Activity and Stability of Platinum Reforming Catalysts.Computer Evaluation and Prediction

Кравцов, А. В.; Иванчина, Э. Д.; Averin, S. N.; Федоров, А. А.; Krupenya, L. V.; Poluboyartsev, D. S.

doi:10.1023/b:cafo.0000031900.43317.7f

Cited by 5 publications

(3 citation statements)

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“…As a result, accumulation of unsaturated intermediate products of compaction occurs. However, the solution of very important industrial problem -how to find desired catalyst -is based on this contradiction [7].…”

Section: Fig2mentioning

confidence: 99%

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Analysis of Pressure Reducing Effectiveness in the Reforming Industrial Unit with Mathematical Modelling Method Using

Yakupova

Chernyakova

Koksharov³

2016

MATEC Web Conf.

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Section: Fig2mentioning

confidence: 99%

“…Petroleum fraction in the range of 85-180°С is being used as raw material. This complex mixture consists of hydrocarbon molecules with 5-12 carbon atoms, mainly including paraffins, olefins, naphthenes, and aromatics [1][2][3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Pressure Reducing Effectiveness in the Reforming Industrial Unit with Mathematical Modelling Method Using

Yakupova

Chernyakova

Koksharov³

2016

MATEC Web Conf.

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“…As shown in this figure, the catalyst lost about 23 percent of its activity at the end of cycle (day 919). According to the works of Kravtsov [34], the optimum relative activity of a commercial Pt-Re/Al2O3 reforming In order to examine results, a comparison between the measured and predicted RON are shown in Figure 7. From this parity plot, it is completely evident that DANN is capable of predicting the RON of gasoline with acceptable precision.…”

Section: Naphtha Catalytic Reforming Modelmentioning

confidence: 99%

Optimizing an Industrial Scale Naphtha Catalytic Reforming Plant Using a Hybrid Artificial Neural Network and Genetic Algorithm Technique

Sadighi¹,

Mohaddecy²,

Norouzian

2015

Bull. Chem. React. Eng. Catal.

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In this paper, a hybrid model for estimating the activity of a commercial Pt-Re/Al2O3 catalyst in an industrial scale heavy naphtha catalytic-reforming unit (CRU) is presented. This model is also capable of predicting research octane number (RON) and yield of gasoline. In the proposed model, called DANN, the decay function of heterogeneous catalysts is combined with a recurrent-layer artificial neural network. During a life cycle (919 days), fifty-eight points are selected for building and training the DANN (60%), nineteen data points for testing (20%), and the remained ones for validating steps. Results show that DANN can acceptably estimate the activity of catalyst during its life in consideration of all process variables. Moreover, it is confirmed that the proposed model is capable of predicting RON and yield of gasoline for unseen (validating) data with AAD% (average absolute deviation) of 0.272% and 0.755%, respectively. After validating the model, the octane barrel level (OCB) of the plant is maximized by manipulating the inlet temperature of reactors, and hydrogen to hydrocarbon molar ratio whilst all process limitations are taken into account. During a complete life cycle results show that the decision variables, generated by the optimization program, can increase the RON, process yield and OCB of CRU to about 1.15%, 3.21%, and 4.56%, respectively.

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Complex modeling system for optimization of compounding process in gasoline pool to produce high-octane finished gasoline fuel

Иванчина

Kirgina

Chekantsev

et al. 2015

Chemical Engineering Journal

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Activity and Stability of Platinum Reforming Catalysts.Computer Evaluation and Prediction

Cited by 5 publications

References 0 publications

Analysis of Pressure Reducing Effectiveness in the Reforming Industrial Unit with Mathematical Modelling Method Using

Analysis of Pressure Reducing Effectiveness in the Reforming Industrial Unit with Mathematical Modelling Method Using

Optimizing an Industrial Scale Naphtha Catalytic Reforming Plant Using a Hybrid Artificial Neural Network and Genetic Algorithm Technique

Complex modeling system for optimization of compounding process in gasoline pool to produce high-octane finished gasoline fuel

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