Shintaro Kumano

Changes in electromagnetic properties during thermal aging of duplex stainless steel

Abstract To maintain the integrity of applications of duplex stainless steels currently in service, a study using two types of electromagnetic testing, i.e. electric resistivity testing and coercivity measurement testing, was conducted to develop a method to nondestructively estimate their Charpy-impact energy at room temperature. Materials tested included four grades of duplex stainless steel with differing ferrite content that had been subjected to long-term heating. Changes in Charpy-impact energy and electromagnetic properties due to aging were observed. It was found that electric resistivity and coercivity are reliable indicators of the process of embrittlement, but their relationship to impact energy is dependent on the material. Further, the dependency on the material differed between the two testing methods employed, though the main cause of embrittlement for duplex stainless steels can be assumed to be ferrite phase separation. Coercivity testing seems to show the property change in the ferrite phase more sensitively than it shows the difference in material, whereas electric resistivity testing distinguishes the difference in material more clearly than the property change in the ferrite phase. Change in Charpy-impact energy due to embrittlement is mainly caused by ferrite phase separation, but Charpy-impact energy is also influenced by the austenite phase. As the conclusion of this study, an equation involving electric resistivity, coercivity and ferrite content was presented as a method applicable to the nondestructive estimation of Charpy-impact energy at room temperature.

Advanced Gas Turbine Diagnostics Using Pattern Recognition

Power plant owners require their plants’ high reliability, availability and also reduction of the cost in today’s power generation industry. In addition, the power generation industry is faced with a reduction of experienced operators and sophistication of power generation equipment. Remote monitoring service provided by original equipment manufacturers (OEMs) has become increasingly popular due to growing demand for both improvement of plant reliability and solution of experienced operator shortage. Through remote monitoring service, customers can benefit from swift and appropriate operational support based on OEM’s know-how. Before implementation of remote monitoring, the customer and OEM often required repeated interchanges of information about operation and instrumentation data. These interchanges took a lot of time. Data analysis and estimation of deterioration were time-consuming. Remote monitoring has enabled us, OEMs, not only to access to a plant’s real-time information but also to trace the historical operation data, and therefore the required time of data analysis and improvement has been reduced. Mitsubishi Heavy Industries, Ltd. also embarked on around-the-clock remote monitoring service for gas turbine plant over a decade ago and has increased its ability over time. At present, the application of remote monitoring systems have been extended not only into proactive maintenance by making use of diagnostic techniques carried out by expert engineers but also into building a pattern recognition system and an artificial intelligence system using expert’ knowledge. Conventional diagnostics is only determining whether the plant is being operated within the prescribed threshold levels. Pattern recognition is a state-of-the-art technique for diagnosing plant operating conditions. By comparing past and present conditions, small deterioration can be detected before it needs inspection or repair, while all the operating parameter is within their threshold levels. Mahalanobis-Taguchi method (MT method) is a technique for pattern recognition and has the advantage of diagnosing overall GT condition by combining many variables into one indicator called Mahalanobis distance. MHI has applied MT method to the monitoring of gas turbines and verified it to be efficient method of diagnostics. Now, in addition to the MT method, automatic abnormal data discrimination system has been developed based on an artificial intelligence technique. Among a lot of artificial intelligence techniques, Bayesian network mathematical model is used.Copyright

Non-uniform azimuth image shift caused by the pitching motion of ships observed in Radarsat images

Non-uniform azimuth image shift of a rigid body is observed, for the first time, in the Radarsat images of moving ships in pitching motion. The pitching velocity is estimated from the SAR image of a known ship, and compared with that computed using a numerical model with the meteorological and ships data; further comparison is made with the wave orbital velocity. The results are shown to be all in excellent agreement. Comparisons are also made between the pitching velocities of unknown ships with the wave orbital velocity, and a reasonable agreement is obtained.

Robust Optimization of Locating Mobile Relay Stations for Radio Communication

This paper describes the facility location problem of mobile relay stations which connect the head office and sensing vehicles for the fast and accurate communication in the case of disaster or urgent situation. The optimal decision of locating relay stations and assigning the radio frequencies for the robust and accurate communication are discussed. The major feature of this paper is that the robustness for multiple communication paths and the high accuracy of communication should be held even if any one of the relay stations becomes out of use. This problem can be formulated as the min-max decision problem of minimizing the decrease of the communication power, which is the combined concept of the number of redundant paths and the communication accuracy, when the most critical station is damaged. This paper proposes a solution method for this nonlinear integer programming problem using the simulated annealing with matrix calculation. The efficiency of the proposed method is shown for concrete numerical examples.

Method for NDE of thermal embrittlement of duplex stainless steels

To verify and maintain the integrity of duplex stainless steels currently in service, we conducted a study in order to develop a method to nondestructively estimate their Charpy-impact energy at room temperature. Hardness of the ferrite phase was found to be a reliable indicator of the process of embrittlement during long-term heating for duplex stainless steels, but further information on the ferrite phase and the austenite phase is required for the estimation of Charpy-impact energy. An equation involving the hardness values of the ferrite and austenite phases,the ferrite content, and the average spacing of ferrite phase islands was found to be applicable in the nondestructive estimation of Charpy-impact energy at room temperature.