The Influence of Measurement Uncertainties and Input Parameters on Hydrostatic Bearing Performance: Analytical, Experimental, and Numerical Comparison

conference paper

en

Design and real-time control of hydrostatic bearings (HS) demand accurate models capable of reliably predicting bearing behavior under varying operational conditions. Analytical models have proven insufficient to estimate key parameters such as carrying capacity, recess pressure, film thickness, or flow rate simultaneously. To address this limitation, Computational Fluid Dynamics (CFD) has emerged as a valuable tool in recent years. However, the accuracy of operational data measurements, used to set numerical and analytical models, plays a significant role in uncertainty propagation. This study concerns an experimental campaign and the development of a CFD model in the OpenFOAM® environment. To reproduce the experimental conditions, numerical and analytical models are set using different input parameters, i.e. flow rate or recess pressure, considering extreme operational conditions tied to the accuracy of experimental data. Results reveal that, while average CFD values exhibit consistent errors in estimating operational parameters, experimental and numerical uncertainty ranges overlap under the investigated operational conditions. In contrast, analytical estimation leads to clear discrepancies, even when considering measurement uncertainties. Furthermore, concerning carrying capacity estimation, recess pressure emerges as the input parameter yielding more satisfactory results. The findings emphasize the importance of considering measurement uncertainties in setting numerical and analytical models for HS bearings, providing valuable insights for their accurate design and real-time control.

Design and real-time control of hydrostatic bearings (HS) demand accurate models capable of reliably predicting bearing behavior under varying operational conditions. Analytical models have proven insufficient to estimate key parameters such as carrying capacity, recess pressure, film thickness, or flow rate simultaneously. To address this limitation, Computational Fluid Dynamics (CFD) has emerged as a valuable tool in recent years. However, the accuracy of operational data measurements, used to set numerical and analytical models, plays a significant role in uncertainty propagation. This study concerns an experimental campaign and the development of a CFD model in the OpenFOAM® environment. To reproduce the experimental conditions, numerical and analytical models are set using different input parameters, i.e. flow rate or recess pressure, considering extreme operational conditions tied to the accuracy of experimental data. Results reveal that, while average CFD values exhibit consistent errors in estimating operational parameters, experimental and numerical uncertainty ranges overlap under the investigated operational conditions. In contrast, analytical estimation leads to clear discrepancies, even when considering measurement uncertainties. Furthermore, concerning carrying capacity estimation, recess pressure emerges as the input parameter yielding more satisfactory results. The findings emphasize the importance of considering measurement uncertainties in setting numerical and analytical models for HS bearings, providing valuable insights for their accurate design and real-time control.

Hydrostatic lubrication, Thin lubricant layer simulation, CFD simu-lation, OpenFOAM

19.10.2024

Springer

978-3-031-70461-1

Latest Advancements in Mechanical Engineering. ISIEA 2024. Lecture Notes in Networks and Systems

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