Mesoscopic structural modeling and thermal insulation performance analysis of rigid polyurethane foams for cryogenic LNG storage

Lightweight and highly insulating rigid polyurethane foams (RPUF) play a vital role in LNG storage, where low thermal conductivity is essential under cryogenic conditions. In this study, a novel cell adaptive-growth model (CAM) was proposed to replicate the natural foaming behavior of RPUF. This model simulates the random nucleation, expansion, and interaction of cells with fully controllable parameters, including average cell size, wall thickness, and the statistical distribution of cell diameters—capturing the stochastic nature of real foam structures. Based on the generated mesoscopic geometries, a comprehensive numerical study is conducted to evaluate the influence of cell morphology on macroscopic insulation performance under coupled conductive and radiative heat transfer conditions. The results reveal that larger average cell sizes and thinner wall structures significantly increase the effective thermal conductivity (ETC) of RPUF. In contrast, nonuniformity in cell size affects only local heat flux distribution without compromising bulk thermal performance due to structural homogenization. At cryogenic temperatures (The operating temperature of LNG storage tanks is 110 K), conduction dominates the heat transfer process, and wall thickness becomes the most critical design parameter. Finally, a cell morphology-based ETC model is established using numerical results to predict thermal conductivity across various mesostructures. This model offers a reliable theoretical framework for the precise thermal design and performance optimization of RPUF insulation systems, especially for underground LNG storage applications under extreme conditions.