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Fragility assessment for electric cabinet in nuclear power plant using response surface methodology

  • Tran, Thanh-Tuan (Civil and Environmental Engineering, Kunsan National University) ;
  • Cao, Anh-Tuan (Civil and Environmental Engineering, Kunsan National University) ;
  • Nguyen, Thi-Hong-Xuyen (Civil and Environmental Engineering, Kunsan National University) ;
  • Kim, Dookie (Civil and Environmental Engineering, Kunsan National University)
  • Received : 2018.09.14
  • Accepted : 2018.12.29
  • Published : 2019.04.25

Abstract

An approach for collapse risk assessment is proposed to evaluate the vulnerability of electric cabinet in nuclear power plants. The lognormal approaches, namely maximum likelihood estimation and linear regression, are introduced to establish the fragility curves. These two fragility analyses are applied for the numerical models of cabinets considering various boundary conditions, which are expressed by representing restrained and anchored models at the base. The models have been built and verified using the system identification (SI) technique. The fundamental frequency of the electric cabinet is sensitive because of many attached devices. To bypass this complex problem, the average spectral acceleration $S_{\bar{a}}$ in the range of period that cover the first mode period is chosen as an intensity measure on the fragility function. The nonlinear time history analyses for cabinet are conducted using a suite of 40 ground motions. The obtained curves with different approaches are compared, and the variability of risk assessment is evaluated for restrained and anchored models. The fragility curves obtained for anchored model are found to be closer each other, compared to the fragility curves for restrained model. It is also found that the support boundary conditions played a significant role in acceleration response of cabinet.

Keywords

References

  1. J. Hur, E. Althoff, H. Sezen, R. Denning, T. Aldemir, Seismic assessment and performance of nonstructural components affected by structural modeling, Nucl. Eng. Technol. 49 (2) (2017) 387-394. https://doi.org/10.1016/j.net.2017.01.004
  2. T.T. Tran, T.H. Nguyen, D. Kim, Seismic incidence on base-isolated nuclear power plants considering uni-and bi-directional ground motions, J. Struct. Integr. Mainten. 3 (2) (2018) 86-94. https://doi.org/10.1080/24705314.2018.1461547
  3. M. Shinozuka, M.Q. Feng, H. Kim, T. Uzawa, T. Ueda, Statistical Analysis of Fragility Curves, 2003.
  4. A.S. Pisharady, P.C. Basu, Methods to derive seismic fragility of NPP components: a summary, Nucl. Eng. Des. 240 (11) (2010) 3878-3887. https://doi.org/10.1016/j.nucengdes.2010.08.002
  5. S. Kwag, D. Hahm, Development of an earthquake-induced landslide risk assessment approach for nuclear power plants, Nucl. Eng. Technol. 50 (8) (2018) 1372-1386. https://doi.org/10.1016/j.net.2018.07.016
  6. L. Eads, E. Miranda, H. Krawinkler, D.G. Lignos, An efficient method for estimating the collapse risk of structures in seismic regions, Earthq. Eng. Struct. Dyn. 42 (1) (2013) 25-41. https://doi.org/10.1002/eqe.2191
  7. A. Bakhshi, P. Asadi, Probabilistic evaluation of seismic design parameters of RC frames based on fragility curves, Sci. Iran. 20 (2) (2013) 231-241.
  8. M. Kohrangi, D. Vamvatsikos, P. Bazzurro, Site dependence and record selection schemes for building fragility and regional loss assessment, Earthq. Eng. Struct. Dyn. 46 (10) (2017) 1625-1643. https://doi.org/10.1002/eqe.2873
  9. N.N. Pujari, T.K. Mandal, S. Ghosh, S. Lala, Optimisation of IDA-based fragility curves, in: Safety, Reliab. Risk Life-cycle Perform. Struct. Infrastructures-proc. 11th Int. Conf. Struct. Saf. Reliab. ICOSSAR 2013, 2013, pp. 4435-4440.
  10. A.H.M. Muntasir Billah, M. Shahria Alam, Seismic fragility assessment of highway bridges: a state-of-the-art review, Struct. Infrastruct. Eng. 11 (6) (2015) 804-832. https://doi.org/10.1080/15732479.2014.912243
  11. B.R. Ellingwood, Earthquake risk assessment of building structures, Reliab. Eng. Syst. Saf. 74 (3) (2001) 251-262. https://doi.org/10.1016/S0951-8320(01)00105-3
  12. S. Günay, K.M. Mosalam, PEER performance-based earthquake engineering methodology, revisited, J. Earthq. Eng.. 17(6), 829-858. https://doi.org/10.1080/13632469.2013.787377
  13. I. Zentner, Numerical computation of fragility curves for NPP equipment, Nucl. Eng. Des. 240 (6) (2010) 1614-1621. https://doi.org/10.1016/j.nucengdes.2010.02.030
  14. B.R. Ellingwood, K. Kinali, Quantifying and communicating uncertainty in seismic risk assessment, Struct. Saf. 31 (2) (2009) 179-187. https://doi.org/10.1016/j.strusafe.2008.06.001
  15. S.H. Jeong, A.M. Mwafy, A.S. Elnashai, Probabilistic seismic performance assessment of code-compliant multi-story RC buildings, Eng. Struct. 34 (2012) 527-537. https://doi.org/10.1016/j.engstruct.2011.10.019
  16. C.B. Haselton, J.W. Baker, A.B. Liel, G.G. Deierlein, Accounting for groundmotion spectral shape characteristics in structural collapse assessment through an adjustment for epsilon, J. Struct. Eng. 137 (3) (2009) 332-344. https://doi.org/10.1061/(asce)st.1943-541x.0000103
  17. A.K. Kazantzi, D. Vamvatsikos, Intensity measure selection for vulnerability studies of building classes, Earthq. Eng. Struct. Dyn. 44 (15) (2015) 2677-2694. https://doi.org/10.1002/eqe.2603
  18. J.W. Baker, C. Allin Cornell, Spectral shape, epsilon and record selection, Earthq. Eng. Struct. Dyn. 35 (9) (2006) 1077-1095. https://doi.org/10.1002/eqe.571
  19. L. Eads, E. Miranda, D.G. Lignos, Average spectral acceleration as an intensity measure for collapse risk assessment, Earthq. Eng. Struct. Dyn. 44 (12) (2015) 2057-2073. https://doi.org/10.1002/eqe.2575
  20. S.K. Kunnath, Modeling of reinforced concrete structures for nonlinear seismic simulation, J. Struct. Integr. Mainten. 3 (3) (2018) 137-149. https://doi.org/10.1080/24705314.2018.1492669
  21. P.C. Nguyen, S.E. Kim, Distributed plasticity approach for time-history analysis of steel frames including nonlinear connections, J. Constr. Steel Res. 100 (2014) 36-49. https://doi.org/10.1016/j.jcsr.2014.04.012
  22. D.K. Kim, F. Wang, S. Chaudhary, Modal energy balance approach for seismic performance evaluation of building structures considering nonlinear behavior, J. Struct. Integr. Mainten. 1 (1) (2016) 10-17. https://doi.org/10.1080/24705314.2016.1153309
  23. M. Vejmelka, M. PALUS, K. SUSMAKOVA, Identification of nonlinear oscillatory activity embedded in broadband neural signals, Int. J. Neural Syst. 20 (02) (2010) 117-128. https://doi.org/10.1142/S0129065710002309
  24. G. Puscasu, B. Codres, Nonlinear system identification and control based on modular neural networks, Int. J. Neural Syst. 21 (04) (2011) 319-334. https://doi.org/10.1142/S0129065711002869
  25. F. Bayramov, C. Tasdemir, M.A. Tasdemir, Optimisation of steel fibre reinforced concretes by means of statistical response surface method, Cement Concr. Compos. 26 (6) (2004) 665-675. https://doi.org/10.1016/S0958-9465(03)00161-6
  26. L.E. Chavez-Valencia, A. Manzano-Ramirez, E. Alonso-Guzman, M.E. Contreras-Garcia, Modelling of the performance of asphalt pavement using response surface methodologydthe kinetics of the aging, Build. Environ. 42 (2) (2007) 933-939. https://doi.org/10.1016/j.buildenv.2005.10.013
  27. R. Brincker, L. Zhang, P. Andersen, Modal identification of output-only systems using frequency domain decomposition, Smart Mater. Struct. 10 (3) (2001), 441. https://doi.org/10.1088/0964-1726/10/3/303
  28. R.G. Budynas, J.K. Nisbett, Shigley's Mechanical Engineering Design, vol. 8, McGraw-Hill, New York, 2008.
  29. A.I. Khuri, S. Mukhopadhyay, Response surface methodology, Wiley Interdiscipl. Rev.: Comput. Stat. 2 (2) (2010) 128-149. https://doi.org/10.1002/wics.73
  30. B. Sadhukhan, N.K. Mondal, S. Chattoraj, Optimisation using central composite design (CCD) and the desirability function for sorption of methylene blue from aqueous solution onto Lemna major, Karbala Int. J. Modern Sci. 2 (3) (2016) 145-155. https://doi.org/10.1016/j.kijoms.2016.03.005
  31. M. Hussan, M.S. Rahman, F. Sharmin, D. Kim, J. Do, Multiple tuned mass damper for multi-mode vibration reduction of offshore wind turbine under seismic excitation, Ocean Eng. 160 (2018) 449-460. https://doi.org/10.1016/j.oceaneng.2018.04.041
  32. NUREG, U.S. Nuclear Regulatory Commission, Seismic Fragility of Nuclear Power Plant Components [PHASE II], NUREG/CR-4659, BNL-NUREG-52007, vols. 2-4, Department of Nuclear Energy, Brookhaven National Laboratory, Long Island, NY, 1987.
  33. P.P. Cordova, G.G. Deierlein, S.S. Mehanny, C.A. Cornell, Development of a twoparameter seismic intensity measure and probabilistic assessment procedure, in: The Second US-Japan Workshop on Performance-based Earthquake Engineering Methodology for Reinforced Concrete Building Structures, 2000, pp. 187-206. September.
  34. PEER. PEER NGA, Database. Pacific Earthquake Engineering Research Center, University of California, Berkeley. California, 2006. http://peer.berkeley.edu/nga/.
  35. J. Alam, D. Kim, B. Choi, Uncertainty reduction of fragility curve of intake tower using bayesian inference and Markov chain Monte Carlo simulation, Struct. Eng. Mech. 63 (1) (2017) 47-53. https://doi.org/10.12989/sem.2017.63.1.047
  36. M.S. Kircil, Z. Polat, Fragility analysis of mid-rise R/C frame buildings, Eng. Struct. 28 (9) (2006) 1335-1345. https://doi.org/10.1016/j.engstruct.2006.01.004
  37. R.P. Kennedy, M.K. Ravindra, Seismic fragilities for nuclear power plant risk studies, Nucl. Eng. Des. 79 (1) (1984) 47-68. https://doi.org/10.1016/0029-5493(84)90188-2
  38. J.W. Baker, Efficient analytical fragility function fitting using dynamic structural analysis, Earthq. Spectra 31 (1) (2015) 579-599. https://doi.org/10.1193/021113EQS025M
  39. C.A. Cornell, F. Jalayer, R.O. Hamburger, D.A. Foutch, Probabilistic basis for 2000 SAC federal emergency management agency steel moment frame guidelines, J. Struct. Eng. 128 (4) (2002) 526-533. https://doi.org/10.1061/(ASCE)0733-9445(2002)128:4(526)
  40. F. Jalayer, R. De Risi, G. Manfredi, Bayesian Cloud Analysis: efficient structural fragility assessment using linear regression, Bull. Earthq. Eng. 13 (4) (2015) 1183-1203. https://doi.org/10.1007/s10518-014-9692-z

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