Assessment of Thermo-Mechanical Fatigue in High-Performance Engines: Development of a Numerical Methodology to Investigate the Influence of Local Boiling

This study investigates the thermo-mechanical fatigue life of the cylinder head of a high-performance V8 engine, focusing on the structural impact of subcooled nucleate boiling. As increasing power densities demand superior heat rejection, understanding the effects of phase-change phenomena on thermal stress distribution becomes critical. The localized boiling boundary conditions are evaluated and mapped into the finite element solver via a dedicated Fortran subroutine, enabling a direct comparison between standard monophasic convection and boiling-enhanced heat transfer. To rigorously assess structural integrity, the fatigue analysis employs both the classical Goodman approach and the multiaxial Dang Van criterion. The adoption of the Dang Van criterion is crucial in this context: it accurately accounts for the non-proportional loading cycles and shifting principal stress axes inherent to complex engine thermo-mechanical interactions, providing a far more physically sound evaluation than simplified uniaxial models. Given the massive scale of the V8 engine geometry, the core computational contribution of this work is a custom Python-based post-processing framework. This workflow was developed to manage the memory constraints and extensive processing times associated with handling massive time-history datasets from large-scale finite element models. The pipeline begins with the systematic extraction of stress and temperature tensors. A dedicated algorithm extrapolates the results from the element integration points to the nodes and performs nodal averaging. This step is essential to accurately evaluate the stress state at the component's surface, which is the critical region for fatigue crack initiation, thereby yielding unique and representative loading histories for millions of nodes. To handle the resulting large-scale datasets, the framework utilizes advanced data compression and hierarchical structuring techniques. This architecture allows the multiaxial fatigue algorithms to operate entirely offline with high computational stability and reduced execution times. Finally, the computed Safety Factors are re-integrated into the solver's environment for direct 3D visualization. This scalable computational tool allows for a rapid evaluation of the engine's durability, aiming to determine whether the localized cooling benefits of nucleate boiling successfully enhance the overall safety margins, or if the induced thermal gradients lead to detrimental localized stress redistributions.