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At least 1,513 records · Page 84

Airframe noise measurements by acoustic imaging

Studies of the noise produced by flow past wind tunnel models are presented. The central objective of these is to find the specific locations within a flow which are noisy, and to identify the fluid dynamic processes responsible, with the expectation that noise reduction principles will be discovered. The models tested are mostly simple shapes which result in types of flow that are similar to those occurring on, for example, aircraft landing gear and wheel cavities. A model landing gear and a flap were also tested. Turbulence has been intentionally induced as appropriate in order to simulate full-scale effects more closely. The principal technique involves use of a highly directional microphone system which is scanned about the flow field to be analyzed. The data so acquired are presented as a pictorial image of the noise source distribution. An important finding is that the noise production is highly variable within a flow field and that sources can be attributed to various fluid dynamic features of the flow. Flow separation was not noisy, but separation closure usually was.

Kendall, J. M.↗

ExaWind: Predictive Wind Energy Simulations

This presentation describes the ExaWind project and the team's progress in creating a suite of performance-portable codes designed for predictive simulations of wind farms on next-generation exascale-class supercomputers. Such simulations will require the resolution of scales spanning many orders of magnitude, from blade boundary layers to wind farm flow structures. In the U.S., the first exascale systems will be GPU accelerated, and different GPU manufacturers have been chosen for the different systems. At the heart of the ExaWind software is a hybrid-solver approach based on the codes Nalu-Wind and AMR-Wind, which are computational fluid dynamics solvers for the incompressible Navier-Stokes equations. Nalu-Wind is an unstructured-grid code used to resolve wind turbine geometry and blade boundary layers, whereas AMR-Wind is a structured-grid background solver for atmospheric turbulent flow and turbine wake propagation. The models are coupled with overset meshes and global linear systems are approximated through a loose-coupling algorithm. Results will include validation-quality high-fidelity simulations and strong/weak scaling results from the Summit supercomputer.

49 EE - Wind and Water Power Program - Wind (EE-4W↗

Observation of Chorus Waves by the Van Allen Probes: Dependence on Solar Wind Parameters and Scale Size

Highly energetic electrons in the Earths Van Allen radiation belts can cause serious damage to spacecraft electronic systems and affect the atmospheric composition if they precipitate into the upper atmosphere. Whistler mode chorus waves have attracted significant attention in recent decades for their crucial role in the acceleration and loss of energetic electrons that ultimately change the dynamics of the radiation belts. The distribution of these waves in the inner magnetosphere is commonly presented as a function of geomagnetic activity. However, geomagnetic indices are nonspecific parameters that are compiled from imperfectly covered ground based measurements. The present study uses wave data from the two Van Allen Probes to present the distribution of lower band chorus waves not only as functions of single geomagnetic index and solar wind parameters but also as functions of combined parameters. Also the current study takes advantage of the unique equatorial orbit of the Van Allen Probes to estimate the average scale size of chorus wave packets, during close separations between the two spacecraft, as a function of radial distance, magnetic latitude, and geomagnetic activity, respectively. Results show that the average scale size of chorus wave packets is approximately 13002300 km. The results also show that the inclusion of combined parameters can provide better representation of the chorus wave distributions in the inner magnetosphere and therefore can further improve our knowledge of the acceleration and loss of radiation belt electrons.

Aryan, Homayon↗

Community structure and function during periods of high performance and system upset in a full-scale mixed microalgal wastewater resource recovery facility

Microalgae have the potential to exceed current nutrient recovery limits from wastewater, enabling water resource recovery facilities (WRRFs) to achieve increasingly stringent effluent permits. The use of photobioreactors (PBRs) and the separation of hydraulic retention and solids residence time (HRT/SRT) further enables increased biomass in a reduced physical footprint while allowing operational parameters (e.g., SRT) to select for desired functional communities. However, as algal technology transitions to full-scale, there is a need to understand the effect of operational and environmental parameters on complex microbial dynamics among mixotrophic microalgae, bacterial groups, and pests (i.e., grazers and pathogens) and to implement robust process controls for stable long-term performance. Here, we examine a full-scale, intensive WRRF utilizing mixed microalgae for tertiary treatment in the US (EcoRecover, Clearas Water Recovery Inc.) during a nine-month monitoring campaign. We investigated the temporal variations in microbial community structure (18S and 16S rRNA genes), which revealed that stable system performance of the EcoRecover system was marked by a low-diversity microalgal community (D INVSIMPSON = 2.01) dominated by Scenedesmus sp. (MRA = 55 %-80 %) that achieved strict nutrient removal (effluent TP < 0.04 mg·L -1 ) and steady biomass concentration (TSS monthly avg . = 400–700 mg·L −1 ). Operational variables including pH, alkalinity, and influent ammonium (NH 4 + ), correlated positively (p < 0.05, method = Spearman) with algal community during stable performance. Further, the use of these parameters as operational controls along with N/P loading and SRT allowed for system recovery following upset events. Importantly, the presence or absence of bacterial nitrification did not directly impact algal system performance and overall nutrient recovery, but partial nitrification (potentially resulting from NO 2 − accumulation) inhibited algal growth and should be considered during long-term operation. The microalgal communities were also adversely affected by zooplankton grazers (ciliates, rotifers) and fungal parasites (Aphelidium), particularly during periods of upset when algal cultures were experiencing culture turnover or stress conditions (e.g., nitrogen limitation, elevated temperature). Altogether, the active management of system operation in order to maintain healthy algal cultures and high biomass productivity can result in significant periods (>4 months) of stable system performance that achieve robust nutrient recovery, even in winter months in northern latitudes (WI, USA).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Facet-dependent growth and dissolution of hematite resulting from autocatalytic interactions with Fe(II) and oxalic acid

The ability to simultaneously monitor the flux of iron atoms within the solution and solid phases can provide considerable insight into mechanisms of iron oxide mineral transformations. The autocatalytic interaction between hematite and Fe(II)-oxalate has long been of interest for its environmental and industrial relevance. In this study we take advantage of iron isotopic labelling and mass-sensitive imaging at the single particle scale to determine how changes in solution composition correlate with the morphologic evolution of faceted, micrometer-sized hematite platelets. Net dissolution is confirmed through analyses of aqueous iron chemistry, as well as by quantitative atomic force microscopy. Isotopic mapping techniques show that Fe(II) readily adsorbs to (001) and (012) surfaces in the absence of oxalate, but when oxalate is present selective dissolution of the (001) surface prevails and 57Fe deposition via recrystallization is not observed. Comparison between particle microtopographies following reaction with Fe(II), oxalate, and Fe(II)-oxalate show substantially different behavior, consistent with distinct mechanisms of interaction with hematite surfaces. The extensive characterization conducted on the coupled solution/solid dynamics in this system provides new insight for distinguishing crystal growth, dissolution, and recrystallization processes.

Taylor, Sandra D. [BATTELLE (PACIFIC NW LAB)]↗

Atmospheric dynamics of the outer planets

Despite major differences in the solar and internal energy inputs, the atmospheres of the four Jovian planets all exhibit latitudinal banding and high-speed jet streams. Neptune and Saturn are the windiest planets, Jupiter is the most active, and Uranus is a tipped-over version of the others. Large oval storm systems exhibit complicated time-dependent behavior that can be simulated in numerical models and laboratory experiments. The largest storm system, the Great Red Spot of Jupiter, has survived for more than 300 years in a chaotic shear zone where smaller structures appear and dissipate every few days. Future space missions will add to the understanding of small-scale processes, chemical composition, and vertical structure. Theoretical hypotheses about the interiors provide input for fluid dynamical models that reproduce many observed features of the winds, temperatures, and cloud patterns. In one set of models the winds are confined to the thin layer where clouds form. In other models, the winds extend deep into the planetary fluid interiors. Hypotheses will be tested further as observations and theories become more exact and detailed comparisons are made.

Ingersoll, Andrew P.↗

SIT 45: An interacting, compact, and star-forming isolated galaxy triplet

The underlying scenario of the formation and evolution of galaxy triplets is still uncertain. Mergers of galaxies in isolated triplets give us the opportunity to study the already complex merging process, with minimal contamination of other environmental effects that potentially allow and accelerate galaxy transitions from active star-forming to passive galaxies. The merging system SIT 45 (UGC 12589) is one of 315 systems in the SDSS-based catalogue of Isolated Triplets (SIT); it is an unusual isolated galaxy triplet, consisting of three merging late-type galaxies. The main aims of this work are to study the dynamical evolution and star formation history (SFH) of SIT 45, as well as its dependence on its local and large-scale environment. Methods. To study its dynamics, parameters such as the velocity dispersion (σ v ), the harmonic radius (R H ), the crossing time (H 0 t c ), and the virial mass (M vir ), along with the compactness of the triplet (S) were considered. To investigate the possible dependence of these dynamical parameters on the environment, the tidal force Q parameters (both local and large-scale) and the projected local density (η k ) were used. To constrain the SFH, we used CIGALE to fit its observed spectral energy distribution using multiwavelength data from the ultraviolet to the infrared. SIT 45 is one of the most compact triplets in the SIT, and it is also more compact than triplets in other samples. According to its SFH, SIT 45 presents star formation, where the galaxies also present recent (~200 Myr) star formation increase, indicating that this activity may have been triggered by the interaction. Its dynamical configuration suggests that the system is highly evolved in comparison to the SIT. However, this is not expected for systems composed of star-forming late-type galaxies, based on observations in compact groups. We conclude that SIT 45 is a system of three interacting galaxies that are evolving within the same dark matter halo; its compact configuration is a consequence of the ongoing interaction rather than being due to a long-term evolution (as suggested from its H 0 t c value). We consider two scenarios for the present configuration of the triplet, one where one of the members is a tidal galaxy, and another where this galaxy arrives to the system after the interaction. Both scenarios need further exploration. The isolated triplet SIT 45 is therefore an ideal system to study short timescale mechanisms (~10 8 yr), such as starbursts triggered by interactions which are more frequent at higher redshift.

79 ASTRONOMY AND ASTROPHYSICS↗

Large scale optimization using ASTROS: An overview

Interest in interdisciplinary systems is widespread around the world. A number of structural optimization systems are being developed and tested. Some examples are listed here. ASOP, FASTOP, and TSO are programs developed for the Air Force Flight Dynamics Laboratory during the seventies. These programs established the feasibility of integrating various disciplines. The program 'STARS' is basically a structural optimization system developed by the Royal Aircraft Establishment (RAE) in England. At present, it is being enhanced to include aeroelasticity. 'LAGRANGE' is an optimization system developed by MBB in Germany. ELFINI is a similar system developed in France. It is being marketed in the U.S. as well as other countries. The Automated STRuctural Optimization System (ASTROS) was developed for the Flight Dynamics Directorate of Wright Laboratory. The ASTROS system is described in viewgraph form.

Venkayya, Vipperia B.↗

Stressors Reveal Ecosystems' Hidden Characteristics

Abstract Vegetation responds dynamically to local microclimates at both short and long time scales via mechanisms ranging from physiological behaviors, such as stomatal closure, to acclimation and adaptation. These responses influence the carbon, water, and energy cycles directly and are therefore crucial to understanding and predicting Earth system responses to a changing climate. Several recent studies have demonstrated that differences in microclimate can induce structural and functional acclimations, and potentially adaptations, within the same ecosystem. Such microclimate divergence can be caused by variability in slopes, disturbance history, or even localized resource availability. Ecosystem stressors such as low soil water availability, limited photoperiod, or high vapor pressure deficit have been shown to reveal the large impact of the subtle differences within these systems such as the number of sun versus shade leaves or differences in whole‐plant water acquisition and use. These findings highlight the linkages between plant canopy structure and ecosystem function, alongside the need for comprehensive analyses of vegetation within the broader context of its environment. This commentary addresses some of the key implications of ecosystem stress responses and accompanying acclimations across three ecosystem types for ecosystem ecology, plant physiology, ecohydrology and trait‐based modeling of vegetation‐climate dynamics.

Matheny, Ashley M.↗

Observing Quantum Measurement Collapse as a Learnability Phase Transition

During a quantum measurement, superpositions of states with different observable properties probabilistically collapse into one with a sharp value of the measured observable. In macroscopic quantum systems, this collapse arises via a continuous measurement-induced phase transition (MIPT) at a critical value of the strength of interaction with the measurement apparatus. MIPTs lie outside established paradigms for equilibrium or nonequilibrium critical phenomena and delineate distinct, stable dynamical and computational phases of matter. Quantum computers enable programmable simulation of the interaction of a measurement apparatus with a dynamical quantum system, to explore MIPT phenomena over a range of system sizes while retaining quantum coherence. Yet, existing experimental protocols rely on fundamentally nonscalable postselection techniques or direct classical simulation of quantum circuits. Here, we report the scalable observation of finite-size scaling evidence for an observable-sharpening MIPT in monitored quantum circuits in a chain of Yb + 171 ions in Quantinuum’s H1-1 trapped-ion quantum processor. By leveraging an equivalent description as a statistical physics problem, we implement scalable classical algorithms to infer the value of the measured observable from a single experimental shot. This technique enables a truly scalable protocol to observe observable-sharpening MIPTs in generic classes of circuits that cannot be directly classically simulated and also provides enhanced means to detect and suppress errors in the quantum simulation. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Hydrologic connectivity and dynamics of solute transport in a mountain stream: Insights from a long-term tracer test and multiscale transport modeling informed by machine learning

The movement of solutes in a watershed is a complex process with multiple interactions and feedbacks across spatial and temporal scales. Modeling the dynamics of solute transport along diverse hydrologic pathways within watersheds – from hillslopes to stream channels and in and out of the hyporheic zones – is challenging but critically important, as these processes integrate and contribute to the biogeochemical functioning of the river corridor up to the river network scale. Here we use results from a long-term network-scale tracer test at the H.J. Andrews experimental forest in western Cascade Mountains, Oregon, USA to inform a multiscale framework for transport in stream corridors. The framework uses a Lagrangian-based subgrid model to represent the effects of hyporheic exchange flow and advective transport at stream network scales. The spatially and temporally resolved stream discharge needed for the transport model is imputed across the river system by an entity-aware long short-term memory network. Modeled concentrations show good agreements with the observations and exhibit power scaling laws indicative of a very wide range of timescales over which hyporheic exchange flow occurs. Our results demonstrate a data-informed modeling framework that links dynamical processes occurring at small scales to a network context to help understand how changes at reach scale cascade into network-scale effects, providing a useful tool for sustainable river basin management.

54 ENVIRONMENTAL SCIENCES↗

Agent-based Modeling for the Multi-objective Optimization of Energy Production Pathways: Integrated Techno-Economics and Life Cycle Assessment

This project developed an integrated modeling framework to evaluate how purpose-grown bioenergy feedstocks could support large-scale sustainable aviation fuel production in the United States. Led by Colorado State University with project partners, the work combined geographically resolved analysis, techno-economic assessment, life cycle assessment, multi-objective optimization, and agent-based modeling to examine feedstock performance, deployment potential, land-use implications, and adoption dynamics. The overall goal was to identify practical and sustainable pathways for producing aviation fuel from feedstocks such as energy crops, woody crops, oilseeds, and algae while helping inform policy, investment, and research needs tied to national SAF goals. In essence, the project provides a systems-level assessment of the opportunities and constraints associated with scaling bioenergy-based aviation fuels in the U.S.

09 BIOMASS FUELS↗

On the Asymptotic Regimes and the Strongly Stratified Limit of Rotating Boussinesq Equations

Asymptotic regimes of geophysical dynamics are described for different Burger number limits. Rotating Boussinesq equations are analyzed in the asymptotic limit, of strong stratification in the Burger number of order one situation as well as in the asymptotic regime of strong stratification and weak rotation. It is shown that in both regimes horizontally averaged buoyancy variable is an adiabatic invariant for the full Boussinesq system. Spectral phase shift corrections to the buoyancy time scale associated with vertical shearing of this invariant are deduced. Statistical dephasing effects induced by turbulent processes on inertial-gravity waves are evidenced. The 'split' of the energy transfer of the vortical and the wave components is established in the Craya-Herring cyclic basis. As the Burger number increases from zero to infinity, we demonstrate gradual unfreezing of energy cascades for ageostrophic dynamics. The energy spectrum and the anisotropic spectral eddy viscosity are deduced with an explicit dependence on the anisotropic rotation/stratification time scale which depends on the vertical aspect ratio parameter. Intermediate asymptotic regime corresponding to strong stratification and weak rotation is analyzed where the effects of weak rotation are accounted for by an asymptotic expansion with full control (saturation) of vertical shearing. The regularizing effect of weak rotation differs from regularizations based on vertical viscosity. Two scalar prognostic equations for ageostrophic components (divergent velocity potential and geostrophic departure ) are obtained.

Babin, A.↗

Feasibility study of a high spatial and time resolution beam emission spectroscopy diagnostic for localized density fluctuation measurements in Lithium Tokamak eXperiment-β (LTX-β)

Trapped electron mode (TEM) is the main source of turbulence predicted for the unique operation regime of a flat temperature profile under low-recycling conditions in the LTX-β tokamak, while ion temperature gradient driven turbulence may also occur with gas fueling from the edge. To investigate mainly TEM scale density fluctuations, a high spatial and time resolution 2D beam emission spectroscopy (BES) diagnostic is being developed. Apart from spatially localized density turbulence measurement, BES can provide turbulence flow and flow shear dynamics. This BES system will be realized using an avalanche photodiode-based camera and narrow band interference filter. The system can acquire data at 2 MHz. Simulations with the Simulation of Spectra (SOS) code indicate that a high signal to noise ratio can be achieved with the proposed system. This will enable sampling the density fluctuations at this high time resolution. Finally, the design considerations and system optimization using the SOS code are presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Machine-learning force-field models for dynamical simulations of metallic magnets

We review recent advances in machine-learning (ML) force-field methods for Landau–Lifshitz–Gilbert simulations of itinerant electron magnets, focusing on their scalability and transferability. Built on the principle of locality, a deep neural-network model is developed to efficiently and accurately predict electron-mediated forces governing spin dynamics. Symmetry-aware descriptors constructed through a group-theoretical approach ensure rigorous incorporation of both lattice and spin-rotation symmetries. The framework is demonstrated using the prototypical s-d exchange model widely employed in spintronics. ML-enabled large-scale simulations reveal novel nonequilibrium phenomena, including anomalous coarsening of tetrahedral spin order on the triangular lattice and the freezing of phase-separation dynamics in lightly hole-doped, strong-coupling square-lattice systems. These results establish ML force-field frameworks as scalable, accurate, and versatile tools for modeling nonequilibrium spin dynamics in itinerant magnets.

Artificial neural networks↗

The Artificial Scientist: in-Transit Machine Learning of Plasma Simulations

Large-scale simulations or scientific experiments produce petabytes of data per run. This poses massive challenges for I/O and storage when scientific analysis workflows are run manually offline. Unsupervised deep learning-based techniques to extract patterns and non-linear relations from these large amounts of data provide a way to build scientific understanding from raw data, reducing the need for manual pre-selection of analysis steps, but require exascale compute and memory to process the full dataset available. In this paper, we demonstrate a heterogeneous streaming workflow in which plasma simulation data is streamed directly to a Machine Learning (ML) application training a model on the simulation data in-transit, completely circumventing the capacity-constrained filesystem bottleneck. This workflow employs openPMD to provide a high level interface to describe scientific data and also uses ADIOS2, to transfer volumes of data that exceed the capabilities of the filesystem. We employ experience replay to avoid catastrophic forgetting in learning from this non-steady state process in a continual manner and adapt it to improve model convergence while learning in-transit. As a proof-of-concept, we approach the ill-posed inverse problem of predicting particle dynamics from radiation in a particle-incell (PIConGPU) simulation of the Kelvin-Helmholtz instability (KHI). We detail hardware-software co-design challenges as we scale PIConGPU to full Frontier, the Top-1 system as of June 2024 Top500 list.

Kelling, Jeffrey [Helmholtz-Zentrum Dresden Rossen↗

Adaptive Stiffness Power Take-Off System for a Hydraulic Hose-Pump Point Absorber Wave Energy Converter

Two crucial challenges faced in the design of ocean wave energy converters (WECs) are maintaining high capacity factors and remaining robust in everchanging, harsh ocean environments. This study introduces a novel mechanism for achieving reactive WEC control with a soft hydraulic power take-off, thereby addressing both challenges. The device of interest involves a hydraulic pump, constructed from a fluidic flexible matrix composite (F2MC), which is cyclically stretched by driving waves and pressurizes working fluid through a turbine-generator. This class of fiber-reinforced stretch hoses is established for ocean use as robust moorings and shock absorbers. The dynamic properties of the F2MC pump depend on internal pressure, which can be controlled by a continuously variable transmission between the turbine and generator, allowing the system to be adapted for better performance over a wide range of wave conditions. This work presents a dynamic model for operation and adaptive behavior of this power take-off system, experimentally validates components of the model, and performs dynamic simulations of the system that show increases in power production and capacity factor compared to non-adaptive operation for a variety of driving wave conditions. This work develops the basis for future large-scale experimental testing and controller design of this system.

Wave energy conversion, fluidic flexible matrix co↗

2022 Chaparral 64S Infrasound Sensor Type Approval Evaluation

Sandia National Laboratories has tested and evaluated a new version of the Chaparral 64S infrasound sensor, designed and manufactured by Chaparral Physics. The purpose of this infrasound sensor evaluation is to measure the performance characteristics in such areas as power consumption, sensitivity, full scale, self-noise, dynamic range, response, passband, sensitivity variation due to changes in barometric pressure and temperature, and sensitivity to acceleration. The Chaparral 64S infrasound sensors are being evaluated for use in the International Monitoring System (IMS) of the Preparatory Commission to the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO).

47 OTHER INSTRUMENTATION↗