Methodology for PSA Uncertainty Estimation and Application in Risk-Informed Decision-Making

Uncertainties are very important in risk analysis and should be considered in the decisionmaking process. This paper proposes the methodology for estimation of PSA uncertainties in riskinformed decision-making. The methodology allows solving the complex task of identifying the sources of uncertainties, assessing their range, and providing an approach for consideration of PSA results with uncertainties in combination with other factors underlying risk-informed decisionmaking. The levels of uncertainties are proposed to be classified using the variation factor. The authors applied the developed methodology to assess alternatives of post-Fukushima safety measures.Невизначеності є дуже важливими в імовірнісному аналізі безпеки (ІАБ) та мають бути враховані в процесі прийняття рішень. У статті запропоновано методологію оцінки невизначеності ІАБ у процесі різик-інформованого прийняття рішень і класифікацію рівня невизначеності введенням коефіцієнта варіації. Методологія дає змогу вирішити комплексне завдання з виявлення джерел невизначеності, оцінки їх значення та врахування невизначеності результатів ІАБ у поєднанні з іншими чинниками, що лежать в основі прийняття рішення. Автори застосували розроблену методологію для оцінки альтернатив пост-фукусімських заходівНеопределенности очень важны в вероятностном анализе безопасности (ВАБ) и должны учитываться в процессе принятия решений. В статье предлагаются методология оценки неопределенностей ВАБ при принятии риск-информированных решений и классификация уровней неопределенностей с использованием коэффициента вариации. Методология позволяет решить комплексную задачу по определению источников неопределенностей, оценке их величины и учету неопределенностей результатов ВАБ в сочетании с другими факторами, лежащими в основе принятия риск-информированных решений. Авторы применили разработанную методологию для оценки альтернативных постфукусимских мероприятий

Uncertainty and sensitivity of neutron kinetic parameters in the dynamic response of a PWR rod ejection accident coupled simulation

In nuclear safety analysis, it is very important to be able to simulate the different transients that can occur in a nuclear power plant with a very high accuracy. Although the best estimate codes can simulate the transients and provide realistic system responses, the use of nonexactmodels, together with assumptions and estimations, is a source of uncertainties whichmust be properly evaluated. This paper describes a Rod Ejection Accident (REA) simulated using the coupled code RELAP5/PARCSv2.7 with a perturbation on the cross-sectional sets in order to determine the uncertainties in the macroscopic neutronic information. The procedure to performthe uncertainty and sensitivity (U&S) analysis is a sampling-based method which is easy to implement and allows different procedures for the sensitivity analyses despite its high computational time. DAKOTA-Jaguar software package is the selected toolkit for the U&S analysis presented in this paper. The size of the sampling is determined by applying the Wilks¿ formula for double tolerance limits with a 95% of uncertainty and with 95% of statistical confidence for the output variables. Each sample has a corresponding set of perturbations that will modify the cross-sectional sets used by PARCS. Finally, the intervals of tolerance of the output variables will be obtained by the use of nonparametric statistical methods.This work has been partially supported by the Spanish Ministerio de Educacion y Ciencia under Project ENE2008-02669, the Generalitat Valenciana under Project ACOMP/2009/058, and the Universitat Politecnica de Valencia under Project PAID-05-09-4285.Mesado Melia, C.; Soler Martínez, MD.; Barrachina Celda, TM.; Miró Herrero, R.; García-Díaz, JC.; Macián-Juan, R.; Verdú Martín, GJ. (2012). Uncertainty and sensitivity of neutron kinetic parameters in the dynamic response of a PWR rod ejection accident coupled simulation. Science and Technology of Nuclear Installations. 2012(6258):1-10. https://doi.org/10.1155/2012/625878S11020126258Kreinovich, V., & Ferson, S. A. (2004). A new Cauchy-based black-box technique for uncertainty in risk analysis. Reliability Engineering & System Safety, 85(1-3), 267-279. doi:10.1016/j.ress.2004.03.016Helton, J. C., & Davis, F. J. (2003). Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems. Reliability Engineering & System Safety, 81(1), 23-69. doi:10.1016/s0951-8320(03)00058-9Iman, R. L., & Conover, W. J. (1982). A distribution-free approach to inducing rank correlation among input variables. Communications in Statistics - Simulation and Computation, 11(3), 311-334. doi:10.1080/0361091820881226

Uncertainty Analysis of Air Radiation for Lunar Return Shock Layers

By leveraging a new uncertainty markup technique, two risk analysis methods are used to compute the uncertainty of lunar-return shock layer radiation predicted by the High temperature Aerothermodynamic Radiation Algorithm (HARA). The effects of epistemic uncertainty, or uncertainty due to a lack of knowledge, is considered for the following modeling parameters: atomic line oscillator strengths, atomic line Stark broadening widths, atomic photoionization cross sections, negative ion photodetachment cross sections, molecular bands oscillator strengths, and electron impact excitation rates. First, a simplified shock layer problem consisting of two constant-property equilibrium layers is considered. The results of this simplified problem show that the atomic nitrogen oscillator strengths and Stark broadening widths in both the vacuum ultraviolet and infrared spectral regions, along with the negative ion continuum, are the dominant uncertainty contributors. Next, three variable property stagnation-line shock layer cases are analyzed: a typical lunar return case and two Fire II cases. For the near-equilibrium lunar return and Fire 1643-second cases, the resulting uncertainties are very similar to the simplified case. Conversely, the relatively nonequilibrium 1636-second case shows significantly larger influence from electron impact excitation rates of both atoms and molecules. For all cases, the total uncertainty in radiative heat flux to the wall due to epistemic uncertainty in modeling parameters is 30% as opposed to the erroneously-small uncertainty levels (plus or minus 6%) found when treating model parameter uncertainties as aleatory (due to chance) instead of epistemic (due to lack of knowledge)

INTERVAL COMPUTATIONS AND INTERVAL-RELATED STATISTICAL TECHNIQUES: ESTIMATING UNCERTAINTY OF THE RESULTS OF DATA PROCESSING AND INDIRECT MEASUREMENTS

In many practical situations, we only know the upper bound Δ on the measurement error: |Δx| ≤ Δ. In other words, we only know that the measurement error is located on the interval [−Δ, Δ]. The traditional approach is to assume that Δx is uniformly distributed on [−Δ, Δ]. In some situations, however, this approach underestimates the error of indirect measurements. It is therefore desirable to directly process this interval uncertainty. Such interval computations methods have been developed since the 1950s. In this paper, we provide a brief overview of related algorithms and results

Clouds, p-boxes, fuzzy sets, and other uncertainty representations in higher dimensions

Uncertainty modeling in real-life applications comprises some serious problems such as the curse of dimensionality and a lack of sufficient amount of statistical data. In this paper we give a survey of methods for uncertainty handling and elaborate the latest progress towards real-life applications with respect to the problems that come with it. We compare different methods and highlight their relationships. We introduce intuitively the concept of potential clouds, our latest approach which successfully copes with both higher dimensions and incomplete information

Failure analysis of a complex system based on partial information about subsystems, with potential applications to aircraft maintenance

In many real-life applications (e.g., in aircraft maintenance), we need to estimate the probability of failure of a complex system (such as an aircraft as a whole or one of its subsystems). Complex systems are usually built with redundancy allowing them to withstand the failure of a small number of components. In this paper, we assume that we know the structure of the system, and, as a result, for each possible set of failed components, we can tell whether this set will lead to a system failure. For each component A, we know the probability P(A) of its failure with some uncertainty: e.g., we know the lower and upper bounds P(A) and P(A) for this probability. Usually, it is assumed that failures of different components are independent events. Our objective is to use all this information to estimate the probability of failure of the entire the complex system. In this paper, we describe several methods for solving this problem, including a new efficient method for such estimation based on Cauchy deviates

Assessment of Radiative Heating Uncertainty for Hyperbolic Earth Entry

This paper investigates the shock-layer radiative heating uncertainty for hyperbolic Earth entry, with the main focus being a Mars return. In Part I of this work, a baseline simulation approach involving the LAURA Navier-Stokes code with coupled ablation and radiation is presented, with the HARA radiation code being used for the radiation predictions. Flight cases representative of peak-heating Mars or asteroid return are de ned and the strong influence of coupled ablation and radiation on their aerothermodynamic environments are shown. Structural uncertainties inherent in the baseline simulations are identified, with turbulence modeling, precursor absorption, grid convergence, and radiation transport uncertainties combining for a +34% and ..24% structural uncertainty on the radiative heating. A parametric uncertainty analysis, which assumes interval uncertainties, is presented. This analysis accounts for uncertainties in the radiation models as well as heat of formation uncertainties in the flow field model. Discussions and references are provided to support the uncertainty range chosen for each parameter. A parametric uncertainty of +47.3% and -28.3% is computed for the stagnation-point radiative heating for the 15 km/s Mars-return case. A breakdown of the largest individual uncertainty contributors is presented, which includes C3 Swings cross-section, photoionization edge shift, and Opacity Project atomic lines. Combining the structural and parametric uncertainty components results in a total uncertainty of +81.3% and ..52.3% for the Mars-return case. In Part II, the computational technique and uncertainty analysis presented in Part I are applied to 1960s era shock-tube and constricted-arc experimental cases. It is shown that experiments contain shock layer temperatures and radiative ux values relevant to the Mars-return cases of present interest. Comparisons between the predictions and measurements, accounting for the uncertainty in both, are made for a range of experiments. A measure of comparison quality is de ned, which consists of the percent overlap of the predicted uncertainty bar with the corresponding measurement uncertainty bar. For nearly all cases, this percent overlap is greater than zero, and for most of the higher temperature cases (T >13,000 K) it is greater than 50%. These favorable comparisons provide evidence that the baseline computational technique and uncertainty analysis presented in Part I are adequate for Mars-return simulations. In Part III, the computational technique and uncertainty analysis presented in Part I are applied to EAST shock-tube cases. These experimental cases contain wavelength dependent intensity measurements in a wavelength range that covers 60% of the radiative intensity for the 11 km/s, 5 m radius flight case studied in Part I. Comparisons between the predictions and EAST measurements are made for a range of experiments. The uncertainty analysis presented in Part I is applied to each prediction, and comparisons are made using the metrics defined in Part II. The agreement between predictions and measurements is excellent for velocities greater than 10.5 km/s. Both the wavelength dependent and wavelength integrated intensities agree within 30% for nearly all cases considered. This agreement provides confidence in the computational technique and uncertainty analysis presented in Part I, and provides further evidence that this approach is adequate for Mars-return simulations. Part IV of this paper reviews existing experimental data that include the influence of massive ablation on radiative heating. It is concluded that this existing data is not sufficient for the present uncertainty analysis. Experiments to capture the influence of massive ablation on radiation are suggested as future work, along with further studies of the radiative precursor and improvements in the radiation properties of ablation products

Propagation of Imprecise Probabilities through Black Box Models

From the decision-based design perspective, decision making is the critical element of the design process. All practical decision making occurs under some degree of uncertainty. Subjective expected utility theory is a well-established method for decision making under uncertainty; however, it assumes that the DM can express his or her beliefs as precise probability distributions. For many reasons, both practical and theoretical, it can be beneficial to relax this assumption of precision. One possible means for avoiding this assumption is the use of imprecise probabilities. Imprecise probabilities are more expressive of uncertainty than precise probabilities, but they are also more computationally cumbersome. Probability Bounds Analysis (PBA) is a compromise between the expressivity of imprecise probabilities and the computational ease of modeling beliefs with precise probabilities. In order for PBA to be implemented in engineering design, it is necessary to develop appropriate computational methods for propagating probability boxes (p-boxes) through black box engineering models. This thesis examines the range of applicability of current methods for p-box propagation and proposes three alternative methods. These methods are applied towards the solution of three successively complex numerical examples.M.S.Committee Chair: Paredis, Chris; Committee Member: Bras, Bert; Committee Member: McGinnis, Leo