A Multi-Physics 3D Modeling Methodology for Multi-Cylinder Diesel Engine Thermal Management and Fatigue Life Prediction

Paper #:
  • 2015-01-0671

  • 2015-04-14
Jahangirian, S., Srivastava, A., Hosseini, S., Ballard, S. et al., "A Multi-Physics 3D Modeling Methodology for Multi-Cylinder Diesel Engine Thermal Management and Fatigue Life Prediction," SAE Int. J. Mater. Manf. 8(3):893-904, 2015, https://doi.org/10.4271/2015-01-0671.
Durability assessments of modern engines often require accurate modeling of thermal stresses in critical regions such as cylinder head firedecks under severe cyclic thermal loading conditions. A new methodology has been developed and experimentally validated in which transient temperature distributions on cylinder head, crankcase and other components are determined using a Conjugate Heat Transfer (CHT) CFD model and a thermal finite element analysis solution. In the first stage, cycle-averaged gas side boundary conditions are calculated from heat transfer modeling in a transient in-cylinder simulation. In the second stage, a steady-state CHT-CFD analysis of the full engine block is performed. Volume temperatures and surface heat transfer data are subsequently transferred to a thermal finite element model and steady state solutions are obtained which are validated against CFD and experimental results. With the goal of emulating an engine test strategy for durability under extreme warm up and cool down cycles, a transient thermal analysis is performed for several loading cycles. Simulated transient temperature traces demonstrate good agreement with time-varying thermocouple measurements on the cylinder head. Temperature distributions at many times during the thermal shock test are utilized to calculate thermal stresses followed by a fatigue life analysis. It is demonstrated that transient thermal stress modeling is critical for the fatigue predictions at some locations on the cylinder head. This comprehensive methodology significantly improves the fidelity of engine thermal management and durability prediction and reduces the cost of engine development under severe fatigue prone conditions.
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