AbstractFouling is a long-standing technical and economical challenge for processing industries. At the very least, surface fouling reduces thermal efficiency, increases usage of fuel, and increases the emissions of carbon dioxide. There are many existing techniques for dealing with the fouling problem. On the other hand, there is limited information about the fouling techniques, and limited ways of predicting the crude oil fouling phenomena mathematically.
There are lots of research suggesting different techniques and mechanisms that provide good explanation to the fouling phenomena. However, these mechanisms have their limitations such as limited amount of data to support these mechanisms. A numerical model which used a combination of fouling threshold modeling and computational fluid dynamics, were used in this thesis to predict the fouling correctly. The fouling threshold model combines both fouling deposition and removal factors where the deposition depends on the operation condition and fluid properties while the removal depends on system shear rate.
A huge task was conducted before model application which was crude oil and asphaltenes foulant properties estimation as function of temperature and pressure. Based on the accuracy of properties estimation the model can succeed.
The model was tested using two sets of data. The first set contained fouling rates from the Exxon mobile works of Ebert and Panchal. The second set contained fouling deposition thickness and heat exchanger cleaning schedule from a local refinery in the state of Kuwait. The results showed that the combined numerical model explained the fouling satisfactory in terms of fouling thickness and fouling rates hence it was used to reproduce these data sets successfully as well as providing extra information about the temperature and velocity profile, and most importantly fouling thickness profiles along the length of tube side in the heat exchanger.
It remains necessary for research and test experiments to be carried out so that mathematical models of the fouling process can be formulated. In this way, it is possible to find out how fouling affects an individual heat exchanger and hence the network in which it resides.
|Date of Award||24 Mar 2021|
|Supervisor||Barry Crittenden (Supervisor), Semali Perera (Supervisor) & John Chew (Supervisor)|
- pre-heat train
- heat exchangers
- computational fluid dynamics