Development of a comprehensive method to analyse glazing systems with Parallel Slat Transparent Insulation material (PS-TIM)

In order to provide enhanced levels of indoor comfort and building energy conservation, significant improvements have been made in the design of glazed facades and window systems, yielding increases in thermal resistance while simultaneously maintaining access to daylight. Some of these approaches result in glazing systems with relatively complex structures and it is difficult to characterise their optical and thermal properties for use in building simulation. In this research, a comprehensive model has been developed to accurately predict the thermal and optical properties of complex glazing systems, and a workflow developed to yield detailed daylight and energy performance (heating, cooling and lighting) predictions of these systems when applied in buildings. Through this approach, the thermal characteristics of complex fenestration systems are obtained from a validated Computational Fluid Dynamics model, and a ray-tracing technique is used to obtain Bidirectional Scattering Distribution Function (BSDF) data to represent their optical characteristics. These characterises may be used in building simulation software (in this case EnergyPlus) to obtain building heating, cooling and lighting energy estimates for a room incorporating complex glazing systems. Detailed visual comfort predictions including useful daylight illuminance, daylight uniformity and glare may also be made, using a complementary optical model run using RADIANCE simulations. This workflow is implemented to investigate a room served by different Parallel Slat Transparent Insulation Materials (PS-TIM), which represents an example of a complex fenestration system. The workflow is used to explore the effect of slat pitch (i.e. the distance between neighbouring slats) on performance and was found to provide reasonable daylight and energy performance prediction. The results indicate that use of glazing systems with PS-TIM can provide homogenous daylight distribution and up to 33.6% energy reduction when the simulation is run using weather data for London.