采用电化学、人工神经网络和数据库方法研究了5种海洋工程钢材在5000m深海环境中非现场腐蚀行为评价技术.结果表明，温度、溶解氧、盐度和pH值是评价5种海洋工程钢材海水腐蚀行为的主要介质参数.根据这一结果，用人工神经网络技术建立了温度、溶解氧、盐度和pH值与5种海洋工程钢材海水腐蚀速度的相关数据库MCM-CORRDB03，并采用WOA海洋要素分布数据集建立了MCM-GOCEANDB03全海域海水腐蚀参数数据库，进而使用MCM-CORRDB03和MCM-GOCEANDB03两个数据库评价了5种海洋工程钢材在5000 m深海环境腐蚀行为，证实了5种钢材均在700 m左右存在最低腐蚀速度，以及溶解氧对钢材深海腐蚀行为具有最主要的影响.结果表明，结合采用多种非现场方法可以可靠评价深海环境钢材的腐蚀行为.
The assessment of the corrosion behavior of the five steels in deep ocean above 5000 meters was made using the methods of electrochemistry, artificial neural network and database. The results showed that temperature, dissolved oxygen, salinity and pH value were main factors which affect the corrosion behavior of the five steels in seawater. According to the results, the correlation database of MCM-CORRDB03 was made for temperature, dissolved oxygen, salinity and pH value, and the corrosion behavior of the five steels in seawater using the method of artificial neural network. Moreover, the database of MCM-GOCEANDB03 was also made for corrosion factors of global ocean using the data collection of World Ocean Atlas. The corrosion behavior of five steels in deep ocean above 5000 meters was assessed with above two databases. It was confirmed that the minimum corrosion rate of the steels was appeared at depth of 500 meters, and the content of dissolved oxygen has the greatest effect on corrosion behavior of the steels in deep ocean. It is also indicated that above methods could assess the corrosion behavior of steel in deep ocean accurately.
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