A new cryogenic air separation process with flash separator is developed. A flash separator is added to the conventional double-column cryogenic air separation process. The flash separator is used to replace the turbine required to recover a portion of the energy in the double-column air separation process. The flash separator served dual purposes of throttling and separation. Both the conventional and the new processes are simulated using Aspen Plus version 11.1 the model air flow rate and compositions are taken as 50000 Nm3/h of air at standard conditions of 1 atm and 25°C and feed composition of 79.1% N2 and 20.9% O2. The new process decreases the energy consumption and increases the productivity.
This work aims to study the behavior of fluid mixtures in the dividing wall column, particularly from a controllability point of view. It covers the aspects of design, modeling, and control. A ternary mixture of benzene, toluene, and o-xylene (BTX) is selected as a case study. A controllability analysis for determining and screening the candidate control combinations of the manipulated variables is carried out with the aid of a linearized model using the concept of relative gain array (RGA). The manipulated variables are the reflux (L), the distillate (D), the side stream (S), the bottom (B) and the boilup (V). Based on RGA criterion, two of the candidate combinations are selected to control the column due to the low interaction between control loops. In each combination the manipulated variables are used to control the top level, the bottom level, the top composition, the middle composition and the bottom composition. Finally, the performance of these two combinations is examined and found to be successful in resisting the disturbances.
Study of dairy products is of great interest to the daily consumer . This research studied the total count of bacteria and the identification of the Escherichia coli (E.coli) bacteria of ready for sale and consumption white cheese.Three samples of locally produced cheese were collected from market in Khartoum at different dates and stored in polypropylene (PP) packaging at temperature of 4oC. The different samples were then subjected to laboratory tests to determine the total bacterial colonies and hence the total count of bacteria and E.coli in white cheese.The quality of white cheese including chemical and microbial characteristics which are affected by several factors were studied. The average bacterial colonies for cheese showed differences at two different dilutions (10-4and 10-5) of the Agar medium used. The average numbers of the bacterial colonies for the three samples were 15.54, 11.74 and 9.79. The biochemical reaction of the isolated bacteria from the three samples of white cheese showed no E.coli presence, gram negative bacteria, however, was found to be present.
A dynamic mathematical model of batch distillation columns is formulated using four basic assumptions: binary separation, negligible vapour holdup, constant pressure and constant molar flows. Simulations performed in the modelling tool MATLAB, proved that the model gives satisfactory description of the process behaviour. Simulations studies were then used to apply the theory of self-optimising control to batch distillation columns, in order to provide a systematic procedure for the selection of controlled variables based on operational economics. It was found that the distillate and boilup flows have good self-optimising properties. The study has also shown the unsuitability of the reflux ratio (Rin) and reflux return (LT) to self-optimising control due to their sensitivity to disturbances in batch distillation of the system.
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.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.