Application of Multi Objective Genetic Algorithm for Optimization of Core Configuration Design of a Fast Breeder Reactor

Jayalal, ML and Riyas, A and Jehadeesan, R and Devan, K and Sai Baba, M (2019) Application of Multi Objective Genetic Algorithm for Optimization of Core Configuration Design of a Fast Breeder Reactor. Computer Reviews Journal, 3. pp. 170-187.

[img]
Preview
Text
2019-CRJ-SaiBaba.pdf - Published Version

Download (689kB) | Preview
ContributionNameEmail
Abstract: The optimization problem of nuclear fuel management, reported in the present study aimed at arriving at the optimal number of subassemblies in the two fuel enrichment zones of the core of a 500 MWe Fast Breeder Reactor. The elitist multi-objective approach of Genetic Algorithm, namely Non-dominated Sorting Genetic Algorithm-II (NSGA-II), was employed in the study. The five parameters considered for optimization are: core excess reactivity, liner heat ratings of inner and outer fuel enrichment zones of the core, fissile material inventory, and breeding ratio. The results obtained from the study indicate that the algorithm is able to produce feasible solutions in an efficient manner while preserving the diversity amongst them. The fast convergence and the diversity-preserving feature of the algorithm are described. The major objective of the work is to study the viability of applying the NSGA-II into the nuclear fuel management problems of fast breeder reactors.
Item Type: Article
Keywords: Genetic Algorithm, Multi Objective Genetic Algorithm, Fast Breeder Reactor, Nuclear Fuel Management, Non dominated Sorting Genetic Algorithm-II (NSGA-II)
Subjects: School of Natural and Engineering Sciences > Environment
Date Deposited: 30 Jun 2020 07:12
Last Modified: 30 Jun 2020 07:12
Official URL: https://purkh.com/index.php/tocomp/article/view/33...
Related URLs:
    Funders: *
    Projects: *
    DOI:
    URI: http://eprints.nias.res.in/id/eprint/1950

    Actions (login required)

    View Item View Item