Sensitivity analysis of truck tyre hydroplaning speed using FEA-SPH model

Sayegh, Zeinab El; Gindy, Moustafa El

doi:10.1504/ijvsmt.2017.087988

Cited by 8 publications

(2 citation statements)

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“…The relative deviation between the empirical equation and simulation was 3.27%, which manifested the rationality of the hydroplaning model. Similar approaches were adopted by previous studies [ 28 , 29 ].…”

Section: Model Establishment and Verificationmentioning

confidence: 99%

Design of Nonsmooth Groove Tire Bioinspired by Shark-Skin Riblet Structure

Liu

Meng

et al. 2022

Applied Bionics and Biomechanics

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As one of the major causes of traffic accidents on wet roads, hydroplaning is prone to occur when the traveling speed of a vehicle rises so high that the hydrodynamic pressure between pavement and tires equals inflation pressure. In this condition, the vehicle nearly loses braking and steering capacity. Inspired by the superior drag reduction function of shark-skin riblet, the purpose of this study is to arrange bionic nonsmooth structures at the bottom of longitudinal grooves to promote the hydroplaning performance without affecting other tire performances. A finite element model of 185/60R15 tire was employed and its accuracy was verified by loading tests with CSS-88100 electronic testing instrument. Meanwhile, a fluid domain model was founded by computational fluid dynamics (CFD) method. The simulated critical hydroplaning speed was in accord with that obtained by the NASA empirical formula. Inspired by shark-skin riblet, three kinds of nonsmooth surfaces were exploited. In addition, the drag reduction rate, shear stress, and flow velocity distribution were compared for different grooves. Then, the optimized nonsmooth structure with the best drag reduction effect among three nonsmooth surfaces was arranged at the bottom of longitudinal grooves for bionic tire. Simulation results demonstrated that the bionic tire obviously decreased hydrodynamic lift and increased flow velocities. With these improvements, the critical hydroplaning speed was effectively improved for the bionic tire. These research results can be applied to the promotion of hydroplaning performance without degrading other tire performances.

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Section: Model Establishment and Verificationmentioning

confidence: 99%

Design of Nonsmooth Groove Tire Bioinspired by Shark-Skin Riblet Structure

Liu

Meng

et al. 2022

Applied Bionics and Biomechanics

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“…In this research, several terrains are modeled and calibrated to predict the tire-terrain interaction. The terrain modeled include soils such as dry and moist sand, clayey soil, dense sand and snow which are modeled using the isotropic-elastic-plastic-hydrodynamic relationship [10,11,14], while other terrains includes the water to model flooded surface [15][16][17]. Furthermore, the moisture effect of the soils is also taken into account by modeling moist sand and sandy loam with different moisture content [18].…”

Section: Sph Terrain Modelmentioning

confidence: 99%

Rolling resistance prediction of off-road tire using advanced simulation and analytical techniques

El-Sayegh

El–Gindy

2020

SN Appl. Sci.

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This paper focuses on developing a relationship between the rolling resistance coefficient of an off-road truck tire running over different terrains and at various operating conditions. The various operating conditions include tire speed, vertical load, and inflation pressure. The different terrains include dry and moist sand, flooded surface, snow, dense sand, clayey soil, and sandy loam with moisture. The off-road truck tire size 315/80R22.5 is modeled and validated using the finite element analysis technique, while the terrains are modeled and calibrated using smoothed-particle hydrodynamics technique. Artificial neural network and genetic algorithm (GA) are then used to develop a relationship between the rolling resistance coefficient and the terrains and operating conditions. The results of both algorithms are compared to the simulation results in terms of R-square goodness of fit and the mean squared error. Finally, a numerical equation is presented that determines the rolling resistance coefficient as a function of the terrains parameters and the operating conditions. It was found that both techniques provide a suitable solution, however, the GA provides an explicit equation.

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