Modeling of the Flux Decline in a Continuous Ultrafiltration System with Multiblock Partial Least Squares

Klimkiewicz, Anna; Cervera-Padrell, Albert E.; Berg, Frans van den

doi:10.1021/acs.iecr.6b01241

Cited by 5 publications

(1 citation statement)

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“…Another example is the use of the Partial Least Square regression (PLSR) model to study the relationship among membrane characteristics, operating conditions, and membrane performance in terms of permeate flux and membrane rejection towards hesperidin and sugars (glucose, fructose, and sucrose) during the UF of orange press liquor [ 187 ]. PLSR has also been applied to investigate flux decline in a multi-stage ultrafiltration process [ 188 ]. Other authors have used Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) modeling to forecast permeate flux in UF of fruit juices [ 69 ].…”

Section: Theorymentioning

confidence: 99%

Prediction of Permeate Flux in Ultrafiltration Processes: A Review of Modeling Approaches

et al. 2021

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In any membrane filtration, the prediction of permeate flux is critical to calculate the membrane surface required, which is an essential parameter for scaling-up, equipment sizing, and cost determination. For this reason, several models based on phenomenological or theoretical derivation (such as gel-polarization, osmotic pressure, resistance-in-series, and fouling models) and non-phenomenological models have been developed and widely used to describe the limiting phenomena as well as to predict the permeate flux. In general, the development of models or their modifications is done for a particular synthetic model solution and membrane system that shows a good capacity of prediction. However, in more complex matrices, such as fruit juices, those models might not have the same performance. In this context, the present work shows a review of different phenomenological and non-phenomenological models for permeate flux prediction in UF, and a comparison, between selected models, of the permeate flux predictive capacity. Selected models were tested with data from our previous work reported for three fruit juices (bergamot, kiwi, and pomegranate) processed in a cross-flow system for 10 h. The validation of each selected model's capacity of prediction was performed through a robust statistical examination, including a residual analysis. The results obtained, within the statistically validated models, showed that phenomenological models present a high variability of prediction (values of R-square in the range of 75.91–99.78%), Mean Absolute Percentage Error (MAPE) in the range of 3.14–51.69, and Root Mean Square Error (RMSE) in the range of 0.22–2.01 among the investigated juices. The non-phenomenological models showed a great capacity to predict permeate flux with R-squares higher than 97% and lower MAPE (0.25–2.03) and RMSE (3.74–28.91). Even though the estimated parameters have no physical meaning and do not shed light into the fundamental mechanistic principles that govern these processes, these results suggest that non-phenomenological models are a useful tool from a practical point of view to predict the permeate flux, under defined operating conditions, in membrane separation processes. However, the phenomenological models are still a proper tool for scaling-up and for an understanding the UF process.

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Section: Theorymentioning

confidence: 99%