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At least 397 records · Page 22

Dependence of the boundary heat flux width on core and edge profiles in Alcator C-Mod

This work presents new evidence that the heat flux width, λ q , in the Alcator C-Mod tokamak scales with the edge electron pressure, as observed in the ASDEX Upgrade (AUG) tokamak, but the scaling with volume-averaged pressure, $\bar{p}$, from the plasma stored energy, is a better predictor of λ q in Alcator C-Mod than the edge electron pressure. These previous studies, which find that λ q decreases with increasing plasma pressure, imply that a high performance core at high pressure will lead to challenging heat and particle exhaust due to very small λ q . This concern has led to our significant enlargement of the C-Mod database with the electron density, temperature, and pressure profile data from the Thomson scattering and electron cyclotron emission diagnostics. Using the C-Mod database augmented with new profile data, we find that λ q decreases with increasing edge electron pressure as ${\lambda }_{q}\propto {p}_{\mathrm{e},95}^{-0.26}$, similar to results from AUG, and showing the strength of cross-machine comparisons. We also find that ${\lambda }_{q}\propto {p}_{\mathrm{e},\mathrm{c}\mathrm{o}\mathrm{r}\mathrm{e}}^{-0.56}$, consistent with the original finding from C-Mod that the heat flux width scales as ${\bar{p}}^{-0.48}$. The scalings of λ q with separatrix pressure and gradient scale length are found to match the AUG results qualitatively. The C-Mod scalings with edge plasma quantities have more scatter than the $\bar{p}$ scaling, and, importantly, show different trends for H-modes relative to L- and I-mode. Furthermore, investigating the source of this discrepancy presents an opportunity for further study that may improve our ability to predict the heat flux width in different confinement scenarios in the pursuit of optimizing core-edge performance in future reactors.

Alcator C-Mod↗

The boundary density profile of a Coulomb droplet. Freezing at the edge

In this paper, we revisit the problem of computing the boundary density profile of a droplet of two-dimensional one-component plasma (2D OCP) with logarithmic inter- action between particles in a confining harmonic potential. At a sufficiently low temperature, but still in the liquid phase, the density exhibits oscillations as a function of the distance to the boundary of the droplet. We obtain the density profile numerically using Monte-Carlo simulations of the 2D OCP. We argue that the decay and period of those oscillations can be explained within a picture of the Wigner crystallization near the boundary, where the crystal is gradually melted with the increasing distance to the boundary.

2D OCP↗

Learning continuous scattering length density profiles from neutron reflectivities using convolutional neural networks

Interpreting neutron reflectivity (NR) data using ad hoc multi-layer models and physics-based models provides information about spatially resolved neutron scattering length density (NSLD) profiles. Recent improvements in data acquisition systems have allowed acquiring thousands of NR curves in a couple of hours, which has led to a need for automated data analysis tools to interpret NR measurements in real-time. Here, we present a machine learning analysis workflow that uses a series of models, based on a convolutional neural network (CNN), to learn the relation between the NSLDs and the NRs, and subsequently produce continuous NSLD profiles directly from NRs. The usefulness of our CNN-based models is demonstrated by constructing NSLDs from NRs of several films containing homopolymer polyzwitterions and diblock copolymers mixed with different types of salts. Comparisons of the NSLDs with those constructed using ad hoc multi-layer models reveal a very good agreement, suggesting the potential of CNN-based models for real-time automated data analysis of NRs.

36 MATERIALS SCIENCE↗

Biostimulation of Salicornia europaea L. crops with plant growth-promoting bacteria in laboratory and field conditions: effects on growth and metabolite profile

Abstract Aim The objective of the work was to assess the effect of biostimulation with selected plant growth-promoting bacteria on growth and metabolite profile of Salicornia europaea. Methods and results Salicornia europaea seeds were inoculated with different combinations of plant growth-promoting bacteria Brevibacterium casei EB3, Pseudomonas oryzihabitans RL18, and Bacillus aryabhattai SP20. Plants germinated from inoculated seeds were grown either in laboratory conditions or in a saline crop field. Fresh and dry weight were determined at the end of the experiment, for biomass quantification. The microbiological quality of fresh shoots for human consumption as salad greens was assessed, and the persistence of the inoculated strains in the plant rhizosphere was confirmed by next-generation sequencing (Illumina) of the 16S rDNA gene. The primary metabolite profile of biostimulated plants was characterized by GC–TOF-MS. In laboratory conditions, inoculation with the two strains Br. casei EB3 and Ps. oryzihabitans RL18 caused the most significant increase in biomass production (fresh and dry weight), and caused a shift in the central metabolic pathways of inoculated plants toward amino acid biosynthesis. In the field experiment, no significant biostimulation effect was detected with any of the tested inoculants. Seed inoculation had no significant effect on the microbiological quality of the edible parts. The persistence of inoculants was confirmed in both experiments. Conclusions Manipulation of the plant microbiome can trigger primary metabolic reconfiguration and modulate the plant metabolism while promoting plant growth.

Ferreira, Maria J.↗

Investigating the origin of observed central dips in radial metallicity profiles

ABSTRACT Radial metallicity trends provide a key indicator of physical processes such as star formation and radial gas migration within a galaxy. Large integral field unit surveys allow for detailed studies of these radial variations, with recent observations detecting central dips in the metallicity, which may trace the impact of various evolutionary processes. However, the origin of these dips has not been conclusively determined, with suggestions that they may be diagnostic dependent. In this paper, we use the Sloan Digital Sky Survey IV Mapping Nearby Galaxies at Apache Point Observatory survey to investigate whether the observed dips represent genuine decreases in the central metallicity, or whether they could be an artefact of the diagnostic used. Using a sub-sample of 758 local star-forming galaxies at low inclinations, we investigate in detail the impact of using different strong line diagnostics on the shapes of the returned profiles, and the prevalence of dips. We find no clear evidence of the dips being caused by changing values of the ionization parameter within galaxies. To investigate physical causes, we explore both global and spatially resolved parameters, finding that galaxies exhibiting central dips in the O3N2 metallicity profile have on average lower H α equivalent width values out to $R/R_{\rm {e}} \sim 1.5$, and higher values of DN(4000) in the central regions. We additionally find a higher prevalence of dips in galaxies with high stellar mass, and lower values of global specific star formation rate, suggesting a possible link to central quenching. Nevertheless, these results are dependent on the diagnostic used, suggesting caution should be taken when interpreting observed features in galaxy metallicity gradients.

79 ASTRONOMY AND ASTROPHYSICS↗

Shocks in the stacked Sunyaev-Zel’dovich profiles of clusters II: Measurements from SPT-SZ + Planck Compton- y map

ABSTRACT We search for the signature of cosmological shocks in stacked gas pressure profiles of galaxy clusters using data from the South Pole Telescope (SPT). Specifically, we stack the latest Compton-y maps from the 2500 deg2 SPT-SZ survey on the locations of clusters identified in that same data set. The sample contains 516 clusters with mean mass $\langle M_{\rm 200m}\rangle = 10^{14.9} \, {\rm M}_\odot$ and redshift 〈z〉 = 0.55. We analyse in parallel a set of zoom-in hydrodynamical simulations from the three hundred project. The SPT-SZ data show two features: (i) a pressure deficit at R/R200m = 1.08 ± 0.09, measured at 3.1σ significance and not observed in the simulations, and; (ii) a sharp decrease in pressure at R/R200m = 4.58 ± 1.24 at 2.0σ significance. The pressure deficit is qualitatively consistent with a shock-induced thermal non-equilibrium between electrons and ions, and the second feature is consistent with accretion shocks seen in previous studies. We split the cluster sample by redshift and mass, and find both features exist in all cases. There are also no significant differences in features along and across the cluster major axis, whose orientation roughly points towards filamentary structure. As a consistency test, we also analyse clusters from the Planck and Atacama Cosmology Telescope Polarimeter surveys and find quantitatively similar features in the pressure profiles. Finally, we compare the accretion shock radius ($R_{\rm sh,\, acc}$) with existing measurements of the splashback radius (Rsp) for SPT-SZ and constrain the lower limit of the ratio, $R_{\rm sh,\, acc}/R_{\rm sp}\gt 2.16 \pm 0.59$.

79 ASTRONOMY AND ASTROPHYSICS↗

Reconstructing large-scale temperature profiles around z ∼ 6 quasars

ABSTRACT High-redshift quasars ionize He ii into He iii around them, heating the intergalactic medium in the process and creating large regions with elevated temperature. In this work, we demonstrate a method based on a convolutional neural network (CNN) to recover the spatial profile for T0, the temperature at the mean cosmic density, in quasar proximity zones. We train the neural network with synthetic spectra drawn from a Cosmic Reionization on Computers simulation. We discover that the simple CNN is able to recover the temperature profile with an accuracy of ≈1400 K in an idealized case of negligible observational uncertainties. We test the robustness of the CNN and discover that it is robust against the uncertainties in quasar host halo mass, quasar continuum, and ionizing flux. We also find that the CNN has good generality with regard to the hardness of quasar spectra. This shows that with noiseless spectra, one could use a simple CNN to distinguish gas inside or outside the He iii region created by the quasar. Because the size of the He iii region is closely related to the total quasar lifetime, this method has great potential in constraining the quasar lifetime on ∼Myr time-scales. However, noise poses a big problem for accuracy and could downgrade the accuracy to ≈2340 K even for very high signal-to-noise (≳50) spectra. Future studies are needed to reduce the error associated with noise to constrain the lifetimes of reionization epoch quasars with currently available data.

79 ASTRONOMY AND ASTROPHYSICS↗

A defined medium based on R2A for cultivation and exometabolite profiling of soil bacteria

SummaryExometabolomics is an approach to assess how microorganisms alter their environments through the depletion and secretion of chemical compounds. Comparisons of inoculated with uninoculated media can be used to provide direct biochemical observations on depleted and secreted metabolites which can be used to predict resource competition, cross-feeding and secondary metabolite production in microbial isolates and communities. This approach is most powerful when used with defined media that enable tracking of all depleted metabolites. However, microbial growth media have traditionally been developed for the isolation and growth of microorganisms but not metabolite utilization profiling through LC-MS/MS. Here, we describe the construction of a defined medium, the Northen Lab Defined Medium (NLDM), that not only supports the growth of diverse bacteria but is defined and therefore suited for exometabolomic experiments. Metabolites included in NLDM were selected based on their presence in R2A medium and soil, elemental stoichiometry requirements, as well as knowledge of metabolite usage by different bacteria. We found that NLDM supported the growth of 53 phylogenetically diverse soil bacterial isolates and all of its metabolites were trackable through LC–MS/MS analysis. These results demonstrate the viability and utility of the constructed NLDM medium for cultivating and characterizing diverse microbial isolates and communities.Originality-Significance StatementWe build a defined medium based on the metabolite composition of R2A medium and soil, elemental stoichiometry requirements, and knowledge of metabolite usage by different bacteria. The newly formulated defined medium was evaluated on its ability to support the growth of soil isolates and its application for metabolite utilization profiling. We found that of 53 phylogenetically diverse soil bacterial isolates grew on the defined medium and all of its metabolites were trackable through LC–MS/MS analysis. This demonstrates the viability and utility of the constructed defined medium for cultivating and characterizing diverse microbial isolates and communities.

de Raad, Markus↗

Testing $f(R)$ gravity with scale dependent cosmic void velocity profiles

Here, we study the impact of cosmological scale modifications to general relativity on the dynamics of halos within voids by comparing N-body simulations incorporating Hu-Sawicki f(R) gravity, with |f R0 | = 10 -6 and 10 -5 , to those of Λ CDM. By examining the radial velocity statistics within voids classified based on their size and density-profile, as “rising” (R-type) or “shell” (S-type), we find that halo motions in small R-type voids, with effective radius <15 Mpc/h, reveal distinctive differences between f(R) and Λ CDM cosmologies. To understand this observed effect, we study the linear and nonlinear fifth forces, and develop an iterative algorithm to accurately solve the nonlinear fifth force equation. We use this to characterize the Chameleon screening mechanism in voids and contrast the behavior with that observed in gravitationally collapsed objects. The force analysis underscores how smaller R-type voids exhibit the highest ratios of fifth force to Newtonian force, which source distinguishable differences in the velocity profiles and thereby provide rich environments in which to constrain gravity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Uncovering dark matter density profiles in dwarf galaxies with graph neural networks

Dwarf galaxies are small, dark-matter-dominated galaxies, some of which are embedded within the Milky Way. Their lack of baryonic matter (e.g., stars and gas) makes them perfect test beds for probing the properties of dark matter—understanding the spatial dark matter distribution in these systems can be used to constrain microphysical dark matter interactions that influence the formation and evolution of structures in our Universe. Here, we introduce a new method that leverages simulation-based inference and graph-based machine learning in order to infer the dark matter density profiles of dwarf galaxies from observable kinematics of stars gravitationally bound to these systems. Our approach aims to address some of the limitations of established methods based on dynamical Jeans modeling. We show that this novel method can place stronger constraints on dark matter profiles and, consequently, has the potential to weigh in on some of the ongoing puzzles associated with the small-scale structure of dark matter halos, such as the core-cusp discrepancy.

79 ASTRONOMY AND ASTROPHYSICS↗

Perturbed Ion Temperature and Toroidal Flow Profile Measurements in Rotating Neoclassical Tearing Mode Magnetic Islands

The perturbed ion temperature and toroidal flow were measured in rotating Neoclassical Tearing Modes (NTM) in a tokamak for the first time. These toroidally and radially resolved profiles were obtained by impurity ion spectroscopy in a 2,1 NTM in DIII-D. In agreement with drift-kinetic simulations, the electron temperature profile is flat, while the ion temperature gradient is restored across the magnetic island O-point in the presence of fast ions; the perturbed flow has minima in the O-points and maxima at the X-points. Furthermore, these measurements provide the first confirmation of the theoretically expected ion temperature and flow response to a magnetic island needed to predict the NTM on set threshold scaling for ITER and other future tokamaks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Broadening of the Divertor Heat Flux Profile in High Confinement Tokamak Fusion Plasmas with Edge Pedestals Limited by Turbulence in DIII-D

Multimachine empirical scaling predicts an extremely narrow heat exhaust layer in future high magnetic field tokamaks, producing high power densities that require mitigation. Here, in the experiments presented, the width of this exhaust layer is nearly doubled using actuators to increase turbulent transport in the plasma edge. This is achieved in low collisionality, high confinement edge pedestals with their gradients limited by turbulent transport instead of large-scale, coherent instabilities. The exhaust heat flux profile width and divertor leg diffusive spreading both double as a high frequency band of turbulent fluctuations propagating in the electron diamagnetic direction doubles in amplitude. The results are quantitatively reproduced in electromagnetic XGC particle-in-cell simulations which show the heat flux carried by electrons emerges to broaden the heat flux profile, directly supported by Langmuir probe measurements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Influence of conical wire array geometry on plasma flow and temperature profiles of radiatively cooled jets

The influence of conical wire array geometry on the formation and dynamics of pulsed-power driven plasma jets is investigated. In the experiments, the jet becomes isolated from the inflows as it passes through an aperture, allowing the study of its intrinsic evolution for different conical angles. Here, our results show that, regardless of the array opening angle, the jets are supersonic, highly collisional, and exhibit an exponential axial density decay with a characteristic scale length of 𝐿 𝑛 ≈ 3 mm, significantly shorter than the overall length of the jet. In contrast, axial velocity systematically increases with larger array opening angles. The near invariance of the density profile is attributed to a compensating mechanism between geometric divergence and axial acceleration, consistent with an asymptotically steady flow regime. Additionally, temperature measurements reveal ion-electron thermal decoupling near the base of the jet, with equilibration downstream. Analysis of radiative cooling and collisional energy exchange timescales indicates that the plasma evolves in a radiatively stable regime and that the two-temperature profile is fully described by the competition between both methods. These findings provide valuable information into the internal structure and evolution of pulsed-power plasma jets in regimes dominated by geometric shaping and radiative cooling, demonstrating experimental control over flow acceleration and collimation relevant to both laboratory and astrophysical contexts.

Physics - Plasma physics↗

In situ temperature profile measurements with high-energy X-rays as a probe of optical floating zone crystal growth environment

The ability of optical floating zone (OFZ) furnaces to rapidly produce large single crystals of complex emerging materials has had a transformative effect on many scientific fields that require samples of this type. However, the crystal growth process within the OFZ furnace is not well understood owing to the challenges involved in monitoring the high-temperature crystal growth process. Novel beamline-compatible optical furnaces that approximate the inhomogeneous growth environment within an OFZ furnace have been fabricated and tested in high-energy synchrotron beamlines. In this paper, it is demonstrated that temperature profiles can be effectively extracted from powder diffraction data collected on polycrystalline ceramic rods heated at their tip. Furthermore, these measured temperature profiles can be accurately reproduced using a heat-transfer model that accounts for solid-state thermal conduction, partial sample lamp power absorption, convective air cooling and radiative cooling, allowing key thermal parameters such as thermal conductivity to be extracted from experimental data.

36 MATERIALS SCIENCE↗

Factorization Machine Learning for Disaggregation of Transmission Load Profiles with High Penetration of Behind-the-Meter Solar

The ever-growing high penetration of ubiquitously distributed energy resources, especially behind-the-meter solar (BTM) generations, has significant impacts on nodal load (i.e., net injection) profiles and consequently caused imperative operational challenges to system operators such as regional transmission organizations (RTOs). Illustrated by real-world nodal data and examples at PJM Interconnection, this paper first discusses the application and necessity of effectively extracting daily nodal load profiles in a non-intrusive manner. More importantly, a novel bi-level architecture, including Factorization Machines (FM) learning procedure has been proposed to effectively disaggregate not only one node but every node in an RTO service territory. Specifically, FM leaning is adopted to capture the interconnections between related features to better utilize the correlation between buses in the same region and between a single bus and the zonal load. The proposed bi-level technique is numerically validated using real-world, minute-level, normalized, and anonymized nodal data at PJM service territory.

behind the meter solar, load disaggregation, load ↗

Extracting and Generating PV Soiling Profiles for Analysis, Forecasting, and Cleaning Optimization

The identification and prediction of the daily soiling profiles of a photovoltaic site is essential to plan the optimal cleaning schedule. In this article, we analyze and propose various methods to extract and generate photovoltaic soiling profiles, in order to improve the analysis and the forecast of the losses. New soiling rate extraction methods are proposed to reflect the seasonal variability of the soiling rates and, for this reason, are found to identify the most convenient cleaning day with the highest accuracy for the investigated sites. Also, we present an approach that could be used to predict future soiling losses through the implementation of stochastic weather generation algorithms whose ability to identify in advance the best cleaning schedule is also successfully tested. The methods presented in this article can optimize the operation and maintenance schedule and could make it possible, in the future, to predict soiling losses through analysis based only on environmental parameters, such as rainfall and particulate matter, without the need of long-term soiling data.

14 SOLAR ENERGY↗

A Stochastic Framework for Estimating Load Profiles at EV Fast Charging Stations

This paper formulates a methodology for estimating the average daily load profiles of EV fast charging stations over a planning horizon of five to ten years. The developed methodology uses historic vehicle registration data, state-level EV adoption targets, seasonal driving patterns, local demographics, competition, and traffic volume information to predict average station usage. Through Monte Carlo simulations, an average daily load profile is obtained for each month in the planning horizon, and prediction uncertainty is quantified. The proposed framework will facilitate the accurate estimation of energy and demand costs incurred by the charging station over the planning period, thereby informing return-on-investment calculations.

Biswas, Shuchismita↗

Influence of Heat Treatments on the Near-Surface Tritium Concentration Profiles

Austenitic stainless steel, type 316, absorbs significant quantities of tritium into the near surface (<1 μm) on exposure to tritium containing gases at room temperature. The tritium concentrations that develop in the near-surface region (<1 μm) are shown to persist for several years without changing. The current work shows the effect of heat treatments on the near-surface tritium-concentration profiles in stainless steel. Identical stainless-steel samples were exposed to tritium at room temperature and then were heated to different temperatures between 100 and 300°C for two hours under a stagnant argon atmosphere. After this initial preheating, the concentration profiles in the first 10 μm were measured by using a combination of a ZnCl2 wash and an etching procedure. Tritium was thermally released by heating the samples to 550°C to measure the residual tritium present in the bulk of the sample. The data show two dominant features. First, preheating causes tritium to migrate both out of the sample and deeper than >1 μm into the bulk. Furthermore, this effect increases with increasing temperature. Second, depletion of tritium from the near surface does not occur until a temperature of 200°C.

36 MATERIALS SCIENCE↗