Modeling and simulation of a liquid extraction column with structured packing

Morales, Carlos; Elman, Hinda; Pérez, A. Ramírez

doi:10.1016/j.compchemeng.2007.02.005

Cited by 10 publications

(6 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the simulation results reveal a significant overestimation of the concentration gradient in the transient region, which agrees with the findings for other types of extraction columns different to this work. 8 One reason for this deviation could be the simplified modeling assumptions regarding the time resolution of the fluid dynamics. Nonetheless, the model accurately predicts the order of magnitude of the timespan of the transient range depending on the chemical system and the considered outlet phase.…”

Section: Dynamic Simulation Of the Transient Range Between Two Steady...mentioning

confidence: 99%

“…As presented in the case study of Section , the simulation represents the steady state with the sufficient accuracy of the final selected models. However, the simulation results reveal a significant overestimation of the concentration gradient in the transient region, which agrees with the findings for other types of extraction columns different to this work . One reason for this deviation could be the simplified modeling assumptions regarding the time resolution of the fluid dynamics.…”

Section: Modeling the Mass Transfer Of An Extraction Columnmentioning

confidence: 99%

“…1D rate-based models provide a more refined approach by incorporating the evaluation of fluid dynamics along the column height, enabling the accurate prediction of concentration profiles. 7 Morales et al 8 coalescence and breakage. 9−11 Here, Jaradat et al analyzed two different standard test systems (STSs) for validating their model for a pulsed structured packed extraction column, using experimental hold-up, mean droplet diameter, and masstransfer profile results.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Dynamic Modeling of a Liquid–Liquid Extraction Column─An Industrial Approach

Brockkötter,

Hammacher,

Becker

et al. 2024

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

Model-based evaluation and optimization of technical extraction columns are necessary when the product specifications of a technical system (TS) are not reached. However, state-of-the-art models are parameterized and validated using standard test systems (STSs) of highest purity. In contrast to that, TSs are characterized by an incomplete list of components, impurities, and batch-depending physicochemical properties. This divergence between STSs and TSs results in a lack of trust regarding developed model-based approaches for extraction columns. In this paper, an experimental approach for parameterization of a one-dimensional rate-based model is presented. The model is parameterized for a STS leading to a weighted absolute percentage error, WAPE w Acetone,out , of 8.53%. The parameter set is then used for a TS leading to a WAPE w TC,out of 17.43%. The distribution coefficient is the most sensitive model parameter as a change in the distribution coefficient of 3% yields a relative change of WAPE w TC,out by 19.39%. Varying the fluid dynamics parameters Sauter diameter and hold-up by 20%, the relative change in WAPE w TC,out is 44.03% and only 5.48%, respectively. A recommendation for minimal instrumentation for lab-scale extraction columns and technical large-scale columns is given.

show abstract

Section: Dynamic Simulation Of the Transient Range Between Two Steady...mentioning

confidence: 99%

Section: Modeling the Mass Transfer Of An Extraction Columnmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Dynamic Modeling of a Liquid–Liquid Extraction Column─An Industrial Approach

Brockkötter,

Hammacher,

Becker

et al. 2024

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

show abstract

“…In the past few decades, extraction columns were designed based on the assumption that each phase follows the ideal plug flow model. However, various studies have been conducted to estimate the deviation of nonideality from ideal plug flow conditions caused by liquid circulation, eddies, turbulence, and the velocity profile. , These parameters were combined into a single parameter based on Fick’s law, and it is expressed as the axial dispersion model . Taylor first studied the axial dispersion model for turbulent mass transfer through a pipe.…”

Section: Introductionmentioning

confidence: 99%

Mixing Characteristics of a Liquid–Liquid Dispersion in a Jet-Driven Mixing Column: Developed for the Separation of Organic Pollutants

Sangtam

Prakash

Majumder

2021

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

The present work focuses on studying the degree of liquid–liquid axial dispersion in a jet-driven mixing column. The online conductivity measurement was performed to study the residence time distribution. The effects of the jet velocity and dispersed phase volume on mixing characteristics were studied. The axial dispersion coefficient range was found to be 25.6 to 106 cm2/s. A general correlation is developed to predict the axial dispersion coefficient based on various operating variables. A mechanistic model is proposed to interpret dispersion due to the turbulence and phase circulation inside the jet-driven mixing column. Based on the velocity distribution model, the velocity characteristic factor and the dispersion factor of drop motion were also enunciated. The present study may be helpful for further understanding a two-phase system in industrial applications, especially in liquid–liquid extraction.

show abstract

“…The spray column is the simplest column among the liquid–liquid extraction columns . Packed columns are similar, in principle, to spray columns but are more efficient because packing elements serve to decrease axial mixing, reduce back‐mixing of the continuous phase, provide tortuous pathways for the two liquids, and can also cause distortions and breakup of the drops.…”

Section: Introductionmentioning

confidence: 99%

Spray and packed liquid–liquid extraction columns: drop size and dispersed phase mass transfer

Khorshidi

Abolghasemi

Khakpay

et al. 2013

Asia-Pacific J Chem Eng

View full text Add to dashboard Cite

The effects of holdup on Sauter mean drop diameter, D 32 , and dispersed phase mass transfer coefficient have been studied in the spray and packed extraction columns. For both columns, two well-defined regions for the dependence of D 32 on holdup were observed. D 32 increased and decreased with an increase in holdup at low and high levels of holdup, respectively. Changes in dispersed phase mass transfer coefficient against holdup were shown to be similar to D 32 for both columns. Moreover, empirical correlations have been derived to predict D 32 and dispersed phase mass transfer coefficient for both columns. It has been shown that the derived correlations are in a good agreement with the experimental data.

show abstract

Modeling and simulation of a liquid extraction column with structured packing

Cited by 10 publications

References 9 publications

Dynamic Modeling of a Liquid–Liquid Extraction Column─An Industrial Approach

Dynamic Modeling of a Liquid–Liquid Extraction Column─An Industrial Approach

Mixing Characteristics of a Liquid–Liquid Dispersion in a Jet-Driven Mixing Column: Developed for the Separation of Organic Pollutants

Spray and packed liquid–liquid extraction columns: drop size and dispersed phase mass transfer

Contact Info

Product

Resources

About