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金属学报  2021, Vol. 57 Issue (6): 811-821    DOI: 10.11900/0412.1961.2020.00326
  研究论文 本期目录 | 过刊浏览 |
模拟近海大气环境下结构钢锈蚀表面特征随机模型
王友德1,2(), 周晓东1,2, 马蕊2,3, 徐善华1,2
1.西安建筑科技大学 省部共建西部绿色建筑国家重点实验室 西安 710055
2.西安建筑科技大学 工程结构安全与耐久重点实验室 西安 710055
3.西安交通大学 第一附属医院 西安 710061
Stochastic Model for Surface Characterization of Structural Steel Corroded in Simulated Offshore Atmosphere
WANG Youde1,2(), ZHOU Xiaodong1,2, MA Rui2,3, XU Shanhua1,2
1.State Key Laboratory of Green Building in Western China, Xi'an University of Architecture and Technology, Xi'an 710055, China
2.Key Lab of Engineering Structural Safety and Durability, Xi'an University of Architecture and Technology, Xi'an 710055, China
3.First Affiliated Hospital, Xi'an Jiaotong University, Xi'an 710061, China
引用本文:

王友德, 周晓东, 马蕊, 徐善华. 模拟近海大气环境下结构钢锈蚀表面特征随机模型[J]. 金属学报, 2021, 57(6): 811-821.
Youde WANG, Xiaodong ZHOU, Rui MA, Shanhua XU. Stochastic Model for Surface Characterization of Structural Steel Corroded in Simulated Offshore Atmosphere[J]. Acta Metall Sin, 2021, 57(6): 811-821.

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摘要: 

对16块Q235B钢板进行了模拟近海大气环境加速腐蚀实验,利用非接触式表面形貌测试方法与自编程序对其表面形貌与特征参数进行采集与分析,明确锈蚀深度、锈坑深度、锈坑径深比分布特征,揭示其均值、方差等统计参数及锈坑形状的变化规律。研究表明,模拟近海大气环境下结构钢腐蚀过程大致经历疮痂、鼓包、剥落3个阶段,疮痂和鼓包阶段以点蚀为主,剥落阶段则表现出全面腐蚀特征;锈蚀深度服从正态分布,锈坑深度和径深比服从对数正态分布;随着腐蚀程度的增大,锈蚀深度均值、标准差与功率谱密度峰值以及锈坑深度对数均值均逐渐增大,锈坑径深比对数均值逐渐减小;各龄期内圆锥体锈坑占比最高,锈坑形状由圆柱或半球体逐渐向圆锥体转变。最后基于锈蚀深度和锈坑参数统计规律,建立了锈蚀深度随机场模型(SFCD)和锈坑随机分布模型(RDCP),实现了模拟近海大气环境锈蚀钢材表面形貌重建。

关键词 近海大气环境结构钢锈蚀表面特征随机模型    
Abstract

Steel structures exposed to offshore atmospheric environment for a long time inevitably suffer from corrosion damage. Safety assessment of corroded steel structures largely depends on the quantification of corroded surface features as the irregular corrosion characteristics are the main factors causing decline in steel mechanical properties. To investigate the structural steel corrosion characteristics in offshore atmospheric environment, accelerated corrosion tests were conducted on 16 pieces of Q235B steel plates by periodic spraying to simulate the offshore atmospheric environment. Moreover, the surface morphologies and characteristic parameters were measured and analyzed using a ST400 3D Noncontact Profilometer and a self-written algorithm. The distribution characteristics such as corrosion depth, pit depth, and aspect ratio were elucidated, and the changing laws of statistical parameters such as mean value, standard deviation, and pitting shapes were revealed. The results indicated that in the simulated offshore atmospheric environment, the structural steel corrosion process generally goes through three stages: scab, swell, and spall. The scab and swell stages are dominated by pitting corrosion, whereas, the spall stage shows the general corrosion characteristics. Moreover, the corrosion depth of structural steel in the simulated offshore atmospheric environment conforms to the normal distribution, whereas, the pit depth and aspect ratio conform to the log-normal distribution. As the degree of corrosion increases, the mean value and standard deviation of the corrosion depth, peak value of the power spectral density of the corrosion depth, and logarithmic mean value of the pit depth also gradually increase, whereas, the logarithmic mean value of the pit aspect ratio decreases. Meanwhile, at different ages, the cone pits have the highest proportion, and the pit shape gradually changes from a cylinder or a hemisphere to a cone. Finally, based on the results of the statistical analysis of the corrosion depth and pit parameters, the stochastic field model of corrosion depth and random distribution model of corrosion pits were constructed, which achieved the accurate characterization and reproduction of the surface morphology of the corroded steel in a simulated offshore atmospheric environment. The research results would lay the foundation for the establishment of an accurate stochastic model and structural reliability analysis in the natural offshore atmospheric environment.

Key wordsoffshore atmospheric environment    structural steel    corrosion    surface characteristic    stochastic model
收稿日期: 2020-08-24     
ZTFLH:  TU511.3  
基金资助:国家自然科学基金项目(51908455);中国博士后科学基金项目(2019M653572);陕西省教育厅科研计划项目(19-JS042)
作者简介: 王友德,男,1988年生,副教授,博士
图1  不同龄期Q235B钢板试件的腐蚀特征(a) S0, 0 d (b1, b2) S1, 30 d (c1, c2) S2, 70 d (d1, d2) S3, 110 d (e1, e2) S4, 150 d (f1, f2) S5, 250 d (g1, g2) S6, 310 d (h1, h2) S7, 370 d (i1, i2) S8, 440 d
图2  模拟与自然[17]近海大气环境下钢材腐蚀失厚对比
图3  腐蚀试件的表面形貌(a) S1 (b) S2 (c) S3 (d) S4 (e) S5 (f) S6 (g) S7 (h) S8
图4  部分试件锈蚀深度频率分布直方图(a) S1 (b) S3 (c) S4 (d) S8

Sample

No.

Δte

μm

Δtave

μm

tsd

μm

ab

Pd

cm-2

μhσhμArσAr
S1-111458241.6181.06215.34.550.242.210.44
S1-211962261.8671.03119.84.230.152.190.41
S2-1374157782.3691.58321.95.330.191.600.50
S2-2379192872.4581.63519.05.490.331.530.55
S3-15522121012.1241.37418.55.640.251.330.61
S3-2540160872.2151.38215.65.400.381.490.63
S4-1582227722.2711.50118.05.620.221.310.62
S4-26022341291.5350.84413.45.560.471.500.47
S5-16922611213.3061.95523.05.600.481.560.55
S5-2698210761.3380.85324.15.720.171.370.39
S6-17962671072.6441.59825.15.970.261.190.55
S6-2808207952.4291.44221.85.660.271.190.50
S7-110912931092.5311.54621.15.950.231.070.59
S7-211443951262.6131.60920.96.280.130.810.61
S8-113873601072.4381.46923.56.220.170.790.54
S8-214343971282.0241.19819.06.380.140.740.48
表1  锈蚀深度与锈坑特征参数统计结果
图5  平均锈蚀深度(Δtave)和锈蚀深度标准差(tsd)的变化规律
图6  部分腐蚀试件功率谱密度函数拟合结果(a) S1 (b) S3 (c) S7
图7  腐蚀表面功率谱拟合参数a和b变化规律
图8  锈坑深度(h)和径深比(Ar)提取结果
图9  锈坑深度对数均值(μh)和锈坑径深比对数均值(μAr)变化规律
图10  锈坑形状分析(a) statistical results of volume-box parameter (VB) (b) relationship between pit depth and shape
图11  近海大气环境锈蚀结构钢基于锈蚀深度随机场模型(SFCD)和锈坑随机分布模型(RDCP)的形貌映射重建(a) S1, 30 d, SFCD simulation (b) S8, 440 d, SFCD simulation(c) S2, 70 d, RDCP simulation (d) S6, 310 d, RDCP simulation
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