海洋钢结构的随机点蚀损伤反演及其结构性能退化与变异的机理

Steel structure serving in marine environment is most likely to suffer from pitting damage, which poses threat to structural safety. Statistical values of pit diameter and depth as well as pitting number are the only information, obtained from corrosion inspection in line with the classification rules, for the random pitting damage. While this is the only basis for making a decision on whether the structure is suitable to continue its service without maintenance or needed to be reinforced. However, at present, it is still short of a modeling method to reflect such statistical feature obtained from the corrosion inspection. As a result, it is yet unclear about the mechanism of degradation and variation of the structural performance due to random pitting damage. In the project, we will carry out structural and numerical experiments of pitted structures in order to reveal the mechanism of structural failure due to random pitting damage. And a stochastic simulation method will be proposed to construct the structural assessment model that can embody the statistical feature of pitting corrosion. A large number of stochastic simulations will be performed to illustrate the mechanism of the degradation and variation of the structural performance, and to clarify the probabilistic characteristics and distribution model of ultimate strength. The interacting between the random pitting damage and relevant parameters of structural performance (dimensions of structure and stiffener, loading pattern and geometric imperfection) will be studied to reveal the law of their coupling effect to weaken the structural performance. An artificial neural network model will be structured to predict the ultimate strength, involving all those compound factors associated with the pitting damage and relevant parameters of structural performance. Finally, a method to assess the ultimate strength under random pitting damage will be presented to provide a scientific basis for structural integrity management of the in-service ship and marine structure.

海洋环境下钢结构易遭受点蚀损伤而威胁结构安全。符合规范的腐蚀检测获取的点蚀损伤统计特性(蚀坑直径与深度的统计值及蚀坑数目)，是建立结构的性能评估模型并评价其是否适于继续服役或有待加固的唯一依据。但目前还缺少能反映腐蚀检测统计特性的随机点蚀损伤建模方法，这使得点蚀结构的性能退化与变异机理至今尚不清楚。本项目拟通过开展点蚀结构的模型试验和数值试验，揭示随机点蚀损伤致使结构破坏的机理；提出随机模拟方法构建能反映点蚀统计特性的性能评估模型；开展大量的随机模拟分析，阐明随机点蚀损伤导致结构性能退化和变异的机理，并明确极限强度的概率特性和概率分布模型；探究点蚀损伤与结构性能关联因素(结构与加强筋尺寸、载荷模式和几何缺陷)间的耦合作用机理，揭示其耦合效应削弱结构性能的规律，并构建人工神经网络模型以预测极限强度。最终形成随机点蚀损伤下结构极限强度的评估方法，为在役船舶与海洋结构的完整性管理提供科学依据。

本项目通过模型试验、数值模拟和理论分析，在材料和构件层面，研究点蚀损伤导致海洋结构的材料力学性能和构件极限强度变异和性能退化的机理，明确性能参数的概率分布模型，提出材料性能和构件极限强度的预测方法。首先，利用机械钻孔法在拉伸试样上构造出人工蚀坑，进行单轴拉伸试验。同时，开展了大量的随机模拟，明确影响点蚀钢材性能退化的关键点蚀参数，确定了材性指标的概率特性和概率分布模型。随后，设计出适合模拟海洋腐蚀环境的元胞机模型，提出了基于元胞机技术的随机点蚀模拟方法。借助该方法，阐明了蚀坑形状、间距、深度影响点蚀结构极限强度退化与失效行为的机理。进一步，开展随机点蚀损伤构件的轴压试验和数值模拟，揭示了蚀坑深度、腐蚀体积、腐蚀区域分布对点蚀构件极限强度和失效行为的影响规律，以及结构尺寸参数与点蚀损伤的耦合效应。随后，在IACS规范中涉及的点蚀强度范围内，研究了点蚀结构极限强度的变异规律，并确定其概率特性和概率分布模型；进一步开展回归分析，给出了极限强度预测公式。最终，运用正交实验设计法减少BP网络模型的训练样本数量，构建人工神经网络模型，预测点蚀结构极限强度与结构尺寸和点蚀参数之间的非线性关系，给出了精度良好的预测公式。结果表明，蚀坑深度、腐蚀体积、腐蚀区域形状均是影响结构性能退化的重要参数，特别是，通常被忽视的蚀坑形状，有重要影响，且其影响可由径深比来表征。随机点蚀钢的材性指标服从正态分布，其性能参数可由腐蚀体积比和蚀坑径深比来决定。随机点蚀结构的极限强度存在显著的变异性，但服从正态分布；传统平均厚度折减方法预测其极限强度，会严重高估其承载力。基于元胞机技术的随机点蚀模拟方法可得到与实船观测相一致的伪随机点蚀损伤。点蚀损伤与结构尺寸参数之间有复杂的耦合关系，所构建的BP神经网络模型可给出较好的预测结果，其预测误差小于10%。本项目研究结果可为在役海洋结构的安全性评估提供参考依据。