EFFECT OF FRICTION FACTOR CORRELATIONS AND PROPAGATION ERRORS ON DIFFERENTIAL PRESSURE IN A CRUDE OIL FOULING MEASURING RIG
Z. Tajudin+, E.Diaz-Bejarano+, F. Coletti*, S. Macchietto+* and G. F. Hewitt+*
+Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
* Hexxcell Ltd, Imperial College Incubator, Bessemer Building Level 2, Imperial College London, London SW7 2AZ, UK
Corresponding author: email@example.com
Keywords: pilot scale, error of propagations, experiment, validation
In order to detect crude oil fouling experimentally, primary measurements of differential pressure and temperatures must be obtained with high fidelity, accuracy and reproducibility at (or close to) industrial conditions. Information of the thermal and hydraulic effects of fouling can be studied by using robust models to decouple the various phenomena involved. To start with, it is important to have a reliable set of primary measurements in which the robust model could be validated against the experiment data.
A novel pilot scale experimental facility for study of crude oil fouling, High Pressure Oil Rig (HIPOR), was developed and tested with non-fouling oil and crude oil at different operating conditions. The experiments have been carefully designed in order to develop comprehensive and reliable baseline validation for both oils without any fouling deposition. The model, an extension of Hexxcell's model for HiPOR, for the tubular test section with vertical geometries, considers the two dimensional (axial and radial) heat transfer in different domains, boundary conditions and other aspects (for example, heat losses) which are carefully determined.
The objectives of this work are divided into two. First, a predictive model for differential pressure of the HIPOR test section is validated against experimental results for both oils. The model consists three friction factors correlation was used to assist in the analysis and interpretation of the experimental data collected, compared with the variation of flowrate as well as different heat inputs. Second, the errors of propagation which are observed from the validation process have been identified and its sensitivity towards inlet bulk temperature increments quantified.
The validation process shows that both oils show excellent agreement with model predictions for at all ranges of operating conditions and capturing all responses including the transient processes. The best agreement is achieved for different friction factor correlations for each oil. The reported results also show that the deviation between simulation data and measured data due to the errors of propagation starts to increase when the inlet bulk temperature of oil is increased from 80 oC onwards. Furthermore, the errors of propagation have a linear correlation with the temperature increment.
It is concluded that the model of the HIPOR rig for non-fouling and crude oil conditions for differential pressure were successfully validated and error of propagations with temperature effects have been quantified.
This research was partially performed under the UNIHEAT project. The authors wish to acknowledge the Skolkovo Foundation and BP for financial support. ZT wishes to also acknowledge MARA and UniKL for their support and funding. The support of Hexxcell Ltd, through provision of Hexxcell Studio™, is also acknowledged.
S. Macchietto, G.F. Hewitt, F. Coletti, B.D. Crittenden, D.R. Dugwell, A. Galindo, G. Jackson, R. Kandiyoti, S.G. Kazarian, P.F. Luckham, O.K. Matar, M. Millan-Agorio, E.A. Müller, W. Paterson, S.J. Pugh, S.M. Richardson, D.I. Wilson, “Fouling in crude oil preheat trains: a systematic solution to an old problem”, Heat Transfer Engineering, 32, 3, 197-215 (2011).
F. Coletti and S. Macchietto, A dynamic, distributed model of shell-and-tube heat exchangers undergoing crude oil fouling. Ind. Eng. Chem. Res. 50 (8), pp 4515–4533 (2011).
Z. Tajudin, Experiments, Modelling and Validation of Crude Oil Fouling on Large Scale Rig. PhD, Imperial College London, UK – submitted for PhD awards (2015).
Hexxcell Ltd., 2015. Hexxcell Studio. http://www.hexxcell.com.
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