Integrated Batch Reactive Distillation Column Configurations for Optimal Synthesis of Methyl Lactate

YesAlthough batch reactive distillation process outperforms traditional reactor-distillation processes due to simultaneous reaction and separation of products for many reaction systems, synthesis of Methyl lactate (ML) through esterification of lactic acid (LA) with methanol in such process is very challenging due to difficulty of keeping the reactants together when one of the reactants (in this case methanol) has the lowest boiling point than the reaction products. To overcome this challenge, two novel reactive distillation column configurations are proposed in this work and are investigated in detail. These are: (1) integrated conventional batch distillation column (i-CBD) with recycled methanol and (2) integrated semi-batch and conventional batch distillation columns (i-SBD) with methanol recovery and recycle. Performances of each of these configurations are evaluated in terms of profitability for a defined separation task. In i-SBD column, an additional constraint is included to avoid overflow of the reboiler due to continuous feeding of methanol into the reboiler as the reboiler is initially charged to its maximum capacity. This study clearly indicates that both integrated column configurations outperform the traditional column configurations (batch or semi-batch) in terms of batch time, energy consumption, conversion of LA to ML, and the achievable profit

Maximization of propylene in an industrial FCC unit

YesThe FCC riser cracks gas oil into useful fuels such as gasoline, diesel and some lighter products such as ethylene and propylene, which are major building blocks for the polyethylene and polypropylene production. The production objective of the riser is usually the maximization of gasoline and diesel, but it can also be to maximize propylene. The optimization and parameter estimation of a six-lumped catalytic cracking reaction of gas oil in FCC is carried out to maximize the yield of propylene using an optimisation framework developed in gPROMS software 5.0 by optimizing mass flow rates and temperatures of catalyst and gas oil. The optimal values of 290.8 kg/s mass flow rate of catalyst and 53.4 kg/s mass flow rate of gas oil were obtained as propylene yield is maximized to give 8.95 wt%. When compared with the base case simulation value of 4.59 wt% propylene yield, the maximized propylene yield is increased by 95%

Modelling and simulation of MSF desalination process using gPROMS and neural network based physical property correlation

NoMulti Stage Flash (MSF) desalination plants are a sustainable source of fresh water in arid regions. Modelling plays an important role in simulation, optimisation and control of MSF processes. In this work an MSF process model is developed, using gPROMS modelling tool. Accurate estimation of Temperature Elevation (TE) due to salinity is important in developing reliable process model. Here, instead of using empirical correlations from literature, a Neural Network based correlation is used to determine the TE. This correlation is embedded in the gPROMS based process model. We obtained a good agreement between the results reported by Rosso et. al. (1996) and those predicted by our model. Effects of seawater temperature (Tseawater) and steam temperature (Tsteam) on the performance of the MSF process are also studied and reported

Multi-model based process condition monitoring of offshore oil and gas production process

10.1016/j.cherd.2009.10.013Chemical Engineering Research and Design885-6572-591CERD