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Development of molecular distillation based simulation and optimization of refined palm oil process based on response surface methodology

Yes / The deodorization of the refined palm oil process is simulated here using ASPEN HYSYS.
In the absence of a library molecular distillation (MD) process in ASPEN HYSYS, first, a single flash
vessel is considered to represent a falling film MD process which is simulated for a binary system
taken from the literature and the model predictions are compared with the published work based
on ASPEN PLUS and DISMOL. Second, the developed MD process is extended to simulate the
deodorization process. Parameter estimation technique is used to estimate the Antoine’s parameters
based on literature data to calculate the pure component vapor pressure. The model predictions
are then validated against the patented results of refining edible oil rich in natural carotenes and
vitamin E and simulation results were found to be in good agreement, within a 2% error of the
patented results. Third, Response Surface Methodology (RSM) is employed to develop non-linear
second-order polynomial equations based model for the deodorization process and the effects of
various operating parameters on the performance of the process are studied. Finally, an optimization
framework is developed to maximize the concentration of beta-carotene, tocopherol and free fatty
acid while optimizing the feed flow rate, temperature and pressure subject to process constrains.
The optimum results of feed flow rate, temperature, and pressure were determined as 1291 kg/h,
147 C and 0.0007 kPa respectively, and the concentration responses of beta- carotene, tocopherol and
free fatty acid were found to be 0.000575, 0.000937 and 0.999840 respectively. / Prince of Songkla University, Songkhla, Thailand for providing financial support (Grant code: PSU2554-022)

Identiferoai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/13023
Date16 July 2017
CreatorsTehlah, N., Kaewpradit, P., Mujtaba, Iqbal
Source SetsBradford Scholars
LanguageEnglish
Detected LanguageEnglish
TypeArticle, Published version
Rights© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0)., CC-BY

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