Weibull model for RUL estimation at RSG-GAS reactor implemented on PA01-AP01 secondary pump-Reference-Cited by-同舟云学术

Weibull model for RUL estimation at RSG-GAS reactor implemented on PA01-AP01 secondary pump

Published:2023-01-06 Issue:2 Volume:88 Page:194-202
ISSN:0932-3902
Container-title:Kerntechnik
language:en
Short-container-title:

Author:

Sudadiyo Sri¹

Affiliation:

1. Research Center for Nuclear Reactor Technology , Research Organization for Nuclear Energy, National Research and Innovation Agency , Kawasan Puspiptek Gd. 80, 15310 , Tangerang Selatan , Indonesia

Abstract

Abstract Remaining Useful Life (RUL) estimation has been extensively explored in recent years. RUL could be used in deciding the maintenance timeline or inspection interval for the Reaktor Serba Guna – G. A. Siwabessy (RSG-GAS reactor). RSG-GAS reactor is a pool-type research reactor (built by the Interatom Internationale of Germany) and has been operating for more than 30 years to date. This study aimed to propose a Weibull model to find the RUL estimation value of the distribution parameters of the mean time to failure (MTTF). Therefore, the RSG-GAS reactor would be higher safety, longer lifetime and higher reliability with a smaller failure rate including for the PA01-AP01 secondary pump. The research methodology is processing data collection and estimating the parameters of the Weibull model to determine maintenance timeline or inspection intervals based on the MTTF value in case the reliability has reached the targeted percentage. Results show that the RUL estimation has been obtained for the RSG-GAS reactor. In the implemented study, a maintenance timeline has been stipulated for the PA01-AP01 secondary pump (with the model of KSB and type of CPK-S350-400) for the reliability of 90% and RUL estimation of circa 29 days.

Publisher

Walter de Gruyter GmbH

Subject

Safety, Risk, Reliability and Quality,General Materials Science,Nuclear Energy and Engineering,Nuclear and High Energy Physics,Radiation

Link

https://www.degruyter.com/document/doi/10.1515/kern-2022-0080/pdf

Reference16 articles.

1. Abdelrazek, I.D., Aly, M.N., Badawi, A.A., and Elnour, A.G.A. (2014). Benchmarking RSG-GAS reactor thermal hydraulic data using Relap5 code. Ann. Nucl. Energy 70: 36, https://doi.org/10.1016/j.anucene.2014.02.023.

2. Aven, T. (2013). Practical implications of the new risk perspectives. Reliab. Eng. Syst. Saf. 115: 136, https://doi.org/10.1016/j.ress.2013.02.020.

3. Beznosov, A.V., Lvov, A.V., Bokov, P.A., Bokova, T.A., and Razin, V.A. (2017). Experimental studies into the dependences of the axial lead coolant pump performance on the impeller cascade parameters. Nucl. Energy Technol. 3: 141, https://doi.org/10.1016/j.nucet.2017.05.009.

4. Boateng, P., Chen, Z., and Ogunlana, S.O. (2015). An analytical network process model for risks prioritization in megaprojects. Int. J. Proj. Manag. 33: 1795, https://doi.org/10.1016/j.ijproman.2015.08.007.

5. Chatzidakis, S., Hainoun, A., Doval, A., Alhabet, F., Francioni, F., Ikonomopoulos, A., and Ridikas, D. (2014). A comparative assessment of independent thermal-hydraulic models for research reactor: the RSG-GAS case. Nucl. Eng. Des. 268: 77–86, https://doi.org/10.1016/j.nucengdes.2013.11.076.