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At least 829 records · Page 46

Using groundwater noble gas measurements to confirm paleorecharge hypotheses at Pahute Mesa, Nevada National Security Site, Nevada, USA

Pahute Mesa (Nevada, USA) was the site of 85 underground nuclear tests between 1965 and 1992 whose residual radio-chemical inventory poses a contaminant threat to local groundwater resources. To assess the fate and transport of these radionuclides in groundwater, several geochemical studies, including this one, have been conducted to understand long-term groundwater flow patterns at, and downgradient of, Pahute Mesa. Groundwater samples from the Pahute Mesa area at the Nevada National Security Site were analyzed for noble gases ( 3 He/ 4 He isotopic ratio and He, Ne, Kr, Ar and Xe concentrations) to infer groundwater recharge temperatures and provide additional evidence in support of groundwater flow patterns and the presence of late-pluvial Pleistocene groundwater. These data confirm recent findings (based on groundwater geochemistry and isotope compositions) that most recharge in the area occurred under temperature conditions much cooler than are found today, except near major drainages where ephemeral run of continues to recharge shallow groundwater. These noble gas data indicate that noble gas recharge temperatures and terrigenic He components have been reset where groundwater has flowed upward over barriers formed by caldera margins, or near the regional discharge area (Oasis Valley) where shallow groundwater has interacted with shallow soil gas. This evidence from groundwater noble gas measurements, in combination with other isotopic and geochemical studies, supports the current understanding of the unusual hydrogeology and recharge history of Pahute Mesa.

54 ENVIRONMENTAL SCIENCES↗

Adaptive anomaly detection for identifying attacks in cyber-physical systems: A systematic literature review

Modern cyberattacks in cyber-physical systems (CPS) rapidly evolve and cannot be deterred effectively with most current methods, which focus on characterizing past threats. Adaptive anomaly detection (AAD) is among the most promising techniques to detect evolving cyberattacks, with an emphasis on fast data processing and model adaptation. AAD has been researched extensively; however, to the best of our knowledge, our work is the first systematic literature review (SLR) on current research in this field. We present a comprehensive SLR, gathering 397 relevant papers and systematically analyzing 65 of them (47 research and 18 survey papers) on AAD in CPS from 2013 to November 2023. We introduce a novel taxonomy considering attack types, CPS application, learning paradigm, data management, and algorithms. Our findings show that most studies addressed either model adaptation or data processing, but rarely both simultaneously. This indicates a research gap in fully adaptive solutions. We also categorize algorithms, datasets, and attack characteristics, and summarize strengths and weaknesses across the literature. Our review provides a structured and accessible reference for researchers and practitioners, offering insights into key trends and highlighting limitations in current approaches. Finally, we outline several future research directions, including the need for integrated real-time processing and adaptive learning, explainability, and uncertainty quantification in AAD for CPS.

Adaptation↗

Effectiveness and outcomes of invasive species removal in Hawaiian streams

Despite aquatic invasive species (AIS) being a widely recognized threat to native biodiversity in streams on subtropical and tropical oceanic islands across the Pacific, AIS management has been constrained by concerns that methods of removal could result in more harm than good. In this study, we assessed the effectiveness and outcomes of combining hand-netting and streamside sequestration of native species with AIS removal via three-pass electrofishing tailored for Hawaiian Island watersheds. Removals were conducted in 13 watersheds on the island of O‘ahu following a before-after, control-impact design to assess how AIS removal and post-removal community reassembly varied by surface flow and target species of interest. We found that removals resulted in a sharp reduction in AIS densities without altering native species densities. Removal efficacy was greatest in streams with intermediate mean discharge irrespective of target group or pre-removal AIS densities. Long-term monitoring demonstrated that removals led to persistent shifts in community composition reflecting sustained reductions in AIS densities. These findings indicate that electrofishing can be a valuable tool for AIS management in Hawaiian and other subtropical Pacific island streams, so long as steps are taken to minimize potential harm to at-risk and culturally important native species.

59 BASIC BIOLOGICAL SCIENCES↗

Formulation, Implementation and Validation of a 1D Boundary Layer Inflow Scheme for the QUIC Modeling System

Recent studies have highlighted the importance of accurate meteorological conditions for urban transport and dispersion calculations. In this work, we present a novel scheme to compute the meteorological input in the Quick Urban & Industrial Complex () diagnostic urban wind solver to improve the characterization of upstream wind veer and shear in the Atmospheric Boundary Layer (ABL). The new formulation is based on a coupled set of Ordinary Differential Equations (ODEs) derived from the Reynolds Averaged Navier–Stokes (RANS) equations, and is fast to compute. Building upon recent progress in modeling the idealized ABL, we include effects from surface roughness, turbulent stress, Coriolis force, buoyancy and baroclinicity. We verify the performance of the new scheme with canonical Large Eddy Simulation (LES) tests with the GPU-accelerated FastEddy"Equation missing" solver in neutral, stable, unstable and baroclinic conditions with different surface roughness. Furthermore, we evaluate QUIC calculations with and without the new inflow scheme with real data from the Urban Threat Dispersion (UTD) field experiment, which includes Lidar-based wind measurements as well as concentration observations from multiple outdoor releases of a non-reactive tracer in downtown New York City. Compared to previous inflow capabilities that were limited to a constant wind direction with height, we show that the new scheme can model wind veer in the ABL and enhance the prediction of the surface cross-isobaric angle, improving evaluation statistics of simulated concentrations paired in time and space with UTD measurements.

54 ENVIRONMENTAL SCIENCES↗

The impact of habitat fragmentation on domatia-dwelling mites and a mite-plant-fungus tritrophic interaction

Abstract Context Habitat fragmentation is a leading threat to biodiversity, yet the impacts of fragmentation on most taxa, let alone interactions among those taxa, remain largely unknown. Objectives We studied how three consequences of fragmentation—reduced patch connectivity, altered patch shape, and edge proximity—impact plant-dwelling mite communities and mite-plant-fungus interactions within a large-scale habitat fragmentation experiment. Methods We sampled mite communities from the leaves of Quercus nigra (a plant species that has foliar domatia which harbor fungivorous and predacious mites) near and far from edge within fragments of varying edge-to-area ratio (shape) and connectivity via corridors. We also performed a mite-exclusion experiment across these fragmentation treatments to test the effects of mite presence and fungal hyphal abundance on leaf surfaces. Results Habitat edges influenced the abundance and richness of leaf-dwelling mites; plants closer to the edge had higher mite abundance and species richness. Likewise, hyphal counts were higher on leaves near patch edges. Despite both mite and fungal abundance being higher at patch edges, leaf hyphal counts were not impacted by mite abundance on those leaves. Neither patch shape nor connectivity influenced mite abundance, mite species richness, or the influence of mites on leaf surface fungal abundance. Conclusion Our results suggest that mites and foliar fungi may be independently affected by edge-structured environmental gradients, like temperature, rather than trophic effects. We demonstrate that large-scale habitat fragmentation and particularly edge effects can have impacts on multiple levels of microscopic communities, even in the absence of cascading trophic effects.

60 APPLIED LIFE SCIENCES↗

A new method for predicting hurricane rapid intensification based on co-occurring environmental parameters

Abstract Tropical cyclones (TCs) that undergo Rapid Intensification (RI) can pose serious socioeconomic threats and can potentially result in major damaging impacts along coastal areas. Considering the complexity of various physical mechanisms that play a role in RI and its relatively low probability of occurrence, predicting RI remains a major operational challenge. In this study, we propose a simple deterministic binary classification model based on the co-occurrence of environmental parameters (MCE) to predict an RI event. More specifically, the model determines the possibility of RI based on a simple count of the number of environmental predictors deemed favorable and unfavorable. We compare our model results to logistic regression (LR) and decision tree (DT) models, well-trained using the same set of environmental predictors. Results reveal that at an RI threshold of 30 kt, the MCE exhibits a critical success index score of 0.233 which is 14% higher than DT and LR model performances. When tested at multiple RI thresholds, the MCE displays relatively higher skill scores across multiple metrics. By simultaneously evaluating the favorability of predictors, the MCE is able to comparatively reduce the number of false alarms predicted when certain predictors are unfavorable toward RI. Interpreting these model results to gain a physical understanding of how co-occurring environmental parameters can affect RI, we highlight future directions for using models based on the MCE approach to understand and predict TC RI as well as other meteorological extremes.

54 ENVIRONMENTAL SCIENCES↗

Computational Design of Alloys for Energy Technologies

Advanced materials that maintain their mechanical performance under elevated temperatures, corrosive environments, and a range of static and evolving stresses are needed to improve the efficiency and reduce the environmental impact of a wide spectrum of energy technologies. For instance, cost-efficient alloys that can withstand high temperatures (e.g., 700 °C) have a critical role in improving the efficiency and economics of power generation to support decarbonization of the energy sector; such is true of both the nuclear and fossil energy sectors. Considering both the threats of the energy crisis, namely soaring costs of greenhouse gas emission-producing energy and climate change, it is essential to increase the pace of material discovery and enable rapid paths for material qualification to advance clean energy technologies. Conventionally, alloy development has followed a slow Edisonian process that uses repeated cycles of making, characterizing, and modifying to arrive at optimum composition and processing conditions to achieve the desired component performance. This optimization is followed by the necessary stepwise materials qualification. Furthermore, the increasing adoption of sound data management and physics-informed machine learning represents the next step in the acceleration of materials design and development. In the integrated computational materials engineering (ICME) approach, computational modeling and simulation data from different length and time scales can be combined with complex microstructural details from multimodal experimental characterization and selective property testing to close the design loop for rapid alloy development.

Computational Design Of Materials↗

Aviation security screening optimizer for risk and throughput (ASSORT)

The increasing number of air travelers each year presents a challenge as many airports are near their capacity in terms of resources and space for passenger screening. Fortunately, advancements in technologies like next-generation millimeter wave scanning offer solutions to ease this strain. The focus remains on managing risk while enhancing the passenger experience for the traveling public. The risk model presented in this paper known as the Aviation Security Screening Optimizer for Risk and Throughput (ASSORT) is designed to assess risk-based approaches for passenger screening and checkpoint operations. Additionally, ASSORT is exploring various traveler categories — general, trusted, and trusted-plus — along with different checkpoint screening Concept of Operations tailored to each traveler type. For instance, travelers with a higher trust level may experience fewer screening technologies, resulting in quicker processing times at the checkpoint. The output of ASSORT provides a risk score for predefined threat scenarios, as well as the overall risk to the checkpoint, aircraft, and airport by traveler type. In conclusion, benefits of using this tool include assessing the trade-offs between the overall risk associated with checkpoints and the throughput rate of passengers screened. We show for example the impact that different passenger volumes at the checkpoint can have on risk.

99 GENERAL AND MISCELLANEOUS↗

Effects of Warming and Elevated CO2 on Stomatal Conductance and Chlorophyll Fluorescence of C3 and C4 Coastal Wetland Species

Abstract Coastal wetland communities provide valuable ecosystem services such as erosion prevention, soil accretion, and essential habitat for coastal wildlife, but are some of the most vulnerable to the threats of climate change. This work investigates the combined effects of two climate stressors, elevated temperature (ambient, + 1.7 °C, + 3.4 °C, and 5.1 °C) and elevated CO 2 ( e CO 2 ), on leaf physiological traits of dominant salt marsh plant species. The research took place at the Salt Marsh Accretion Response to Temperature eXperiment (SMARTX) at the Smithsonian Environmental Research Center, which includes two plant communities: a C 3 sedge community and a C 4 grass community. Here we present data collected over five years on rates of stomatal conductance (g s ), quantum efficiency of PSII photochemistry ( F v / F m ), and rates of electron transport (ETR max ). We found that both warming and e CO 2 caused declines in all traits, but the warming effects were greater for the C 3 sedge. This species showed a strong negative stomatal response to warming in 2017 and 2018 (28% and 17% reduction, respectively in + 5.1 °C). However, in later years the negative response to warming was dampened to < 7%, indicating that S. americanus was able to partially acclimate to the warming over time. In 2022, we found that sedges growing in the combined + 5.1 °C e CO 2 plots exhibited more significant declines in g s , F v /F m , and ETR max than in either treatment individually. These results are important for predicting future trends in growth of wetland species, which serve as a large carbon sink that may help mitigate the effects of climate change.

54 ENVIRONMENTAL SCIENCES↗

Chapter 32 - Power Grid Resilience

The new energy paradigm is altering the current power grid trend from synchronous generator reliant system toward power-electronics-based distributed energy resources (DERs). The resilient operation of modern power grid is highly dependent upon cyber and physical reliable operation of DERs. Power grid resilience broadly refers to the ability of the grid to be robust to eventualities and singularities that may disrupt the continuity of reliable power flow. This could involve resilience related to the physical system but more recently, the focus on cyber resilience has been evolving rapidly especially given the burgeoning growth of distributed generation and power-electronics-based DERs under smart grid and given that such threats to reliable operation do not have to evolve localized to where the physical asset is. Commonly, in power grids dominated by DERS, control and energy management are structured at a multitime scale multilayer fashion: (i) primary control layer at microseconds time scale, (ii) secondary control layer at millisecond time scale, and (iii) tertiary control layer at seconds to minutes time scale. The cyber-related issues that may affect the power grid resilience can be introduced in through primary, secondary, and tertiary control layers. The failure of each of these control layers may impact the reliable and resilient operation of the overall network and cause widespread failures which leads to unintended blackouts. As such, this chapter focuses on cyber-related resilience issues in primary control layer, secondary control layer, tertiary control layer, wide area/utility control, and anomaly detection and resilient communication.

anomaly detection↗

Air-coupled tsunamis generated from impacts and airbursts: Our understanding before Hunga-Tonga Hunga-Ha'apai

The effort to prevent or mitigate the effects of an impact on Earth is known as planetary defense. A significant component of planetary defense research involves risk assessment. Much of our understanding of the risk from near-Earth objects comes from the geologic record in the form of impact craters, but not all asteroid impacts are crater-forming events. Small asteroids explode before reaching the surface, generating an airburst, and most impacts into the ocean do not penetrate the water to form a crater in the sea floor. The risk from these non-crater-forming ocean impacts and airbursts is difficult to quantify and represents a significant uncertainty in our assessment of the overall threat. We are currently working to better understand impact scenarios that can generate dangerous tsunamis.

54 ENVIRONMENTAL SCIENCES↗

Lead tolerance and bioremoval by four strains of green algae from Nigerian fish ponds

Heavy metals from industry pose threats to human and environmental health. Microalgae are prime candidates to remove heavy metals from water and soil due to their metal-binding affinities, high growth rates, and contamination tolerance. Strain selection and composition of resulting contaminated biomass must be considered for downstream processing. In this study, we assessed the ability of four microalgae strains (Chlorophyceae) that were isolated from contaminated Nigerian fish ponds to take up dissolved lead at environmentally relevant concentrations (<0.05 mg L -1 – WHO standard). In a microplate assay, all strains grew in the presence of lead, tolerating concentrations up to 60 ppm, though the addition of dissolved lead affected the growth of the four strains. In a photobioreactor assay, all strains demonstrated the ability to take up dissolved lead, with removal efficiencies ranging from 86 to 93%. The concentrations of lead in contaminated biomass, removal efficiencies, and bioconcentration factors were greatest in one of the isolates Chlorella sp. MOW 12. Our results reinforce the fact that live microalgae have a greater biosorption capacity. Lead recovery from freeze-dried biomass using five different reagents showed that a 0.1 M hydrochloric acid solution was the most effective, with 83.4% recovery. We also showed that presence of lead in the culture medium resulted in an increase in the quantity of protein in the biomass. Elemental analysis of lead-bound biomass showed an increase in elements including boron and copper and a decrease in cobalt and sodium. Synergystic and antagonystic effect in uptake of other elements was strain specific, suggesting the possibility of tailored wastewater treatments depending on specific requirements.

59 BASIC BIOLOGICAL SCIENCES↗

Development of a novel minigenome and recombinant VSV expressing Seoul hantavirus glycoprotein-based assays to identify anti-hantavirus therapeutics

Seoul virus (SEOV) is an emerging global health threat that can cause hemorrhagic fever with renal syndrome (HFRS), which results in case fatality rates of ~2%. There are no approved treatments for SEOV infections. We developed a cell-based assay system to identify potential antiviral compounds for SEOV and generated additional assays to characterize the mode of action of any promising antivirals. Here, to test if candidate antivirals targeted SEOV glycoprotein-mediated entry, we developed a recombinant reporter vesicular stomatitis virus expressing SEOV glycoproteins. To facilitate the identification of candidate antiviral compounds targeting viral transcription/replication, we successfully generated the first reported minigenome system for SEOV. This SEOV minigenome (SEOV-MG) screening assay will also serve as a prototype assay for discovery of small molecules inhibiting replication of other hantaviruses, including Andes and Sin Nombre viruses. Ours is a proof-of-concept study in which we tested several compounds previously reported to have activity against other negative-strand RNA viruses using our newly developed hantavirus antiviral screening systems. These systems can be used under lower biocontainment conditions than those needed for infectious viruses, and identified several compounds with robust anti-SEOV activity. Our findings have important implications for the development of anti-hantavirus therapeutics.

60 APPLIED LIFE SCIENCES↗

Hazard analysis for identifying common cause failures of digital safety systems using a redundancy-guided systems-theoretic approach

Replacing the existing aging analog instrumentation and control (I&C) systems with modern safety control and protection, digital technology offers one of the foremost means of performance improvements and cost reductions for the existing nuclear power plants (NPPs). However, the qualification of digital I&C systems remains a challenge, especially considering the issue of software common-cause failures (CCFs), which are difficult to address. With the application and upgrades of advanced digital I&C systems, software CCFs have become a potential threat to plant safety because most redundant designs use similar digital platforms or software in the operating and application systems. With complex designs of multilayer redundancy to meet the single-failure criterion, digital I&C safety systems (e.g., engineered safety-features actuation system [ESFAS]) are of a particular concern in the U.S. Nuclear Regulatory Commission (NRC) licensing procedures. Here, this paper applies a modularized approach to conduct redundancy-guided systems-theoretic hazard analysis for an advanced digital ESFAS with multilevel redundancy designs. Systematic methods and risk-informed tools are incorporated to address both hardware and software CCFs, which provide guidance to eliminate the causal factors of potential single points of failure in the design of digital safety systems in advanced plant designs.

42 ENGINEERING↗

Multiscale modeling of hydrogenolysis of ethane and propane on Ru(0001): Implications for plastics recycling

Plastic waste presents an environmental threat. Chemical recycling via hydrogenolysis can convert plastic waste into waxes, lubricants, and fuels. Among catalysts, Ru stands out for its superior activity and selectivity. The chemistry of light alkane hydrogenolysis can help understanding plastics deconstruction. Here, we perform first-principles calculations, develop descriptor-based relations, and conduct microkinetic modeling and analysis on ethane and propane. Predictions are in excellent agreement with experimental data. We identify a similar cracking pattern for both hydrocarbons entailing a deeply dehydrogenated species with the removal of four hydrogen atoms: CHCH*+* → 2CH* for ethane and CH 3 CCH*+2* → CH 3 C* + CH* for propane. We find that the rate-determining step is the C-C cracking for ethane and the first dehydrogenation from the terminal carbon (CH 3 CH 2 CH 3 *+* → CH 3 CH 2 CH 2 *+H*) for propane. The vinyl species CH 2 CH* produced from propane cracking is responsible for whether a single or multiple cracking events occur and effectively controls the selectivity. Specifically, ethane formation in propane hydrogenolysis is suppressed at elevated temperatures due to over-cracking via multiple (two here) cracking events being preferred over hydrogenation and desorption of ethane from the catalyst. Our workflow and models provide a baseline for future studies on heavier hydrocarbons. Insights into recent experimental studies of polyethylene over Ru-based catalysts are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Load altering attack-tolerant defense strategy for load frequency control system

Cyber attacks are emerging threats to every information-oriented energy management system. By violating the cyber systems, the hacker can disrupt the security and stability due to the strong coupling between the cyber and physical facilities. In this paper, one type of cyber attacks designated as the load altering attack is studied for the power system frequency control, and corresponding defense strategies are proposed to improve the frequency control performance. Considering the difficulty of the application of model-based controller into large-scale power systems, a novel model-free defense framework is for the first time presented. Under this framework, both active defense and passive defense strategies are designed. The former assumes that the defender has the initiative to learn different attack scenarios. Adaptive defense strategies are implemented using the online attack identification information and off-line trained strategy pool. The latter assumes that the defender passively tolerates various attack scenarios via the pre-trained off-line strategy. Both approaches prove to be effective through validation based on the IEEE benchmark systems. The proposed defense framework and defense strategies can be extended to other energy control systems to enhance their attack tolerance capability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Analyzing at-scale distribution grid response to extreme temperatures

Threats against power grids continue to increase, as extreme weather conditions and natural disasters (extreme events) become more frequent. Hence, there is a need for the simulation and modeling of power grids to reflect realistic conditions during extreme events conditions, especially distribution systems. Herein, this paper presents a modeling and simulation platform for electric distribution grids which can estimate overall power demand during extreme weather conditions. The presented platform's efficacy is shown by demonstrating estimation of electrical demand for 1) Electricity Reliability Council of Texas (ERCOT) during winter storm Uri in 2021, and 2) alternative hypothetical scenarios of integrating Distributed Energy Resources (DERs), weatherization, and load electrification. In comparing to the actual demand served by ERCOT during the winter storm Uri of 2021, the proposed platform estimates approximately 34 GW of peak capacity deficit. These numbers are consistent with state-of-the-art prediction results published in the literature. For the case of the future electrification of heating loads, peak capacity of 78 GW (124% increase) is estimated, which would be reduced to 47 GW (38% increase) with the adoption of efficient heating appliances and improved thermal insulation. Integrating distributed solar PV and storage into the grid causes improvement in the local energy utilization and hence reduces the potential unmet energy by 31% and 40%, respectively.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Physics-informed graphical neural network for power system state estimation

State estimation is highly critical for accurately observing the dynamic behavior of the power grids and minimizing risks from cyber threats. However, existing state estimation methods encounter challenges in accurately capturing power system dynamics, primarily because of limitations in encoding the grid topology and sparse measurements. Here, this paper proposes a physics-informed graphical learning state estimation method to address these limitations by leveraging both domain physical knowledge and a graph neural network (GNN). We employ a GNN architecture that can handle the graph-structured data of power systems more effectively than traditional data-driven methods. The physics-based knowledge is constructed from the branch current formulation, making the approach adaptable to both transmission and distribution systems. The validation results of three IEEE test systems show that the proposed method can achieve lower mean square error more than 20% than the conventional methods.

43 PARTICLE ACCELERATORS↗