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Presentation summarizing DOE Consequence Management assets available to support state, local, territorial, and tribal partners during a radiological emergency. This presentation will be given at various state engagements, including training and outreach for ingestion pathway exercises, national and regional CM exercises, and trainings for radiological emergency preparedness events as requested.
On May 16-20, 2022, federal mission partners (e.g., DOE Consequence Management, CDC, FDA, FBI, DHS) as well as integrated state, local, tribal, and territorial governments took part in Cobalt Magnet 22 (CM22), a large-scale, week-long radiological incident exercise in Austin, Texas, that linked several important national assets (National Search Program, Radiological Assistance Program, and Consequence Management [CM] personnel) into a single response effort. The exercise had nine (9) overarching Objectives and an additional 162 associated Critical Tasks for all the participating organizations. In total, 13 National Core Capabilities spanning 5 Mission Areas were represented in the final exercise. This exercise enabled a full range of capabilities to be fielded together and examine the operational connection between major assets, discover any resource shortages associated with conducting multiple mission areas simultaneously or in close succession, and identify any challenges related to leadership. This report summarizes nearly 100 successes and observations provided from players and controllers supporting the LA Division, Fly Away Laboratory (FAL) and Gamma Spectroscopist operations. The observations were categorized to align with the FRMAC programmatic functional areas to consider for future improvements: Logistics, CBRN Responder, Laboratory Analysis, Sampling and Monitoring, Health and Safety, Gamma Spectroscopist Operations, Fly Away Laboratory, and the FRMAC Interdivision Interoperability Group (FIIG).
In March 2021, a functional area drill was held at the Remote Sensing Laboratory–Nellis that focused on using CBRNResponder and the Digital Field Monitoring (DFM) tablets for sample hotline operations and the new paper Sample Control Forms (SCFs) for sample collection. Participants included staff trained and billeted as sample control specialists and Consequence Management Response Team (CMRT) field monitoring personnel. Teams were able to successfully gather and transfer samples to the sample control hotline staff through the manual process, though there were several noted areas for improvement. In July and October 2021, two additional functional area drills were held at Sandia National Laboratories that focused on field sample collection and custody transfer at the sample control hotline for the Consequence Management (CM) Radiological Assistance Program (RAP) program. The overarching goal of the drills was to evaluate the current CM process for sample collection, sample drop off, and sample control using the CBRNResponder mobile and web-based applications. The July 2021 drill had an additional focus to have a subset of samples analyzed by the local analytical laboratory, Radiation Protection Sample Diagnostics (RPSD) laboratory, to evaluate the Laboratory Access portal on CBRNResponder. All three drills were able to accomplish their objectives however, there were several issues noted (Observations: 25 Urgent, 29 Important, and 22 Improvement Opportunities). The observations were prioritized according to their impact on the mission as well as categorized to align with the programmatic functional area required to address the issue. This report provides additional detail on each observation for skillset/program leads and software developers to consider for future improvement or mandatory efforts.
A critical challenge in the Consequence Management (CM) domain is the appropriate allocation of necessary and skilled military and civilian personnel and materiel resources in unexpected emergencies. To aid this process we used the Forces module in the Improved Performance Research Integration Tool (IMPRINT). This module enables analysts to enter personnel and equipment capabilities, prioritized schedules and numbers available, along with unexpected emergency requirements in order to assess force response requirements. Using a suspected terrorist threat on a college campus, we developed a test case model which exercised the capabilities of the module, including the scope and scale of operations. The model incorporates data from multiple sources, including daily schedules and frequency of events such as fire calls. Our preliminary results indicate that the model can predict potential decreases in civilian emergency response coverage due to an involved unplanned incident requiring significant portions of police, fire and civil responses teams.
Reference inhalation dose models rely on deterministic biokinetics and reference computational phantoms, limiting their applicability to the variability present in population-specific exposures encountered in emergency response scenarios. Here, this study introduces REDCAL, a Python-based computational framework developed to propagate uncertainty in inhalation dose coefficients using the International Commission on Radiological Protection (ICRP) Publication 66 Human Respiratory Tract Model. REDCAL integrates ICRP deposition and clearance models, systemic biokinetics, and governing physics principles, and leverages Sandia National Laboratories’ Dakota toolkit for uncertainty quantification via Latin Hypercube Sampling. REDCAL was validated against DCAL, with biokinetic retention results differing by less than 1% and effective dose coefficients by less than 2% across all tested radionuclides. Stochastic sampling introduced variability in dose coefficients, with geometric standard deviations (GSD) in committed effective dose coefficients (CEDC) ranging from 1.0 to 1.5, based on lognormal distribution fits. Analysis demonstrated that variations in the activity median aerodynamic diameter (AMAD) notably influenced the computed CEDC values. Smaller particles (<1 µm) increased doses by 20–30% due to deeper lung deposition and prolonged retention for alpha emitting radionuclides, such as 241 Am and 239 Pu. Radionuclides with fast clearance, such as 133 I, demonstrated a dose reduction exceeding 50%, as AMAD increased beyond 5 µm due to upper airway deposition and rapid mucociliary clearance. The greatest GSD among the radionuclides reported in this study was for 241 Am. In most cases, the largest GSDs in the CEDC were associated with larger particle sizes, an expected outcome, as ICRP Publication 66 defines GSD in particle size as a function of AMAD, resulting in an extended tail of the lognormal distribution. The findings support improved inhalation dose assessments and enhance consequence management strategies for the U.S. Federal Radiological Monitoring and Assessment Center by quantifying uncertainty in dose coefficients and strengthening decision-making for emergency response scenarios.
This presentation will be used in the pilot NA-81 Consequence Monument course. This presentation discusses monitoring techniques that can be used when responding to a radiological incident.
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Explore the source record for details and available documents.
Explore the source record for details and available documents.
Presentation outlining the the intention and procedures of a mobile radiation detection system for emergency response and monitoring
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The Federal Radiological Monitoring and Assessment Center (FRMAC) is an operational center, available on request by the Department of Homeland Security (DHS) to respond to nuclear and radiological incidents as described in the National Response Framework (NRF). Under the Federal Interagency Operational Plan for Response and Recovery’s Nuclear/Radiological Annex, the U.S. Department of Energy (DOE) has the responsibility to maintain the operational readiness of the FRMAC during the emergency phase of an event. FRMAC is initially established and managed by the Nuclear Emergency Support Team (NEST) and serves as an interagency operations center with representatives from various federal, state, and local radiological response organizations. The purpose of the FRMAC is to assist state, local, tribal, and territorial governments (SLTT) in their mission to protect the health and well-being of their citizens with: • Verified radiation measurements. • Interpretations of radiation distributions based on Environmental Protection Agency (EPA), Food and Drug Administration (FDA), or local Protective Action Guidelines (PAGs). • Characterization of overall radiological conditions. Once a declaration to respond to a radiological emergency has been made, the National Nuclear Security Administration (NNSA) Headquarters will coordinate the response in consultation with the cognizant NNSA Regional Coordinating Office (RCO). Each of the eight RCOs maintain a 24-hour response capability for radiological emergencies that may occur in states served by its region. When a FRMAC is established, it operates under the parameters of the Incident Command System (ICS), as defined in the National Incident Management Systems (NIMS) construct. The Consequence Management Home Team (CMHT) will be activated immediately during normal business hours (Pacific Time Zone), and within two hours otherwise. The Consequence Management Response Team (CMRT) is prepared for deployment within six hours after activation. Along with the assets, FRMAC provides an operational framework for coordinating of all federal off-site radiological monitoring and assessment activities during a response to a radiological emergency to support the coordinating agency and SLTT governments. Potential radiological emergencies that fall within FRMAC vary widely in terms of the area affected, the nature of the contamination, and the scope of the government’s response. Detonation of a nuclear device, accidental release of radiation from a nuclear power plant, and a terrorist threat are just a few of the many possible scenarios FRMAC must be prepared to address. Through all this, supporting the state, local, and tribal organizations in the protection of the public remains the primary goal of the federal response.
Chloride-induced stress corrosion cracking (CISCC) of canisters has been identified as a potential degradation mechanism requiring ageing management — especially in a marine air environment. Methods for monitoring helium gas leakage from canisters have been developed on the basis of a phenomenon that the bottom temperature of the canister increases as the top temperature of the canister decreases when helium gas leaks during storage. In this paper, we consider the radiological consequences of CISCC based on two scenarios of helium gas leakage and propose effective management that includes a timeline for monitoring and mitigation. Monitoring helium gas leakage by measuring the difference in temperature between canister surfaces in the dry cask storage of spent fuel (SF) can detect leakage before SF undergoes oxidation as a result of air ingress and before country-specific regulatory limits of off-site doses are exceeded, thereby enabling mitigatory action.
During the summer and fall of 2021, several functional area drills were held that focused on exercising Consequence Management’s (CM) ability to extract and use data from RadResponder for the purpose of answering intermediate-phase questions presented as technical inject requests for information (RFI) in Sandia National Laboratories (SNL) Consequence Management Operational System (COSMOS) software. The scenario chosen was that of Northern Lights 2016 (NL16) which was a large-scale nuclear power plant (NPP) release exercise in the state of Minnesota. The NL16 data was extracted from the Radiological Assessment and Monitoring System (RAMS) event where it was created and was reformatted for implanting to a new RadResponder event. Next, the beta-version of a laboratory sample data simulator was used to generate more sample data that was injected to the event. Five “mini-drills” were devised with each prompt defined by a data-based need. For each drill, a team of assessment and NARAC scientists worked the problem using the drill prompt and the available data in RadResponder. The teams held a kickoff meeting, had several days to work the problem, and then reported their results as well as observations in a hotwash. Several areas for improvement in both the software and process were identified during the course of these drills. This report will document the process of addressing each RFI and the discovered gaps in both software capability and methodology so that they can be considered for future development and investment by the CM and NIRT programs.
Presentation for an International Atomic Energy Agency sponsored workshop on Consequence Management (virtual). Presentation sponsored by DOE NA-81
Case study on contingency planning for the MARS 2020 rover launch. Intended as part of a training for international consequence management personnel for IAEA and/or NATO-sponsored training classes. Funded through NA-81
Increased congestion required urban Americans to travel 6.8 billion hours more and purchase 3.1 billion gallons of fuel for a congestion cost of $\$$153 billion, according to the 2019 Urban Mobility Report. How to effectively manage the regional mobility system and improve the energy efficiency presents a big challenge to public agencies. Recent years have witnessed massive multi-jurisdictional multi-modal system-level data from various sources, which provides an unprecedented opportunity to improve the mobility system and its energy efficiency. However, implications of system-level data for mobility and energy efficiency are unclear. Those system-level data sets are siloed, spatially and temporally sparse, biased, not unified, and lacking of insights for system management. Consequently, there is a real need to acquire, fuse, mine and learn from multi-source system-level data to prepare public agencies to deal more effectively with large-scale energy efficiency modeling, management and planning. This project proposes to intensively review inexpensive, replicable and openly-accessible data from multi-modal systems, develop a data-driven system-level modeling framework enabled and validated by data, identify the energy inefficiencies of mobility systems from infrastructure, vehicles, passenger systems, and quantify the benefits of system-level strategies to improve mobility/energy efficiency. In addition, this research develops models to effectively estimate energy consumption and emissions from various types of vehicles on the roadway networks, with high granularity and high fidelity. Traditional models often heavily rely on aggregated infrastructure or vehicle/passenger data, for example, the census survey, land-use, and traffic counts of one or several classes, which may lead to research gaps considering the emerging vehicle technologies. Those models do not contain individual vehicular information. We propose an integrated data-driven method that combines multiple network modeling components, featuring the utilization of state-wide vehicle registration data. The additional vehicle registration data improve the model performance, and produce high-resolution vehicle-specific estimates of emissions and network performance metrics. Two case studies on the Pittsburgh and Philadelphia regional network show that the proposed method can efficiently and effectively estimate the emissions of a large-scale network, and provide valuable information for evaluating common management strategies.
Remote Area Modular Monitoring (RAMM) for canister surface temperature measurement (TM), or RAMM-TM, is a novel remote monitoring device for detection of gas leakage based on surface temperature measurements of canisters containing spent nuclear fuel. Here we describe the development of RAMM-TM, as is the demonstration of its performance in detecting canister gas leakage from a small, simulated chloride-induced stress corrosion crack in experiments using a 1/4.5-scale model cask. Both helium and air gas leakage from a canister were detected within hours after the start of the leakage. The change in surface temperatures at the top and bottom of the canister (ΔTBT) during gas leakage (depressurization) triggered automatic alarms, providing a sound basis for early detection of gas leakage from the canister. This methodology would allow consequence management through the implementation of mitigatory actions to continue effective aging management and to reduce risks to public safety, health, and the environment.