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At least 1,261 records · Page 70

Resonant ultrasound spectroscopy probe for in-situ neutron scattering measurements

Resonant ultrasound spectroscopy (RUS) is an efficient, nondestructive technique to study the elastic properties of solids. A low-temperature (2-300 K) probe has been assembled and tested at the NOMAD beamline at the Spallation Neutron Source at Oak Ridge National Laboratory to assess the probe's neutronic properties, data acquisition system, and compatibility with existing sample environment. A case study on a bulk metallic glass, La 65 Cu 20 Al 10 Co 5, served to benchmark both hardware and software developments. The elastic constants of the metallic glass were determined as a function of temperature between 4 and 300 K and were used to guide neutron diffraction measurements at NOMAD. Tracking of a specific RUS peak center frequency and width enabled live monitoring of the sample temperature evolution that lagged thermometry by upwards of 40 K near room temperature. Assembly of a high-temperature (300-875 K) probe is underway and both probes are scheduled to be available to users by late-2021. Our aim is to provide users with live monitoring of an intrinsic variable at the neutron scattering beamlines, in addition to existing controls, to monitor the state of their samples and its elastic moduli and make informed decisions in real time.

Torres, James↗

Low-energy gamma ray attenuation characteristics of aviation fuels

Am241 (59.5 keV) gamma ray attenuation characteristics were investigated in 270 aviation fuel (Jet A and Jet A-1) samples from 76 airports around the world as a part of world wide study to measure the variability of aviation fuel properties as a function of season and geographical origin. All measurements were made at room temperature which varied from 20 to 27 C. Fuel densities (rho) were measured concurrently with their linear attenuation coefficients (mu), thus providing a measure of mass attenuation coefficient (mu/rho) for the test samples. In 43 fuel samples, rho and mu values were measured at more than one room temperature, thus providing mu/rho values for them at several temperatures. The results were found to be independent of the temperature at which mu and rho values were measured. It is noted that whereas the individual mu and rho values vary considerably from airport to airport as well as season to season, the mu/rho values for all samples are constant at 0.1843 + or - 0.0013 cu cm/gm. This constancy of mu/rho value for aviation fuels is significant since a nuclear fuel quantity gauging system based on low energy gamma ray attenuation will be viable throughout the world.

Singh, Jag J.↗

Remote and automated high-throughput powder diffraction measurements enabled by a robotic sample changer at SSRL beamline 2-1

The general-purpose powder diffractometer beamline (BL2-1) at the Stanford Synchrotron Radiation Lightsource (SSRL) is described. The evolution of design and performance of BL2-1 are presented, in addition to current operating specifications, applications and measurement capabilities. Recent developments involve a robotic sample changer enabling high-throughput X-ray diffraction measurements, applicable to mail-in and remote operations. In situ and operando capabilities to measure samples with different form factors ( e.g. capillary, flat plate or thin film, and transmission) and under variable experimental conditions are discussed. Several example datasets and accompanying Rietveld refinements are presented.

43 PARTICLE ACCELERATORS↗

The iron oxidation state of Ryugu samples

The Hayabusa2 mission sampled Ryugu, an asteroid that did not suffer extensive thermal metamorphism, and returned rocks to the Earth with no significant air exposure. It therefore offers a unique opportunity to study the redox state of carbonaceous Cb-type asteroids and evaluate the overall redox state of the most primitive rocks of the solar system. An analytical framework was developed to investigate the iron mineralogy and valence state in extraterrestrial material at the micron scale by combining x-ray diffraction, conventional Mössbauer (MS), and nuclear forward scattering (NFS) spectroscopies. An array of standard minerals was analyzed and cross-calibrated between MS and NFS. Then, MS and NFS spectra on three Ryugu grains were collected at the bulk and the micron scales. In Ryugu samples, iron is essentially accommodated in magnetite, clay minerals (serpentine–smectite), and sulfides. Only a single set of Mössbauer parameters was necessary to account for the entire variability observed in MS and NFS spectra, at all spatial scales investigated. These parameters therefore make up a fully consistent iron mineralogical model for the Ryugu samples. As far as MS and NFS spectroscopies are concerned, Ryugu grains are overall similar to each other and share most of their mineralogical features with CI-type chondrites. In detail however, no ferrihydrite is found in Ryugu particles even at the very sensitive scale of Mössbauer spectroscopy. The typical Fe 3+ /Fe tot of clay minerals is much lower than typical redox ratios measured in CI chondrites (Fe 3+ /Fe tot = 85%–90%). Furthermore, magnetite from Ryugu is stoichiometric with no significant maghemite component, whereas up to 12% of maghemite was previously identified in the Orgueil's so-called magnetite. These differences suggest that most CI meteorites suffered terrestrial alteration and that the preterrestrial composition of these carbon-rich samples was less oxidized than previously measured. However, it is not clear yet whether or not the parent bodies of CI chondrites were as reduced as Ryugu. Finally, the high spatial resolution of NFS allows to disentangle the redox state and the crystal chemistry of iron accommodated in serpentine and smectite. The most likely polytype of serpentine is lizardite, containing <35% of Fe 3+ , a fraction of which being tetrahedrally coordinated. Smectite is more oxidized (Fe 3+ /Fe tot > 65%) and mainly contains octahedral ferric iron. In conclusion, this finding implies that these clays formed from highly alkaline fluids and the spatial variability highlighted here may suggest a temporal evolution or a spatial variability of the nature of this fluid.

58 GEOSCIENCES↗

Planning Bias: Planning as a Source of Sampling Bias

Many data-driven planning methods are trained on data generated by planners. It is well known that many statistical learning methods are sensitive to sampling bias, and yet there has been little or no attention to planning as a sampling method and its role in introducing sampling bias into planner-generated training data. Recently, it has been demonstrated that A**,* in the presence of problems with variable heuristic error, prefers some solutions over other equally cost-optimal solutions. But, as we discuss in this paper, mitigation may not be as simple as resolving arbitrary tie-breaking by sampling from ties uniformly at random. In this paper, we formalize an intuition of planning bias. We focus on problems which output a single solution. Diverse planning only complicates the problem by generalizing it to bias in the set of sets; we show how it is subject to bias in the single solution. We make some useful observations about deterministic algorithms in contrast to non-deterministic algorithms. We explain how information entropy may be a good way to measure planning bias, and discuss some issues in evaluating practical approaches to measurement. We address the intuition that uniform random tiebreaking should mitigate bias; and sketch a novel approach to constructing an appropriate random distribution for duplicate detection during forward search for unbiased A*. Finally, we suggest directions for future work.

Planning Scheduling Algorithms↗

A Probabilistic Model for Global EMIC Wave Activity Using Van Allen Probes Observations

Electromagnetic ion cyclotron (EMIC) waves play a key role in radiation belt dynamics through resonant interactions. However, their low occurrence probability, high variability, and spatial intermittency pose challenges for accurate modeling. In this study, we present a machine learning (ML)-based global EMIC wave model built on the entire data set from the Van Allen Probes mission. To capture the distinct statistical characteristics of wave occurrence and amplitude, the model is separated into two modules: an occurrence model trained using ML techniques, and a wave amplitude model sampled from observed probability distributions. The input parameters are limited to real-time or predictable variables to ensure practical applicability. Our model shows strong performance across the entire test set and demonstrates improved predictive capability over a baseline random occurrence model, particularly during quiet geomagnetic conditions. Evaluation during both quiet and active periods confirms the model's ability to represent the clustered and intermittent nature of EMIC wave activity. Furthermore, the model provides global estimates of wave power, enabling integration with radiation belt electron data and showing signatures consistent with wave-induced scattering. We found a good correlation between the global wave activity from the model and relativistic electron observation by Van Allen Probes, regardless of the availability of in situ wave observations. The modular structure of the model also allows for straightforward expansion for additional wave properties, such as wave frequency, which can be modeled independently. This flexible, event-sensitive approach offers a promising framework for data-driven radiation belt simulations and space weather applications.

79 ASTRONOMY AND ASTROPHYSICS↗

Synthesis of Post-fire Monitoring Activities in the Great Basin Desert, Mojave Desert, and Transition Zones

In the deserts of the American Southwest, fire return intervals of centuries to millennia are being replaced by fire return intervals of decades. This increased burn frequency has implications for post-closure management and long-term stewardship for Soils Corrective Action Units (CAUs) and Corrective Action Sites (CASs) on the Nevada National Security Site (NNSS), Tonopah Test Range, and Nevada Test and Training Range for which the U.S. Department of Energy (DOE), Environmental Management-Nevada (EM-NV) is responsible. For many CAUs and CASs, where closure-in-place alternatives were implemented or are being considered, there is a chance that these sites could burn over while they still pose a risk to the environment or human health given the long half-lives of some of the radionuclide contaminants of concern (COCs) (Shafer et al., 2007; Shafer and Gomes, 2009). Although it would have been ideal to conduct a fire-related study at a radionuclide contaminated site on the NNSS to determine how contaminated soils are transported post-fire, it was more practical to examine fires in environments analogous to where Soils Activity CAUs and CASs exist. Therefore, a series of studies were initiated at three radiologically uncontaminated analog sites to better understand the possible effects of wildfire on erosion and sediment transport by wind and water should vegetation at contaminated sites burn at the NNSS. The studies took place at the sites of the Gleason Fire, a prescribed burn that occurred near Ely, Nevada, which is in the Great Basin ecoregion; the White Rock Fire that occurred near Mesquite, Nevada, which is in the Mojave Desert ecoregion; and the Jacob Fire that occurred near Hiko, Nevada, in the transitional zone between the Great Basin Desert and the Mojave Desert. Each site was representative of one of the three ecoregions found on the NNSS. Erosion and vegetation characteristics were measured multiple times post-fire on both burned and unburned test plots at these study sites to compare and monitor the effects of fire over time. However, at the Mojave Desert site, there was an additional burn from nearly 25 years ago that was also compared with the more recent burned areas from 2013. Also, the time elapsed after the fire and the time when sampling began differed among the ecoregions. For example, at the Great Basin site, samples were collected prior to the fire and less than one month after the fire, whereas data collected at the Mojave Desert site did not occur until 22 months after the fire. The differences between the sample measurements and the time that elapsed after the fire may contribute to the variability in the data and the interpretations of the data. Runoff and water erosion were quantified through a series of rainfall and runoff simulation tests in which controlled amounts of water were delivered to the soil surface. Runoff data were collected from different microhabitats (e.g., undercanopies, interspace soils, ridges, and drainage areas). The data showed soil hydrophobicity (i.e., water repellency) on the Great Basin site for up to 12 months after the fire. The soil structure remained changed and weaker on the burned areas compared with the unburned areas for the three-year study period. Although runoff data at both the Great Basin site and transition zone site were highly variable, the post-fire runoff potential did not generally increase at either location after three years of monitoring. Mojave runoff did not differ much between fire ages or between burned and unburned areas, possibly because of the amount of vegetation growing on all three surfaces and because the fire intensity was likely lower relative to other ecoregions due to the amount of space between plants. Additionally, the measurements conducted on the Mojave fire occurred several years after the fire had burned and not within several months of the burn, which may also account for the lack of differences in runoff between burned and unburned locations. Wind erosion was assessed and quantified with a Portable In-Situ Wind ERosion Lab (PI-SWERL) on both the burned and unburned soils of different microhabitats (e.g., ridges, drainages, interspaces between plants, and plant undercanopies). Estimates of emissions (e.g., particulate matter with aerodynamic diameters less than or equal to 10 micrometers, or PM10) at different wind speeds were collected and filter samples were analyzed for chemical composition. The measurements among the fires were similar and the results of the wind erosion measurements indicate that there were seasonal influences on many parameters, but the potential for PM10 windblown dust emissions was higher on burned areas compared with unburned areas. Among the burned areas, drainages produced the most dust emissions, whereas burned ridges were the least emissive. Emissions at the Mojave site and transition zone site were similar between burned and unburned areas approximately three years after the respective fires. Emissions remained much greater on burned soils at the Great Basin site. However, site selection may have also contributed to the differences of emissions among the three study locations. Post-fire vegetation responses were documented for three years following each fire in different microhabitats (e.g., ridge, drainage, undercanopy, and interspace) at the Great Basin and transition zone sites. In 2013, at the Mojave fire site, random permanent plots were established in newly burned areas, areas that burned approximately 25 years ago, and an unburned control area. At each fire site, the regeneration of native plant species dominated the burned areas, but invasive annual grasses were present at each fire site. During the course of each three-year study, the invasive annual grasses increased in density or percentage at both the Great Basin and transition fire sites but not at the Mojave site, where annual invasive grasses remained high throughout the study period. However, the chronosequence data from the Mojave site indicate a transition to different invasive grass species with time. The post-burn vegetation at all three ecoregions is still in the early stages of succession, and shrub size should increase over time and shrub density should decrease over time. However, the recovery of the plant communities to pre-burn compositions may not occur for decades or centuries, or may not occur because of changes in climate and the presence of invasive annual grasses. Results from the three study locations suggested that contaminated soils on the NNSS that experienced wildfire had the potential for soil erosion and transport of contaminated soils. Both wind and soil runoff studies indicated that locations in the Great Basin and transition zone ecoregions were more susceptible to erosion than the Mojave Desert ecoregion, but the highest levels of erosion occurred during the early portions of the study (the first 24 months) and the Mojave Desert was not measured until 22 months after the burn. Additionally, data from the Great Basin indicated deeper soils may increase susceptibility to wind erosion. Historically, the Great Basin and transition zone ecoregions burned more frequently than the Mojave Desert because of fuel abundance and connectivity—and they continue to burn more frequently, particularly after the introduction of invasive grasses (Davies and Nafus, 2013). However, both ecoregions and the transition zone have burned with extensive, high-severity fires when certain weather and fuel conditions are met. For example, the high abundance and productivity of annual grasses and forbs—which are usually produced by above average winter precipitation—combined with early spring and summer warm, dry conditions. Future climate scenarios predict increased temperatures, variable to reduced precipitation, and larger, more extreme wildfires throughout western North America. These predictions suggest that future fires on the NNSS could increase in frequency, intensity, and severity similar to their analog ecosystems throughout the Great Basin and Mojave Desert (Dennison et al., 2014; Abatzoglou andWilliams, 2016; Westerling, 2016).

54 ENVIRONMENTAL SCIENCES↗

Steps toward determination of the size and structure of the broad-line region in active galactic nuclei. 6: Variability of NGC 3783 from ground-based data

The Seyfert 1 galaxy NGC 3783 was intensely monitored in several bands between 1991 December and 1992 August. This paper presents the results from the ground-based observations in the optical and near-IR bands, which complement the data set formed by the International Ultraviolet Explorer (IUE) spectra, discussed elsewhere. Spectroscopic and photometric data from several observatories were combined in order to obtain well-sampled light curves of the continuum and of H(beta). During the campaign the source underwent significant variability. The light curves of the optical continuum and of H(beta) display strong similarities to those obtained with the IUE. The near-IR flux did not vary significantly except for a slight increase at the end of the campaign. The cross-correlation analysis shows that the variations of the optical continuum have a lag of 1 day or less with respect to those of the UV continuum, with an uncertainty of is less than or equal to 4 days. The integrated flux of H(beta) varies with a delay of about 8 days. These results confirm that (1) the continuum variations occur simultaneously or with a very small lag across the entire UV-optical range, as in the Seyfert galaxy NGC 5548; and (2) the emission lines of NGC 3783 respond to ionizing continuum variations with less delay than those of NGC 5548. As observed in NGC 5548, the lag of H(beta) with respect to the continuum is greater than those of the high-ionization lines.

Stirpe, G. M.↗

The RR Lyrae variables in the globular cluster M68

New observations, made with the Helen Sawyer Hogg telescope at Las Campanas, have been analyzed in a search for double-mode pulsators (RRd stars) in the metal-poor globular cluster, Messier 68. Of the 30 stars studied, nine have been identified as RRd stars; V33, which exhibited the characteristics of an RRd star in 1950, now appears to be an RRc star. Reliable periods and period ratios have been determined for six of the RRd stars. Masses for these RRd stars, calculated from fitting formulas given by Kovacs et al. (1991), range from 0.75 to 0.90 solar mass, depending on the assumed luminosity and metal abundance. These masses are in the same range as those for the RRd stars in M 15, whose RRd sample resembles that of M68 very closely. Fourier parameters determined for the light curves of the M68 variables show that the RRc stars in the two clusters are also very similar. In particular, on the plot of phase parameter phi sub 31 with period, the M15 and M68 RRc samples are virtually indistinguishable. A comparison of the new M68 observations with observations made 40 yr ago shows that the periods of some of the stars have changed, but the 40 yr interval is too short for detecting period changes caused by evolutionary effects.

Clement, Christine M.↗

Beryllium Isotopes in Rainfall for Stratospheric-Tropospheric Exchange Dynamics Experiment (BIRDIE) (Final Report)

The Beryllium Isotopes in Rainfall for Stratospheric-Tropospheric Exchange Dynamics Experiment or BIRDIE was a precipitation collection campaign designed to measure cosmogenic isotopes of beryllium in rainfall and other forms of precipitation across the DOE Southern Great Plains (SGP) Atmospheric Radiation Measurement (ARM) site. Precipitation samples were collected over three weeks (May 21-June 10, 2022) at 11 SGP sites across a 120 km 2 domain in northern and central Oklahoma. The field campaign targeted summer-time convection rain events. We aimed to capture any spatial and/or temporal variability in the concentrations of beryllium-10 (10Be) and beryllium-7 (7Be) across the SGP ARM site during these rainfall events. The ratio of 10Be to 7Be (10/7Be) has been shown to be a powerful tracer for transport processes in the stratosphere-troposphere exchange (STE) system (e.g., Koch and Rind 1998). Any observed variability is analyzed to see if it could be linked to STE processes, including overshooting of deep convection clouds which penetrate the lower stratosphere. Six wet weather system events were collected within our three-week span. Five out of six of these rainfall events are classified as moderately to strongly convective. Those events are studied in more detail. The five systems also follow each other over a short time period of eleven days. In our rainfall samples we observed spatial and event variability in the concentrations of beryllium-10 and -7 which resulted in variability of 10/7 Be ratios. Each weather event appeared to exhibit a unique 10/7Be pattern across the domain that was not directly linked to storm total precipitation amount. To better understand the causes for this spatial variability, cloud characteristics in the domain were looked at to assess cloud type, cloud height and depth information. We also ran Hysplit back trajectories to identify possible air mass and moisture origins across our events. Detailed analysis is still on-going. The purpose of this technical report is to provide background on using cosmogenic isotopes as atmospheric tracers, describe the experimental design, and present the beryllium concentration and ratio data.

58 GEOSCIENCES↗

IRAS observations of novae. III - The related objects

Results are presented on an analysis of IRAS observations of a selected sample of 116 objects that show properties similar to those of classical novae detected and modeled by Harrison and Gehrz (1988, 1991). These objects include dwarf novae, novalike variables, symbiotic stars, and planetary nebulae with close binary central-star systems. A high detection rate of 80 percent was found for this sample, as compared with about 50 percent detection rate found in the earlier examined sample. A reexamination of data showed that, at low galactic latitudes, source confusion can account for many of the detections of novae. The seemingly high detection rates of other objects and the many high-latitude novae are difficult to explain.

Harrison, Tom↗

STELLAR RADIAL VELOCITIES IN THE OLD OPEN CLUSTER M67 (NGC 2682). I. MEMBERSHIPS, BINARIES, AND KINEMATICS

We present results from 13776 radial-velocity (RV) measurements of 1278 candidate members of the old (4 Gyr) open cluster M67 (NGC 2682). The measurements are the results of a long-term survey that includes data from seven telescopes with observations for some stars spanning over 40 years. For narrow-lined stars, RVs are measured with precisions ranging from about 0.1 to 0.8 km s{sup −1}. The combined stellar sample reaches from the brightest giants in the cluster down to about 4 mag below the main-sequence turnoff (V=16.5), covering a mass range of about 1.34 M{sub ⊙} to 0.76 M{sub ⊙}. Spatially, the sample extends to a radus of 30 arcmin (7.4 pc in projection at a distance of 850 pc or 6–7 core radii). We find M67 to have a mean RV of +33.64 km s{sup −1} (with an internal precision of ±0.03 km s{sup −1}) well separated from the mean velocity of the field. For stars with ⩾3 measurements, we derive RV membership probabilities and identify RV variables, finding 562 cluster members, 142 of which show significant RV variability. We use these cluster members to construct a color–magnitude diagram and identify a rich sample of stars that lie far from the standard single star isochrone, including the well-known blue stragglers, sub-subgiants and yellow giants. These exotic stars have a binary frequency of (at least) 80%, more than three times that detected for stars in the remainder of the sample. We confirm that the cluster is mass segregated, finding the binaries to be more centrally concentrated than the single stars in our sample at the 99.8% confidence level (and at the 98.7% confidence level when only considering main-sequence stars). The blue stragglers are centrally concentrated as compared to the solar-type main-sequence single stars in the cluster at the 99.7% confidence level. Accounting for measurement precision, we derive an RV dispersion in M67 of 0.80 ± 0.04 km s{sup −1} for our sample of single main-sequence stars, subgiants and giants with V⩽15.5. When corrected for undetected binaries, this sample yields a true RV dispersion of 0.59{sub −0.06}{sup +0.07} km s{sup −1}. The radial distribution of the velocity dispersion is consistent with an isothermal distribution within our stellar sample. Using the cluster RV dispersion, we estimate a virial mass for the cluster of 2100{sub −550}{sup +610} M{sub ⊙}.

79 ASTRONOMY AND ASTROPHYSICS↗

CALIPSO Observations of Near-Cloud Aerosol Properties as a Function of Cloud Fraction

This paper uses spaceborne lidar data to study how near-cloud aerosol statistics of attenuated backscatter depend on cloud fraction. The results for a large region around the Azores show that: (1) far-from-cloud aerosol statistics are dominated by samples from scenes with lower cloud fractions, while near-cloud aerosol statistics are dominated by samples from scenes with higher cloud fractions; (2) near-cloud enhancements of attenuated backscatter occur for any cloud fraction but are most pronounced for higher cloud fractions; (3) the difference in the enhancements for different cloud fractions is most significant within 5km from clouds; (4) near-cloud enhancements can be well approximated by logarithmic functions of cloud fraction and distance to clouds. These findings demonstrate that if variability in cloud fraction across the scenes used to composite aerosol statistics are not considered, a sampling artifact will affect these statistics calculated as a function of distance to clouds. For the Azores-region dataset examined here, this artifact occurs mostly within 5 km from clouds, and exaggerates the near-cloud enhancements of lidar backscatter and color ratio by about 30. This shows that for accurate characterization of the changes in aerosol properties with distance to clouds, it is important to account for the impact of changes in cloud fraction.

near-cloud aerosol↗

Water Stable Isotopes in Precipitation, Rivers, and Groundwater Across an Elevation Gradient in the Sierra Nevada Mountains (USA) Reflect Source Elevation

Understanding watershed processes is critical to predict the impacts of climate change and forest management on water resources. However, collecting hydrological data in mountainous terrain is challenging. Precipitation, river water, and groundwater H and O stable isotope data can provide insights into processes occurring at the mountain range scale. Water δ 2 H and δ 18 O values in precipitation vary with terrain elevation; thus, the resulting isotopic lapse rates of precipitation, groundwater, and river water have the potential to elucidate watershed processes and source elevations of major rivers. We analysed H and O stable isotope data of precipitation, groundwater, and river water over the course of one Water Year (Oct 2016—Oct 2017) in the Sierra Nevada mountains of California, USA. We calculated elevation-dependent isotopic lapse rates of these waters to estimate the source elevation of major rivers draining the west flank of the Sierra Nevada mountains. We also investigated the Cosumnes River's watershed in more detail to determine how river flow may be more fully partitioned. Here, we found that H and O stable isotopes in precipitation are temporally variable, but isotopic lapse rates are generally consistent with prior studies. However, groundwater samples across an elevation gradient provide a more consistent and accessible isotopic lapse rate to predict river water source elevations.

54 ENVIRONMENTAL SCIENCES↗

Little vertical and circumferential variations in stem xylem water Δ 2 H and Δ 18 O in three tree species

Vertical and circumferential patterns of xylem water isotope signatures in large trees are rarely characterized but may influence interpretation of water source investigations and soil/xylem water isotope offsets. Furthermore, to examine vertical and circumferential variation in xylem water δ 2 H and δ 18 O, we collected xylem tissue at 5 heights (0, 1, 4, 7 and 10 m) from three replicate trees of three species with contrasting xylem anatomy, two angiosperms (Liquidambar styraciflua and Quercus nigra) and one gymnosperm (Pinus taeda). Concurrently, we also determined δ 2 H and δ 18 O of groundwater, soil water, and recent precipitation. On a different day, we collected circumferential samples at 1 m from the same trees to test for sectorality effects. Water from stem and soil samples were cryogenically extracted and analyzed for δ 2 H and δ 18 O. Mean xylem water δ 2 H and δ 18 O were significantly different between species, both vertically and circumferentially. We did not find significant (p = 0.05) systematic variation in δ 2 H or δ 18 O with height. We found no significant evidence for sectorality effects on δ 2 H, δ 18 O. Variances of vertical synoptic xylem water δ 2 H or δ 18 O were similar between species, 7.2–10.4‰ for δ 2 H and 0.58–0.81‰ for δ 18 O. Circumferential variances were also similar between species, 4.0–6.0 for δ 2 H and 0.37–0.44 for δ 18 O. A mixing model showed that sweetgum, water oak and loblolly pine, were drawing most of their water from deep soil from 45 to 190 cm (84.7, 68.4 and 53.2%, respectively) however, soil water-excess values indicate δ 2 H fractionation effects on these estimates. Dual isotope mixing model evaluation with single and multiple sample configurations showed that source water estimates were not affected by within tree variability of xylem water signatures. Xylem water δ 2 H and δ 18 O variability with height or circumference, was 3.2 and 2.7 times less than between tree variation because of transient temporal and spatial processes and is, therefore, not likely to affect interpretations of water sourcing in these three species.

59 BASIC BIOLOGICAL SCIENCES↗

Physical, socio-psychological, and behavioural determinants of household energy consumption in the UK

Determining which attitudes and behaviours predict household energy consumption can help accelerate the low-carbon energy transition. Conventional approaches in this domain are limited, often relying on survey methods that produce data on individuals’ motivations and self-reported activities without pairing these with actual energy consumption records, which are particularly hard to collect for large, nationally representative samples. This challenge precludes the development of empirical evidence on which attitudes and behaviours influence patterns of energy consumption, thus limiting the extent to which these can inform energy interventions or conservation programs. This study demonstrates a novel methodology for estimating energy consumption in the absence of actual energy records by using a large, publicly available data set of energy consumption in the UK. We develop a predictive model using the Smart Energy Research Laboratory (SERL) data portal (with records from nearly 13,000 UK households) and then use this model to predict energy consumption (both electric and gas) for a sample of 1,000 UK householders for which we separately collect over 200 variables relating to climate change attitudes and practices. Our approach uses a set of over 50 independent variables that are shared between the data sets, allowing us to train a model on the SERL data and use it to analyse the relationship between energy consumption and the opinions, motivations, and daily practices of survey respondents. Results show that electricity consumption is influenced by a broader range of factors compared to gas. Household energy use is best explained by physical dwelling characteristics, socio-demographic variables, and certain behavioural and attitudinal measures. Notably, pro-environmental attitudes, frugality, and conscientiousness correlate with lower energy use, while income and consumerism are linked to higher consumption. We discuss how these findings can inform efforts to decarbonise home energy use in the UK.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

An anomaly detection framework for dynamic systems using a Bayesian hierarchical framework

Complex systems are susceptible to many types of anomalies, faults, and abnormal behavior caused by a variety of off-nominal conditions that may ultimately result in major failures or catastrophic events. Early and accurate detection of these anomalies using system inputs and outputs collected from sensors and smart devices has become a challenging problem and an active area of research in many application domains. In this article, we present a new Bayesian hierarchical framework that is able to model the relationship between system inputs (sensor measurements) and outputs (response variables) without imposing strong distributional/parametric assumptions while using only a subset of training samples and sensor attributes. Then, an optimal cost-sensitive anomaly detection framework is proposed to determine whether a sample is an anomalous one taking into consideration the trade-off between misclassification errors and detection rates. The model can be used for both supervised and unsupervised settings depending on the availability of data regarding the behavior of the system under anomaly conditions. The unsupervised model is particularly useful when it is prohibitive to identify in advance the anomalies that a system may present and where no data are available regarding the behavior of the system under anomaly conditions. A Bayesian hierarchical setting is used to structure the proposed framework and help with accommodating uncertainty, imposing interpretability, and controlling the sparsity and complexity of the proposed anomaly detection framework. A Markov chain Monte Carlo algorithm is also developed for model training using past data. Furthermore, the numerical experiments conducted using a simulated data set and a wind turbine data set demonstrate the successful application of the proposed work for system response modeling and anomaly detection.

17 WIND ENERGY↗

Predicting oxidation damage in ultra high-temperature borides: A machine learning approach

Ultra-high temperature (UHT) borides are ceramics materials with melting points above 3000 °C for structural applications in extreme environments. However, at temperatures exceeding 1600 °C and under oxidizing conditions, the material suffers from detrimental degradation. Optimized design and performance of diboride materials under such extreme conditions requires filling the missing composition-microstructure-oxidation gap. This study proposes a computational data-driven framework to connect the processing and microstructure of Ultra-high temperature borides with the oxidation damage. Random Forest Regressor (RFR) model is adopted to forecast the oxide scale thickness developed after oxidation testing based on processing variables and microstructural features. The model trained on a dataset consisting of 107 samples of experimental data extracted from the literature aims to predict oxidation damage. With proper data manipulation and fine model tuning, the predictor could forecast the oxide scale thickness of UHT diborides with a Mean Absolute Error of 37.45 μm and an R-square of 0.83. This model could be used as a high-throughput scheme to design and test new UHT diborides materials computationally. Furthermore, a model with larger composition capabilities could also be developed in the future as more experimental data become available.

36 MATERIALS SCIENCE↗