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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Congenital Malformations and Perinatal Deaths Among the Children of Atomic Bomb Survivors: A Reappraisal

From 1948 to 1954, the Atomic Bomb Casualty Commission conducted a study of pregnancy outcomes among births to atomic bomb survivors (Hiroshima and Nagasaki, Japan) who had received radiation doses ranging from 0 Gy to near-lethal levels. Past reports (1956, 1981, and 1990) on the cohort did not identify significant associations of radiation exposure with untoward pregnancy outcomes, such as major congenital malformations, stillbirths, or neonatal deaths, individually or in aggregate. We reexamined the risk of major congenital malformations and perinatal deaths in the children of atomic bomb survivors (n = 71,603) using fully reconstructed data to minimize the potential for bias, using refined estimates of the gonadal dose from Dosimetry System 2002 and refined analytical methods for characterizing dose-response relationships. The analyses showed that parental exposure to radiation was associated with increased risk of major congenital malformations and perinatal death, but the estimates were imprecise for direct radiation effects, and most were not statistically significant. Nonetheless, the uniformly positive estimates for untoward pregnancy outcomes among children of both maternal and paternal survivors are useful for risk assessment purposes, although extending them to populations other than the atomic bomb survivors comes with uncertainty as to generalizability.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Quantitative Validation of Control Bands Using Bayesian Statistical Analyses

Abstract This study presents a quantitative validation of 15 Similar Exposure Groups (SEGs) that were derived via control bands inherent to the Risk Level Based Management System currently being used at the Lawrence Livermore National Laboratory. For 93% of the SEGs that were evaluated, statistical analyses of personal exposure monitoring data, through Bayesian Decision Analysis (BDA), demonstrated that the controls implemented from the initial control bands assigned to these SEGs were at least as protective as the controls from the control band outcomes derived from the quantitative data. The BDA also demonstrated that for 40% of the SEGs, the controls from the initial control bands were overly protective, thus allowing controls to be downgraded, which resulted in a significant saving of environmental safety and health (ES&H) resources. Therefore, as a means to both confirm existing controls and to identify candidate SEGs for downgrading controls, efforts to continuously improve the accuracy of Control Banding (CB) strategies through the routine quantitative validation of SEGs are strongly encouraged. Targeted collaborative efforts across institutions and even countries for both the development of CB strategies and the validation of discreetly defined SEGs of commonly performed tasks will not only optimize limited ES&H resources but will also assist in providing a simplified process for essential risk communication at the worker level to the benefit of billions of workers around the world.

McCord, Tyler A.↗
DOE OSTI2022

A genome-wide association study of suicide attempts in the million veterans program identifies evidence of pan-ancestry and ancestry-specific risk loci

In this study, to identify pan-ancestry and ancestry-specific loci associated with attempting suicide among veterans, we conducted a genome-wide association study (GWAS) of suicide attempts within a large, multi-ancestry cohort of U.S. veterans enrolled in the Million Veterans Program (MVP). Cases were defined as veterans with a documented history of suicide attempts in the electronic health record (EHR; N = 14,089) and controls were defined as veterans with no documented history of suicidal thoughts or behaviors in the EHR ( N = 395,064). GWAS was performed separately in each ancestry group, controlling for sex, age and genetic substructure. Pan-ancestry risk loci were identified through meta-analysis and included two genome-wide significant loci on chromosomes 20 ( p = 3.64 × 10 -9 ) and 1 ( p = 3.69 × 10 -8 ). A strong pan-ancestry signal at the Dopamine Receptor D2 locus ( p = 1.77 × 10 -7 ) was also identified and subsequently replicated in a large, independent international civilian cohort ( p = 7.97 × 10 -4 ). Additionally, ancestry-specific genome-wide significant loci were also detected in African-Americans, European-Americans, Asian-Americans, and Hispanic-Americans. Pathway analyses suggested over-representation of many biological pathways with high clinical significance, including oxytocin signaling, glutamatergic synapse, cortisol synthesis and secretion, dopaminergic synapse, and circadian rhythm. These findings confirm that the genetic architecture underlying suicide attempt risk is complex and includes both pan-ancestry and ancestry-specific risk loci. Moreover, pathway analyses suggested many commonly impacted biological pathways that could inform development of improved therapeutics for suicide prevention.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

De-risking fault leakage risk and containment integrity for subsurface storage applications

The subsurface is pivotal in the energy transition, for the sequestration of CO 2 and energy storage. It is crucial to understand to what extent geological faults may form leakage pathways that threaten the containment integrity of these projects. Fault flow behavior has been studied in the context of hydrocarbon development, supported by observations from wells drilled through faults, but such observations are rare in geoenergy projects. Focusing on mechanical behavior as early indicator of potential leakage risks, a probabilistic Coulomb Failure Stress workflow is developed and demonstrated using data from the Decatur CO 2 sequestration project to rank faults based on their containment risk. The analysis emphasizes the importance of fault throw relative to reservoir thickness and pore pressure change in assessing reactivation risks. Integrating this mechanical assessment with geological and dynamic fault analyses contributes to derisking fault containment for geoenergy applications, providing valuable insights for the successful development of subsurface storage projects.

58 GEOSCIENCES↗
DOE OSTI2021

Vegetable intake and the risk of bladder cancer in the BLadder Cancer Epidemiology and Nutritional Determinants (BLEND) international study

Although a potential inverse association between vegetable intake and bladder cancer risk has been reported, epidemiological evidence is inconsistent. This research aimed to elucidate the association between vegetable intake and bladder cancer risk by conducting a pooled analysis of data from prospective cohort studies. Vegetable intake in relation to bladder cancer risk was examined by pooling individual-level data from 13 cohort studies, comprising 3203 cases among a total of 555,685 participants. Pooled multivariate hazard ratios (HRs), with corresponding 95% confidence intervals (CIs), were estimated using Cox proportional hazards regression models stratified by cohort for intakes of total vegetable, vegetable subtypes (i.e. non-starchy, starchy, green leafy and cruciferous vegetables) and individual vegetable types. In addition, a diet diversity score was used to assess the association of the varied types of vegetable intake on bladder cancer risk. The association between vegetable intake and bladder cancer risk differed by sex ( P -interaction = 0.011) and smoking status ( P -interaction = 0.038); therefore, analyses were stratified by sex and smoking status. With adjustment of age, sex, smoking, energy intake, ethnicity and other potential dietary factors, we found that higher intake of total and non-starchy vegetables were inversely associated with the risk of bladder cancer among women (comparing the highest with lowest intake tertile: HR = 0.79, 95% CI = 0.64–0.98, P = 0.037 for trend, HR per 1 SD increment = 0.89, 95% CI = 0.81–0.99; HR = 0.78, 95% CI = 0.63–0.97, P = 0.034 for trend, HR per 1 SD increment = 0.88, 95% CI = 0.79–0.98, respectively). However, no evidence of association was observed among men, and the intake of vegetable was not found to be associated with bladder cancer when stratified by smoking status. Moreover, we found no evidence of association for diet diversity with bladder cancer risk. Higher intakes of total and non-starchy vegetable are associated with reduced risk of bladder cancer for women. Further studies are needed to clarify whether these results reflect causal processes and potential underlying mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Differential patterns of reproductive and lifestyle risk factors for breast cancer according to birth cohorts among women in China, Japan and Korea

Background: The birth cohort effect has been suggested to influence the rate of breast cancer incidence and the trends of associated reproductive and lifestyle factors. We conducted a cohort study to determine whether a differential pattern of associations exists between certain factors and breast cancer risk based on birth cohorts. Methods: This was a cohort study using pooled data from 12 cohort studies. We analysed associations between reproductive (menarche age, menopause age, parity and age at first delivery) and lifestyle (smoking and alcohol consumption) factors and breast cancer risk. We obtained hazard ratios (HRs) with 95% confidence intervals (CIs) using the Cox proportional hazard regression analysis on the 1920s, 1930s, 1940s and 1950s birth cohorts. Results: Parity was found to lower the risk of breast cancer in the older but not in the younger birth cohort, whereas lifestyle factors showed associations with breast cancer risk only among the participants born in the 1950s. In the younger birth cohort group, the effect size was lower for parous women compared to the other cohort groups (HR [95% CI] 0.86 [0.66–1.13] compared to 0.60 [0.49–0.73], 0.46 [0.38–0.56] and 0.62 [0.51–0.77]). Meanwhile, a higher effect size was found for smoking (1.45 [1.14–1.84] compared to 1.25 [0.99–1.58], 1.06 [0.85–1.32] and 0.86 [0.69–1.08]) and alcohol consumption (1.22 [1.01–1.48] compared to 1.10 [0.90–1.33], 1.15 [0.96–1.38], and 1.07 [0.91–1.26]). Conclusion: We observed different associations of parity, smoking and alcohol consumption with breast cancer risk across various birth cohorts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Risk Analysis of a 100 MW Hydrogen Generation Facility near a Nuclear Power Plant

Nuclear power plants (NPPs) are considering flexible plant operations to take advantage of excess thermal and electrical energy. One option for NPPs is to pursue hydrogen production through high temperature electrolysis as an alternate revenue stream to remain economically viable. The intent of this study is to investigate the risk of a 100 MW hydrogen production facility in close proximity to an NPP. Previous analyses have evaluated preliminary designs of a hydrogen production facility in a conservative manner to determine if it is feasible to co-locate the facility within 1 km of an NPP. This analysis specifically evaluates the risk components of a 100 MW hydrogen production facility design, including the likelihood of a leak within the system and the associated consequence to critical NPP targets. This analysis shows that although the likelihood of a leak in an HTEF is not negligible, the consequence to critical NPP targets is not expected to lead to a failure given adequate distance from the plant.

08 HYDROGEN↗
DOE OSTI2024

Dose Consequence and Probabilistic Risk Assessment Integration into Digital Documented Safety Analysis

This is an intern poster presentation. The current reactor authorization process is complex and error prone. The development of a digital Documented Safety Analysis has been proposed to provide an automated and integrated solution to enhance the design and authorization process. The digital DSA will consist of interlinked models, analyses, and reports, all of which will be updated using automated workflows when design changes are made. This poster examines the integration of the probabilistic risk assessment (PRA) with the transient and dose consequence analyses. A PRA for a generic high temperature gas-cooled reactor (HTGR) has been constructed which will drive the input parameters for a transient analysis model currently being constructed. Dose consequence will be determined using the results of the transient analysis and the Radiation Safety Analysis Computer (RSAC) code. Dose consequence data will then be input back into the PRA to drive design parameters.

42 ENGINEERING↗
DOE OSTI2023

Data-Driven Whole-Genome Clustering to Detect Geospatial, Temporal, and Functional Trends in SARS-CoV-2 Evolution

Current methods for defining SARS-CoV-2 lineages ignore the vast majority of the SARS-CoV-2 genome. We develop and apply an exhaustive vector comparison method that directly compares all known SARS-CoV-2 genome sequences to produce novel lineage classifications. We utilize data-driven models that (i) accurately capture the complex interactions across the set of all known SARS-CoV-2 genomes, (ii) scale to leadership-class computing systems, and (iii) enable tracking how such strains evolve geospatially over time. We show that during the height of the original Omicron surge, countries across Europe, Asia, and the Americas had a spatially asynchronous distribution of Omicron sub-strains. Moreover, neighboring countries were often dominated by either different clusters of the same variant or different variants altogether throughout the pandemic. Analyses of this kind may suggest a different pattern of epidemiological risk than was understood from conventional data, as well as produce actionable insights and transform our ability to prepare for and respond to current and future biological threats.

Jacobson, Daniel↗
DOE OSTI2022

Cryo-GCMS Outgassing Screening: Thermal Filler Materials

A study was conducted to investigate the outgassing characteristics of four thermal filler materials. The purpose of this screening was to identify any outgassing products that might be considered reactive, specifically compounds that could result in corrosion in the systems where these materials are used. A range of compounds was observed in the sample headspaces, though most do not stand out as being known reactive species of concern. However, several halogenated compounds and sulfurous compounds- classes compounds known to facilitate corrosion reactions under certain conditions- were observed in low concentrations. The TFLEX 760 exhibited the highest total outgassing, while the GR130 had the lowest. Therm-a-Gap75 and the Si thermal grease exhibited very similar outgassing profiles. It is difficult to predict the extent to which any given compound observed in an analysis of this type might pose a risk in an actual system; factors such as temperature, system geometry, concentration, and gas conductance all play a role in the kinetics governing chemical reactions. It is recommended that the results of these analyses are shared with pertinent materials SMEs familiar with the system(s) in question to evaluate potential risks.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Optimizing Information Automation Using a New Method Based on System-Theoretic Process Analysis: Tool Development and Method Evaluation

This report is an update to a prior report that describes progress and findings for a program of research supporting the design and optimization of information automation systems for nuclear power plants. Much of the domestic nuclear fleet is currently focused on modernizing technologies and processes, including transitioning toward digitalization in the control room and throughout the plant, along with a greater interest in the use of automation, artificial intelligence, robotics, and other emerging technologies. While there are significant opportunities to apply these technologies toward greater plant safety, efficiency, and overall cost-effectiveness, optimizing their design and avoiding potential safety and performance risks depends on ensuring that human performance-related organizational and technical design issues are identified and addressed early in the design process. This report describes modeling tools and techniques, based on sociotechnical systems theory, to support these design goals and their application in the current research effort. The report is primarily intended for senior nuclear energy stakeholders, including regulators, corporate management, and senior plant management. We have developed and employed a method to design an optimized information automation ecosystem (IAE) based on the systems-theoretic constructs underlying sociotechnical systems theory in general and the Systems-Theoretic Accident Modeling and Processes (STAMP) approach in particular. We argue that an IAE can be modeled as an interactive information control system whose behavior can be understood in terms of dynamic control, feedback, and communication relationships amongst the system’s technical and organizational components. We have employed two STAMP-based tools in this effort. The first is Causal Analysis based on STAMP (CAST), an accident and incident analysis technique that was used to examine a performance- and safety-related incident at an industry partner’s plant involving the unintentional activation of an emergency diesel generator. This analysis provided insight into the behavior of the plant’s current information control structure within the context of a specific, significant event. The second tool is Systems Theoretic Process Analysis (STPA) which is a proactive risk analysis tool used to examine existing and potential, planned sociotechnical systems. STPA was used to identify risk factors in the current design of a generic nuclear power plant (NPP) preventive maintenance system. Our analyses focused on identifying near-term system improvements and longer-term design requirements for an optimized IAE system. CAST analysis findings indicate an important underlying contributor to the incident under investigation, and a significant risk to information automation system performance, was perceived time and schedule pressure, which exposed weaknesses in interdepartmental coordination between and within responsible plant organizations and challenged the resilience of established plant processes, until a human caused the eventual event. These findings are discussed in terms of their risk to overall system performance and their implications for information automation system resilience and brittleness. STPA findings exposed several areas of concern in the design of current preventive maintenance systems. We also present two preliminary information automation models. The proactive issue resolution (PIR) model is a test case of an information automation concept with significant near-term potential for application and subsequent reduction in significant plant events. The IAE model is a more general representation of a broader, plantwide information automation system and represents an end-state vision for our work. From our results, we have generated an initial set of preliminary system-level requirements and safety constraints for these models. We have also focused on early development of easy to learn, easy to use “transportable” tools for sociotechnical systems analysis. We intend these to be used by NPP personnel as a means of gaining reliable and relatively quick insight into (1) sociotechnical systems factors impacting incidents and accidents, (2) potential sociotechnical risk factors in existing or planned system designs, and (3) potential weaknesses in a system’s safety and/or information control structure. We conclude the report with a set of summary recommendations, a discussion of planned and potential follow-on research and development, and a draft list of system-level requirements and safety constraints for optimized information automation systems.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Application of Constellation's best estimate alternate source term methodology

Safety analyses for a nuclear power plants need to consider postulated accidents that results in a risk of accidental release of radiation. The regulations require plant specific safety analysis reports to include an evaluation of the requirements of 10CFR50.67. Such a safety analysis report mandates limits such that calculated radiological consequences at certain locations do not exceed established limits in 10CFR50.67 following a postulated release of radioactivity. Analyses should demonstrate, with reasonable assurance, that these prescribed limits are complied with. Conventional methodologies utilize conservative approaches to address lack of uncertainty quantification in the utilized approaches, methods, and/or inputs. These built-in excess conservatisms often result in with compounding effects and hence overly conservative results in the estimated radiological consequences, which leads to inaccurate margin evaluation for operation and accident mitigation. Therefore, evaluating accurate dose consequences is needed for both operational and safety reasons. This paper illustrates the use of the best estimate source term (BEAST) methodology to the case of the loss of coolant accident (LOCA) dose analysis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Advancing process-based flood frequency analysis for assessing flood hazard and population flood exposure

Recent studies have showcased the use of process-based hydrological models with Stochastic Storm Transposition (SST) techniques to conduct Flood Frequency Analysis (FFA). This framework, referred hereby FFA-SST, has proved to be a robust strategy to estimate peak flows of specific annual exceedance probability (e.g., 100-year peak flow) that can reflect natural and anthropogenic disturbances, including changes in land use and meteorological patterns. With the objective of advancing the FFA-SST framework, this study presents for the first time the use of an Integrated Surface-Subsurface Hydrological Model (ISSHM) to conduct FFA-SST by extending the analysis from peak flow responses to flood extent, enabling a unique view and analysis of flood hazard and population flood exposure at the basin scale. As a proof-of-concept, we used the ISSHM, Advanced Terrestrial Simulator (Amanzi-ATS) model, and the SST model, RainyDay, to conduct FFA-SST by simulating the flood response to 5,000 annual synthetic storm events in a 2,227 $km^2$ Southeast Texas watershed. We demonstrate that ATS, without site-specific calibration, provides a robust process-based representation of peak flows, flood extent, streamflow, evapotranspiration, soil moisture content, and water storage changes. Our results and analyses, covering frequency curves up to a 500-year return period for peak flows, basin inundation fractions, and the number of people exposed to flooding, offer a unique perspective to analyze flood impacts across spatial scales. Overall, this study provides critical insights for flood risk management by extending the FFA-SST framework to include both flood hazard and population flood exposure analyses at the basin scale. Such an approach will empower stakeholders and disaster emergency agencies with a more comprehensive understanding of flood impacts across the entire basin domain, facilitating informed decision-making for flood risk assessment and management.

58 GEOSCIENCES↗
DOE OSTI2025

Species Transport Framework Development in SAM for System-Level Tritium Source Term Analysis

The SAM code is under development as a modern system-level modeling and simulation tool for advanced non–light water reactor safety analyses, with recent efforts to add capabilities to evaluate radiological source term risks in these novel reactor concepts. By leveraging the established system-level multiphysics thermal-hydraulic models in SAM, a framework for tightly coupled species transport modeling has been integrated into the code for engineering-scale source term evaluation. This species transport framework was first applied to the simulation of tritium, which is a well-known source term in conventional light water reactors. Tritium poses a unique risk in salt-cooled reactors, especially those with lithium-bearing salts such as the fluoride salt–cooled high-temperature reactor (FHR) concept, as tritium is generated in the salt coolant in significant quantities due to neutron interactions. A compounding factor is the increased mobility of tritium at high temperatures, which is able to permeate through metals while also potentially being retained in graphite pebbles and structures. Engineering-scale models for the tritium transport pathways in a FHR have been developed using the new species transport framework in SAM. The capabilities are assessed through analytical verification problems and validated with data from a graphite retention experiment. In conclusion, the system-level model is demonstrated by performing an initial estimate of baseline tritium generation and flows in a generic reference SAM FHR model, setting a foundation for future studies of source term transient analysis with the potential for further multiscale and multiphysics integration.

SAM↗
DOE OSTI2025

AUTOMATIC GENERATION OF EVENT TREES AND FAULT TREES: A MODEL-BASED APPROACH

In the past few decades, increasing complexity in modern engineering systems has been driven by the integration of a large number of components and by the fact that the system operations involve many disciplines (e.g., thermal-hydraulics, plant operations, cyber-security). Current safety/reliability modeling approaches to such systems are labor intensive, difficult to learn, and rely heavily on simplistic Boolean logic to depict failure propagation and accident progression. While these methods serve well for simple systems (i.e., linear causal systems with limited small inter- and intra-system interactions), their results are difficult to verify when modeling complex systems (typically performed through the extensive use of modeling assumptions). The development of new methods is addressed to meet these challenges through a model-based system engineering (MBSE) lens. Under MBSE philosophy, every aspect of the system (form or function) is represented by a model that completely characterizes its architecture or behavior. MBSE approach greatly improves the management of design, analysis and verification of complex systems. An integration of Dynamic Probabilistic Risk Assessment (DPRA) methods with MBSE models is proposed to perform safety/reliability analyses of engineering systems. In particular, MBSE representation of the system (performed using Systems Modeling Language [SysML]) is coupled with DPRA methods to automatically generate event trees and fault trees.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Failure Analysis–Informed Risk Assessment Framework for Geological Carbon Storage Using Numerical Simulation and Machine Learning

Geological carbon storage (GCS) is recognized as a critical technology for achieving large-scale reductions in anthropogenic carbon dioxide (CO 2 ) emissions. Ensuring long-term containment and safety requires robust risk assessment frameworks that account for geological uncertainty and identify potential failure scenarios. Among various indicators, the area of review (AoR) serves as a key metric for evaluating storage performance, regulatory compliance, and monitoring design, as it delineates the spatial extent impacted by pressure buildup and plume migration. However, conventional AoR-based risk assessments typically perturb parameters within narrow uncertainty bounds, potentially overlooking rare but high-impact events arising from extreme geological conditions. In this study, we present a failure analysis–informed risk assessment framework for large-scale GCS projects to improve site prescreening and monitoring design. A suite of 300 numerical simulations was generated using stochastic geological models that vary five key parameters: net-to-gross ratio, anisotropy azimuth, porosity multiplier, permeability multiplier, and vertical-to-horizontal permeability ratio. Among these, 200 realizations represent normal geological uncertainty, while 100 additional cases explore extreme yet plausible conditions for failure-case analysis. The AoR was simulated and computed from pressure and CO 2 saturation fields, where the baseline AoR boundary, representing the extent predicted under typical geological uncertainty, was defined as the union of 200 normal-range simulations, and failure was identified when extreme-range cases exceeded this baseline. Results show that incorporating broader parameter uncertainty produces significantly larger AoR extents, underscoring the potential underestimation of risk under conventional uncertainty ranges. Furthermore, spatial probability maps derived from failure-induced AoR exceedance identify regions requiring enhanced monitoring attention. Various machine learning (ML)–based classifiers were developed to predict failure occurrence from geological parameters, with the random forest model achieving the highest performance (F1-score of 0.986). Consistent findings from correlation coefficient, feature importance, and Sobol sensitivity analyses reveal that low net-to-gross ratios and permeability multipliers are the dominant risk drivers, reflecting reduced reservoir connectivity and limited pressure dissipation. Altogether, these results provide a novel framework for risk-informed site prescreening and monitoring design that explicitly considers rare but high-impact geological scenarios in GCS projects.

25 ENERGY STORAGE↗
DOE OSTI2020

Risk-Informed ATF and FLEX Analysis for an Enhanced Resilient BWR Under Design-Basis and Beyond-Design-Basis Accidents

This report documents the activities performed by the Idaho National Laboratory (INL) during fiscal year (FY) 2020 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk-Informed System Analysis (RISA) Pathway, Enhanced Resilient Plant (ERP) Systems research. The purpose of the RISA Pathway research and development is to support plant owner-operator decisions with the aim to improve the economics, reliability, and maintain the high levels of safety of current nuclear power plants over periods of extended plant operations. The concept of ERP refers to the combinations of accident-tolerant fuel (ATF), optimal use of diverse and flexible coping strategy (FLEX), enhancements to plant components and systems, and the incorporation of augmented or new passive cooling systems, as well as improved fuel cycle efficiency. The objective of the ERP research effort is to use the RISA methods and toolkit in industry applications, including methods development and early demonstration of technologies, in order to enhance existing reactors’ safety features (both active and passive) and to substantially reduce operating costs through risk-informed approaches to plant design modifications to the plant and their characterization. One main focus of the FY 2020 efforts documented in this report was to extend the analyses conducted in FYs 2018 and 2019 for a pressurized water reactor (PWR) to a boiling water reactor (BWR). The same analysis process, risk analysis approaches, and analysis tools as in the previous work for PWR were used for a generic BWR with near-term ATF cladding (i.e., Iron-Chromium-Aluminum [FeCrAl] cladding and Chromium [Cr]-coated cladding) designs under the postulated station blackout (SBO) and medium loss-of-coolant (MLOCA) accident scenarios. In addition, a FLEX model was developed and incorporated into a generic BWR probabilistic risk assessment (PRA) model using the INL-developed software tool, Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE), to assess the risk impact from FLEX. The other main focus of the FY 2020 efforts was to advance analysis methods, including developing dynamic approach for FLEX human reliability analysis (HRA) using the INL-developed software tool, Event Modeling Risk Assessment using Linked Diagrams (EMRALD), as well as developing a multicriterion benefit evaluation (MCBE) method for evaluating costs and benefits of safety enhancements in nuclear power plants (NPPs). As a case study, the MCBE method was applied to evaluate the costs and benefits brought by FLEX implementation.

99 GENERAL AND MISCELLANEOUS↗