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At least 703 records · Page 39

A Transdisciplinary Approach to Characterize Hydrological Controls on Groundwater-Dependent Ecosystem Health

Sustainable groundwater management provides an opportunity for environmental water needs to be considered and secured by establishing appropriate groundwater thresholds. Ecosystems that require access to groundwater for some or all their water requirements are referred to as groundwater dependent ecosystems (GDEs). However, large data gaps often exist around the cause-and-effect relationships between groundwater conditions and the impacts they have on GDEs. These data gaps are largely attributed to a lack of shallow monitoring wells near GDEs, and a lack of practical biological metrics to characterize ecosystem health. This transdisciplinary study explores the use of geophysics (electrical resistivity tomography) to fill in our understanding of shallow subsurface soil-hydrological conditions within GDEs. In addition, we develop an approach to characterize ecosystem health within GDEs, using groundwater-dependent vegetation (phreatophytes) as indicators. Ten vegetation variables were used to characterize six biological indicators—growth, diversity, recruitment, structure, native plant dominance, and survivorship—which were used to infer ecosystem health conditions. Health indicators for groundwater-dependent vegetation were found to directly correlate with subsurface conditions, where greater groundwater availability (higher soil moisture content and shallower groundwater levels) was associated with “healthier” vegetation. This study provides a new approach to integrate hydrological, geophysical, and biological data to strengthen monitoring programs and inform water resource management decisions.

54 ENVIRONMENTAL SCIENCES↗

A Control Chart Approach for Representing and Mining Data Streams with Shape Based Similarity

The mining of data streams for online condition monitoring is a challenging task in several domains including (electric) power grid system, intelligent manufacturing, and consumer science. Considering a power grid application in which thousands of sensors, called the phasor measurement units, are deployed on the power grid network to continuously collect streams of digital data for real-time situational awareness and system management. Depending on design, each sensor could stream between ten and sixty data samples per second. The myriad of sensory data captured could convey deeper insights about sequence of events in real-time and before major damages are done. However, the timely processing and analysis of these high-velocity and high-volume data streams is a challenge. Hence, a new data processing and transformation approach, based on the concept of control charts, for representing sequence of data streams from sensors is proposed. In addition, an application of the proposed approach for enhancing data mining tasks such as clustering using real-world power grid data streams is presented. The results indicate that the proposed approach is very efficient for data streams storage and manipulation.

big data↗

Controlling O&M Costs of Advanced SMRs using Prognostics and Enhanced Risk Monitoring

Advanced small modular reactors (AdvSMRs) can contribute to safe, sustainable, and carbon-neutral energy production. The economics of small reactors (including AdvSMRs) will be impacted by the reduced economy-of-scale savings when compared to traditional light water reactors. The most significant controllable element of the day-to-day costs involves operations and maintenance (O&M). Enhancing affordability of AdvSMRs through technologies that help control O&M costs will be critical to ensuring their practicality for wider deployment.A significant component of O&M costs is the management and mitigation of degradation of components due to their impact on planning maintenance activities and staffing levels. Technologies that help characterize real-time risk of failure of key components are important in this context. Given the possibility of frequently changing AdvSMR plant configurations, approaches are needed to integrate three elements – advanced plant configuration information, equipment condition information, and risk monitors – to provide a measure of risk that is customized for each AdvSMR unit and support real-time decisions on O&M. This article describes an overview of ongoing research into diagnostics/prognostics and enhanced predictive risk monitors (ERM) for this purpose.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Evaluation of Enhanced Risk Monitors for Use on Advanced Reactors

This study provides an overview of the methodology for integrating time-dependent failure probabilities into nuclear power reactor risk monitors. This prototypic enhanced risk monitor (ERM) methodology was evaluated using a hypothetical probabilistic risk assessment (PRA) model, generated using a simplified design of a liquid-metal-cooled advanced reactor (AR). Component failure data from industry compilation of failures of components similar to those in the simplified AR model were used to initialize the PRA model. Core damage frequency (CDF) over time were computed and analyzed. In addition, a study on alternative risk metrics for ARs was conducted. Risk metrics that quantify the normalized cost of repairs, replacements, or other operations and management (O&M) actions were defined and used, along with an economic model, to compute the likely economic risk of future actions such as deferred maintenance based on the anticipated change in CDF due to current component condition and future anticipated degradation. Such integration of conventional-risk metrics with alternate-risk metrics provides a convenient mechanism for assessing the impact of O&M decisions on safety and economics of the plant. It is expected that, when integrated with supervisory control algorithms, such integrated-risk monitors will provide a mechanism for real-time control decision-making that ensure safety margins are maintained while operating the plant in an economically viable manner.

ECA↗

Co-optimization of nuclear reactor flexible power operation and maintenance scheduling

As flexible power operation of nuclear power plants becomes more attractive due to the reduction in fossil-fueled dispatchable generation on energy grids, finding optimal power production strategies that balance revenue generation with operational concerns becomes more complex. This article presents a general framework to aid operators in designing economically optimal long term dispatch strategies for nuclear power plants. The principal novelty is the linking of estimated system remaining useable life (RUL) to strategic operational decisions. It is shown that, depending on the relationship between the fixed costs from maintenance and the associated lost revenue from an outage, it can be economically optimal in the long term to delay a maintenance outage and not perform this alongside refueling. For a given relationship between power ramping and degradation, optimal strategies were found that discouraged load following in some situations while minimizing unnecessary maintenance. It is shown that heavy load following can cause maintenance and refueling outages to diverge due to their inverse relationships with respect to load following, potentially leading to a significant loss in capacity factor. As a result, this general framework can be applied to specific reactor dispatch allowing operators to adapt operational strategies as future grid conditions change.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Diagnostic-free onboard battery health assessment

Diverse usage patterns induce complex and variable aging behaviors in lithiumion batteries, complicating accurate health diagnosis and prognosis. Separate diagnostic cycles are often used to untangle the battery’s current state of health from prior complex aging patterns. However, these same diagnostic cycles alter the battery’s degradation trajectory, are time-intensive, and cannot be practically performed in onboard applications. Here, in this work, we leverage portions of operational measurements in combination with an interpretable machine learning model to enable rapid, onboard battery health diagnostics and prognostics without offline diagnostic testing and the requirement of historical data. We integrate mechanistic constraints within an encoder-decoder architecture to extract electrode states in a physically interpretable latent space and enable improved reconstruction of the degradation path. The health diagnosis model framework can be flexibly applied across diverse application interests with slight fine-tuning.

battery aging reconstruction↗

Prognostic model and failure mechanisms of steam generators in Sodium-Cooled fast reactors

This paper presents a prognostic model for sodium-cooled fast reactor (SFR) steam generators (SGs). Here, the purpose of the model is to estimate the remaining useful life of SFR SGs and thus to support the decision-making of autonomous control. SFR SGs are of great interest for plant integrity due to their harsh operation environment. They operate at higher temperatures and higher coolant-to-steam pressure differences than those of current light water reactors (LWR). The severity of the SFR SG failure consequences, which include water-sodium contact, is another reason. Understanding its failure mechanisms is important for the development of its prognostic model. Based on our literature review and physics-based analysis, we concluded that creep would be a dominant degradation mode of SFR SGs due to SFR’s high-temperature and high-pressure environment. Thus, creep is the focus of the prognostic model. Various other failure modes were also investigated in this study. The mechanical fatigue due to flow-induced vibration is usually observed in early developmental phases and would not be an important issue during normal operation. The thermal fatigue due to thermal stripping is occasionally observed in other components in SFRs but does not affect SG integrity. Pure water stress corrosive crack, fretting, and so on are commonly observed in LWR SGs but are significantly less important in SFR SGs because of the high temperatures, high pressure differences, and chemical properties of liquid sodium. Based on these investigations, a prognostic model focusing on creep failures was developed. It estimates the failure probability profile by sampling the Larson-Miller parameter (LMP) and temperature and associated uncertainties through Monte Carlo methods. Two case studies were presented. The first one demonstrated the model’s capability to calculate the failure probability for a new specimen within a given time. If the tube is working under temperatures of 500C ± 3 and pressures of 15.2 MPa, which leads to LMP of 20,100 ± 50, the failure probabilities within 50, 70, and 90 years are approximately 0.1 %, 3.2 %, and 17.5 %. The second demonstrated how adjusting the workload can help to protect the integrity of the component. For an old tube reaching 99 % of its lifespan, continuing to run at temperatures of 500C ± 3 and LMP of 20,100 ± 50 leads to a failure probability of about 29.0 % within a year. If the temperature is reduced by 5C, the failure probability can be reduced to 2.5 %, and, if the pressure is also reduced such that the LMP is increased by 100, the failure probability can further be reduced to 0.12 %.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Machine learning-based bias-corrected future projections of ozone concentrations from a chemistry-climate model

Reliable projection of future near-surface ozone is crucial for air quality management and health risk assessment. However, potential biases in spatial distribution, magnitude and trends in ozone concentrations simulated by global chemistry-climate models limit their applicability in regional-scale evaluations. In this study, LightGBM, a machine learning (ML) algorithm is applied to correct biases in CESM2-simulated ozone concentrations over China, the United States and Europe and calibrate future ozone projections under two diverse Shared Socioeconomic Pathways (SSP1-2.6 and SSP5-8.5) scenarios from 2020 to 2060. The ML-based correction significantly improves the spatial distribution and reduces the model bias by 40%–60%. It also reverses the potentially incorrect trend of ozone change under SSP1-2.6 in eastern China. When applying ML-based bias correction to CESM2 future projections, warm season mean ozone concentrations decrease across China, the United States, and Europe by –13.5, –17.9, and –13.7 µg/m³, respectively, between 2020 and 2060 in SSP1-2.6, while they increase by 9.4, 2.0, and 5.2 µg/m³ in SSP5-8.5. Decomposition analysis show that changes in anthropogenic emissions dominate future ozone changes in both scenarios, while strong climate penalty from ozone changes occurs in polluted eastern China and climate benefit is found in western China, the United States and Europe under SSP5-8.5. These findings demonstrate the value of combining ML with chemistry-climate models to produce more accurate air quality projections, thereby informing more effective and region-specific environmental protection strategies.

Chemistry Model↗

Structures of honeybee-infecting Lake Sinai virus reveal domain functions and capsid assembly with dynamic motions

Understanding the structural diversity of honeybee-infecting viruses is critical to maintain pollinator health and manage the spread of diseases in ecology and agriculture. We determine cryo-EM structures of $T$ = 4 and $T$ = 3 capsids of virus-like particles (VLPs) of Lake Sinai virus (LSV) 2 and delta-N48 LSV1, belonging to tetraviruses, at resolutions of 2.3–2.6 Å in various pH environments. Structural analysis shows that the LSV2 capsid protein (CP) structural features, particularly the protruding domain and C-arm, differ from those of other tetraviruses. The anchor loop on the central β-barrel domain interacts with the neighboring subunit to stabilize homo-trimeric capsomeres during assembly. Delta-N48 LSV1 CP interacts with ssRNA via the rigid helix α1’, α1’–α1 loop, β-barrel domain, and C-arm. Cryo-EM reconstructions, combined with X-ray crystallographic and small-angle scattering analyses, indicate that pH affects capsid conformations by regulating reversible dynamic particle motions and sizes of LSV2 VLPs. C-arms exist in all LSV2 and delta-N48 LSV1 VLPs across varied pH conditions, indicating that autoproteolysis cleavage is not required for LSV maturation. The observed linear domino-scaffold structures of various lengths, made up of trapezoid-shape capsomeres, provide a basis for icosahedral $T$ = 4 and $T$ = 3 architecture assemblies. These findings advance understanding of honeybee-infecting viruses that can cause Colony Collapse Disorder.

59 BASIC BIOLOGICAL SCIENCES↗

Toward achieving cost-effective hexagonal BN semi-bulk crystals and BN neutron detectors via halide vapor phase epitaxy

Presently, thermal neutron detectors fabricated from boron-10 enriched hexagonal boron nitride (h-10BN) ultrawide bandgap semiconductor grown by metal organic chemical vapor deposition (MOCVD) hold the record high detection efficiency among all solid-state detectors at 59%. To overcome the short comings of MOCVD growth, including inherently low growth rate and unavoidable impurities such as carbon in metal organic source, we demonstrate here the growth of natural hexagonal boron nitride (h-BN) semi-bulk wafers using halide vapor phase epitaxy (HVPE), which is an established technique for producing GaN semi-bulk crystals at a high growth rate. Electrical transport characterization results revealed that these HVPE grown materials possess an electrical resistivity of 1 × 1013 Ω cm, and a charge carrier mobility and lifetime product of 2 × 10−4 cm2/V s. Detectors fabricated from a 100 μm thick h-BN wafer have demonstrated a thermal neutron detection efficiency of 20%, corresponding to a charge collection efficiency of ∼60% at an operating voltage of 500 V. This initial demonstration opens the door for mass producing high efficiency h-BN semiconductor neutron detectors at a reduced cost, which could create unprecedented applications in nuclear energy, national security, nuclear waste monitoring and management, the health care industry, and material sciences.

Physics↗

A Cable Condition Monitoring Strategy for Safe and Reliable Plant Operation

Electrical cables provide essential functions, such as delivery of power or instrumentation signals for monitoring systems. Most cables installed in industrial applications are constructed with organic polymer insulations that can become brittle, crack, or degrade over time from exposure to harsh environmental conditions, such as elevated temperatures, moisture, vibration, mechanical shock, and radiation. This paper describes an overall strategy for assessing the health and managing the aging of cables during the operating life of an industrial facility. This strategy involves performing condition assessments and monitoring of electrical cables using both in situ and laboratory testing techniques. It includes in situ testing to identify anomalies in the circuits, such as degraded terminations, splices, connections, and degraded sections of cable insulation, as well as as-found evaluations to determine the current condition of installed cables. Furthermore, these cable condition evaluations provide important information about the current state of the cable circuits. Moreover, the test results can be used to trend/monitor age-related degradation and estimate the remaining useful life of installed cables.

36 MATERIALS SCIENCE↗

Power Cycle Testing of Power Switches: A Literature Survey

Reliability of power converters and lifetime prediction has been a major topic of research in the last few decades, especially for traction applications. The main failures in high power semiconductors are caused by thermomechanical fatigue. Power cycling and temperature cycling are the two most common thermal acceleration tests used in assessing reliability. The objective of this paper is to study the various power cycling tests found in the literature and to develop generalized steps in planning application specific power cycling tests. A comparison of different tests based on the failures, duration, test circuits, and monitored electrical parameters is presented.

42 ENGINEERING↗

The landscape of soil carbon data: Emerging questions, synergies and databases

Soil carbon has been measured for over a century in applications ranging from understanding biogeochemical processes in natural ecosystems to quantifying the productivity and health of managed systems. Consolidating diverse soil carbon datasets is increasingly important to maximize their value, particularly with growing anthropogenic and climate change pressures. In this progress discussion, we describe recent advances in soil carbon data led by the International Soil Carbon Network and other networks. We highlight priority areas of research requiring soil carbon data, including (a) quantifying boreal, arctic and wetland carbon stocks, (b) understanding the timescales of soil carbon persistence using radiocarbon and chronosequence studies, (c) synthesizing long-term and experimental data to inform carbon stock vulnerability to global change, (d) quantifying root influences on soil carbon and (e) identifying gaps in model–data integration. Furthermore, we describe the landscape of soil datasets currently available, highlighting their strengths, weaknesses and synergies. Now more than ever, integrated soil data are needed to inform climate mitigation, land management and agricultural practices. This report will aid new data users in navigating various soil databases and encourage scientists to make their measurements publicly available and to join forces to find soil-related solutions.

54 ENVIRONMENTAL SCIENCES↗

In situ potassium and hydrogen ion exchange into a cubic zirconium silicate microporous material

The selective separation of ions from aqueous systems, and even in the human body, is a crucial to overall environmental management and health. Nanoporous materials are widely known for their selective removal of cations from aqueous media, and therefore have been targeted for use as a pharmaceutical to treat hyperkalemia. This study investigated the detailed crystallographic molecular mechanisms that control the potassium ion selectivity in the nanoporous cubic zirconium silicate (CZS) related materials. Using time-resolved in situ Raman spectroscopy and time-resolved in situ X-ray diffraction, the selectivity mechanisms were determined to involve a synchronous cation-cation repulsion process that serves to open a favorable coordination bonding environment for potassium, not unlike the ion selectivity filter process found in potassium ion channels in proteins. Enhancement of ion exchange was observed when the CZS material was in a partial protonated state (≈3:1 Na:H), causing an expansion of the unit-cell volume, enlargement of the 7 member-ring window, and distortion of framework polyhedra, which allowed increased accessibility to the cage structures and resulted in rapid irreversible potassium ion exchange.

59 BASIC BIOLOGICAL SCIENCES↗

Building Toxic Metal Characterization and Decontamination Report: Area 6, Building 914

The purpose of this report is to outline the toxic metal characterization and decontamination efforts in Area 6, Building 914. This includes the initial building inspection, the hotspot sampling, results/findings, building cleanup, and the verification sampling. Building 914 is a steel light frame building that was constructed in 1992. It is about 16,454 square feet, and five employees are assigned to this building. According to the building's floor plan blueprints, it could be inferred that this building was once a Wiremen/Lineman shop. In 2002-2004, the National Nuclear Security Administration Nevada Site Office embarked on a broad characterization of beryllium (Be) surface concentrations throughout the North Las Vegas Facility, the Nevada National Security Site (NNSS), and ancillary facilities like the Special Technologies Laboratory, Remote Sensing Laboratory, etc. Building 914 was part of this characterization. The results of the 2002 study illustrated that the metal housekeeping limits were within acceptable limits and from a Be standpoint, the building was determined to be fit for occupancy. On March 2, 2011, based on a request from Building 914 users, National Security Technologies, LLC (NSTec) Industrial Hygiene (IH) collected bulk samples from the southwest corner of Building 914 at heights above 6 feet where black dust had been noticed on this particular wall. IH conducted surface swipe sampling of the area and analyzed the samples for toxic metals, namely, beryllium (Be), cadmium (Cd), chromium (Cr), lead (Pb), and manganese (Mn). The sample results indicated values two to four times above the housekeeping threshold for Be, Cd, Cr, Pb, and Mn. Subsequently, the facility was closed and posted; the necessary personnel were notified; and controls were instituted for ingress and egress of the building. On March 17, 2011, IH performed an extensive sampling event involving the entire warehouse in accordance with NSTec Organization Procedure OP-P250.004, Sampling Procedures. Analysis of the results from this exercise illustrated that toxic metal contamination was ubiquitous throughout the warehouse section of this building but did not extend into the office, restroom, and break room areas. On March 22, 2011, a planning meeting was held with Environment, Safety, Health & Quality management; Operations & Infrastructure (O&I) mangement; Facility Management; Occupational Medicine; O&I Operations; and IH. After a brief discussion concerning the salient facts of the surface sample results, it was agreed that the facility and its contents required cleaning. The facility would then be re-sampled to verify cleanliness and suitability for re-occupancy. On April 18, 2011, warehouse cleanup activites began. On July 5, 2011, upon receipt of the results from the last cleaned section, the cleanup operations were concluded. The building was statistically determined to be clean; thus, it could be reoccupied and the warehouse operations could resume immediately.

54 ENVIRONMENTAL SCIENCES↗

DOE/SNL/GCBS: Biorisk Management Curriculum for Vietnam One Health University Network

In line with the Global Health Security Agenda for Vietnam SNL has successfully engaged in country by ensuring long term sustainability of its programs and building BRM capacity by engaging with Government Institutions and strengthening the national biosafety and biosecurity and also by engaging with academic institutions through Vietnam One Health University Network to educate the One Health Workforce and promote a shared culture of responsibility, reduce dual use risks, mitigate biological proliferation and deliberate use threats.

60 APPLIED LIFE SCIENCES↗