Numerical parameter sensitivity analysis of residual stresses induced by deep rolling for a 34CrNiMo6 steel railway axle

Abstract

To optimise the benefits of the deep-rolling process in the service life context of treated components, the process application must be investigated. In addition to the reduction in surface roughness and near-surface material strengthening, compressive residual stresses are introduced, which are primarily responsible for the increase in service life for components, especially in the case of high-strength steel materials. A numerical parameter sensitivity analysis is performed in order to investigate the introduced residual stresses in detail. For this purpose, a validated deep-rolling simulation model is used, which replicates the deep rolling of a railway axle made of the high-strength steel material 34CrNiMo6. The model is based on an elastic-plastic Chaboche material model parameterised on uniaxial tensile and LCF test results and validated with residual stress measurements. Using this model as a basis, the effect of the main process parameters deep-rolling force, feed rate, friction coefficient, number of overruns, tool geometry, and shaft geometry on the resulting residual stress state are investigated. The results reveal that the deep-rolling force has the most significant influence on the introduced residual stress state and should therefore be highlighted. In the case of applying a deep-rolling force of more than 10 kN, maximum compressive residual stresses of around − 1000 MPa are introduced, and a strong saturating behaviour is shown. Maximum compensating tensile residual stresses of + 100 MPa occur below the surface. The main influence of the deep-rolling force is the effective depth achieved, which is determined by the depth of the zero crossing. This varies from 1 mm with an applied force of 2 kN to more than 3.5 mm with 20 kN. Furthermore, the results are analysed to conclude suggestions for the process’s applicability, and a proposal for an optimised deep-rolling treatment is presented. There multiple deep rolling with decreased deep-rolling forces is used to achieve a comparably optimised residual stress state. In summary, with the presented results, a contribution to a deeper understanding of the deep-rolling process can be achieved; the influence of the most important process parameters on the residual stress in-depth profiles is established; an optimisation proposal is presented; and correlations are found. Thus, the base work for further fatigue strength assessments and the optimisation of the deep-rolling process regarding the increase of service is laid.

Strain-Based Assessment to Evaluate Damage Caused by Deep Rolling

“…To determine the damage caused by deep rolling, the allowable number of load cycles N is determined for each deep rolling disc tool based on the strain amplitude that occurs. The simulation model validated with residual stress measurements is used to analyse the influence of deep rolling parameters on the introduced residual stresses [15]. The simulation model basically consists of a simplified cuboid section of the railway axle and deep rolling disc tools.…”

“…In [15], the influence of deep rolling parameters and an optimization proposal regarding the introduced residual stresses is investigated. The most influential parameters, specifically the deep rolling force and feed rate, and the proposed optimisation are selected and investigated in this study.…”

“…Finally, the influence of optimising the deep rolling application presented in [15] on the induced damage is investigated. It was found that repeated deep rolling with reduced deep rolling forces has a positive effect on the induced residual stress state.…”

“…In addition to the measurements, a numerical deep rolling simulation model is presented and validated with the residual stress measurements. The simulation model is used to investigate the influence of deep rolling parameters and optimisations on the residual stresses applied, and the results are presented in [15]. The influence of these on cracking behaviour [16] and fatigue strength [17] is also investigated.…”

Deep Rolling Techniques: A Comprehensive Review of Process Parameters and Impacts on the Material Properties of Commercial Steels

“…The FEA methodology developed was reported to be efficient for yielding faster simulation with higher accuracy of results. Some application-specific studies involving the simulation of DR of crankshafts [114,147,148], railway axels [109,149], cylinder inner surfaces [80,150], fine blanking punch edges [22], turbine/compressor blades [105,134], torsion bars [120], and welded joints [124,126,151] revealed the potential of numerical techniques for effective assessment and optimization of process parameters. However, the material models and boundary conditions along with process kinematics were reported to be the key factors that must be modeled appropriately to obtain a reliable conclusion.…”