Data-driven and physics-informed approaches for improving the performance of dynamic models of fluid film bearings

Shutin, Denis; Kazakov, Yuri; Stebakov, Ivan; Savin, Leonid

doi:10.1016/j.triboint.2023.109136

Tribology International

2024

DOI: 10.1016/j.triboint.2023.109136

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Data-driven and physics-informed approaches for improving the performance of dynamic models of fluid film bearings

Denis Shutin,

Yuri Kazakov,

Ivan Stebakov

et al.

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2024

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Cited by 2 publications

References 31 publications

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Methodology for Optimal Design of Active Fluid Film Bearings Considering Their Power Losses, Stability and Controllability: Theory and Experiment

Shutin,

Fetisov,

Litovchenko

et al. 2024

Energies

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This study addresses the problem of the automated synthesis of active fluid film bearings optimized for their adjustable design for new generations of turbomachines. The developed methodology proposes a criterion describing the ability of a bearing’s mechanical design to effectively implement control actions along with its energy efficiency and stability properties considered in a solved multi-objective optimization problem. The design process of actively lubricated journal bearings was investigated in the context of the proposed approach. A multi-objective optimization problem was solved with heuristic algorithms. An analysis of the results obtained with the MOGA and MOPSO algorithm revealed their shortcomings emerging in such problems. The MOPSO algorithm was improved to expand the range and uniformity of the distribution of solutions in the resulting Pareto set and to speed up calculations. Four bearing configurations with significantly different properties were selected from the obtained set of solutions, manufactured and experimentally tested, showing the good agreement between the actual parameters and those set during the design procedure. The results substantiate the applicability of the proposed theoretical and computational tools for designing active fluid film bearings with pre-specified properties to meet the comprehensive requirements of the energy efficiency, reliability and service life of turbomachines.

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Methodology for Optimal Design of Active Fluid Film Bearings Considering Their Power Losses, Stability and Controllability: Theory and Experiment

Shutin,

Fetisov,

Litovchenko

et al. 2024

Energies

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Multi-Objective Deep Q-Network Control for Actively Lubricated Bearings

Shutin,

Kazakov

2024

Lubricants

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This paper aims to study and demonstrate the possibilities of using reinforcement learning for the synthesis of multi-objective controllers for radial actively lubricated hybrid fluid film bearings (ALHBs), which are considered to be complex multi-physical systems. In addition to the rotor displacement control problem being typically solved for active bearings, the proposed approach also includes power losses due to friction and lubricant pumping in ALHBs among the control objectives to be minimized by optimizing the lubrication modes. The multi-objective controller was synthesized using the deep Q-network (DQN) learning technique. An optimal control policy was determined by the DQN agent during its repetitive interaction with the simulation model of the rotor system with ALHBs. The calculations were sped up by replacing the numerical model of an ALHB with its surrogate ANN-based counterpart and by predicting the shaft displacements in response to operation of two independent control loops. The controller synthesized considering the formulated reward function for DQN agent is able to find a stable shaft position that reduces power losses by almost half compared to the losses observed when using a passive system. It also is able to prevent the established limit of the minimum fluid film thickness being exceeded to avoid possible system damage, for example, when the rotor is unbalanced during the operation. Analysis of the development process and the results obtained allowed us to draw conclusions about the main advantages and disadvantages of the considered approach, and also allowed us to identify some important directions for further research.

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Data-driven and physics-informed approaches for improving the performance of dynamic models of fluid film bearings

Cited by 2 publications

References 31 publications

Methodology for Optimal Design of Active Fluid Film Bearings Considering Their Power Losses, Stability and Controllability: Theory and Experiment

Methodology for Optimal Design of Active Fluid Film Bearings Considering Their Power Losses, Stability and Controllability: Theory and Experiment

Multi-Objective Deep Q-Network Control for Actively Lubricated Bearings

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