一般大气环境下锈蚀结构钢表面特征与随机模型

doi:10.11900/0412.1961.2019.00156

金属学报

2020, Vol. 56

Issue (2): 148-160 DOI: 10.11900/0412.1961.2019.00156

研究论文

本期目录 | 过刊浏览

一般大气环境下锈蚀结构钢表面特征与随机模型

王友德^1,²(

),徐善华^1,²,李晗^1,²,张海江^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

Surface Characteristics and Stochastic Model of Corroded Structural Steel Under General Atmospheric Environment

WANG Youde^1,²(

),XU Shanhua^1,²,LI Han^1,²,ZHANG Haijiang^1,²

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

引用本文:

王友德,徐善华,李晗,张海江. 一般大气环境下锈蚀结构钢表面特征与随机模型[J]. 金属学报, 2020, 56(2): 148-160.
Youde WANG, Shanhua XU, Han LI, Haijiang ZHANG. Surface Characteristics and Stochastic Model of Corroded Structural Steel Under General Atmospheric Environment[J]. Acta Metall Sin, 2020, 56(2): 148-160.

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摘要:

对处于大气腐蚀环境中的结构钢开展了6批次人工加速腐蚀实验和为期8 a的自然暴露实验，利用表面形貌测试方法和腐蚀表征参数自编分析程序对锈蚀结构钢表面特征参数及演变规律进行研究，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，一般大气环境下结构钢锈蚀深度服从正态分布，锈坑深度与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；锈坑形状由圆柱或半球体逐渐向圆锥体转变。最后基于锈蚀深度参数和锈坑参数统计分析结果，考虑各表征参数的变化规律与内在联系，建立了锈蚀深度随机场模型与锈坑随机分布模型，实现了一般大气环境锈蚀钢材表面特征的准确模拟与重建。

关键词 ：一般大气环境, 结构钢, 锈蚀, 表面特征, 随机模型

Abstract：

Steel structures exposed to corrosive atmospheres for a long time are highly susceptible to corrosion damage. The safety assessments of existing corroded steel structures rely heavily on the quantification of corrosion itself. In order to study the corrosion characteristics of structural steel in general atmospheric environment, 6 batches of artificial accelerated corrosion experiments and 8 a of natural exposure experiments were carried out. The surface characteristic parameters and evolution rules of corroded structural steel were studied by the surface morphology tests and self-programmed morphology analysis program. The distribution characteristics of corrosion depth, pit depth and aspect ratio were clarified, and the changing laws of statistical parameters (such as mean value and standard deviation) and pitting shapes were revealed. The results indicated that the corrosion depth of structural steel in general atmospheric environment obeyed the normal distribution, and the pit depth and aspect ratio obeyed the lognormal distribution. With the increase of corrosion degree, the mean value and standard deviation of corrosion depth, the peak value of power spectrum density of corrosion depth, and the logarithmic mean value of pit depth gradually increased, and the logarithmic mean value of pit aspect ratio decreased. Meanwhile, the shape of pits was gradually changed from a cylinder or hemisphere to a cone. Finally, based on the statistical analysis results of corrosion depth parameters and pit parameters, and taking the variation laws and internal relationships of characterization parameters into consideration, the stochastic field model of corrosion depth and the random distribution model of corrosion pits were established, which achieved the accurate simulation and reconstruction of surface characteristics of corroded steel under general atmospheric environment.

Key words： general atmospheric environment structural steel corrosion surface characteristic stochastic model

收稿日期: 2019-05-20

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(19JS042)

作者简介: 王友德，男，1988年生，博士

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https://www.ams.org.cn/CN/10.11900/0412.1961.2019.00156 或 https://www.ams.org.cn/CN/Y2020/V56/I2/148

图1 锈蚀深度参数提取示意图

图2 锈坑参数提取原理示意图与提取结果

表1 试件腐蚀程度参数

图3 加速腐蚀试件表面形貌

图4 自然腐蚀试件表面形貌

图5 加速腐蚀与自然腐蚀部分试件锈蚀深度频率分布直方图

表2 锈蚀深度参数统计结果

图6 平均锈蚀深度(Δtave)和锈蚀深度标准差(tsd)的变化规律

图7 部分加速腐蚀试件功率谱密度函数拟合结果

图8 与腐蚀程度相关的腐蚀表面功率谱拟合参数κ1和κ2变化规律

图9 锈坑深度(h)和径深比(Ar)提取结果

Sample No.	P_d / cm^-2		μ_h		σ_h		μ $A r$		σ $A r$
Sample No.	Side A	Side B	Side A	Side B	Side A	Side B	Side A	Side B	Side A	Side B
A1	22.2	19.1	4.91	5.09	0.19	0.16	1.58	1.55	0.55	0.53
A2	20.5	20.1	5.21	5.35	0.20	0.18	1.56	1.62	0.69	0.63
A3	19.4	18.5	5.68	5.51	0.07	0.10	0.90	1.43	0.61	0.59
A4	16.2	17.2	5.75	5.80	0.11	0.21	0.94	0.85	0.60	0.63
A5	12.5	13.2	5.63	5.82	0.13	0.14	1.21	0.92	0.64	0.66
A6	10.1	11.5	5.88	5.95	0.24	0.16	1.33	0.95	0.63	0.60
HTF	20.2	6.4	5.46	6.47	0.53	0.38	0.97	0.34	0.69	0.69
HBF	6.9	7.5	6.38	6.23	0.39	0.31	0.72	0.72	0.54	0.68
HW	9.4	11.5	6.34	5.98	0.34	0.21	0.16	0.25	0.5	0.53
STF	15.7	7.6	5.40	6.35	0.40	0.44	1.24	0.61	0.64	0.66
SBF	13.4	10.7	5.88	5.72	0.67	0.48	0.43	0.57	0.62	0.60
SW	8.6	6.8	5.89	6.46	0.38	0.36	1.07	0.68	0.51	0.51
VTF	15.3	14.6	5.49	5.80	0.47	0.63	0.58	0.24	0.49	0.62
VBF	11.0	13.3	6.09	6.27	0.50	0.34	0.28	0.24	0.56	0.56
VW	12.2	14.5	5.91	5.70	0.35	0.39	0.69	0.73	0.49	0.59

表3 锈坑特征参数统计结果

图10 锈坑深度对数均值(μh)和锈坑径深化对数均值(μAr)变化规律

图11 锈坑形状参数(VB)统计结果

图12 锈坑深度与锈坑形状的关系

图13 锈坑密度(Pd)变化规律

图14 HTF试件(Side B)映射重建形貌

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