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Zairyo-to-Kankyo Vol. 63 (2014), No. 2
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Zairyo-to-Kankyo Vol. 63 (2014), No. 2
Development of the Forecasting System of the Current from Sacrificial Anodes of Marine Structures using Data Assimilation
Naoki Yoneya, Yoshikazu Akira, Kenkichi Tashiro, Tomohiro Iida, Toru Yamaji, Kenji Amaya
pp. 43-49
DOI:
10.3323/jcorr.63.43Abstract
A new method for forecasting the current of sacrificial anodes using data assimilation was developed. In our system, In the framework of data assimilation, the system model forecasts the future state by the technical knowledge gained from experiments. The observation model corrects the forecasted result by the measurement information. In order to demonstrate the effectiveness and efficiency of our system, the verification experiment was performed at the real marine steel structures. The proposed method is expected to be a new approach for corrosion protection maintenance.
Practical Method for Estimating Time-Dependent Corrosion Depth of Uncoated Carbon Steel Plate under Atmospheric Environment using Fe/Ag Galvanic Couple ACM-Type Corrosion Sensor
Shigenobu Kainuma, Yuya Yamamoto, Hideyuki Hayashi, Yoshihiro Itoh, Wataru Oshikawa
pp. 50-57
DOI:
10.3323/jcorr.63.50Abstract
To maintain economically steel structures against corrosion damage, it is necessary to quantitatively clarify the corrosion environments of individual parts in the structures and to evaluate the time-dependent corrosion behavior. In this research, an evaluating method for the time-dependent corrosion depth of uncoated structural steel plates using Fe/Ag galvanic couple ACM type corrosion sensor was proposed. This method was focused on the environments with and without effect of rainfall and airborne sea salt. Atmospheric exposure tests were carried out on the uncoated steel plates in four fields in which the environments varied widely as a function of rainfall and airborne sea salt. In addition to this, the corrosive environments of the skyward- and groundward-facing surfaces of the plates were monitored using the ACM sensors.
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