[en] This report presents a brief overview of the possible development of a model for the attenuation of radionuclide concentrations in urban environments due to rainfall/runoff relationships. The following sequence of actions is suggested: (1) preliminary review, (2) exploratory modeling, (3) detailed literature review, (4) development of mathematical model, (5) development of computer model, and (6) model review including verification and sensitivity analysis. To facilitate the initiation of the indicated efforts, an introduction to the relevant literature is provided. Further, the following topics are also briefly discussed: (1) radionuclide transport and removal in the terrestrial environment, (2) need for a description of the chemical and physical forms of the radionuclides released in a reactor accident, and (3) potential importance of surface-water contamination. (orig./HP)

[en] A formal description of the structure of several recent performance assessments (PAs) for the Waste Isolation Pilot Plant (WIPP) is given in terms of the following three components: a probability space (S_st, L_st, P_st) for stochastic uncertainty, a probability space (S_su, L_su, P_su) for subjective uncertainty and a function (i.e., a random variable) defined on the product space associated with (S_st, L_st, P_st) and (S_su, L_su, P_su). The explicit recognition of the existence of these three components allows a careful description of the use of probability, conditional probability and complementary cumulative distribution functions within the WIPP PA. This usage is illustrated in the context of the US Environmental Protection Agency's standard for the geologic disposal of radioactive waste (40 CFR 191, Subpart B). The paradigm described in this presentation can also be used to impose a logically consistent structure on PAs for other complex systems

[en] Procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses are described and illustrated. These procedures attempt to detect increasingly complex patterns in scatterplots and involve the identification of (i) linear relationships with correlation coefficients, (ii) monotonic relationships with rank correlation coefficients, (iii) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (iv) trends in variability as defined by variances and interquartile ranges, and (v) deviations from randomness as defined by the chi-square statistic. A sequence of example analyses with a large model for two-phase fluid flow illustrates how the individual procedures can differ in the variables that they identify as having effects on particular model outcomes. The example analyses indicate that the use of a sequence of procedures is a good analysis strategy and provides some assurance that an important effect is not overlooked

[en] The Pathways-to-Man Model was developed at Sandia National Laboratories to represent the environmental movement and human uptake of radionuclides. This model is implemented by the computer program PATH1. The purpose of this document is to present a sequence of examples of facilitate use of the model and the computer program which implements it. Each example consists of a brief description of the problem under consideration, a discussion of the data cards required to input the problem to PATH1, and the resultant program output. These examples are intended for use in conjunction with the technical report which describes the model and the computer progam which implements it (NUREG/CR-1636, Vol 1; SAND78-1711). In addition, a sequence of appendices provides the following: a description of a surface hydrologic system used in constructing several of the examples, a discussion of mixed-cell models, and a discussion of selected mathematical topics related to the Pathways Model. A copy of the program PATH1 is included with the report

[en] The following techniques for uncertainty and sensitivity analysis are briefly summarized: Monte Carlo analysis, differential analysis, response surface methodology, Fourier amplitude sensitivity test, Sobol' variance decomposition, and fast probability integration. Desirable features of Monte Carlo analysis in conjunction with Latin hypercube sampling are described in discussions of the following topics: (i) properties of random, stratified and Latin hypercube sampling, (ii) comparisons of random and Latin hypercube sampling, (iii) operations involving Latin hypercube sampling (i.e. correlation control, reweighting of samples to incorporate changed distributions, replicated sampling to test reproducibility of results), (iv) uncertainty analysis (i.e. cumulative distribution functions, complementary cumulative distribution functions, box plots), (v) sensitivity analysis (i.e. scatterplots, regression analysis, correlation analysis, rank transformations, searches for nonrandom patterns), and (vi) analyses involving stochastic (i.e. aleatory) and subjective (i.e. epistemic) uncertainty

[en] The Sandia/NRC Risk Assessment Methodology consists of a procedure for assessing the post-closure, long-term risk from the disposal of radioactive waste in deep geologic formations. This procedure contains: (1) methods for selecting and screening potentially disruptive events, features and processes (i.e., scenarios); (2) models for use in simulating the physical processes and estimating the potential health effects associated with the deep geologic disposal of radioactive waste (e.g., repository evolution, ground-water flow and nuclide transport, biosphere transport and human exposure, and dose commitment and dose response); and (3) probabilistic and statistical procedures for use in risk estimates and in sensitivity and uncertainty analyses. Results of the demonstration of this methodology in the analysis of a hypothetical high-level waste repository in bedded salt are presented for the following three scenarios: (1) a hydraulic communication (boreholes or shafts) connects the middle and lower sandstone aquifers allowing water to flow through the depository; (2) a hydraulic communication allows water to flow from the middle sandstone aquifer through the depository and back to middle sandstone aquifer, referred to as a U-tube scenario; and (3) withdrawl wells completed into the middle sandstone aquifer down-gradient from the depository are coupled with the U-tube of Scenario 2

[en] The problem of incorporating and representing uncertainty in the analysis of geologic waste disposal has been discussed. The approach has been to view uncertainty analysis in the context of the problem of how to convert from a deterministic model (i.e., a function whoe input is a sequence of real numbers) to a probabilistic model (i.e., a function whoe input is a sequence of random variables and whose output is one or more random variables). Then, uncertainty analysis becomes the study of how the properaties of the output random variable are determined by the properties of the output random variable are determined by the properties of the input random variables. In the context of this approach, various questions which relate to uncertainty analysis for geologic waste disposal have been discussed and the manner in which the problems associated with these questions are being treated in the Sandia project has been indicated

[en] The robustness of procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses is investigated. These procedures are based on attempts to detect increasingly complex patterns in the scatterplots under consideration and involve the identification of (i) linear relationships with correlation coefficients, (ii) monotonic relationships with rank correlation coefficients, (iii) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (iv) trends in variability as defined by variances and interquartile ranges, and (v) deviations from randomness as defined by the chi-square statistic. The following two topics related to the robustness of these procedures are considered for a sequence of example analyses with a large model for two-phase fluid flow: the presence of Type I and Type II errors, and the stability of results obtained with independent Latin hypercube samples. Observations from analysis include: (i) Type I errors are unavoidable, (ii) Type II errors can occur when inappropriate analysis procedures are used, (iii) physical explanations should always be sought for why statistical procedures identify variables as being important, and (iv) the identification of important variables tends to be stable for independent Latin hypercube samples

[en] Uncertainties in health and economic consequence models stem principally from two types of uncertainties: limitations in the models and limitations in the data used in these models. This paper presents an overview of uncertainty and sensitivity analysis for reactor accident consequence models. Section II presents examples of previous treatments of uncertainty; Section III describes some of the possible approaches to treatment uncertainty; Section IV illustrates the use of one of these techniques; and finally, Section V presents a summary and discussion

[en] In this paper, available methods for uncertainty analysis and sensitivity analysis in a PRA are reviewed. This review first treats methods for use with individual components of a PRA and then considers how these methods could be combined in the performance of a complete PRA. The goal of uncertainty analysis is to measure the imprecision in PRA outcomes of interest, and the goal of sensitivity analysis is to identify the major contributors to this imprecision. 56 references