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At least 1,675 records · Page 93

Emerging mobile lidar technology to study boundary layer winds influenced by operating turbines

The development of a microjoule-class pulsed Doppler lidar and deployment of this compact system on mobile platforms such as aircraft, ships, or trucks have opened a new opportunity to characterize the dynamics of complex mesoscale wind flows. The PickUp-based Mobile Atmospheric Sounder (PUMAS) truck-based lidar system was recently used during the American Wake Experiment (AWAKEN) to assess the general structure of boundary layer (BL) wind and turbulence around wind turbines in central Oklahoma. Wind speed profiles averaged over PUMAS transects influenced by the operating turbines (waked flow) show a 1–2 m s −1 reduction compared to mean undisturbed (free flow) wind speed profiles. Spatial variability in wind speed was observed in time–height cross-sections at different distances from turbines. The wind speeds were about 9–12 m s −1 at 6 km distance compared to 5–7 m s −1 at the transects near the turbines. The PUMAS dataset from AWAKEN demonstrated the capability of the mobile Doppler lidar system to document spatial variability in wind flows at different distances from wind turbines and obtain quantitative estimates of wind speed reduction in the waked flow. The high-frequency, simultaneous measurements of the horizontal and vertical winds provide a new approach for characterizing dynamic processes critical for wind farm wake analyses.

17 WIND ENERGY↗

Understanding plasma turbulence through exact coherent structures

Plasma turbulence is a key challenge in understanding transport phenomena in magnetically confined plasmas. This work presents a generalized framework to analyze plasma turbulence that utilizes periodic orbit theory. In periodic orbit theory, doubly periodic solutions (coherent structures) of the governing equation(s) serve as building blocks of the considered turbulent dynamics. To illustrate the concept and method, the particularly simple Kuramoto–Sivashinsky (referred to here as LMRT for the original authors: LaQuey, Mahajan, Rutherford, and Tang) trapped-ion mode toy model is used. By applying numerical optimization techniques to the LMRT equation, we extract coherent spacetime patterns that represent the library of allowable fundamental structures of the equation. These structures provide a framework to systematically describe turbulence as a composition of recurrent solutions, revealing an underlying order within chaotic plasma motion. Although illustrated here using the simplified LMRT model for clarity, this framework provides a general strategy that can be extended to more complex and realistic models of plasma turbulence, including gyrokinetic systems. This offers a new method for predicting and potentially controlling transport processes in fusion plasmas by providing a bridge between nonlinear dynamical systems theory and plasma physics in the form of a generalized framework with which to analyze and understand spatially extended nonlinear partial differential equations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Porous Flow Modeling of Axial Gas Redistribution in Fragmented LWR Fuel Rods using MOOSE

Understanding how gas axially redistributes within fragmented fuel pellets is crucial for predicting the behavior of Light Water Reactor (LWR) fuel rods, particularly during transient and accidental scenarios. The time scale of this phenomenon plays a fundamental role in determining the progression and hazard of a Loss Of Coolant Accident (LOCA), especially when high burn-up fuel in a severe state of fragmentation is involved. Here, this study presents a Computational Fluid Dynamics (CFD) model developed within the Multiphysics Object-Oriented Simulation Environment (MOOSE) to predict the time-scale of plenum depressurization in Light-Water Reactor (LWR) fuel rods driven by axial gas transport through fragmented pellets. The model examines the effects of incorporating non-linearities in the friction term by comparing the results with experimental data. The experiment employed surrogate fuel rods containing pellets subjected to mechanical and/or thermal loadings to simulate various severity of cracking, and aimed at studying the influence of fuel conditions on axial gas redistribution. The results of this analysis indicate that under certain flow regime conditions - determined by the value of an equivalent Reynolds number - accounting for the non-linear friction term in Navier-Stokes equations guarantees better predictions for the time-scale of plenum depressurization. Also, the model enabled the simulation of the pressure decay by assigning distinct permeability values to each pellet instead of a single uniform value. Multiple simulations were run across all possible pellet position combinations, having each pellet assigned with values of permeability extracted from the experimental data. This allows to quantify the impact of the considering various non-uniform distributions of permeability on the dynamics of axial gas redistribution. The present work findings enhance the understanding of axial gas transport, and provide valuable insights for the integration of a model for predicting the axial gas redistribution during a LOCA scenario into the BISON fuel performance code.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Dual Electron Spectrometer for Magnetospheric Multiscale Mission: Results of the Comprehensive Tests of the Engineering Test Unit

The Magnetospheric Multiscale mission (MMS) is designed to study fundamental phenomena in space plasma physics such as a magnetic reconnection. The mission consists of four spacecraft, equipped with identical scientific payloads, allowing for the first measurements of fast dynamics in the critical electron diffusion region where magnetic reconnection occurs and charged particles are demagnetized. The MMS orbit is optimized to ensure the spacecraft spend extended periods of time in locations where reconnection is known to occur: at the dayside magnetopause and in the magnetotail. In order to resolve fine structures of the three dimensional electron distributions in the diffusion region (reconnection site), the Fast Plasma Investigation's (FPI) Dual Electron Spectrometer (DES) is designed to measure three dimensional electron velocity distributions with an extremely high time resolution of 30 ms. In order to achieve this unprecedented sampling rate, four dual spectrometers, each sampling 180 x 45 degree sections of the sky, are installed on each spacecraft. We present results of the comprehensive tests performed on the DES Engineering & Test Unit (ETU). This includes main parameters of the spectrometer such as energy resolution, angular acceptance, and geometric factor along with their variations over the 16 pixels spanning the 180-degree tophat Electro Static Analyzer (ESA) field of view and over the energy of the test beam. A newly developed method for precisely defining the operational space of the instrument is presented as well. This allows optimization of the trade-off between pixel to pixel crosstalk and uniformity of the main spectrometer parameters.

Avanov, Levon A.↗

Physics-Informed Active Learning With Simultaneous Weak-Form Latent Space Dynamics Identification

The parametric greedy latent space dynamics identification (gLaSDI) framework has demonstrated promising potential for accurate and efficient modeling of high-dimensional nonlinear physical systems. However, it remains challenging to handle noisy data. Here, to enhance robustness against noise, we incorporate the weak-form estimation of nonlinear dynamics (WENDy) into gLaSDI. In the proposed weak-form gLaSDI (WgLaSDI) framework, an autoencoder and WENDy are trained simultaneously to discover intrinsic nonlinear latent-space dynamics of high-dimensional data. Compared with the standard sparse identification of nonlinear dynamics (SINDy) employed in gLaSDI, WENDy enables variance reduction and robust latent space discovery, therefore leading to more accurate and efficient reduced-order modeling. Furthermore, the greedy physics-informed active learning in WgLaSDI enables adaptive sampling of optimal training data on the fly for enhanced modeling accuracy. The effectiveness of the proposed framework is demonstrated by modeling various nonlinear dynamical problems, including viscous and inviscid Burgers' equations, time-dependent radial advection, and the Vlasov equation for plasma physics. With data that contains 5%–10% Gaussian white noise, WgLaSDI outperforms gLaSDI by orders of magnitude, achieving 1%–7% relative errors. Compared with the high-fidelity models, WgLaSDI achieves 121 to 1779x speed-up.

97 MATHEMATICS AND COMPUTING↗

Unravelling the dynamics of the maturation protein in MS2 bacteriophage via molecular simulations

The MS2 bacteriophage capsid serves as a model system for studying viral structure and function. Mature MS2 virus consists of 178 capsid proteins and a single maturation protein (MP), which is essential for host receptor binding and infection initiation. Despite its critical role, the dynamic behavior of the capsid with the MP remains poorly understood. To address this, we conducted 0.5 µs all-atom molecular dynamics (MD) simulations of the MS2 capsid with and without the MP, revealing key insights into its structural dynamics. Our simulations showed that MP exhibits high flexibility, particularly in the “tip” and “side-loop” regions, which undergo significant motions that likely enhance its ability to engage with the F-pilus receptor. Detailed analysis of MP conformational states revealed that loop rearrangements around H357 enable transient switching between “semi-closed” and “open” conformations, suggesting a conformational selection mechanism for pilus binding. Additionally, ion interaction analyses revealed distinct sodium and chloride binding patterns, where sodium ions were mostly found at the outer capsid shell, while chloride ions interacted with the basic residues on the RNA-facing side. We also found that the presence of the MP enhances salt-bridge interactions, contributing to increased capsid stability, yet it does not significantly alter the pore sizes of pentameric and hexameric units. Together, these findings provide new insights into the functional role of the MP, highlighting its contribution to capsid stability and host receptor engagement. This study offers a foundation for understanding capsid dynamics relevant to viral infectivity and may guide future rational strategies aimed at disrupting host-virus interactions.

Capsid stability↗

Dynamic modeling of orographically induced precipitation

Local orography governs the triggering of cloud formation and the enhancement of processes such as condensation and hydrometeor nucleation and growth in mountainous regions. Intense, lengthy precipitation events are typical upwind of the topographic divide, with sharply decreasing magnitude and duration on the lee side. Differences in mean annual precipitation of several hundred percent between windward slopes of orographic barriers and adjacent valleys or lee side slopes are not unusual. Because much of the streamflow in areas such as the western United States is derived from mountainous areas that are remote and often poorly instrumented, modeling of orographic precipitation has important implications for water resources management. Models of orographically induced precipitation differ by their treatment of atmospheric dynamics and by the extent to which they rely on bulk parameterization of cloud and precipitation physics. Adiabatic ascent and a direct proportionality between efficiency and orographically magnified updrafts are the most frequent assumptions in orographic precipitation modeling. Space-time discretization (i.e., resolution) is a major issue because of the high spatial variability of orographic precipitation. For a specific storm, relative errors as large as 50 to 100% are common in the forecast/hindcast of precipitation intensity and can be even larger in the case of catastrophic storms. When monthly or seasonal timescales are used to evaluate model performance, the magnitude of such errors decreases dramatically, reaching values as low as 10 to 15%. Current research is focusing on the development of data assimilation techniques to incorporate radar and satellite observations, and on the development of aggregation and disaggregation methodologies to address the implications of modeling a multiscale problem at restricted spatial and temporal resolutions.

Barros, Ana Paula↗

Stress Analyzer

SPATE 900 Dynamic Stress Analyzer is an acronym for Stress Pattern Analysis by Thermal Emission. It detects stress-induced temperature changes in a structure and indicates the degree of stress. Ometron, Inc.'s SPATE 9000 consists of a scan unit and a data display. The scan unit contains an infrared channel focused on the test structure to collect thermal radiation, and a visual channel used to set up the scan area and interrogate the stress display. Stress data is produced by detecting minute temperature changes, down to one-thousandth of a degree Centigrade, resulting from the application to the structure of dynamic loading. The electronic data processing system correlates the temperature changes with a reference signal to determine stress level.

Source record↗

Is there an exact magnetic moment for charged particle motion in a time-dependent, homogeneous magnetic field?

The non-perturbative guiding-centre model provides an exact alternative to full-orbit simulations of charged particle dynamics in situations where traditional guiding-centre theory may fail. We demonstrate that the charged particle motion in a homogeneous, time-varying magnetic field is a solvable example of the non-perturbative guiding-centre model. This entails showing that the exact magnetic moment of Qin and Davidson can be constructed to be asymptotic to the adiabatic invariant series of Kruskal. In contrast to the perturbative invariant, the exact invariant contains information about parametric resonances. These resonances destroy the conservation of the usual magnetic moment over very long times. This refutes some previous claims about the all-time invariance of the magnetic moment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Atomic dynamics of gas-dependent oxide reducibility

Understanding oxide reduction is critical for advancing metal production, catalysis and energy technologies. Although carbon monoxide (CO) and hydrogen (H 2 ) are widely used reductants, the mechanisms by which they work are often presumed to be similar, both involving lattice oxygen removal. However, because of growing interest in replacing CO with H 2 to lower CO 2 emissions, distinguishing gas-specific reduction pathways is critical. Yet, capturing these atomic-scale processes under reactive gas and high-temperature conditions remains challenging. Here we use environmental transmission electron microscopy, which is capable of real-time, atomic-resolution imaging of gas–solid redox reactions to directly visualize the gas-dependent oxide reduction dynamics in NiO. We show that CO drives surface nucleation and the growth of metallic Ni islands, leading to self-limiting surface metallization. Conversely, H 2 activates a coupled surface-to-bulk transformation, where protons from dissociated H 2 infiltrate the oxide lattice to promote the inward migration of surface-generated oxygen vacancies and enabling bulk metallization. By contrast, oxygen vacancies formed by CO remain confined near the surface, where they rapidly form a metallic Ni layer that inhibits further reduction. Furthermore, these results reveal distinct atomistic pathways for CO and H 2 and provide insights that may guide metallurgical processes and catalyst design.

36 MATERIALS SCIENCE↗

Purpose, Design, and Analysis of the NSTX-U Centerstack Casing Lateral Support Shims

The National Spherical Torus Experiment Upgrade (NSTX-U) centerstack casing surrounds the central magnet core of NSTXU. It provides the inner vacuum boundary of the plasma chamber and supports the radially inboard plasma facing components lining the plasma chamber. The casing is supported like a cantilever, fixed at the lower flange by a connection to the TF Bundle through a G-10 ring. It is flexibly supported at the top by bellows, and insulated shims intended to react the largest part of the inventory of the disruption loads at the upper support, thereby protecting the upper and lower connections from excessive loads. A large part of the qualification of the casing and tiles requires addressing and quantifying disruption loads. These have been estimated based on extensions of the behavior of NSTX during its run period roughly 15 years ago. Structural qualification of the Upgrade used these estimates of the loading as input to calculations to demonstrate adequacy for a “most probable” disruption. The estimates are included in a requirements document to guide conservative design of all components loaded by disruptions. However, the changes made for the upgrade made the extrapolation of disruption behavior uncertain. Disruptions include axisymmetric loading from axisymmetric currents induced in the vessel shells. In addition, more complex currents called Halo currents are a result of plasma poloidal currents impinging on the casing. The halo currents add another layer of uncertain behavior and net lateral loading to the casing. As a result, NSTX-U is equipped with a number of instruments intended to assess the nature and severity of disruptions. The casing shims are required for lateral support of the casing, but these have also been converted to load cells to provide another measure of the magnitude of symmetric and asymmetric loading. Some of the logic in the development of the requirements document are presented. Electromagnetic analysis of axisymmetric and halo loading is described. Global simulations of the casing transient dynamic response, and local analysis and testing of the shim/load cell are included. The shim load cells and other instrumentation will be an important guide in planning NSTX-U experiments beyond its next run period expected in late 2026 or early 2027.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Comparative analysis of plasmon modes in layered Lindhard metals and strange metals

The enigmatic strange metal remains one of the central unsolved problems of 21st century science. Understanding this phase of matter requires knowledge of the momentum- and energy-resolved dynamic charge susceptibility 𝜒⁡(𝑞,𝜔), especially at finite momentum. Inelastic electron scattering (EELS), performed in either transmission or reflection geometry, is a powerful probe of 𝜒⁡(𝑞,𝜔). For the prototypical strange metal Bi 2 ⁢Sr 2 ⁢CaCu 2 ⁢O 8+𝑥 , transmission- and reflection EELS, and infrared (IR) spectroscopy agree at 𝑞∼0, all revealing a highly damped plasmon near 1 eV. At larger 𝑞, however, EELS results show unresolved discrepancies. Since IR data are highly reproducible, it is advantageous to use IR data to calculate what the expected EELS response should be at modest 𝑞. Building on prior momentum-resolved reflection geometry M-EELS work [Chen et al., Phys. Rev. B 109, 045108 (2024)], we extend this approach to transmission EELS for finite stacks of metallic layers, comparing a “textbook” Lindhard metal to a strange metal. In the Lindhard case, the low-𝑞 response is dominated by long-lived, standing wave plasmon modes arising from interlayer Coulomb coupling, with in-plane dispersions that resemble the well-known Fetter modes of layered metals. This behavior depends only on the geometry and the long-range nature of the Coulomb interaction and is largely insensitive to layer details. At larger 𝑞, the response reflects the microscopic properties of individual layers. For the strange metal, calculations based on IR data predict a highly damped plasmon with weak dispersion and no distinct surface mode. While our results match IR and M-EELS at low 𝑞, they do not reproduce any published EELS spectra at large 𝑞, highlighting unresolved discrepancies that demand further experimental investigation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Leveraging Groundwater Dynamics to Improve Predictions of Summer Low-Flow Discharges

Summer streamflow predictions are critical for managing water resources; however, warming-induced shifts from snow to rain regimes impact low-flow predictive models. Additionally, reductions in snowpack drive earlier peak flows and lower summer flows across the western United States increasing reliance on groundwater for maintaining summer streamflow. However, it remains poorly understood how groundwater contributions vary interannually. Here, we quantify recession limb groundwater (RLGW), defined as the proportional groundwater contribution to the stream during the period between peak stream flow and low flow, to predict summer low flows across three diverse western US watersheds. We ask (a) how do snow and rain dynamics influence interannual variations of RLGW contributions and summer low flows?; (b) which watershed attributes impact the effectiveness of RLGW as a predictor of summer low flows? Linear models reveal that RLGW is a strong predictor of low flows across all sites and drastically improves low-flow prediction compared to snow metrics at a rain-dominated site. Results suggest that strength of RLGW control on summer low flows may be mediated by subsurface storage. Subsurface storage can be divided into dynamic (i.e., variability saturated) and deep (i.e., permanently saturated) components, and we hypothesize that interannual variability in dynamic storage contribution to streamflow drives RLGW variability. In systems with a higher proportion of dynamic storage, RLGW is a better predictor of summer low flow because the stream is more responsive to dynamic storage contributions compared to deep-storage-dominated systems. Overall, including RLGW improved low-flow prediction across diverse watersheds.

54 ENVIRONMENTAL SCIENCES↗