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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Test Report for the Qualification Testing of the ORNL-SFC-W-1 Special Form Capsule

Three prototypes the ORNL-SFC-W-1 special form capsules (SFCs) of the same design were evaluated to determine if the requirements of Title 49, Code of Federal Regulations (CFR), Part 173.469, Tests for Special Form Class 7 (Radioactive) Materials, were met. The results of the special form tests are documented in this test report. This report describes the special form testing activities performed on the three ORNL-SFC-W-1 capsules. The test units were designated as TU-1, TU-2 and TU-3. TU-1 was subjected to leak testing, impact testing and percussion testing. TU-1 was leak tested using the leak rate test specified in 49 CFR 173.469(a)(4)(i). The impact test was conducted according to the requirements in 49 CFR 173.469 (b)(1). The percussion test that was carried out on TU-1 was conducted in accordance with 49 CFR 173.469 (b)(2). Both TU-2 and TU-3 were subjected to a leak rate test as specified in 173.469(a)(4)(i) and a heat test as specified in 49 CFR 173.469(b)(4). Each test unit was leak tested before and after these respective tests. The leak rate tests performed were helium back-pressure tests and bubble tests as specified in American National Standards Institute (ANSI) N14.5-2014.The measured leak rates were converted to standard condition leak rates as specified in American Society for Testing and Measurement (ASTM) E 493. The determined standardized leak rates obtained from the test and the calculations for all the test units met the requirements for special form certification. The testing was performed under the direction of the Oak Ridge National Laboratory (ORNL) Package Testing Program (PTP).

42 ENGINEERING↗
DOE OSTI2021

A Risk-Informed Performance-Based Methodology to Manage Fire Protection Systems in Nuclear Facilities

Fire protection systems (FPSs) and features are installed in U.S. Department of Energy (DOE) Hazard Category 1, 2, or 3 nuclear facilities to protect property (maximum possible fire loss thresholds), life, and nuclear safety (i.e., structures, systems, and components). These FPSs and features are designed and maintained in accordance with the prescriptive guidance provided in applicable building codes and National Fire Protection Association codes and standards. Management, operations, and maintenance activities of FPSs involve significant effort. A DOE facility’s documented safety analysis or other safety basis document could also rely on FPSs to provide either a safety significant or safety class function to mitigate fire hazards and minimize radiological consequences. In some cases, the designation of safety significant or safety class may be determined to provide a layer of defense-in-depth to minimize nuclear safety risks independent of the fire risk. DOE standards allow the use of performance-based design alternatives developed by the fire industry but do not consider the defense-in-depth layers of protection provided in DOE facilities to prevent or mitigate the risks associated with unintended release of radioactive materials into the environment. Pacific Northwest National Laboratory developed a decision-making methodology tailored for DOE non-reactor nuclear facilities to manage FPSs and features by integrating nuclear safety risk insights into a performance-based analysis. This risk-informed, performance-based (RIPB) methodology can be used to provide the technical basis for classifying an FPS as safety class and safety significant, tailoring administrative controls (e.g., technical safety requirements), and ranking the importance of FPSs to prioritize maintenance, upgrades, and replacement activities. The RIPB methodology is a graded approach to inform DOE facility owners and Fire Protection Program managers of the most risk-significant FPSs and equipment, and those systems would be cost-beneficial to relax rigor if there is a need to re-design the FPS coverage or deviate from DOE and National Fire Protection Association standards for those systems that would be less significant. This paper describes the framework used to develop the RIPB methodology and the outcome of implementing this methodology in a use-case nuclear facility. This paper also discusses the impact to DOE policies and standards and the safety margins and defense-in-depth measures credited in nuclear safety assessments in a facility’s documented safety analysis and the benefits of implementing an RIPB methodology in lieu of a prescriptive method to comply with fire protection requirements.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

MELCOR

MELCOR is a fully integrated, engineering-level computer code for modeling the progression of severe accidents in light water reactors (LWR) at nuclear power plants and nuclear fuel cycle facilities. Originally developed to assess severe accidents following Three Mile Island, MELCOR’s flexible modeling framework has enabled it to be applied to safety assessments of a much broader range of nuclear power reactor designs and other types of nuclear facilities processing radioactive material. Further, MELCOR can model a broad spectrum of severe accident phenomena such as thermal-hydraulic response in a reactor coolant system; core heat-up, degradation, and relocation; and transport behavior in both boiling water and pressurized water reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

MACCS Theory Manual

This report describes the models of the MACCS computer code as presented in MACCS Version 3.10.0. The purpose of MACCS is to simulate the impact of severe accidents at nuclear power plants on the surrounding environment. MACCS has been developed by Sandia National Laboratories for the U.S. Nuclear Regulatory Commission. From a given release of radioactive material into the atmosphere, MACCS estimates the extent and magnitude of radiological contamination, offsite doses, protective actions, socioeconomic impacts and costs, and health effects. Since the weather at the time of an accident is not predictable, MACCS supports various sampling options to run a representative set of simulations to evaluate weather variability. MACCS simulates atmospheric transport with a straight-line Gaussian plume segment model. From the estimated air and ground concentrations, MACCS models dose projections through several dose exposure pathways. These exposures can be offset by protective actions during the emergency response and long-term recovery of the accident. MACCS users directly specify the evacuation and sheltering area, while other protective actions (e.g., relocation, farmland restrictions, decontamination) are based on user-specified dose or concentration limits. While protective actions help reduce dose accumulation, they also cause social and economic impacts. MACCS models the extent of displaced individuals and land contamination, and the cost of offsite property damage, economic disruptions, and various accident expenditures caused by protective actions. Finally, from the dose accumulation, MACCS estimates early and stochastic health effects according to dose-response models. The purpose of consequence analyses is to be able to understand and estimate the impact of nuclear accidents. Consequence analysis is an essential tool to inform determinations of adequate protection of the public, to understand nuclear power hazards, to measure the value of regulations, and to help us appreciate the importance of nuclear safety. As such, MACCS has a variety of regulatory uses including environmental analyses (10 CFR 51.53, 52.47), regulatory cost-benefit analyses, backfit analyses (10 CFR 50.109), consequence analysis studies such as SOARCA (NUREG-1935), Level 3 PRA studies, and risk-informing of emergency planning (10 CFR 50 App. E and 50.47). This report updates the previous MACCS theory manual (NUREG/CR-4691 Vol. 2; Chanin, Sprung, Ritchie, & Jow, 1990) and accompanies the MACCS User's Guide (SAND-2021-1588) that describes the use and input requirements of the graphical user interface of MACCS known as WinMACCS. The MACCS User's Guide is also a reference guide that describes data input file formats, describes various software components in the MACCS code suite, and provides a set of example tutorials for running WinMACCS. Also, soon to be published is a MACCS input parameter guidance report (NUREG/CR-7270) that provides technical bases for commonly used MACCS input values. This page left blank

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

ASER Annual Site Environmental Report 2020

Los Alamos National Laboratory’s (the Laboratory’s) annual site environmental reports are prepared each year by the Laboratory’s environmental organizations, as required by U.S. Department of Energy Order 231.1B, Administrative Change 1, Environment, Safety, and Health Reporting, and Order 458.1, Administrative Change 4, Radiation Protection of the Public and the Environment. The following chapters in this report discuss our success in complying with environmental laws, regulations, and orders (Chapter 2, Compliance Summary); how we manage the Laboratory’s environmental performance (Chapter 3, Environmental Programs and Analytical Data Quality); how we monitor for air emissions of radioactive materials and climate conditions (Chapter 4, Air Quality); how we monitor for effects of Laboratory operations on groundwater quality (Chapter 5, Groundwater Protection); how we monitor the movement of chemicals and radionuclides by storm water runoff and the levels of chemicals and radionuclides in deposited sediment (Chapter 6, Watershed Quality); how we monitor for the presence, levels, and effects of chemicals and radionuclides in plants, animals, soil, and vegetation (Chapter 7, Ecosystem Health); and finally, what radionuclide dose or risk from chemical exposure members of the public may experience as a result of Laboratory operations (Chapter 8, Public Dose and Risk Assessment).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Update to the Finite Cloud Dose Correction Factors in MACCS

In WASH - 1400, external exposure from the finite radioactive cloud (cloudshine) is calculated by assuming that the cloud is semi-infinite, the concentration of radioactive material is uniform, and by using a correction factor to account for these approximations. This correction factor is originally based upon formulations by Healy and depends on the effective size of the plume and the distance from the plume center to the receptor. The range of the finite cloud dose correction factor table from WASH - 1400 developed using Healy formulations can be exceeded in certain situations. When the range of the table is exceeded, no extrapolation is performed; rather interpolation at the edge of the table is performed per WASH - 1400. The tabulated values of these finite cloud dose correction factors from WASH - 1400 and the interpolation at the edge of the table have been used in MACCS since its creation. An expanded table of finite cloud dose correction factors is one way to reduce the need of using interpolation at the edge of the table. The generation of an expanded finite cloud dose correction factor table for future use in MACCS is documented in this report.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Detection of Anomalies in Environmental Gamma Radiation Background with Hopfield Artificial Neural Network - Consortium on Nuclear Security Technologies (CONNECT) Q3 Report

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to investigate performance of a Hopfield Neural Network (HNN) in in detection and identification of weak nuisances and anomalies events in the presence of a highly fluctuating background. Performance of HNN algorithm is benchmarked using search data from an environmental screening campaign. One data set contained a 137 Cs source, and another dataset contained a 131 I source.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Development of Hopfield Artificial Neural Network for Anomaly Detection in Environmental Gamma Radiation Background: Consortium on Nuclear Security Technologies (CONNECT) (Q2 Report)

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to explore supervised machine learning (ML) algorithms for development of a Hopfield Neural Network (HNN) in conjunction with an image processing algorithm for detection and identification of weak nuisances and anomalies events in the presence of a highly fluctuating background.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Brief Introduction to Gamma Spectroscopy [Slides]

Radiation energy is measured in units of electron volts (eV). Photon energies are like a fingerprint that allow us to identify specific radioisotopes. Radiation interacts with our detector & deposits energy. That deposited energy produces a proportional signal. Signals are sorted and analyzed. Signals are placed in a histogram, making a gamma spectrum. Analyze gamma spectrum and identify the radioactive material.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Alpha Spectrometry Results for Groundwater Samples Collected in Northern Iraq and a Summary of the Environmental Setting of the Adaya Burial Site

The Radiation Protection Center (RPC) of the Iraqi Ministry of Environment continues to evaluate the potential health impacts associated with the Adaya Burial Site, which is located 33 kilometers (20.5 miles) southwest of Mosul. This report documents the radiological analyses of 16 groundwater samples collected from wells located in the vicinity of the Adaya Burial Site and at other sites in northern Iraq. The Adaya Burial Site is a high-risk dump site because a large volume of radioactive material and contaminated soil is located on an unsecure hillside above the village of Tall ar Ragrag. The uranium activities for the 16 water samples in northern Iraq are considered to be naturally occurring and do not indicate artificial (man-made) contamination. With one exception, the alpha spectrometry results for the 16 wells that were sampled in 2019 indicate that the water quality concerning the three uranium isotopes (Uranium-233/234, Uranium-235/236, and Uranium-238) was acceptable for potable purposes (drinking and cooking). However, Well 7 in Mosul had a Uranium-233/234 activity concentration that slightly exceeded the World Health Organization guidance level. Eight of the 16 wells are located in the villages of Tall ar Ragrag and Adaya and had naturally occurring uranium concentrations. Wells in the villages of Tall ar Ragrag and Adaya are located near the Adaya Burial Site and should be sampled on an annual schedule. The list of groundwater analytes should include metals, total uranium, isotopic uranium, gross alpha/beta, gamma spectroscopy, organic compounds, and standard water quality parameters. Our current understanding of the hydrogeologic setting in the vicinity of the Adaya Burial Site is solely based on villager's domestic wells, topographic maps, and satellite imagery. To better understand the hydrogeologic setting, a Groundwater Monitoring Program needs to be developed and should include the installation of twelve groundwater monitoring wells in the vicinity of Tall ar Ragrag and the Adaya Burial Site. Characterization of the limestone aquifer and overlying alluvium is needed. RPC should continue to support health assessments for the villagers in Tall ar Ragrag and Adaya. Collecting samples for surface water (storm water), airborne dust, vegetation, and washway sediment should be conducted on a routine basis. Human access to the Adaya Burial Site needs to be strictly limited. Livestock access on or near the burial site needs to be eliminated. The surface-water exposure pathway is likely a greater threat than the groundwater exposure pathway. Installation of a surface-water diversion or collection system is recommended in order to reduce the potential for humans and livestock to come in contact with contaminated water and sediment. To reduce exposure to villagers, groundwater treatment should be considered if elevated uranium or other contaminants are detected in drinking water. Installing water-treatment systems would likely be quicker to accomplish than remediation and excavation of the Adaya Burial Site. The known potential for human exposure to uranium and metals (such as arsenic, chromium, selenium, and strontium) at the Adaya Burial Site is serious. Additional characterization , mitigation, and remediation efforts should be given a high priority.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Detection of Anomalies in Gamma Background Radiation Data with K-Means and Self-Organizing Map Clustering Algorithms (Consortium on Nuclear Security Technologies (CONNECT) Q1 Report)

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to explore unsupervised machine learning (ML) algorithms for detection and identification of weak nuisances and anomalies events in the presence of highly fluctuating background. The challenge is that spectral lines of isotopes are difficult to observe in one-second measurements. Averaging over the entire measurement campaign data set reveals spectral lines of most common background isotopes. Spectral lines of orphan sources, which might appear only in a few measurements during the campaign, will be washed out if averaging is performed over the entire measurement data set. The approach we have explored consists of extracting one-second measurements containing weak spectral features through data clustering. Averaging one-second spectra in a cluster should reveal the presence of anomaly sources. We created two ML models using K-means clustering and Neural Network Self-organizing Map (SOM). Performance of these ML models was benchmarked using search data. One data set contained 137 Cs source, and another dataset contained 131 I source.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2022

Anomaly Detection in Gamma Spectra Using Hopfield Neural Network with B-SAT and Grover’s Algorithm on a Quantum Computing Simulator

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. In principle, gamma radiation sources can be detected and identified by their unique spectral lines. However, detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. In recent prior work, we have developed a Hopfield Neural Network (HNN) in conjunction with an image processing algorithm to detect a weak signal anomaly hidden among the highly fluctuating background spectra. The objective of this work is to explore quantum computing methods to increase the speed of HNN. The approach is based on the Grover’s search algorithm in conjunction with a 3-SAT problem formalism. The Grover’s algorithm is implemented on a quantum computing simulator using Qiskit software. Performance of HNN algorithm is benchmarked using search data from an environmental screening campaign, where the anomaly is a subset of measurements containing a 137 Cs source. Results indicate that using Grover’s algorithm on a quantum simulator reduces runtime of HNN by two orders of magnitude.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

MCNP Intrinsic Source Constructor (MISC): A User’s Guide

The MCNP Intrinsic Source Constructor (MISC) facilitates the construction of MCNP source definition cards for radioactive materials. Given a material nuclide specification, either weight or atom fractions of those nuclides, and either a weight or atom density of the material, MISC will construct the source spectrum distribution of a specified particle type. MISC also calculates the absolute number of particles emitted per second per unit mass or volume. Furthermore, if decay chain information is available in the data sets selected by the user, the initial isotopes specified by the user can be approximately decayed to the resulting isotopes after a specified amount of time.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

User's Manual for RESRAD-BUILD Code Version 4: Vol. 2 - User's Guide for RESRAD-BUILD Code Version 4

The RESRAD-BUILD computer code is designed to assess radiological doses to individuals who live or work in a building contaminated with radioactive material. The code is equipped with a user-friendly interface that has many features to facilitate using the computer code and understanding the results. The design of the interface provides various options, from entering data and performing calculations to displaying calculation results. General and context-specific help are available, providing information on editing and viewing the radionuclide database, the definitions of input parameters and their use in the calculations, and the selection of the calculation results for placement into other applications. Two types of sensitivity analysis are supported by the code, i.e., deterministic and probabilistic, that can be used to study the influence of input parameters on the calculation results. This user’s guide provides instructions to help users on how to install the RESRAD-BUILD code, navigate the interface, and use the various features to set up a dose/risk analysis and to view/print the results in text and graphical outputs.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2022

Cost Efficient-by-Design Microreactors: Trade-offs between cost, technical, and regulatory factors

This research evaluates a cost reduction investigation through adoption of a functional containment approach on the microreactor system and structure. Trade-offs between microreactor system designs, fuels and reactor module sizes are evaluated based on performance-based and risk-informed design procedures. Cost savings are evaluated against trade-offs in the reliability of passive heat removal systems, reactivity control, and radioactive material containment. Results can inform the Microreactor Program and reactor designs on “sweet spots” for microreactors that are cost-efficient while meeting required safety limits.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

EMP, Attachment 3: Dose Assessment Guidance

This Dose Assessment Guidance (DAG) describes methods used to comply with the reporting requirements for dose to an individual member of the public receptor, collective dose, and biota dose for radionuclide air emissions under the U.S. Department of Energy, Office of Science, Pacific Northwest National Laboratory (PNNL) Environmental Monitoring Plan (EMP). The National Emission Standards for Hazardous Air Pollutants (40 CFR 61), Subpart H, is the greatest driver for the requirements. This DAG applies to public dose from radioactive material releases to the air from PNNL Richland Campus and PNNL Sequim Campus. Dose determinations from Richland Campus surveillance of ambient external dose and ambient air particulates is also briefly discussed. This guidance is Attachment 3 to PNNL’s EMP (PNNL-20919) and addresses a discrete, vital subject area of the EMP that is subject to revision independent of the main text of the EMP document.

40 CFR 61 Subpart H↗
DOE OSTI2021

EMP Attachment 3: Dose Assessment Guidance (Rev.3)

This Dose Assessment Guidance (DAG) describes methods used to comply with the reporting requirements for dose to an individual member of the public receptor, collective dose, and biota dose for radionuclide air emissions under the U.S. Department of Energy, Office of Science, Pacific Northwest National Laboratory (PNNL) Environmental Monitoring Plan (EMP). The National Emission Standards for Hazardous Air Pollutants (40 CFR 61), Subpart H, is the greatest driver for the requirements. This DAG applies to public dose from radioactive material releases to the air from PNNL-Richland Campus and PNNL Marine and Coastal Research Laboratory. Dose determinations from Richland Campus surveillance of ambient external dose and ambient air particulates is also briefly discussed. This guidance is Attachment 3 to PNNL’s EMP (PNNL-20919) and addresses a discrete, vital subject area of the EMP that is subject to revision independent of the main text of the EMP document.

40 CFR 61 Subpart H↗
DOE OSTI2021

PNNL Sequim Campus Radionuclide Air Emissions Report for Calendar Year 2020

The U.S. Department of Energy Office of Science (DOE-SC) Pacific Northwest Site Office has oversight and stewardship duties associated with the Pacific Northwest National Laboratory Sequim Campus. Some research projects have the potential to emit low levels of radioactive materials. This report is prepared to document compliance with the Code of Federal Regulation, Title 40, Protection of the Environment, Part 61, National Emission Standards for Hazardous Air Pollutants, Subpart H, “National Emission Standards for Emissions of Radionuclides Other than Radon from Department of Energy Facilities” and Washington Administrative Code Chapter 246-247, "Radiation Protection–Air Emissions." Compliance is indicated by comparing the estimated effective dose equivalent (EDE) to the maximally exposed individual (MEI) member of the public with the 10 millirem per year (mrem/yr) U.S. Environmental Protection Agency (EPA) standard. The PNNL Sequim Campus has only fugitive emissions sources. Despite the fact that the regulations are intended for application to point source emissions, fugitive emissions are included with regard to complying with the EPA standard. The EDE to the Campus MEI due to routine operations in 2020 was 3.5E-05 mrem (3.5E-07 mSv). No non-routine emissions occurred in 2020. The Sequim Campus is in compliance with the federal and state 10 mrem/yr standard.

40 CFR 61 Subpart H↗