Lifetime Assessment of Cylinder Heads for Efficient Heavy Duty Engines Part II: Component-Level Application of Advanced Models for Thermomechanical Fatigue Life Prediction of Lamellar Graphite Cast Iron GJL250 and Vermicular Graphite Cast Iron GJV450 Cylinder Heads

Paper #:
  • 2017-01-0346

Published:
  • 2017-03-28
DOI:
  • 10.4271/2017-01-0346
Citation:
Hazime, R., Seifert, T., Kessens, J., and Ju, F., "Lifetime Assessment of Cylinder Heads for Efficient Heavy Duty Engines Part II: Component-Level Application of Advanced Models for Thermomechanical Fatigue Life Prediction of Lamellar Graphite Cast Iron GJL250 and Vermicular Graphite Cast Iron GJV450 Cylinder Heads," SAE Int. J. Engines 10(2):350-358, 2017, doi:10.4271/2017-01-0346.
Pages:
9
Abstract:
A complete thermomechanical fatigue (TMF) life prediction methodology is developed for predicting the TMF life of cast iron cylinder heads for efficient heavy duty internal combustion engines. The methodology uses transient temperature fields as thermal loads for the non-linear structural finite-element analysis (FEA). To obtain reliable stress and strain histories in the FEA for cast iron materials, a time and temperature dependent plasticity model which accounts for viscous effects, non-linear kinematic hardening and tension-compression asymmetry is required. For this purpose a unified elasto-viscoplastic Chaboche model coupled with damage is developed and implemented as a user material model (USERMAT) in the general purpose FEA program ANSYS. In addition, the mechanism-based DTMF model for TMF life prediction developed in Part I of the paper is extended to three-dimensional stress states under transient non-proportional loading conditions. The material properties of the plasticity model are determined for lamellar graphite cast iron GJL250 and vermicular graphite cast iron GJV450 from isothermal and non-isothermal uniaxial tests. The methodology is applied to obtain a TMF life prediction on two cast iron cylinder heads for heavy duty diesel engine applications made from both cast iron materials. It is shown that the life predictions using the developed methodology correlate very well with observed lives from two bench tests in terms of location as well as number of cycles to failure.
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