Mitigation and monitoring of fouling is a major concern for the process industries. It is especially important in crude oil refineries. Increase in maintenance and operational costs, higher CO
2 emissions and faster material deterioration represent some of the most harmful consequences of fouling. Fouling deposits create an extra thermal resistance which jeopardises the thermal and hydraulic performance of a heat exchanger network. Previous research has focused on identifying the main variables that set the deposition of unwanted material onto the heat transfer surface. Significant advances have been achieved regarding the chemical basis for fouling [
1,
2]; and several mechanisms have been proposed according to fluid nature and operational conditions [
3]. Each of these mechanisms can be modelled and each of these models can be applied for further prediction, optimisation of cleaning schedules and new designs or retrofit using the concept of fouling threshold [
4]. The fouling threshold is defined as the operational locus relating wall temperature and wall shear stress below which fouling does not occur, or at least can be considered as negligible. If the fouling threshold curve is found for a specific crude oil, operational changes can take place in order to minimise fouling occurrence. The fouling models proposed so far involve adjustable parameters that need to be fitted to experimental data for each sample of crude oil tested. However, experimental tests take a significant amount of time, and laboratory tests cannot be fully extrapolated to field conditions [
5]. An alternative approach is to use the data from the plant itself, allowing the data to be fitted to a single or multiple fouling models, which can be used to improve the network performance and structure. This work proposes a new methodology which allows for fitting a set of fouling model parameters using reconciled operating data. The data needs to be treated before using it for fitting purposes, since measurement error and potential bias need to be mitigated to obtain reliable data. The reconciliation process is addressed as a nonlinear minimisation problem, where the square of the difference between measured and fitted data is optimised using mass and energy balances to constraint the measurement magnitudes. Once the data is reconciled, it can be fitted against a certain fouling model, which is selected depending on the operational conditions and physical properties of the fluid. As a result, the set of model parameters can be obtained and fouling dynamics can be included in operational optimisation based on the concept of fouling threshold [
6], improving the current understanding of fouling deposition and thermal performance of heat exchanger networks. The proposed methodology is applied to a case study, where the simulation of the network, data reconciliation and fitting processes are assessed. Results show that the use of data reconciliation improves the reliability of measurements and the noise included within the data is mitigated, allowing for an accurate fitted process and network outlet conditions prediction. Mitigation and identification of faulty measurements is also achieved, and an analysis of system redundancy and minimum bias magnitude isolation is presented. The methodology can be included in new design and retrofit methods to solve simultaneously the optimisation of cleaning schedules and topological design by accounting fouling dynamics.
[1] A. P. Watkinson, "Chemical reaction fouling of organic fluids," Chemical engineering & technology, vol. 15, pp. 82-90, 1992.
[2] A. Watkinson and D. Wilson, "Chemical reaction fouling: A review," Experimental Thermal and Fluid Science, vol. 14, pp. 361-374, 1997.
[3] N. Epstein, "Thinking about heat transfer fouling: a 5x5 matrix," Heat transfer engineering, vol. 4, pp. 43-56, 1983.
[4] W. Ebert and C. Panchal, "Analysis of Exxon crude-oil-slip stream coking data," Argonne National Lab., IL (United States)1995.
[5] U. Deshannavar, M. Rafeen, M. Ramasamy, and D. Subbarao, "Crude oil fouling: A review," Journal of Applied Sciences, vol. 10, pp. 3167-3174, 2010.
[6] C. Rodriguez and R. Smith, "Optimization of Operating Conditions for Mitigating Fouling in Heat Exchanger Networks," Chemical Engineering Research and Design, vol. 85, pp. 839 - 851, 2007.
