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Reaction Kinetics, Mechanisms and Catalysis

, Volume 126, Issue 1, pp 83–102 | Cite as

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

  • Mohammad GhashghaeeEmail author
Article
  • 34 Downloads

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.

Keywords

Petroleum residue Delayed coking Correlation Pyrolysis Fuel oil 

List of symbols

a, b, …, k

Correlation constants (–)

API

API gravity (°)

CCR

Conradson carbon residue (wt%)

CFR

Ratio of total feed (including recycle) to fresh feed (–)

d

Density (g/cm3)

ESS

Error sum of squares (–)

G

Gas yield (wt%)

GO

Total gas oil yield (wt%)

HGO

Yield of heavy gas oil (350+ °C) (wt%)

L

Liquid yield (wt%)

LGO

Yield of light gas oil (wt%)

MAD

Mean absolute deviation (–)

N

Naphtha (gasoline) yield (wt%)

P

Pressure (bar)

PRESS

Prediction error sum of squares (–)

R2

Coefficient of multiple determination (–)

\(R_{\text{adj}}^{ 2}\)

Adjusted coefficient of multiple determination (–)

\(R_{\text{CV}}^{2}\)

Predicted squared correlation coefficient (–)

RSS

Regression sum of squares (–)

S

Sulfur content (wt%)

SG

Specific gravity (–)

Sum

Summation of the estimated yields (–)

t

Reaction time or space time (min)

T

Temperature (°C)

TSS

Total sum of squares (–)

WAPE

Weighted absolute percentage error (%)

xi

Independent variable (–)

y

Response dependent variable (–)

Greek letters

γ

Parameter in the recycle term (–)

φ

Recycle term (–)

Subscripts

est

Estimated

ext

External

F

Feed

G

Gaseous product

GO

Gas oil

L

Liquid product

obs

Observed

pred

Predicted

tr

Training

Notes

Acknowledgements

The author appreciates helpful discussions with Ms. Samira Shirvani.

Funding

Iran National Science Foundation (INSF) under grant 94016123.

Compliance with ethical standards

Conflict of interest

The author has no conflict of interest to declare.

Supplementary material

11144_2018_1467_MOESM1_ESM.pdf (1 mb)
Supplementary material 1 (PDF 1028 kb)

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Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2018

Authors and Affiliations

  1. 1.Faculty of PetrochemicalsIran Polymer and Petrochemical InstituteTehranIran

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