Thorough assessment of delayed coking correlations against literature data: Development of improved alternative models View Full Text


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Article Info

DATE

2019-02

AUTHORS

Mohammad Ghashghaee

ABSTRACT

The predictability of the existing and some improved correlations were evaluated against the available largest dataset for the prediction of the product yields from delayed coking, such as, coke, liquid, gas, gas oil, naphtha, heavy gas oil, liquid sulfur content as well as API vs. CCR. Except for some cases where the relationships of Volk et al. and Castiglioni and the simplistic models of Maples, and Gary–Handwerk predicted somewhat appropriately, the existing models failed in most of the cases. The alternative models contained seven independent variables including three feedstock properties and four operating conditions. Overall, the developed correlations accounted for higher than 86% of the variances. The quality of the regressions followed the order of naphtha < dry gas < distillate < liquid sulfur content < heavy gas oil < coke < gas oil with the maximum correlation coefficient of 96.7%. The weighted absolute percentage errors with the alternative relationships of total gas oil, heavy gas oil, liquid sulfur content, and distillate were smaller than 11.12%, indicating the good predictability of the models. The new models can then be recommended for application over a wide range of operating conditions with various types of heavy fuel oils and petroleum residues. More... »

PAGES

1-20

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http://scigraph.springernature.com/pub.10.1007/s11144-018-1467-0

DOI

http://dx.doi.org/10.1007/s11144-018-1467-0

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54 schema:description The predictability of the existing and some improved correlations were evaluated against the available largest dataset for the prediction of the product yields from delayed coking, such as, coke, liquid, gas, gas oil, naphtha, heavy gas oil, liquid sulfur content as well as API vs. CCR. Except for some cases where the relationships of Volk et al. and Castiglioni and the simplistic models of Maples, and Gary–Handwerk predicted somewhat appropriately, the existing models failed in most of the cases. The alternative models contained seven independent variables including three feedstock properties and four operating conditions. Overall, the developed correlations accounted for higher than 86% of the variances. The quality of the regressions followed the order of naphtha < dry gas < distillate < liquid sulfur content < heavy gas oil < coke < gas oil with the maximum correlation coefficient of 96.7%. The weighted absolute percentage errors with the alternative relationships of total gas oil, heavy gas oil, liquid sulfur content, and distillate were smaller than 11.12%, indicating the good predictability of the models. The new models can then be recommended for application over a wide range of operating conditions with various types of heavy fuel oils and petroleum residues.
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