Construction and optimization of corrosion map in a broad region of acidic soil via machine learning

IF 1.1 4区材料科学 Q4 MATERIALS SCIENCE, MULTIDISCIPLINARY

Corrosion Pub Date : 2024-01-24 DOI:10.5006/4498

Hui Su, Jun Wang, Yuxing Zeng, Chenmeng Dang, Yi Xie, Song Xu, Yongli Huang, Zhi Li, Tangqing Wu

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引用次数: 0

Abstract

Machine learning has been widely applied to exploring the key affecting factors for metal corrosion in some local regions. However, there is a lack of systemic research and practicable prediction model for the metal corrosion in a broad region. In this paper, the corrosion map of Q235 steel in a broad region of acidic soils of Hunan province of Central China was constructed and optimized via the field experiment and machine learning. Both the experimental and optimized corrosion maps confirmed that the corrosion rate of the steel decreased from the western to the eastern part of the province. The concentrations of pH, F−, Cl−, NO3−, HCO3−, K+ and Mg2+ were the key affecting factors in the broad region of acidic soils of the province. Among them, the contribution rate of the HCO3− concentration was higher than that of other factors. The optimization model based on the ordinary least squares could be used for the optimization of the corrosion map of steels a broad region of acidic soils. The optimized corrosion map was a good alternative of the estimation methods for the corrosion rate of steels in soil.

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通过机器学习构建和优化广阔酸性土壤区域的腐蚀地图

机器学习已被广泛应用于探索一些局部地区金属腐蚀的关键影响因素。然而，目前还缺乏针对大区域金属腐蚀的系统研究和实用预测模型。本文通过现场实验和机器学习，构建并优化了 Q235 钢在中国中部湖南省大面积酸性土壤中的腐蚀图谱。实验图和优化后的腐蚀图均证实，钢材的腐蚀速率从该省西部向东部递减。pH、F-、Cl-、NO3-、HCO3-、K+和Mg2+的浓度是该省广大酸性土壤区域的关键影响因素。其中，HCO3-浓度的贡献率高于其他因子。基于普通最小二乘法的优化模型可用于优化大面积酸性土壤中钢材的腐蚀图。优化后的腐蚀图可以很好地替代土壤中钢材腐蚀速率的估算方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Corrosion MATERIALS SCIENCE, MULTIDISCIPLINARY-METALLURGY & METALLURGICAL ENGINEERING

CiteScore

2.80

自引率

12.50%

发文量

审稿时长

3 months

期刊介绍： CORROSION is the premier research journal featuring peer-reviewed technical articles from the world’s top researchers and provides a permanent record of progress in the science and technology of corrosion prevention and control. The scope of the journal includes the latest developments in areas of corrosion metallurgy, mechanisms, predictors, cracking (sulfide stress, stress corrosion, hydrogen-induced), passivation, and CO2 corrosion. 70+ years and over 7,100 peer-reviewed articles with advances in corrosion science and engineering have been published in CORROSION. The journal publishes seven article types – original articles, invited critical reviews, technical notes, corrosion communications fast-tracked for rapid publication, special research topic issues, research letters of yearly annual conference student poster sessions, and scientific investigations of field corrosion processes. CORROSION, the Journal of Science and Engineering, serves as an important communication platform for academics, researchers, technical libraries, and universities. Articles considered for CORROSION should have significant permanent value and should accomplish at least one of the following objectives: • Contribute awareness of corrosion phenomena, • Advance understanding of fundamental process, and/or • Further the knowledge of techniques and practices used to reduce corrosion.