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[1]段文义,王林元,邓洪波,等.氯乙烯储罐注水堵漏腐蚀风险的预测方法研究*[J].中国安全生产科学技术,2021,17(9):114-119.[doi:10.11731/j.issn.1673-193x.2021.09.018]
　DUAN Wenyi,WANG Linyuan,DENG Hongbo,et al.Study on prediction method for corrosion risk of water injection leak-stoppage of vinyl chloride storage tank[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2021,17(9):114-119.[doi:10.11731/j.issn.1673-193x.2021.09.018]
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氯乙烯储罐注水堵漏腐蚀风险的预测方法研究*
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《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
17
期数:
2021年9期
页码:
114-119
栏目:
职业安全卫生管理与技术
出版日期:
2021-09-30

文章信息/Info

Title:
Study on prediction method for corrosion risk of water injection leak-stoppage of vinyl chloride storage tank
文章编号:
1673-193X(2021)-09-0114-06
作者:
段文义; 王林元; 邓洪波; 杨雅冰
（西南石油大学 化学化工学院，四川 成都 610500)
Author(s):
DUAN Wenyi;  WANG Linyuan;  DENG Hongbo;  YANG Yabing
(School of Chemistry and Chemical Engineering,Southwest Petroleum University,Chengdu Sichuan 610500,China)
关键词:
流程模拟分析; 神经网络; 挂片实验; 储罐注水：腐蚀速率
Keywords:
process simulation analysis;  neural network;  coupon test;  water injection of storage tank;  corrosion rate
分类号:
X933
DOI:
10.11731/j.issn.1673-193x.2021.09.018
文献标志码:
A
摘要:
为更好地解决氯乙烯储罐注水堵漏可能导致储罐发生腐蚀泄漏的实际问题，提出1种基于ASPEN和神经网络的氯乙烯储罐注水堵漏腐蚀风险的预测方法。运用ASPEN流程模拟软件，对氯乙烯储罐注水堵漏工艺进行模拟，得到不同泄漏孔径下注水速率和HCl浓度的关系；以HCl浓度作为导致腐蚀的主要影响因素，对不同种钢材进行挂片腐蚀实验；结合神经网络分析，得出HCl浓度与腐蚀速率之间的拟合式，预测储罐腐蚀情况。结果表明：神经网络预测结果平均相对误差7.63%，随注水速率的提高，HCl浓度变化呈下降趋势，腐蚀速率变化呈下降趋势；在等效泄漏孔径24 mm、注水速率0.87 m/s时，Q345R腐蚀速率13.93 mm/a，20#腐蚀速率10.48 mm/a，201不锈钢腐蚀速率7.09 mm/a为3者中最低，但此工况下，201不锈钢有点蚀倾向，储罐易发生穿孔，故201不锈钢不宜用作氯乙烯储罐母材，并提出对《石油化工企业设计防火标准(2018年版)》的修订建议。
Abstract:
In order to study the actual problem of the corrosion and leakage of vinyl chloride storage tank caused by the water injection leak-stoppage,a prediction method for the corrosion risk of the vinyl chloride storage tank with water injection leak-stoppage based on ASPEN and neural network was proposed.By applying the ASPEN process simulation software,the water injection leak-stoppage process of vinyl chloride storage tank was simulated,and the relationship between water injection rate and HCl concentration under different leakage apertures was obtained.Taking the HCl concentration as the main influencing factor of corrosion,the coupon corrosion tests were conducted on different kinds of steel.Combined with the neural network analysis,the fitting formula between HCl concentration and corrosion rate was obtained to predict the corrosion of storage tank.The results showed that the average relative error of the prediction results of neural network was 7.63 %,and the HCl concentration and corrosion rate decreased with the increase of water injection rate.When the equivalent leakage aperture was 24 mm and the water injection rate was 0.87 m/s,the corrosion rate of Q345R was 13.93 mm/a,the corrosion rate of 20# was 10.48 mm/a,and the corrosion rate of 201 stainless steel was 7.09 mm/a,which was the lowest among the three.However,under this working condition,the 201 stainless steel had the tendency of pitting corrosion,and the tank was prone to occur the perforation.Therefore,the 201 stainless steel should not be used as the base material for the vinyl chloride storage tanks,and the suggestions for revising “fire prevention standard of petrochemical enterprises design” were proposed.

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备注/Memo

备注/Memo:
收稿日期： 2021-03-12
* 基金项目： 国家自然科学基金项目（51874255）
作者简介： 段文义，硕士研究生，主要研究方向为油气化工安全。
通信作者： 王林元，博士，教授，主要研究方向为化工安全。
更新日期/Last Update: 2021-10-02