Prediction for CUI in Piping Systems using Fuzzy Logic with Sensitivity Analysis of Corrosion Producing Factors

Abstract

Corrosion under insulation (CUI) is a progressive problem for piping systems in oil and gas industries especially in petrochemical and chemical plants due to its catastrophic disasters and consequently its automatic impact on the environment. To ensure CUI problem should not spark sudden surprise in plants, indeterminate factors that contribute to the deterioration of pipes subject to CUI should be recognized and taken care seriously. Operating temperature, type of environment, insulation type, pipe complexity and insulation condition of the pipes are the key factors that cause significant deterioration of pipes due to CUI. As per its varying nature, CUI is difficult to predict as it remains hidden beneath the insulation and gets growth in an ambiguous and abrupt manner. For such an uncertain and critical situation, fuzzy logic is a good choice to be deal with. Thus, in this study, CUI corrosion rate for insulated carbon steel piping systems has been predicted by fuzzy logic using API 581 data. Predicted CUI corrosion rates obtained by the developed fuzzy logic model are committing quite satisfactory results when comparing with API 581 published CUI corrosion rates. At the end of study, sensitivity analysis (SA) of CUI producing factors has also been performed. SA is showing the role of each CUI producing factor in terms of percentage, having participation for the cause of 1 mm/year CUI in pipes. The predicted CUI corrosion rates and SA will help inspection engineers for setting and delivering the risk-based inspection priority for insulated piping systems at their concerned plants.