Preparation of coated fuel particles using the fluidized bed-chemical vapor deposition (FB-CVD) process is a key step in the production of nuclear fuel particles for high-temperature gas-cooled reactors (HTGRs). The p...Preparation of coated fuel particles using the fluidized bed-chemical vapor deposition (FB-CVD) process is a key step in the production of nuclear fuel particles for high-temperature gas-cooled reactors (HTGRs). The process of applying four coating layers on high-density uranium dioxide kernel particles results in an increase in particle size and a decrease in density. Most existing coating models at the single-particle scale assume homogeneous coating under thin layer conditions, which makes it difficult to accurately describe the actual evolution process of coated particles preparation. Therefore, this study proposed a particle-binding-type heterogeneous layer (PBT-HL) model combined the binding concept with the CFD-DEM method, which accounts for dynamic changes in the density of coated particles. Then model validation in terms of gas-solid interaction and mass transfer, and coating condition parameter analysis were given at first. The results showed that changes in operational parameters such as the layer density, loading capacity, and inlet gas velocity can affect the spouted fluidization state, further influencing the deposition rate and coating effectiveness. These findings also suggested that the heterogeneous coating model in binding configuration can be further developed to study the anisotropy of single-particle layer thickness quantitatively. In summary, the variable-density PBT-HL model approximates the actual coating layer preparation process more closely, aiding in the acquisition of coating process information and guiding the optimization of coating techniques. The proposed heterogeneous coating model also holds potential for further development to characterize the intra-particle uniformity and the conformality feature of FB-CVD technique in the future.展开更多
基金funded by National Natural Science Foundation of China(grant No.22478220)National Youth Talent Support Program of China(grant No.20224723061)+1 种基金National Major S&T Project of China(grant No.ZX06901)National Nuclear Technology Development Project of China(grant No.HNKF202314-48).
文摘Preparation of coated fuel particles using the fluidized bed-chemical vapor deposition (FB-CVD) process is a key step in the production of nuclear fuel particles for high-temperature gas-cooled reactors (HTGRs). The process of applying four coating layers on high-density uranium dioxide kernel particles results in an increase in particle size and a decrease in density. Most existing coating models at the single-particle scale assume homogeneous coating under thin layer conditions, which makes it difficult to accurately describe the actual evolution process of coated particles preparation. Therefore, this study proposed a particle-binding-type heterogeneous layer (PBT-HL) model combined the binding concept with the CFD-DEM method, which accounts for dynamic changes in the density of coated particles. Then model validation in terms of gas-solid interaction and mass transfer, and coating condition parameter analysis were given at first. The results showed that changes in operational parameters such as the layer density, loading capacity, and inlet gas velocity can affect the spouted fluidization state, further influencing the deposition rate and coating effectiveness. These findings also suggested that the heterogeneous coating model in binding configuration can be further developed to study the anisotropy of single-particle layer thickness quantitatively. In summary, the variable-density PBT-HL model approximates the actual coating layer preparation process more closely, aiding in the acquisition of coating process information and guiding the optimization of coating techniques. The proposed heterogeneous coating model also holds potential for further development to characterize the intra-particle uniformity and the conformality feature of FB-CVD technique in the future.
