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At least 163 records · Page 9

FIC Consequence Profile - Hypothetical Cybercrime Syndicate Adversary Dossier

The FIC team has engaged PNNL’s Shamrock Cyber team to produce this Consequence Profile. This Consequence Profile is an Adversary Dossier, which provides the foundation for a thorough understanding of unacceptable mission outcomes, and the threats and vulnerabilities that make these outcomes plausible. The dossier helps stakeholders and development teams understand each other’s viewpoints. It also provides a means for reducing overall risk by prioritizing threats and vulnerabilities based on unacceptable outcomes. The Consequence Profile can be used as is, or as content to inform other reports tailored to a specific audience. It is intended to enable decision makers at all levels to improve the security posture of the system.

Beaman, Jacob E.↗

Modeling cell venting and gas-phase reactions in 18650 lithium ion batteries during thermal runaway

A numerical model is developed to study cell venting, internal pressure, and gas-phase dynamics behavior of 18650 Li-ion cells undergoing thermal runaway. A k-e Reynolds-Averaged Navier-Stokes (RANS) model is adopted to describe the turbulent flow out of the cells, while the fluid dynamics inside the cells is described by Darcy-Forchheimer's equation. Thermal abuse reactions and gas generation kinetics are described by a single-step lumped reaction model. Then, a series of computational fluid dynamics (CFD) simulations are conducted on a single 18650 cell at various states-of-charge (100%, 50%, 25%) to study detailed flow and thermal behavior as a function of quantity of gas generated during cell venting. Venting events are categorized into two stages: i) breaching of the cell container and ii) thermal runaway reactions. It is found that the cell response is dominated by the second stage since most of the gases are generated during thermal runaway. Also, the propensity for propagation is highly affected by state-of-charge (SOC). Cells at higher SOCs produce more heat and gas during the venting event, owing to higher mass and concentrations of reacting gases, and consequently reach higher internal cell pressures which increase the risk of side-wall breaching.

25 ENERGY STORAGE↗

Using Satellite‐Derived Fire Arrival Times for Coupled Wildfire‐Air Quality Simulations at Regional Scales of the 2020 California Wildfire Season

Abstract Wildfire frequency has increased in the Western US over recent decades, driven by climate change and a legacy of forest management practices. Consequently, human structures, health, and life are increasingly at risk due to wildfires. Furthermore, wildfire smoke presents a growing hazard for regional and national air quality. In response, many scientific tools have been developed to study and forecast wildfire behavior, or test interventions that may mitigate risk. In this study, we present a retrospective analysis of 1 month of the 2020 Northern California wildfire season, when many wildfires with varying environments and behavior impacted regional air quality. We simulated this period using a coupled numerical weather prediction model with online atmospheric chemistry, and compare two approaches to representing smoke emissions: an online fire spread model driven by remotely sensed fire arrival times and a biomass burning emissions inventory. First, we quantify the differences in smoke emissions and timing of fire activity, and characterize the subsequent impact on estimates of smoke emissions. Next, we compare the simulated smoke to surface observations and remotely sensed smoke; we find that despite differences in the simulated smoke surface concentrations, the two models achieve similar levels of accuracy. We present a detailed comparison between the performance and relative strengths of both approaches, and discuss potential refinements that could further improve future simulations of wildfire smoke. Finally, we characterize the interactions between smoke and meteorology during this event, and discuss the implications that increases in regional smoke may have on future meteorological conditions.

54 ENVIRONMENTAL SCIENCES↗

Gas Generation Models for Thermal Runaway in Lithium Ion Batteries

A numerical model is implemented to study cell venting, internal pressure, and gas-phase dynamics behavior of Li-ion cells undergoing thermal runaway. A k-ɛ Reynolds-Averaged Navier-Stokes (RANS) model is adopted to describe the turbulent flow out of the cells, while the fluid dynamics inside the cells is described by Darcy-Forchheimer’s equation. Thermal abuse reactions and gas generation kinetics are described by a single-step lumped reaction model. A series of computational fluid dynamics (CFD) simulations are conducted on a single cell at various states-of-charge (100%, 50%, 25%) to demonstrate detailed flow and thermal behavior as a function of quantity of gas generated during cell venting. Venting events are categorized into two stages: i) breaching of the cell container and ii) thermal runaway reactions. It is shown that the cell response is dominated by the second stage since most of the gases are generated during thermal runaway. Also, the propensity for propagation is highly affected by state-of-charge (SOC). Cells at higher SOCs produce more heat and gas during the venting event, owing to higher mass and concentrations of reacting gases, and consequently reach higher internal cell pressures which increase the risk of side-wall breaching.

Kim, Jinyong↗

Considerations for Resilience Guidelines for Clean Energy Plans: For the Oregon Public Utility Commission and Oregon Electricity Stakeholders

This document summarizes relevant approaches, research, models, and national examples for state utility regulators tasked with developing utility guidelines for risk-based resiliency planning. In 2021, the Oregon Legislature enacted a 100 percent clean electricity by 2040 standard that requires the Oregon Public Utility Commission (PUC) to oversee utility planning for aggressive clean energy deployment through Clean Energy Plans (House Bill 2021, Sec. 4). In addition to meeting emissions reductions targets, Clean Energy Plans must also: "Include a risk-based examination of resiliency opportunities that includes costs, consequences, outcomes, and benefits based on reasonable and prudent industry resiliency standards and guidelines established by the Public Utility Commission." This report will support the Oregon Public Utility Commission in developing resilience guidelines. Other state public utility commissions may also benefit from this research.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Carbon Scaffold Architectures for Stable Lithium Metal Anodes

In light of the skyrocketing demand for electric vehicles and consequent need for high-performing lithium-ion batteries, there has been significant research into the creation of a battery with a lithium metal anode due to its high theoretical capacity and energy density. Unfortunately, nonuniform lithium deposition and consequent dendrite growth diminish performance and pose a safety risk. To combat this, lightweight carbon scaffolds are being developed to stabilize the electric field of these batteries and induce uniform deposition through rational design at the nano-, micro-, and meso- scales. However, there is a paucity of research on the impacts of macroscale scaffold topology on lithium cycling performance. Here, we report the creation of two graphite-based scaffolds with distinct 3D topologies: one a series of triangular prisms and one a series of rectangular prisms. Coin cells were made using these scaffolds and cycled at a current of 1mA/cm2 for 50 cycles to test the performance. The triangular topology was found to outperform the rectangular topology in terms of both potential magnitude and stability during cycling. Disassembling the cells revealed more even lithium deposition on the rectangular scaffold; however, some of the rectangular prisms were broken while all the triangular prisms remained intact. Last, future experiments are proposed regarding the scaffold spacing and mass of the cells in order to isolate the topological impact.

25 ENERGY STORAGE↗

Poster: Responsible Adoption of Artificial Intelligence (AI) in Electric Grid Operations

The rapid integration of artificial intelligence (AI) in the utility transmission and distribution (T&D) sector is revolutionizing traditional grid management practices. As utilities encounter complexities from evolving consumer behaviors and energy integration, AI becomes a critical solution for enhancing grid monitoring, fault detection, and operational optimization. However, increased reliance on interconnected technologies introduces significant cybersecurity risks, regulatory compliance challenges, and human factors concerns. This study proposes a strategic, responsible and consequence-driven approach to AI implementation, examining the dual nature of AI adoption by highlighting its transformative benefits for utilities and associated risks. It provides utilities with a framework for evaluating AI integration, enabling them to navigate challenges and capitalize on opportunities to achieve greater reliability, efficiency, and resilience in an increasingly complex energy landscape.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Radiological Releases from Novel Fuel Forms in Advanced Reactors During Severe Accidents for Consequence Analyses

Various advanced reactor developers are exploring the potential for reductions in the size of physical security forces and emergency planning zones. These reductions are based on robust fuel forms and inherently safe reactor designs. However, such reductions in physical protection measures could increase the risk of sabotage. To assess the possibility of reducing these measures, sabotage-induced radiological consequence analyses were carried out. These analyses considered accident scenarios that were beyond design basis accidents and overly conservative (Shah, 2025a; Shah, 2025b; Shah and Hartanto, 2026), yielding very large release fractions. These fractions, which can be used to evaluate physical protection and emergency planning requirements, have been crudely determined and applied as demonstrations for a sodium-cooled fast reactor (SFR) (Shah and Hartanto, 2025a), a high-temperature gas-cooled reactor (HTGR) (Shah and Hartanto, 2025b), a heat pipe–cooled reactor (HPR) (Shah and Hartanto, 2025c), and a molten salt–cooled reactor (MSR) (Shah et al., 2026). A Sandia National Laboratories (SNL) team used MELCOR—a fully integrated severe accident analysis code—to demonstrate the code’s capability to analyze advanced (i.e., not light water–cooled) reactors (including a fluoride salt–cooled high-temperature reactor [FHR]) and calculate radiological releases to the environment during severe accidents (Wagner et al., 2022a, 2022b, 2022c, 2023a, and 2023b). Although the analyses were carried out to demonstrate MELCOR’s growing capability, the release source terms were estimated for advanced reactors, providing valuable insights into the accident progression and radiological releases. These findings from prior SNL studies, including estimated source terms and related sensitivity studies, were leveraged to derive source terms for postulated sabotage-induced accidents. Insights from these sensitivity studies informed the scaling of SNL’s estimated source terms for the defined accident scenarios. The derived release fractions for the severe accident scenarios for the respective reactor designs can be used to perform more nuanced dose consequence analyses to evaluate the reactors’ physical protection and emergency planning zone requirements. These analyses are in accordance with the risk-informed, performance-based approach proposed under 10 CFR Part 53. This study builds on the prior source term analyses and associated sensitivity studies by SNL to derive time-dependent and design-informed release fractions. Section 2 describes the diverse advanced reactor designs analyzed by the SNL team. Section 3 discusses the severe accident analyses, the release fractions calculated, and the limitations and assumptions of the demonstration project. Section 4 presents the release percentages derived for the hypothetical sabotage-induced severe accidents at the advanced reactors. Section 5 summarizes the study’s findings and conclusions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

On the Language of Reliability: A System Engineer Perspective

In its classical definition, risk is defined by three elements: what can go wrong, what are its consequences, and how likely is it to occur? While this definition makes sense in a regulatory-based framework where for the current fleet of operating light water reactors (LWRs), the risks associated with nuclear power plants typically are characterized in terms of core damage and large early release frequency (LERF), this approach does not provide a useful snapshot of the health of the plant from a broader perspective. This is due to the very narrow context in which the term “risk” typically is defined as nuclear safety aspects that have the potential to impact public health. In this paper, we take the viewpoint of nuclear safety that is reflective of the current fleet of operating LWRs for which core damage frequency and LERF are appropriate metrics. For other advanced reactor designs, other more applicable technology neutral metrics of reactor safety metrics would be specified. A possible alternate path would start by redefining the word risk with a broader meaning that better reflects the needs of a system health and asset management decision-making process. Rather than asking how likely an event could occur (in probabilistic terms), we can ask how far this event is from occurring. Our approach starts by defining and quantifying component and system health in terms of a “distance” between its actual and limiting conditions, i.e., determination of the margin that exists between the current state/condition and the state where the component/system is no longer capable of achieving its intended function. A margin is a measure that is more reflective of the current state or performance of a component, and therefore more closely tied to decisions that are made on an ongoing basis. Further, we will show how, given the data available from plant equipment reliability and monitoring (e.g., pump vibration data) and prognostic (e.g., component remaining useful life estimation) data, a margin can be described and determined for all types of maintenance approaches (e.g., corrective or predictive maintenance). We show how classical reliability models (e.g., fault trees) can be used to quantify the system margin provided component margin values. In the approach described in this paper, the propagation of margin values through classical reliability models are not performed using classical probabilistic calculations applied to sets (as performed in a typical plant probabilistic risk assessment). Instead, we show how it is possible to propagate margin values through Boolean logic gates (i.e., AND and OR operators) through distance-based operations.

97 MATHEMATICS AND COMPUTING↗

Dynamic risk assessment for geologic CO 2 sequestration

At a geologic CO 2 sequestration (GCS) site, geologic uncertainty usually leads to large uncertainty in the predictions of properties that influence metrics for leakage risk assessment, such as CO 2 saturations and pressures in potentially leaky wellbores, CO 2 /brine leakage rates, and leakage consequences such as changes in drinking water quality in groundwater aquifers. The large uncertainty in these risk-related system properties and risk metrics can lead to over-conservative risk management decisions to ensure safe operations of GCS sites. The objective of this work is to develop a novel approach based on dynamic risk assessment to effectively reduce the uncertainty in the predicted risk-related system properties and risk metrics. We demonstrate our framework for dynamic risk assessment on two case studies: a 3D synthetic example and a synthetic field example based on the Rock Springs Uplift (RSU) storage site in Wyoming, USA. Results show that the U.S. National Risk Assessment Partnership’s Open Source Integrated Assessment Model (NRAP-Open-IAM) coupled with a conformance evaluation can be used to effectively quantify and reduce the uncertainty in the predictions of risk-related system properties and risk metrics in GCS.

58 GEOSCIENCES↗

Engineering in Cyber Resilience with Cyber-Informed Engineering

Engineers have super powers to provide cybersecurity resilience with deterministic engineering solutions and to protect systems from the most catastrophic consequences that a cyber saboteur could cause. Come to this session to learn how to use engineering risk management skills to harden your engineered systems from cyberattacks. Objective 1 Identify what system functions could be digitally induced to cause undesired high-impact consequences. Objective 2 Analyze how loss or instability of digital controls in a subsystem could lead to high-impact consequences. Objective 3 Analyze how loss or instability in the digital connectivity between systems could lead to high-impact consequences. Objective 4 Identify engineering controls which could build resilience by eliminating digital loss or instability pathways or reduce the impact of digital loss or instability. This presentation will introduce Cyber-Informed Engineering, described below, and walk participants through specific engineering use cases to show how engineers can consider the potential for cyber sabotage in their existing system designs and enact deterministic engineering-based controls which eliminate pathways for attack or mitigate specific consequences. A wide variety of application use cases will be considered so that audience members can align the material with familiar engineering applications. CIE is an engineering approach that integrates cyber resilience into the conception, design, build, and operation of any physical system that has digital connectivity, sensors, monitoring, or control. CIE offers the opportunity to use engineering to eliminate or mitigate avenues for cyber attack—starting from the earliest stage of design and continuing throughout the system’s lifecycle. Today, engineers and industrial control system (ICS) technicians build engineered systems with specific goals for safety, reliability, and functionality. While systems engineering includes considerable safety and failure mode analysis, cybersecurity risks are often not specifically addressed—particularly the risks of intentional cyber compromise, exploitation, and misuse. Cyber-Informed Engineering pairs well with traditional cyber defenses and offers an extra designed-in protection to eliminate the most catastrophic consequences which can be realized by an adversary should traditional cyber defenses fail.

42 ENGINEERING↗

Risk-Oriented PMU Placement Approach in Electric Power Systems

The objective of traditional PMU placement approaches is to use the minimal number of PMUs to cover system complete observability. Very few consider the probability and the consequence severity of observability loss. For example, following line trip, grid topology changes, which may results in observability loss and overloaded lines. As long as the overloaded lines are still observable, then we can take action in time to correct the system; and the consequence of the observability loss is not severe, although some parts of the system is not observable. Otherwise, if the overloaded lines become unobservable, then we lose the situation awareness of the system and the consequence of the observability loss is severe. To address the above points in PMU placement, this paper proposes a risk-oriented PMU placement approach. The proposed approach uses two indices, namely the probability of observability loss and its corresponding consequence of severity to design the optimal PMU placement strategy. We show that our proposed approach is able to capture the critical events while the traditional approaches fail to do so. Extensive simulation results carried out on the IEEE 39-bus and 118-bus systems demonstrate its effectiveness.

observability, risk of observability loss, PMUs pl↗

The evolution of the Human Systems and Simulation Laboratory in nuclear power research

The events at Three Mile Island in the United States brought about fundamental changes in the ways that simulation would be used in nuclear operations. The need for research simulators was identified to scientifically study human-centered risk and make recommendations for process control system designs. This paper documents the human factors research conducted at the Human Systems and Simulation Laboratory (HSSL) since its inception in 2010 at Idaho National Laboratory. The facility’s primary purposes are to provide support to utilities for system upgrades and to validate modernized control room concepts. In the last decade, however, as nuclear industry needs have evolved, so too have the purposes of the HSSL. Thus, beyond control room modernization, human factors researchers have evaluated the security of nuclear infrastructure from cyber adversaries and evaluated human-in-the-loop simulations for joint operations with an integrated hydrogen generation plant. Lastly, our review presents research using human reliability analysis techniques with data collected from HSSL-based studies and concludes with potential future directions for the HSSL, including severe accident management and advanced control room technologies.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Challenges in Demonstrating Safety Criteria Satisfaction for External Events under a Risk-Informed Performance-Based Framework

The NRC is currently developing 10 CFR Part 53 that would establish a technology-inclusive regulatory framework for use by applicants for new commercial advanced nuclear reactors. The new draft rule language brings new explicit regulatory requirements of the quantitative health objectives (QHOs) as a constraint on plant risk and safety criteria for the plant design, including external hazards. Historically, light water reactors (LWRs) have demonstrated satisfaction of the QHOs through the use of surrogates in the form of CDF/LERF. However, these risk surrogates are not broadly applicable for all advanced reactor types, and for advanced reactors where external events are likely to be the dominant contributor to plant risk, a direct calculation of the QHOs in terms of offsite consequence is likely necessary. While the detailed analysis of low frequency events provides insights that can help justify alternative treatments to past conservatisms, the findings are dependent on the quality and confidence associated with the analyses. The assessment of external hazards presents a unique challenge, as their potential frequency of occurrence, especially of largemagnitude events, is inherently uncertain given the long return periods in question. This paper evaluates the QHOs and their potential role as safety criteria in evaluating external event risk as it applies to advanced reactors to aid in the development of consistent and appropriate analysis methodologies.

Chen, Ben↗

Third-Party Supplier Risk Re-Classification Using Multi-Model Semantic Voting and External Web Augmentation

Risk decisions in many third-party risk management (TPRM) workflows rely on static inherent risk questionnaires (IRQ). These static forms provide a snapshot of the vendor from the business users’ perspective, as these requests are processed without cross-referencing for evidence. Consequently, responses can be misinformed or embellished with inaccuracies, thereby masking the vendor’s true risk to the enterprise. This paper presents a multi-stage verification framework to augment IRQs with web evidence and a deterministic ensemble of large language model assessors to reclassify risk. In a case study of 100 submissions previously misclassified as low risk, the proposed framework correctly identified 76% of the cases as high risk, while the existing workflow identified none. McNemar’s continuity corrected statistics of 74 were obtained with a two sided p-value of 2.65 × 10-23, indicating a significantly more effective workflow compared to the legacy model.

99 - GENERAL AND MISCELLANEOUS↗

Cybersecurity Resiliency of Marine Renewable Energy Systems Part 2: Cybersecurity Best Practices and Risk Management

Marine renewable energy (MRE) is an emerging source of power for marine applications, marine devices, and coastal communities. This energy source relies on industrial control systems and IT to support operations and maintenance activities, which create a pathway for an adversary to gain unauthorized access to systems and data and disrupt operations. Incorporating cybersecurity risk prevention measures and mitigation capabilities from inception, development, operation, to decommissioning of the MRE system and components is paramount to the protection of energy generation and the security of network architecture and infrastructure. To improve the resilience of MRE systems as a predictable, affordable, and reliable source of energy, cybersecurity guidance was developed to enable operators to assess cybersecurity risks and implement security measures commensurate with the risk. This publication is the second of a two-part series, with Part 1 addressing a framework to determine cybersecurity risk by assessing the vulnerability of an MRE system to potential cyber threats and the consequences a cyberattack would have on the end user. This Part 2 publication describes an approach to select appropriate cybersecurity best practices commensurate with the MRE system's cybersecurity risk. The guidance includes 86 cybersecurity best practices, which are associated with 36 cybersecurity domains and grouped into nine categories. The best practices follow the core functions of the National Institute of Science and Technology Cybersecurity Framework (e.g., identify, detect, protect, respond, and and recover) and insights from both maritime and energy industry guidance documents to identify security measures effective in protecting information and operational technology assets prevalent in MRE systems.

97 MATHEMATICS AND COMPUTING↗

Utility-Scale Operational Consequences for Solar Grid Services

This report delves into the critical aspects of grid services provided by solar inverter-based resources (IBRs), with an emphasis on the evolving landscape of microgrids, virtual power plants (VPPs), aggregators, and distributed energy resource management systems (DERMS). As the energy sector undergoes a transformative shift towards more decentralized and resilient grid architectures, understanding the multifaceted risks associated with these technologies becomes paramount. The report categorizes these risks into organizational, technical, and procedural domains, providing a thorough risk assessment framework that stakeholders can utilize to anticipate and mitigate potential issues. In addressing the increasing complexity of grid interconnections, the report highlights the importance of Cyber-Informed Engineering (CIE). By embedding engineering controls and cybersecurity measures into the early stages of system design, this approach aims to fortify grid infrastructure against emerging cyber threats. The analysis includes an exploration of best practices and strategies for integrating CIE principles to enhance grid security and resilience. To provide practical insights, the report conducts a detailed consequence analysis of various grid services and cyber mitigations that can be applied through the interconnection process. This analysis evaluates the potential impacts of different failure modes and vulnerabilities, offering a clear understanding of the consequences that could arise from disruptions within the energy grid. The findings are further enriched by a series of case studies that illustrate real-world scenarios and lessons learned from past incidents. Through this comprehensive examination of grid services and their criticality, the report aims to prepare industry professionals with the knowledge and tools necessary to navigate the complexities of modern energy systems. By providing a comprehensive approach that includes risk assessment, cybersecurity, and consequence analysis, solar stakeholders can more effectively guarantee the reliability, efficiency, and security of the energy grid.

14 SOLAR ENERGY↗

An Integrated Risk Assessment Process of Safety-Related Digital I&C Systems in Nuclear Power Plants

Upgrading the existing analog instrumentation and control (I&C) systems to state-of-the-art digital I&C (DI&C) systems will greatly benefit existing light water reactors. However, the issue of software common cause failure (CCF) remains an obstacle in terms of qualification for digital technologies. Existing analyses of CCFs in I&C systems mainly focus on hardware failures. With the application and upgrading of new DI&C systems, design flaws could cause software CCFs to become a potential threat to plant safety, considering that most redundancy designs use similar digital platforms or software in their operating and application systems. With complex multilayer redundancy designs to meet the single failure criterion, these I&C safety systems are of particular concern in U.S. Nuclear Regulatory Commission licensing procedures. In Fiscal Year 2019, the Risk-Informed Systems Analysis (RISA) Pathway of the U.S. Department of Energy’s Light Water Reactor Sustainability Program initiated a project to develop a risk assessment strategy for delivering a strong technical basis to support effective, licensable, and secure DI&C technologies for digital upgrades and designs. An integrated risk assessment for the DI&C process was proposed for this strategy to identify potential key digital-induced failures, implement reliability analyses of related digital safety I&C systems, and evaluate the unanalyzed sequences introduced by these failures (particularly software CCFs) at the plant level. Here this paper summarizes these RISA efforts in the risk analysis of safety-related DI&C systems at Idaho National Laboratory.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗