07MnNiCrMoVDR钢在H_2S水溶液中腐蚀疲劳裂纹扩展特性研究
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摘要
压力容器是具有爆炸危险的特种生产与输送承压设备,尤其对于承受苛刻介质的压力容器,当这类设备存在相当严重缺陷时,一旦与腐蚀介质相互作用,必然成为事故的主要根源。如不及时治理,将造成重大灾难。
    本文研究通过对我国化工和石油化工装置中的典型材料07MnNiCrMoVDR钢在腐蚀介质H2S水溶液中疲劳裂纹扩展速率的研究,寻找其腐蚀疲劳裂纹扩展速率da/dN和应力强度因子幅值ΔK之间的关系,探索研究在役含缺陷压力容器腐蚀疲劳安全评定技术。
    本文主要研究07MnNiCrMoVDR钢在H2S水溶液中腐蚀疲劳裂纹扩展速率以及其剩余寿命的可靠度问题,主要研究内容及结果如下:
    (1)开展07MnNiCrMoVDR钢在H2S水溶液中腐蚀疲劳裂纹扩展速率试验,试验结果表明:随着H2S水溶液浓度的增大,加载频率的降低,应力比的增加,07MnNiCrMoVDR钢腐蚀疲劳裂纹扩展速率也相应增大;
    (2)开展07MnNiCrMoVDR钢在H2S水溶液中腐蚀疲劳裂纹扩展影响因素重要度的探讨,主要影响因素为介质浓度、加载频率、应力比。在以上三影响因素中,应力比所占的重要度最大,载荷频率次之,介质浓度的重要度最小;
    (3)将神经网络技术和Monte-Carlo方法应用于腐蚀疲劳裂纹扩展速率及寿命预测。应用BP神经网络预测不同条件下(介质浓度、加载频率、应力比)07MnNiCrMoVDR钢在H2S水溶液中腐蚀疲劳裂纹扩展速率系数C和指数n,结合Monte-Carlo方法进行环境条件下剩余寿命及可靠度的计算;
    (4)开展07MnNiCrMoVDR钢在H2S水溶液中腐蚀疲劳裂纹扩展速率公式的研究。利用训练出的神经网络找出介质浓度、加载频率、应力比在环境加速因子Cenv中的关系形式,并通过Matlab中数理统计工具箱回归出07MnNiCrMoVDR钢在H2S水溶液中的裂纹扩展速率公式,以便于工程应用;
    (5)利用Visual Basic编写腐蚀疲劳评定程序,初步实现了07MnNiCrMoVDR钢在H2S水溶液中腐蚀疲劳工程评估及剩余寿命预测、可靠度计算的计算机程序化,从而使腐蚀疲劳工程评估方法方便、快捷。
Pressure vessels are equipment which endured high pressure for specific production and transportation with explosion danger. Especially for these vessels used in corrosion solution environment, when serious defects were founded in them explosion must occur as soon as defects and corrosion solution reacted each other. If proper measures were not taken in time, serious disaster must happen.
    The object of the present paper was to study the relationship between corrosion fatigue crack growth rate da/dN and stress intensity factor amplitude ΔK of 07MnNiCrMoVDR steel by corrosion fatigue crack growth rate experiment in H2S solution. This steel is the typical material used in chemistry and oil chemistry equipment in our country. Corrosion fatigue safety assessment method of pressure vessels with defects in service could be explored and investigated.
    In the present paper, corrosion fatigue crack growth rate and reliability of remainder life of 07MnNiCrMoVDR steel in H2S solution were mainly researched. The research contents and results were as follows.
    (1)Experiments of corrosion fatigue crack growth rate of 07MnNiCrMoVDR steel in H2S solution were conducted. The results indicated that corrosion fatigue crack growth rate of 07MnNiCrMoVDR steel increased with an increase in H2S solution concentration, stress rate and a decrease in loading frequency.
    (2)Importance of influence factors was discussed in the process of corrosion fatigue crack growth of 07MnNiCrMoVDR steel in H2S solution. Main influence factors were solution concentration, loading frequency and stress rate. The importance of stress rate was largest among these influence factors. The loading frequency was second important influence factor, while solution concentration was the last one.
    (3) Neural network technology and Monte-Carlo method were used to predict corrosion fatigue crack growth rate and remainder life. Coefficients C and n of corrosion fatigue crack growth rate of 07MnNiCrMoVDR steel in H2S solution under different conditions (solution concentration, loading frequency and stress rate) were predicted by BP neural network, and then remainder life and its reliability of corrosion fatigue were calculated by combining neural network with Monte-Carlo method.
    (4)Formula of corrosion fatigue crack growth rate of 07MnNiCrMoVDR steel in H2S solution was proposed. Using neural network, the expression of Cenv could be obtained, and then the formula was regressed with statistical toolbox in Matlab, which could be easily used in engineering.
    (5)The corrosion fatigue assessment program was compiled by use of Visual Basic. The corrosion fatigue assessment, remainder life prediction and reliability calculation of 07MnNiCrMoVDR steel in H2S solution were realized by the program. Therefore it made the corrosion fatigue assessment engineering method more simple and faster.
引文
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