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At least 1,135 records · Page 63

Experiments with partially-reflected square-pitched arrays of water-moderated 6.9 enriched UO{sub 2} fuel rods - 14593

The Seven Percent Critical Experiment (7uPCX) at Sandia National Laboratories was designed to provide benchmark criticality and reactor physics data for water-moderated pin-fueled nuclear reactor cores in the 5 to 10 percent enrichment range. Approach-to-critical experiments were performed on nineteen partially-reflected arrays of pure water-moderated and -reflected fuel rods with a fuel-to-water volume ratio of 0.67. Those configurations are described and the results of the measurements are reported in this paper. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Stratigraphic and structural controls on groundwater flow in an outcropping fossil fan delta: the case of Sant Llorenç del Munt range (NE Spain)

Hydrogeological models of mountain regions present the opportunity to understand the role of geological factors on groundwater resources. The effects of sedimentary facies and fracture distribution on groundwater flow and resource exploitation studied in the ancient fan delta of Sant Llorenç de Munt (central Catalonia, Spain) by integrating geological field observations (using sequence stratigraphy methods) and hydrogeological data (pumping tests, hydrochemistry and environmental isotopes). A comprehensive analysis of data portrays the massif as a single unit, constituted by different compartments determined by specific layers and sets of fractures. Two distinct flow systems—local and regional—are identified based on pumping test analysis as well as hydrochemical and isotopic data. Drawdown curves derived from pumping tests indicate that the behavior of the saturated layers, whose main porosity is given by the fracture network, corresponds to a confined aquifer. Pumping tests also reflect a double porosity within the system and the occurrence of impervious boundaries that support a compartmentalized model for the whole aquifer system. Hydrochemical data and associated spatial evolution show the result of water–rock interaction along the flow lines. Concentration of magnesium, derived from dolomite dissolution, is a tracer of the flow-path along distinct stratigraphic units. Water stable isotopes indicate that evaporation (near a 5% loss) occurs in a thick unsaturated zone within the massif before infiltration reaches the water table. The hydrogeological analysis of this outcropping system provides a methodology for the conceptualization of groundwater flow in similar buried systems where logging and hydrogeological information are scarce.

58 GEOSCIENCES↗

Investigating Vegetation Responses to Underground Nuclear Explosions Through Integrated Analyses

Vegetation has the potential to respond to underground nuclear explosions, yet these links have not been fully explored. Given the lack of previously described signatures, the changes in vegetation are possibly subtle. The integration of multiple different data streams is potentially a useful approach to improve signal detection. Here, we investigate whether semi-arid vegetation growth patterns responded to eight legacy underground nuclear tests at the Nevada National Security Site in southern Nevada, USA. We tested for spatial and temporal changes in vegetation cover, tree growth patterns, and tree leaf spectral properties using ground-based measurements, including those from tree-rings and hyperspectral surface vegetation reflectance, as well as space-based measurements of Normalized Difference Vegetation Index (NDVI) from Landsat. Multiple data streams suggest a localized (<1.2 km) spatial pattern whereby tree growth is enhanced closer to the source of the underground test relative to sites further away. We also observed a more regional (>1.2–9 km) pattern whereby tree growth is suppressed coincident with a drought beginning 1 year before the 1989 tests, but continuing in the 5 years following the tests, which is anomalous relative to what is expected based on the response of tree growth to previous droughts. furthermore, quantification of the relative effects of the tests on vegetation remains a challenge due to the coincident drought and the potential for other disturbances to have impacted tree growth at this time, but the integration of these data reveals a more nuanced growth response than any other one data set indicates alone.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

The time of a photoinduced spin-Peierls phase transition

The time τ of the spin-Peierls phase transition is analyzed theoretically as a function of the duration τ{sub p} of the exciting light pulse and the average number x{sub 0} of absorbed photons per magnetic ion after the transmission of the pulse. It is shown that the phase transition occurs at x{sub 0} > x{sub c}. The critical value x{sub c} is determined as a function of the duration τ{sub p} of the light pulse. A photoinduced variation in the optical reflection coefficient R is calculated as a function of time t. The results of calculation are compared with experimental data on ultrafast photoinduced melting of the low-temperature spin-Peierls phase into potassium tetracyanoquinodimethan (K-TCNQ)

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A robust aerosol impact on clouds along the subtropical to tropical transition

Marine clouds undergo a transition from subtropical stratocumulus (Sc) to shallow cumulus (Cu) and eventually to deep convective (DC) systems as air masses advect from the subtropics towards the deep tropics. How aerosols modulate this Lagrangian cloud evolution remains largely uncertain. Here we use both 5 years of satellite observations mapped along 8 d Lagrangian trajectories and complementary large-eddy simulations from 9 initiation locations across the Northeast Pacific, Southeast Pacific, and Southeast Atlantic. This Lagrangian framework allows us to quantify the aerosol effect and its co-variability with meteorological conditions on cloud microphysics, macrophysics, and top-of-atmosphere radiation through the full Sc-Cu-DC transition. We show that increasing aerosol concentrations leads to deeper and more reflective clouds throughout this cloud transition. Examining the thermodynamic evolution along the trajectory indicates a well-known trend: enhanced moistening near the boundary-layer top and lower free troposphere under polluted conditions, suggesting that part of the co-variability between aerosol and meteorological conditions may be internally driven. The agreement between model simulations and satellite data alongside the multi-basin coherence of the results indicates that aerosols systematically amplify cloud depth and reflectivity during the subtropical–to–tropical cloud transition.

54 ENVIRONMENTAL SCIENCES↗

Indexing amyloid peptide diffraction from serial femtosecond crystallography: new algorithms for sparse patterns

Special methods are required to interpret sparse diffraction patterns collected from peptide crystals at X-ray free-electron lasers. Bragg spots can be indexed from composite-image powder rings, with crystal orientations then deduced from a very limited number of spot positions. Still diffraction patterns from peptide nanocrystals with small unit cells are challenging to index using conventional methods owing to the limited number of spots and the lack of crystal orientation information for individual images. New indexing algorithms have been developed as part of the Computational Crystallography Toolbox (cctbx) to overcome these challenges. Accurate unit-cell information derived from an aggregate data set from thousands of diffraction patterns can be used to determine a crystal orientation matrix for individual images with as few as five reflections. These algorithms are potentially applicable not only to amyloid peptides but also to any set of diffraction patterns with sparse properties, such as low-resolution virus structures or high-throughput screening of still images captured by raster-scanning at synchrotron sources. As a proof of concept for this technique, successful integration of X-ray free-electron laser (XFEL) data to 2.5 Å resolution for the amyloid segment GNNQQNY from the Sup35 yeast prion is presented.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Dehydration of Uranyl Nitrate Hexahydrate to Uranyl Nitrate Trihydrate under Ambient Conditions as Observed via Dynamic Infrared Reflectance Spectroscopy

the hexahydrate [UO 2 (NO 3 ) 2 (H 2 O) 6 ] (UNH) and the trihydrate [UO 2 (NO 3 ) 2 (H 2 O) 3 ] (UNT) forms. Their stabilities depend on both relative humidity and temperature. Both phases have previously been studied by infrared transmission spectroscopy, but the data were limited by both instrumental resolution and the ability to prepare the samples as pellets without desiccating them. We report time-resolved infrared (IR) measurements using an integrating sphere that allow us to observe the transformation from the hexahydrate to the trihydrate simply by flowing dry nitrogen gas over the sample. Hexahydrate samples were prepared and confirmed via known XRD patterns, then measured in reflectance mode. The hexahydrate has a distinct uranyl asymmetric stretch band at 949.0 cm -1 that shifts to shorter wavelengths and broadens as the sample dehydrates and recrystallizes to the trihydrate, first as a blue edge shoulder but ultimately resulting in a doublet band with reflectance peaks at 966 and 957 cm -1 . The data are consistent with transformation from UNH to UNT since UNT has two non-equivalent UO 2 2+ sites. The dehydration of UO 2 (NO 3 ) 2 (H 2 O) 6 to UO 2 (NO 3 ) 2 (H 2 O) 3 is both a morphological and structural change that has the lustrous lime green crystals changing to the dull greenish yellow of the trihydrate. Crystal structures and phase transformation were confirmed theoretically using DFT calculations and experimentally via microscopy methods. Both methods showed a transformation with two distinct sites for the uranyl cation in the trihydrate, as opposed to a single crystallographic site in the hexahydrate.

36 MATERIALS SCIENCE↗

Improved crystal orientation and physical properties from single-shot XFEL stills

X-ray free-electron laser crystallography relies on the collection of still-shot diffraction patterns. New methods are developed for optimal modeling of the crystals’ orientations and mosaic block properties. X-ray diffraction patterns from still crystals are inherently difficult to process because the crystal orientation is not uniquely determined by measuring the Bragg spot positions. Only one of the three rotational degrees of freedom is directly coupled to spot positions; the other two rotations move Bragg spots in and out of the reflecting condition but do not change the direction of the diffracted rays. This hinders the ability to recover accurate structure factors from experiments that are dependent on single-shot exposures, such as femtosecond diffract-and-destroy protocols at X-ray free-electron lasers (XFELs). Here, additional methods are introduced to optimally model the diffraction. The best orientation is obtained by requiring, for the brightest observed spots, that each reciprocal-lattice point be placed into the exact reflecting condition implied by Bragg’s law with a minimal rotation. This approach reduces the experimental uncertainties in noisy XFEL data, improving the crystallographic R factors and sharpening anomalous differences that are near the level of the noise.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Leveraging machine learning to enhance aerosol classification using Single-Particle Mass Spectrometry

Advancing automated classification of atmospheric aerosols from Single-Particle Mass Spectrometry (SPMS) data remains challenging due to overlapping ion signatures, compositional diversity, and limited labeled data. This study evaluates supervised and semi-supervised learning frameworks to enhance aerosol identification by jointly leveraging labeled and unlabeled spectra. Four models were compared: a supervised Support Vector Machine (SVM), a self-training SVM, a stacked autoencoder classifier, and a stacked autoencoder trained using a temporal-ensembling Mean Teacher approach. All models achieved high and stable accuracies (90.0 %–91.1 %), surpassing previous results on the same dataset (87 %) and matching the performance of state-of-the-art deep learning methods. Despite small global metric differences (≤ 1 %), semi-supervised variants yielded up to 5 %–10 % improvements for compositionally rare particle types – such as soot (0.77 % of spectra, F1-score: 0.93–0.97) and hazelnut pollen (0.98 % of spectra, F1-score: 0.97–1.00) – equating to roughly ∼ 187 additional correctly classified spectra. These gains are scientifically significant, as such rare particles exert disproportionate influence on radiative absorption and ice nucleation processes; their improved detection reduces modeled uncertainties in aerosol absorption optical depth and mixed-phase cloud ice nucleation rates. The models' residual misclassifications (≈ 9 %) largely arise from true spectral overlap among chemically adjacent species (e.g., Na- vs. K-feldspar, coated vs. uncoated feldspars), reflecting physical compositional continuity rather than algorithmic error. Collectively, these findings demonstrate that leveraging unlabeled data to learn robust spectral representations and refine classification enhances both fidelity and interpretability, bridging data-driven analysis with aerosol–climate process understanding.

54 ENVIRONMENTAL SCIENCES↗

Energy Prediction Impact of the Space Level Occupancy Schedule for a Primary School

By using the same occupant schedule for all spaces, a building level occupancy schedule in building energy modelling can reduce the cost and time of data collection, especially for large-scale simulations or when detailed occupancy data cannot be obtained. However, by describing the unique occupancy status in each space, a space level schedule can better reflect real-world scenarios. This research investigates the energy prediction impact of a space level occupancy schedule for primary school modelling in 16 ASHRAE climate zones. The results show that when switched from a building level to a space level occupancy schedule, the energy prediction difference is between -1.0% and 0.8%. Generally, the predicted building energy consumption using a space level occupancy schedule is higher than when using a building level occupancy schedule in hot and warm climate zones, but lower in other climate zones.

building energy model↗

Could geoengineering research help answer one of the biggest questions in climate science?: GEOENGINEERING RESEARCH

Anthropogenic aerosol impacts on clouds constitute the largest source of uncertainty in quantifying the radiative forcing of climate, and hinders our ability to determine Earth's climate sensitivity to greenhouse gas increases. Representation of aerosol–cloud interactions in global models is particularly challenging because these interactions occur on typically unresolved scales. Observational studies show influences of aerosol on clouds, but correlations between aerosol and clouds are insufficient to constrain aerosol forcing because of the difficulty in separating aerosol and meteorological impacts. In this commentary, we argue that this current impasse may be overcome with the development of approaches to conduct control experiments whereby aerosol particle perturbations can be introduced into patches of marine low clouds in a systematic manner. Such cloud perturbation experiments constitute a fresh approach to climate science and would provide unprecedented data to untangle the effects of aerosol particles on cloud microphysics and the resulting reflection of solar radiation by clouds. Here, the control experiments would provide a critical test of high-resolution models that are used to develop an improved representation aerosol–cloud interactions needed to better constrain aerosol forcing in global climate models.

54 ENVIRONMENTAL SCIENCES↗

Predicting combustion characteristics in externally heated micro-tubes

Here this study employs a simplified analytical model to obtain qualitative predictions of transitions between non-adiabatic combustion regimes found in non-catalytic tubular micro-flow reactors, i.e. normal stable flames, flames with repetitive extinction and ignition (FREI), and weak flames that are stabilized by wall heat transfer. Assuming large activation energy for single-step kinetics, a comparison of exact solutions for constant and variable wall temperature profiles reveals that while a non-zero wall temperature gradient introduces a temperature lag, it has no impact on the structure of the flame solution itself. This result is significant as it establishes a link to quenching characteristics within heated micro-tubes, and further facilitates a simplified micro-flow reactor analysis. Predictions for sweeps of wall temperatures are combined to S-curves, which allow for a combustion regime classification for a given combination of micro-flow reactor geometry and mixture properties. A variation of parameters such as tube diameter or mixture stoichiometry yields predictions of shifts in regime transitions, thus providing insights on interactions between heat transfer and first order effects of chemical kinetics. A comparison to experimental data illustrates that the theoretical framework, - within inherent limitations, - captures qualitatively correct trends that reflect experimental observations, thus providing valuable insights for micro-flow reactor design and operation.

42 ENGINEERING↗

Progress and plan of KSTAR plasma control system upgrade

The plasma control system (PCS) has been one of essential systems in annual KSTAR plasma campaigns: starting from a single-process version in 2008, extensive upgrades are done through the previous 7 years in order to achieve major goals of KSTAR performance enhancement. Here, major implementations are explained in this paper. In consequences of successive upgrades, the present KSTAR PCS is able to achieve ~48 s of 500 kA plasma pulses with full real-time shaping controls and real-time NB power controls. It has become a huge system capable of dealing with 8 separate categories of algorithms, 26 actuators directly controllable during the shot, and real-time data communication units consisting of +180 analog channels and +600 digital input/outputs through the reflective memory (RFM) network. The next upgrade of the KSTAR PCS is planned in 2015 before the campaign. An overview of the upgrade layout will be given for this paper. The real-time system box is planned to use the CERN MRG-Realtime OS, an ITER-compatible standard operating system. New hardware is developed for faster real-time streaming system for future installations of actuators/diagnostics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Geothermal Play Fairway Analysis, Part 2: GIS methodology

Play Fairway Analysis (PFA) in geothermal exploration originates from a systematic methodology developed within the petroleum industry and is based on a geologic, geophysical, and hydrologic framework of identified geothermal systems. We tailored this methodology to study the geothermal resource potential of the Snake River Plain and surrounding region, but it can be adapted to other geothermal resource settings. We adapted the PFA approach to geothermal resource exploration by cataloging the critical elements controlling exploitable hydrothermal systems, establishing risk matrices that evaluate these elements in terms of both probability of success and level of knowledge, and building a code-based ‘processing model’ to process results. A geographic information system was used to compile a range of different data types, which we refer to as elements (e.g., faults, vents, heat flow, etc.), with distinct characteristics and measures of confidence. Discontinuous discrete data (points, lines, or polygons) for each element were transformed into continuous interpretive 2D grid surfaces called evidence layers. Because different data types have varying uncertainties, most evidence layers have an accompanying confidence layer which reflects spatial variations in these uncertainties. Risk layers, as defined here, are the product of evidence and confidence layers, and are the building blocks used to construct Common Risk Segment (CRS) maps for heat, permeability, and seal, using a weighted sum for permeability and heat, but a different approach with seal. CRS maps quantify the variable risk associated with each of these critical components. In a final step, the three CRS maps were combined into a Composite Common Risk Segment (CCRS) map, using a modified weighted sum, for results that reveal favorable areas for geothermal exploration. Additional maps are also presented that do not mix contributions from evidence and confidence (to allow an isolated view of evidence and confidence), as well as maps that calculate favorability using the product of components instead of a weighted sum (to highlight where all components are present). Our approach helped to identify areas of high geothermal favorability in the western and central Snake River Plain during the first phase of study and helped identify more precise local drilling targets during the second phase of work. By identifying favorable areas, this methodology can help to reduce uncertainty in geothermal energy exploration and development.

15 GEOTHERMAL ENERGY↗

Pitfalls in Prediction Modeling for Normal Tissue Toxicity in Radiation Therapy: An Illustration With the Individual Radiation Sensitivity and Mammary Carcinoma Risk Factor Investigation Cohorts

Purpose: To identify the main causes underlying the failure of prediction models for radiation therapy toxicity to replicate. Methods and Materials: Data were used from two German cohorts, Individual Radiation Sensitivity (ISE) (n=418) and Mammary Carcinoma Risk Factor Investigation (MARIE) (n=409), of breast cancer patients with similar characteristics and radiation therapy treatments. The toxicity endpoint chosen was telangiectasia. The LASSO (least absolute shrinkage and selection operator) logistic regression method was used to build a predictive model for a dichotomized endpoint (Radiation Therapy Oncology Group/European Organization for the Research and Treatment of Cancer score 0, 1, or ≥2). Internal areas under the receiver operating characteristic curve (inAUCs) were calculated by a naïve approach whereby the training data (ISE) were also used for calculating the AUC. Cross-validation was also applied to calculate the AUC within the same cohort, a second type of inAUC. Internal AUCs from cross-validation were calculated within ISE and MARIE separately. Models trained on one dataset (ISE) were applied to a test dataset (MARIE) and AUCs calculated (exAUCs). Results: Internal AUCs from the naïve approach were generally larger than inAUCs from cross-validation owing to overfitting the training data. Internal AUCs from cross-validation were also generally larger than the exAUCs, reflecting heterogeneity in the predictors between cohorts. The best models with largest inAUCs from cross-validation within both cohorts had a number of common predictors: hypertension, normalized total boost, and presence of estrogen receptors. Surprisingly, the effect (coefficient in the prediction model) of hypertension on telangiectasia incidence was positive in ISE and negative in MARIE. Other predictors were also not common between the 2 cohorts, illustrating that overcoming overfitting does not solve the problem of replication failure of prediction models completely. Conclusions: Overfitting and cohort heterogeneity are the 2 main causes of replication failure of prediction models across cohorts. Cross-validation and similar techniques (eg, bootstrapping) cope with overfitting, but the development of validated predictive models for radiation therapy toxicity requires strategies that deal with cohort heterogeneity.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

X-ray topographic study of Bridgman-grown CdZnTeSe

We have characterized the structural quality of Cd 0.9 Zn 0.1 Te 0.93 Se 0.07 ingot grown by the vertical Bridgman growth technique. The structural quality of Cd 0.9 Zn 0.1 Te 0.93 Se 0.07 ingot along the length was investigated via X-ray topography in the reflection mode using a white beam synchrotron radiation source. The X-ray topography data revealed the presence of very few sub grain boundaries and no sub-grain boundary network for the CdZnTeSe samples used in this study.

36 MATERIALS SCIENCE↗

Integrating field observations and process-based modeling to predict watershed water quality under environmental perturbations

Watersheds play a critical role in supplying water resources needed for human use and ecosystem health. Understanding and predicting how, when, and where changes in the quantity and quality of water resources occur under different environmental stresses including extreme events is crucial for sustainable management of water resources under a changing environment. However, few studies have attempted to quantify or identify the factors and process interactions controlling the impact of extreme events across water-shed systems. Only few large-scale studies include coordinated monitoring and modeling efforts, which limits our ability to assess the large-scale impact of extreme events on water supply and quality. Methods are lacking to propagate uncertainty in process understanding through an integrated hydro-biogeochemical model framework and evaluate its importance, thus failing to take full advantage of the information potentially available through transformative advances in characterization technologies from high-resolution mass spectrometry to airborne and satellite-based remote sensing. There are consequent risks to our nations water security and to human and ecosystem health that may become exacerbated with the increasing frequency of extreme events that is projected for the coming decades. This paper reviews the current status of watershed science for both water quantity and quality and identifies critical gaps in our current knowledge and modeling capability in addressing the emergent needs in predicting watershed hydrologic and biogeochemical responses (i.e., water quantity and quality) under natural and anthropogenic perturbations. We highlight the need to (1) understand how environmental perturbations including extreme events like floods and droughts propagate through watershed systems and assess their short- and long-term impacts on watershed biogeochemistry, water quality and their recovery pathways; (2) develop and improve a watershed water quality model that reflects the state of scientific understanding gained from observations; and (3) construct a data-model fusion system for watershed characterization, process identification, and mechanistic model parameterization. A large base of modeling, monitoring and data capabilities have been built by various federal government agencies given the relevance of water to their critical missions. An emerging need is to build an integrated national capability for watershed water availability and quality that can address water-related missions across multiple federal agencies.

13 HYDRO ENERGY↗