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

Subject Area Coating and Surface Technology
Term from 2018 to 2023
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 408781233
 
Final Report Year 2024

Final Report Abstract

The subject of this project was the continuation of the project "AlkoMo". The overall objective was the experimental and model-theoretical investigation of alcoholate corrosion on aluminum alloys in biogenic fuel blends in order to describe and predict the potential risk of corrosion and thus enable valid statements to be made on the material compatibility of relevant material/fuel combinations. The occurrence of so-called alcoholate corrosion in fuel-carrying components of vehicles and in the fuel (petro)chemical industry, for example, is directly related to an increase in the ethanol content of gasoline aimed at reducing emissions. Depending on the stress conditions, alcoholate corrosion can lead to critical failure of aluminum components due to interactions in the corrosion system. The activation of the degradation process depends on various factors, which were investigated experimentally in this project. In order to describe the interactions, a modeling approach was developed. In a first step, this approach illuminates the initiation of corrosion. In a second step, based on numerical simulations, it allows to predict the course of corrosion and to quantitatively identify critical process variables. The developed numerical model couples the chemical reaction kinetics with material properties and environmental conditions.

Publications

  • Modelling of microstructure-dependent localized alcoholate corrosion of Al by phase-field method, EuroCorr, virtual, 2021
    E. Gazenbiller, D. Hoeche, M. Zheludkevich, V. Arya, R. Reitz, T. Engler & M. Oechsner
  • Phase field modelling of alcoholate pitting corrosion of Al in non-aqueous ethanol-blended fuels, EuroCorr, Berlin, 2022
    E. Gazenbiller, D. Hoeche, M. Zheludkevich, V. Arya, R. Reitz & M. Oechsner
  • Exploring supervised machine learning algorithms for predicting pitting corrosion damage of AA1050 exposed to ethanol-containing fuels, DigitalTotal, Hamburg, 2023
    L. C. Jarren, E. Gazenbiller, V. Arya, R. Reitz, M. Oechsner, C. Feiler, M. L. Zheludkevich & D. Höche
  • Numerical modelling of alcoholate pitting corrosion of AA1050 in ethanol-blended fuels, ASST, Stockholm, 2023
    E. Gazenbiller, D. Hoeche, M. Zheludkevich, V. Arya, R. Reitz, T. Engler & M. Oechsner
  • Evaluation of innovative microreactor for examination of alkoxide pitting corrosion and data generation for numerical transient model. Materialwissenschaft und Werkstofftechnik, 55(3), 302-313.
    Arya, V.; Gazenbiller, E.; Reitz, R.; Oechsner, M. & Höche, D.
 
 

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