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MRS Proceedings | 2002

Risks and Uncertainties Associated With High-Level Waste Tank Closure

David W. Esh; Anna H. Bradford; Kristina L. Banovac; B. Jennifer Davis

Closure of tanks containing high-level radioactive waste (HLW) is a challenging problem involving potentially competing influences from economic, societal, and technological considerations. The U.S. Department of Energy (DOE) is faced with protecting public health and the environment while making economically responsible decisions. Risk (i.e., annual dose) is becoming more prominent as DOEs metric to evaluate the economic consequences of its decisions. Risks are assessed through modeling and calculations commonly known as performance assessment (PA). In the process of tank closure, the U.S. Nuclear Regulatory Commission (NRC) is typically consulted to perform an independent review of DOEs PAs. The NRC staff developed a generic PA model, applicable to HLW tank closure, which NRC utilizes to complete its independent review. The model was developed using the generic simulation software, GoldSim, because of its probabilistic capabilities and its adaptability to different problems [1]. The NRC staff uses the resultant risk from the generic models to evaluate the reasonableness of performance assessment models submitted by DOE. Large differences in the estimates of risk between the generic PA model and the DOE PA would likely indicate a need for stronger technical basis for processes significantly contributing to annual dose (risk) reduction.


Archive | 2004

The Interpretation of Risk and Sensitivity Under the Peak-of-the-Mean Concept

Richard B. Codell; David W. Esh; Sitakanta Mohanty

In quantitative performance assessment (PA) for nuclear waste repositories, probabilistic (e.g., Monte Carlo) calculations are frequently used to estimate dose and risk [1], Each Monte Carlo realization represents the uncertain estimate of the future effect of the repository. There are at least two ways to interpret the model output; (1) take the peak doses from the Monte Carlo realizations and draw conclusions from their ensemble, e.g., the mean of the peak doses; and (2) at each instant of time, look at the ensemble of all realizations, and synthesize a representative dose-versus-time curve, e.g., the mean. Method 1 is easy to understand and explain. However, the calculation of the mean of the peak doses allows an additional degree of freedom that may inadvertently overestimate risk, because the peaks occur at different times and therefore the mean may include contributions from peaks outside of a single person’s life span. This dilemma has been discussed previously in connection with the definition of the critical group, e.g., Corbett [2]. The U.S. Nuclear Regulatory Commission (NRC) has adapted Method 2, taking the peak value of the mean curve to represent the dose that the Reasonably Maximally Exposed Individual (RMEI) could receive during the regulatory time period for the purpose of defining risk. We call this the “peak-of-the-mean (POM)” approach, and believe that it is the clearest and fairest definition of risk. However, calculations and sensitivity analyses with the POM must proceed thoughtfully, since there are computational pitfalls and results are sometimes counterintuitive.


EPJ Web of Conferences | 2013

Hydrated phases and pore solution composition in cement- solidified saltstone waste forms

Kenneth A. Snyder; Paul E. Stutzman; Jacob Philip; David W. Esh


EPJ Web of Conferences | 2011

Performance assessments insights on the use of cements in waste management

David W. Esh; Jacob Philip; Kenneth A. Snyder


AMP 2010 | 2010

PERFORMANCE ASSESSMENTS INSIGHTS ON THE USE OF CEMENTS IN WASTE MANAGEMENT

David W. Esh; Jacob Philip; Kenneth A. Snyder


NUCPERF 2009 Conference Proceedings | 2009

HYDRATED PHASES IN BLENDED CEMENTITIOUS SYSTEMS FOR NUCLEAR INFRASTRUCTURE

Kenneth A. Snyder; Paul E. Stutzman; Jacob Philip; David W. Esh


Archive | 2013

Performance Impact of Fast Flow Paths Through Grout Monoliths Used for Radioactive Waste Disposal - 13224

Cynthia Lynn Dinwiddie; Gary R. Walter; David W. Esh; Cynthia S. Barr


Archive | 2012

Site-Specific Analyses for Demonstrating Compliance with 10 CFR 61 Performance Objectives - 12179

C. J. Grossman; David W. Esh; P. Yadav; A. G. Carrera; Rockville Pike


Archive | 2009

Risk-informed Analytical Approaches to Concentration Averaging for the Purpose of Waste Classification - 9199

David W. Esh; Karen E. Pinkston; Cynthia S. Barr; Anna H. Bradford; A. Christianne Ridge; Rockville Pike


Archive | 2008

Lessons Learned from Radioactive Waste Storage and Disposal Facilities

David W. Esh; Anna H. Bradford

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Anna H. Bradford

Nuclear Regulatory Commission

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Jacob Philip

Nuclear Regulatory Commission

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Kenneth A. Snyder

National Institute of Standards and Technology

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Paul E. Stutzman

National Institute of Standards and Technology

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Richard B. Codell

Nuclear Regulatory Commission

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B. Jennifer Davis

Nuclear Regulatory Commission

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Gary R. Walter

Southwest Research Institute

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Kristina L. Banovac

Nuclear Regulatory Commission

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Sitakanta Mohanty

Southwest Research Institute

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