Collection of big data for corrosion under insulation (CUI) of pipes has been a major concern in maintenance management. It is expected that new inforamtion is extracted from the collected data. To extract the statistical information from the data, statistical treatment should be done carefully. This paper investigates statistical treatment of metal loss growth rate of CUI (hereafter referred as CUI rate) for the collected data under the project of Ministry of Economy, Trade and Industry (METI) . The variability of CUI rate is normally modelled as Gumbel distribution. However, it is often reported that the variability of CUI rate depends on the inspection period. Especially, the variability in CUI rate in shorter inspection period prones to increase. It is supposed that the CUI rate data in longer inspection period has been used for the evaluation. However, it is clear that the statistical treatment is important for the accurate estimation of CUI rate. This paper shows that the variability of the wall thickness is not negligible for the statistical evaluation of CUI rate and proposes a new statistical model including the variation of thickness. When the nominal thickness value is used as the initial thickness, the evaluated CUI rate includes the uncertainty of the thickness. Thus, the evaluated CUI rate is not the true value, but only apparent value. The validity of the model is confirmed for the data in database, and by Monte Carlo Simulation. Finally, it will be shown that the apparent CUI rate is expressed mathematically using moment generating function.

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This article introduces real time corrosion monitoring technologies, with unique technologies of transmitter to provide 4 corrosion related signals at the same time where it is located, and of combination of corrosion prediction software, which is mainly for refining process, and software function automatically obtaining required process variables and environmental information from Historian, DCS (Distributed Control System) and LIMS (Laboratory Information Management System) to predict corrosion rate of relevant refining asset or system, continuously.
Real time corrosion monitoring can provide visualized corrosion trend as same as other process values, i. e. temperature, flow rate, pressure, etc. , which can provide availability to manage corrosion by correlating visualized corrosion rate trend with other process variables which to allow refining process operation within IOW (Integrity Operating Windows) of operation conditions within the corrosion allowance range of the asset design life.

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Indentation test is one of the solutions for predicting the local mechanical properties of weld joint as proposed in our previous work. In the present study, the test method was improved to apply for the material with large yield elongation, and the predicted mechanical properties were compared with those obtained by the tensile tests for the base and weld metals. Fairly good agreement is achieved for the base material with 2. 5% yield elongation when the prediction includes the measurements of the dent sizes on the surface and in the depth. The prediction of the weld metal exhibits large scatter whose lower limit tend to agree with the result of the tensile test obtained by small specimens cut from the center of the weld metal. Also performed were the tensile tests for weld specimens whose weld lines were parallel, perpendicular or 45 degree to the loading direction. Strain distributions were measured in terms of the digital image correlation (DIC) method and compared with those simulated by the finite element analysis (FEA) . The strain distributions obtained by the DIC and FEA demonstrate good agreement and strong effect of the loading pass for the weld metal, therefore, the consideration of the local mechanical properties is significant for the welded components.

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Improvement of hydrogen filling capacity of hydrogen refueling stations in city area is required due to increasing number of fuel cell vehicles and for refueling fuel cell buses with large tank capacity. Since installation space area in city is limited, cryopump system is optimal for its compression efficiency and effective utilization of cold heat energy. However, cryopump system is operated under extremely low temperature and high pressure hydrogen environment. In order to select optimal material of cryopump system for hydrogen refueling stations, evaluation of hydrogen embrittlement resistance evaluation and toughness at low temperature is necessary. In this research, hydrogen embrittlement resistance and low temperature toughness of XM-19 (ASME SA479) and SUH660 (JIS G4312) were evaluated to determine their adaptability for cryopump system.

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