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At least 793 records · Page 44

The Compound Risk of Heat and COVID-19 in New York City: Riskscapes, Physical and Social Factors, and Interventions

Climate change is disrupting the fundamental conditions of human life and exacerbating existing inequity by placing further burdens on communities that are already vulnerable. Risk exposure varies by where people live and work. In this article, we examine the spatial overlap of the compound risks of COVID-19 and extreme heat in New York City. We assess the relationship between socio-demographic and natural, built and social environmental characteristics, and the spatial correspondence of COVID-19 daily case rates across three pandemic waves. We use these data to create a compound risk index combining heat, COVID-19, density and social vulnerability. Our findings demonstrate that the compound risk of COVID-19 and heat are public health and equity challenges. Heat and COVID-19 exposure are influenced by natural, built, and social environmental factors, including access to mitigation infrastructure. Socio-demographic characteristics are significant indicators of COVID-19 and heat exposure and of where compound vulnerability exists. Using GIS mapping, we illustrate how COVID-19 risk geographies change across the three waves of the pandemic and the particular impact of vaccinations before the onset of the third wave. We, then, use our compound risk index to assess heat interventions undertaken by the City, identify neighborhoods of both adequate and inadequate coverage and provide recommendations for future interventions.

COVID-19↗

A Method of Compliance for Achieving Target Collision Risk in UTM Operations

This work proposes a method of compliance to ensure that the collision risks among small unmanned aircraft systems meet the target level of safety. This method presents what is needed for a strategic conflict detection service to achieve the target level of safety when conflict between operational intents are not permitted in nominal situations. A volume-based collision risk model is first developed to calculate the UA-to-UA collision risk given any two operational intent volumes. With this collision risk model, a test strategy is then proposed to assess if a strategic conflict detection service can reduce the collision risk and meet the target level of safety. The method also specifies operational data that are required to be collected to verify if requirements on conformance are being met. Additionally, two new requirements are identified and proposed by this method beyond the current standard for strategic conflict detection. In the sensitivity analysis, three main factors contributing to the collision risk are investigated. The analysis shows that buffers should be considered in a strategic conflict detection service when deconflicting operational intents. The results also reveal that the selection of test cases plays an important role in evaluating the strategic conflict detection service, and they should be representative and sufficiently complex in evaluation tests.

Collision Risk↗

A Method of Compliance for Achieving Target Collision Risk in UTM Operations

This work proposes a method of compliance to ensure that the collision risks among small unmanned aircraft systems meet the target level of safety. This method presents what is needed for a strategic conflict detection service to achieve the target level of safety when conflict between operational intents are not permitted in nominal situations. A volume-based collision risk model is first developed to calculate the UA-to-UA collision risk given any two operational intent volumes. With this collision risk model, a test strategy is then proposed to assess if a strategic conflict detection service can reduce the collision risk and meet the target level of safety. The method also specifies operational data that are required to be collected to verify if requirements on conformance are being met. Additionally, two new requirements are identified and proposed by this method beyond the current standard for strategic conflict detection. In the sensitivity analysis, three main factors contributing to the collision risk are investigated. The analysis shows that buffers should be considered in a strategic conflict detection service when deconflicting operational intents. The results also reveal that the selection of test cases plays an important role in evaluating the strategic conflict detection service, and they should be representative and sufficiently complex in evaluation tests.

UTM, Method of Compliance, collision risk↗

A Method of Compliance for Achieving Target Collision Risk in UTM Operations

This work proposes a method of compliance to ensure that the collision risks among small unmanned aircraft systems meet the target level of safety. This method presents what is needed for a strategic conflict detection service to achieve the target level of safety when conflict between operational intents are not permitted in nominal situations. A volume-based collision risk model is first developed to calculate the UA-to-UA collision risk given any two operational intent volumes. With this collision risk model, a test strategy is then proposed to assess if a strategic conflict detection service can reduce the collision risk and meet the target level of safety. The method also specifies operational data that are required to be collected to verify if requirements on conformance are being met. Additionally, two new requirements are identified and proposed by this method beyond the current standard for strategic conflict detection. In the sensitivity analysis, three main factors contributing to the collision risk are investigated. The analysis shows that buffers should be considered in a strategic conflict detection service when deconflicting operational intents. The results also reveal that the selection of test cases plays an important role in evaluating the strategic conflict detection service, and they should be representative and sufficiently complex in evaluation tests.

UTM↗

Development/Modernization of an Advanced Non-Light Water Reactor Probabilistic Risk Assessment

In 2015, GE Hitachi Nuclear Energy (GEH) teamed with Argonne National Laboratory (Argonne) to perform Research and Development (R&D) of next-generation Probabilistic Risk Assessment (PRA) methodologies for the modernization of an advanced non-Light Water Reactor (non-LWR) PRA. This effort built upon a PRA developed in the early 1990s for GEH’s Power Reactor Inherently Safe Module (PRISM) Sodium Fast Reactor (SFR). The work had four main tasks: internal events development modeling the risk from the reactor for hazards occurring at-power internal to the plant; an all hazards scoping review to analyze the risk at a high level from external hazards such as earthquakes and high winds; an all modes scoping review to understand the risk at a high level from operating modes other than at-power; and risk insights to integrate the results from each of the three phases above. To achieve these objectives, GEH and Argonne used and adapted proven PRA methodologies and techniques to build a modern non-LWR all hazards/all modes PRA. The teams also advanced non-LWR PRA methodologies, which is an important outcome from this work. This report summarizes the project outcomes in two major phases. The first phase presents the methodologies developed for non-LWR PRAs. The methodologies are grouped by scope, from Internal Events At-Power (IEAP) to hazards analysis to modes analysis. The second phase presents details of the PRISM PRA model which was developed as a validation of the non-LWR methodologies. The PRISM PRA was performed in detail for IEAP, and at a broader level for hazards and modes. In addition to contributing methodologies, this project developed risk insights applicable to non-LWR PRA, including focus-areas for future R&D, and conclusions about the PRISM design.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

RISK MONITORING CAPABILITES FROM DYNAMIC PRA DATA

Risk Monitors (RMs) are software tools that are employed in nuclear power plants to monitor the safety properties of the plant itself during operation. These safety properties are generated using classical PRA methods which are typically based on static Boolean structures such as Fault-Trees (FTs) and Event-Trees (ETs). The outcomes of these methods are Core Damage Frequency (CDF) and risk importance values of plant components (e.g., valves and pumps). Examples of Risk Importance Measures (RIMs) commonly used are: Risk Achievement Worth (RAW), Risk Reduction Worth (RRW), Birnbaum (B) and Fussell-Vesely (FV) [1,2]. In a RM these values are updated in real time once plant components status is updated (e.g., under maintenance, off-line, testing). In addition, RMs can be used to optimize maintenance schedules so those safety features of the plant are below plant standard values. This paper presents an approach to create temporal profiles of RIMs (i.e., RM capabilities) given a temporal change of the plant configuration. Instead of employing data generated by ETs and FTs, the proposed approach will employ data generated by Dynamic PRA methods. In contrast to classical PRA methods, Dynamic PRA methods couple stochastic methods with safety analysis codes to determine risk associate to complex systems such as nuclear plants. Compared to classical PRA methods, they can evaluate with higher resolution the safety impact of timing and sequencing of events on the accident progression. We will describe how classical RIMs can be generated by Dynamic PRA data and then we will show how the temporal profiles of the RIMs can be generated given a temporal profile of the system configuration.

97 MATHEMATICS AND COMPUTING↗

Risk Methodology for Assessment of Fuel Debris Retrieval Options at the Fukushima Daiichi Nuclear Power Station

The mission of the Nuclear Damage Compensation and Decommissioning Facilitation Corporation (NDF) includes the mid-to-long-term decommissioning planning of the reactors at the Fukushima Daiichi Nuclear Power Station. To carry out its mission, NDF needs to be able to assess worker safety and public health risks that currently exist at the Fukushima Daiichi Nuclear Power Station and the implications of various actions that may be taken to reduce such risks. Pacific Northwest National Laboratory (PNNL) entered into a contract with NDF to support NDF’s mission by developing a risk assessment methodology that will support NDF’s evaluation of options for transitioning molten and solidified fuels within each unit into safer, more stable, configurations given the ever-changing state of knowledge and large uncertainties. The underpinning of this approach, which incorporates both expert elicitation and adapts probabilistic risk assessment and hazard analysis techniques, is its organization of potential release mechanisms and accident scenarios into a more manageable set of safety issues, which are systematically characterized to allow for useful comparison between fuel debris retrieval options as well as the identification of risk drivers and discriminators. The approach also lends itself to be easily updated as the general state of knowledge improves and will serve as a vital input to prioritizing future investigations associated with human health and safety at the Fukushima site. This paper describes the overall approach developed by PNNL to risk-inform the comparison between fuel debris retrieval strategies and discusses lessons learned from implementing the approach.

Fukushima, Risk Assessmnet, Nuclear Decommissionin↗

Qualitative Decision and Risk Assessment Approaches for Managing Nuclear Materials - 19061

Qualitative approaches to performing decision analyses and risk assessments have recently been developed at ORNL with the goal of providing simple tools to help manage complex projects that have a variety of drivers, constraints, or both. Many of the DoE's nuclear materials management projects involve making 'keep-or-dispose' decisions for nuclear materials and then developing projects to manage or dispose of the materials. ORNL uses decision analysis tools to identify and rank options for accomplishing nuclear materials management projects, and risk assessment tools to evaluate the preferred option(s) to identify risks and prioritize mitigation actions to reduce risks during implementation. This paper focuses on application of the decision analysis and risk-based planning tool(s) to guide management of projects during the planning and start-up phases when only preliminary project information is likely to be available. Such an analysis seeks to reduce risks, lower costs, and improve chances of project success. Examples showing the use of the tools in nuclear waste management scenarios are provided. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Nuclear power plant risk-informed surveillance frequency control program implementation at the Duke Catawba nuclear plant with a focus on instrumentation and control systems - 333

This paper summarizes an updated process for risk-informed surveillance frequency control program (SFCP) implementation at the Catawba Nuclear Power Plant in the past year. This program includes selection and prioritization of specific target surveillance test interval extensions; and development, review, and implementation of surveillance test risk informed documented evaluation (STRIDE) packages designed to support extension of conventional surveillance requirement test intervals, in accordance with 'Risk-Informed Technical Specifications Initiative 5b, Risk-Informed Method for Control of Surveillance Frequencies, Industry Guideline,' NEI 04-10, Revision 1 . The scope of work associated with STRIDE development includes probabilistic risk assessment (PRA) case studies, deterministic assessment (DA) evaluations, and, where required, instrument drift evaluation (IDE). The STRIDE implementation efforts have also included support of independent decision-making panel (IDP) meetings at the implementing power stations and IDP member training. The purpose of this paper is to provide a presentation of a refined process for STRIDE development with a focus on instrumentation and control systems based on author experience, which includes support for the development of multiple STRIDE packages for the Catawba Nuclear Plant. This paper outlines a framework for practical implementation of an SFCP within the context of an integrated risk-informed performance-based regulation application program with emphasis on instrumentation and control systems. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Application of Banking Scoring and Rating for Coherent Risk Measures in Electricity Systems ABSCORES

This project developed a framework for asset and system risk management that can be incorporated into current electricity system operations to improve economic efficiency and establish an Electric Assets Risk Bureau. We leveraged scoring and ratings from banking and financial institutions alongside current optimization methods in dispatching power systems to help system operators and electricity markets schedule resources. This approach is based on the observation that there are major discrepancies between the power scheduled by a system operator and the actual power generated/consumed. These discrepancies—exacerbated by unplanned contingencies (e.g., natural disasters)—are caused by multiple factors, including the different financial, environmental and risk preferences of power producers, consumers, and aggregators. We developed a framework that counteracts two failures in electricity system operations: imperfect information and missing markets for products. The technical approach included five tasks. Tasks 1 and 2 supported the development of risk scores at the asset level with historical data collected for this project. Tasks 3, 4, and 5 incorporated scoring into decision-making at the system level. The proposed effort achieved PERFORM's Program Objectives because the proposed outputs and algorithms do not exist in the electricity industry and are an innovative approach to managing risk. Since the acknowledged need to better assess and act upon risk profiles for grid assets has not been met by the industry, this project will also impact ARPA-E's Mission Areas, including improving energy efficiency and giving the U.S. a technological lead in advanced energy technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Improving online risk assessment with equipment prognostics and health monitoring

The current approach to evaluating the risk of nuclear power plant (NPP) operation relies on static probabilities of component failure, which are based on industry experience with the existing fleet of nominally similar light water reactors (LWRs). As the nuclear industry looks to advanced reactor designs that feature non-light water coolants (e.g., liquid metal, high temperature gas, molten salt), this operating history is not available. Many advanced reactor designs use advanced components, such as electromagnetic pumps, that have not been used in the US commercial nuclear fleet. Given the lack of rich operating experience, we cannot accurately estimate the evolving probability of failure for basic components to populate the fault trees and event trees that typically comprise probabilistic risk assessment (PRA) models. Online equipment prognostics and health management (PHM) technologies can bridge this gap to estimate the failure probabilities for components under operation. The enhanced risk monitor (ERM) incorporates equipment condition assessment into the existing PRA and risk monitor framework to provide accurate and timely estimates of operational risk.

active and passive components↗

The National Risk Assessment Partnership’s integrated assessment model for carbon storage: A tool to support decision making amidst uncertainty

The US DOE-funded National Risk Assessment Partnership (NRAP) has developed an integrated assessment model (NRAP-IAM-CS) that can be used to simulate carbon dioxide (CO 2 ) injection, migration, and associated impacts at a geologic carbon storage site. The model, NRAP-IAM-CS, incorporates a system-modeling-based approach while taking into account the full subsurface system from the storage reservoir to groundwater aquifers and the atmosphere. The approach utilizes reduced order models (ROMs) that allow fast computations of entire system performance even for periods of hundreds to thousands of years. The ROMs are run in Monte Carlo mode allowing estimation of uncertainties of the entire system without requiring long computational times. The NRAP-IAM-CS incorporates ROMs that realistically represent several key processes and properties of storage reservoirs, wells, seals, and groundwater aquifers. Results from the NRAP-IAM-CS model are used to quantify risk profiles for selected parameter distributions of reservoir properties, seal properties, numbers of wells, well properties, thief zones, and groundwater aquifer properties. A series of examples is used to illustrate how the risk under different storage conditions evolves over time, both during injection, in the near-term post injection period, and over the long term. Finally, it is also shown how results from NRAP-IAM-CS can be used to investigate the importance of different parameters on risk of leakage and risk of groundwater contamination under different storage conditions.

54 ENVIRONMENTAL SCIENCES↗

Fossil Power Plant Cyber Security Life-Cycle Risk Reduction, A Practical Framework for Implementation

Market conditions are forcing fossil electricity generation facility owners and operators to implement advanced digital technologies. These technologies enable efficiencies, operational flexibility, operations and maintenance efficiencies, and adapting to a transitioning workforce. These digital technologies, however, can increase the cybersecurity attack surface. The purpose of this research was to develop a holistic cybersecurity risk reduction framework for fossil generation facilities. The framework begins with assessing how cyber risk changes across facility life cycles, including plant, system, vendor, and business life cycles. The next phase performs consequence analysis to prioritize high consequence events. Focusing on high consequence events allows owners to use a graded, risk-informed approach to prioritize cybersecurity efforts. The final phase identifies the digital asset attack surface in sensors and instrumentation and control equipment. After the vulnerabilities are identified, the owner selects mitigating cybersecurity control measures (or countermeasures) based on the risk analysis from the previous phases. This report describes the current industry cybersecurity best practices in fossil generation that are based on the first principles for cybersecurity engineering. The report is divided into five sections that describe the implementation of the risk reduction framework and present identified research, methodological, and technology gaps that were identified through this course of research and development.

01 COAL, LIGNITE, AND PEAT↗

Probabilistic Risk Assessment of a Sustained Lunar Presence

The Artemis Base Camp will be our first sustainable foothold on the lunar frontier. The base camp includes a lunar surface habitat, power systems, and infrastructure needed to develop capabilities on future missions to Mars. NASA Probabilistic Risk Assessment (PRA) methodologies tend to focus on in-flight Loss of Crew (LOC) or Loss of Vehicle (LOV) risk estimates for short mission durations. However, lunar habit support systems and power generation systems will need to continuously operate. Existing risk methodologies will need to adapt to understand risk drivers in new environments under different operating conditions, such as lunar dust and increased micro-meteoroid exposure. Insights from the nuclear and oil industries can provide guidance to NASA risk practitioners to tackle this new challenge.

risk assessment↗

Mental Models for Managing Grid Cybersecurity Risk - ARC Industry Forum, Cybersecurity and Energy Transition

A proper mental model of the concepts of cyber risk and its components of threat and exploitability and consequence is necessary to allocate limited resources to different security activities, especially when considered alongside reliability and regulatory and economic risks. Understanding the consequence and frequency different risks are realized also helps align the right mitigations to the right risks. Cyber-informed engineering (CIE) is an emerging method to “engineer out” cyber risk across product and system lifecycles, and INL has a portfolio of programs operationalizing CIE’s principles for the energy sector.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Identification of Novel, Replicable Genetic Risk Loci for Suicidal Thoughts and Behaviors Among US Military Veterans

Importance: Suicide is a leading cause of death; however, the molecular genetic basis of suicidal thoughts and behaviors (SITB) remains unknown. Objective: To identify novel, replicable genomic risk loci for SITB. Design, Setting, and Participants: This genome-wide association study included 633 778 US military veterans with and without SITB, as identified through electronic health records. GWAS was performed separately by ancestry, controlling for sex, age, and genetic substructure. Cross-ancestry risk loci were identified through meta-analysis. Study enrollment began in 2011 and is ongoing. Data were analyzed from November 2021 to August 2022. Main Outcome and Measures: SITB. Results: A total of 633 778 US military veterans were included in the analysis (57 152 [9%] female; 121 118 [19.1%] African ancestry, 8285 [1.3%] Asian ancestry, 452 767 [71.4%] European ancestry, and 51 608 [8.1%] Hispanic ancestry), including 121 211 individuals with SITB (19.1%). Meta-analysis identified more than 200 GWS (P < 5 × 10 -8 ) cross-ancestry risk single-nucleotide variants for SITB concentrated in 7 regions on chromosomes 2, 6, 9, 11, 14, 16, and 18. Top single-nucleotide variants were largely intronic in nature; 5 were independently replicated in ISGC, including rs6557168 in ESR1, rs12808482 in DRD2, rs77641763 in EXD3, rs10671545 in DCC, and rs36006172 in TRAF3. Associations for FBXL19 and AC018880.2 were not replicated. Gene-based analyses implicated 24 additional GWS cross-ancestry risk genes, including FURIN, TSNARE1, and the NCAM1-TTC12-ANKK1-DRD2 gene cluster. Cross-ancestry enrichment analyses revealed significant enrichment for expression in brain and pituitary tissue, synapse and ubiquitination processes, amphetamine addiction, parathyroid hormone synthesis, axon guidance, and dopaminergic pathways. Seven other unique European ancestry–specific GWS loci were identified, 2 of which (POM121L2 and METTL15/LINC02758) were replicated. Two additional GWS ancestry-specific loci were identified within the African ancestry (PET112/GATB) and Hispanic ancestry (intergenic locus on chromosome 4) subsets, both of which were replicated. Further, no GWS loci were identified within the Asian ancestry subset; however, significant enrichment was observed for axon guidance, cyclic adenosine monophosphate signaling, focal adhesion, glutamatergic synapse, and oxytocin signaling pathways across all ancestries. Within the European ancestry subset, genetic correlations (r > 0.75) were observed between the SITB phenotype and a suicide attempt-only phenotype, depression, and posttraumatic stress disorder. Additionally, polygenic risk score analyses revealed that the Million Veteran Program polygenic risk score had nominally significant main effects in 2 independent samples of veterans of European and African ancestry.

60 APPLIED LIFE SCIENCES↗

Association of female reproductive and hormonal factors with gallbladder cancer risk in Asia: A pooled analysis of the Asia Cohort Consortium

Abstract The female predominance of gallbladder cancer (GBC) has led to a hypothesis regarding the hormone‐related aetiology of GBC. We aimed to investigate the association between female reproductive factors and GBC risk, considering birth cohorts of Asian women. We conducted a pooled analysis of 331,323 women from 12 cohorts across 4 countries (China, Japan, Korea, and Singapore) in the Asia Cohort Consortium. Cox proportional hazard models were used to estimate the hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) to assess the association between reproductive factors (age at menarche, parity, age at first delivery, breastfeeding, and age at menopause) and GBC risk. We observed that a later age at menarche was associated with an increased risk of GBC (HR 1.4, 95% CI 1.16–1.70 for 17 years and older vs. 13–14 years), especially among the cohort born in 1940 and later (HR 2.5, 95% CI 1.50–4.35). Among the cohort born before 1940, women with a later age at first delivery showed an increased risk of GBC (HR 1.56, 95% CI 1.08–2.24 for 31 years of age and older vs. 20 years of age and younger). Other reproductive factors did not show a clear association with GBC risk. Later ages at menarche and at first delivery were associated with a higher risk of GBC, and these associations varied by birth cohort.

Shin, Aesun↗

Risk assessment of engineering diseases of embankment–bridge transition section for railway in permafrost regions

Abstract The embankment–bridge transition section (EBTS) is one of the zones where railway diseases occur frequently in permafrost regions. Disease risk assessment of EBTSs can provide guidance for maintenance. In this study, considering the engineering geological conditions, climate characteristics, and embankment structure types along the Qinghai–Tibet Railway (QTR) as well as based on the disease inventory of the QTR from 2010 to 2019, the logistic regression (LR), support vector machine (SVM), and combination‐weight‐based gay relation analysis (GRA) were used for disease risk assessment of the EBTSs along the QTR in permafrost regions. The results indicate that the LR and SVM models have a better capability for EBTS disease prediction than the GRA model, and the SVM model can select more disease samples in relatively larger regions than the LR model. Based on the SVM and LR models, the risk level of EBTSs is divided into four classes: low‐ (29.9%), moderate‐ (39.6%), high‐ (22.1%), and very high (8.4%) risk. Finally, we selected 272 EBTSs in high‐ and very‐high‐risk classes for key observation during the maintenance of the QTR in permafrost regions. This study provides a reference for the risk assessment of railways built in permafrost regions using data‐driven methods.

Zhang, Saize↗