Pulsed Liquid-liquid Extraction Column Research Articles

Investigation of dispersed phase holdup in a Tenova pulsed liquid-liquid extraction column

BackgroundPulsed extraction columns have been designed and studied in different types of internal equipment such as packed, tray, and doughnut discs. In recent years (2017), researchers have turned to research on Tenova columns, which is the newest generation of pulsed columns. Correlations for predicting the hydrodynamics of the Tenova column have not been reported. MethodA pulsed Tenova column with a 7.4 cm diameter and 130 cm height including 30 pairs of modified doughnuts and discs was fabricated and tested. Standard chemical systems with low, medium, and high interfacial tension approved by the European Federation of Liquid-Liquid Extraction are used. Holdup as one of the most important hydrodynamic parameters in designing is studied. The effects of dispersed and continuous phase velocity and pulsation intensity have been taken into account. Significant findingsDimensional analysis used for predicting hold-up and an error about 8% have been obtained. Other experimental relations proposed by researchers in pulsed columns have been studied and the error of about 16% found. First and second critical pulsation intensity, which are the commencement and the end of breaking of drops has been seen in these experiments. The recommended operating pulsation intensity is between these two critical values.

Mass transfer from nanofluid drops in a pulsed liquid–liquid extraction column

Mass transfer in gas–liquid systems has been significantly enhanced by recent developments in nanotechnology. However, the influence of nanoparticles in liquid–liquid systems has received much less attention. In the present study, both experimental and theoretical works were performed to investigate the influence of nanoparticles on the mass transfer behaviour of drops inside a pulsed liquid–liquid extraction column (PLLEC). The chemical system of kerosene–acetic acid–water was used, and the drops were organic nanofluids containing hydrophobic SiO2 nanoparticles at concentrations of 0.01, 0.05, and 0.1vol%. The experimental results indicate that the addition of 0.1vol% nanoparticles to the base fluid improves the mass transfer performance by up to 60%. The increase in mass transfer with increased nanoparticle content was more apparent for lower pulsation intensities (0.3–1.3cm/s). At high pulsation intensities, the Sauter mean diameter (d32) decreased to smaller sizes (1.1–2.2mm), leading to decreased Brownian motion in the nanoparticles. Using an analogy for heat and mass transfer, an approach for determining the mass diffusion coefficient was suggested. A new predictive correlation was proposed to calculate the effective diffusivity and mass transfer coefficient in terms of the nanoparticle volume fraction, Reynolds number, and Schmidt number. Finally, model predictions were directly compared with the experimental results for different nanofluids. The absolute average relative error (%AARE) of the proposed correlation for the mass transfer coefficient and effective diffusivity were 5.3% and 5.4%, respectively.

The influence of nanoparticles on hydrodynamic characteristics and mass transfer performance in a pulsed liquid–liquid extraction column

With respect to the influence of nanoparticles on mass transfer characteristics, limited number of studies available in the literature, deal primarily with gas–liquid systems. In this work, mass transfer performance and hydrodynamic characteristics including static and dynamic dispersed phase hold-ups of nanofluids have been investigated for pulsed liquid–liquid extraction column (PLLEC). The nanofluids used were prepared by dispersing SiO 2 nanoparticles of 0.01, 0.05 and 0.1 volume percent with two different hydrophobicities in kerosene as base fluid using ultrasonication. UV–vis spectrophotometer was also used for evaluation of the nanofluids stability. The results were compared with conditions of no-nanoparticles in the dispersed phase and in the absence of mass transfer effect (no acetic acid as solute). Different pulsation intensities were maintained for the fixed mass flow rates of dispersed ( Q d) and continuous ( Q c) phases (with ratio Q c/ Q d = 1.2) with mass transfer direction being made from the dispersed phase to the continuous one. The results indicate that in the presence of the nanofluids, static and dynamic dispersed phase hold-ups increased by 23–398%, and 23–257%, respectively, while mass transfer performance was enhanced by 4–60%.

Drop size in a liquid pulsed sieve-plate extraction column

The (Benzoic acid + kerosene + water) system was studied in a 5.0 cm diameter liquid pulsed liquid-liquid extraction column with a total number of 80 sieve plates. The effect of pulsation intensity, dispersed phase superficial velocity, and continuous phase superficial velocity on volume-surface mean diameter was studied. Generally, the mean drop diameter decreased more rapidly with the increase of pulsation intensities and superficial velocities at low pulsation intensities and superficial velocities. However, the effect was not found to be significant at higher pulsation intensities and higher superficial velocities. In the interpretation of the experimental results, the drop size was observed to be a function of the operating regimes (mixer-settler, dispersion, and emulsion) of the pulsed sieve-plate extraction column. The experimental mean drop diameters were compared to the most acceptable analytical drop size correlation developed by Kumar and Hartland (1986). The correlation proved to be in good agreement for the column operating in the dispersion regime.

Multivariable Control of a Pulsed Liquid-Liquid Extraction Column by Neural Networks

Modelling and control of chemical process systems are usual applications of artificial neural networks that have been explored so far with success. This paper deals with the potential application of neural networks to the multivariable control of a solvent extraction pilot plant. The pilot plant to be controlled is a pulsed liquid-liquid extraction column, which presents a non-linear behaviour and time-varying dynamics. Previous works have shown that the column could be maintained in its optimal behaviour by means of the control of conductivity by action on the pulse frequency. A given product specification can be obtained by the control of the product concentration in the outlet stream by acting on the solvent feed-flow rate. Owing to interactions between one variable and the other, a two input-two output control scheme has been developed and implemented. Promising experimental results have been obtained by using neural networks as an alternative tool for online control of chemical plant with dynamic changes.

Simulation of a pneumatically pulsed liquid-liquid extraction column

The model presented simulates the hydrodynamic operation of a pneumatically pulsed countercurrent liquid-liquid extraction column. A balance on the droplet population is compiled at all levels of the column. This balance, which accounts for transport, rupture and coalescence mechan The experimental results obtained in steady-state conditions on a pilot plant facility served to validate the proposed model. Dynamic simulations of va

Regularized pole-placement adaptive control of a liquid-liquid extraction column

Some critical computations in pole-placement design and in that of many model reference adaptive systems are described. These numerical problems are associated with the resolution of the diophantine equation. They occur when the assumption of no common poles and zeros is violated. Regularization techniques which cope with ill-conditioning are presented. The resulting algorithm combines a standard indirect pole-placement adaptive control algorithm and a dimension-free regularization procedure of the design equations, thus avoiding the pole-zero cancellation problem and yet retaining the other properties of the algorithm. The application of this control scheme in a pulsed liquid-liquid extraction column is described. The control objective is to optimize the column behaviour. Extraction columns are subject to changes in feed compositions, feed flow-rates, physical properties of the solvent (the extractor) and the solute (liquid mixture) and various disturbances. The column exhibits highly non-linear and time-varying dynamics. The conductivity measured at a specific place in the column and the pulse frequency have been selected as control variables. Experimental results demonstrate the usefulness and the robustness of this regularized pole-placement adaptive control algorithm.

CONTROL OF A PULSED LIQUID-LIQUID EXTRACTION COLUMN BASED ON A MULTILEVEL SYSTEM OF AUTOMATA

This paper presents the real-time application of the learning control theory to the control of a chemical pilot plant: a pulsed liquid-liquid extraction column. The behaviour of an agitated liquid-liquid extraction column can be related to random mechanisms such as the phenomena of droplets breakage and coalescence. Previous studies on hydrodynamic and mass transfer aspects showed that a pulsed liquid-liquid extraction column had an optimal behaviour for operating conditions close to flooding. These results led to choose the following strategy to control the column in its optimal behaviour zone: - the measure of the conductivity of the liquid medium below the distributor which gives a good information about flooding, is the controlled variable -the pulse frequency is the control action. The learning control algorithm is based on a multilevel system of automata which operates in a random environment. By means of an evaluation unit of the performances of the column which generates either penalty (inaction) ...

Adaptive Linear Quadratic Control of an Extractor

The paper describes an application of an adaptive linear quadratic control algorithm to a pulsed liquid-liquid extraction column. The extractors are used in several industries as a separation technique. They perform a high degree of purification and are not heavy on energy. The considered plant has the same dimensions as those currently used in fine chemical processes. The control objective is to optimize the column behaviour in spite of fluctuations in flow and physical properties of the solvent (extractor) and the solute (liquid mixture). The physical model developed for the column is too complex to use for control purpose. Therefore a single input-single output discrete time linear model is adopted. The selected control variables are the pulse frequency and the conductivity measured at the bottom of the column. The experiences have been made with a mixture of water and toluene. The control algorithm is derived from a minimization of a quadratic cost function. The resulting Riccati equation is iterated until the closed-loop poles do belong to a predefined stability domain included in the unit circle. The adaptive control algorithm involves a parameter identification procedure and a state-feedback control law which uses the estimated parameters. The estimation procedure uses normalised data and a forgetting factor which is adjusted to maintain the trace of the estimator gain matrix constant. Details on the practical implementation of the control algorithm which is based on PDP-11 micro-computer are provided. The experimental results obtained show the ability of this algorithm to improve the efficiency of the considered process.

Identification of a Pulsed Liquid-liquid Extraction Column

In this paper, the identification of a pulsed liquid-liquid extraction column is dealt with. This chemical operation consists in creating an intimate contact of the mixture containing the component to be extracted with a solvent (extractor) and separate the obtained immiscible phases. The behaviour of the columns is governed by hydrodynamic and mass transfer phenomenons. The conductivity measured under the distributor and the pulse frequency have been selected as the control variables. For control purposes, the complex dynamics of the considered process have been modeled by a linear discrete-time model. The recursive least squares identification methods using U-D factorization have been implemented on a PDP-11 computer, which is used for on-line estimation of the model parameters. Several problems associated with on-line identification such as model parametrization, plant operation and supervision and signals conditioning are examined. Model validation is carried out using several criterions, such as Akaike's criteria for order selection, residuals analysis and loss functions evaluation. Some techniques that have been used to estimated the time delay are also described. The outcome of the experiments is a model which highlights the behaviour of this very sensitive plant.

Multivariable learning control of an extractor

This paper deals with the application of the learning approach to the multivariable control of an extraction pilot plant. This separation process presents a highly nonlinear behaviour and time-varying dynamics. A learning system is composed of three distinct parts. The first part consists of an automation with variable structure whose actions are selected according to a probability distribution associated to the set of actions. An updating scheme (or reinforcement scheme) adapts this probability distribution according to the “good” or “bad” behaviour of the process. The quality of the behaviour is defined on the basis of heuristic rules contained in a performance evaluation unit through information collected in the process (measurements). The pilot plant to be controlled is a pulsed liquid-liquid extraction column. The control strategy involves both the control of the column in its optimal-behaviour zone and the minimization of the solvent flow rate needed to obtain a specific product quality. Previous works have shown that the column could be maintained in its optimal behaviour by means of the regulation of conductivity by action on the pulse frequency. The obtaining of a given product specification can be achieved by the control of the product concentration in the outlet stream by acting on the solvent feed flow rate. Owing to interactions between one variable and another it seems promising to use a two input-two output control scheme. Experimental results are presented which show the feasibility of such an approach for on-line control of a chemical plant.

Learning control of a pulsed liquid-liquid extraction column

Liquid-liquid extraction has proved to be a very competitive technique compared to conventional separation methods such as distillation. It allows a higher degree of extraction, separation and concentration of the desired products to be obtained. Generally, a liquid-liquid extraction column is run manually. This, however, is not satisfactory, especially concerning new valuable applications in the field of fine chemistry where processes must reveal themselves flexible and polyvalent. The objective of this study was to improve the quality of control even with poor a priori information on the process and thereby to maintain the column in its optimal behaviour zone. This optimal behaviour has been shown to be reached for flooding conditions which can be controlled by measuring the conductivity of the liquid medium at a place located at the bottom of the column (below the distributor), the pulsing action being the command variable. The column considered is modelled as a random medium and the search tactics for the control problem are formulated as those of automation behaviour in a random medium. The automation is considered to be stochastic with a varying structure. This control approach requires minimum possible a priori information on the process. Usually the developed model of chemical plants is static or very complex and cannot be used to derive a control strategy. The experimental results illustrate the efficiency of learning control.

Self Tuning Control of a Pulsed Liquid-Liquid Extraction Column

This paper deals with the application of a self-tuning controller (STC) to a pulsed liquid-liquid extraction column. The control purpose is to maintain the column in its optimal behaviour zone in spite of flow and physical properties of solvent and solute fluctuations. The process model is re-parameterized to express it in terms of the controller parameters, which are identified on line.

GENERALIZED PREDICTIVE CONTROL OF A PULSED LIQUID-LIQUID EXTRACTION COLUMN

This paper deals with the application of a general predictive controller to a pulsed liquid-liquid extraction column. The control purpose is to maintain the column in its optimal behaviour zone in spite or flowrates and physical properties of solvent and solute fluctuations. The complex dynamics of the column is modeled by a low order linear discrete model with time varying parameters which are recursively identified. Based on these estimates, the control policy is adapted on line. The obtained results illustrate the successful application of such an adaptive algorithm.