optimization of TCR design.
Refractive index and density matching are essential for optical measurements of neutrally buoyant liquid–liquid flows. In this study, we proposed a design of experiments (DoE) to develop refractive index and density matching systems, including objective setting, candidates screening, sampling and fitting, and a detailed matching process. Candidates screening criteria based on the density and refractive index ranges of the aqueous and organic phases were used. Using the DoE, we proposed a system with a ternary aqueous phase potassium thiocyanate (KSCN)/ammonium thiocyanate (NH4SCN) solution and m-dichlorobenzene/tripropionin solution as the organic phase to achieve the tuning of the RI and density simultaneously. Empirical correlations of the refractive index and density with respect to the concentration and temperature for the three mixtures were obtained by combining Latin hypercube sampling with binary polynomial fitting. Correlations were validated with existing data in the literature and were found to align with deviations as low as 4×10−4 for the refractive index and 2×10−3g⋅cm−3 for the density. Using the correlations, the refractive indices for the ternary aqueous phase, the binary organic phase, and the device materials were matched to be equal. Density matching was performed for the liquid–liquid phases as well. Refractive index- and density-matched recipes could be obtained for a wide range of temperatures (15–65 °C) and device materials (PMMA, borosilicate glass, quartz, and silica gel). These recipes provide options for the optical measurement of a liquid–liquid system required to neutralize buoyancy.
This paper proposes a milli-reactor design method incorporating reactor runaway criteria. Based on Computational Fluid Dynamic (CFD) simulation, neural networks are applied to obtain the optimal reactor structure according to the target reaction requirements. Varma’s theory, the critical Nusselt number for stable operation of the flow reactor, is derived. Inserts of the multi-blade structure are designed and investigated to enhance mixing and heat transfer performance. The flow field and heat transfer capacities are obtained by CFD calculations in the range of Re 50–1800. The internal components increase the heat transfer performance up to 21 times, and the pressure drop up to 16 times. The inclined angle of the blade is recommended to be 45°, which can effectively improve heat transfer without generating excessive pressure drop. By partial least squares regression (PLS) analysis, Re and the number of blades are the most critical factors affecting heat transfer, and the five blades and smaller tilt angles are recommended. The CFD calculation results are in good agreement with the Particle Image Velocimetry (PIV) experimental results.
The yields of chemical reactions are highly dependent on the mixing pattern between reactants. Herein, we report the modification of a meso-micromixing interaction reaction model which is applied in batch reactors by leveraging the flow characteristics in the continuous reactors. Both experimental and model-predicted yields were compared using the classical Villermaux–Dushman method in a self-designed split and recombination reactor. This modified model significantly reduced the error in predicted product yields from approximately 15% to within 3%, compared to a model containing the micromixing term only. The effects of flow rates and reactor structure parameters on mixing performance were analyzed. We found that increasing flow rates and the degree of twist in the mixing element’s grooves, as well as decreasing the cross-sectional area of grooves, improved mixing performance. The optimization of reactor flow rates and structural parameters was achieved by combining Gaussian process regression and Bayesian optimization with the modified model. This approach provided higher target product yields for consecutive reactions, while simultaneously achieving a lower pressure drop in the reactor. Corresponding combinations of reactor parameters were also identified during this process. Our modified model-based optimization methodology can be applied to a diversity of reactors, serving as a reference for the selection of their structure and operational parameters.
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