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At least 343 records · Page 19

Neutrino mass and mass ordering: no conclusive evidence for normal ordering

The extraction of the neutrino mass ordering is one of the major challenges in particle physics and cosmology, not only for its implications for a fundamental theory of mass generation in nature, but also for its decisive role in the scale of future neutrinoless double beta decay experimental searches. It has been recently claimed that current oscillation, beta decay and cosmological limits on the different observables describing the neutrino mass parameter space provide robust decisive Bayesian evidence in favor of the normal ordering of the neutrino mass spectrum. We further investigate these strong claims using a rich and wide phenomenology, with different sampling techniques of the neutrino parameter space. Contrary to the findings of Jimenez et al., no decisive evidence for the normal mass ordering is found. Neutrino mass ordering analyses must rely on priors and parameterizations that are ordering-agnostic: robust results should be regarded as those in which the preference for the normal neutrino mass ordering is driven exclusively by the data, while we find a difference of up to a factor of 33 in the Bayes factors among the different priors and parameterizations exploited here. An ordering-agnostic prior would be represented by the case of parameterizations sampling over the two mass splittings and a mass scale, or those sampling over the individual neutrino masses via normal prior distributions only. In this regard, we show that the current significance in favor of the normal mass ordering should be taken as 2.7σ (i.e. moderate evidence), mostly driven by neutrino oscillation data. Let us stress that, while current data favor NO only mildly, we do not exclude the possibility that this may change in the future. Eventually, upcoming oscillation and cosmological data may (or may not) lead to a more significant exclusion of IO.

79 ASTRONOMY AND ASTROPHYSICS↗

An international laboratory comparison of dissolved organic matter composition by high resolution mass spectrometry: Are we getting the same answer?

Since the first detailed compositional analysis of dissolved organic matter (DOM) in 1995, high resolution mass spectrometry (HRMS) has become a vital tool for DOM characterization. While the upward trend in HRMS for molecular level analysis of DOM continues, so do the challenges of data comparison and interpretation between laboratories operating instruments of differing performance and user operating conditions. It is therefore essential that the community establishes whether data and trends can be compared robustly between research groups. To this end, 4 identically prepared DOM samples were each studied by 16 laboratories, representing 17 commercially-purchased instruments located across 8 countries, using positive- and negative-mode electrospray ionization (ESI) HRMS analysis. Despite the widely reported sensitivity of ESI experiments to sample matrix, preparation, ion source operation and instrument tuning parameters, the instruments used in this study showed relatively low variability between results for the same samples, particularly H/C and AI metrics. The variation in O/C and m/z metrics was relatively higher, although z-score graphs and %BCD demonstrated that the relative difference in general chemical composition between samples was the same for each instrument included in the study. As such, these metrics can be used for fingerprinting of DOM samples and as a benchmark for quality control in participating laboratories, with future strides in environmental science building upon these efforts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantifying the Site Heterogeneities of Non‐Uniform Catalysts Using QuantEXAFS

Abstract We present the Multi‐site (MS) QuantEXAFS approach, designed to model the EXAFS data from samples containing an element in different local bonding geometries. Building upon our QuantEXAFS method, which maps experimental extended X‐ray absorption fine structures (EXAFS) data to DFT‐optimized structures, MS‐QuantEXAFS introduces the key capability to probe fractional contributions of multiple sites that may be present in an experimental sample. Specifically, we demonstrate effectiveness of this technique by investigating mixed samples containing known fractions of site‐isolated subsurface Pt/MgO with Pt nanoparticles uniformly supported on MgO. The ‘site‐fractions’ obtained through MS‐QuantEXAFS closely match (i. e., ±6%) the known fractions of the physically mixed samples. This approach has been generalized to other oxides, and thus represents an important advance in quantifying the speciation of non‐uniform catalyst samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Teleconnections of the Quasi–Biennial Oscillation in a multi–model ensemble of QBO–resolving models

The quasi-biennial oscillation (QBO) dominates the interannual variability of the tropical stratosphere and influences other regions of the atmosphere. The high predictability of the QBO implies that its teleconnections could lead to in-creased skill of seasonal and decadal forecasts provided the relevant mechanisms are accurately represented in models. Here modelling and sampling uncertainties of QBO teleconnections are examined using a multi-model ensemble of QBO-resolving atmospheric general circulation models that have carried out a set of coordinated experiments as part of the Stratosphere-troposphere Processes And their Role in Climate (SPARC) QBO initiative (QBOi). During Northern Hemisphere winter the stratospheric polar vortex in most of these models strengthens when the QBO near 50 hPa is westerly and weakens when it is easterly, consistent with, but weaker than, the observed response. These weak responses are likely due to model errors, such as systematically weak QBO amplitudes near 50 hPa, affecting the teleconnection. The teleconnection to the North Atlantic Oscillation is less well captured overall, but of similar strength to the observed signal in the few models that do show it. Furthermore, the models do not show clear evidence of a QBO teleconnection to the Northern Hemisphere Pacific sector subtropical jet.

54 ENVIRONMENTAL SCIENCES↗

Detection of surface water temperature variations of Mongolian lakes benefiting from the spatially and temporally gap-filled MODIS data

Lakes provide critical water resources for human activities and ecosystems, particularly in the Mongolian Plateau (MP), which is characterized by a dry climate and a harsh environment. As a region that is sensitive to anthropogenic warming, tracking lake surface water temperature (LSWT) changes in Mongolian lakes is crucial for understanding the consequences of a warming climate on lake ecosystems. However, the long-term monitoring of LSWT is restricted by the spatiotemporal gaps in the raw imagery of remote sensing-based land surface temperature (LST), e.g., the commonly used Moderate Resolution Imaging Spectroradiometer (MODIS) LST products. This study applied an improved gap-filling method by utilizing the discrete cosine transform-based penalized least squares (DCT-PLS) strategy in the spatial domain combined with the linear interpolation (LI) algorithm in the temporal domain. The method was applied to fill gaps in the LSWT imagery of 12 representative lakes across MP. The randomly sampled high-quality MODIS LSWT values in the spatial and temporal domains were excavated as false data gaps and considered “virtual true” validation datasets. The spatial validation results showed that the estimated LSWT for all the lake cases were comparable with the “virtual true” LSWT values, with the average values of the coefficient of determination, mean absolute error, mean square error, and root mean square error being 0.98, 0.38 °C, 0.45 °C, and 0.59 °C, respectively. Meanwhile, the error of nighttime LSWT results was relatively lower than that of daytime LSWT. For temporal interpolation validation, the LI algorithm exhibited relatively better performance and could more objectively indicate the variation in LSWT. Benefiting from the spatially and temporally well-constrained data, we analyzed the interannual and intra-annual change characteristics of the LSWTs of the 12 lakes. The long-term variations of annual and seasonal mean LSWTs in the 12 selected lakes exhibited no evident trends in 2000–2020, while presented apparent interannual fluctuations. The slight changes in the average LSWTs of the 12 selected lakes were in excellent synchronization with the surrounding LST derived from the reanalysis datasets, confirming the widely reported phenomenon of “global warming hiatus” that occurred in the early 21st century. This study improves the understanding of the LSWT variations in Mongolian lakes in response to global climate change. It has the potential to provide an effective approach for monitoring LSWT changes in other large-scale studies.

54 ENVIRONMENTAL SCIENCES↗

Transmission Electron Microscopy based Characterization of a U-20Pu-10Zr Fuel Irradiated in Experimental Breeder Reactor-II

U-Pu-Zr metallic fuels are important fuel candidate for future advanced and/or test reactors. To better understand fuel performance and guide future fuel development, a U-20Pu-10Zr (in weight) metallic fuel irradiated in the Experimental Breeder Reactor was revisited using advanced electron microscopies. This fuel was irradiated to a burnup of 7.6 % at a peak cladding temperature of 521 °C. In this research, several transmission electron microscopy samples were extracted from different but representative radial locations of the fuel cross section using focused ion beam technique. Phase identification and chemical analysis with sub-micron spatial resolution was carried out using scanning transmission electron microscopy. Multiple phenomena that are critical to fuel performance, such as Zr phase and its distribution in a different matrix, were revealed in an unpreceded and highly detailed manner. An improved understanding of fuel reconstruction in U-Pu-Zr metallic fuel under reactor irradiation is provided.

36 MATERIALS SCIENCE↗

Characterizing How Meteorological Forcing Selection and Parameter Uncertainty Influence Community Land Model Version 5 Hydrological Applications in the United States

Despite the increasing use of large-scale Land Surface Models (LSMs) in predicting hydrological responses in extreme conditions, there's a critical gap in understanding the uncertainties in these predictions. This study addresses this gap through a detailed diagnostic evaluation of the uncertainties arising from meteorological forcing selection and model parametrization in hydrological simulations of the Community Land Model version 5 (CLM5). CLM5 is configured at a spatial scale of about 12-km to simulate runoff processes for 464 headwater watersheds, selected from the Catchment Attributes for Large-Sample Studies (CAMELS) dataset to be representative of physiographic and climatic gradients across the conterminous United States. For each watershed, CLM5 is driven by five commonly used gridded forcing datasets in combination with a large ensemble (> 1200) of key CLM5 hydrologic parameters. Our results suggest that uncertainty in CLM5 runoff simulations resulting from both forcing and parametric sources is markedly higher in arid regions, e.g., Great Plains and Midwest regions. Uncertainty in low flow is dominated by parametric uncertainty, while the selection of meteorological forcing contributes more dominantly to high flow and seasonal flows during fall and spring. Our analysis also demonstrates that the selection of forcing datasets and the metrics used to calibrate CLM5 significantly impact the model’s predictive accuracy in extreme event severity for both floods and droughts. Overall, the results from this study highlight the need to understand and account for forcing and parametric uncertainties in CLM5 simulations, particularly for hazard and risk assessments addressing hydrologic extremes.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of overtime phenotypic variation of yeasts in chronic vulvovaginal candidosis cases

Abstract Chronic vulvovaginal candidosis results either from reinfection or from the ability of Candida spp. to persist in the vulva and/or vagina. Persistence is usually associated with increased antifungal (mainly azoles) resistance rates, which can explain treatment failure, and/or increased expression of virulence factors by Candida spp. The aim of this study was to assess the mechanisms leading to Candida spp persistence, by studying sequential isolates from women with chronic vulvovaginal candidosis, focusing on strains genotypes, azole resistance, and ability to form biofilms along the period of clinical evaluation. The strains were identified at species level by automated analysis of biochemical profiles and molecular typing evaluated by polymorphic DNA analysis. The capacity to form biofilm was assessed with a microtiter plate assay. Fluconazole susceptibility was determined by the microdilution broth assay at both pH 7 (following the recommended guideline) and pH 4.5 (as representative of vaginal pH). We studied samples from 17 clinically recurrent cases. In 53% of the chronic cases there were two or more isolates that had a phylogenetic relationship while the remaining (47%) were caused by different species. In those cases where related strains were involved in recurrence, we verified an increase in MIC at pH 7 and also an increased capacity to form biofilms over time. Significant correlation between these two parameters was observed only in cases caused by C. glabrata, evidencing the importance of these two factors to enhance persistence in the vaginal mucosa for this particular species.

Faria-Gonçalves, Paula↗

Asymmetric drift in MaNGA: mass and radially dependent stratification rates in galaxy discs

ABSTRACT We measure the age–velocity relationship from the lag between ionized gas and stellar tangential speeds in ∼500 nearby disc galaxies from MaNGA in Sloan Digital Sky Survey IV (SDSS-IV). Selected galaxies are kinematically axisymmetric. Velocity lags are asymmetric drift, seen in the Milky Way’s (MW) solar neighbourhood and other Local Group galaxies; their amplitude correlates with stellar population age. The trend is qualitatively consistent in rate ($\dot{\sigma }$) with a simple power-law model where σ ∝ tb that explains the dynamical phase-space stratification in the solar neighbourhood. The model is generalized based on disc dynamical times to other radii and other galaxies. We find in-plane radial stratification parameters σ0,r (dispersion of the youngest populations) in the range of 10–40 km s−1 and 0.2 < br < 0.5 for MaNGA galaxies. Overall, brincreases with galaxy mass, decreases with radius for galaxies above 10.4 dex (M⊙) in stellar mass, but is ∼constant with radius at lower mass. The measurement scatter indicates the stratification model is too simple to capture the complexity seen in the data, unsurprising given the many possible astrophysical processes that may lead to stellar population dynamical stratification. None the less, the data show dynamical stratification is broadly present in the galaxy population, with systematic trends in mass and density. The amplitude of the asymmetric drift signal is larger for the MaNGA sample than the MW, and better represented in the mean by what is observed in the discs of M31 and M33. Either typical discs have higher surface-density or, more likely, are dynamically hotter (hence thicker) than the MW.

Bershady, Matthew A. (ORCID:0000000231314374)↗

Yield From Iowa's First Commercial Miscanthus Fields: Implications of Spatial Variability for Productivity and Sustainability Beyond Research Plots

The cultivation of sterile giant miscanthus (Miscanthus × giganteus, M × g) for bioenergy and bioproducts has expanded into grain-cropped land in the United States (US) as local markets developed for this high-yielding perennial grass (10–30 Mg DM ha −1 ). However, the magnitude of spatial and temporal variability in yield within US Corn Belt fields, along with impacts on economic return and sustainable land management, is poorly understood. This study established a diagnostic model relating remote sensing-derived vegetation indices to ground truth data from 105 hand-harvested stem biomass samples, which were strategically selected to represent the full range of vegetation index observations. The high-resolution satellite-sensed vegetation indices captured > 90% of the yield variation measured within fields. This model was then used to predict yield variability and assess economic performance across four of the first commercial M × g fields in the Corn Belt state of Iowa, US. Significant spatial variability in biomass dry matter (DM) yields (9.3–18.1 Mg DM ha −1 ) and net profits ($\$$83 to $\$$1211.5 ha −1 ) was observed. All fields were profitable in all site-years. When low profit occurred, it was explained by limited management experience of the crop in Iowa. The breakeven yield at a selling price of $\$$130 Mg −1 varied from 9.0–12.1 Mg ha −1 at 15% moisture content (7.6–10.3 Mg DM ha −1 ). Breakeven prices ranged from $\$$73 to $\$$122.4 Mg −1 , matching ranges used in the Department of Energy Billion Ton Report (US Department of Energy, 2023). Notably, M × g yield and profits were commensurate with grain crops particularly with favorable precipitation. This study provides insight on the M × g management “learning curve”, performance on marginal land and in drought conditions, and demonstrates that addressing yield gaps, reducing costs, and implementing precision agriculture strategies can enhance profitability. These findings emphasize the value of remote sensing technologies in guiding sustainable and competitive commercial-scale M × g production.

60 APPLIED LIFE SCIENCES↗

Microbial Diversity and Sulfur Cycling in an Early Earth Analogue: From Ancient Novelty to Modern Commonality

Life emerged and diversified in the absence of molecular oxygen. The prevailing anoxia and unique sulfur chemistry in the Paleo-, Meso-, and Neoarchean and early Proterozoic eras may have supported microbial communities that differ from those currently thriving on the earth’s surface. Zodletone spring in southwestern Oklahoma represents a unique habitat where spatial sampling could substitute for geological eras namely, from the anoxic, surficial light-exposed sediments simulating a preoxygenated earth to overlaid water column where air exposure simulates oxygen intrusion during the Neoproterozoic era. We document a remarkably diverse microbial community in the anoxic spring sediments, with 340/516 (65.89%) of genomes recovered in a metagenomic survey belonging to 200 bacterial and archaeal families that were either previously undescribed or that exhibit an extremely rare distribution on the current earth. Such diversity is underpinned by the widespread occurrence of sulfite, thiosulfate, tetrathionate, and sulfur reduction and the paucity of sulfate reduction machineries in these taxa.

59 BASIC BIOLOGICAL SCIENCES↗

Measuring Equality in Machine Learning Security Defenses: A Case Study in Speech Recognition

Over the past decade, the machine learning security community has developed a myriad of defenses for evasion attacks. An understudied question in that community is: for whom do these defenses defend? This work considers common approaches to defending learned systems and how security defenses result in performance inequities across different sub-populations. We outline appropriate parity metrics for analysis and begin to answer this question through empirical results of the fairness implications of machine learning security methods. We find that many methods that have been proposed can cause direct harm, like false rejection and unequal benefits from robustness training. The framework we propose for measuring defense equality can be applied to robustly trained models, preprocessing-based defenses, and rejection methods. We identify a set of datasets with a user-centered application and a reasonable computational cost suitable for case studies in measuring the equality of defenses. In our case study of speech command recognition, we show how such adversarial training and augmentation have non-equal but complex protections for social subgroups across gender, accent, and age in relation to user coverage. We present a comparison of equality between two rejection-based defenses: randomized smoothing and neural rejection, finding randomized smoothing more equitable due to the sampling mechanism for minority groups. This represents the first work examining the disparity in the adversarial robustness in the speech domain and the fairness evaluation of rejection-based defenses.

• Artificial intelligence (AI) / machine learning ↗

Dated soil C–N–P profiles, water quality, and chamber fluxes across Ohio and Michigan wetlands (2024–2025)

This dataset includes dated soil core chemistry (bulk density, phosphorus, nitrogen and carbon concentrations), water quality, and chamber flux measurements collected from wetlands in the Midwest United States—12 sites in Ohio, one site in Indiana, one site in Michigan—collected in the spring or summer of 2024 or 2025, all in (.csv) format. These data were generated to examine how wetland restoration, management activities, and time since restoration affect biogeochemical processes, carbon sequestration, nutrient accumulation, water quality, and greenhouse gas emissions. Specifically, these data aim to investigate how restored wetlands differ from natural wetlands in terms of carbon, nitrogen, phosphorus dynamics, as well as carbon dioxide and methane fluxes. Also included are surface and porewater quality parameters and chamber flux measurements across these different wetlands. Sampling was conducted at various sites representing a range of restoration stages, from about 4 years post-restoration up to 105 years post-restoration, and also includes a natural wetland used as a reference in Michigan. These data can be used to determine carbon sequestration rates, nutrient cycling, and to enhance our understanding of biogeochemical responses to wetland restoration in temperate ecosystems. This data package contains (1) a csv file (Water_Quality.csv) containing water quality data (dissolved organic carbon, total dissolved nitrogen, and temperature) organized by location; (2) a csv file (Soil_C_N_P_Seq.csv) containing carbon, nitrogen, and phosphorus concentrations at each soil level and time of each soil level, as well as their sequestration rates; (3) a csv file (CH4_CO2_Flux.csv) including methane and carbon dioxide fluxes that were measured with a chamber; (4) a file-level metadata (FLMD.csv) file that lists each file contained in the dataset with associated metadata; (5) a data dictionary (DD.csv) file that contains terms/column headers used throughout the files along with a definition, units, and data type; and (6) a locations metadata file (Location_metadata.csv).

Earth Science > Atmosphere > Atmospheric Chemistry↗

Enabling Dark Energy Measurements from DESI and LSST (Final Technical Report)

This grant enabled efforts to lead the Survey Validation of the Luminous Red Galaxy (LRG) sample for DESI, entailing intensive work to prepare target samples, test their performance with DESI data, and validate that the requirements of the survey for this key sample are met. Luminous Red Galaxies represent the gold standard target class for Baryon Acoustic Observation experiments to study Dark Energy. It also funded work to co-leading the Follow-up Task Force within the LSST Dark Energy Science Collaboration (LSST DESC), which is intended to help develop collaborations with external groups and to produce cross-working group proposals for telescope time, policy proposals and white papers as needed in order to help the collaboration obtain and make use of complementary data which will strengthen LSST Dark Energy constraints. The PI has been particularly engaged in efforts to obtain access to spectroscopic training sets for LSST photometric redshifts in the first years of the survey, which requires developing relationships with groups that are obtaining such data for other purposes. This group has evolved into an External Synergies working group within DESC, also co-led by the PI. These groups have developed white papers for Astro2020, letters of intent and white papers for Snowmass2021, and a response to a DOE-NASA RFI. It also has enabled smaller contributions to improving LSST DESC pipeline infrastructure for photometric redshifts.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Geophysical Characterization and Monitoring of the 200 Area Treated Effluent Disposal Facility to Support Permit Renewal; TEDF Geophysical Monitoring

The Treated Effluent Disposal Facility (TEDF), located in the 200 East Area of the Hanford Site, is a site where non-hazardous and non-radioactive liquid wastes are disposed into two state-permitted infiltration basins. In 2016, the Washington State Department of Ecology denied a permit renewal request for TEDF due to the inability to adequately assess the impact of TEDF discharge water on the underlying groundwater quality. TEDF overlies the relatively impermeable Ringold Lower Mud (RLM) unit, whose upper contact lies in the vadose zone approximately 30 m below ground surface and approximately 10 m above the water table boundary. The RLM is assumed to isolate TEDF discharge water from the natural groundwater aquifer, which is monitored using wellbores screened below the RLM. Therefore, samples collected from monitoring wells near TEDF are not considered representative of TEDF discharge water. Rather, TEDF discharge water is assumed to mound on top of the RLM to form a perched aquifer. To support permitting of the TEDF, a new monitoring well is required that can be used to sample water from the presumed perched water aquifer above the RLM. Ideally, the screened section of the well would be located at the peak of the perched water mound(s), which presumably occurs at the point of maximum vertical flux from TEDF to the RLM, or equivalently where the dominant infiltration flow paths reach the RLM. This report describes how time-lapse 3D electrical resistivity tomography (ERT) was used in conjunction with nominal TEDF discharge operations to image the dominant flow paths from each pond to the RLM. Results are summarized in Figure ES.1. Figure ES.1A shows a satellite image of the TEDF overlain by an array of surface ERT electrodes. The solid and dashed black circles denote the zones of maximum vertical flux at the RLM within the south and north ponds, respectively, and presumably the regions where perched water peaks during discharge. Figure ES.1B shows time-lapse difference imaging results approximately 15 days after switching discharge from the south pond to the north pond. Blue iso-surfaces beneath the north pond denote regions of increasing bulk electrical conductivity caused by increasing saturation due to infiltrating water. Red iso-surfaces beneath the south pond denote regions that were previously saturated during the south pond discharge and are now de-saturating, causing a decrease in bulk electrical conductivity. In both cases, the zones of maximum change mark the dominant flow paths to the RLM. Figure ES.1C shows time-lapse imaging results approximately 15 days after switching discharge from the north pond to the south pond. In this case, blue iso-surfaces mark the dominant flow paths to the RLM from the south pond. The red iso-surfaces mark the dominant flow paths that existed during discharge to the north pond. The regions of maximum change in bulk conductivity (due to saturation or desaturation) that mark the primary flow paths are equivalent in both cases and denoted by the dashed solid and black circles. If a perched water zone forms on the RLM, it is likely to mound within or near the dashed circle during discharge to the north pond, and in the solid circle during discharge to the south pond. In other words, if perched water mounding occurs, the circles mark the optimum locations suggested by the ERT imaging for monitoring boreholes to be placed, enabling samples to be collected that are representative of TEDF discharge impacts on groundwater quality.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Sludge Batch 11 Assembly: Tank 26

Savannah River Mission Completion Nuclear Safety and Engineering Integration (SRMC-E) has requested that Savannah River National Laboratory (SRNL) perform Tank 26 characterization analyses in support of Sludge Batch 11 (SB11) assembly. This report provides important characterization of the slurry in Tank 26 prior to transfer from Tank 26 to Tank 51 that confirms the transfer is "Low Rem" and ensures the sludge concurs with the estimated transfer mass for the SB11 recipe. Two Tank 26 samples were delivered to SRNL and composited into a single sample in September 2023. The composite sample was analyzed for the following: density, weight percent solids, chemical composition, radionuclides, supernate corrosion control tests, and x-ray diffraction for burkeite, gibbsite, and boehmite. The slurry was also evaluated for sulfate washing behavior in order to provide knowledge on insoluble sulfate dissolution during Tank 51 sludge washing similar to a previous washing study performed in 2019. The Tank 26 sample results are consistent with and representative of PUREX sludge and the prior usage of Tank 26 as a feed tank for the 1F and 2F Evaporators.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Sludge Batch 11 Assembly: Tank 26 (Rev.1)

Savannah River Mission Completion Nuclear Safety and Engineering Integration (SRMC-E) has requested that Savannah River National Laboratory (SRNL) perform Tank 26 characterization analyses in support of Sludge Batch 11 (SB11) assembly. This report provides important characterization of the slurry in Tank 26 prior to transfer from Tank 26 to Tank 51 that confirms the transfer is "Low Rem" and ensures the sludge concurs with the estimated transfer mass for the SB11 recipe. Two Tank 26 samples were delivered to SRNL and composited into a single sample in September 2023. The composite sample was analyzed for the following: density, weight percent solids, chemical composition, radionuclides, supernate corrosion control tests, and x-ray diffraction for burkeite, gibbsite, and boehmite. The slurry was also evaluated for sulfate washing behavior in order to provide knowledge on insoluble sulfate dissolution during Tank 51 sludge washing similar to a previous washing study performed in 2019. The Tank 26 sample results are consistent with and representative of PUREX sludge and the prior usage of Tank 26 as a feed tank for the 1F and 2F Evaporators.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Detection of DoS Attacks Using ARFIMA Modeling of GOOSE Communication in IEC 61850 Substations

Integration of Information and Communication Technology (ICT) in modern smart grids (SGs) offers many advantages including the use of renewables and an effective way to protect, control and monitor the energy transmission and distribution. To reach an optimal operation of future energy systems, availability, integrity and confidentiality of data should be guaranteed. Research on the cyber-physical security of electrical substations based on IEC 61850 is still at an early stage. In the present work, we first model the network traffic data in electrical substations, then, we present a statistical Anomaly Detection (AD) method to detect Denial of Service (DoS) attacks against the Generic Object Oriented Substation Event (GOOSE) network communication. According to interpretations on the self-similarity and the Long-Range Dependency (LRD) of the data, an Auto-Regressive Fractionally Integrated Moving Average (ARFIMA) model was shown to describe well the GOOSE communication in the substation process network. Based on this ARFIMA-model and in view of cyber-physical security, an effective model-based AD method is developed and analyzed. Two variants of the statistical AD considering statistical hypothesis testing based on the Generalized Likelihood Ratio Test (GLRT) and the cumulative sum (CUSUM) are presented to detect flooding attacks that might affect the availability of the data. Our work presents a novel AD method, with two different variants, tailored to the specific features of the GOOSE traffic in IEC 61850 substations. The statistical AD is capable of detecting anomalies at unknown change times under the realistic assumption of unknown model parameters. The performance of both variants of the AD method is validated and assessed using data collected from a simulation case study. We perform several Monte-Carlo simulations under different noise variances. The detection delay is provided for each detector and it represents the number of discrete time samples after which an anomaly is detected. In fact, our statistical AD method with both variants (CUSUM and GLRT) has around half the false positive rate and a smaller detection delay when compared with two of the closest works found in the literature. Our AD approach based on the GLRT detector has the smallest false positive rate among all considered approaches. Whereas, our AD approach based on the CUSUM test has the lowest false negative rate thus the best detection rate. Depending on the requirements as well as the costs of false alarms or missed anomalies, both variants of our statistical detection method can be used and are further analyzed using composite detection metrics.

IEC 61850 electrical substations↗