材料科学
电偶腐蚀
腐蚀
概率逻辑
原电池
汽车工业
材料加工
冶金
计算机科学
制造工程
人工智能
工程类
航空航天工程
作者
Leila Saberi,Mehdi Amiri
出处
期刊:Corrosion Reviews
日期:2024-05-29
标识
DOI:10.1515/corrrev-2023-0152
摘要
Abstract To address the need for reduced vehicle weight and improved environmental sustainability, the automotive industry has increasingly turned to mixing lightweight materials and alloys with metal alloys. However, this integration of dissimilar materials has heightened the risk of galvanic corrosion. This study addresses the gap in modeling of galvanic corrosion under dynamic thin film electrolyte by incorporating data derived from real-world weather conditions and finite element simulations. The presented model successfully captures the trend of galvanic corrosion rate for a given atmospheric environmental condition. The model predictions are compared with experimental data in the literature. Good agreements are observed. The model is further used for prediction of galvanic corrosion of two identical vehicles located in two different geographic locations (i.e., Miami Beach in Florida and Wendover in Nevada) in the year 2021 leveraging weather station data. Additionally, a Bayesian estimation method is used to account for uncertainties in the model parameters and estimation of the probability of failure.
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