STUDY ON THE INFLUENCE OF INTERNAL HEAT SOURCE CHARACTERISTICS AND DISTRIBUTION ON EFFECTIVE THERMAL CONDUCTIVITY OF CYLINDRICAL PARTICLE DISPERSED FUEL

Dispersing fuel particles within a matrix is a pivotal strategy for next-generation nuclear fuels. The internal temperature distribution of dispersion fuels is generally determined by the lumped parameter method, where Effective Thermal Conductivity (ETC) plays a critical role. Most computations yet use classical ETC models that lack consideration for internal heat sources, such as Maxwell-Eucken model, Chiew-Glandt model, and Effective Medium Theory. Some researchers have noted that classical models tend to underestimate the temperature when internal heat sources exist. Additionally, the stochastic distribution of heat sources introduces uncertainty in ETC values and, consequently, temperature predictions. This study focuses on cylindrical dispersions with randomly distributed particles, and employs the three-dimensional finite element method to calculate their ETCs. Various parameters, including component thermal conductivity, particle radius, volume fraction, and minimum particle spacing, are adjusted in different cases. For each parameter configuration, a large number of cases are randomly generated and simulated. Statistical characteristics of ETC results are analyzed. It reveals that, when internal heat sources are considered, the value and uncertainty of cylindrical dispersion ETC are influenced not only by volume fraction and component thermal conductivity, but also by the size of heat-generating particles and the minimum particle spacing. It underscores the necessity of characterizing and quantifying the distribution of internal heat sources when proposing novel ETC models for dispersion fuel.