Hypo-elastohydrodynamic lubrication of journal bearings with deformable surface

Ren, Guojun

doi:10.1016/j.triboint.2022.107787

Cited by 8 publications

(3 citation statements)

References 18 publications

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“…One type of modification addressing this phenomenon is detailed in the paper. 18 All these factors, whether conventional or novel, are particularly relevant in the context of heavily loaded bearings and contribute to the significant computational complexity mentioned earlier. This computational complexity underscores the intricacies involved in modeling journal bearings under various operating conditions, serving as a testament to the ongoing research efforts aimed at enhancing the understanding and predictive capabilities in this critical field.…”

Section: Journal Bearing Modelingmentioning

confidence: 99%

AI techniques for evaluating misaligned journal bearing performance: An approach beyond the Sommerfeld number

Rossopoulos,

Papadopoulos

2024

Proceedings of the Institution of Mechanical Engineers, Part J:

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This paper presents two novel artificial intelligence-based approaches for evaluating the performance of heavily loaded marine journal bearings including shaft misalignment. Traditionally, the Sommerfeld number has been used as a key parameter to evaluate the performance similarity between different bearings. However, this method has limitations, particularly when dealing with complex elastic geometries, heavily loaded journal bearings and shaft misalignment. The first proposed approach leverages neural networks to analyze key bearing performance parameters and provide a more accurate and comprehensive assessment of bearing performance similarity, including additional parameters beyond the Sommerfeld number limitations. The second method utilizes artificial intelligence convolutional networks to assess the bearing similarity based on their simulated pressure profiles under isoviscous and isothermal hydrodynamic lubrication regime. The effectiveness of the proposed methods is demonstrated and compared to the traditional Sommerfeld number method, discussing various potential applications and extensions of this concept.

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Section: Journal Bearing Modelingmentioning

confidence: 99%

AI techniques for evaluating misaligned journal bearing performance: An approach beyond the Sommerfeld number

Rossopoulos,

Papadopoulos

2024

Proceedings of the Institution of Mechanical Engineers, Part J:

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“…Although such polymers exhibit high deformation rate under load, they are often chosen for their tribological properties. Ren et al [25] and Serdjuchenko et al [26] also studied the behavior of non-metallic elastic WLBs. Other researchers that have provided insight on the operation of polymerbased water-lubricated bearings are Liu et al [27], who studied WLBs operating in high angular velocities and Litwin et al [28,29,30], who conducted experiments for several different types of materials, in order to compare the most widely used WLB materials and For the case of 100 µm roughness height, Figures 11 and 12 depict the turbulent dissipation rate (e) and dynamic pressure distributions, respectively.…”

Section: Fluid-structure Interactionmentioning

confidence: 99%

Investigation of Cavitated Flow in Water-Lubricated Bearings Considering Surface Roughness, Thermal, and Elastic Effects

Charamis,

Nikolakopoulos

2024

Lubricants

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Contrary to conventional journal bearings, which operate using oil-based substances, water-lubricated bearings (WLBs) utilize water and, thus, constitute a more environmentally responsible solution. The shipping industry, among others, as already been introduced to this technology with a lot of commercial ships using water-lubricated stern tube systems; in other cases, hydropower plants manage to keep up with the strict environmental regulations by implementing the use of WLBs in water turbines. However, there are a lot of challenges when it comes to transitioning from conventional bearings to water-based ones. Such challenges are caused by the low viscosity of water and lead to phenomena of high complexity. Such phenomena are related but not limited to cavitation and turbulent flow due to the interaction between the lubricating water and bearing surface. In this study, a numerical method will be used to simulate the fluid film and bearing geometries in order to perform a thermo-elastohydrodynamic (TEHD) analysis. The dynamic characteristics of the bearing will be calculated and the results will be discussed. The novelty of the study is evident in but not limited to the determination of the elastic deformation of a WLB during operation, as well as the effect of surface roughness, cavitation, and thermal effects on bearing characteristics.

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“…Tooth surface gluing is the direct contact between two tooth surfaces due to rupture of the oil film under pressure, which results in adhesion and tearing. Depending on the mechanism of production, there are two types of gluing: hot gluing and cold gluing [49]. In the event of gear wear, vibration, or overload, the worn gear surface will generate high frictional heat.…”

Section: (C) Tooth Surface Gluingmentioning

confidence: 99%

Analysis of Wind Turbine Equipment Failure and Intelligent Operation and Maintenance Research

Peng

Shangguan

et al. 2023

Sustainability

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Power generation from wind farms is growing rapidly around the world. In the past decade, wind energy has played an important role in contributing to sustainable development. However, wind turbines are extremely susceptible to component damage under complex environments and over long-term operational cycles, which directly affects their maintenance, reliability, and operating costs. It is crucial to realize efficient early warning of wind turbine failure to avoid equipment breakdown, to prolong the service life of wind turbines, and to maximize the revenue and efficiency of wind power projects. For this purpose, wind turbines are used as the research object. Firstly, this paper outlines the main components and failure mechanisms of wind turbines and analyzes the causes of equipment failure. Secondly, a brief analysis of the cost of wind power projects based on equipment failure is presented. Thirdly, the current key technologies for intelligent operation and maintenance (O&M) in the wind power industry are discussed, and the key research on decision support systems, fault diagnosis models, and life-cycle costs is presented. Finally, current challenges and future development directions are summarized.

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Hypo-elastohydrodynamic lubrication of journal bearings with deformable surface

Cited by 8 publications

References 18 publications

AI techniques for evaluating misaligned journal bearing performance: An approach beyond the Sommerfeld number

AI techniques for evaluating misaligned journal bearing performance: An approach beyond the Sommerfeld number

Investigation of Cavitated Flow in Water-Lubricated Bearings Considering Surface Roughness, Thermal, and Elastic Effects

Analysis of Wind Turbine Equipment Failure and Intelligent Operation and Maintenance Research

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