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Modeling Steam Generator System of Pressurized Water Reactor Using Fuzzy Arithmetic

  • Wan Munirah Wan Mohamad
  • Tahir AhmadEmail author
  • Azmirul Ashaari
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 652)

Abstract

Steam generator system is known as the bridge between the primary and secondary systems for phase changes from water into steam. The aim of this paper is to identify the best input that influence the steam generator system in the process of changing from water to steam, to ensure the process is efficient. The method consists of the transformation method of fuzzy arithmetic which is to compute the measure of influence for each parameter in the model system. The result is then verified against simulation and analysis.

Keywords

Fuzzy arithmetic Transformation method Measure of influence and steam generator 

Notes

Acknowledgments

The authors are thankful to Universiti Teknologi Malaysia for providing necessary environment and technical support for research.

References

  1. 1.
    Ashaari, A., Ahmad, T., Shamsuddin, M., Omar, N.: Modeling steam generator system of pressurized water reactor using fuzzy state space. Int. J. Pure Appl. Math. 103, 106–115 (2015)CrossRefGoogle Scholar
  2. 2.
    Glasstone, S., Sesonske, A.: Nuclear Reactor Engineering: Reactor Systems Engineering. Springer Science & Business Media (2012)Google Scholar
  3. 3.
    Wan Mohamad, W.M., Ahmad, T., Ahmad, S., Ashaari, A.: Simulation of furnace system with uncertain parameter. Malays. J. Fundam. Appl. Sci. 11, 5–9 (2015)Google Scholar
  4. 4.
    Wan Mohamad, W.M., Ahmad, T., Ashaari, A., Abdullah, A.: Modeling fuzzy state space of reheater system for simulation and analysis. AIP Conf. Proc. 1605, 488–493 (2014)Google Scholar
  5. 5.
    Hanss, M.: The transformation method for the simulation and analysis of systems with uncertain parameters. Fuzzy Sets Syst. 130, 277–289 (2002)MathSciNetCrossRefzbMATHGoogle Scholar
  6. 6.
    Hanss, M.: Applied Fuzzy Arithmetic. Springer, Heidelberg (2005)zbMATHGoogle Scholar
  7. 7.
    Hanss, M., Oliver, N.: Simulation of the human glucose metabolism using fuzzy arithmetic. In: 19th International Conference of the North American Fuzzy Information Processing Society, NAFIPS, pp. 201–205. IEEE (2000)Google Scholar
  8. 8.
    Hanss, M., Oliver, N.: Enhanced parameter identification for complex biomedical models on the basis of fuzzy arithmetic. In IFSA World Congress and 20th NAFIPS International Conference, Joint 9th, pp. 1631–1636. IEEE (2001)Google Scholar
  9. 9.
    Haag, T., Hanss, M.: Comprehensive modeling of uncertain systems using fuzzy set theory. Nondeterministic Mech. 539, 193–226 (2012)MathSciNetCrossRefzbMATHGoogle Scholar
  10. 10.
    Ismail, R.: Fuzzy state space modeling for solving inverse problems in multivariable dynamic systems. Ph.D Thesis, Universiti Teknologi Malaysia, Faculty of Science (2005)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2016

Authors and Affiliations

  • Wan Munirah Wan Mohamad
    • 1
  • Tahir Ahmad
    • 1
    • 2
    Email author
  • Azmirul Ashaari
    • 1
  1. 1.Department of Mathematical Science, Faculty of ScienceUniversiti Teknologi MalaysiaUTM SkudaiMalaysia
  2. 2.Centre for Sustainable Nanomaterials, Ibnu Sina Institute for Scientific and Industrial ResearchUniversiti Teknologi MalaysiaUTM SkudaiMalaysia

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