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Impact factor analysis, prediction, and mapping of soil corrosion of carbon steel across China based on MIV-BP artificial neural network and GIS

机译:基于MIV-BP人工神经网络和GIS的中国碳钢土壤腐蚀的影响因子分析,预测和映射

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Purpose Q235 carbon steel is one of the most widely used carbon steels, and soil corrosion and failures of it caused accidents, casualties, and great financial losses. Corrosion of Q235 carbon steel differed in spatial because of spatial variation in soil environmental factors. However, the national scale spatial pattern of soil corrosion of Q235 carbon steel across China has not been explored. Materials and methods The values of 12 impact factors, corrosion rate, and pitting corrosion rate at 25 sites covered all soil types in China were collected. Mean impact value (MIV) algorithm and back propagation artificial neural network (BP ANN) were combined and applied in the impact factor analysis. Prediction models for corrosion rate and pitting corrosion were developed based on BP ANN. The proposed prediction models and information about soil properties with high resolution (1 km x 1 km) were used in the prediction of corrosion rate. Based on geographical information system (GIS), the national scale spatial pattern of soil corrosion of Q235 carbon steel across China were analyzed. Results and discussion The water content and pH were of the largest influence (|MIV| 0.522) on both corrosion rate and pitting corrosion rate. For prediction models of corrosion rate and pitting corrosion rate, the predicted values were close to the measured values. Corrosion rates were of higher spatial differences, ranged from 0.632 to 5.181 g/(dm(2)center dot a). Pitting corrosion rates in the northeast were higher than other areas, which might be caused by higher values of total salt content, organic matter, and total voidage. Average corrosion rate in soil type 1 (1.161 mm/a) was nearly two times of that in soil type 2 (0.610 mm/a) and over three times of that in other types, indicating that corrosion rate varied largely among different soil types. Conclusion The importance of 12 impact factors of corrosion of Q235 carbon steel were evaluated, and the national scale corrosion rate and pitting corrosion rate in China were predicted and mapped for the first time. Both pitting corrosion rates and corrosion rates were of strong spatial variation.
机译:目的Q235碳钢是最广泛使用的碳钢之一,土壤腐蚀和失败导致事故,伤亡和巨大的经济损失。由于土壤环境因素的空间变化,Q235碳钢的腐蚀在空间中不同。然而,跨越中国Q235碳钢土壤腐蚀的全国规模空间模式尚未探讨。材料和方法在25个地点的12个影响因子,腐蚀速率和点腐蚀速率的值覆盖了中国所有土壤类型。相结合并应用了平均撞击值(MIV)算法和后传播人工神经网络(BP ANN)并应用于冲击因子分析。基于BP ANN开发了用于腐蚀速率和蚀腐蚀的预测模型。建议的预测模型和有关具有高分辨率(1 km×1km)的土壤性质的信息用于预测腐蚀速率。基于地理信息系统(GIS),分析了中国Q235碳钢土壤腐蚀的全国规模空间模式。结果与讨论含水量和pH值最大的影响(| MIV | 0.522),腐蚀速率和蚀腐蚀速率。对于腐蚀速率和点腐蚀速率的预测模型,预测值接近测量值。腐蚀速率具有较高的空间差异,范围为0.632至5.181g /(DM(2)中心点A)。东北部的点腐蚀速率高于其他区域,这可能是较高的总盐含量,有机物和总空转的值引起的。土壤1(1.161mm / a)的平均腐蚀速率接近土壤2(0.610mm / a)的两倍,其其他类型的三次,表明腐蚀速率在很大程度上在不同的土壤类型中变化。结论评估了1235季碳钢腐蚀腐蚀的12个影响因素的重要性,预测了中国的全国规模腐蚀速率和蚀腐蚀速率。蚀腐蚀速率和腐蚀速率都具有很强的空间变化。

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