A Dynamic, Distributed Model of Shell-and-Tube Heat Exchangers Undergoing Crude Oil Fouling

Fouling in refinery preheat trains causes major energy inefficiencies, resulting in increased costs, greenhouse gas emissions, maintenance efforts, and safety hazards. Fouling deposition is not well understood, and current exchanger design and monitoring practices neglect the local effects and dynam...

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Bibliographic Details
Published inIndustrial & engineering chemistry research Vol. 50; no. 8; pp. 4515 - 4533
Main Authors Coletti, Francesco, Macchietto, Sandro
Format Journal Article
LanguageEnglish
Published Washington, DC American Chemical Society 20.04.2011
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Summary:Fouling in refinery preheat trains causes major energy inefficiencies, resulting in increased costs, greenhouse gas emissions, maintenance efforts, and safety hazards. Fouling deposition is not well understood, and current exchanger design and monitoring practices neglect the local effects and dynamics of fouling, in favor of lumped, steady-state, heuristic models (e.g., Tubular Exchanger Manufacturers Association (TEMA) fouling factors). In this paper, a dynamic, distributed model for a multipass shell-and-tube heat exchanger undergoing crude oil fouling is proposed. The model calculates fouling rates as a function of local conditions and time. It accounts for heat exchanger geometry, variation of oil physical properties with temperature, local accumulation of fouling deposits, and their structural change over time (aging). The interaction between fouling growth and fluid dynamics inside the tubes is accounted for by solving a moving boundary problem. Moreover, a procedure to analyze refinery data and support the estimation of a set of model parameters has been established. The model is validated using data from an ExxonMobil refinery and shows excellent agreement (less than 2% error) with primary plant measurements even when it is tested for its predictive capabilities over long periods (i.e., 1 year). It is concluded that the model can be used with confidence to identify and predict the fouling state of exchangers, to assess economic losses due to fouling, to support operating decisions such as planning of cleaning schedules, and to assist in the design and retrofit of heat exchangers.
ISSN:0888-5885
1520-5045
DOI:10.1021/ie901991g