Development and Validation of a Multi-Process Coupled Heat Transfer Model for Composite Insulation Quilts in Chinese Solar Greenhouses

To enhance the energy efficiency and environmental sustainability of solar greenhouses, precise microclimate control is essential. Composite thermal blankets critically influence heating demand and carbon footprint, yet conventional heat transfer models often neglect their internal structural characteristics, limiting simulation accuracy and optimization. Accordingly, a heat transfer model for composite thermal blankets was developed based on the law of energy conservation. The model discretizes the internal structure and integrates radiation, convection, conduction, and latent heat from condensation. It uniquely incorporates dynamic environmental factors and blanket properties including layered composition, porosity, and moisture content. Accuracy was validated through numerical simulations and field experiments in both traditional brick-wall and prefabricated flexible-wall solar greenhouses under various weather conditions. Validation showed strong agreement: for the brick-wall greenhouse, mean absolute error (MAE) was 1.21 °C, root mean square error (RMSE) 1.27 °C, and R2 0.97; for the flexible-wall greenhouse, MAE was 0.56 °C, RMSE 1.08 °C, and R2 0.85. These indicators confirm that the model reliably quantifies the impact of thermal insulation blanket material and structure on thermal performance, providing a basis for design optimization and a reduction in supplemental heating demand and carbon emissions. Further analysis examined the porosity and moisture effects on spray-bonded cotton, PE foam, and needle-punched felt. Under low moisture, higher porosity reduced thermal conductivity by up to 27.4%, 57.6%, and 52.4%, respectively. However, under high moisture, conductivity increased with porosity in materials with interconnected pores (spray-bonded cotton and Needle-punched felt) due to continuous water channels, while closed-cell PE foam conductivity continued decreasing. All materials showed linearly increasing conductivity with moisture content, with higher-porosity materials exhibiting greater sensitivity. For example, at porosities of 0.95, 0.95, and 0.85, moisture content rising from 0 to 0.225 increased conductivity by 264%, 209.6%, and 196.7%. This model provides a robust theoretical foundation for the scientific selection, structural optimization, and performance evaluation of composite thermal blankets in greenhouse applications.