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At least 19 records

Role of peracetic acid on the disruption of lignin packing structure and its consequence on lignin depolymerisation

Peracetic acid (PAA) is an effective oxidant capable of solubilising lignin and efficiently depolymerising it to selective phenolic compounds; however, the specific role by which PAA initiates the depolymerisation is still elusive. Herein, interaction between PAA and the lignin macromolecule and the consequent structural changes of the latter were studied by characterising the lignin packing structure and its associated changes during the oxidation process. While the lignin packing structure and its changes associated with the PAA-mediated oxidation were probed by X-ray diffraction, the impact of the PAA on different chemical functionalities present in the lignin structure was established by 13 C and 1 H– 13 C heteronuclear single-quantum coherence nuclear magnetic resonance (NMR) spectroscopy. Further, combining the NMR spectroscopy results, and the product distribution, we conclude that the predominant reaction pathway for the oxidative depolymerisation of lignin with PAA is the Baeyer–Villiger oxidation of the ketone formed by the oxidation of the benzylic hydroxyl group adjacent to the β-O-4 linkage. The experimental evidence provided herein corroborated that PAA instigates oxygen insertion to the lignin macromolecule resulting in disruption of its packing structures and facilitates depolymerisation. We also investigated various metal oxide and mixed metal oxide catalysts to identify effective catalysts that further enhance the efficiency of PAA-mediated depolymerisation of lignin and produce selective monomeric phenolic compounds. Techno-economic analysis was also conducted to identify the key parameters associated with this oxidative process that need to be considered for possible commercial application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Technical Bases for Consequence Analyses Using MACCS (MELCOR Accident Consequence Code System)

The use of MELCOR Accident Consequence Code System (MACCS) in regulatory applications requires that input parameters used in MACCS models have a defensible and transparent technical basis. The existing technical basis for MACCS parameters was identified and updates were developed based on current data and information. The transparent way these updates are documented provides a technical basis for updating MACCS parameters with consistent application among the MACCS user community.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Thermodynamic consequences of Tyr to Trp mutations in the cation–π-mediated binding of trimethyllysine by the HP1 chromodomain

Evolution has converged on cation–p interactions for recognition of quaternary alkyl ammonium groups such as trimethyllysine (Kme3). While computational modelling indicates that Trp provides the strongest cation–p interaction of the native aromatic amino acids, there is limited corroborative data from measurements within proteins. Herein we investigate a Tyr to Trp mutation in the binding pocket of the HP1 chromodomain, a reader protein that recognizes Kme3. Binding studies demonstrate that the Trpmediated cation–p interaction is about -5 kcal mol -1 stronger, and the Y24W crystal structure shows that the mutation is not perturbing. Quantum mechanical calculations indicate that greater enthalpic binding is predominantly due to increased cation–π interactions. NMR studies indicate that differences in the unbound state of the Y24W mutation lead to enthalpy–entropy compensation. These results provide direct experimental quantification of Trp versus Tyr in a cation–π interaction and afford insight into the conservation of aromatic cage residues in Kme3 reader domains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Consequence analyses of sabotage-induced radiological releases in high-temperature helium-cooled prismatic microreactors

Here, this study analyzes the radiological dose consequences of sabotage-induced accidents at three high-temperature helium-cooled prismatic microreactors (HTPMs) with thermal power ratings of 1, 10, and 50 MWt. Each HTPM employs uranium oxycarbide tristructural isotropic fuel enriched to 19.75 wt% high-assay low-enriched uranium. Simulations were conducted to estimate reactor core inventory at the point of fuel discharge––when the effective multiplication factor reduced to less than 1––representing peak radionuclide inventory. Postulated sabotage scenarios leading to reactor shutdown were analyzed at two intervals: immediately post-shutdown (0 h) and 3 days after shutdown using the SCALE code for radionuclide inventories and the RASCAL tool for dose consequences. Results show that although HTPMs benefit from inherent safety features and robust fuel design, radiological consequences scale with reactor power because of increased source term inventories. Smaller microreactors exhibited proportionally lower dose consequences. To support the economic and regulatory feasibility of microreactor deployment, this study emphasizes the value of a risk-informed, performance-based approach, as supported by regulations like 10 CFR Parts 100 and 53 in the United States. Microreactor developers should perform site-specific assessments of potential sabotage or low-probability, high-consequence events, especially when considering minimal on-site or full off-site emergency response.

Consequence↗

Addressing Consequence within Operational Risk (O.T. Gagnon III) 9-18-2024

Addressing Consequence within Operational Risk: Why threats and security are just not that important! When dealing with cyber or physical risk within any critical infrastructure (CI) environment, don’t concern yourself with vulnerabilities and threats, at least not at first! Also, don’t be overly fixated on “securing the systems” within the organization. The endeavor of tackling operational risk focused on consequences in any critical infrastructure environment to include the complex Aviation ecosystem is challenging even for the most resourced entity but can be advanced though a simplified approach: identifying, binning, and prioritizing the infrastructure environment. While no two entities within a single element of the 16 critical infrastructure sectors are exactly alike when it comes to risk, there is a basic process to move toward a greater understanding of operational risk through becoming more informed about the infrastructure environment in which the entity exists. The process starts with bringing internal and external stakeholders and subject matter experts together to analyze key areas such as Information Technology (IT) and Operational Technology (OT) components and points of convergence, analyzing internal and external cyber and physical dependencies, accounting for explosive growth in devices and wireless technology, and leveraging the contributions of people inside and outside the operational environment. Attaining a common understanding of the infrastructure environment as part of addressing consequences within operational risk is not easy to do or resource light, but the process outlined provides the framework to further any entity’s efforts in this space. When it comes to cyber risks, before an organization can consider vulnerabilities within and threats to its operations, it must first have a solid understanding of the consequences existing inside its infrastructure environment. Idaho National Lab’s Consequence-Driven, Cyber-Informed Engineering is offered as an example of this approach to effective and efficient cyber risk mitigation.

99 GENERAL AND MISCELLANEOUS↗

MACCS (MELCOR Accident Consequence Code System) User Guide

The MELCOR Accident Consequence Code System (MACCS) is used by Nuclear Regulatory Commission (NRC) and various national and international organizations for probabilistic consequence analysis of nuclear power accidents. This User Guide is intended to assist analysts in understanding the MACCS/WinMACCS model and to provide information regarding the code. This user guide version describes MACCS Version 3.10.0. Features that have been added to MACCS in subsequent versions are described in separate documentation. This User Guide provides a brief description of the model history, explains how to set up and execute a problem, and informs the user of the definition of various input parameters and any constraints placed on those parameters. This report is part of a series of reports documenting MACCS. Other reports include the MACCS Theory Manual, MACCS Verification Report, Technical Bases for Consequence Analyses Using MACCS, as well as documentation for preprocessor codes including SecPop, MelMACCS, and COMIDA2. PAPERWORK REDUCTION ACT STATEMENT The NUREG does not contain information collection requirements and, therefore, is not subject to the requirements of the Paperwork Reduction Act of 1995 (44 USC 3501, et seq.). PUBLIC PROTECTION NOTIFICATION The NRC may not conduct or sponsor, and a person is not required to respond to, a request for information or an information collection requirement unless the requesting document displays a currently valid OMB control number. ACKNOWLEDGEMENTS Contributions to this User Guide were received from NRC and Sandia National Laboratories (SNL) project managers, technical experts, and code authors dedicated to the production of a valuable resource for the MACCS user community. Instructions and guidance included herein were developed over many years and include advancements in the code that provide users the ability to develop complex consequence modeling scenarios. WinMACCS and many of the early MACCS developments were due to vision of an earlier Project Manager, Jocelyn Mitchell. Jonathan Barr and AJ Nosek also contributed to the development of this report. The current NRC Project Manager, Salman Haq, provided the leadership to ensure this document was completed. Several other NRC and Sandia staff provided insights supporting development of the MACCS code and of this document.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Comparative Assessment of Radiological Consequences from Sabotage-Induced Releases in Diverse Microreactor Designs

Many microreactor design developers are planning to reduce on-site physical protection measures and emergency planning zones by relying on robust fuel and reactor designs and leveraging passive safety systems. These reductions raise the risk of sabotage at these microreactors. To evaluate these requirements, this study assessed the radiological consequences of sabotage-induced accidents at microreactors. For the assessment, five diverse designs, each producing 30 MWt, were considered. These designs included pressurized water microreactors (PWMs), sodium-cooled fast microreactors (SFMs), high-temperature helium-cooled prismatic microreactors (HTPMs), heat pipe–cooled microreactors (HPMs), and molten salt–cooled microreactors (MSMs). For each design, two postulated sabotage-induced accidents were defined along with the associated release percentages of fission products. Additionally, consequences from the release of activation products were assessed. With regard to evaluating physical protection and emergency planning requirements, the consequences of sabotage-induced accidents for each design type were found to be comparable. The differences were primarily because of the distinct fuel forms (and associated release mechanisms), burnup, and neutron spectra of the different microreactor types. Future effort will further investigate the release percentages of fission products to perform accurate dose consequence assessment.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Consequence-driven cyber-informed engineering and related systems and methods

Embodiments of the disclosure relate to a computer-implemented consequence-driven cyber-informed engineering tool for performing and reporting consequence-based prioritization, system-of-systems breakdown, consequence-based targeting, and mitigations and protections. Embodiments of a CCE tool may perform one or more steps of defining a target industrial control system (ICS), wherein the target ICS includes operational goals, critical functions, and critical services; determining one or more scored high consequence events (HCE) associated with the defined target ICS; prioritizing the scored HCEs according to an HCE severity index; and updating a dashboard with one or more representations of the prioritized HCEs, wherein the updated dashboard is associated with the CCE tool and presented at a display.

Assante, Michael↗

Consequence analyses of sabotage-induced radiological releases in sodium-cooled fast microreactors

Analysis of three sodium-cooled fast microreactors (SFMs) with thermal powers of 10, 30, and 50 MWt showed that smaller reactors result in lower radiological consequences during a postulated sabotage-induced event because of their reduced core inventory. All SFMs used U-10Zr metal fuel enriched to 15 wt% high-assay low-enriched uranium and operated until their respective effective multiplication factor (k eff ) reduced to less than 1 or until the end of their operational lifespan. Sabotage scenarios were simulated at this point, when the fuel inventory within the core contains the highest-level of radioactivity. Radionuclide core inventories were calculated using the SCALE code at shutdown and 3 days post-shutdown. Dose consequence analyses were performed for three sabotage scenarios using the RASCAL tool. As microreactor developers plan for minimal on-site or complete off-site emergency response, it remains essential to evaluate their physical protection needs and potential hazards, including assessing postulated sabotage-induced events that could become more relevant. SFM licensees should identify a credible worst-case, major accident, estimate release source terms, and perform dose consequence analyses to evaluate site-specific physical protection measures. In conclusion, this recommendation supports a risk-informed, performance-based approach, aligning with applicable regulatory requirements, i.e., 10 CFR Parts 100 and 53 rulemaking in the United States.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Animal displacement from marine energy development: Mechanisms and consequences

For marine wave and tidal energy to successfully contribute to global renewable energy goals and climate change mitigation, marine energy projects need to expand beyond small deployments to large-scale arrays. However, with large-scale projects come potential environmental effects not observed at the scales of single devices and small arrays. One of these effects is the risk of displacing marine animals from their preferred habitats or their migration routes, which may increase with the size of arrays and location. Many marine animals may be susceptible to some level of displacement once large marine energy arrays are increasingly integrated into the seascape, including large migratory animals, non-migratory pelagic animals with large home ranges, and benthic and demersal mobile organisms with more limited ranges, among many others. Yet, research around the mechanisms and effects of displacement have been hindered by the lack of clarity within the international marine energy community regarding the definition of displacement, how it occurs, its consequences, species of concern, and methods to investigate the outcomes. This review paper leveraged lessons learned from other industries, such as offshore development, to establish a definition of displacement in the marine energy context, explore which functional groups of marine animals may be affected and in what way, and identify pathways for investigating displacement through modeling and monitoring. In the marine energy context, we defined displacement as the outcome of one of three mechanisms (i.e., attraction, avoidance, and exclusion) triggered by an animal's response to one or more stressors acting as a disturbance, with various consequences at the individual through population levels. The knowledge gaps highlighted in this study will help the regulatory and scientific communities prepare for mitigating, observing, measuring, and characterizing displacement of various animals around marine energy arrays in order to prevent irreversible consequences.

16 TIDAL AND WAVE POWER↗

An Overview of the State-of-the-Art Reactor Consequence Uncertainty Assessment Accident Progression Insights

The U.S. Nuclear Regulatory Commission (NRC) with Sandia National Laboratories (Sandia) have completed three uncertainty analyses (UAs) as part of the State-of-the-Art Reactor Consequence Analyses (SOARCA) program. The SOARCA UAs included an integrated evaluation of uncertainty in accident progression, radiological release, and offsite health consequence projections. The UA for Peach Bottom, a boiling-water reactor (BWR) with a Mark I containment located in the State of Pennsylvania, analyzed the unmitigated long-term station blackout SOARCA scenario. The UA for Sequoyah, a 4-loop Westinghouse pressurized-water reactor (PWR) located in the State of Tennessee, analyzed the unmitigated short-term station blackout SOARCA scenario, with a focus on issues unique to the ice condenser containment and the potential for early containment failure due to hydrogen deflagration. The UA for Surry, a 3-loop Westinghouse PWR with a sub-atmospheric large dry containment located in the State of Virginia, analyzed the unmitigated short-term station blackout SOARCA scenario including the potential for thermally-induced steam-generator tube rupture. These three UAs are currently documented in three NUREG/CR reports. This report provides input to planned NRC documentation on the insights and findings from the SOARCA UA program. The purpose of the summary report is to provide a useful reference for regulatory applications that require the evaluation of offsite consequence risk from beyond design basis event severe accidents. This report focuses on the accident progression and source term insights developed from the MELCOR analyses. MELCOR is the NRC's best-estimate, severe accident computer code used in the SOARCA UAs. In anticipation of the SOARCA UA insights work, NRC and Sandia benchmarked the response of the Peach Bottom model to selected reference calculations from the Peach Bottom SOARCA UA. Peach Bottom was the first SOARCA UA performed and was completed in 2015 using the MELCOR 1.8.6 code. The PWR SOARCA UAs evolved the original methodology and utilized the updated MELCOR 2.2 computer code. The Peach Bottom model has been systematically updated for other NRC research efforts and has been updated to MELCOR 2.2. computer code. The findings from the new reference calculations using the updated model with the MELCOR 2.2 code are also integrated into the report. A second objective is an assessment of the applicability of the results to the other nuclear reactors in the U.S. As the key findings are reviewed, judgments are presented on the applicability of the results to other U.S. nuclear power plants. An important objective of the SOARCA program relied on high- fidelity plant-specific modeling. However, the nature of the insights and conclusions allowed judgements to be made on the applicability of the various insights to the same general classification of plant (i.e., BWR or PWR) or the entire fleet of plants. Finally, the results from the SOARCA UA accident progression calculations contain a wealth of information not previously documented in the NUREG/CRs. This report includes new but related information that can be used to benchmark past or support future regulatory decisions related to severe accidents. The new work includes a benchmark of the NUREG-1465 licensing source term definitions, the variability of key accident progression events and timing to radionuclide release, and an improved understanding of the timing and source terms from consequential steam generator tube ruptures. iii ACKNOWLEDGEMENTS The Sandia authors gratefully acknowledge the significant technical and programmatic contributions from the NRC SOARCA team which are reflected throughout the report. Dr. Tina Ghosh has been involved throughout the SOARCA UAs, providing the primary managerial and technical oversight. The long lists of NRC and Sandia contributors from the SOARCA UAs are cited in the three NUREG/CRs and are also gratefully acknowledged by the small team of authors compiling the results of their efforts. Significant technical contributions, advice, and reviews were provided by Dr. Hossein Esmaili, Dr. Alfred Hathaway, and Dr. Edward Fuller (retired) of the NRC. Dr. Randal Gauntt (retired), Mr. Patrick Mattie, Mr. Joseph Jones (retired), and Dr. Doug Osborn from Sandia are recognized as the SOARCA UA managers guiding the past efforts. There is a comparable list of project managers at the NRC including Ms. Patricia Santiago, Dr. Salman Haq, and Mr. Jon Barr. Sadly, we have lost Mr. Charlie Tinkler and Mr. Robert Prato, who were important contributors to the original SOARCA project. Finally, Mr. Kyle Ross and Mr. Mark Leonard have also retired but were significant technical contributors. Mr. Kyle Ross was the technical lead on all three SOARCA UAs and the original pressurized water reactor SOARCA study. Mr. Leonard was the technical lead on the original boiling water reactor SOARCA study and a key contributor to the first Peach Bottom SOARCA UA. iv

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Economic Model for Estimation of GDP Losses in the MACCS Offsite Consequence Analysis Code

The MACCS (MELCOR Accident Consequence Code System) code is the U.S. Nuclear Regulatory Commission (NRC) tool used to perform probabilistic health and economic consequence assessments for atmospheric releases of radionuclides. It is also used by international organizations, both reactor owners and regulators. It is intended and most commonly used for hypothetical accidents that could potentially occur in the future rather than to evaluate past accidents or to provide emergency response during an ongoing accident. It is designed to support probabilistic risk and consequence analyses and is used by the NRC, U.S. nuclear licensees, the Department of Energy, and international vendors, licensees, and regulators. This report describes the modeling framework, implementation, verification, and benchmarking of a GDP-based model for economic losses that has recently been developed as an alternative to the original cost-based economic loss model in MACCS. The GDP-based model has its roots in a code developed by Sandia National Laboratories for the Department of Homeland Security to estimate short-term losses from natural and manmade accidents, called the Regional Economic Accounting analysis tool (REAcct). This model was adapted and modified for MACCS and is now called the Regional Disruption Economic Impact Model (RDEIM). It is based on input-output theory, which is widely used in economic modeling. It accounts for direct losses to a disrupted region affected by an accident, indirect losses to the national economy due to disruption of the supply chain, and induced losses from reduced spending by displaced workers. RDEIM differs from REAcct in its treatment and estimation of indirect loss multipliers, elimination of double counting associated with inter-industry trade in the affected area, and that it is designed to be used to estimate impacts for extended periods that can occur from a major nuclear reactor accident, such as the one that occurred at the Fukushima Daiichi site in Japan. Most input-output models do not account for economic adaptation and recovery, and in this regard RDEIM differs from its parent, REAcct, because it allows for a user-definable national recovery period. Implementation of a recovery period was one of several recommendations made by an independent peer review panel to ensure that RDEIM is state-of-practice. For this and several other reasons, RDEIM differs from REAcct. Both the original and the RDEIM economic loss models account for costs from evacuation and relocation, decontamination, depreciation, and condemnation. Where the original model accounts for an expected rate of return, based on the value of property, that is lost during interdiction, the RDEIM model instead accounts for losses of GDP based on the industrial sectors located within a county. The original model includes costs for disposal of crops and milk that the RDEIM model currently does not, but these costs tend to contribute insignificantly to the overall losses. This document discusses three verification exercises to demonstrate that the RDEIM model is implemented correctly in MACCS. It also describes a benchmark study at five nuclear power plants chosen to represent the spectrum of U.S. commercial sites. The benchmarks provide perspective on the expected differences between the RDEIM and the original cost-based economic loss models. The RDEIM model is shown to consistently predict larger losses than the original model, probably in part because it accounts for national losses by including indirect and induced losses; whereas, the original model only accounts for regional losses. Nonetheless, the RDEIM model predicts losses that are remarkably consistent with the original cost-based model, differing by 16% at most for the five sites combined with three source terms considered in this benchmark.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗