An interlaboratory effort has developed a probabilistic framework to characterize uncertainty in data products that are developed by the US Department of Energy Consequence Management Program in support of the Federal Radiological Monitoring and Assessment Center. The purpose of this paper is to provide an overview of the probability distributions of input variables and the statistical methods used to propagate and quantify the overall uncertainty of the derived response levels that are used as contours on data products due to the uncertainty in input parameters. Uncertainty analysis results are also presented for several study scenarios. This paper includes an example data product to illustrate the potential real-world implications of incorporating uncertainty analysis results into data products that inform protective action decisions. Data product contours that indicate areas where public protection actions may be warranted can be customized to an acceptable level of uncertainty. The investigators seek feedback from decision makers and the radiological emergency response community to determine how uncertainty information can be used to support the protective action decision-making process and how it can be presented on data products.
This report was developed to help the U.S. Defense Threat Reduction Agency understand the radionuclide detection requirements necessary to establish air monitoring systems that can detect airborne radionuclide activity at levels that could warrant protective actions.. The report provides representative integrated air activity derived response levels that correspond to the U.S. Environmental Protection Agency's protective action guidelines for the Early Phase (0-96 h) following a release to the environment. Environmental releases from nuclear fallout, nuclear power plants, and radiological dispersal devices are considered.
The goal of this project, started in FY17, is to develop and execute methods of characterizing uncertainty in data products that are developed and distributed by the DOE Consequence Management (CM) Program. This report presents the results of uncertainty analyses performed in FY18 for additional scenarios of increased complexity, including different time phases and radionuclide source terms.
The goal of this project is to develop and execute methods for characterizing uncertainty in data products that are deve loped and distributed by the DOE Consequence Management (CM) Program. A global approach to this problem is necessary because multiple sources of error and uncertainty from across the CM skill sets contribute to the ultimate p roduction of CM data products. This report presents the methods used to develop a probabilistic framework to characterize this uncertainty and provides results for an uncertainty analysis for a study scenario analyzed using this framework.
This Federal Radiological Monitoring and Assessment Center (FRMAC) Assessment Manual has been prepared by representatives of those Federal and State agencies that can be expected to play the major roles during a radiological emergency. Federal Agencies include: the National Nuclear Security Administration (NNSA), the Nuclear Regulatory Commission (NRC), the Environmental Protection Agency (EPA), the Department of Agriculture (USDA), the Food and Drug Administration (FDA), and the Centers for Disease Control (CDC). This final manual was reviewed by experts from across the community and their input has been incorporated.
A set of radionuclide - decay chain truncation rules have been developed for use in the Turbo FRMAC and Specialized Hazard Assessment Response Capability (SHARC) software programs used to support radiological emergency response activities . Following the proposed rules, the software will truncate a decay chain after it encounters a progeny radionuclide with a half - life greater than 5,000 years. An analysis of the projected dose from many parent and progeny radionuclides over a 50 - year time period yielded that a radionuclide half - life cutoff of 5,000 years will exclude a negligible dose. Implementing the truncation rules will reduce the time required for assessments and minimize computer hardware requ irements without having a significant detrimental effect on dose projections and emergency response decisions. It is noted that the truncation rules may not be suited for long - term ( greater than 50 year) environmental assessments.
This report specifies the electronic file format that was agreed upon to be used as the file format for normalized radiological data produced by the software tool developed under this TI project. The NA-84 Technology Integration (TI) Program project (SNL17-CM-635, Normalizing Radiological Data for Analysis and Integration into Models) investigators held a teleconference on December 7, 2017 to discuss the tasks to be completed under the TI program project. During this teleconference, the TI project investigators determined that the comma-separated values (CSV) file format is the most suitable file format for the normalized radiological data that will be outputted from the normalizing tool developed under this TI project. The CSV file format was selected because it provides the requisite flexibility to manage different types of radiological data (i.e., activity concentration, exposure rate, dose rate) from other sources [e.g., Radiological Assessment and Monitoring System (RAMS), Aerial Measuring System (AMS), Monitoring and Sampling). The CSV file format also is suitable for the file format of the normalized radiological data because this normalized data can then be ingested by other software [e.g., RAMS, Visual Sampling Plan (VSP)] used by the NA-84’s Consequence Management Program.
This goal of this project is to address the current inability to assess the overall error and uncertainty of data products developed and distributed by DOE’s Consequence Management (CM) Program.
This report describes the procedure that will be implemented to normalize radiological data, collected at various times, to one point in time. Raw radiological data is adjusted for the effects of radioactive decay and weathering processes. Normalizing the radiological data to one point in time enables data that has been collected at various times to be directly compared and utilized in radiological assessment, statistical analysis, and atmospheric dispersion models. This report fulfills a deliverable requirement for the U.S. Department of Energy’s, NA-84 Technology Integration Program for the FY17 project, SNL17-CM-635, Normalizing Radiological Data for Analysis and Integration into Models.
This goal of this project is to address the current inability to assess the overall error and uncertainty of data products developed and distributed by DOE’s Consequence Management (CM) Program. This is a widely recognized shortfall, the resolution of which would provide a great deal of value and defensibility to the analysis results, data products, and the decision making process that follows this work. A global approach to this problem is necessary because multiple sources of error and uncertainty contribute to the ultimate production of CM data products. Therefore, this project will require collaboration with subject matter experts across a wide range of FRMAC skill sets in order to quantify the types of uncertainty that each area of the CM process might contain and to understand how variations in these uncertainty sources contribute to the aggregated uncertainty present in CM data products. The ultimate goal of this project is to quantify the confidence level of CM products to ensure that appropriate public and worker protections decisions are supported by defensible analysis.
This report reviews the method recommended by the U.S. Food and Drug Administration for calculating Derived Intervention Levels (DILs) and identifies potential improvements to the DIL calculation method to support more accurate ingestion pathway analyses and protective action decisions. Further, this report proposes an alternate method for use by the Federal Emergency Radiological Assessment Center (FRMAC) to calculate FRMAC Intervention Levels (FILs). The default approach of the FRMAC during an emergency response is to use the FDA recommended methods. However, FRMAC recommends implementing the FIL method because we believe it to be more technically accurate. FRMAC will only implement the FIL method when approved by the FDA representative on the Federal Advisory Team for Environment, Food, and Health.
A proposed method is considered to classify the regions in the close neighborhood of selected measurements according to the ratio of two radionuclides measured from either a radioactive plume or a deposited radionuclide mixture. The subsequent associated locations are then considered in the area of interest with a representative ratio class. This method allows for a more comprehensive and meaningful understanding of the data sampled following a radiological incident.