This research demonstrates coupled models integrating computational fluid dynamics and chrono-physiology, highlighting improved predictive metrics for vascular shear stress.
In building science, modelling human Chrono-physiology has progressed from basic two-node systems to detailed frameworks like JOS-3, which incorporate deep body and skin temperature layers to better simulate unsteady thermal states. Despite its significance, deep body temperature is paradoxically treated as a fixed set point, thereby limiting the realism of physiological simulations. Fluid-structure interaction (FSI) techniques offer insight into vascular shear stress but are constrained by computational challenges. Therefore, this study advocates for a more practical approach to human thermal analysis using coupled models that integrate computational fluid dynamics (CFD) and Chrono-physiology. Meshing complexities hinder whole-body CFD modelling, prompting the need for accessible macroscopic frameworks. Central to this research is the redefinition of “heat” in human-environment interactions. Demonstration cases evaluate vascular behavior under muscle activity using simplified equations and dimensionless heat flow metrics. By considering dynamic vessel deformation and adiabatic conditions, the study proposes a methodology for future hybrid models bridging physiology and environmental heat transport. These findings support the development of novel computational models for diverse applications, from building science to sports engineering. The proposed metrics show promise in enhancing predictive accuracy without requiring full-scale FSI computations, offering a foundational step toward three-dimensional physiological simulations.
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Tatsuhiro Yamamoto (2025) studied this question.
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