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40 results on '"Mujtaba, I. M."'

4. Introduction

Author

Al-Obaidi, Mudhar, primary, Kara-Zaitri, Chakib, additional, and Mujtaba, I. M., additional

Published
2020
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12. Reduction of Energy Consumption of Brackish Water Reverse Osmosis Desalination System Via Model Based Optimisation.

Author

Al-Obaidi, Mudhar A., Alsarayreh, Alanood A., and Mujtaba, I. M.

Subjects
ENERGY consumption, REVERSE osmosis, KEY performance indicators (Management), PERFORMANCE evaluation
Abstract

Reverse Osmosis (RO) process is being engaged to yield fresh water from brackish water sources. However, the RO process is characterized by its high specific energy consumption (SEC) owing to high-pressure pumps. The current study focuses on reducing the SEC of the brackish water RO desalination plant using model-based optimization practice. The inlet conditions of RO process such as the feed pressure, flow rate (individual membrane module and total plant) and temperature, have a substantial influence on the performance indicators namely, water productivity, product concentration and SEC. Therefore, the optimisation of this study has been directed to determine optimal inlet conditions within feasible limits to minimise SEC. Arab Potash Company (APC) brackish water RO desalination plant has been considered as the case study. The optimal inlet conditions have resulted in a significant energy saving of 27.97% depending on the set of decision variables being considered at a fixed brackish water feed concentration. [ABSTRACT FROM AUTHOR]

Published
2023
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24. Simulation of full‐scale reverse osmosis filtration system for the removal of N‐nitrosodimethylamine from wastewater.

Author

Al‐Obaidi, M. A., Kara‐Zaïtri, C., and Mujtaba, I. M.

Subjects
REVERSE osmosis, WASTEWATER treatment, MATHEMATICAL models, DIMETHYLNITROSAMINE, SIMULATION methods & models
Abstract

Abstract: Reverse osmosis (RO) is becoming one of the most promising technologies used in wastewater treatment because it offers high rate of contaminant rejection and lower energy consumption in comparison with other thermal treatment processes. Earlier research by the same authors in respect of a distributed 1‐dimensional mathematical model for a single spiral‐wound RO membrane module based on the solution–diffusion model has been used in this paper to simulate the rejection of N‐nitrosodimethylamine (NDMA) from wastewater in a series of 7 RO elements full‐scale treatment plant. First, the applicability of this model has been evaluated using a simulation study, and the results have been compared against experimental data gathered from the literature for a given plant. Second, further simulation and analysis studies are carried out to assess the performance of the plant for NDMA rejection and recovery rate under different operating conditions of feed pressure, flow rate, and concentration. For the studied RO configuration, it is concluded that a maximum of 55.1% NDMA rejection can be achieved, which confirms the remaining issue of lower NDMA rejection. [ABSTRACT FROM AUTHOR]

Published
2018
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27. Improvement of Multicomponent Batch Reactive Distillation under Parameter Uncertainty by Inferential State with Model Predictive Control.

Author

Weerachaipichasgul, W., Kittisupakorn, P., and Mujtaba, I. M.

Subjects
REACTIVE distillation, PREDICTIVE control systems, OBSERVABILITY (Control theory), KALMAN filtering, ESTIMATION theory, MATHEMATICAL models
Abstract

Batch reactive distillation is aimed at achieving a high purity product, therefore, there is a great deal to find an optimal operating condition and effective control strategy to obtain maximum of the high purity product. An off-line dynamic optimization is first performed with an objective function to provide optimal product composition for the batch reactive distillation: maximum productivity. An inferential state estimator (an extended Kalman filter, EKF) based on simplified mathematical models and on-line temperature measurements, is incorporated to estimate the compositions in the reflux drum and the reboiler. Model Predictive Control (MPC) has been implemented to provide tracking of the desired product compositions subject to simplified model equations. Simulation results demonstrate that the inferential state estimation can provide good estimates of compositions. Therefore, the control performance of the MPC with the inferential state is better than that of PID. In addition, in the presence of unknown/uncertain parameters (forward reaction rate constant), the estimator is still able to provide accurate concentrations. As a result, the MPC with the inferential state is still robust and applicable in real plants. [ABSTRACT FROM AUTHOR]

Published
2013

29. State of the Art Review of Engineering Materials Selection Methods.

Author

Sapuan, S. M., Mujtaba, I. M., and Wright, C. S.

Subjects
*ENGINEERING design, *MATERIALS, *DATABASES, *ARTIFICIAL intelligence, *COMPUTER-aided design
Abstract

In this paper, a review of materials selection methods is presented. It initially discusses the importance of materials selection in various fields of scientific study particularly in engineering design. Various tools and methods for the selection of materials are reviewed. These include materials handbook, materials data-bases, materials selection charts, artificial intelligence systems, and other computer-aided materials selection systems. [ABSTRACT FROM AUTHOR]

Published
2009
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30. Efficient Optimization of Batch Distillation with Chemical Reaction Using Polynomial Curve Fitting Techniques

Author

Mujtaba, I. M. and Macchietto, S.

Abstract

A computationally efficient framework is presented for dynamic optimization of batch distillation where chemical reaction and separation take place simultaneously. An objective to maximize the conversion of the limiting reactant dynamic optimization problem (maximum conversion problem) is formulated for a representative system, and parametric solutions of the problem are obtained. Polynomial curve fitting techniques are then applied to the results of the dynamic optimization problem. These polynomials are used to formulate a nonlinear algebraic maximum profit problem which can be solved extremely efficiently using a nonlinear optimization solver. This provides an efficient framework which can be used for on-line optimization of batch distillation within scheduling programs for batch processes. The method can also be easily extended to nonreactive batch distillation and to nonconventional batch distillation columns.

Published
1997

34. Simulation of middle vessel batch reactive distillation column: Application to hydrolysis of methyl lactate

Author

Edreder, E. A., Mujtaba, I. M., and Mansour Emtir

Subjects
lcsh:Computer engineering. Computer hardware, lcsh:TP155-156, lcsh:TK7885-7895, lcsh:Chemical engineering
Abstract

The middle vessel column (MVC) is a combination of a batch rectifier (conventional column) and a batch stripper (inverted column). Therefore it is possible to obtain a light and a heavy fraction simultaneously from the top and the bottom of the column while an intermediate fraction may also be recovered in the middle vessel. Several researchers in the past have proposed the esterification of lactic acid (impure) with alcohol to obtain lactate ester which is then separated by distillation. To the best of our knowledge, simulation of middle vessel batch reactive distillation column for hydrolysis system has not yet been explored. In this work, the hydrolysis reaction of methyl lactate to produce lactic acid (LA) is carried out in a middle vessel column with fixed batch time while control variables are treated as a piecewise constant reflux ratio (multiple time intervals) and a single reboil ratio. For MVC, the LA being the heaviest in the reaction mixture, reflux and reboil ratios policy plays an important role to achieve high purity of LA.

35. THE USE OF SIMULINK BLOCK DIAGRAM TO SOLVE MATHEMATICAL MODELS AND CONTROL EQUATIONS

Author

Ghasem, N. M.; Department of Chemical Engineering University of Malaya, 50603 Kuala Lumpur, Malaysia, School of Engineering, Design and Technology, University of Bradford, Bradford BD7 1DP, UK, Hussain, M. A.; Department of Chemical Engineering University of Malaya, 50603 Kuala Lumpur, Malaysia, School of Engineering, Design and Technology, University of Bradford, Bradford BD7 1DP, UK, Mujtaba, I. M.; Department of Chemical Engineering University of Malaya, 50603 Kuala Lumpur, Malaysia, School of Engineering, Design and Technology, University of Bradford, Bradford BD7 1DP, UK, Ghasem, N. M.; Department of Chemical Engineering University of Malaya, 50603 Kuala Lumpur, Malaysia, School of Engineering, Design and Technology, University of Bradford, Bradford BD7 1DP, UK, Hussain, M. A.; Department of Chemical Engineering University of Malaya, 50603 Kuala Lumpur, Malaysia, School of Engineering, Design and Technology, University of Bradford, Bradford BD7 1DP, UK, and Mujtaba, I. M.; Department of Chemical Engineering University of Malaya, 50603 Kuala Lumpur, Malaysia, School of Engineering, Design and Technology, University of Bradford, Bradford BD7 1DP, UK

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