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Fouling modeling in crude oil heat exchangers is of great importance industrially. Current approaches use empirical or semiempirical approaches, where fouling rate models are necessary. A series of parameters need to be determined, which directly depend on the nature and type of crude oil. These parameters can be estimated either by using laboratory experiments or, in principle, by measured process data. This work focuses on the estimation of fouling rate model parameters using measured data. An optimization-based data reconciliation approach, which accounts for random and gross errors, is integrated with a parameter-fitting algorithm. The methodology is tested in a case study, where a multipass heat exchanger is simulated. The effects of measurement error and fouling deposition on both sides are addressed. The fouling resistance is predicted and compared with the simulated data, showing good agreement as well as providing evidence for a successful separation of fouling resistances on both sides of a heat...

Estimation of Fouling Model Parameters for Shell Side and Tube Side of Crude Oil Heat Exchangers Using Data Reconciliation and Parameter Estimation