Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “risk”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 613 records · Page 34

A Tool for the Risk-Informed Management of Critical Mission Resilience

We describe a methodology and tool for the risk-informed management and planning of mission resilience. By mapping concepts of resilience onto the elements of a streamlined risk model we are able to tap the substantial portfolio of established risk concepts to provide rapid insights in the evaluation and high-level screening of prospective resilience enhancement measures. This provides a risk-informed, levelized basis for the comparison of disparate resilience solutions and the means of establishing preferences. The methodology begins with identification of critical missions met by a site, and establishment of the supporting physical assets. Scenarios that would result in failure of these assets are systematically identified. Each scenario comprises three elements: realization of a hazard or threat resulting in loss of resources (the current focus being on power, natural gas, and water) to the asset, failure of measures in place to protect the asset against those losses, and realization of the consequent impacts. These scenarios are quantified in terms of their probabilities of occurrence and the magnitude of the resultant consequences (mission outage time), allowing risk-prioritization to focus resilience enhancement considerations. What-If? analyses are conducted through adjusting elements of the risk calculation to reflect the deployment of prospective resilience measures, by which means the efficacies of each of those measures can be compared using common risk metrics across diverse resilience strategies. This paper will also describe the insights from example applications.

resilience, risk, risk assesment, energy, water↗

Adaptive changes in sexual behavior in the high–risk population in response to human monkeypox transmission in Canada can help control the outbreak: Insights from a two–group, two–route epidemic model

Monkeypox, a zoonotic disease, is emerging as a potential sexually transmitted infection/disease, with underlying transmission mechanisms still unclear. We devised a risk-structured, compartmental model, incorporating sexual behavior dynamics. We compared different strategies targeting the high-risk population: a scenario of control policies geared toward the use of condoms and/or sexual abstinence (robust control strategy) with risk compensation behavior change, and a scenario of control strategies with behavior change in response to the doubling rate (adaptive control strategy). Monkeypox's basic reproduction number is 1.464, 0.0066, and 1.461 in the high-risk, low-risk, and total populations, respectively, with the high-risk group being the major driver of monkeypox spread. Policies imposing condom use or sexual abstinence need to achieve a 35% minimum compliance rate to stop further transmission, while a combination of both can curb the spread with 10% compliance to abstinence and 25% to condom use. With risk compensation, the only option is to impose sexual abstinence by at least 35%. Adaptive control is more effective than robust control where the daily sexual contact number is reduced proportionally and remains constant thereafter, shortening the time to epidemic peak, lowering its size, facilitating disease attenuation, and playing a key role in controlling the current outbreak.

60 APPLIED LIFE SCIENCES↗

Waterlogging risk assessment based on self-organizing map (SOM) artificial neural networks: A case study of an urban storm in Beijing

Due to rapid urbanization, waterlogging induced by torrential rainfall has become a global concern and a potential risk affecting urban habitant's safety. Widespread waterlogging disasters have occurred almost annually in the urban area of Beijing, the capital of China. Based on a self-organizing map (SOM) artificial neural network (ANN), a graded waterlogging risk assessment was conducted on 56 low-lying points in Beijing, China. Social risk factors, such as Gross domestic product (GDP), population density, and traffic congestion, were utilized as input datasets in this study. The results indicate that SOM-ANN is suitable for automatically and quantitatively assessing risks associated with waterlogging. The greatest advantage of SOM-ANN in the assessment of waterlogging risk is that a priori knowledge about classification categories and assessment indicator weights is not needed. As a result, SOM-ANN can effectively overcome interference from subjective factors, producing classification results that are more objective and accurate. In this paper, the risk level of waterlogging in Beijing was divided into five grades. As a result, the points that were assigned risk grades of IV or V were located mainly in the districts of Chaoyang, Haidian, Xicheng, and Dongcheng.

54 ENVIRONMENTAL SCIENCES↗

Land use and air quality in urban environments: Human health risk assessment due to inhalation of airborne particles

Highlights: • Biomonitors showed intraurban differences in particles bound metals. • The PM{sub 10} limit (150 µg/m{sup 3}) was exceeded in almost all land uses categories. • Industrial sites had an unacceptable carcinogenic risk (> 1 × 10{sup −4}). • Adults and elder are the most susceptible age groups. • Land use influence health risk due to particle inhalation. Particle matter (PM) and its associated compounds are a serious problem for urban air quality and a threat to human health. In the present study, we assessed the intraurban variation of PM, and characterized the human health risk associated to the inhalation of particles measured on PM filters, considering different land use areas in the urban area of Cordoba city (Argentina) and different age groups. To assess the intraurban variation of PM, a biomonitoring network of T. capillaris was established in 15 sampling sites with different land use and the bioaccumulation of Co, Cu, Fe, Mn, Ni, Pb and Zn was quantified. After that, particles were collected by instrumental monitors placed at the most representative sampling sites of each land use category and an inhalation risk was calculated. A remarkable intraurban difference in the heavy metals content measured in the biomonitors was observed, in relation with the sampling site land use. The higher content was detected at industrial areas as well as in sites with intense vehicular traffic. Mean PM{sub 10} levels exceeded the standard suggested by the U.S. EPA in all land use areas, except for the downtown. Hazard Index values were below EPA's safe limit in all land use areas and in the different age groups. In contrast, the carcinogenic risk analysis showed that all urban areas exceeded the acceptable limit (1 × 10{sup −6}), while the industrial sampling sites and the elder group presented a carcinogenic risk higher that the unacceptable limit. These findings validate the use of T. capillaris to assess intraurban air quality and also show there is an important intraurban variation in human health risk associated to different land use.

54 ENVIRONMENTAL SCIENCES↗

Occurrence and ecological risk of pharmaceuticals in river surface water of Bangladesh

Highlights: • Twelve pharmaceuticals were investigated in river surface water. • Nine pharmaceuticals were detected at ng L{sup −1} level. • MNZ was dominant followed by TMP, ERY-H{sub 2}O and SMX. • Contamination of SMX, TMP and TYL was associated with fed aquaculture. • Preliminary ecological risk assessment showed the medium to low risks. Pharmaceutical contamination in the aquatic environment is a global issue that affects aquatic animals, micro-organisms and human health. The occurrence and preliminary ecological risk of 12 (11 antibiotics and 1 antiepileptic drug) pharmaceuticals were investigated for the first time in the surface water of the old Brahmaputra River, where open-water-fed aquaculture activities are being practiced in Bangladesh. The pharmaceuticals were quantified by high-performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS), operated with positive electrospray ionization (ESI{sup +}) and a multiple reaction monitoring (MRM) mode. Nine pharmaceuticals were detected in the river surface water, whereas three were below the limit of detection (LOD). Metronidazole was detected in all the samples with concentrations ranging from 0.05 to 13.51 ng L{sup −1}. Trimethoprim had the second highest frequency of detection (95%) with the highest concentration (17.20 ng L{sup −1}). The ranges of concentration and detection frequency of sulfonamides and macrolides were < LOD-11.35 and < LOD-16.68 ng L{sup −1}; 35–70 and 60–85%, respectively, whereas carbamazepine was in the range of < LOD-8.80 ng L{sup −1} and had a detection frequency of 65%. The concentrations of sulfamethoxazole, trimethoprim, erythromycin-H{sub 2}O and tylosin were distinctly higher in the fed aquaculture areas. The principal component analysis confirmed that fed aquaculture activities contributed most of the pharmaceutical contamination in the river surface water. Hospitals, nursing homes, sewage wastewater or surface runoff from the surrounding areas might all contribute to the presence of metronidazole and carbamazepine. The preliminary ecological risk assessment revealed that sulfamethoxazole, erythromycin-H{sub 2}O and tylosin showed medium risk, and carbamazepine displayed low risk to sensitive aquatic organisms for maximum measured concentrations. Thus, this study suggests that pharmaceutical contamination in different rivers and seasons needs to be quantified, and ecological as well as human health risks need to be assessed in Bangladesh.

54 ENVIRONMENTAL SCIENCES↗

A quantitative risk assessment framework for fault reactivation in underground hydrogen storage: Coupled simulation and deep learning approach

Underground hydrogen storage (UHS) is emerging as a critical solution for large-scale energy storage. However, like all subsurface fluid injection activities, UHS poses the risk of injection-induced fault reactivation. Accurate risk assessment is essential to ensuring the safety and efficiency of UHS operations. This study presents the development of deep-learning surrogate models for fault reactivation prediction in UHS, trained on a comprehensive database of fully coupled fluid flow-geomechanics simulations. Our findings reveal that analytical models often yield unreliable estimates, with errors up to 54% in the allowable injection pressure, potentially leading to a 40% reduction in UHS operational capacity. The developed surrogate models were incorporated into a quantitative risk assessment (QRA) framework, enabling probabilistic evaluation of fault reactivation risk while accounting for uncertainties in the input variables. Site-specific features, such as horizontal stress gradients, fault’s dip and strike angles, and operational parameters like bottom-hole injection pressure and well-fault distance, were identified as the primary drivers of fault reactivation across various stress regimes. Whereas other hydraulic, geological, and poroelastic reservoir properties were found to have a secondary impact. Notably, we observed that the risk of fault reactivation for a critically oriented fault with a static friction coefficient greater than 0.55 remains below 10% in a normal faulting stress regime. However, the risk significantly increases as the stress regime transitions from normal to strike-slip and ultimately to reverse faulting conditions. These findings underscore the importance of rigorous site characterization and comprehensive QRA evaluations to optimize UHS performance and minimize geomechanical risks.

25 ENERGY STORAGE↗

Utilizing toxicogenomic data to understand chemical mechanism of action in risk assessment

The predominant role of toxicogenomic data in risk assessment, thus far, has been one of augmentation of more traditional in vitro and in vivo toxicology data. This article focuses on the current available examples of instances where toxicogenomic data has been evaluated in human health risk assessment (e.g., acetochlor and arsenicals) which have been limited to the application of toxicogenomic data to inform mechanism of action. This article reviews the regulatory policy backdrop and highlights important efforts to ultimately achieve regulatory acceptance. A number of research efforts on specific chemicals that were designed for risk assessment purposes have employed mechanism or mode of action hypothesis testing and generating strategies. The strides made by large scale efforts to utilize toxicogenomic data in screening, testing, and risk assessment are also discussed. These efforts include both the refinement of methodologies for performing toxicogenomics studies and analysis of the resultant data sets. The current issues limiting the application of toxicogenomics to define mode or mechanism of action in risk assessment are discussed together with interrelated research needs. In summary, as chemical risk assessment moves away from a single mechanism of action approach toward a toxicity pathway-based paradigm, we envision that toxicogenomic data from multiple technologies (e.g., proteomics, metabolomics, transcriptomics, supportive RT-PCR studies) can be used in conjunction with one another to understand the complexities of multiple, and possibly interacting, pathways affected by chemicals which will impact human health risk assessment.

60 APPLIED LIFE SCIENCES↗

Risk Assessment of Salmonellosis from Consumption of Alfalfa Sprouts and Evaluation of the Public Health Impact of Sprout Seed Treatment and Spent Irrigation Water Testing

Abstract We developed a risk assessment of human salmonellosis associated with consumption of alfalfa sprouts in the United States to evaluate the public health impact of applying treatments to seeds (0–5‐log 10 reduction in Salmonella ) and testing spent irrigation water (SIW) during production. The risk model considered variability and uncertainty in Salmonella contamination in seeds, Salmonella growth and spread during sprout production, sprout consumption, and Salmonella dose response. Based on an estimated prevalence of 2.35% for 6.8 kg seed batches and without interventions, the model predicted 76,600 (95% confidence interval (CI) 15,400 – 248,000) cases/year. Risk reduction (by 5 ‐ to 7‐fold) predicted from a 1‐log 10 seed treatment alone was comparable to SIW testing alone, and each additional 1‐log 10 seed treatment was predicted to provide a greater risk reduction than SIW testing. A 3‐log 10 or a 5‐log 10 seed treatment reduced the predicted cases/year to 139 (95% CI 33 – 448) or 1.4 (95% CI <1 – 4.5), respectively. Combined with SIW testing, a 3‐log 10 or 5‐log 10 seed treatment reduced the cases/year to 45 (95% CI 10–146) or <1 (95% CI <1 – 1.5), respectively. If the SIW coverage was less complete (i.e., less representative), a smaller risk reduction was predicted, e.g., a combined 3‐log 10 seed treatment and SIW testing with 20% coverage resulted in an estimated 92 (95% CI 22 – 298) cases/year. Analysis of alternative scenarios using different assumptions for key model inputs showed that the predicted relative risk reductions are robust. This risk assessment provides a comprehensive approach for evaluating the public health impact of various interventions in a sprout production system.

60 APPLIED LIFE SCIENCES↗

Role of reinforcement learning for risk-based robust control of cyber-physical energy systems

Critical infrastructures such as cyber-physical energy systems (CPS-E) integrate information flow and physical operations that are vulnerable to natural and targeted failures. Safe, secure, and reliable operation and control of CPS-E is critical to ensure societal well-being and economic prosperity. Automated control is key for real-time operations and may be mathematically cast as a sequential decision-making problem under uncertainty. Emergence of data-driven techniques for decision making under uncertainty, such as reinforcement learning (RL), have led to promising advances for addressing sequential decision-making problems for risk-based robust CPS-E control. However, existing research challenges include understanding the applicability of RL methods across diverse CPS-E applications, addressing the effect of risk preferences across multiple RL methods, and development of open-source domain-aware simulation environments for RL experimentation within a CPS-E context. This article systematically analyzes the applicability of four types of RL methods (model-free, model-based, hybrid model-free and model-based, and hierarchical) for risk-based robust CPS-E control. Problem features and solution stability for the RL methods are also discussed. We demonstrate and compare the performance of multiple RL methods under different risk specifications (risk-averse, risk-neutral, and risk-seeking) through the development and application of an open-source simulation environment. Motivating numerical simulation examples include representative single-zone and multizone building control use cases. Finally, six key insights for future research and broader adoption of RL methods are identified, with specific emphasis on problem features, algorithmic explainability, and solution stability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

SU-F-T-246: Evaluation of Healthcare Failure Mode And Effect Analysis For Risk Assessment

Purpose: To evaluate the differences between the Veteran Affairs Healthcare Failure Modes and Effect Analysis (HFMEA) and the AAPM Task Group 100 Failure and Effect Analysis (FMEA) risk assessment techniques in the setting of a stereotactic radiosurgery (SRS) procedure were compared respectively. Understanding the differences in the techniques methodologies and outcomes will provide further insight into the applicability and utility of risk assessments exercises in radiation therapy. Methods: HFMEA risk assessment analysis was performed on a stereotactic radiosurgery procedure. A previous study from our institution completed a FMEA of our SRS procedure and the process map generated from this work was used for the HFMEA. The process of performing the HFMEA scoring was analyzed, and the results from both analyses were compared. Results: The key differences between the two risk assessments are the scoring criteria for failure modes and identifying critical failure modes for potential hazards. The general consensus among the team performing the analyses was that scoring for the HFMEA was simpler and more intuitive then the FMEA. The FMEA identified 25 critical failure modes while the HFMEA identified 39. Seven of the FMEA critical failure modes were not identified by the HFMEA and 21 of the HFMEA critical failure modes were not identified by the FMEA. HFMEA as described by the Veteran Affairs provides guidelines on which failure modes to address first. Conclusion: HFMEA is a more efficient model for identifying gross risks in a process than FMEA. Clinics with minimal staff, time and resources can benefit from this type of risk assessment to eliminate or mitigate high risk hazards with nominal effort. FMEA can provide more in depth details but at the cost of elevated effort.

60 APPLIED LIFE SCIENCES↗

TU-FG-201-11: Evaluating the Validity of Prospective Risk Analysis Methods: A Comparison of Traditional FMEA and Modified Healthcare FMEA

Purpose: To examine the ability of traditional Failure mode and effects analysis (FMEA) and a light version of Healthcare FMEA (HFMEA), called Scenario analysis of FMEA (SAFER) by comparing their outputs in terms of the risks identified and their severity rankings. Methods: We applied two prospective methods of the quality management to surface image guided, linac-based radiosurgery (SIG-RS). For the traditional FMEA, decisions on how to improve an operation are based on risk priority number (RPN). RPN is a product of three indices: occurrence, severity and detectability. The SAFER approach; utilized two indices-frequency and severity-which were defined by a multidisciplinary team. A criticality matrix was divided into 4 categories; very low, low, high and very high. For high risk events, an additional evaluation was performed. Based upon the criticality of the process, it was decided if additional safety measures were needed and what they comprise. Results: Two methods were independently compared to determine if the results and rated risks were matching or not. Our results showed an agreement of 67% between FMEA and SAFER approaches for the 15 riskiest SIG-specific failure modes. The main differences between the two approaches were the distribution of the values and the failure modes (No.52, 54, 154) that have high SAFER scores do not necessarily have high FMEA RPN scores. In our results, there were additional risks identified by both methods with little correspondence. In the SAFER, when the risk score is determined, the basis of the established decision tree or the failure mode should be more investigated. Conclusion: The FMEA method takes into account the probability that an error passes without being detected. SAFER is inductive because it requires the identification of the consequences from causes, and semi-quantitative since it allow the prioritization of risks and mitigation measures, and thus is perfectly applicable to clinical parts of radiotherapy.

60 APPLIED LIFE SCIENCES↗

Collagen Turnover in Relation to Risk Factors and Hemodynamics in Human Intracranial Aneurysms

Determinants for molecular and structural instability, that is, impending growth or rupture, of intracranial aneurysms (IAs) remain uncertain. To elucidate this, we endeavored to estimate the actual turnover rates of the main molecular constituent in human IA (collagen) on the basis of radiocarbon ( 14 C) birth dating in relation to IA hemodynamics. Collagen turnover rates in excised human IA samples were calculated using mathematical modeling of 14 C birth dating data of collagen in relation to risk factors and histological markers for collagen maturity/turnover in selected IA. Hemodynamics were simulated using image-based computational fluid dynamics. Correlation, logistic regression, and receiver operating characteristic analyses were performed. Collagen turnover rates were estimated in 46 IA (43 patients); computational fluid dynamics could be performed in 20 IA (20 patients). The mean collagen turnover rate (γ) constituted 126% (±1% error) per year. For patients with arterial hypertension, γ was greater than 2600% annually, whereas γ was distinctly lower with 32% (±1% error) per year for patients without risk factors, such as smoking and hypertension. There was a distinct association between histological presence of rather immature collagen in human IA and the presence of modifiable risk factors. Spatial-temporal averaged wall shear stress predicted rapid collagen turnover (odds ratio, 1.6 [95% CI, 1.0–2.7]). Receiver operating characteristic analysis demonstrated a good test accuracy (area under the curve, 0.798 [95% CI, 0.598–0.998]) for average wall shear stress with a threshold ≥4.9 Pa for rapid collagen turnover. Our data indicate that turnover rates and stability of collagen in human IA are strongly associated with the presence of modifiable risk factors and aneurysmal hemodynamics. Finally, these findings underline the importance of strict risk factor modification in patients with unruptured IA. Future should include more detailed risk factor data to establish a more causal understanding of hemodynamics and the rupture risk of individual IA.

60 APPLIED LIFE SCIENCES↗

A New Approach to Reduce Uncertainties in Space Radiation Cancer Risk Predictions

The prediction of space radiation induced cancer risk carries large uncertainties with two of the largest uncertainties being radiation quality and dose-rate effects. In risk models the ratio of the quality factor (QF) to the dose and dose-rate reduction effectiveness factor (DDREF) parameter is used to scale organ doses for cosmic ray proton and high charge and energy (HZE) particles to a hazard rate for γ-rays derived from human epidemiology data. In previous work, particle track structure concepts were used to formulate a space radiation QF function that is dependent on particle charge number Z, and kinetic energy per atomic mass unit, E. QF uncertainties where represented by subjective probability distribution functions (PDF) for the three QF parameters that described its maximum value and shape parameters for Z and E dependences. Here I report on an analysis of a maximum QF parameter and its uncertainty using mouse tumor induction data. Because experimental data for risks at low doses of γ-rays are highly uncertain which impacts estimates of maximum values of relative biological effectiveness (RBE max ), I developed an alternate QF model, denoted QF γAcute where QFs are defined relative to higher acute γ-ray doses (0.5 to 3 Gy). The alternate model reduces the dependence of risk projections on the DDREF, however a DDREF is still needed for risk estimates for high-energy protons and other primary or secondary sparsely ionizing space radiation components. Risk projections (upper confidence levels (CL)) for space missions show a reduction of about 40% (CL~50%) using the QF γAcute model compared the QFs based on RBE max and about 25% (CL~35%) compared to previous estimates. In addition, I discuss how a possible qualitative difference leading to increased tumor lethality for HZE particles compared to low LET radiation and background tumors remains a large uncertainty in risk estimates.

59 BASIC BIOLOGICAL SCIENCES↗

Technical Report on Preliminary Methodology for Enhancing Risk Monitors with Integrated Equipment Condition Assessment

Small modular reactors (SMRs) generally include reactors with electric output of ~350 MWe or less (this cutoff varies somewhat but is substantially less than full-size plant output of 700 MWe or more). Advanced SMRs (AdvSMRs) refer to a specific class of SMRs and are based on modularization of advanced reactor concepts. AdvSMRs may provide a longer-term alternative to traditional light-water reactors (LWRs) and SMRs based on integral pressurized water reactor concepts currently being considered. Enhancing affordability of AdvSMRs will be critical to ensuring wider deployment. AdvSMRs suffer from loss of economies of scale inherent in small reactors when compared to large (~greater than 600 MWe output) reactors. Some of this loss can be recovered through reduced capital costs through smaller size, fewer components, modular fabrication processes, and the opportunity for modular construction. However, the controllable day-to-day costs of AdvSMRs will be dominated by operation and maintenance (O&M) costs. Technologies that help characterize real-time risk are important for controlling O&M costs. Risk monitors are used in current nuclear power plants to provide a point-in-time estimate of the system risk given the current plant configuration (e.g., equipment availability, operational regime, and environmental conditions). However, current risk monitors are unable to support the capability requirements listed above as they do not take into account plant-specific normal, abnormal, and deteriorating states of active components and systems. This report documents technology developments that are a step towards enhancing risk monitors that, if integrated with supervisory plant control systems, can provide the capability requirements listed and meet the goals of controlling O&M costs. The report describes research results from an initial methodology for enhanced risk monitors by integrating real-time information about equipment condition and POF into risk monitors.

advanced small modular reactor↗

Risk Evaluation for the Diesel Fuel Leak Near Generator Building TRA-674 at the Advanced Test Reactor Complex

This report describes the risk-based evaluation conducted for the underground diesel fuel leak near Generator Building TRA-674 at the Advanced Test Reactor Complex, located at the Idaho National Laboratory. The risk evaluation process followed the Idaho Risk Evaluation Manual for Petroleum Releases (August 2012) guidance document and used the Idaho Risk Evaluation Computational Software (August 2015) to estimate the human health risks posed by residual contamination. Site-specific data were collected to estimate the representative concentrations of the soil for estimating the cumulative risk. Based on historical and current data, the site does not exceed unacceptable risk to human health receptors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Methods to Automate Assessing the Outage Risk and Technical Specification Compliance for Planned Work and Current Plant Conditions. Light Water Reactor Sustainability Program report

This research effort is a part of the Light Water Reactor Sustainability (LWRS) Program, which is a research and development (R&D) program sponsored by the Department of Energy. The LWRS Program is performed in close collaboration with industry R&D programs that provide the technical foundations for licensing and managing the long term, safe, and economical operation of current nuclear power plants (NPPs). The LWRS Program serves to help the United States (U.S.) nuclear industry adopt new technologies and engineering solutions that facilitate the continued safe operation of these NPPs and the extension of their current operating licenses. The Outage Risk Management Improvement Pilot Project seeks to improve the management of nuclear power plant outages. This is done through the development of tools to assist in evaluating pending activities against requirements to detect undesired interactions. Significant efforts are expended to manage the nuclear risk of an outage. The utilities conduct pre outage risk assessments, based on a very detailed review of the outage schedule, to identify where combinations of outage work and out of service equipment would result in degraded conditions with respect to nuclear safety or regulatory compliance. Probabilistic risk assessment studies are conducted to quantify incremental core damage frequency as a result of the outage activities and system unavailability. These studies are usually presented to site and fleet management, the site plant operational review committee, and the NPP’s independent Nuclear Safety Review Board for concurrence that the outage is planned safely and that reasonable measures have been taken to reduce the added risk of conducting the outage. During the outage, the plant configuration is monitored continuously to ensure that it conforms to the approved safety plan. Deviations must be assessed and approved by management committees and, in some cases, the plant operational review committee. In virtually all outage meetings and job briefings, the current nuclear safety status of the plant is communicated, including information on the specific equipment necessary to meet the requirements of the nuclear safety plan. In addition, the operations and outage organizations implement several layers of physical and administrative barriers to prevent unintended interaction with the systems and equipment credited for nuclear safety. In spite of all these efforts, nuclear safety challenges still occur too frequently during outages. While some of these are due to failures of equipment credited for safety, the majority occur because of human error. These typically involve some form of interaction between work activities and plant configuration changes. Some of them are very subtle and are extremely challenging to detect in advance. Nevertheless, they are not acceptable and represent clear opportunities to improve nuclear safety during outages. This particular report will provide a demonstration of the capabilities in the development of a predictive software platform for improving configuration control and accessing the plant risks associated with outage work protocols and illustrate how the software assists in strategies to minimize these interactions. In addition to maintaining nuclear safety, there are numerous administrative requirements that must be complied with during an outage. This report will discuss the use of logic modelling to monitor planned work against technical specification requirements for given plant conditions and to integrate these requirements with shutdown risk models, clearance order requirements and other plant condition requirements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Evaluation of the Los Alamos Nuclear Material Packaging Risk Ranking Method

Repackaging nuclear material into robust containers to protect workers and the public has been ongoing at LANL and around the DOE complex for nearly two decades. The number of containers at LANL is around 5,000; limited resources for repackaging material has led to extended repackaging campaigns and the need to prioritize repackaging. Various methodologies have been used to prioritize the repackaging efforts and to demonstrate progress in risk reduction over time (e.g., Boerigter, 1997). The 2000-1 DNFSB recommendation recognized the limited DOE resources for repackaging, and acknowledged the need to “prioritize and schedule tasks to be undertaken with available funds according to consideration of risks.” Later, in DNFSB recommendation 2005-1, in addition to recommending that DOE develop a packaging standard, the Board recommended that “Characterization information should also be used to develop a surveillance program prioritized according to expected material and container risk (including, for example, material type, material form, and the age and type of container).” In response to requests and recommendations from the DOE and DNSFB to prioritize according to worker risk, a risk ranking method based on the potential consequence of dropping a container from 3 meters was developed in 2007 (Smith, 2007) and updated in 2014 (Hoffman, 2014). Various LANL implementation plans for repackaging were developed over the years using this methodology (Stone, 2014). Currently, this method is utilized in conjunction with an algorithm to mitigate programmatic risk to prioritize container repackaging and material processing (Prochnow, 2015). The purpose of this study is to document how the current risk ranking method works, how it is used and potential limitations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Treatment of uncertainties for security-related design aspects of advanced reactors when using a risk-informed licensing approach

Sabotage of nuclear plants and theft of special nuclear material are different from many other issues potentially affecting public health and safety, and some of those differences drive the content of the present report. A high-level indication of these differences is provided in the US Nuclear Regulatory Commission’s Safety Goal Policy. Promulgated in the mid-1980’s, when it had become reasonably clear that risk analysis had improved to the point where it was possible to understand the risks associated with plant operation, the Safety Goal Policy articulates qualitative safety goals and quantitative health objectives that are meant to guide regulatory and risk management activities, with the following key exceptions noted in the original policy statement: The possible effects of sabotage or diversion of nuclear material are also not presently included in the safety goals. At present there is no basis on which to provide a measure of risk on these matters. It is the Commission’s intention that everything that is needed will be done to keep these types of risks at their present very low level; and it is the Commission’s expectation that efforts on this point will continue to be successful. With these exceptions, it is the Commission’s intent that the risks from all the various initiating mechanisms be considered to the best of the capability of current evaluation techniques. The present report discusses extensions of classical risk management to address some of the special issues that arise in the context of security. Although the present emphasis is on physical security, some attention will be paid to cyber security. A particular focus of the report is on quantitative framework to manage and address uncertainties. This framework is demonstrated via a couple of hypothetical examples.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗