This paper presents the integration of muscle fatigue modeling into the finite element solver PAK, based on an extended version of Hill’s phenomenological model. While traditional muscle models focus primarily on force generation, this study incorporates fatigue dynamics to provide a more realistic representation of muscle performance over time. By extending Hill’s three-component model to take into account different types of muscle fibers and their distinct fatigue characteristics, we improve the accuracy of computational muscle simulations.
The proposed approach employs functionally graded materials (FGM) to model heterogeneous muscle structures and utilizes an incremental-iterative finite element scheme to calculate equilibrium configurations. The developed model is validated through comparisons with experimental data, demonstrating its ability to capture key aspects of muscle contraction, force production, fatigue progression, and recovery.
The implementation of this model in PAK provides a powerful computational tool for biomechanical research, with potential applications in rehabilitation engineering, sports science, and musculoskeletal system simulations. Future work will focus on refining fatigue mechanisms and extending the model to simulate full musculoskeletal interactions. This study contributes to the advancement of computational biomechanics by enabling more accurate and physiologically relevant simulations of muscle function.
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