Materials Map

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (2/2 displayed)

  • 2024Numerical parameter sensitivity analysis of residual stresses induced by deep rolling for a 34CrNiMo6 steel railway axle5citations
  • 2023Experimental and numerical investigation of the deep rolling process focussing on 34CrNiMo6 railway axles7citations

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Chart of shared publication
Buzzi, Christian
2 / 6 shared
Leitner, Martin
2 / 66 shared
Pertoll, Tobias
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Seisenbacher, Benjamin
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Winter, Gerhard
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Dutzler, Andreas
1 / 2 shared
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2024
2023

Co-Authors (by relevance)

  • Buzzi, Christian
  • Leitner, Martin
  • Pertoll, Tobias
  • Seisenbacher, Benjamin
  • Winter, Gerhard
  • Dutzler, Andreas
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article

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

  • Buzzi, Christian
  • Leitner, Martin
  • Pertoll, Tobias
  • Boronkai, László
Abstract

<p>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.</p>

Topics
  • impedance spectroscopy
  • surface
  • polymer
  • simulation
  • strength
  • steel
  • fatigue