Statistical analysis of a time series relevant to passive systems of nuclear power plants

A. Chandrakar (), D. Datta, A. K. Nayak and Gopika Vinod
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A. Chandrakar: Homi Bhabha National Institute
D. Datta: Bhabha Atomic Research Centre
A. K. Nayak: Bhabha Atomic Research Centre
Gopika Vinod: Bhabha Atomic Research Centre

International Journal of System Assurance Engineering and Management, 2017, vol. 8, issue 1, No 9, 89-108

Abstract: Abstract In this study, we present the methodology for fitting auto-regressive integrated moving average (ARIMA) model to one of the independent process parameter (atmospheric temperature) of passive safety systems. We also present how to generate the synthetic data of the modelled time series of this independent process parameter, which can be used for uncertainty propagation and reliability estimation of passive safety systems. As an illustration to the methodology of model fitting and synthetic data generation, a time series of monthly-maximum atmospheric temperature of district Chittaurgarh (Rajasthan, India) has been considered. With the help of methodology, a non-contiguous ARIMA model of AR (1,3,6,9,12), MA (1,3,6,9,12) has been found to represent the differenced (at lags 12) stationary series of monthly-maximum atmospheric temperature. A synthetic series of length 1224 months have been generated based on the finalized ARIMA model.

Keywords: Passive safety system; APSRA; APSRA+; ARIMA (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s13198-016-0570-8

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