Numerical Prediction of Surface Wear and Roughness Parameters During Running-In for Line Contacts Under Mixed Lubrication

Zhang, Yazhao; Kovalev, Alexander; Hayashi, Noriyuki; Nishiura, Kensuke; Meng, Yonggang

doi:10.1115/1.4039867

Cited by 29 publications

(17 citation statements)

References 32 publications

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“…The feature of the wear model is able to account of loading sequence, which is different from the constant load assumption adopted in Archard's wear law. Zhang et al [234] presented a stochastic model for prediction of the evolutions of wear profile and surface height probability density function (PDF) of initial line contacts during running-in under mixed lubrication condition. The wear depth on the contact region was estimated according to the modified Archard's wear model using the asperity contact pressure.…”

Section: Wear Modelingmentioning

confidence: 99%

A review of recent advances in tribology

et al. 2020

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The reach of tribology has expanded in diverse fields and tribology related research activities have seen immense growth during the last decade. This review takes stock of the recent advances in research pertaining to different aspects of tribology within the last 2 to 3 years. Different aspects of tribology that have been reviewed including lubrication, wear and surface engineering, biotribology, high temperature tribology, and computational tribology. This review attempts to highlight recent research and also presents future outlook pertaining to these aspects. It may however be noted that there are limitations of this review. One of the most important of these is that tribology being a highly multidisciplinary field, the research results are widely spread across various disciplines and there can be omissions because of this. Secondly, the topics dealt with in the field of tribology include only some of the salient topics (such as lubrication, wear, surface engineering, biotribology, high temperature tribology, and computational tribology) but there are many more aspects of tribology that have not been covered in this review. Despite these limitations it is hoped that such a review will bring the most recent salient research in focus and will be beneficial for the growing community of tribology researchers.

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Section: Wear Modelingmentioning

confidence: 99%

A review of recent advances in tribology

et al. 2020

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“…(6)(7)(8)(9) are limited to statistically independent rough surfaces. After wearing-in, a Gaussian distribution may not be present [32,33]. Consequently, the modelling of worn-in asperity contacts with the GT-model may lead to inaccuracies.…”

Section: Statistical Contact Model According Tomentioning

confidence: 99%

“…The procedure is further explained in Refs. [17,32]. Furthermore, the extended Reynold's equation is modified by substituting the nominal gap height h by an average gap height h according to Wu and Zheng [50], which is the mean distance of the centerlines when the deformation due to asperity collision is considered.…”

Section: Mixed Ehl-simulationmentioning

confidence: 99%

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Numerical prediction of the frictional losses in sliding bearings during start-stop operation

2020

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With the increased use of automotive engine start-stop systems, the numerical prediction and reduction of frictional losses in sliding bearings during starting and stopping procedures has become an important issue. In engineering practice, numerical simulations of sliding bearings in automotive engines are performed with statistical asperity contact models with empirical values for the necessary surface parameters. The aim of this study is to elucidate the applicability of these approaches for the prediction of friction in sliding bearings subjected to start-stop operation. For this purpose, the friction performance of sliding bearings was investigated in experiments on a test rig and in transient mixed elasto-hydrodynamic simulations in a multi-body simulation environment (mixed-EHL/MBS). In mixed-EHL/MBS, the extended Reynold’s equation with flow factors according to Patir and Cheng has been combined on the one hand with the statistical asperity contact model according to Greenwood and Tripp and on the other hand with the deterministic asperity contact model according to Herbst. The detailed comparison of simulation and experimental results clarifies that the application of statistical asperity contact models with empirical values of the necessary inputs leads to large deviations between experiment and simulation. The actual distribution and position of surface roughness, as used in deterministic contact modelling, is necessary for a reliable prediction of the frictional losses in sliding bearings during start-stop operation.

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“…According to the references, the friction of piston ring-cylinder liner could account about 50 percent of the total mechanical friction of an internal combustion engine [1][2][3]. In order to obtain the better tribological performance, the scholars are focusing on establishing friction and wear model to investigate the relationship between friction and energy consumption of the ICEs [4][5][6][7][8], and the effect of lubrication on friction of piston rings-cylinder liner was studied [9,10]. To monitor the wear state, some scholars analyzed the wear information of abrasive particles in the oil, and the wear of the ICEs was evaluated [11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Wear assessment model for cylinder liner of internal combustion engine under fuzzy uncertainty

Kang

Lü

Luo

et al. 2021

Mechanics & Industry

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The wear of the piston ring-cylinder system is inevitable in the operation of the internal combustion engines (ICEs). If wear exceeds the maximum, the piston ring-cylinder system will be failure. A novel wear assessment model is proposed based on the support vector regression, and the fuzzy uncertainty is modeled to describe the random behavior under small sample. To verify the proposed model, the sample data of cylinder liner wear is applied. For best results, the particle swarm optimization (PSO) algorithm is used to optimize the model parameters. A back propagation neural network (BPNN) is employed to verify the effectiveness of the proposed model. The results show that the novel support vector regression has better prediction accuracy than other methods for cylinder wear in this paper, the proposed model can evaluate the cylinder liner wear of the ICEs effectively. The work provides a technical support for evaluating the service performance of the piston ring-cylinder liner and a reference for regular maintenance of the ships.

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Numerical Prediction of Surface Wear and Roughness Parameters During Running-In for Line Contacts Under Mixed Lubrication

Cited by 29 publications

References 32 publications

A review of recent advances in tribology

A review of recent advances in tribology

Numerical prediction of the frictional losses in sliding bearings during start-stop operation

Wear assessment model for cylinder liner of internal combustion engine under fuzzy uncertainty

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