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Radiant systems are an energy-efficient method for providing cooling to building occupants through active surfaces. To assess the impact of the radiant environment on occupants in space, we develop a ray-tracing simulation, which accounts for longwave radiation. Thermal radiation shares many characteristics with visible light, and thus is highly dependent on surface geometry. Much research effort has been dedicated to characterizing the behavior of visible light in the built environment and its impact on the human experience of space. However, longwave infrared radiation's effect on the human perception of heat is still not well characterized or understood within the design community. In order to make the embodied effect of radiant surfaces' geometry and configuration legible, we have developed a Mean Radiant Temperature (MRT) simulation method, which is based on a ray-tracing technique. It accounts for the detailed geometry of the human body and its surrounding environment. We use a case study of a pavilion built with an envelope consisting of active cooling panels in Singapore. Using measured data for the surrounding surface temperatures in the pavilion, we explore the impact of both the active panels and the surrounding passive elements and thermal environment on a person's radiant heat exchange in different postures. The reflectivity and emissivity values of different surfaces are taken into account, and the ray-tracing process allows for multiple-bounce simulation. The model accounts for both longwave and shortwave radiation, and the simulation results are compared with field measurements for validation. The results are expressed both numerically and as spatial radiant-heat-maps. These show a variation of up to 11°C in MRT across the space studied. Furthermore, a digital manikin is used to assess the impact of the radiant cooling panels across the human body. The results show a 10°C variation in radiant temperature perceived by different regions of the body in one position. The findings reveal a significant heterogeneity of radiant heat transfer that current analysis methods typically overlook for both architectural space and the geometry of the human body. [ABSTRACT FROM AUTHOR]

This research proposes a Computation in Design (C-in-D) framework for design practices to consider the adoption of computational technologies in their design process. Examples of computational design technologies include but are not limited to computational algorithms, the Internet of Things (IoT), reality capture and digital fabrications. We develop the framework by categorizing design projects based on their physical scales, defining the work stages in a design project, and decomposing the design process into tasks and data flows. The computational design technologies can then be assessed by mapping its usage onto these data flows. The framework provides a basic structure for practices to customize and systematically assess the impacts of using computational design technologies in their design process. We demonstrate the C-in-D framework in three case studies, a sculpture design, an interior retrofit, and a form-based code development. The demonstration shows that web-based interactive parametric modeling and reality capture technologies can improve collaboration between the artist and modeler in the sculpture design project. IoT and optimization algorithms can improve the daylighting performance of the interior retrofit, and the use of Geographic Information System and reality capture technology can improve site analysis and visioning of the form-based code development process. The framework is a valuable tool for facilitating the adoption of new design technologies in practice. [ABSTRACT FROM AUTHOR]