The accident scenario in question is among the most consequential in nuclear safety analysis. During a large-break loss-of-coolant accident, or LBLOCA, a major pipe rupture drains coolant from the reactor vessel, the reactor scrams, and the fuel rods heat up as their cooling water flashes away. If cladding temperatures climb high enough, the zirconium alloy tubes surrounding the uranium dioxide pellets can balloon and burst, releasing radioactive fission products and, in the worst case, shattering the brittle, high-burnup fuel inside them. That fragmentation, relocation, and dispersal of fuel—known in the trade as FFRD—shot to prominence after the 2011 Fukushima accident, when examinations of irradiated fuel revealed that pellets can crumble into fragments during refueling, raising concerns that hot, embrittled cladding could fail catastrophically during an accident and scatter fuel debris. Regulatory agencies in the United States and abroad have since demanded ever-more-rigorous assessments of this phenomenon, particularly for fuel discharged at high burnup.

What makes the new study unusual is its sheer scope. Traditional fuel performance analyses pick out a handful of the most punishing rods—those with the highest burnup or the hottest operating temperatures—and model them in isolation. That approach identifies limiting cases but says nothing about the reactor as a whole. The team behind the new work, led by Ian Greenquist of Oak Ridge National Laboratory under the Department of Energy’s Nuclear Energy Advanced Modeling and Simulation program, instead built a multiphysics pipeline that resolves the entire 764-assembly core of Limerick Unit 1 rod by rod. The framework chains together three codes: VERA, the Virtual Environment for Reactor Applications, which computes the neutron physics and fuel depletion across the core; TRACE, the Nuclear Regulatory Commission’s thermal-hydraulics code, which simulates the two-phase flow of boiling water and steam during the accident; and BISON, Idaho National Laboratory’s finite-element fuel performance code, which calculates the temperatures, stresses, strains, and fission gas behavior inside each individual rod.

Limerick Unit 1 itself provided a demanding test case. The reactor, a General Electric design operated by Constellation Energy since 1984, runs at 3,515 megawatts thermal on a 24-month fuel cycle, with assemblies typically remaining in the core for up to three cycles. Its core is a lattice of 10-by-10 fuel assemblies, each holding 92 fuel rods plus two internal water rods, and it mixes full-length rods with short and long partial-length rods and even unenriched rods placed near control blades to soften the neutron flux gradient. To push the analysis into the high-burnup regime where FFRD concerns are sharpest, the team also folded in eight high-burnup lead use assemblies that had been irradiated in the plant’s twin unit, Limerick Unit 2, for a third cycle beyond their normal exposure limits under the Nuclear Regulatory Commission’s lead test assembly program. Real plant data—actual loading patterns, control blade positions, and coolant conditions—anchored the simulations to physical reality.

The computational choreography unfolded in stages. VERA first simulated three complete irradiation cycles, tracking the burnup, power history, and isotopic composition of every rod in a quarter of the core, then handed those histories to BISON, which modeled 945 rods—five sampled from each of 191 modeled assemblies—through normal operation. The rod selection used orthogonal sampling to ensure that no two rods came from the same row or column of any assembly, capturing the full diversity of fuel types and exposures. Meanwhile, TRACE was calibrated against BISON’s fuel centerline temperature predictions during steady-state operation, a code-to-code benchmark that showed reasonable agreement given the uncertainties involved. Once satisfied, the team ran the LBLOCA transient in TRACE, extracting time-dependent cladding surface temperatures, coolant pressures, and linear heat generation rates, and stitched these boundary conditions directly into the BISON simulations in place of the final shutdown step of the cycle. Each BISON run thus carried a rod from fresh fuel through its entire irradiation history and straight into the accident without interruption.

The BISON models themselves received a substantial upgrade for this campaign. In 2025, the code gained a set of boiling-water-reactor-specific capabilities: treatment of burnable gadolinium-oxide absorbers in the pellets and their effects on burnup and thermal conductivity, models for modern BWR cladding materials, meshing options for cladding liners, two-phase flow heat transfer, and hydrogen pickup with hydride formation. This study represents the first time these features have been exercised in a core-scale simulation set. The team incorporated gadolinium into the fuel composition and added the hydrogen pickup and hydride models, while the fuel rods were re-meshed so that axial variations in density, enrichment, and gadolinium concentration—previously averaged away—were represented block by block. The cladding secondary creep model was swapped for the LOCA-specific Erbacher formulation, fuel creep was added, and the uranium dioxide thermal conductivity correlation was updated to one better suited to the burnup and temperature range of the analysis. Not every new feature made the cut: because Limerick uses conventional Zircaloy-2 cladding, the modern cladding materials were unnecessary, and the cladding liner meshing option was left out after it triggered numerical instabilities.

Cladding integrity was judged by two independent burst criteria built into BISON. The Chapman correlation, drawn from classic LOCA experiments, computes a burst temperature from the cladding’s hoop stress and heating rate, declaring failure if the metal exceeds that threshold; the team added a minimum burst temperature of 700 degrees Celsius to keep the empirical correlation within its validated range. The strain rate criterion, by contrast, predicts rupture when the cladding’s hoop strain rate exceeds 100 per hour. The results were unambiguous. During the transient, the linear heat generation rate collapsed by roughly 99 percent as the reactor scrammed, and peak cladding temperatures reached only about 540 degrees Celsius—well below the 700-degree floor of the Chapman correlation and far below the 700-to-1,000-degree peaks reported in earlier single-code studies of comparable accidents. Neither burst model predicted a single rod failure anywhere in the core, and because the outcome was uniform across all 945 rods, no fragmentation or statistical analysis was needed to bound the FFRD susceptibility: for this reactor, under these modeled conditions, it was zero.

The detailed predictions revealed rich structure in how the core behaves. Rod-average burnup spanned 14.2 to 66.1 megawatt-days per kilogram of uranium, and the rods sorted cleanly into behavioral families. Fresh and once-burned rods, sitting in the hotter central core, ran higher powers and temperatures, while twice-burned rods on the periphery ran cooler. Peak cladding hoop strain during normal operation reached 1.1 percent, driven by the familiar cycle of thermal expansion, creep-down under coolant pressure, and renewed expansion as the cladding contacts swelling fuel. Plenum pressures climbed from 2 to 3 megapascals in fresh rods to as much as 8.9 megapascals in aggressively burned once-burned rods, propelled by fission gas release that peaked at 12.7 percent. During the accident itself, fuel temperatures spiked to 240 to 560 degrees Celsius at 100 seconds before emergency core cooling brought the core down to a stable 75 to 280 degrees, fission gas release stayed negligible because the fuel never got hot enough to activate the transient microcracking model, and the cladding cooled too quickly for hydrides to reprecipitate. Comparing against a previous version of the analysis without the new BISON features showed that individual rod predictions shifted—notably, gadolinium-bearing rods ran hotter—but the whole-core distributions changed only minimally.

The authors are careful to frame the result honestly. The findings are theoretical: no comparison to actual or experimental LOCA data has been made, and the conclusions apply specifically to Limerick Unit 1 as modeled, with its particular fuel designs, operating conditions, and safety system response—they cannot be generalized to other reactors. Nor is the framework finished. Models for fuel relocation due to fracture and for the high-burnup structure that forms in heavily irradiated pellets are still being developed and validated, the cladding liner meshing awaits a fix for its numerical instabilities, and the same updates will be applied to pressurized water reactor simulations to see whether they shift FFRD predictions there as well. Most importantly, uncertainty propagation across the three coupled codes has yet to be quantified; understanding how uncertainties in reactor conditions and input values cascade through the framework is flagged as a critical next step for establishing the accuracy of these predictions.

Still, the study signals a shift in how nuclear safety can be argued. Rather than extrapolating from a handful of worst-case rods, regulators and operators can now contemplate whole-core, rod-resolved accident analyses that capture the staggering diversity of fuel histories inside a working reactor—rods that vary in burnup by a factor of nearly five, in plenum pressure by a factor of three, and in irradiation history in ways that single-rod techniques simply cannot capture. As extended power uprates and longer fuel cycles push the existing light water reactor fleet to record capacity factors, tools like this multiphysics pipeline may become the standard by which the industry demonstrates that its fuel can survive even its worst imagined day.

Subject of Research: Multiphysics simulation of fuel fragmentation, relocation, and dispersal susceptibility during a large-break loss-of-coolant accident in a boiling water reactor

Article Title: Full-core high-burnup BWR LOCA fuel performance analysis and FFRD susceptibility

Article References: Greenquist, I., Wysocki, A., Simon, P.-C. A., Sweet, R., Gamble, K., Asgari, M., Hansen, A., Sarikaya, B., Porter, I., Tusar, J., Capps, N., & Salko, R., Jr. (2026). Full-core high-burnup BWR LOCA fuel performance analysis and FFRD susceptibility. Frontiers in Nuclear Engineering, 5, Article 1822290. https://doi.org/10.3389/fnuen.2026.1822290

Image Credits: AI Generated

DOI: 10.3389/fnuen.2026.1822290

Keywords: boiling water reactor, loss-of-coolant accident, fuel fragmentation relocation and dispersal, BISON, VERA, TRACE, fuel performance, cladding burst, high burnup fuel, Limerick Unit 1, nuclear safety, multiphysics simulation

The editorial, compiled by Nadja Zeleznik of the Milan Vidmar Electric Power Research Institute in Ljubljana, synthesizes four studies that approach nuclear emergency preparedness from strikingly different angles. What emerges is a common thread with far-reaching implications: effective response to a radiological crisis depends not on any single technological breakthrough, but on the seamless integration of trustworthy information, robust technology, institutional coordination, human judgement, and societal engagement. In an era when artificial intelligence and cloud computing promise to revolutionize disaster management, the message is both timely and sobering.

The first contribution, by Min, tackles the relationship between advanced modelling, decision-support systems, and the humans who must ultimately make life-or-death choices. Viewing emergency preparedness as a complex adaptive system, the review identifies a persistent and troubling gap: analytical capabilities keep growing, yet their effective operational use under uncertainty, time pressure, and multi-actor coordination lags behind. Highly predefined, scenario-driven approaches, the analysis finds, perform well when emergencies unfold as expected but falter when events develop in unexpected ways, which is precisely when they matter most. Min proposes the concept of Hybrid Emergency Operations Centres, an integrative framework in which modelling supports rather than replaces human judgement, embedding computational tools within broader processes of governance, communication, and coordination.

The second study shifts attention to a vulnerability that few members of the public ever consider: the cybersecurity of radiation detection itself. Agbemava and colleagues examine cloud-enabled radiation detection systems, which offer scalability, rapid processing, and operational flexibility for distributed monitoring networks. But the same digital infrastructure that makes modern monitoring powerful also creates attack surfaces that could compromise the availability, integrity, and trustworthiness of the very information on which emergency decisions depend. Through a risk-informed approach, the researchers identify threats including supply-chain compromise, manipulation of sensor data, identity spoofing, and disruption of cloud services. Their conclusion is unambiguous: cybersecurity must be regarded as an integral part of nuclear and radiological monitoring and preparedness, not as a separate information-technology concern to be delegated to another department.

Reliable technology, however, must operate within clearly defined institutional arrangements, and this is where the third contribution exposes uncomfortable truths. Camtakan and Saloglu examine nuclear security event response within the Turkish all-hazards emergency management system, highlighting a critical distinction between the formal alignment of emergency plans on paper and the operational clarity required when several organisations with different mandates must act simultaneously. Using communication, coordination, collaboration, and cooperation as an analytical framework, the study identifies interfaces that demand particular attention: command transitions between agencies, forensic evidence management, security-sensitive information sharing, response activation following detection, and international notification. The lesson generalizes far beyond Turkey. Institutional arrangements, the authors suggest, reveal their true strength or fragility precisely at their boundaries, where responsibilities, information, and authority intersect during an evolving event.

The fourth perspective comes from Bertho, who turns to an increasingly visible phenomenon in the aftermath of major nuclear accidents: citizen measurement of ambient dose rates. Since Fukushima, volunteer networks equipped with portable radiation detectors have proliferated across affected regions and beyond, contributing to education, risk awareness, and wider engagement with radiological protection. But Bertho’s review is candid about the challenges that determine whether such networks endure: sustainability, funding, credibility, measurement quality, and the practical use of collected data. The longer-term value of citizen measurement, the analysis suggests, depends on overcoming these obstacles, and doing so would yield benefits that go beyond data collection. Building confidence in measurements and strengthening public understanding of radiation risks can complement institutional monitoring while fostering a more informed risk culture across society.

Taken together, the four studies converge on a socio-technical understanding of preparedness and response, in which technology, organisations, human judgement, and societal actors are closely interconnected. The value of information, whether generated by a sophisticated atmospheric dispersion model, a cloud-connected sensor, or a volunteer with a handheld detector, ultimately depends on its reliability, interpretation, communication, and integration into decision-making processes. The editorial emphasizes that the interfaces between these elements, between models and decision-makers, sensors and digital infrastructure, organisations with different responsibilities, and expert monitoring systems and citizens, are critical points at which resilience can either be strengthened or weakened. A failure at any single interface can cascade through the entire response architecture.

This perspective encourages a decisive shift away from considering individual technologies, models, or procedures in isolation, toward understanding emergency preparedness and response as an integrated system of systems. The implications for future research and investment are concrete. Advances should combine technical innovation with validation in realistic operational settings, systematic attention to human and organisational factors, secure and interoperable information infrastructures, effective communication of uncertainty to decision-makers and the public, and mechanisms that strengthen institutional and societal trust. Exercises, simulations, and interdisciplinary research, the editorial argues, remain essential for testing not only whether individual components perform as intended, but whether they function coherently when brought together under the demanding, chaotic conditions of a real emergency.

The mutual dependence of advanced modelling and management emerges as perhaps the collection’s most important insight. More capable analytical tools can indeed improve situational awareness during a crisis, but their full value is realized only when information is secure, institutions can coordinate effectively, decision-makers can adapt to uncertainty, and relevant stakeholders can understand and trust the processes that produce the numbers flashing on their screens. A state-of-the-art dispersion model is of little use if its output cannot be communicated credibly to evacuated communities, or if the cyber infrastructure feeding it data has been compromised, or if the agencies interpreting its results lack a shared command structure.

As nuclear power expands globally in the pursuit of low-carbon energy and as new radiological technologies proliferate, the stakes of getting emergency preparedness right continue to rise. The research assembled in this collection suggests that the path forward lies not in any single silver bullet, but in the patient, interdisciplinary work of connecting technical, organisational, governance, and societal dimensions into approaches that are adaptive, resilient, and, above all, trusted by the people they are designed to protect. The next nuclear emergency, whenever it comes, will be managed not by machines or institutions alone, but by the strength of the connections between them.

Subject of Research: Nuclear Engineering

Article Title: Editorial: Advanced modeling and management strategies for nuclear and radiological incidents

Article References: Zeleznik, N. (2026). Editorial: Advanced modeling and management strategies for nuclear and radiological incidents. Frontiers in Nuclear Engineering, 5, Article 1966757. https://doi.org/10.3389/fnuen.2026.1966757

Image Credits: AI Generated

DOI: 10.3389/fnuen.2026.1966757

Keywords: nuclear emergencies, radiological incidents, emergency preparedness, decision-support systems, cybersecurity, radiation monitoring, citizen science, socio-technical systems, nuclear safety, crisis management, Editorial, Advanced

The motivation is rooted in a persistent problem in high-consequence industries. Probabilistic Risk Assessment, or PRA, is the discipline that identifies potential failure modes, estimates their likelihoods, and quantifies their consequences across hazards ranging from internal component failures to external events like floods and earthquakes. Yet many commercial-grade tools that carry out this work rest on software architectures dating back to the 1980s. They demand complex installations, specific operating environments, and costly licensing agreements, creating a high barrier for academic researchers, start-ups, small engineering firms, and regulators who simply need to run a rapid check or verify a third party’s results. Worse, the black-box nature of proprietary code makes it difficult to audit how a risk number was actually computed.

KUREAS answers with a zero-deployment philosophy built entirely on HTML5, CSS3, and JavaScript. Because all processing happens in the user’s local browser memory, sensitive facility data never leaves the machine, an air-gapped-by-design property that is especially valuable in nuclear and aerospace settings. The one-file-per-module approach also simplifies configuration management: users can archive the exact software version alongside their project data, ensuring that future analysts can reproduce results with the same tools used in the original study. Since the source code is the HTML itself, anyone can read precisely what calculations are performed, a transparency the author argues is essential for regulatory verification and peer review of safety-critical logic.

The suite mirrors the multi-stage workflow of contemporary risk engineering through specialized modules. KUREAS-HA handles hazard analysis, letting analysts categorize internal and external hazards by frequency and impact, visualize hazard curves, and embed engineering justifications with a built-in rich text editor. KUREAS-FTL constructs fault trees on a drag-and-drop canvas supporting the full range of Boolean gates, including AND, OR, NOT, NAND, and N-of-M voting logic, with automated name-conflict detection and support for sub-tree transfers. KUREAS-ETL manages event trees for accident sequences using a backward rendering algorithm that keeps branch placement consistent with established PRA standards, with real-time path highlighting to trace failures from initiating events to end states.

The heart of the suite is KUREAS-SYS, which departs from conventional graphical modeling with a novel scripting language the author calls How the System Works. Instead of manually wiring logic gates, analysts describe system success in readable keywords such as SYSTEM WORKS, RELIES ON, and IF/THEN, the way system engineers naturally think about their designs. A redundant emergency cooling system with three pumps and two power buses, for example, is captured in a single line combining two of three pumps with either power bus. The software then automatically translates that success description into failure logic, generates the fault tree, and quantifies it. Each component can carry multiple failure modes, ISA-standard piping and instrumentation diagram symbols, and a graphical Failure Modes and Effects Analysis built inside the module’s editors.

In a worked example, with each pump assigned a failure probability of 0.06 and each power bus 0.05, KUREAS-SYS identified the minimal cut sets, the smallest combinations of failures that doom the system: any two pumps failing, or both power buses failing. The overall system failure probability came to 1.3E-2 using Binary Decision Diagram quantification, a result validated independently in Excel. When the built-in common-cause failure module was engaged with a beta-factor of 0.02, accounting for the possibility that supposedly independent components fail together, the estimate rose to 1.9E-2. The engine then produces importance measures that turn raw probabilities into engineering guidance: the Risk Increase Ratio shows how much system risk spikes if a component is assumed failed, the Risk Reduction Ratio shows the safety gain from making a component perfectly reliable, and Percent Contribution identifies which events dominate the failure profile. In the example, each pump carried a Risk Increase Ratio of 9.24, flagging pump maintenance as the most risk-sensitive activity.

Under the hood, the solver proceeds through five steps: translating the success script into failure logic via De Morgan transformations, computing minimal cut sets bottom-up with memoization so repeated modules are solved only once, truncating cut sets whose bounded probability falls below a project threshold, expanding common-cause candidates that share failure mode and component type, and finally quantifying by rare-event approximation, the Minimal Cut-set Upper Bound method, or BDD, the default. The BDD construction orders basic events by frequency of appearance, shares identical nodes through a unique table, and memoizes pairwise operations, and it treats complements exactly, so non-coherent logic is handled without approximation. For repeated importance calculations, the diagram is built once and re-evaluated with modified probabilities at a cost of one pass each.

Benchmarking suggests the browser-based approach is no toy. Against the U.S. Nuclear Regulatory Commission’s classic Fault Tree Handbook, KUREAS reproduced the handbook’s results for series and parallel systems, including a two-phase redundant valve problem yielding a system failure probability of 8E-4. More demanding, the full Generic Pressurized Water Reactor model released for the established SAPHIRE software, comprising 244 fault trees, was solved in KUREAS-FTL down to a 1E-10 truncation in roughly 18 seconds on a laptop, versus 36 seconds for SAPHIRE. A proprietary pumping system design produced more than 13,000 minimal cut sets at a 1E-12 truncation in about nine seconds. A synthetic stress test stacking nested 3-of-5 voting gates grew from 100 to 100,000 cut sets, with KUREAS-SYS matching SAPHIRE’s counts exactly, taking about 92 seconds at the largest size compared with SAPHIRE’s 4 seconds. A built-in Reliability Designer also lets analysts adjust component failure probabilities interactively; in one demonstration, degrading damper reliability fivefold raised system failure probability from 1.1E-4 to 2.0E-4.

Quality assurance is treated as a first-class concern given the software’s ambitions for nuclear and high-safety facilities. KUREAS is developed with ASME NQA-1 Subpart 2.7 software quality requirements in mind, though it does not yet hold NQA-1 certification. The current test suite for KUREAS-SYS contains 76 automated tests covering probability storage edge cases, logic generation, quantification methods, common-cause handling, and importance measures, and periodic regression tests compare outputs against SAPHIRE within numerical tolerances. Project data can be validated and locked from inside the software, with change tracking and quality reporting built in, while GitHub version control provides a transparent record of every modification. Bayesian analysis capabilities round out the suite, maintaining prior and posterior failure distributions alongside operational data, and a reporting module generates formatted Word and Markdown documents with automatic acronyms, numbering, and templates.

The broader significance may lie less in raw speed than in access. Small firms can now run in-house reliability studies without enterprise licensing; students can explore Boolean logic, uncertainty quantification, and system modeling without installation hurdles; and infrastructure projects in developing regions can adopt modern risk methods with nothing more than a browser. For regulators, the one-file, one-logic design means an auditor can read the script directly or rerun an analysis in a controlled environment to confirm reproducibility, potentially smoothing licensing cycles and fostering collaboration between designers and authorities. The author positions KUREAS not as a finished product but as a flexible framework for the next generation of risk research, including dynamic PRA with time-dependent failure models, advanced uncertainty sampling techniques, and machine learning approaches to automated model generation. By lowering the cost of entry to rigorous analysis, the project aims to foster a culture of proactive safety, empowering more engineers to ask what-if questions about the complex systems that underpin modern life before those questions are answered by failure.

Subject of Research: Open-source browser-based software for probabilistic risk assessment and system reliability engineering

Article Title: KUREAS: knowledgebase with uncertainty for risk engineering analysis of systems

Article References: Smith, C. L. (2026). KUREAS: knowledgebase with uncertainty for risk engineering analysis of systems. SoftwareX, 36, Article 103105. https://doi.org/10.1016/j.softx.2026.103105

Image Credits: AI Generated

DOI: 10.1016/j.softx.2026.103105

Keywords: probabilistic risk assessment, system reliability, fault tree analysis, open-source software, minimal cut sets, common-cause failure, importance measures, nuclear safety, Bayesian analysis, web-based tools, Binary Decision Diagrams, quality assurance