Application of metaheuristics optimization in fuel rod design: A case study for helium charging pressure. (December 2021)

• Record Type: Journal Article
• Authors: Ghasabian, M.; Talebi, S.; Safarzadeh, O.
• Is Part Of: Progress in nuclear energy. Volume 142(2021)
• Publication Date: 2021-12
• Subjects: ABC algorithm -- Fuel rod -- Gap pressure; Nuclear energy -- Periodicals; Nuclear engineering -- Periodicals; 333.7924
• DOI: 10.1016/j.pnucene.2021.103982
• Languages: English
• ISSNs: 0149-1970

Abstract

Abstract: In this paper, it is suggested that the design parameters of the fuel rod can be optimized by using a metaheuristics algorithm so that the fuel rod is entirely safe in its normal operation and has a more efficient performance than usual. We applied Artificial Bee Colony (ABC) in fuel rod design. The fuel burnup, irradiation history, and operation data of the heavily burned fuel rod are obtained for typical VVER-1000 NPP by modeling core cycle design data from the first to the fourth cycle in the KASKAD package. This package intended for core calculation of VVER reactors consists of several primary modules such as BIPR-7A for assembly-wise core calculation, PERMAK-A for pin-by-pin core calculation, and TVS-M for macroscopic cross-section generation. The conventional initial gas pressure in the VVER reactor is 2 MPa. In this paper, considering the effects of gap gas pressure on the heat distribution of the fuel rod, the objective function has been selected to reduce the maximum temperature and the average temperature of the fuel pellet while maintaining safety standards. The optimal pressure obtained in this paper for this particular reactor with a specific power history is 0.467 MPa which is entirely safe in terms of safety throughout the reactor operation. It reduces the average fuel temperature during the process. Furthermore, the core calculations show that using this optimal pressure increases the quantity of energy produced. Fuel burnup increases at optimum pressure with an overall decrease in fuel temperature. Graphical abstract: Image 1 Highlights: The gas pressure in the gap is optimized for a VVER-1000 reactor. ABC metaheuristics optimization algorithm and fuel temperature objective function are used. Fuel rod performance is evaluated for efficiency and safety at optimum pressure. Fuel burnup increases at optimum pressure with an overall decrease in fuel temperature.