S.R. Abd Shukor

Integrated CFD simulation of concentration polarization in narrow membrane channel

Numerous analyses on the mass transfer phenomena and hydrodynamics for the fluid adjacent to the membrane have been studied and visualized by computational fluid dynamics (CFD) mathematical modeling and simulation. The availability of CFD simulation study to reveal the concentration polarization profile in the membrane channel, which considering hydrodynamics and membrane transport properties is found to be limited. The main goal of this paper is targeted to the utilization of CFD simulation using commercial CFD package FLUENT to predict the concentration polarization profile, mass transfer coefficient and wall shear stress under different types of conditions in the empty narrow membrane channel. The permeation conditions such as permeation flux and mass fraction have been taken into account in the solution of the governing equations. Simulation results show that the concentration polarization phenomena can be reduced by increasing feed Reynolds number. The decrease of wall shear stress also contributes to the formation of the concentration polarization layer along the membrane surface. The simulated results were validated and compared with the literature data, showing a satisfactory agreement.

Sustainable biocatalytic synthesis of L-homophenylalanine as pharmaceutical drug precursor

Over the past decade, L-homophenylalanine is extensively used in the pharmaceutical industry as a precursor for production of angiotensin-converting enzyme (ACE) inhibitor, which possesses significant clinical application in the management of hypertension and congestive heart failure (CHF). A number of chemical methods have been reported thus far for the synthesis of L-homophenylalanine. However, chemical methods generally suffer from process complexity, high cost, and environmental pollution. On the other hand, enantiomerically pure L-homophenylalanine can be obtained elegantly and efficiently by employing biocatalytic methods, where it appears to be the most attractive process in terms of potential industrial applications, green chemistry and sustainability. Herein we review the biocatalytic synthesis of vital L-homophenylalanine as potentially useful intermediate in the production of pharmaceutical drugs in environmentally friendly conditions, using membrane bioreactor for sustainable biotransformation process. One envisages the future prospects of developing an integrated membrane bioreactor system with improved performance for L-homophenylalanine production.

Development of Process Inverse Neural Network Model to Determine the Required Alum Dosage at Segama Water Treatment Plant Sabah, Malaysia

Abstract The determination of the optimal coagulant dosage in the coagulation process of a water treatment plant (WTP) is very essential to produce satisfactory treated water quality and to maintain economic plant operation such as reducing manpower and expensive chemical costs. Failing to do this will also reduce the efficiency in sedimentation and filtration process in the treatment plant. Traditionally, jar test is used to determine the optimum coagulant dosage. However, this method is expensive, time-consuming and does not enable responses to changes in raw water quality in real time. Modeling such as neural network can be used to overcome these limitations. In this work, an inverse neural network model is developed to predict the optimum coagulant dosage in Segama WTP in Lahad Datu, Sabah, Malaysia. Real data from the WTP was obtained along with extensive data analysis and preparation, significant input-output selection and consideration of important raw and treated water lag parameters were carried out. The modeling results shown that the prediction capabilities are improving with the consideration of appropriate input parameters. Neural network models with different network architectures, including single and two hidden layers were developed and the optimum network architecture obtained was [11-27-9-1]. This model performed very well over the range of data used for training, with r-value of 0.95, mean square error (MSE) of 0.0019 and mean absolute error (MAE) of 0.024 mg/l when applied on the testing data set. Hence, the proposed techniques can significantly improve and have a great potential of replacing the conventional method of jar test due to its advantages; quick responsive tools, economical operating cost and its ability to be applied in real time process.

Nonlinear Model Predictive Control of a Distillation Column Using NARX Model

Abstract Distillation column is an important process unit in petroleum refining and chemical industries, and needs to be controlled close to optimum operating conditions because of economic incentives. Nonlinear model based control (NMPC) scheme is one of the best options to be explored for proper control of distillation columns. In this work, NMPC scheme using sigmoidnet based nonlinear autoregressive with exogenous inputs (NARX) model has been developed to control distillation column The Unscented Kalman Filter (UKF) was used to estimate the state variables in NMPC and the nonlinear programming (NLP) problem was solved using sequential quadratic programming (SQP) method. The closed loop control studies have indicated that the NARX NMPC performed well in disturbance rejection and set point tracking.

INVESTIGATING MEMBRANE MORPHOLOGY AND QUANTITY OF IMMOBILIZED PROTEIN FOR THE DEVELOPMENT OF LATERAL FLOW IMMUNOASSAY

This study was aimed at gaining a quantitative understanding of the effect of protein quantity and membrane pore structure on protein immobilization. The concentration of immobilized protein was measured by staining with Ponceau S and measuring its color intensity. In this study, both membrane morphology and the quantity of deposited protein significantly influenced the quantity of protein immobilization on the membrane surface. The sharpness and intensity of the red protein spots varied depending on the membrane pore structure, indicating a dependence of protein immobilization on this factor. Membranes with smaller pores resulted in a higher color density, corresponding to enhanced protein immobilization and an increased assay sensitivity level. An increased of immobilized volume has a significant jagged outline on the protein spot but, conversely, no difference in binding capacity.

Optimization of Membrane Formulation and Process Variables via Crossed-Design Concept in Design of Experimental (DOE)

Abstract A mixture-process design methodology, i.e., the crossed design, is proposed for experimental analysis and optimization. Five mixture materials for membrane formulation and two process factors for casting condition were fixed in the design methodology. The study was to generate a regression model for each of the responses, based on the experimental data and analysis variance of the study. Based on the response models, the optimal blend and casting condition were predicted. The highest desirability function, D, which prevailed from the optimization was 0.66. This optimal blend composition of the cast solution and the process condition in crossed design is proven to increase the membrane performance through the high membrane porosity, the high protein binding ability, and the fast lateral wicking rate.