Exposure of Al alloy structures to ethanol containing fuels at elevated temperatures leads to high risk of rapid pitting corrosion and component failure. Understanding of decisive mechanisms and driving forces is necessary for predicting critical conditions for corrosion occurrence.
The interplay between microstructural alloy aspects and chemical/electrochemical reactions in the fluid phase and at the interface is key for capturing critical aspects of the corrosion. We use a combinative statistical, machine learning and Finite Element Method approach for modelling the problem cases at Hereon whereas the experimental part is conducted by TU Darmstadt partners.
Department of Interface Modelling