(29c) Optimising Chemical Cleaning of Heat Exchangers

Chemical cleaning methods provide a flexible, economic and quick way of restoring heat exchange performance. However, a wrong selection of the cleaning agent and/or duration of the cleaning action can lead to uneconomical decisions. In this paper, a framework integrating condition-based cleaning models that capture kinetics and efficiency of a cleaning action as a function of the characteristics of fouling deposits (e.g. composition, layering, degree of coking) with a predictive maintenance simulator is presented. The approach uses a few parameters, determined in the lab, to predict cleaning performance of given solvents thus providing the field engineer with actionable information on the best method to be used, duration of the cleaning and expected economic benefits. Results are presented using case studies for individual heat exchangers and entire networks.