An occupant-centric approach for spatio-temporal visual comfort assessment and optimization in daylit sports spaces

Most visual comfort analysis is based on glare detections in limited fixed view scenes, but sports spaces present challenges given occupants' spatial and view directional variations in sports-related visual tasks. This paper proposes an occupant-centric approach for spatio-temporal visual comfort assessment and optimization (ST-VCAO) in daylit sports spaces by better considering the occupants' movement behaviour. It introduces the movable view scenes (MVS) in glare simulations and further accelerates the ST-VCAO process using the GPU-based parallel simulation combining response surface methodology. The proposed approach was applied to a real case building in Harbin, China. Annual daylight and glare simulations in two tennis courts with a total of 500 MVS were performed using Perez all-weather sky model with Chinese standard weather data. Results indicate that the proposed approach could sufficiently clarify the spatial variance and temporal variation of visual comfort across all MVS, which is appropriate for sports spaces. Meanwhile, using the developed workflow, the total computational time could be saved by 27.08% (Case 1) or 71.25% (Case 2). Amongst all Pareto solutions, the optimum alternative upon the worst one observed 200% (Case 1) or 50.7% (Case 2) higher visual comfort.

Automated summary

Most visual comfort analysis in sports spaces is limited to fixed view scenes, but this paper proposes an occupant-centric approach that considers the occupants' movement behavior in order to assess and optimize spatio-temporal visual comfort. By introducing movable view scenes and using GPU-based parallel simulation, the proposed approach can clarify the spatial and temporal variation of visual comfort across different views, while reducing computational time. Applied to a real case building, the results show significant improvements in visual comfort and computational efficiency.