Development of a detailed reaction network for industrial upgrading of heavy reformates to xylenes using differential evolution technique

Kinetics of Heavy Reformate Conversion to Xylenes over MCM-41 on Zeolite Beta Composite Catalyst

Commercial heavy reformate is converted over MCM-41 on zeolite beta composite catalyst to produce mixed xylenes in a fluidized-bed batch reactor. The heavy reformate feedstock contains 67.4 wt.% trimethyl benzenes (TMBs) and 31.1 wt.% methyl ethyl benzenes (MEBs). The experiments were carried out at 300, 350 and 400 °C, while the reaction times were varied between 5 and 20 s. The conversion of MEBs was more than two times the conversion of TMBs. The selectivity to xylenes was quite high (60–65 wt.%) but changed very little with reaction time or temperature. A kinetic model was developed using a five-reaction network. The product composition obtained from the estimated kinetic parameters closely matches the experimental results, which confirms the validity of the assumptions made for kinetic modeling. The trend in the apparent activation energies of the reactions was in accordance with the relative size of the reactant molecules, and the lowest activation energy was for the transalkylation of TMBs with toluene to produce xylenes.

A novel algorithm with differential evolution and coral reef optimization for extreme learning machine training

Extreme learning machine (ELM) is a novel and fast learning method to train single layer feed-forward networks. However due to the demand for larger number of hidden neurons, the prediction speed of ELM is not fast enough. An evolutionary based ELM with differential evolution (DE) has been proposed to reduce the prediction time of original ELM. But it may still get stuck at local optima. In this paper, a novel algorithm hybridizing DE and metaheuristic coral reef optimization (CRO), which is called differential evolution coral reef optimization (DECRO), is proposed to balance the explorative power and exploitive power to reach better performance. The thought and the implement of DECRO algorithm are discussed in this article with detail. DE, CRO and DECRO are applied to ELM training respectively. Experimental results show that DECRO-ELM can reduce the prediction time of original ELM, and obtain better performance for training ELM than both DE and CRO.

Effect of zeolite pore structure on the diffusion and catalytic behaviors in the transalkylation of toluene with 1,2,4-trimethylbenzene

The effect of zeolite pore structure on catalytic properties in the transalkylation of toluene with 1,2,4-trimethylbenzene is investigated by studying the diffusion process and reaction mechanism.