Risk Analysis, Vol. 29, No. 5, 2009 DOI: 10.1111/j.1539-6924.2009.01221.x Uncertainty Analysis Based on Probability Bounds (P-Box) Approach in Probabilistic Safety Assessment Durga Rao Karanki, 1,2∗ Hari Shankar Kushwaha, 2 Ajit Kumar Verma, 3 and Srividya Ajit 3 A wide range of uncertainties will be introduced inevitably during the process of perform- ing a safety assessment of engineering systems. The impact of all these uncertainties must be addressed if the analysis is to serve as a tool in the decision-making process. Uncertainties present in the components (input parameters of model or basic events) of model output are propagated to quantify its impact in the final results. There are several methods available in the literature, namely, method of moments, discrete probability analysis, Monte Carlo simu- lation, fuzzy arithmetic, and Dempster-Shafer theory. All the methods are different in terms of characterizing at the component level and also in propagating to the system level. All these methods have different desirable and undesirable features, making them more or less useful in different situations. In the probabilistic framework, which is most widely used, probabil- ity distribution is used to characterize uncertainty. However, in situations in which one can- not specify (1) parameter values for input distributions, (2) precise probability distributions (shape), and (3) dependencies between input parameters, these methods have limitations and are found to be not effective. In order to address some of these limitations, the article presents uncertainty analysis in the context of level-1 probabilistic safety assessment (PSA) based on a probability bounds (PB) approach. PB analysis combines probability theory and interval arithmetic to produce probability boxes (p-boxes), structures that allow the comprehensive propagation through calculation in a rigorous way. A practical case study is also carried out with the developed code based on the PB approach and compared with the two-phase Monte Carlo simulation results. KEY WORDS: Epistemic and aleatory uncertainty; Monte Carlo simulation; probabilistic safety assess- ment; probability bounds; unavailability 1. INTRODUCTION Probabilistic safety assessment (PSA) is a con- ceptual and mathematical tool for deriving numerical estimates of risk for nuclear power plants (NPP) and 1 Paul Scherrer Institut. 2 Bhabha Atomic Research Centre, Mumbai, India. 3 Indian Institute of Technology—Bombay, Mumbai, India. ∗ Address correspondence to (current address) Dr. D. R. Karanki, Scientist, Risk and Human Reliability Group, Paul Scherrer In- stitut, Villigen PSI, 5232, Switzerland; durga k rao@yahoo.com; durga.karanki@psi.ch. industrial installations in general. PSA aims at iden- tifying the events and their combinations that can lead to severe accidents, assessing the probability of occurrence of each combination and evaluating the consequences. It is the most effective and efficient tool to assist decision making for safety and risk man- agement. It also provides insights into the strengths and weaknesses of design and operation of systems. It further supports risk/reliability-based inspection (RBI), technical specification optimization, accident management, etc. (1,2) In spite of several potential ap- plications of PSA, the uncertainties associated with parameters, models, phenomena, and assumptions 662 0272-4332/09/0100-0662$22.00/1 C  2009 Society for Risk Analysis