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Probability, conditional probability and complementary cumulative distribution functions in performance assessment for radioactive waste disposal

Description: 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{sub st}, S{sub st}, p{sub st}) for stochastic uncertainty, a probability space (S{sub su}, S{sub su}, p{sub su}) for subjective uncertainty and a function (i.e., a random variable) defined on the product space associated with (S{sub st}, S{sub st}, p{sub st}) and (S{sub su}, S{sub su}, p{sub 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 U.S. 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.
Date: March 1, 1996
Creator: Helton, J.C.
Partner: UNT Libraries Government Documents Department

Uncertainty and Sensitivity Analysis in Performance Assessment for the Waste Isolation Pilot Plant

Description: The Waste Isolation Pilot Plant (WIPP) is under development by the U.S. Department of Energy (DOE) for the geologic (deep underground) disposal of transuranic (TRU) waste. This development has been supported by a sequence of performance assessments (PAs) carried out by Sandla National Laboratories (SNL) to assess what is known about the WIPP and to provide .tidance for future DOE research and development activities. Uncertainty and sensitivity analysis procedures based on Latin hypercube sampling and regression techniques play an important role in these PAs by providing an assessment of the uncertainty in important analysis outcomes and identi~ing the sources of thk uncertainty. Performance assessments for the WIPP are conceptually and computational] y interesting due to regulatory requirements to assess and display the effects of both stochastic (i.e., aleatory) and subjective (i.e., epistemic) uncertainty, where stochastic uncertainty arises from the possible disruptions that could occur over the 10,000 yr regulatory period associated with the WIPP and subjective uncertainty arises from an inability to unambi-aously characterize the many models and associated parameters required in a PA for the WIPP. The interplay between uncertainty analysis, sensitivity analysis, stochastic uncertainty and subjective uncertainty are discussed and illustrated in the context of a recent PA carried out by SNL to support an application by the DOE to the U.S. Environmental Protection Agency for the certification of the WIPP for the disposal of TRU waste.
Date: December 17, 1998
Creator: Helton, J.C.
Partner: UNT Libraries Government Documents Department

Incorporation of Uncertainty and Variability of Drip Shield and Waste Package Degradation in WAPDEG Analysis

Description: This presentation investigates the incorporation of uncertainty and variability of drip shield and waste package degradation in analyses with the Waste Package Degradation (WAPDEG) program (CRWMS M&O 1998). This plan was developed in accordance with Development Plan TDP-EBS-MD-000020 (CRWMS M&O 1999a). Topics considered include (1) the nature of uncertainty and variability (Section 6.1), (2) incorporation of variability and uncertainty into analyses involving individual patches, waste packages, groups of waste packages, and the entire repository (Section 6.2), (3) computational strategies (Section 6.3), (4) incorporation of multiple waste package layers (i.e., drip shield, Alloy 22, and stainless steel) into an analysis (Section 6.4), (5) uncertainty in the characterization of variability (Section 6.5), and (6) Gaussian variance partitioning (Section 6.6). The presentation ends with a brief concluding discussion (Section 7).
Date: April 19, 2000
Creator: Helton, J.C.
Partner: UNT Libraries Government Documents Department

Perspectives Gained in an Evaluation of Uncertainty, Sensitivity, and Decision Analysis Software

Description: The following software packages for uncertainty, sensitivity, and decision analysis were reviewed and also tested with several simple analysis problems: Crystal Ball, RiskQ, SUSA-PC, Analytica, PRISM, Ithink, Stella, LHS, STEPWISE, and JMP. Results from the review and test problems are presented. The study resulted in the recognition of the importance of four considerations in the selection of a software package: (1) the availability of an appropriate selection of distributions, (2) the ease with which data flows through the input sampling, model evaluation, and output analysis process, (3) the type of models that can be incorporated into the analysis process, and (4) the level of confidence in the software modeling and results.
Date: February 24, 1999
Creator: Davis, F.J. & Helton, J.C.
Partner: UNT Libraries Government Documents Department

A Monte Carlo procedure for the construction of complementary cumulative distribution functions for comparison with the EPA release limits for radioactive waste disposal

Description: A Monte Carlo procedure for the construction of complementary cumulative distribution functions (CCDFs) for comparison with the US Environmental Protection Agency (EPA) release limits for radioactive waste disposal (40 CFR 191, Subpart B) is described and illustrated with results from a recent performance assessment (PA) for the Waste Isolation Pilot Plant (WIPP). The Monte Carlo procedure produces CCDF estimates similar to those obtained with stratified sampling in several recent PAs for the WIPP. The advantages of the Monte Carlo procedure over stratified sampling include increased resolution in the calculation of probabilities for complex scenarios involving drilling intrusions and better use of the necessarily limited number of mechanistic calculations that underlie CCDF construction.
Date: October 1, 1994
Creator: Helton, J.C. & Shiver, A.W.
Partner: UNT Libraries Government Documents Department

Uncertainty analysis associated with radioactive waste disposal: a discussion paper

Description: 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.
Date: January 1, 1980
Creator: Cranwell, R.M. & Helton, J.C.
Partner: UNT Libraries Government Documents Department

Calculation of source terms for NUREG-1150

Description: The source terms estimated for NUREG-1150 are generally based on the Source Term Code Package (STCP), but the actual source term calculations used in computing risk are performed by much smaller codes which are specific to each plant. This was done because the method of estimating the uncertainty in risk for NUREG-1150 requires hundreds of source term calculations for each accident sequence. This is clearly impossible with a large, detailed code like the STCP. The small plant-specific codes are based on simple algorithms and utilize adjustable parameters. The values of the parameters appearing in these codes are derived from the available STCP results. To determine the uncertainty in the estimation of the source terms, these parameters were varied as specified by an expert review group. This method was used to account for the uncertainties in the STCP results and the uncertainties in phenomena not considered by the STCP.
Date: October 1, 1987
Creator: Breeding, R.J.; Williams, D.C.; Murfin, W.B.; Amos, C.N. & Helton, J.C.
Partner: UNT Libraries Government Documents Department

Statistical Analyses of Scatterplots to Identify Important Factors in Large-Scale Simulations, 1: Review and Comparison of Techniques

Description: 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 11errors 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.
Date: March 24, 1999
Creator: Kleijnen, J.P.C. & Helton, J.C.
Partner: UNT Libraries Government Documents Department

Statistical Analyses of Scatterplots to Identify Important Factors in Large-Scale Simulations, 2. Robustness of Techniques

Description: 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.
Date: March 24, 1999
Creator: Helton, J.C. & Kleijnen, J.P.C.
Partner: UNT Libraries Government Documents Department

Statistical Analyses of Scatterplots to Identify Important Factors in Large-Scale Simulations

Description: 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 (1) linear relationships with correlation coefficients, (2) monotonic relationships with rank correlation coefficients, (3) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (4) trends in variability as defined by variances and interquartile ranges, and (5) 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: (1) Type I errors are unavoidable, (2) Type II errors can occur when inappropriate analysis procedures are used, (3) physical explanations should always be sought for why statistical procedures identify variables as being important, and (4) the identification of important variables tends to be stable for independent Latin hypercube samples.
Date: April 1, 1999
Creator: Kleijnen, J.P.C. & Helton, J.C.
Partner: UNT Libraries Government Documents Department

Computational implementation of a systems prioritization methodology for the Waste Isolation Pilot Plant: A preliminary example

Description: A systems prioritization methodology (SPM) is under development to provide guidance to the US DOE on experimental programs and design modifications to be supported in the development of a successful licensing application for the Waste Isolation Pilot Plant (WIPP) for the geologic disposal of transuranic (TRU) waste. The purpose of the SPM is to determine the probabilities that the implementation of different combinations of experimental programs and design modifications, referred to as activity sets, will lead to compliance. Appropriate tradeoffs between compliance probability, implementation cost and implementation time can then be made in the selection of the activity set to be supported in the development of a licensing application. Descriptions are given for the conceptual structure of the SPM and the manner in which this structure determines the computational implementation of an example SPM application. Due to the sophisticated structure of the SPM and the computational demands of many of its components, the overall computational structure must be organized carefully to provide the compliance probabilities for the large number of activity sets under consideration at an acceptable computational cost. Conceptually, the determination of each compliance probability is equivalent to a large numerical integration problem. 96 refs., 31 figs., 36 tabs.
Date: April 1, 1996
Creator: Helton, J.C.; Anderson, D.R. & Baker, B.L.
Partner: UNT Libraries Government Documents Department

Conceptual structure of performance assessments conducted for the Waste Isolation Pilot Plant

Description: The Waste Isolation Pilot Plant (WIPP) in southeastern New Mexico is being developed by the US Department of Energy as a disposal facility for transuranic waste. In support of this project, Sandia National Laboratories is conducting an ongoing performance assessment (PA) for the WIPP. The ordered triple representation for risk proposed by Kaplan and Garrick is used to provide a clear conceptual structure for this PA. This presentation describes how the preceding representation provides a basis in the WIPP PA for (1) the definition of scenarios and the calculation of scenario probabilities and consequences, (2) the separation of subjective and stochastic uncertainties, (3) the construction of the complementary cumulative distribution functions required in comparisons with the US Environmental Protection Agency`s standard for the geologic disposal of radioactive waste (i.e., 40 CFR Part 191, Subpart B), and (4) the performance of uncertainty and sensitivity studies. Results obtained in a preliminary PA for the WIPP completed in December of 1991 are used for illustration.
Date: April 1, 1993
Creator: Helton, J. C.; Marietta, M. G. & Rechard, R. P.
Partner: UNT Libraries Government Documents Department

Performance Assessment in Support of the 1996 Compliance Certification Application for the Waste Isolation Pilot Plant

Description: The conceptual and computational structure of a performance assessment (PA) for the Waste Isolation Pilot Plant (WIPP) is described. Important parts of thk structure are @ maintenance of a separation between stochastic (i.e., aleatory) and subjective (i.e., epistemic) uncertain, with stochastic uncefinty arising from the many possible disruptions that could occur over the 10,000 Y regulatory period fiat applies to the WIPP and subjective uncertainty arising from `the imprecision with which many of the quantities rquired in tie `hdysis are known, (ii) use of Latin hypercttbe sampling to incorporate the effects of subjective uncefirtty, (iii) use of Monte Carlo (i.e., random) sampling to incorporate the effects of stochastic uncetinty, and OV) efficient use of tie necessarily limited number of mechanistic calculations that can be performed to SUPPOII the analysis. The WIPP is under development by the U.S. Department of Ener~ (DOE) for the geologic (i.e., deep underground) disposal of transuranic (TRU) waste, with the indicated PA supporting a ~Compliance Certification Application (CCA) by the DOE to the U.S. Environmental Protection Agency (EPA) in October 1996 for tie necessary certifications for the WIPP to begin operation. If certified, the WIPP will be the first operational faciliv in tie United States for the geologic disposal of ra&oactive waste.
Date: October 14, 1998
Creator: Anderson, D.R.; Basabilvazo, G.; Helton, J.C.; Jow, H.-N. & Marietta, M.G.
Partner: UNT Libraries Government Documents Department

Performance assessment in support of the 1996 compliance certification application for the Waste Isolation Pilot Plant: A decision analysis perspective

Description: The Waste Isolation Pilot Plant (WIPP) is under development by the US Department of Energy (DOE) for the geologic disposal of transuranic waste. The primary regulatory requirements (i.e., 40 CFR 191 and 40 CFR 194) placed on the WIPP by the US Environmental Protection Agency (EPA) involve a complementary cumulative distribution function (CCDF) for normalized radionuclide releases to the accessible environment. The interpretation and use of this CCDF from a decision analysis perspective is discussed and illustrated with results from the 1996 performance assessment for the WIPP, which was carried out to support a compliance certification application by the DOE to the EPA for the WIPP.
Date: August 1, 1998
Creator: Helton, J.C.; Anderson, D.R.; Jow, H.N.; Marietta, M.G. & Basabilvazo, G.
Partner: UNT Libraries Government Documents Department

Uncertainty analysis in the 1996 performance assessment for the Waste Isolation Pilot Plant

Description: The appropriate treatment of uncertainty is now widely recognized as an essential component of performance assessments (PAs) for complex systems. When viewed at a high-level, the uncertainty in such analyses can typically be partitioned into two types: (1) stochastic uncertainty, which arises because the system can behave in many different ways and is thus a property of the system itself, and (2) subjective uncertainty, which arises from a lack of knowledge about quantities that are believed to have (or, at least, are assumed to have) fixed values and is thus a property of the analysts carrying out the study. The 1996 PA for the Waste Isolation Pilot Plant (WIPP) carried out at Sandia National Laboratories (SNL) will be used to illustrate the treatment of these two types of uncertainty in a real analysis. In particular, this PA supported a compliance certification application (CCA) by the US Department of Energy (DOE) to the US Environmental Protection Agency (EPA) for the certification of the WIPP for the geologic disposal of transuranic waste. Insights on the conceptual and computational structure of PAs for complex systems gained from these and other analyses are being incorporated into a new software system under development at SNL to facilitate the performance of analyses that maintain a separation between stochastic and subjective uncertainty.
Date: July 1, 1998
Creator: Helton, J.C.; Anderson, D.R.; Jow, H.N.; Marietta, M.G. & Basabilvazo, G.
Partner: UNT Libraries Government Documents Department

Incorporating long-term climate change in performance assessment for the Waste Isolation Pilot Plant

Description: The United States Department of Energy (DOE) is developing the Waste Isolation Pilot Plant (WIPP) in southeastern New Mexico for the disposal of transuranic wastes generated by defense programs. Applicable regulations (40 CFR 191) require the DOE to evaluate disposal-system performance for 10,000 yr. Climatic changes may affect performance by altering groundwater flow. Paleoclimatic data from southeastern New Mexico and the surrounding area indicate that the wettest and coolest Quaternary climate at the site can be represented by that at the last glacial maximum, when mean annual precipitation was approximately twice that of the present. The hottest and driest climates have been similar to that of the present. The regularity of global glacial cycles during the late Pleistocene confirms that the climate of the last glacial maximum is suitable for use as a cooler and wetter bound for variability during the next 10,000 yr. Climate variability is incorporated into groundwater-flow modeling for WIPP PA by causing hydraulic head in a portion of the model-domain boundary to rise to the ground surface with hypothetical increases in precipitation during the next 10,000 yr. Variability in modeled disposal-system performance introduced by allowing had values to vary over this range is insignificant compared to variability resulting from other causes, including incomplete understanding of transport processes. Preliminary performance assessments suggest that climate variability will not affect regulatory compliance.
Date: March 1, 1994
Creator: Swift, P.N.; Baker, B.L.; Economy, K.; Garner, J.W.; Helton, J.C. & Rudeen, D.K.
Partner: UNT Libraries Government Documents Department

Evaluation of severe accident risks: Methodology for the containment, source term, consequence, and risk integration analyses; Volume 1, Revision 1

Description: NUREG-1150 examines the risk to the public from five nuclear power plants. The NUREG-1150 plant studies are Level III probabilistic risk assessments (PRAs) and, as such, they consist of four analysis components: accident frequency analysis, accident progression analysis, source term analysis, and consequence analysis. This volume summarizes the methods utilized in performing the last three components and the assembly of these analyses into an overall risk assessment. The NUREG-1150 analysis approach is based on the following ideas: (1) general and relatively fast-running models for the individual analysis components, (2) well-defined interfaces between the individual analysis components, (3) use of Monte Carlo techniques together with an efficient sampling procedure to propagate uncertainties, (4) use of expert panels to develop distributions for important phenomenological issues, and (5) automation of the overall analysis. Many features of the new analysis procedures were adopted to facilitate a comprehensive treatment of uncertainty in the complete risk analysis. Uncertainties in the accident frequency, accident progression and source term analyses were included in the overall uncertainty assessment. The uncertainties in the consequence analysis were not included in this assessment. A large effort was devoted to the development of procedures for obtaining expert opinion and the execution of these procedures to quantify parameters and phenomena for which there is large uncertainty and divergent opinions in the reactor safety community.
Date: December 1, 1993
Creator: Gorham, E.D.; Breeding, R.J.; Brown, T.D.; Harper, F.T.; Helton, J.C.; Murfin, W.B. et al.
Partner: UNT Libraries Government Documents Department

Uncertainty and sensitivity analysis of early exposure results with the MACCS Reactor Accident Consequence Model

Description: Uncertainty and sensitivity analysis techniques based on Latin hypercube sampling, partial correlation analysis and stepwise regression analysis are used in an investigation with the MACCS model of the early health effects associated with a severe accident at a nuclear power station. The primary purpose of this study is to provide guidance on the variables to be considered in future review work to reduce the uncertainty in the important variables used in the calculation of reactor accident consequences. The effects of 34 imprecisely known input variables on the following reactor accident consequences are studied: number of early fatalities, number of cases of prodromal vomiting, population dose within 10 mi of the reactor, population dose within 1000 mi of the reactor, individual early fatality probability within 1 mi of the reactor, and maximum early fatality distance. When the predicted variables are considered collectively, the following input variables were found to be the dominant contributors to uncertainty: scaling factor for horizontal dispersion, dry deposition velocity, inhalation protection factor for nonevacuees, groundshine shielding factor for nonevacuees, early fatality hazard function alpha value for bone marrow exposure, and scaling factor for vertical dispersion.
Date: January 1, 1995
Creator: Helton, J. C.; Johnson, J. D.; McKay, M. D.; Shiver, A. W. & Sprung, J. L.
Partner: UNT Libraries Government Documents Department

Uncertainty and sensitivity analysis of food pathway results with the MACCS Reactor Accident Consequence Model

Description: Uncertainty and sensitivity analysis techniques based on Latin hypercube sampling, partial correlation analysis and stepwise regression analysis are used in an investigation with the MACCS model of the food pathways associated with a severe accident at a nuclear power station. The primary purpose of this study is to provide guidance on the variables to be considered in future review work to reduce the uncertainty in the important variables used in the calculation of reactor accident consequences. The effects of 87 imprecisely-known input variables on the following reactor accident consequences are studied: crop growing season dose, crop long-term dose, milk growing season dose, total food pathways dose, total ingestion pathways dose, total long-term pathways dose, area dependent cost, crop disposal cost, milk disposal cost, condemnation area, crop disposal area and milk disposal area. When the predicted variables are considered collectively, the following input variables were found to be the dominant contributors to uncertainty: fraction of cesium deposition on grain fields that is retained on plant surfaces and transferred directly to grain, maximum allowable ground concentrations of Cs-137 and Sr-90 for production of crops, ground concentrations of Cs-134, Cs-137 and I-131 at which the disposal of milk will be initiated due to accidents that occur during the growing season, ground concentrations of Cs-134, I-131 and Sr-90 at which the disposal of crops will be initiated due to accidents that occur during the growing season, rate of depletion of Cs-137 and Sr-90 from the root zone, transfer of Sr-90 from soil to legumes, transfer of Cs-137 from soil to pasture, transfer of cesium from animal feed to meat, and the transfer of cesium, iodine and strontium from animal feed to milk.
Date: January 1, 1995
Creator: Helton, J. C.; Johnson, J. D.; Rollstin, J. A.; Shiver, A. W. & Sprung, J. L.
Partner: UNT Libraries Government Documents Department

Uncertainty and sensitivity analysis of chronic exposure results with the MACCS reactor accident consequence model

Description: Uncertainty and sensitivity analysis techniques based on Latin hypercube sampling, partial correlation analysis and stepwise regression analysis are used in an investigation with the MACCS model of the chronic exposure pathways associated with a severe accident at a nuclear power station. The primary purpose of this study is to provide guidance on the variables to be considered in future review work to reduce the uncertainty in the important variables used in the calculation of reactor accident consequences. The effects of 75 imprecisely known input variables on the following reactor accident consequences are studied: crop growing season dose, crop long-term dose, water ingestion dose, milk growing season dose, long-term groundshine dose, long-term inhalation dose, total food pathways dose, total ingestion pathways dose, total long-term pathways dose, total latent cancer fatalities, area-dependent cost, crop disposal cost, milk disposal cost, population-dependent cost, total economic cost, condemnation area, condemnation population, crop disposal area and milk disposal area. When the predicted variables are considered collectively, the following input variables were found to be the dominant contributors to uncertainty: dry deposition velocity, transfer of cesium from animal feed to milk, transfer of cesium from animal feed to meat, ground concentration of Cs-134 at which the disposal of milk products will be initiated, transfer of Sr-90 from soil to legumes, maximum allowable ground concentration of Sr-90 for production of crops, fraction of cesium entering surface water that is consumed in drinking water, groundshine shielding factor, scale factor defining resuspension, dose reduction associated with decontamination, and ground concentration of 1-131 at which disposal of crops will be initiated due to accidents that occur during the growing season.
Date: January 1, 1995
Creator: Helton, J. C.; Johnson, J. D.; Rollstin, J. A.; Shiver, A. W. & Sprung, J. L.
Partner: UNT Libraries Government Documents Department

The 1996 performance assessment for the Waste Isolation Pilot Plant

Description: The Waste Isolation Pilot Plant (WIPP) is under development by the US Department of Energy (DOE) for the geologic disposal of transuranic (TRU) waste that has been generated at government defense installations in the United States. The WIPP is located in an area of low population density in southeastern New Mexico. Waste disposal will take place in excavated chambers in a bedded salt formation approximately 655 m below the land surface. This presentation describes a performance assessment (PA) carried out at Sandia National Laboratories (SNL) to support the Compliance Certification Application (CCA) made by the DOE to the US Environmental Protection Agency (EPA) in October, 1996, for the certification of the WIPP for the disposal of TRU waste. Based on the CCA supported by the PA described in this presentation, the EPA has issued a preliminary decision to certify the WIPP for the disposal of TRU waste. At present (April 1998), it appears likely that the WIPP will be in operation by the end of 1998.
Date: July 1, 1998
Creator: Anderson, D.R.; Jow, H.N.; Marietta, M.G.; Chu, M.S.Y.; Shephard, L.E.; Helton, J.C. et al.
Partner: UNT Libraries Government Documents Department

Probabilistic accident consequence uncertainty analysis: Dispersion and deposition uncertainty assessment, appendices A and B

Description: The development of two new probabilistic accident consequence codes, MACCS and COSYMA, completed in 1990, estimate the risks presented by nuclear installations based on postulated frequencies and magnitudes of potential accidents. In 1991, the US Nuclear Regulatory Commission (NRC) and the Commission of the European Communities (CEC) began a joint uncertainty analysis of the two codes. The objective was to develop credible and traceable uncertainty distributions for the input variables of the codes. Expert elicitation, developed independently, was identified as the best technology available for developing a library of uncertainty distributions for the selected consequence parameters. The study was formulated jointly and was limited to the current code models and to physical quantities that could be measured in experiments. To validate the distributions generated for the wet deposition input variables, samples were taken from these distributions and propagated through the wet deposition code model along with the Gaussian plume model (GPM) implemented in the MACCS and COSYMA codes. Resulting distributions closely replicated the aggregated elicited wet deposition distributions. Project teams from the NRC and CEC cooperated successfully to develop and implement a unified process for the elaboration of uncertainty distributions on consequence code input parameters. Formal expert judgment elicitation proved valuable for synthesizing the best available information. Distributions on measurable atmospheric dispersion and deposition parameters were successfully elicited from experts involved in the many phenomenological areas of consequence analysis. This volume is the second of a three-volume document describing the project and contains two appendices describing the rationales for the dispersion and deposition data along with short biographies of the 16 experts who participated in the project.
Date: January 1, 1995
Creator: Harper, F. T.; Young, M. L.; Miller, L.A.; Hora, S. C.; Lui, C. H.; Goossens, L. H. J. et al.
Partner: UNT Libraries Government Documents Department

Evaluation of severe accident risks: Quantification of major input parameters: MAACS (MELCOR Accident Consequence Code System) input

Description: Estimation of offsite accident consequences is the customary final step in a probabilistic assessment of the risks of severe nuclear reactor accidents. Recently, the Nuclear Regulatory Commission reassessed the risks of severe accidents at five US power reactors (NUREG-1150). Offsite accident consequences for NUREG-1150 source terms were estimated using the MELCOR Accident Consequence Code System (MACCS). Before these calculations were performed, most MACCS input parameters were reviewed, and for each parameter reviewed, a best-estimate value was recommended. This report presents the results of these reviews. Specifically, recommended values and the basis for their selection are presented for MACCS atmospheric and biospheric transport, emergency response, food pathway, and economic input parameters. Dose conversion factors and health effect parameters are not reviewed in this report. 134 refs., 15 figs., 110 tabs.
Date: December 1, 1990
Creator: Sprung, J.L.; Jow, H-N (Sandia National Labs., Albuquerque, NM (USA)); Rollstin, J.A. (GRAM, Inc., Albuquerque, NM (USA)) & Helton, J.C. (Arizona State Univ., Tempe, AZ (USA))
Partner: UNT Libraries Government Documents Department

Probabilistic accident consequence uncertainty analysis: Dispersion and deposition uncertainty assessment, main report

Description: The development of two new probabilistic accident consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the risks presented by nuclear installations based on postulated frequencies and magnitudes of potential accidents. In 1991, the US Nuclear Regulatory Commission (NRC) and the Commission of the European Communities (CEC) began a joint uncertainty analysis of the two codes. The ultimate objective of the joint effort was to develop credible and traceable uncertainty distributions for the input variables of the codes. Expert elicitation was identified as the best technology available for developing a library of uncertainty distributions for the selected consequence parameters. The study was formulated jointly and was limited to the current code models and to physical quantities that could be measured in experiments. Experts developed their distributions independently. To validate the distributions generated for the wet deposition input variables, samples were taken from these distributions and propagated through the wet deposition code model. Resulting distributions closely replicated the aggregated elicited wet deposition distributions. To validate the distributions generated for the dispersion code input variables, samples from the distributions and propagated through the Gaussian plume model (GPM) implemented in the MACCS and COSYMA codes. Project teams from the NRC and CEC cooperated successfully to develop and implement a unified process for the elaboration of uncertainty distributions on consequence code input parameters. Formal expert judgment elicitation proved valuable for synthesizing the best available information. Distributions on measurable atmospheric dispersion and deposition parameters were successfully elicited from experts involved in the many phenomenological areas of consequence analysis. This volume is the first of a three-volume document describing the project.
Date: January 1, 1995
Creator: Harper, F. T.; Young, M. L.; Miller, L. A.; Hora, S. C.; Lui, C. H.; Goossens, L. H. J. et al.
Partner: UNT Libraries Government Documents Department