Thermal-Performance Evaluation of Bicycle Helmets for Convective and Evaporative Heat Loss at Low and Moderate Cycling Speeds

Abstract

The main objective of the study was to investigate the thermal performance of five (open and closed) bicycle helmets for convective and evaporative heat transfer using a nine-zone thermal manikin. The shape of the thermal manikin was obtained by averaging the 3D-point coordinates of the head over a sample of 85 head scans of human subjects, obtained through magnetic resonance imaging (MRI) and 3D-printed. Experiments were carried out in two stages, (i) a convective test and (ii) an evaporative test, with ambient temperature maintained at 20.5 ± 0.5 °C and manikin skin temperature at 30.5 ± 0.5 °C for both the tests. Results showed that the evaporative heat transfer contributed up to 51%–53% of the total heat loss from the nude head. For the convective tests, the open helmet A1 having the highest number of vents among tested helmets showed the highest cooling efficiency at 3 m/s (100.9%) and at 6 m/s (101.6%) and the closed helmet (A2) with fewer inlets and outlets and limited internal channels showed the lowest cooling efficiency at 3 m/s (75.6%) and at 6 m/s (84.4%). For the evaporative tests, the open helmet A1 showed the highest cooling efficiency at 3 m/s (97.8%), the open helmet A4 showed the highest cooling efficiency at 6 m/s (96.7%) and the closed helmet A2 showed the lowest cooling efficiency at 3 m/s (79.8%) and at 6 m/s (89.9%). Two-way analysis of variance (ANOVA) showed that the zonal heat-flux values for the two tested velocities were significantly different (p < 0.05) for both the modes of heat transfer. For the convective tests, at 3 m/s, the frontal zone (256–283 W/m2) recorded the highest heat flux for open helmets, the facial zone (210–212 W/m2) recorded the highest heat flux for closed helmets and the parietal zone (54–123 W/m2) recorded the lowest heat flux values for all helmets. At 6 m/s, the frontal zone (233–310 W/m2) recorded the highest heat flux for open helmets and the closed helmet H1, the facial zone (266 W/m2) recorded the highest heat flux for the closed helmet A2 and the parietal zone (65–123 W/m2) recorded the lowest heat flux for all the helmets. For evaporative tests, at 3 m/s, the frontal zone (547–615 W/m2) recorded the highest heat flux for all open helmets and the closed helmet H1, the facial zone (469 W/m2) recorded the highest heat flux for the closed helmet A2 and the parietal zone (61–204 W/m2) recorded the lowest heat flux for all helmets. At 6 m/s, the frontal zone (564–621 W/m2) recorded highest heat flux for all the helmets and the parietal zone (97–260 W/m2) recorded the lowest heat flux for all helmets.

Analytical-Numerical Model for Temperature Prediction of a Serpentine Belt Drive System

“…All the values in matrix TR bR thus become TR bR. The heat dissipation on the belt surfaces can be easily calculated [31], thereby yielding function k(TR bR ,…). The thermal balance of the belt can be expressed as…”

“…Hence, the density of air is computed by using the incompressible ideal gas equation and its change is negligible. The finite volume method used in this analysis solves the governing equations in integral form, as shown below [31]: j j ∂ Figure 9. Polyhedral mesh for the numerical analysis.…”

“…q is the occurring heat flux. The additional SST k-ω model transport equations, which are turbulence kinetic energy and specific dissipation rate equations, are also necessary [31]:…”

Special Issue on “Human Health Engineering”

“…Contributions can focus on sensors, wearable hardware, algorithms, or integrated monitoring systems. We organized the different papers according to their contributions to the main parts of the monitoring and control engineering scheme applied to human health applications, namely papers focusing on measuring/sensing of physiological variables [24][25][26][27][28][29][30][31], contributions describing research on the modelling of biological signals [32][33][34][35][36][37][38], papers highlighting health monitoring applications [39][40][41][42], and finally examples of control applications for human health [43][44][45][46][47][48]. In comparison to biomedical engineering, we envision that the field of human health engineering also covers applications on healthy humans (e.g., sports, sleep, and stress) and thus not only contributes to develop technology for curing patients or supporting chronically ill people, but also for disease prevention and optimizing human well-being more generally.…”

“…Since their method is based on cheap PPG sensing elements that can be integrated in wearables, this approach can significantly contribute to (preventive) health monitoring as, compared to classical (expensive) cuff-based methods, as it allows 24/7 measurements. The work of Mukunthan et al [27] describes the use of a nine-zone thermal manikin head for measuring convective and evaporative heat losses from a human head wearing a bicycle helmet. They demonstrated that the design of the helmet, mainly characterized by the number and position of vent openings and the presence of internal air channels, has a significant effect on the heat losses of a human head when covered by a bicycle helmet.…”