Alcoholate (Dry) Corrosion: Critical damage mechanisms and their progression identified and described via experiment and modeling (AlcoMo)

• Applicants: Dr. Daniel Höche; Professor Dr.-Ing. Matthias Oechsner
• Subject Area: Coating and Surface Technology
• Term: from 2018 to 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 408781233

Subject of this research proposal is to seek the opportunity to continue the (ongoing) project "AlkoMo", which is funded by the DFG, for another two years.The overall objective is the experimental and model-theoretical investigation of alcoholate (dry) corrosion on aluminium alloys in biogenic fuel blends in order to describe and predict the risk potential for corrosion and thus to enable valid statements to be made on the material compatibility of relevant material-fuel combinations. The physical and chemical fundamentals as well as the relevance of the topic have already been discussed in detail in the first application. During the first 20 months of the current project, a statistical method was developed to initiate the initiation phase of the initially local attack during alcoholate corrosion in anhydrous ethanol using the example of pure aluminium EN AW-1050A. Furthermore, the growth could be characterized by a Gumbel analysis of the pit size maxima, so that a prediction of the maximum lateral expansion of isolated and localized attack sites at a given medium temperature is possible. In principle, these methods can also be applied to alloyed material-fuel combinations and fuel blends close to the field. In addition to the development of a suitable evaluation methodology, the microreactor outlined in the initial application was designed, manufactured, commissioned and successfully validated. First promising experiments were carried out, which allow a considerably more sensitive application of the stress parameters as well as a more precise detection and generation of input data for further model development.To create a completely physically based and time-dependent finite element model the evaluation plan defined in the initial application was modified and an intermediate step based on data analysis and neural networks was introduced, which allows to extract differential equations and constants from data series. This innovative and promising method is now able to cope with the multitude of variable parameters and the resulting complexity of the system under investigation. It also allows to develop a model based on physical relationships for predicting the corrosion behavior of aluminum materials in biogenic fuels.The goals are directly based on the goals of AlkoMo, but have been adapted by the simulative, experimental and methodological knowledge gained during the project as well as the newly available innovative experimental equipment: 1. identification of corrosion initiation and characterization of corrosion progress.2. model adaptation and experimental validation3. development of a physicochemical description approach for corrosion initiation4. transfer of results and final evaluation

• DFG Programme: Research Grants
• Co-Investigator: Dr.-Ing. Christopher Tom Engler