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At least 847 records · Page 47

Can we use antipredator behavior theory to predict wildlife responses to high-speed vehicles?

Animals seem to rely on antipredator behavior to avoid vehicle collisions. There is an extensive body of antipredator behavior theory that have been used to predict the distance/time animals should escape from predators. These models have also been used to guide empirical research on escape behavior from vehicles. However, little is known as to whether antipredator behavior models are appropriate to apply to an approaching high-speed vehicle scenario. We addressed this gap by (a) providing an overview of the main hypotheses and predictions of different antipredator behavior models via a literature review, (b) exploring whether these models can generate quantitative predictions on escape distance when parameterized with empirical data from the literature, and (c) evaluating their sensitivity to vehicle approach speed using a simulation approach wherein we assessed model performance based on changes in effect size with variations in the slope of the flight initiation distance (FID) vs. approach speed relationship. The slope of the FID vs. approach speed relationship was then related back to three different behavioral rules animals may rely on to avoid approaching threats: the spatial, temporal, or delayed margin of safety. We used literature on birds for goals (b) and (c). Our review considered the following eight models: the economic escape model, Blumstein’s economic escape model, the optimal escape model, the perceptual limit hypothesis, the visual cue model, the flush early and avoid the rush (FEAR) hypothesis, the looming stimulus hypothesis, and the Bayesian model of escape behavior. We were able to generate quantitative predictions about escape distance with the last five models. However, we were only able to assess sensitivity to vehicle approach speed for the last three models. The FEAR hypothesis is most sensitive to high-speed vehicles when the species follows the spatial (FID remains constant as speed increases) and the temporal margin of safety (FID increases with an increase in speed) rules of escape. The looming stimulus effect hypothesis reached small to intermediate levels of sensitivity to high-speed vehicles when a species follows the delayed margin of safety (FID decreases with an increase in speed). The Bayesian optimal escape model reached intermediate levels of sensitivity to approach speed across all escape rules (spatial, temporal, delayed margins of safety) but only for larger (> 1 kg) species, but was not sensitive to speed for smaller species. Overall, no single antipredator behavior model could characterize all different types of escape responses relative to vehicle approach speed but some models showed some levels of sensitivity for certain rules of escape behavior. We derive some applied applications of our findings by suggesting the estimation of critical vehicle approach speeds for managing populations that are especially susceptible to road mortality. Overall, we recommend that new escape behavior models specifically tailored to high-speeds vehicles should be developed to better predict quantitatively the responses of animals to an increase in the frequency of cars, airplanes, drones, etc. they will face in the next decade.

54 ENVIRONMENTAL SCIENCES↗

Revisiting Newly Large Magellanic Cloud Age-gap Star Clusters

Recently, a noticeable number of new star clusters was identified in the outskirts of the Large Magellanic Cloud (LMC) populating the so-called star-cluster age gap, a space of time (∼4–12 Gyr) where the only known star cluster is up-to-date ESO 121-SC 03. We used Survey of the Magellanic Stellar History DR2 data sets, as well as those employed to identify these star-cluster candidates, to produce relatively deep color–magnitude diagrams (CMDs) of 17 out of 20 discovered age-gap star clusters with the aim of investigating them in detail. Our analysis relies on a thorough CMD cleaning procedure of the field-star contamination, which presents variations in its stellar density and astrophysical properties, such as luminosity and effective temperature, around the star-cluster fields. We built star-cluster CMDs from stars with membership probabilities assigned from the cleaning procedure. These CMDs and their respective spatial distribution maps favor the existence of LMC star field density fluctuations rather than age-gap star clusters, although a definitive assessment on them will be possible from further deeper photometry.

47 OTHER INSTRUMENTATION↗

Broadband X-ray ptychography using multi-wavelength algorithm

Ptychography is a rapidly developing scanning microscopy which is able to view the internal structures of samples at a high resolution beyond the illumination size. The achieved spatial resolution is theoretically dose-limited. A broadband source can provide much higher flux compared with a monochromatic source; however, it conflicts with the necessary coherence requirements of this coherent diffraction imaging technique. In this paper, a multi-wavelength reconstruction algorithm has been developed to deal with the broad bandwidth in ptychography. Compared with the latest development of mixed-state reconstruction approach, this multi-wavelength approach is more accurate in the physical model, and also considers the spot size variation as a function of energy due to the chromatic focusing optics. Therefore, this method has been proved in both simulation and experiment to significantly improve the reconstruction when the source bandwidth, illumination size and scan step size increase. It is worth mentioning that the accurate and detailed information of the energy spectrum for the incident beam is not required in advance for the proposed method. Further, we combine multi-wavelength and mixed-state approaches to jointly solve temporal and spatial partial coherence in ptychography so that it can handle various disadvantageous experimental effects. The significant relaxation in coherence requirements by our approaches allows the use of high-flux broadband X-ray sources for high-efficient and high-resolution ptychographic imaging.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Cathodoluminescence of Ultrathin Twisted Ge 1–x Sn x S van der Waals Nanoribbon Waveguides

Ultrathin van der Waals semiconductors have shown extraordinary optoelectronic and photonic properties. Propagating photonic modes make layered crystal waveguides attractive for photonic circuitry and for studying hybrid light-matter states. Accessing guided modes by conventional optics is challenging due to limited spatial resolution and poor out-of-plane far field coupling. Scanning near-field optical microscopy (SNOM) can overcome these issues and can characterize waveguide modes down to tens of nm resolution, albeit for planar samples or nanostructures with moderate height variations. Electron microscopy provides atomic-scale localization also for more complex geometries, and recent advances extended the accessible excitations from interband transitions to phonons. In this work, bottom-up synthesized layered semiconductor (Ge 1-x Sn x S) nanoribbons with axial twist and deep sub-wavelength thickness are demonstrated as a platform for realizing waveguide modes, and cathodoluminescence (CL) spectroscopy is introduced as a tool to characterize them. Combined experiments and simulations show the excitation of guided modes by the electron beam and their efficient detection via photons emitted in the ribbon plane, which enables measuring key properties such as the evanescent field into the vacuum cladding with nanometer resolution. The results identify van der Waals waveguides operating in the infrared and highlight an electron microscopy-based approach for probing complex-shaped nanophotonic structures.

36 MATERIALS SCIENCE↗

Programming twist angle and strain profiles in 2D materials

Moiré superlattices in twisted two-dimensional materials have generated tremendous excitement as a platform for achieving quantum properties on demand. However, the moiré pattern is highly sensitive to the interlayer atomic registry, and current assembly techniques suffer from imprecise control of the average twist angle, spatial inhomogeneity in the local twist angle, and distortions caused by random strain. We manipulated the moiré patterns in hetero- and homobilayers through in-plane bending of monolayer ribbons, using the tip of an atomic force microscope. This technique achieves continuous variation of twist angles with improved twist-angle homogeneity and reduced random strain, resulting in moiré patterns with tunable wavelength and ultralow disorder. Our results may enable detailed studies of ultralow-disorder moiré systems and the realization of precise strain-engineered devices.

Science & Technology - Other Topics↗

Seismic Characterization of the Blue Mountain Geothermal Field

Subsurface characterization is crucial for geothermal energy exploration and production. Yet hydrothermal reservoirs usually reside in highly fractured and faulted zones where accurate characterization is very challenging because of low signal-to-noise ratios of land seismic data and lack of coherent reflection signals. We perform an active-source seismic characterization for the Blue Mountain geothermal field in Nevada using active seismic data to reveal the elastic medium property complexity and fault distribution at this field. We first employ an unsupervised machine learning method to attenuate groundroll and near-surface guided-wave noise and enhance coherent reflection and scattering signals from noisy seismic data. We then build a smooth initial P-wave velocity model based on an existing magnetotellurics survey result, and use 3D first-arrival traveltime tomography to refine the initial velocity model. We then derive a set of elastic wave velocities and anisotropic parameters using elastic full-waveform inversion, and obtain PP and PS images using elastic reverse-time migration. We identify major faults by analyzing the variations of seismic velocities and anisotropy parameters, and reveal mid- to small-scale faults by applying a supervised machine learning method to the seismic migration images. Our characterization reveals complex velocity heterogeneities and anisotropies, as well as faults, with a high spatial resolution. These results can provide valuable information for optimal placement of future injection and production wells to increase geothermal energy production at the Blue Mountain geothermal power plant.

58 GEOSCIENCES↗

Data for Clumping Index Estimation With 30°-tilted Cameras in Row Crops: Evaluation of Methods and Segment Size Effects

The clumping index (CI) quantifies the spatial distribution of foliage elements and is essential for accurately estimating the plant area index (PAI), canopy radiative transfer, and photosynthesis. Traditionally, the finite-length averaging method (LX), the gap size distribution method (CC), and a combined approach of CC and LX (CLX) have been applied to instruments like TRAC and digital hemispherical photography to estimate CI. However, a comprehensive evaluation of these methods in row crops remains limited, especially regarding the influence of segment size on CI. Meanwhile, digital cameras offer a cost-effective and user-friendly solution for canopy measurements in row crops, yet their application in this context remains underexplored. In this study, we employed a new approach using a 30°-tilted digital camera to estimate CI in corn and soybean fields, applying the LX, CC, and CLX methods. We systematically assessed the performance of these three methods by combining field measurements in real-world fields with simulations using the LESS 3D radiative transfer model. Our results showed that CLX applied to the whole image and 45° segment offered accurate estimation of CI (bias within ±0.1, RMSE < 0.2) and PAI (bias within ±0.4, RMSE < 1) in real-world fields and LESS simulations. The accuracy of the LX method was highly sensitive to segment size, with the best performance observed at the 15° segment (PAI bias within ±0.4). In contrast, the CC method remained stable across different segment sizes, and its performance was generally comparable to that of LX, except at the 15° segment. Across view zenith angles, CI derived from CC generally showed a continuous increase, while those from LX and CLX followed a rising trend at small zenith angles but began to decline at 68°, likely due to an increasing proportion of no-gap segments. Seasonally, LX tended to show decreasing CI during early growth stages but increased as the canopy matured, whereas CC and CLX showed gradually increasing CI before plateauing at peak PAI. The 30°-tilted camera effectively captured CI variations across different angles and growth stages, making it a practical and robust instrument for row crop canopy structure analysis. Applying these CI methods to digital cameras offers a low-cost and accessible CI estimation alternative, improving canopy structure monitoring accuracy in row crops.

Modeling↗

Determining Optimal Magnetometer Configuration on MAGIS-100

Long-baseline atom interferometers such as the Matter-wave Atomic Gradiometer Interferometric Sensor (MAGIS-100) require stringent control and continuous characterization of background magnetic fields and spatial gradients to prevent systemic phase shifts that mimic ultralight dark matter or gravitational wave signatures. Because direct sensor placement within the ultra-high vacuum beam pipe is infeasible, in-situ magnetic field monitoring relies on external sensor arrays situated in the surrounding annular region. This work demonstrates a field reconstruction framework for a 5.3-meter MAGIS-100 modular section using finite-element Opera simulations. Transverse magnetic fields are expanded using a cylindrical multipole framework as informed by Fermilab’s Muon g-2 experiment, with magnetometer array configurations optimized via Fisher information matrix D-optimality. Inverting external sensor readings through a Gauss-Newton scheme recovers interior tube fields across distinct axial positions. In the discontinuity-averse uniform region (slice pair P4), the model achieves sub-noise-floor performance with a cross-validated root-mean-square error (RMSE) of $6.7227 \times 10^{-4}\text{ A/m}$ ($0.845\times$ sensor noise floor) and an interior field coefficient of variation of $1.71\%$. An elbow criterion in the Fisher bounds establishes $n_{\text{max}} = 2$ as the optimal multipole truncation order to prevent noise amplification from over-parameterization, with $n_{\text{max}} = 3$ (sextupole) order chosen for analysis to demonstrate further complexity and cross-pair comparison. Furthermore, analytical differentiation of the fitted multipole coefficients yields dense spatial maps of the transverse Jacobian gradient matrix $\nabla \mathbf{H}$ along with propagated $1\sigma$ uncertainty bounds across the beam region ($r \le 2.75\text{ in}$). This operational framework confirms that external magnetometer arrays can reliably monitor magnetic field uniformity and spatial gradients along the 100-meter flight path given appropriate sampling for any complexity order.

Appleby, Darwin [William Rainey Harper Coll.] (ORC↗

Determining Optimal Magnetometer Configuration on MAGIS-100

Long-baseline atom interferometers such as the Matter-wave Atomic Gradiometer Interferometric Sensor (MAGIS-100) require stringent control and continuous characterization of background magnetic fields and spatial gradients to prevent systemic phase shifts that mimic ultralight dark matter or gravitational wave signatures. Because direct sensor placement within the ultra-high vacuum beam pipe is infeasible, in-situ magnetic field monitoring relies on external sensor arrays situated in the surrounding annular region. This work demonstrates a field reconstruction framework for a 5.3-meter MAGIS-100 modular section using finite-element Opera simulations. Transverse magnetic fields are expanded using a cylindrical multipole framework as informed by Fermilab’s Muon g-2 experiment, with magnetometer array configurations optimized via Fisher information matrix D-optimality. Inverting external sensor readings through a Gauss-Newton scheme recovers interior tube fields across distinct axial positions. In the discontinuity-averse uniform region (slice pair P4), the model achieves sub-noise-floor performance with a cross-validated root-mean-square error (RMSE) of $6.7227 \times 10^{-4}\text{ A/m}$ ($0.845\times$ sensor noise floor) and an interior field coefficient of variation of $1.71\%$. An elbow criterion in the Fisher bounds establishes $n_{\text{max}} = 2$ as the optimal multipole truncation order to prevent noise amplification from over-parameterization, with $n_{\text{max}} = 3$ (sextupole) order chosen for analysis to demonstrate further complexity and cross-pair comparison. Furthermore, analytical differentiation of the fitted multipole coefficients yields dense spatial maps of the transverse Jacobian gradient matrix $\nabla \mathbf{H}$ along with propagated $1\sigma$ uncertainty bounds across the beam region ($r \le 2.75\text{ in}$). This operational framework confirms that external magnetometer arrays can reliably monitor magnetic field uniformity and spatial gradients along the 100-meter flight path given appropriate sampling for any complexity order.

Appleby, Darwin [William Rainey Harper Coll.] (ORC↗

In-Situ Magnetic Field Reconstruction in the MAGIS-100 Experiment

Long-baseline atom interferometers such as the Matter-wave Atomic Gradiometer Interferometric Sensor (MAGIS-100) require stringent control and continuous characterization of background magnetic fields and spatial gradients to prevent systemic phase shifts that mimic ultralight dark matter or gravitational wave signatures. Because direct sensor placement within the ultra-high vacuum beam pipe is infeasible, in-situ magnetic field monitoring relies on external sensor arrays situated in the surrounding annular region. This work demonstrates a field reconstruction framework for a 5.3-meter MAGIS-100 modular section using finite-element Opera simulations. Transverse magnetic fields are expanded using a cylindrical multipole framework as informed by Fermilab’s Muon g-2 experiment, with magnetometer array configurations optimized via Fisher information matrix D-optimality. Inverting external sensor readings through a Gauss-Newton scheme recovers interior tube fields across distinct axial positions. In the discontinuity-averse uniform region (slice pair P4), the model achieves sub-noise-floor performance with a cross-validated root-mean-square error (RMSE) of $6.7227 \times 10^{-4}\text{ A/m}$ ($0.845\times$ sensor noise floor) and an interior field coefficient of variation of $1.71\%$. An elbow criterion in the Fisher bounds establishes $n_{\text{max}} = 2$ as the optimal multipole truncation order to prevent noise amplification from over-parameterization, with $n_{\text{max}} = 3$ (sextupole) order chosen for analysis to demonstrate further complexity and cross-pair comparison. Furthermore, analytical differentiation of the fitted multipole coefficients yields dense spatial maps of the transverse Jacobian gradient matrix $\nabla \mathbf{H}$ along with propagated $1\sigma$ uncertainty bounds across the beam region ($r \le 2.75\text{ in}$). This operational framework confirms that external magnetometer arrays can reliably monitor magnetic field uniformity and spatial gradients along the 100-meter flight path given appropriate sampling for any complexity order.

Appleby, Darwin [William Rainey Harper Coll.; Ferm↗

Collaborative Research Activities of the Arase and Van Allen Probes

This paper presents the highlights of joint observations of the inner magnetosphere by the Arase spacecraft, the Van Allen Probes spacecraft, and ground-based experiments integrated into spacecraft programs. The concurrent operation of the two missions in 2017–2019 facilitated the separation of the spatial and temporal structures of dynamic phenomena occurring in the inner magnetosphere. Because the orbital inclination angle of Arase is larger than that of Van Allen Probes, Arase collected observations at higher L-shells up to L ~ 10. After March 2017, similar variations in plasma and waves were detected by Van Allen Probes and Arase. We describe plasma wave observations at longitudinally separated locations in space and geomagnetically-conjugate locations in space and on the ground. The results of instrument intercalibrations between the two missions are also presented. Arase continued its normal operation after the scientific operation of Van Allen Probes completed in October 2019. The combined Van Allen Probes (2012-2019) and Arase (2017-present) observations will cover a full solar cycle. This will be the first comprehensive long-term observation of the inner magnetosphere and radiation belts.

97 MATHEMATICS AND COMPUTING↗

Macroscale property assessment and indentation characteristics of thick section friction stir welded AA 5083

The spatial gradients in microstructure have been proven to be effective in optimizing the performance of components, and several techniques have been developed to achieve this microstructure. Nevertheless, the local microstructural modification methods inevitably result in the formation of gradient microstructure leading to a variation in the property. Herein this work systematically investigates the effect of gradient microstructure formed during thick section friction stir weld Al5083 alloy on its mechanical properties. A novel macro-indentation technique, profilometer-based indentation plastometry (PIP), is utilized to capture the variation in the mechanical properties in the feedstock (rolled plate) and weld region. The feedstock exhibited a gradient microstructure owing to different stress states during rolling. Additionally, the stirring of the tool resulted in a complex material flow pattern producing a microstructure gradient in the weld region. The aspect ratio of the grains was identified as the primary factor causing variation in indentation response in the feedstock. In contrast, variation in the grain size in the weld region resulted in property variation. Overall, the stir zone has a lower yield strength (158±4MPa) than the base material (173±3MPa). In addition, microstructure heterogeneity in the stir zone resulted in lower elongation than the base material.

36 MATERIALS SCIENCE↗

Algorithms for coordinate reconstruction in position-sensitive virtual Frisch-grid detectors

Arrays of position-sensitive virtual Frisch-grid (VFG) CdZnTe (CZT) detectors provide a cost-effective solution for integrating large-area arrays for gamma-ray imaging and spectroscopy. These detectors employ high-aspect ratio CZT crystals (bars) with thicknesses up to 50 mm and cross-sections of up to 10 × 10 mm 2 . Despite the long drift distances of charge carriers in such crystals, the detectors have demonstrated excellent performance, achieving energy resolutions better than 1 % full width at half maximum (FWHM) at 662 keV and 3D position resolutions finer than 1 mm. The high spatial resolution is a critical feature of these detectors, as it enables correction of response non-uniformities caused by crystal defects, which remain present even in the highest-quality CZT material. Dislocations and dislocation walls are the primary defects responsible for variations in charge carrier losses as they drift from the interaction points toward the charge-collecting electrodes. The mechanism by which these defects affect carrier transport is generally well understood. Dislocations and sub-grain boundaries act as sinks for carrier-trapping centers, primarily impurities and secondary phases such as tellurium inclusions and precipitates. Here, these regions exhibit significantly higher carrier-trapping rates, leading to variations in the μτ-products. Because the locations of these micron-sized regions are fixed within the detector volume, fluctuations in the total collected charge arise from the random distribution of interaction sites. This results in non-uniform detector responses and degradation of energy resolution. However, by measuring the interaction-site locations with sufficient precision, charge-loss variations can be accurately corrected, allowing recovery of nearly intrinsic energy resolution.

47 OTHER INSTRUMENTATION↗

Integrated parameter and process learning for hydrologic and biogeochemical modules in Earth System Models

Focus area: Primary focal area #2; secondary focal area #3: Learning about parameters and processes of land surface hydrologic and biogeochemical models in Earth System models by integrating machine learning, physics, and big data. Science challenges: How do we maximally leverage big-data observations to improve hydrobiogeochemical process description and parameterization so that such modules more realistically capture hydrologic and vegetation responses and feedbacks under the future climate? For example, how can we leverage physics, limited observations of vegetation and streamflow to better estimate evapotranspiration, and, relatedly, net primary productivity, especially for drought areas? Vegetation plays a critical role in regional and global water cycles; however, existing vegetation models have failed to predict vegetation response to droughts (McDowell & Xu, 2017) , arctic greening (Keenan & Riley, 2018) , and critical transitions between forest and savanna (Hirota et al., 2011) . These studies suggest that when we build process-based models (PBM) parameterized from regional and global plant traits, we tend to poorly describe plant adaptation and local-scale competition processes. The models and their associated parameters assigned for different regions in the world are not capturing essential heterogeneity in vegetation responses at finer spatial scales. Many parameters of the land surface models control hydrology and vegetation dynamics at the same time. The heterogeneity in vegetation response is a function of (i) plant type, (ii) plant size, (iii) competition and succession, (iv) environmental controls, and (v) local variations due to the unique ecological community that are very difficult to describe (e.g., the size of gaps resulting from fire that facilitated the coexistence of pioneering species). In the demographic models, only factors (i) and (iv) were captured, and plant types were generally described only by leaf phenology and climate zones. With current demographic models, we generally consider more traits to define plant types (i) and calibrate these traits to consider factors (ii), (iii) and (iv); however, it is substantially challenging to scale to regional and global simulations due to trait variations across space (Ali et al., 2016). Moreover, it has been noted that hillslope processes, including ridge-to-valley flow and sunny vs. shady slopes are primary organizers of water, energy, and vegetation (Clark et al., 2015; Fan et al., 2019) . Although gradual improvements in the hydrologic model component in earth system models may reduce this error (at a remarkably slow pace), the long-term, gradual impact of hydrology on plant traits are not well captured. Recent work showed that the hydrologic controls exerted by groundwater and lateral flow are primary regulators of rooting depth (Fan et al., 2017) . Such hydrologic controls have seldom been reflected in vegetation model parameterizations.

54 ENVIRONMENTAL SCIENCES↗

A Macroalgal Cultivation Modeling System (MACMODS): Evaluating the Role of Physical-Biological Coupling on Nutrients and Farm Yield

Offshore aquaculture has the potential to expand the macroalgal industry. However, moving into deeper waters requires suspended structures that will present novel farm-environment interactions. Here, we present a computational modeling framework, the Macroalgal Cultivation Modeling System (MACMODS), to explore within-farm modifications to light, seawater flow, and nutrient fields across time and space scales relevant to macroalgae. A regional ocean model informs the site-specific setting, the Santa Barbara Channel in the Southern California Bight. A fine-scale hydrodynamic model predicts modified flows and turbulent mixing within the farm. A spatially resolved macroalgal growth model, parameterized for giant kelp, Macrocystis pyrifera , predicts kelp biomass. Key findings from model integration are that regional ocean conditions set overall farm performance, while fine-scale within-farm circulation and nutrient delivery are important to resolve variation in within-farm macroalgal performance. Therefore, we conclude that models resolving within-farm dynamics can provide benefit to farmers with insight on how farm design and regional ocean conditions interact to influence overall yield. Here, the presence of repeating longlines aligned with the mean current generate flow diversions around the farm as well as attached Langmuir circulations and increased turbulence intensity. These flow-induced phenomena lead to less biomass in the interior portion of the farm relative to the edges. We also find that there is an effluent “footprint” that extends as much as 20 km beyond the farm. In this regard, MACMODS can be used to not only evaluate farm design and cultivation practices that maximize yield but also explore interactions between the farm and ecosystem in order to minimize impacts.

54 ENVIRONMENTAL SCIENCES↗

The Peculiar Variable X-Ray Spectrum of the Active Galactic Nucleus PKS 2005–489

PKS 2005-489 is a well-known, bright southern BL Lac object that has been detected up to TeV energies. In a low-flux state it exhibits the expected multiwavelength double-peaked spectrum in the radio- γ -ray band. The high-flux state shows extreme flux variations in the X-ray band with a hardening as well as a peculiar curved feature in the spectrum. Thus far, PKS 2005-489 is the only source to exhibit such a feature. To study the X-ray variability further, we obtained the first hard X-ray spectrum of the source with the Nuclear Spectroscopic Telescope Array. We compare quasi-simultaneous radio, optical, UV, soft and hard X-ray, and γ -ray data of PKS 2005-489 to archival data in order to study its broadband behavior. We find a very consistent quiet state in the spectral energy distribution, with little variation in spectral shape or flux between the 2012 and 2020 data. A possible explanation for the peculiar X-ray spectrum in the flaring state is an additional component in the jet, possibly accelerated via magnetic reconnection, that is not co-spatial to the low-flux state emission region.

79 ASTRONOMY AND ASTROPHYSICS↗

Codisposal Waste Package Loading Options for DOE SNF and HLW PPT

The U.S. Department of Energy (DOE) is responsible for managing spent nuclear fuel (SNF) that is currently in, or will in the future come into, its possession. DOE must continue to safely store that SNF, transport it to an interim storage site or a repository, and dispose of it. These fuels come from a wide range of reactor types with various cladding materials and enrichments. Many of these reactors, now decommissioned, had unique design features, such as core configuration, fuel element and assembly geometry, moderator and coolant materials, operational characteristics, and neutron spatial and spectral properties, resulting in a large diversity of reactor and fuel designs. Because of the wide variety and conditions of SNF, a robust DOE Standard Canister was proposed that would confine radionuclides and preclude moderator. The DOE Standard Canister had four variations: 3.05-meter (10-foot) or 4.57-meter (15-foot) length, and 45.7-cm (18-inch) or 61.0-cm (24-inch) diameter. For ultimate disposal in the Yucca Mountain Repository, these canisters were to be grouped with 61.0-cm (24-inch) diameter high level waste (HLW) canisters in a 2.13-meter (84-inch) diameter co-disposal waste package. The smaller 45.7-cm (18-inch) diameter DOE Standard Canister could be placed in the middle of five HLW canisters. The larger 61.0-cm (24-inch) diameter DOE Standard Canister would take the place of one of the five HLW canisters on the outer ring in the co-disposal waste package. No DOE Standard Canisters have been loaded. A preliminary evaluation has estimated the number of elements of a fuel type that can fit into the different sizes of the DOE Standard Canister, but no definitive loading configuration has been selected. Changing the loading configuration could impact the number of loadable DOE Standard Canisters and the number of co-disposal waste packages needed for eventual disposition. This paper conveys the ranges of DOE Standard Canisters and HLW canisters that may be produced under certain conditions. It also examines the differences in the estimated number of co-disposal waste packages produced for eventual disposal when using different loading strategies in the DOE Standard Canister for Advanced Test Reactor (ATR), Peach Bottom, and High Flux Isotope Reactor (HFIR) SNF. Changing the loading configurations of ATR, Peach Bottom, and HFIR SNF slightly impacted the number of co-disposal waste packages that may be needed for ultimate disposal. The change in loading configuration was more impactful when a different canister was used, as opposed to varying the number of elements that could fit inside the same size canister. In one case, a reduction of co-disposal waste packages could be achieved by allowing mixing of short HLW canisters with long DOE Standard Canisters. The main conclusion from this analysis is that the ratio between HLW canisters and DOE Standard Canisters will drive the total number of co-disposal waste packages. If too many HLW canisters (i.e., more than five times the number of 18-inch DOE standard canisters) or DOE Standard Canisters are produced, some co-disposal waste packages may not have all positions filled. A co-disposal waste package may be filled with all HLW with no DOE Standard Canister, or a co-disposal waste package could be filled with a single DOE Standard Canister. A ratio that does not closely align to optimum could allow for the design of waste packages that hold just HLW canisters or just DOE SNF canisters.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Co-Disposal Waste Package Loading Options for DOE SNF and HLW - 20331

The U.S. Department of Energy (DOE) is responsible for managing spent nuclear fuel (SNF) that is currently in, or will in the future come into, its possession. DOE must continue to safely store that SNF, transport it to an interim storage site or a repository, and dispose of it. These fuels come from a wide range of reactor types with various cladding materials and enrichments. Many of these reactors, now decommissioned, had unique design features, such as core configuration, fuel element and assembly geometry, moderator and coolant materials, operational characteristics, and neutron spatial and spectral properties, resulting in a large diversity of reactor and fuel designs. Because of the wide variety and conditions of SNF, a robust DOE Standard Canister was proposed that would confine radionuclides and preclude moderator. The DOE Standard Canister had four variations: 3.05-meter (10-foot) or 4.57-meter (15-foot) length, and 45.7-cm (18-inch) or 61.0-cm (24-inch) diameter. For ultimate disposal in the Yucca Mountain Repository, these canisters were to be grouped with 61.0-cm (24-inch) diameter high level waste (HLW) canisters in a 2.13-meter (84-inch) diameter co-disposal waste package. The smaller 45.7-cm (18-inch) diameter DOE Standard Canister could be placed in the middle of five HLW canisters. The larger 61.0-cm (24-inch) diameter DOE Standard Canister would take the place of one of the five HLW canisters on the outer ring in the co-disposal waste package. No DOE Standard Canisters have been loaded. A preliminary evaluation has estimated the number of elements of a fuel type that can fit into the different sizes of the DOE Standard Canister, but no definitive loading configuration has been selected. Changing the loading configuration could impact the number of loadable DOE Standard Canisters and the number of co-disposal waste packages needed for eventual disposition. This paper conveys the ranges of DOE Standard Canisters and HLW canisters that may be produced under certain conditions. It also examines the differences in the estimated number of co-disposal waste packages produced for eventual disposal when using different loading strategies in the DOE Standard Canister for Advanced Test Reactor (ATR), Peach Bottom, and High Flux Isotope Reactor (HFIR) SNF. Changing the loading configurations of ATR, Peach Bottom, and HFIR SNF slightly impacted the number of co-disposal waste packages that may be needed for ultimate disposal. The change in loading configuration was more impactful when a different canister was used, as opposed to varying the number of elements that could fit inside the same size canister. In one case, a reduction of co-disposal waste packages could be achieved by allowing mixing of short HLW canisters with long DOE Standard Canisters. The main conclusion from this analysis is that the ratio between HLW canisters and DOE Standard Canisters will drive the total number of co-disposal waste packages. If too many HLW canisters (i.e., more than five times the number of 18-inch DOE standard canisters) or DOE Standard Canisters are produced, some co-disposal waste packages may not have all positions filled. A co-disposal waste package may be filled with all HLW with no DOE Standard Canister, or a co-disposal waste package could be filled with a single DOE Standard Canister. A ratio that does not closely align to optimum could allow for the design of waste packages that hold just HLW canisters or just DOE SNF canisters. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗