INTEGRATED EXPERIMENTAL AND COMPUTATIONAL ANALYSIS OF MIXED CONVECTION HEAT TRANSFER FROM THE HUMAN HEAD, FULL BODY, AND CLOTHING MICROCLIMATE

Abstract

Thermal comfort and heat exchange between the human body and its environment are critical factors in building design, apparel engineering, occupational safety, and the assessment of human performance in diverse climates. Accurately predicting the convective, radiative, and total heat transfer rates for the human body, and specific body segments such as the head, requires an integrated approach that combines controlled experimental measurements with high-accuracy computational fluid dynamics (CFD) modeling. The present study develops and validates a comprehensive computational fluid dynamics (CFD) framework designed to investigate mixed convection heat transfer from two critical human geometries: the human head and the full standing human body. These models represent both localized and whole-body thermal behavior, capturing the distinct effects of buoyancy-driven flows interacting with forced convection. The objective is to derive semi-empirical correlation for the average Nusselt number, providing predictive capability across a wide range of Reynolds, Grashof, and Richardson numbers. This correlation is developed with careful attention to it applicability for complex geometries, such as the head, where curvature, orientation, and local flow separation introduce additional complexities absent in simpler canonical cases like spheres or flat plates. Building on this, the study further extends its scope to investigate heat transfer through the skin–clothing microclimate, using a fabric-covered cylinder model to represent clothed body segments. In this context, the fabric is treated as a porous medium, with permeability and porosity controlling the degree of airflow penetration and transport through the clothing layer. This addition captures a critical component of real-world heat exchange: the interaction between the skin surface, entrapped air gaps, and textile layers. By modeling the porous zone in detail, including parameters such as viscous and inertial resistance coefficients, porosity, absorption, scattering, and radiation exchange, the study ensures that both transport through the fabric and radiative transfer within the pores are accounted for. This approach enables evaluation of clothing’s thermal insulation in a physically realistic manner. A high-resolution 3D CFD model of a nude thermal manikin head was created from 3D body scans, meshed with unstructured tetrahedral grids refined near the surface, and simulated in ANSYS Fluent (2020 R2) using the RNG k-ε turbulence model with enhanced wall treatment and discrete ordinates radiation modeling. Air properties were evaluated at the film temperature, and mesh independence testing ensured accuracy. Predicted convective heat transfer coefficients (h_c ) were validated against five experimental cases (0.05–0.5 m/s air velocity; 5–30°C temperature difference), with deviations typically within ±2%. Total and radiative heat fluxes varied spatially, peaking at the nose and forehead due to flow acceleration and plume interaction. The methodology was extended to a full standing body to compare whole-body and segmental heat transfer. Natural convection coefficients matched published mid-range values (≈3.76 W/m²K), while forced convection coefficients scaled with air velocity in agreement with ASHRAE and Fanger correlations. Radiative coefficients (≈4.93 W/m²K) matched established data. Velocity field analyses revealed buoyancy-driven plume tilting and recirculation patterns that shifted with Richardson number, supporting the mixed-convection modeling approach. A 2D arm–clothing microclimate model quantified the effects of air gap, fabric conductivity, and emissivity. Results showed smaller gaps reduced natural convection but increased conduction, while higher conductivity and emissivity improved heat loss, demonstrating applicability to clothing design. This integrated experimental–numerical approach links localized, whole-body, and clothing-related heat transfer, enabling accurate prediction across diverse conditions. Findings support applications in comfort assessment, thermal safety, and protective clothing design, with recommendations for future work including transient modeling, evaporative cooling, and complex garment simulations.