Predictive modeling for dynamic heat load in frigid railway roadbeds: An energy-efficient approach

This research presents an innovative approach to dynamic heat load prediction in railway roadbeds situated in cold climates by incorporating the concept of heat load, traditionally used in the building sector. The method facilitates a comprehensive evaluation and energy-efficient control of heating systems in these specialized transportation infrastructures. Utilizing an integrated building simulation toolkit (DeST), a computational model for roadbed micro-elements is established, integrating weather, radiation, and shading models to simulate pertinent environmental factors. Employing the state space method, a thermal module calculates the base temperature of these micro-elements. Subsequent calculations determine the roadbed's target temperature and temporal heat load. Empirical data from the Harbin-Qiqihar high-speed railway validates the method, revealing strong alignment between computed and measured roadbed temperatures. Heat load peaks at 945 W/m and averages 335 W/m in freezing conditions. The method accounts for thermal hysteresis and variations related to roadbed orientation and depth. Regional statistics show a heat load range of 531 to 1,338 W/m and establish a direct correlation between heat load and latitude. The findings significantly enhance the ability to assess frost damage and design energy-efficient heating plans for railway roadbeds in frigid environments.