Detection and analysis of transition from annular to intermittent flow in vertical tubes

In vertical co-current gas-liquid flow, the transition from annular to intermittent flow occurs when gas core becomes interrupted by liquid bridges due to the instability of the interfacial capillary waves. An analytical model is formulated to explain the liquid bridging in terms of the growth of finite amplitude interfacial capillary waves. Experimental results show that the longest wave length, which is associated with the transition, is about eight times the wave length of waves moving with the velocity of the liquid film.     

Efficient solution of population balance equations with discontinuities by finite elements

Two refinements of Galerkin's method on finite elements were evaluated for the solution of population balance equations for precipitation systems. The traditional drawbacks of this approach have been the time required for computation of the two-dimensional integrals arising from the aggregation integrals and the difficulty in handling discontinuities that often arise in simulations of seeded reactors. The careful arrangement of invariant integrals for separable aggregation models allows for a thousandfold reduction in the computational costs. Discontinuities that may be present due to the hyperbolic nature of the system may be specifically tracked by the method of characteristics. These discontinuities will arise only from the initial distribution or nucleation and are readily identified. A combination of these techniques can be used that is intermediate in computational cost while still allowing discontinuous number densities. In a case study of calcium carbonate precipitation, it is found that the accuracy improvement gained by tracking the slope discontinuity may not be significant and that the computation speed may be sufficient for dynamic online optimization.     

MAXIMIZING SELECTIVITY OF LIQUID-LIQUID REACTION SYSTEMS. CONTROL OF THE DISPERSION PROCESS

Currently available information on droplet coalescence and break-up rates in turbulent flows in mixing vessels can be used to control drop sizes in dispersed phase equipment. The effect of drop size distributions on the selectivity and productivity in multi-reaction systems is examined in this paper.

The reaction system features the primary desired product (C) as resulting from reaction (in the bulk phase) between a reactant (A) in the drop phase and a second reactant (B) in the bulk phase. An adverse reaction is also envisaged which consumes (C) by further reaction with (B) to form a waste product. While small drops promote conversion because of large interfacial area, larger drops promote selectivity because of the facility of the product to re-enter the drop phase avoiding further reaction (to form waste) in the bulk phase. The effect of the bivariate distribution of drop size and reactant (A) concentration in the feed to a continuous stirred tank reactor on the selectivity and productivity of (C) is investigated within the framework of film theory while neglecting drop dynamics such as coalescence and break-up.

The results show the selectivity can be substantially improved by controlling drop size and distribution of the reactants among the differently sized droplets. Contrary to conventional wisdom which emphasizes creation of interfacial area by promoting very small droplets, it emerges that optimal distributions of drop size and reactant concentration which maximize productivity of the desired product exist. The practical implications are discussed.     

A model for transitional breakage probability of droplets in agitated lean liquid-liquid dispersions

A model for transitional breakage probability of droplets in agitated lean fiquid-liquid dispersions is proposed based on the mechanism of breakage of droplets due to their oscillations resulting from relative velocity fluctuations. A universal transitional breakage probability in terms of non-dimensionalized drop diameter is derived for all dispersed phases whose density and viscosity are almost the same as that of continuous phase. The maximum stable drop diameter d_s derived from the model, shows a dependence of N_We^?0.6. It is shown that a “power law” approximation Kvⁿ is valid for transitional breakage probability for d/d_s up to 2. The exponent 2.67, predicted by this model corresponds rather well with an estimate of 2, obtained from experimental observations. A functional relation for the rate constant K in terms of the parameters and physical properties of the system is derived. A universal non-dimensionalized equilibrium drop-size distribution for agitated lean liquid-liquid dispersions is derived by analytical solution of a population balance equation simplified by order of magnitude estimates. Interestingly enough, this analytical solution is the same as the Gaussian distribution suggested empirically by Chen and Middleman.     

CO2 process intensification of algae oil extraction to biodiesel

Algae-to-biodiesel processes are hindered by high costs and low energy return on investment.^1,2. Herein, three foci in research improve algae-to-biodiesel processes by: (1) reducing high installation and energy costs in the CO₂ sequestration, cultivation, and harvesting stages; (2) improving oil extraction and biodiesel generation; and (3) increasing utilization of the proteins in lipid-extracted biomass (e.g., for animal feed), as well as the omega-3 fatty acids for nutraceuticals and food supplements. A process is introduced that uses carbon dioxide to aid in all three of these foci. CO₂ is used first in the form of microbubbles to lyse algae cell walls, releasing triglyceride oils. CO₂ also aids with transesterification of these triglycerides using methanol. At low temperatures (353.15–368.15 K) and intermediate pressures (5–10 MMPa), carbon dioxide causes methanol to dissolve partially in the triglyceride phase and triglyceride to dissolve partially in the methanol phase, increasing the transesterification reaction rate. Due to the nondestructive nature of these processes, other metabolites can also be harvested providing improvements in both mass and economic efficiency with an overall sharp reduction in the modeled price of biodiesel.     

Performance evaluation of an ANN–GA aided experimental modeling and optimization procedure for enhanced synthesis of marine biosurfactant in a stirred tank reactor

BACKGROUND: An improved resilient back‐propagation neural network modeling coupled with genetic algorithm aided optimization technique was employed for optimizing the process variables to maximize lipopeptide biosurfactant production by marine Bacillus circulans. RESULTS: An artificial neural network (ANN) was used to develop a non‐linear model based on a 2⁴ full factorial central composite design involving four independent parameters, agitation, aeration, temperature and pH with biosurfactant concentration as the process output. The polynomial model was optimized to maximize lipopeptide biosurfactants concentration using a genetic algorithm (GA). The ranges and levels of these critical process parameters were determined through single‐factor‐at‐a‐time experimental strategy. Improved ANN‐GA modeling and optimization were performed using MATLAB v.7.6 and the experimental design was obtained using Design Expert v.7.0. The ANN model was developed using the advanced neural network architecture called resilient back‐propagation algorithm. CONCLUSION: Process optimization for maximum production of marine microbial surfactant involving ANN‐GA aided experimental modeling and optimization was successfully carried out as the predicted optimal conditions were well validated by performing actual fermentation experiments. Approximately 52% enhancement in biosurfactant concentration was achieved using the above‐mentioned optimization strategy. © 2012 Society of Chemical Industry     

Performance evaluation of batch and unsteady state fed‐batch reactor operations for the production of a marine microbial surfactant

BACKGROUND: Biosurfactants are microbially derived surface‐active and amphipathic molecules produced by various microorganisms. These versatile biomolecules can find potential applications in food, cosmetics, petroleum recovery and biopharmaceutical industries. However, their commercial use is impeded by low yields and productivities in fermentation processes. Thus, an attempt was made to enhance product yield and process productivity by designing a fed‐batch mode reactor strategy. RESULTS: Biosurfactant (BS) production by a marine bacterium was performed in batch and fed‐batch modes of reactor operation in a 3.7 L fermenter. BS concentration of 4.61 ± 0.07 g L^?1 was achieved in batch mode after 22 h with minimum power input of 33.87 × 10³ W, resulting in maximum mixing efficiency. The volumetric oxygen flow rate (K_La) of the marine culture was about 0.08 s^?1. BS production was growth‐associated, as evident from fitting growth kinetics data into the Luedeking‐Piret model. An unsteady state fed batch (USFB) strategy was employed to enhance BS production. Glucose feeding was done at different flow rates ranging from 3.7 mL min^?1 (USFB‐I) to 10 mL min^?1 (USFB‐II). USFB‐I strategy resulted in a maximum biosurfactant yield of 6.2 g l^?1 with an increment of 35% of batch data. The kinetic parameters of USFB‐I were better than those from batch and USFB‐II. CONCLUSION: Comparative performance evaluation of batch and semi‐continuous reactor operations was accomplished. USFB‐I operation improved biosurfactant production by about 35% over batch mode. USFB‐I strategy was more kinetically favorable than batch and USFB‐II. © 2012 Society of Chemical Industry     

A New Bad Data Detection & Identification Algorithm

A fast and reliable algorithm for detecting and indentifying bad data in active-power measurements is proposed. The states are chosen to be the bus-voltage magnitudes and bus-voltage angle-differences. The bus-voltage angle-differences satisfy a set of loop equations derived from the topology of the network and a set of power-flow equations at nodes with no generations and loads. The algorithm is based on inspecting a similar set of equations. The proposed algorithm is tested on a realistic example and the results are compared with those of the conventional bad data elimination scheme.     

Simulation of bubble populations in a gas fluidized bed

The dynamics of bubble populations in a gas fluidized bed have been analyzed using a simulation technique due to the authors [11,12]. It is shown that small bubble populations arising from progressive coalescence may lead to inherent fluctuations which may be considerable. Evidently, such fluctuations could manifest in conversions in fluidized bed reactors. The results obtained were based on a model due to Argyriou, List and Shinnar[1].