A review of RayMan in thermal comfort simulation: Development, applications and prospects

Thermal comfort simulation is critical for evaluating performance and energy consumption related to human comfort within built environments, particularly in mitigating the challenges posed by urban heat islands. Many software programs have been applied in urban microclimatology and computational simulation. This paper provides a comprehensive review of the RayMan model, a diagnostic tool widely used in urban microclimate studies to compute radiation fluxes and thermal comfort indices, and addresses its development, applications, and prospects in thermal comfort simulation. By analyzing 134 studies spanning diverse climate zones, this paper validates RayMan's accuracy in modeling microclimatic variations and its robustness under different conditions. However, notable limitations are also identified, such as inaccuracies in low solar altitude scenarios, challenges in complex urban geometries, and limitations in large-scale data processing. This review also emphasizes RayMan's adaptability through integration with complementary tools, such as ENVI-met and weather information platforms, to enhance its simulation capabilities. The findings provide valuable insights for researchers and practitioners aiming to leverage RayMan in thermal comfort studies and urban planning. The paper concludes with recommendations for future improvements, including the incorporation of advanced algorithms, dynamic vegetation models, and machine learning techniques to address current limitations and expand its applicability.