Assesment of quality classification of green pellets for nuclear power plants using improved levenberg-marquardt algorithm

Benyamin Kusumo Putro, Rozandi Prarizky, Wahidin Wahab, Dede Sutarya, Lina

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Cylindrical uranium dioxide pellets, which are the main components for nuclear fuel elements in Light Water Reactor, should have a high density profile, uniform shape and quality for the safety used as a reactor fuel component. The quality of green pellets is conventionally monitored through a laboratory measurement of the physical pellets characteristics followed by a graphical chart classification technique. However, this conventional classification method shows some drawbacks, such as the difficulties on its usage, low accuracy and time consuming, and does not have the ability to adress the non-linearity and the complexity of the relationship between the pellet's quality variables and the pellett's quality. In this paper, an Improved Levenberg-Marquard based neural networks is used to classify the quality process of the green pellets. Robustness of this learning algorithm is evaluated by comparing its recognition rate to that of the conventional Back Propagation neural learning algorithm. Results show that the Improved Levenberg-Marquard algorithm outperformed the Back Propagation learning algorthm for various percentage of training/testing paradigm, showing that this system could be applied effectively for classification of pellet quality

Original languageEnglish
Title of host publicationProgress in Renewable and Sustainable Energy
Pages825-834
Number of pages10
DOIs
Publication statusPublished - 7 Jan 2013
Event2nd International Conference on Energy, Environment and Sustainable Development, EESD 2012 - Jilin, China
Duration: 12 Oct 201214 Oct 2012

Publication series

NameAdvanced Materials Research
Volume608-609
ISSN (Print)1022-6680

Conference

Conference2nd International Conference on Energy, Environment and Sustainable Development, EESD 2012
CountryChina
CityJilin
Period12/10/1214/10/12

Keywords

  • Back propagation neural networks
  • Improved levenberg-marquard algorithm
  • Pellet quality classification
  • Uranium dioxide pellets

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    Putro, B. K., Prarizky, R., Wahab, W., Sutarya, D., & Lina (2013). Assesment of quality classification of green pellets for nuclear power plants using improved levenberg-marquardt algorithm. In Progress in Renewable and Sustainable Energy (pp. 825-834). (Advanced Materials Research; Vol. 608-609). https://doi.org/10.4028/www.scientific.net/AMR.608-609.825