Browsing by Author "Kelley, Josephine"

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    A Neural Network for Fast Modeling of Elastohydrodynamic Line Contacts
    (SSRN, 2024) Kelley, Josephine; Schneider, Volker; Marian, Max; Poll, Gerhard
    When modeling bearings in the context of entire transmissions or drivetrains, there are practical limits to the calculation resources available to calculate single bearings or even contacts. In settings such as these, curve-fitting methods have historically been deployed to estimate the elastohydrodynamic lubrication conditions. Machine learning methods have the potential to enable more sophisticated physical modeling in the context of larger computation environments, as the evaluation time of a trained model is typically negligible. We present a neural network that accurately evaluates the elastohydrodynamic film pressure and film thickness and explore its applications. Employing a neural network for the EHL film thickness calculations can enable a more physically precise modeling strategy at almost no additional computational cost.
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    Enhancing practical modeling: A neural network approach for locally-resolved prediction of elastohydrodynamic line contacts
    (2024) Kelley, Josephine; Schneider, Volker; Poll, Gerhard; Marian, Max
    When modeling bearings in the context of entire transmissions or drivetrains, there are practical limits to the calculation resources available to calculate single bearings or even contacts. In settings such as these, curve-fitting methods have historically been deployed to estimate the elastohydrodynamic lubrication conditions. Machine learning methods have the potential to enable more sophisticated physical modeling in the context of larger computation environments, as the evaluation time of a trained model is typically negligible. We present a neural network that accurately evaluates the locally variable elastohydrodynamic film pressure and film thickness distributions and explore its application to (e.g.) cylindrical roller bearings. Employing a neural network for the EHL film thickness calculations rather than the curve-fitted, simplified methods that are today’s standard can enable a more physically precise modeling strategy at almost no additional computational cost.
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    Novel capacitive measuring method to determine the complex impedance behavior of machine elements
    (2025) Schneider, Volker; Kelley, Josephine; Lehnhardt, Bela; Krewer, Marius; Bader, Norbert; Marx, Johannes; Poll, Gerhard; Marian, Max
    This study focuses on the analysis of the capacitive charging behavior of lubricant films in rolling bearings. A methodology is presented to process experimental data and apply mathematical models for extracting key parameters such as capacitance and parallel resistance of a lubricated bearing. The results provide insights into the electrical properties of the lubricant film, which are crucial for understanding the operational characteristics and durability of rolling bearings.