Estimation of railway wheel running temperatures using a hybrid approach

Vakkalagadda, M.R.K.; Vineesh, K.P.; Racherla, Vikranth

doi:10.1016/j.wear.2015.03.026

Cited by 30 publications

(26 citation statements)

References 34 publications

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“…Surfaces other than the contact patch is allowed with convection mode of heat transfer. The heat transfer coefficient (hc) is chosen to be 12 W/m 2 K, and the ambient temperature is taken to be 30°C (Vakkalagadda et al, 2015). Thus, obtained temperature field acts as the boundary condition for structural analysis.…”

Section: Finite Element Modelmentioning

confidence: 99%

Rolling Contact Fatigue Life of Rail for Different Slip Conditions

Srivastava

Sarkar

Meesala

et al. 2017

Lat. Am. j. solids struct.

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A three-dimensional elastic-plastic finite element analysis (FEA) is carried out to estimate the rolling contact fatigue (RCF) crack initiation life for varied slip range on the rail arising from operational variations. The wheel load produces Hertzian contact pressure. Variation in engine traction induces slip variations that evolves thermal load in terms of heat flux. The aperiodic rolling of wheel on rail develops non-proportional multiaxial fatigue loading. Present study combines these effects by translating the wheel load on rail for multiple (twelve) pass in presence of thermal load, contact pressure and traction through a proposed simulation. The temperature dependent Chaboche material model with nonlinear kinematic hardening law is implemented to estimate the stresses and plastic strains governing the multiaxial fatigue condition at the interface. The location of maximum von Mises stress, found at a material point on or a layer below the rail-head, contemplates the fatigue crack initiation site. A coded search algorithm helps to identify the critical plane of crack initiation corresponding to the maximum fatigue parameter (FP). In contrast to available predictions of RCF life considering contact pressure and/or traction or frictional heat in isolation, present study combines all these loads together and provides a more realistic result by numerical simulation.

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Section: Finite Element Modelmentioning

confidence: 99%

Rolling Contact Fatigue Life of Rail for Different Slip Conditions

Srivastava

Sarkar

Meesala

et al. 2017

Lat. Am. j. solids struct.

View full text Add to dashboard Cite

show abstract

“…Heat generated at rail-wheel and wheel-brake block interfaces are estimated using the train running model presented in Vakkalagadda et al [2]. Rail chill effect and heat partitioning at wheel-brake block interfaces are estimated using the approach presented in Vakkalagadda et al [3]. As per this, fraction of heat generated at brake block-wheel interface entering the wheel is taken as 0.985 for composite brake blocks.…”

Section: Finite Element Modelingmentioning

confidence: 99%

“…As per this, fraction of heat generated at brake block-wheel interface entering the wheel is taken as 0.985 for composite brake blocks. In axi-symmetric analyses, of the kind considered here, heat loss to rail can be accounted by using an effective convective heat transfer coefficient h ax on rail-wheel contact width that depends on train speed, axle tonnage, wheel and rail profiles, and wheel diameter (see Vakkalagadda et al [3]). More specifically, we take…”

Section: Finite Element Modelingmentioning

confidence: 99%

“…The finite element model predictions matched quite accurately with the measured wheel temperatures. Details of finite element model validation are presented in Vakkalagadda et al [3].…”

Section: Finite Element Modelingmentioning

confidence: 99%

“…Prediction of wheel temperatures, for a given train running and braking history, is challenging due to several factors including evolving contact at brake block-wheel and rail-wheel interfaces. In this work, a hybrid approach reported and validated in Vakkalagadda et al [3] is used to estimate wheel temperatures and thermal stresses for a given running and braking scenario. Limited research exists in open literature on the estimation of service induced residual stresses and wheel gauge as a function of relevant factors.…”

Section: Introductionmentioning

confidence: 99%

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