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Comparative Analysis of a Numerical Method and Machine Learning Methods of Temperature Determination of a Doped Lubricating Layer with Experimental Data

  • EXPERIMENTAL MECHANICS, DIAGNOSTICS, AND TESTING
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Abstract

This article compares machine learning methods and a numerical method of determination of the doped lubricating layer with experimental data. Based on the sweep method, the one-dimensional Fourier heat equation with boundary and initial conditions is solved. As a result of comparing numerical and predictive data with experiments, it can be concluded that machine learning models are better at predicting results compared to numerical data.

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Authors and Affiliations

  1. Mechanical Engineering Research Institute of the Russian Academy of Sciences, 101990, Moscow, Russia

    A. Tokhmetova & A. Yu. Albagachiev

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  1. A. Tokhmetova
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  2. A. Yu. Albagachiev
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Correspondence to A. Tokhmetova.

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Translated by I. Moshkin

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Tokhmetova, A., Albagachiev, A.Y. Comparative Analysis of a Numerical Method and Machine Learning Methods of Temperature Determination of a Doped Lubricating Layer with Experimental Data. J. Mach. Manuf. Reliab. 52, 509–515 (2023). https://doi.org/10.3103/S1052618823050163

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  • DOI: https://doi.org/10.3103/S1052618823050163

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