Characteristics and Likelihood Modeling of Corrosion Under Insulation Analyzed By Inspection Data and the Practicability of the Neutron Moisture Meter of Insulation for CUI Screening in Japanese Chemical Plants -Introduction the Results of Iot and Mainten

Corrosion Under Insulation (CUI) is the most common and hazardous degradation phenomenon in aged chemical plant. Many studies have been conducted and some guidelines have been published. But there have been some remaining problems for CUI. One of these problems is more accurate likelihood estimation model for CUI and other is more practicable NDE method for CUI screening.

Ministry of Economy, Trade and Industry, Japan had recognized the importance of CUI problems and decided to start the project in 2016. Asahi Kasei Corporation was chosen the contractor for this project and organized group of 14 chemical companies in Japan Petrochemical Industry Association.

Two subjects have been studied in this project. First subject is to reveal the controlling factors for CUI and to develop the likelihood estimation model for CUI. About 13,600 points and 36 items data were collected from grouped chemical companies and studied statistically.

Second subject is to study the capability of neutron moisture meter for screening method for CUI inspection. The moisture data of insulation measured by neutron moisture meter and CUI depth data at the corresponding location were gathered form grouped companies and were analyzed. About 4,500 points and 44 items data were collected.

Some quantitative characteristics of CUI have been revealed from data analysis. For example, CUI depth distribution of towers is wider than piping and vessels, and the parts of equipment are affecting CUI depth distribution.

Based on these results, the CUI likelihood estimation index named “C” is developed. The correlation between the remaining thicknesses after CUI occurred and C index is high calculated for the gathered piping data. Trial calculation using C index for refining inspection points for CUI is conducted for gathered data, and it is estimated that narrowing down inspection points evaluated by C index is possible without reducing the reliability of inspection.

For the second subject, although the correlation between the moisture level of insulation measured by Neutron Moisture meter and CUI depth is low, it may be possible to adopt the Neutron Moisture measurement as screening method of CUI inspection.

Some new findings are revealed from this study, but there are some remaining problems, like the validity and the verification of the CUI estimation modeling, and other appropriate screening method for CUI inspection. It is expected that this project would be continued to study and to solve these remaining problems.

Keywords: chemical plant, Corrosion Under Insulation, likelihood estimation model, neutron moisture meter