An exploratory sensitivity study with the MACCS reactor accident consequence model

Helton, Jon C.; Rollstin, J.A.; Sprung, J.L.; Johnson, Jay

doi:10.1016/0951-8320(92)90095-3

Cited by 11 publications

(2 citation statements)

References 45 publications

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“…The model used in this application is MELCOR Accident Consequence Code System (MACCS), described in Helton et al (1992). Helton et al (1992).…”

Section: Analysis Application I1mentioning

confidence: 99%

Evaluating prediction uncertainty

McKay

1995

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The probability distribution of a model prediction is presented as a proper basis for evaluating the uncertainty in a model prediction that arises from uncertainty in input values. Determination of important model inputs and subsets of inputs is made through comparison of the prediction distribution with conditional prediction probability distributions. Replicated Latin hypercube sampling and variance ratios are used in estimation of the distributions and in construction of importance indicators. The assumption of a linear relation between model output and inputs is not necessary for the indicators to be effective. A sequential methodology which includes an independent validation step is applied in two analysis applications to select subsets of input variables which are the dominant causes of uncertainty in the model predictions. Comparison with results from methods which assume linearity shows how those methods may fail. Finally, suggestions for treating structural uncertainty for submodels are presented.iii NWEG/CR-63 1 1 CONTENTS

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“…The model used in this application is MELCOR Accident Consequence Code System (MACCS), described in Helton et al (1992). Helton et al (1992).…”

Section: Analysis Application I1mentioning

confidence: 99%

Evaluating prediction uncertainty

McKay

1995

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“…155 In addition, the NRC has used sampling-based uncertainty and sensitivity analysis procedures in a sequence of studies involving reactor accident consequence models. [156][157][158][159] Similar uncertainty propagation procedures were also used in the DOE's successful compliance certification application to the EPA for the Waste Isolation Pilot Plant. 61,62 A simple example is now presented using the following definition for D N (τ |e D ), which is introduced solely for illustrative purposes: is a vector of epistemically uncertain analysis inputs with the distributions specified in Table 2.…”

Section: Calculation Of Expected Dose and Display Of Epistemic Uncertmentioning

confidence: 99%

Illustration of sampling-based approaches to the calculation of expected dose in performance assessments for the proposed high level radioactive waste repository at Yucca Mountain, Nevada.

Helton

Sallaberry

2007

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A deep geologic repository for high level radioactive waste is under development by the U.S. Department of Energy at Yucca Mountain (YM), Nevada. As mandated in the Energy Policy Act of 1992, the U.S. Environmental Protection Agency (EPA) has promulgated public health and safety standards (i.e., 40 CFR Part 197) for the YM repository, and the U.S. Nuclear Regulatory Commission has promulgated licensing standards (i.e., 10 CFR Parts 2, 19, 20, etc.) consistent with 40 CFR Part 197 that the DOE must establish are met in order for the YM repository to be licensed for operation. Important requirements in 40 CFR Part 197 and 10 CFR Parts 2, 19, 20, etc. relate to the determination of expected (i.e., mean) dose to a reasonably maximally exposed individual (RMEI) and the incorporation of uncertainty into this determination. This presentation describes and illustrates how general and typically nonquantitive statements in 40 CFR Part 197 and 10 CFR Parts 2, 19, 20, etc. can be given a formal mathematical structure that facilitates both the calculation of expected dose to the RMEI and the appropriate separation in this calculation of aleatory uncertainty (i.e., randomness in the properties of future occurrences such as igneous and seismic events) and epistemic uncertainty (i.e., lack of knowledge about quantities that are poorly known but assumed to have constant values in the calculation of expected dose to the RMEI).

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