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At least 1,621 records · Page 90

Wind-Tunnel Overpressure Signatures From a Low-Boom HSCT Concept With Aft-Fuselage-Mounted Engines

A 1:300 scale wind-tunnel model of a conceptual High-Speed Civil Transport (HSCT) designed to generate a shaped, low-boom pressure signature on the ground was tested to obtain sonic-boom pressure signatures in the Langley Research Center Unitary Plan Wind Tunnel at a Mach number of 1.8 and a separation distance of about two body lengths or four wing-spans from the model. Two sets of engine nacelles representing two levels of engine technology were used on the model to determine the effects of increased nacelle volume. Pressure signatures were measured for (model lift)/(design lift) ratios of 0.5, 0.63, 0.75, and 1.0 so that the effect of lift on the pressure signature could be determined. The results of these tests were analyzed and used to discuss the agreement between experimental data and design expectations.

Mack, Robert J.↗

Observational Evidence of How Magnetofluid Turbulence in the Solar Wind Dissipates

The solar wind appears to be a fully developed turbulent magnetofluid. As this magnetofluid expands into the heliosphere, it cools significantly less rapidly than would be expected of an adiabatically expanding gas. The evolution of the temperature with distance is roughly what would be expected if the turbulence dissipated by heating the thermal plasma. Several physical mechanisms have been proposed, including resonance absorption of waves and Landau damping. Recently, high-time resolution magnetic field data from the four Cluster spacecraft have illustrated damping of the fluctuations out to the electron inertial scale. Use of the wave telescope/k-filtering technique during two intervals of busrt mode data suggests that dissipation of the fluctuations is due to Landau damping, first on protons, then on electrons.

Goldstein, Melvyn L.↗

Machine Learning for Daily Forecasts of Arctic Sea Ice Motion: An Attribution Assessment of Model Predictive Skill

Physics-based simulations of Arctic sea ice are highly complex, involving transport between different phases, length scales, and time scales. Resultantly, numerical simulations of sea ice dynamics have a high computational cost and model uncertainty. We employ data-driven machine learning (ML) to make predictions of sea ice motion. The ML models are built to predict present-day sea ice velocity given present-day wind velocity and previous-day sea ice concentration and velocity. Models are trained using reanalysis winds and satellite-derived sea ice properties. We compare the predictions of three different models: persistence (PS), linear regression (LR), and a convolutional neural network (CNN). We quantify the spatiotemporal variability of the correlation between observations and the statistical model predictions. Additionally, we analyze model performance in comparison to variability in properties related to ice motion (wind velocity, ice velocity, ice concentration, distance from coast, bathymetric depth) to understand the processes related to decreases in model performance. Results indicate that a CNN makes skillful predictions of daily sea ice velocity with a correlation up to 0.81 between predicted and observed sea ice velocity, while the LR and PS implementations exhibit correlations of 0.78 and 0.69, respectively. The correlation varies spatially and seasonally: lower values occur in shallow coastal regions and during times of minimum sea ice extent. LR parameter analysis indicates that wind velocity plays the largest role in predicting sea ice velocity on 1-day time scales, particularly in the central Arctic. Regions where wind velocity has the largest LR parameter are regions where the CNN has higher predictive skill than the LR.

54 ENVIRONMENTAL SCIENCES↗

Transmission electron microscopy characterization of the fuel-cladding chemical interactions in HT9 cladded U-10Zr fuel

Fuel cladding chemical interaction (FCCI) is a key phenomenon needs to be better understood to establish the design basis for U-10Zr metallic fuel performance. Characterizing the microstructure and chemical composition of FCCI at micron and sub-micron scale is critically important toward a more mechanistic understanding of FCCI phenomenon and its potential effects on cladding integrity and metallic fuel performance. This paper, by using transmission electron microscopy, investigated the FCCI region in HT9 cladded U-10Zr fuel irradiated to 5.7% FIMA burnup at a peak inner cladding temperature of 615 °C in Fast Flux Test Facility (FFTF). Four distinct layers are identified in the FCCI region. The migration of Fe into the fuel side leads to the formation of several U-Zr-Fe ternary phases, including ?-Fe0.5Zr0.32U0.18, e-Fe0.3Zr0.4U0.3, and ?-Fe0.06Zr0.23U0.71, mingled with UFe2, U6Fe, and U phase at various Fe penetration depth up to ~ 150 µm. On the cladding side, grain coarsening and significant lanthanides infiltration along grain boundaries are observed. Laves phase, (Fe,Cr)2(Mo,W), which typically does not exist in fresh HT9, is identified in a wide radial range in the cladding. The typical HT9 martensitic lath structure and pre-existing M23C6 precipitates disappear, partially or completely, depending on the radial distance from the fuel-cladding interface. Those microstructural and compositional changes could cause mechanical degradation in the HT9 cladding. The present characterization results will improve the understanding of FCCI phenomenon and facilitate the development of microstructure-informed FCCI modeling for metallic fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The large scale structure of the solar wind

The solar wind structure is reviewed based on experimental space measurements acquired over approximately the last decade. The character of the interplanetary medium is considered from the viewpoint of the temporal behavior of the solar wind over increasingly longer time intervals, the average properties of the various solar wind parameters and their interrelationships. A brief discussion is included of interplanetary-terrestrial relationships and the expected effects of heliographic latitude and radial distance.

Wolfe, J. H.↗

Geospatial coherence of surface-atmosphere fluxes in the upper Great Lakes region

Surface-atmosphere fluxes are known to vary at multiple time scales, but uncertainty is high as to how fluxes change spatially within regions. With an increase in the number of eddy covariance towers, we are now able to examine the geospatial coherence of ecosystem fluxes, using time-series correlation. Eighteen sites from Michigan and Wisconsin were used in this study, ranging from 100 m to 600 km apart. Surface-atmosphere fluxes from a six-month period were used to quantify spatial coherence on a pair-wise basis. Using geospatial statistics, carbon and sensible heat (H) fluxes were found to be 95% correlated directly outside of their flux footprint and 56% correlated up to a distance of ~35 km. Latent (LE) and momentum (τ) fluxes were less correlated, 83% directly outside of their flux footprint and 40% at a distance of ~130 km albeit, at a much larger spatial distance than for the carbon and sensible heat fluxes. All fluxes showed strong spectral resonance at diel and seasonal timescales, with 1-, 2- and 3-month periods being common modes of variability among H, LE, and τ fluxes. Results based on Empirical Orthogonal Function show distinct transitions of net ecosystem exchange from fall to winter before photosynthesis or respiration while H and τ do not exhibit coherent trends. Here, this work demonstrates the potential of quantifying geospatial coherence of surface-atmosphere fluxes in the Midwestern United States, with the ability to predict fluxes beyond the spatial limit of a single flux tower footprint. Ultimately, expanding the flux measurements to larger scales would allow better spatial scaling of terrestrial surface-atmosphere fluxes between tower footprint and modeling or remote sensing scales.

54 ENVIRONMENTAL SCIENCES↗

On the correlation between plastic strain and misorientation in polycrystalline body-centered-cubic microstructures with an emphasis on the grain size, loading history, and crystallographic orientation

In this work, the correlation between plastic strain and crystallographic misorientation, grain size, grain orientation, distance from grain boundary, and loading history were investigated experimentally and numerically for body-centered-cubic (BCC) polycrystalline microstructures based on a misorientation deviation (MD) approach. Nine monotonic tensile experiments were performed on two BCC titanium alloys inside a scanning electron microscope (SEM). The influence of reference orientation was explored both at the grain scale and at the mesoscale using electron backscattered diffraction (EBSD). The correlation between global plastic strain and the MD was quantified. The tendency for orientation change was quantified as a function of plastic strain and grain orientation for three crystallographic orientations (i.e., [100], [110], and [111]) with respect to tensile direction. The subpopulation of small grains exhibited a lower level of misorientation dispersion compared with larger grains, and this discrepancy became more pronounced at higher strains. An empirical equation was proposed to estimate the level of misorientation dispersion for individual grains as a function of grain size and global plastic strain level. Two interrupted in-situ SEM experiments were performed, and this resulted in a significantly increased misorientation compared with uninterrupted tests performed to similar plastic strain levels.

36 MATERIALS SCIENCE↗

Network analysis of earthquake ground motion spatial correlation: a case study with the San Jacinto seismic nodal array

SUMMARY The spatial correlation of earthquake ground motion intensity can be measured from strong motion data; however, the data used in past studies is sparsely sampled in space, and only the interstation distance was considered as a correlation variable. These limitations mean that we have only weak constraints on the true correlation structure of ground motion and that potentially important aspects of spatial correlation are unconstrained. In this study, we combine a large-N seismic array and graph analytics to explore this issue at a local scale using small local and regional earthquakes. Our result suggests site conditions, and how they interact with the incident seismic wavefield, strongly condition the spatial correlation of ground motion. Future progress in characterizing ground motion spatial variability will require dense wavefield measurements, either through nodal deployments, or perhaps distributed acoustic sensing measurements, of seismic wavefields. Aftershock sequences of major earthquakes would provide particularly data-rich targets of opportunity.

58 GEOSCIENCES↗

The transition from resistance to acceptance: Managing a marine invasive species in a changing world

Abstract Marine invasive species can transform coastal ecosystems, yet mitigating their effects can be difficult, and even impractical. Often, marine invasive species are managed at poorly matched spatial scales, and at the same time, rates of spread and establishment are increasing under climate change and can outpace resources available for population suppression. These circumstances challenge traditional conservation goals of maintaining a historic environmental state, especially for a species like the European green crab ( Carcinus maenas ), a formidable invader with few examples of successful long‐term removal programs. A management paradigm where decision alternatives include resisting or accepting a new ecological trajectory may be needed. We apply mathematical concepts from decision theory to develop a quantitative framework for navigating management decisions in this new resist‐accept paradigm. We develop a model of European green crab growth, removal and colonization, and we find optimal levels of removal effort that minimize both ecological change and removal cost. We establish a benchmark of colonization pressure at which green crab density becomes decoupled from a decision maker's actions, such that population control can no longer shape the invasion trajectory. For informing the decision boundary between resistance and acceptance, our results highlight that a decision maker's understanding of how removal cost scales with removal effort is more important than understanding the density‐impact relationship. We show that assuming stationary system dynamics can result in sub‐optimal levels of species removal effort, highlighting the importance of developing anticipatory management strategies by accounting for non‐stationary dynamics. Policy implications . For marine invasive species that can disperse across long distances and recolonize rapidly after removal, the focus of conservation policy should shift away from understanding how to resist change to understanding when to stop resisting change. Navigating this decision problem involves trade‐offs among competing objectives, highlighting the need for structured approaches to elicit objective weights that reflect the values of the decision maker. For natural resource managers facing possible ecosystem transformation, this decision framework can enable proactive and strategic decisions made under uncertainty in a changing world.

Keller, Abigail G. [Department of Environment Scie↗

Geographic patterns and determinants of antibiotic resistomes in coastal sediments across complex ecological gradients

Coastal areas are highly influenced by terrestrial runoffs and anthropogenic disturbances, commonly leading to ecological gradients from bay, nearshore, to offshore areas. Although the occurrence and distribution of sediment antibiotic resistome are explored in various coastal environments, little information is available regarding geographic patterns and determinants of coastal sediment antibiotic resistomes across ecological gradients at the regional scale. Here, using high-throughput quantitative PCR, we investigated the geographic patterns of 285 antibiotic resistance genes (ARGs) in coastal sediments across a ~ 200 km scale in the East China Sea. Sediment bacterial communities and physicochemical properties were characterized to identify the determinants of sediments antibiotic resistome. Higher richness and abundance of ARGs were detected in the bay samples compared with those in nearshore and offshore samples, and significant negative correlations between the richness and/or abundance of ARGs and the distance to coastline (DTC) were identified, whereas different types of ARGs showed inconsistency in their relationships with DTC. The composition of antibiotic resistome showed significant correlations with nutrition-related variables (including NH 4 + -N, NO 3 − -N, and total phosphorus) and metals/metalloid (including As, Cu, Ni, and Zn), suggesting that terrestrial disturbances largely shape the antibiotic resistome. The Bipartite network showed strong associations between ARGs and mobile genetic elements (MGEs), and Partial Least Squares Path Modeling further revealed that terrestrial disturbance strength (as indicated by DTC) directly affected abiotic environmental conditions and bacterial community composition, and indirectly affected antibiotic resistome via MGEs. These findings provide insights into regional variability of sediment antibiotic resistome and its shaping path across complex ecological gradients, highlighting terrestrial disturbances as determinative forces in shaping coastal sediment antibiotic resistomes.

Xiong, Shangling↗

Deep Learning and Photogrammetric Reconstruction for Automated Crack Detection and Dimensional Measurement in Mining Operations

Surface crack detection and dimensional measurement at active mining sites present significant safety and operational challenges. Manual inspection methods are labor-intensive, spatially incomplete, and expose personnel to hazardous environments, while existing automated approaches have been developed primarily for concrete civil infrastructure and have not been validated on the complex, variable surfaces characteristic of mining environments. This dissertation presents an automated pipeline that integrates deep learning semantic segmentation with Structure-from-Motion photogrammetry to detect surface cracks and measure their aperture, length, and vertical displacement from standard RGB imagery acquired during routine Uncrewed Aerial Vehicle (UAV) survey operations, without requiring additional sensor hardware or manual measurement. The pipeline combines a U-Net architecture with an EfficientNet-B0 encoder, pretrained on the SDNET2018 concrete crack dataset and fine-tuned on a mining-specific dataset spanning laboratory concrete specimens, coal refuse impoundment embankments, and post-blast limestone quarry benches. Photogrammetric reconstruction is performed using COLMAP Structure-from-Motion and Multi-View Stereo, with crack segmentation masks projected into the reconstructed point cloud to enable three-dimensional vertical displacement measurement through local plane fitting and bimodal surface detection. The pipeline was validated across 36 controlled laboratory specimens at three imaging distances and four vertical displacement levels, achieving aperture measurement RMSE of 0.047 cm and R² of 0.954, and vertical displacement RMSE of 0.140 cm and R² of 0.966, against independent caliper measurements. Field application at a coal refuse impoundment in southwestern Pennsylvania detected 71 crack components across the embankment crest, with a dominant longitudinal crack exhibiting aperture values reaching 28 cm and a 95th percentile vertical displacement of 35.53 cm, consistent in magnitude and spatial distribution with simultaneously acquired LiDAR-derived estimates. Application across four post-blast limestone quarry bench datasets in California successfully characterized blast-induced fracture networks at ground sampling distances ranging from 0.59 to 1.23 cm/pixel, with detected crack geometries physically consistent with observable surface conditions at each site. The results demonstrate that deep learning-based crack detection and photogrammetric measurement can be integrated into routine UAV inspection workflows at mining sites, providing repeatable, scalable, and quantitative crack characterization across surface types, crack scales, and displacement magnitudes not previously addressed in the literature. The pipeline requires no dedicated surveying equipment beyond the UAV platforms already deployed at mine sites for survey and monitoring purposes, supporting practical adoption within existing operational workflows.

Crack detection, Dimensional Measurement↗

Fluctuating loads measured on an over-the-wing supersonic jet model

Fluctuating pressure loads on the wing and flap of an over-the-wing supersonic jet model were measured. The model was tested statically and at a Mach number of 0.1 in a small free jet to simulate forward speed. Test parameters were impingement angle, nozzle height, and flap deflection. Load levels as high as 170 db were measured at the center of the impingement region during static tests. Forward speed reduced the loading about 1 db. Load level increased with increasing impingement angle and decreasing nozzle height above the wing. The effect of flap deflection was small. When scaled to full-size aircraft conditions, the maximum amplitude of the one-third-octave fluctuating pressure spectra was about 154 db at about 160 Hz. Maximum load level occurred near the intersection of the nozzle center line with the impinged surface. Downstream of the maximum the fluctuating pressure is inversely proportional to the distance downstream of the nozzle.

Willis, C. M.↗

Generation of Martian chaos and channels by debris flows

A debris flow mechanism is proposed to account for the formation of chaos and the large channels debouching into Crysae Planitia from the adjacent southern uplands of Mars. Based on considerations of the juxtaposition of individual channel environments, the morphological assemblages within each environment and flow dynamics, it is suggested that the debris flows were triggered by the large-scale failure of subsurface sediments, possibly initiated by a seismic event. During the initial, slow-moving phase of the flow, the debris would have formed gently sinuous channels with multiple side-wall slumps, grooves and ridges, and elongate erosional remnants. The flow would have gained mobility as the debris moved downslope, producing travel distances greatly in excess of those characteristic of terrestrial examples, and eroded, streamlined remnants at the distal reaches of the channel. Finally, due to internal and boundary friction, the flow would have been slowed down once it entered the Chryse plains, resulting in a thin debris blanket with no depositional relief.

Nummedal, D.↗

Long Period Variations in Tidal and Librational Forcing of Europa

The gravitational field of Jupiter exerts a profound influence on the energy balance, thermal evolution, and stress regime of Europa. It widely appreciated that dissipation associated with the spheroidal tidal deformation is a major source of heat. Another possibly important source of dissipation is the toroidal deformation field associated with forced librations. Both tidal and librational deformations depend on the distance and direction Jupiter, as seen from Europa. These quantities vary with time as a result of the finite values of orbital eccentricity and spin pole obliquity, though the obliquity effects have been ignored in most previous studies. Variations in eccentricity and obliquity of the Galilean satellites occur on a very wide range of time scales, as angular momentum is exchanged among the orbital and rotational components of the coupled system. The orbital periods are only a few days in length, and the secular changes in orbital period associated with tidal and librational dissipation have characteristic time scales of 10-9 years or longer. On intermediate time scales, the satellites perturb each other, and the Sun and Saturn make additional contributions. The present values of satellite orbital inclinations and obliquities are not particularly representative their respective longer term variations. As a result, the tidal stress and dissipation regimes at present may not provide adequate explanation of the sources of surface features seen on the satellites.

Bills, Bruce G.↗

An Overview of the Guided Parafoil System Derived from X-38 Experience

The NASA Johnson Space Center built a 4200 sq ft parafoil for the U.S. Army Natick Soldier Center to demonstrate autonomous flight using a guided parafoil system to deliver 10,000 lbs of useable payload. The parafoil's design was based upon that developed during the X-38 program. The drop test payload consisted of a standard 20-foot Type V airdrop platform, a standard 12-foot weight tub, a 60 ft drogue parachute, a 4200 ft2 parafoil, an instrumentation system, and a Guidance, Navigation, and Control (GN&C) system. Instrumentation installed on the load was used to gather data to validate simulation models and preflight loads predictions and to perform post flight trajectory and performance reconstructions. The GN&C system, developed during NASA's X-38 program, consisted of a flight computer, modems for uplink commands and downlink data, a compass, laser altimeter, and two winches. The winches were used to steer the parafoil and to perform the dynamic flare maneuver for a soft landing. The laser was used to initiate the flare. The GN&C software was originally provided to NASA by the European Space Agency. NASA incorporated further software refinements based upon the X-38 flight test results. Three full-scale drop tests were conducted, with the third being performed during the Precision Airdrop Technology Conference and Demonstration (PATCAD) Conference at the U.S. Army Yuma Proving Ground (YPG) in November of 2003. For the PATCAD demonstration, the parafoil and GN&C software and hardware performed well, concluding with a good flare and the smallest miss distance ever experienced in NASA's parafoil drop test program. This paper describes the 4200 sq ft parafoil system, simulation results, and the results of the drop tests.

Stein, Jenny M.↗

Satellite Remote Sensing: Aerosol Measurements

Aerosols are solid or liquid particles suspended in the air, and those observed by satellite remote sensing are typically between about 0.05 and 10 microns in size. (Note that in traditional aerosol science, the term "aerosol" refers to both the particles and the medium in which they reside, whereas for remote sensing, the term commonly refers to the particles only. In this article, we adopt the remote-sensing definition.) They originate from a great diversity of sources, such as wildfires, volcanoes, soils and desert sands, breaking waves, natural biological activity, agricultural burning, cement production, and fossil fuel combustion. They typically remain in the atmosphere from several days to a week or more, and some travel great distances before returning to Earth's surface via gravitational settling or washout by precipitation. Many aerosol sources exhibit strong seasonal variability, and most experience inter-annual fluctuations. As such, the frequent, global coverage that space-based aerosol remote-sensing instruments can provide is making increasingly important contributions to regional and larger-scale aerosol studies.

Kahn, Ralph A.↗

Integrated field phenotyping and management platform for crop development and precision agriculture

A field controller and sensor is presented as an elongate body having a hollow interior and axially opposite first and second ends with a first arm extending outward from the elongate body adjacent to the first axial end and a second arm extending outward from the elongate body adjacent to the second, axially opposite end. Each of the arms has an imaging device. The first arm imaging device is positioned to obtain images in a direction toward the second axial end of the elongate body. The second arm imaging device is positioned to obtain images in a direction toward the first axial end. The first and second arms are spaced apart from one another along a length of the elongate body at a distance sufficient to image a canopy of crop growth in a field in which the field controller and sensor is deployed. The sensor may be formed from modules that allow the operator the ability to vary the height of the sensor by stacking the modules together end to end, which in turn allows users to scale their particular system with varying crop sizes within crop rotations.

Shakoor, Nadia↗

Molecular Mechanisms of Sorbed Ion Effects during Boehmite Particle Aggregation

Classical theories of particle aggregation, such as Derjaguin–Landau–Verwey–Overbeek (DLVO), do not explain recent observations of ion-specific effects or the complex concentration dependence for aggregation. Thus, here, we probe the molecular mechanisms by which selected alkali nitrate ions (Na + , K + , and NO 3 –) influence aggregation of the mineral boehmite (γ-AlOOH) nanoparticles. Nanoparticle aggregation was analyzed using classical molecular dynamics (CMD) simulations coupled with the metadynamics rare event approach for stoichiometric surface terminations of two boehmite crystal faces. Calculated free energy landscapes reveal how electrolyte ions alter aggregation on different crystal faces relative to pure water. Consistent with experimental observations, we find that adding an electrolyte significantly reduces the energy barrier for particle aggregation (~3–4×). However, in this work, we show this is due to the ions disrupting interstitial water networks, and that aggregation between stoichiometric (010) basal–basal surfaces is more favorable than between (001) edge–edge surfaces (~5–6×) due to the higher interfacial water densities on edge surfaces. The interfacial distances in the interlayer between aggregated particles with electrolytes (~5–10 Å) are larger than those in pure water (a few Ångströms). Together, aggregation/disaggregation in salt solutions is predicted to be more reversible due to these lower energy barriers, but there is uncertainty on the magnitudes of the energies that lead to aggregation at the molecular scale. By analyzing the peak water densities of the first monolayer of interstitial water as a proxy for solvent ordering, we find that the extent of solvent ordering likely determines the structures of aggregated states as well as the energy barriers to move between them. Further, the results suggest a path for developing a molecular-level basis to predict the synergies between ions and crystal faces that facilitate aggregation under given solution conditions. Such fundamental understanding could be applied extensively to the aggregation and precipitation utilization in the biological, pharmaceutical, materials design, environmental remediation, and geological regimes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗