DOI QR코드

DOI QR Code

Pump availability prediction using response surface method in nuclear plant

  • Received : 2022.10.03
  • Accepted : 2023.09.03
  • Published : 2024.01.25

Abstract

The safety-related raw water system's strong operational condition supports the radiation defense and biological shield of nuclear plant containment structures. Gaps and failures in maintaining proper working condition of main equipment like pump were among the most common causes of unavailability of safety related raw water systems. We integrated the advanced data analytics tools to evaluate the maintenance records of water systems and gave special consideration to deficiencies related to pump. We utilized maintenance data over a three-and-a-half-year period to produce metrics like MTBF, MTTF, MTTR, and failure rate. The visual analytic platform using tableau identified the efficacy of maintenance & deficiency in the safety raw water systems. When the number of water quality violation was compared to the other O&M deficiencies, it was discovered that water quality violations account for roughly 15% of the system's deficiencies. The pumps were substantial contributors to the deficit. Pump availability was predicted and optimized with real time data using response surface method. The prediction model was significant with r-squared value of 0.98. This prediction model can be used to predict forth coming pump failures in nuclear plant.

Keywords

References

  1. M. Anantharaman, F. Khan, V. Garaniya, B. Lewarn, Reliability assessment of main engine subsystems considering turbocharger failure as a case study, TransNav, Int. J. Mar. Navig. Saf. Sea Transp. 12 (2018) 271-276, https://doi.org/10.12716/1001.12.02.06. 
  2. T. Thepmanee, A. Julsereewong, S. Pongswatd, PFD analysis of LNG fuel gas supply system for improving combined-cycle power plant safety, Energy Rep. 8 (2022) 684-690, https://doi.org/10.1016/j.egyr.2021.11.188. 
  3. S. Parasuraman, S. Ganapathiraman, A. Bhargavan, Multivariate regression studies for investigating and setting the action levels for the system water quality parameters of a nuclear plant, Water Environ. J. 36 (2022) 553-563, https://doi.org/10.1111/WEJ.12786. 
  4. M. Rezaie-Balf, N.F. Attar, A. Mohammadzadeh, M.A. Murti, A.N. Ahmed, C.M. Fai, N. Nabipour, S. Alaghmand, A. El-Shafie, Physicochemical parameters data assimilation for efficient improvement of water quality index prediction: comparative assessment of a noise suppression hybridization approach, J. Clean. Prod. 271 (2020), https://doi.org/10.1016/j.jclepro.2020.122576. 
  5. H.P. Jagtap, A.K. Bewoor, R. Kumar, M.H. Ahmadi, M. El Haj Assad, M. Sharifpur, RAM analysis and availability optimization of thermal power plant water circulation system using PSO, Energy Rep. 7 (2021) 1133-1153, https://doi.org/10.1016/j.egyr.2020.12.025. 
  6. P. Suganya, G. Swaminathan, B. Anoop, S.P.S. Prabhakaran, M. Kavitha, Prediction model for evaluating the raw water quality parameters and its significance in pipe failures of nuclear power plant, Lect. Notes Civ. Eng. 178 (2022) 335-345, https://doi.org/10.1007/978-981-16-5501-2_27. 
  7. AERB, Safety Classification and Seismic Categorisation for Structures, Systems and Components of Pressurised Heavy Water Reactors, 2003. http://www.aerb.gov.in/T/PUBLICATIONS/CODESGUIDES/SG-D-01.PDF. 
  8. H. Jagtap, A. Bewoor, R. Kumar, M.H. Ahmadi, G. Lorenzini, Markov-based performance evaluation and availability optimization of the boiler-furnace system in coal-fired thermal power plant using PSO, Energy Rep. 6 (2020) 1124-1134, https://doi.org/10.1016/j.egyr.2020.04.028. 
  9. L. Carnevali, L. Ciani, A. Fantechi, G. Gori, M. Papini, An efficient library for reliability block diagram evaluation, Appl. Sci. 11 (2021), https://doi.org/10.3390/app11094026. 
  10. S. Kabir, An overview of fault tree analysis and its application in model based dependability analysis, Expert Syst. Appl. 77 (2017) 114-135, https://doi.org/10.1016/j.eswa.2017.01.058. 
  11. E. So, M.C. Kim, Application of Chernoff bound to passive system reliability evaluation for probabilistic safety assessment of nuclear power plants, Nucl. Eng. Technol. 54 (2022) 2915-2923, https://doi.org/10.1016/J.NET.2022.03.011. 
  12. L.X. Chen, A.A. Chowdhury, C.M. Loulakis, M.A. Ownes, H. Thorisson, E. B. Connelly, C.J. Tucker, J.H. Lambert, Visualization of large data sets for project planning and prioritization on transportation corridors, 2015 Syst. Inf. Eng. Des. Symp. SIEDS 2015 (2015) 1-6, https://doi.org/10.1109/SIEDS.2015.7116954. 
  13. S.M.A. Rahman, I.M.R. Fattah, S. Maitra, T.M.I. Mahlia, A ranking scheme for biodiesel underpinned by critical physicochemical properties, Energy Convers. Manag. 229 (2021), 113742, https://doi.org/10.1016/J.ENCONMAN.2020.113742. 
  14. M.A. McGregor, MTBCF calculation for system with unequal periodic maintenance times, Proc. Annu. Reliab. Maintainab. Symp. (1990) 15-18, https://doi.org/10.1109/ARMS.1990.67923. 
  15. RAM Commander User Manual, 2014. www.aldservice.com. (Accessed 30 July 2021). 
  16. S. He, Y. Peng, Y. Jin, X. Shu, B. Wan, Reliability assessment of a full-ocean-depth pressure-retaining sediment sampler using fault tree analysis, J. Appl. Sci. Eng. 25 (2022) 173-185, https://doi.org/10.6180/jase.202202_25(1).0018. 
  17. AERB, AERB Safety Guide for Design Basis Events for PHWR, AERB Safety Guide No, AERB/SG/D-5, Mumbai, India, 2000. 
  18. D. Price, B. Kochunas, Performing linear regression with responses calculated using Monte Carlo transport codes, Nucl. Eng. Technol. 54 (2022) 1902-1908, https://doi.org/10.1016/J.NET.2021.11.003. 
  19. AERB, AERB Safety Guide for Ultimate Heat Sink and Associated Systems in PHWR, AERB Safety Guide No, AERB/SG/D-15, Mumbai, India, 2000. 
  20. AERB, Safety Code Design of PHWR Based Nuclear Power Plants, AERB/NPP-PHWR/SC/D (Rev. 1), Mumbai, India, 2009.