The aim of this paper is to present an artificial neural network (ANN) controller trained on a historical data set that covers a wide operating range of the fundamental parameters that affect the demulsifier dosage in a crude oil desalting process. The designed controller was tested and implemented on-line in a gas-oil separation plant. The results indicate that the current control strategy overinjects chemical demulsifier into the desalting process whereas the proposed ANN controller predicts a lower demulsifier dosage while keeping the salt content within its specification targets. Since an on-line salt analyzer is not available in the desalting plant, an ANN based on historical measurements of the salt content in the desalting process was also developed. The results show that the predictions made by this ANN controller can be used as an on-line strategy to predict and control the salt concentration in the treated oil.
Cite this article as: Ali Alshehri and Zhiping Lai, Attainability and minimum energy of multiple-stage cascade membrane Systems, Journal of Membrane Science, http://dx.doi.org/10.1016/j.memsci. 2015.08.020 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ABSTRACTProcess design and simulation of multi-stage membrane systems have been widely studied in many gas separation systems. However, general guidelines have not been developed yet for the attainability and the minimum energy consumption of a multi-stage membrane system. Such information is important for conceptual process design and thus it is the topic of this work. Using a well-mixed membrane model, it was determined that the attainability curve of multi-stage systems is defined by the pressure ratio and membrane selectivity. Using the constant recycle ratio scheme, the recycle ratio can shift the attainability behavior between single-stage and multistage membrane systems. When the recycle ratio is zero, all of the multi-stage membrane processes will decay to a single-stage membrane process. When the recycle ratio approaches infinity, the required selectivity and pressure ratio reach their absolute minimum values, which have a simple relationship with that of a single-stage membrane process, as follows:, where n is the number of stages. The minimum energy consumption of a multi-stage membrane process is primarily determined by the membrane selectivity and recycle ratio. A low recycle ratio can significantly reduce the required membrane selectivity without substantial energy penalty. The energy envelope curve can provide a guideline from an energy perspective to determine the minimum required membrane selectivity in membrane process designs to compete with conventional separation processes, such as distillation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.