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December 13, 2022 article Aachen paper

Machine learning based surrogate modelling for the prediction of maximum contact temperature in EHL line contacts

Tribology International, vol. 179, pp. 108166

DOI: 10.1016/j.triboint.2022.108166 OpenAlex

Authors 4

  1. Animesh Singh corresponding Aachen Institute for Machine Elements and Systems Engineering

    RWTH Aachen University

    Affiliation as printed

    RWTH Aachen University, Institute for Machine Elements and Systems Engineering, Schinkelstrasse 10, 52062 Aachen, Germany

  2. Marius Wolf

    Robert Bosch (Germany)

    Affiliation as printed

    Robert Bosch GmbH, Corporate Sector Research and Advance Engineering, Robert-Bosch-Campus 1, 71272 Renningen, Germany

  3. Georg Jacobs Aachen Institute for Machine Elements and Systems Engineering

    RWTH Aachen University

    Affiliation as printed

    RWTH Aachen University, Institute for Machine Elements and Systems Engineering, Schinkelstrasse 10, 52062 Aachen, Germany

  4. Florian König corresponding Aachen Institute for Machine Elements and Systems Engineering

    RWTH Aachen University

    Affiliation as printed

    RWTH Aachen University, Institute for Machine Elements and Systems Engineering, Schinkelstrasse 10, 52062 Aachen, Germany

Cited by 30 stored of 32

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References 52