Issue
Korean Journal of Chemical Engineering,
Vol.35, No.3, 621-625, 2018
A reliability model for process systems under changing operating conditions
Reliability analysis of process systems, which is often based on a model of Weibull distribution, is semiquantitative at best because it uses constant parameters, requiring assumption of steady state operating conditions. A reliability model based on a variable scale parameter Weibull distribution is proposed in this work, in which a power law, the Arrhenius factor, and instantaneous amplitudes and frequencies of the operating condition variables are introduced. Numerical experiment indicates that when an operating condition variable fluctuates, the assumption of an average steady state operating condition can cause a serious error in reliability analysis. Therefore, the proposed method is expected to contribute to more quantitative risk assessment, and thus more rigorous safety analysis of process systems under changing operating conditions.
[References]
  1. API, Risk-Based Inspection Methodology: API Recommended Practice 581, 3rd Ed., American Petroleum Institute (2016).
  2. Helle HPE, Proc. 14th Middle East Corrosion Conference Exhibition, 133-MS-20 (2012).
  3. Kaley LC, API RP 581 Risk-Based Inspection Methodology - Documenting and Demonstrating the Thinning Probability of Failure Calculations, 3rd Ed., Trinity Bridge, LLC (2014).
  4. ReliaSoft, Life Data Analysis Reference, ReliaSoft Corporation (2015).
  5. Escobar LA, Meeker WQ, Statistical Science, 21(4), 552, 2006
  6. Arnold J, Blattau N, Hillman C, Sweatman K, Reliability testing of Ni-modified SnCu and SAC305: Accelerated thermal cycling, IPC/JEDEC Lead Free Conference, March (2008).
  7. Choi SH, J. Korean Institute Gas, 7(4), 20, 2003
  8. Huang NE, Shen Z, Long SR, Wu MC, Shih HH, Zheng Q, Yen NC, Tung CC, Liu HH, Proc. R. Soc. Lond. A, 454, 903, 1998
  9. Schlurmann T, Rogue Waves 2000, 157 (2001).
  10. Brown F, National Board Bulletin, 65(3), 12, 2010
  11. Park K, Korean J. Chem. Eng., 34(3), 642, 2017
  12. Jung S, Korean J. Chem. Eng., 33(1), 1, 2016