Finite element simulation of high-entropy alloys: Process-structure-property modelling across manufacturing and mechanical performance

High-entropy alloys (HEAs) combine strength, ductility, and thermal stability rarely achieved simultaneously by conventional alloys, but their compositional complexity and multiphase microstructures make experimental characterisation alone insufficient for understanding and optimising their behaviour. This review synthesises how finite element simulation has been used across the HEA development lifecycle, with emphasis on two areas where the field has matured fastest: manufacturing-process modelling (casting, spark plasma sintering, and additive manufacturing) and mechanical-performance prediction (elasticity, plasticity, fracture, fatigue, and creep). For each process and failure mode, the review extracts the quantitative trends reported in the literature, including stress, strain, and temperature magnitudes, reported model-experiment agreement and quantitative prediction errors where available, and processing-parameter sensitivities, rather than only describing model architectures. Crystal plasticity finite element modelling (CPFEM) is identified as the connective methodology linking manufacturing-induced microstructure to mechanical response, and the integration of machine learning (ML) with FEA, ranging from data-driven constitutive modelling to surrogate-based screening, is critically assessed, while physics-informed and inverse-design approaches are identified as emerging directions whose HEA-specific validation remains limited. The review argues that the principal barrier to predictive, integrated computational materials engineering (ICME) for HEAs is not a shortage of modelling techniques but the scarcity of validated thermomechanical property databases and in-situ experimental validation, and it concludes with a focused set of priorities for closing this gap.