Predicting the effect of droplet geometry and size distribution on atmospheric corrosion

A new approach is proposed to numerically predict and study atmospheric corrosion for ranging droplet size distributions and the influence of the droplet geometry. The proposed methodology allows for a corrosion prediction based on observed droplet size distributions and droplet contact angles. A mechanistic finite element model, including...

Towards understanding and prediction of atmospheric corrosion of an Fe/Cu corrosion sensor via machine learning

The atmospheric corrosion of carbon steel was monitored by a Fe/Cu type galvanic corrosion sensor for 34 days. Using a random forest (RF)-based machine learning approach, the impacts of relative humidity, temperature and rainfall were identified to be higher than those of airborne particles, sulfur dioxide, nitrogen dioxide, carbon monoxide...