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For thermal comfort research, globe thermometers have become the de facto tool for mean radiant temperature, tr, measurement. They provide a quick means to survey the radiant environment in a space with nearly a century of trials to reassure researchers. However, as more complexity is introduced to built environments, we must reassess the accuracy of globe measurements. In particular, corrections for globe readings taking wind into account rely on a forced convection heat transfer coefficient. In this study, we investigate potential errors introduced by buoyancy driven flow, or free convection, induced by radiant forcing of a black globe’s surface to a temperature different from the air. We discovered this error in an experimental radiant cooling system with high separation of air to radiant temperature. Empirical simulations and the data collected in a radiant cooling setup together demonstrate the influence of free convection on the instrument’s readings. Initial simulation and data show that tr measurements neglecting free convection when calculating tr from air temperatures of 2 K above tr could introduce a mechanism for globe readings to incorrectly track air temperatures. The experimental data constructed to test this hypothesis showed the standard correction readings are 1.94 ± 0.90 °C higher than the ground truth readings for all measurements taken in the experiment. The proposed mixed convection correction is 0.51 ± 1.07 °C higher than the ground truth, and is most accurate at low air speeds, within 0.25 ± 0.60 °C. This implies a potential systematic error in millions of measurements over the past 30 years of thermal comfort research. Future work will be carried out to experimentally validate this framework in a controlled climate chamber environment, examining the tradeoffs between accuracy and precision with globe thermometer measurements.

We present results of a radiant cooling system that made the hot and humid tropical climate of Singapore feel cool and comfortable. Thermal radiation exchange between occupants and surfaces in the built environment can augment thermal comfort. The lack of widespread commercial adoption of radiant-cooling technologies is due to two widely held views: 1) The low temperature required for radiant cooling in humid environments will form condensation; and 2) cold surfaces will still cool adjacent air via convection, limiting overall radiant-cooling effectiveness. This work directly challenges these views and provides proof-of-concept solutions examined for a transient thermal-comfort scenario. We constructed a demonstrative outdoor radiant-cooling pavilion in Singapore that used an infrared-transparent, low-density polyethylene membrane to provide radiant cooling at temperatures below the dew point. Test subjects who experienced the pavilion (n = 37) reported a “satisfactory” thermal sensation 79% of the time, despite experiencing 29.6 ± 0.9 °C air at 66.5 ± 5% relative humidity and with low air movement of 0.26 ± 0.18 m⋅s−1. Comfort was achieved with a coincident mean radiant temperature of 23.9 ± 0.8 °C, requiring a chilled water-supply temperature of 17.0 ± 1.8 °C. The pavilion operated successfully without any observed condensation on exposed surfaces, despite an observed dew-point temperature of 23.7 ± 0.7 °C. The coldest conditions observed without condensation used a chilled water-supply temperature 12.7 °C below the dew point, which resulted in a mean radiant temperature 3.6 °C below the dew point.

For sustainable building design, performance-based optimization incorporating parametric modelling and evolutionary optimization can allow architects to leverage building massing design to improve energy performance. However, two key challenges make such applications of performance-based optimization difficult in practice. First, due to the parametric modelling approaches, the topological variability in the building massing variants is often very limited. This, in turn, limits the scope for the optimization process to discover high-performing solutions. Second, for architects, the process of creating parametric models capable of generating the necessary topological variability is complex and time-consuming, thereby significantly disrupting the design processes. To address these two challenges, this paper presents a parametric massing algorithm based on the subtractive form generation principle. The algorithm can generate diverse building massings with significant topological variability by removing different parts from a predefined volume. Additionally, the algorithm can be applied to different building massing design scenarios without additional parametric modelling being required. Hence, using the algorithm can help architects achieve an explorative performance-based optimization for building massing design while streamlining the overall design process. Two case studies of daylighting performance optimizations are presented, which demonstrate that the algorithm can enhance the exploration of the potential in building massing design for energy performance improvements.

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