【摘要】 应用人工神经网络方法建立了 1 6Mn钢管道材料在土壤环境中的腐蚀速率描述模型 .利用土壤腐蚀速率的试验数据训练所建立的腐蚀速率描述模型 ,结果表明 :采用土壤的含水率、土壤环境中阴离子 SO42 -,CO3 2 -,HCO3 -,Cl-的含量和土壤电阻率 6个参数可以很好地描述 1 6Mn钢管道材料在土壤中腐蚀速率的变化规律 .应用所建立的模型分析了土壤含水率和土壤中阴离子含量对土壤腐蚀速率的影响 ,含水率是最显著的影响因素 ,阴离子的影响较小更多还原

【Abstract】 The model for analyzing corrosion rate of 16Mn pipeline steel in soil is established by using neural network, and it is exercised by the experimental data of corrosion rate. The results show that the corrosion rate can be well described by 6 parameters of soil, that is, water content, the contents of cathodic ions SO 4^2-, CO 3^2-, HCO 3^- and Cl^-, and resistivity. The neural network model trained is used to study the effects of water content and the contents of the cathodic ions on the corrosion rate. It is shown that the effect of water content is greater than those of the cathodic ion contents.更多还原