CAREER: Intelligent Corrosion Mitigation System of Steel Structures with Duplex Coating

该学院早期职业发展计划（Career）项目旨在探索、开发和推广钢结构和钢筋混凝土结构全生命周期腐蚀管理的自主决策支持系统。这项创新技术可以将目前基于时间的视觉检测方法转变为基于传感器/数据的决策支持过程，从而实现及时的腐蚀管理。智能系统不仅可以告知最终用户识别和降低安全风险，以避免意外故障和相关死亡，而且还可以通过提高老化基础设施的使用寿命来实现卓越运营，而腐蚀退化是主要问题。由于腐蚀造成的损失约占国民生产总值的3.1%，因此，这种减缓/管理技术可大大节省成本，从而大大有利于国民经济。这项跨学科研究的结果和发现可以直接整合到与腐蚀相关的课程中，吸引了来自多个学科的本科生和研究生更广泛的参与。大学预科课程腐蚀工程师（CORE）的学习活动从腐蚀基础知识的视频讲座到服装作为最低水渗透腐蚀防护涂层的动手资格测试，可以激发K-12年轻女孩对STEM教育的兴趣。此外，还有两个CORE项目是为来自弱势群体的中学生和高中生设计的。该系统由内部热喷涂有色金属层和外部纳米材料改性聚合物密封漆层组成的双相防腐涂层、嵌入分布式光纤传感器的双相涂层腐蚀评估策略以及具有动态风险评估建模的决策工具组成。本研究将通过优化有色金属涂层复合材料以获得强大的机械和耐腐蚀性，以及了解纳米添加剂与聚合物涂料之间的化学相互作用以实现理想的分散，从而推动双相涂层技术的发展。采用拉脱试验、扫描电镜（SEM）和能谱仪（EDS）分析界面结构和状态，以及x射线衍射（XRD）技术分析相组成，研究了钢基与光纤传感器双相涂层的界面结合力学和行为，以及金属复合材料和纳米添加剂对提高结合强度的影响。通过在双相涂层中嵌入分布式光纤传感器，本研究还旨在了解阴极和屏障联合保护涂层结构钢的原位腐蚀恶化机制。通过智能系统提供的现场腐蚀数据，可以了解双相涂层中水分和氧气的渗透路径和速率，从而评估通过大面积多孔涂层或涂层降解进行均匀腐蚀的情况，或者通过局部缺陷和损伤进行点蚀的情况。相应的评估结果将被输入一个实时腐蚀状况更新算法，以开发一个自更新的混合腐蚀风险管理模型，以经济有效地确定缓减行动的优先次序。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This Faculty Early Career Development Program (CAREER) project is to explore, develop and promote an autonomous decision supporting system for the life-cycle corrosion management of steel structures and steel reinforced concrete structures. The innovative technology can transform the current practice of time-based visual inspection with inconsistent decisions to a sensor/data-based decision-supporting process for timely corrosion management. The intelligent system can not only inform end users identify and reduce safety risks to avoid unexpected failure and associated fatality but it can also achieve operational excellence by enhancing the service life of aging infrastructures where corrosion degradation is a main concern. As corrosion has shown to cost about 3.1 percent of the national gross domestic product, this mitigation/management technology can have significant cost saving, and thus greatly benefit national economy. The results and findings from this interdisciplinary research can be directly integrated into corrosion-related curriculums, attracting a broader participation of both undergraduate and graduate students from several disciplines. The pre-college, CORrosion Engineers (CORE), program with learning activities from video lectures on corrosion fundamentals to hands-on qualification tests of clothes as corrosion protection coating for minimum water penetration can stimulate the interests for STEM educations among K-12 young girls. In addition, two CORE programs are designed to involve middle and high school students from the underrepresented groups.The system consists of a corrosion protective duplex coating of an inner thermally-sprayed non-ferrous metal layer and an outer nanomaterial modified polymeric sealing paint layer, a corrosion assessment strategy with distributed fiber optic sensors embedded in the duplex coating, and a decision-making tool with dynamic risk assessment modeling. This research will advance the duplex coating technology by 1) optimizing composites of non-ferrous metal coating to achieve robust mechanical and corrosion resistance, and 2) understanding the chemical interaction between nano-additives and polymeric paints to accomplish the desirable dispersion. The interface bonding mechanics and behavior of duplex coating with both steel substrates and fiber optic sensors, more importantly, the effect of metal composites and nano-additives on improving the bond strength will be investigated using pull-off tests, scanning electron microscopy (SEM) with energy dispersion system (EDS) for interface structure and state analysis, and X-ray diffraction (XRD) technique for phase composition analysis. With the distributed fiber optic sensors embedded in duplex coating layers, this research also aims to understand the in-situ corrosion deterioration mechanism of coated structural steel with combined cathodic and barrier protection. The in-situ corrosion data availed by the intelligent system enable the understanding on the path and rate of moisture and oxygen penetration through duplex coating to assess scenarios of the uniform corrosion through a large area of porous coatings or coating degradation, or pitted corrosion through local defects and damage. The corresponding assessment will be fed into a real-time corrosion condition updating algorithm to develop a self-updated hybrid corrosion risk management model for a cost-effective prioritization of mitigation actions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.