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Here, the Chebyshev Rational Approximation Method (CRAM) algorithm has become the method of choice for modern nuclear depletion calculations. A simple modification of the CRAM yields not only depleted nuclide amounts but also time-averaged nuclide amounts, with little additional calculation cost.
Future, high-fidelity simulations of multi-GeV-class laser Wakefield accelerators (LWFAs) will need to model the propagation of high-intensity laser drivers over meter-scale plasmas with high spatial and temporal resolutions, thus requiring high amounts of computational resources. Various techniques have been devised over the years to reduce the computational cost of such simulations, including the time-averaged ponderomotive approximation, and the use of the Lorentz boosted frame technique. In this paper we discuss the combination of these two computational techniques, highlighting the resulting significant reduction in the computational cost of LWFA simulations and the limitations of this approach. The combination of the two techniques can potentially become essential for the modeling of a multi-TeV, LWFA-based collider.
Time-Averaged "Slow" Carbon Dioxide Flux Data from wind and gas files, with additional diagnostic data: 22m samples
Time-Averaged "Slow" Carbon Dioxide Flux Data from wind and gas files, with additional diagnostic data: 40m samples
Time-Averaged "Slow" Carbon Dioxide Flux Data from wind and gas files, with additional diagnostic data: 45m samples
A new integrating model has been developed to couple tokamak edge multiscale magnetohydrodynamic (MHD) events and transport simulations, such as edge-localized mode (ELM) cycles. As a proof of principle, we first start from a set of three-field two-fluid model equations, which includes the pressure, current, and vorticity. Here, the equations are separated into the slowly evolving part of the axisymmetric component by taking a time average of the axisymmetric component. The time-averaged fluxes, which are quadratic in fluctuating quantities, act as driven terms for the time-averaged axisymmetric quantities that determine the plasma transport, and therefore the large-scale evolution of the plasma profiles. Then the HL-2A's ELM cycles are simulated using the model. Good agreements of ELM size and pedestal recovery time have been achieved for the solutions obtained from the coupled simulation compared with experiment. For one ELM cycle simulation, the coupled code can achieve a speedup of a factor of up to 30 over standalone code.
This dataset contains microseismic data acquired during the Frisco pad flow test project led by Fervo Energy, conducted between July 17th - Aug 12th 2024, near the Utah FORGE geothermal site. The microseismic data was collected from various Utah FORGE wells: via Distributed Acoustic Sensing (DAS) fiber in 16B, and two 3-component geophones located in wells 56-32 and 78B. The dataset is structured in SEGY format, where the first six traces represent data from the geophones, and the remaining traces capture DAS data from well 16B. Each SEGY file in this dataset contains triggered microseismic events, with event initiation based on Short-Time Average over Long-Time Average (STA/LTA) detection criteria during the stimulation process. Files are grouped by time intervals and named following the structure "[WellPad][WellName][Month]_[Year]Divine_Trigger[EventNumber].sgy," indicating well pad, well name, date, and event number. Sampling parameters include a spatial sampling of approximately 2 meters for DAS channels and a temporal sampling rate of 2000 Hz, with each data record spanning 1.2 seconds. The files' coordinates are referenced to the location of the FORGE 16A-32 wellhead, positioned at UTM coordinates: Easting 334641.1891 m and Northing 4263443.693 m. The geographic coordinates for this origin are 38.50402147 latitude and -112.8963897 longitude, with an elevation of 1650.0249 meters above sea level.
This dataset contains microseismic data acquired during the Frisco 2-P well stimulation project led by Fervo Energy, conducted between June 1 and June 11, 2024, near the Utah FORGE geothermal site. The microseismic data was collected from various Utah FORGE wells: via Distributed Acoustic Sensing (DAS) fiber in 16B, and three 3-component geophones located in wells 56-32, 78B, and 32. The dataset is structured in SEGY format, where the first nine traces represent data from the geophones, and the remaining traces capture DAS data from well 16B. Each SEGY file in this dataset contains triggered microseismic events, with event initiation based on Short-Time Average over Long-Time Average (STA/LTA) detection criteria during the stimulation process. Files are grouped by time intervals and named following the structure "[WellPad][WellName][Month]_[Year]Divine_Trigger[EventNumber].sgy," indicating well pad, well name, date, and event number. Sampling parameters include a spatial sampling of approximately 2 meters for DAS channels and a temporal sampling rate of 2000 Hz, with each data record spanning 1.2 seconds. The files' coordinates are referenced to the location of the FORGE 16A-32 wellhead, positioned at UTM coordinates: Easting 334641.1891 m and Northing 4263443.693 m. The geographic coordinates for this origin are 38.50402147 latitude and -112.8963897 longitude, with an elevation of 1650.0249 meters above sea level.
Many models of the atmosphere simulate vertical profiles of observable fields, such as temperature, moisture, and vertical velocity. To assess the realism of such model output, it is important to evaluate the modeled profiles against observations. However, many extant evaluations consist of comparing time averaged profiles from the model and the observations. Such time averages can smooth out unrealistic features that appear in instantaneous profiles. In this way, the time averages may obscure certain model errors from detection. For instance, many models misrepresent turbulent processes, leading to profiles that are too smoothed out or too noisy. E.g., if a model has coarse vertical resolution and overly strong diffusion, then the model may be unable to produce observed sharp peaks. On the other hand, a model may have artificial approximations that produce spurious jumps in the vertical. Much can be learned by browsing through instantaneous snapshots of model output. But the volume of output produced by a global model is far too great to rely purely on visual inspection. In addition, we need a way to statistically characterize the profiles, so that anomalies can be detected more conveniently.
Atmospheric processes over the Southern Ocean have a profound influence on regional and global climate. This is a part of the world where global climate models perform particularly poorly, with models persistently overpredicting the amount of sunlight reaching the Earth's surface (Regayre et al. 2020). A major challenge when trying to improve the representation of atmospheric processes in this part of the globe is the scarcity of observations capable of constraining our understanding. During 2024/25 a U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility field campaign (CAPE-k) deployed a suite of instrumentation at the kennaook/Cape Grim atmospheric monitoring station in Tasmania, Australia to provide detailed cloud-aerosol observations in this region in order to address the greatest source of uncertainty in climate models – atmospheric aerosols and how they influence cloud formation (Carslaw et al. 2013). In support of the ARM observations, an Australian Research Council (ARC)-funded project “Southern Ocean aerosols: sources, sinks and impact on cloud properties,” led by the Queensland University of Technology, complemented the ARM measurements with a suite of chemical measurements at the kennaook/Cape Grim site in northwestern Tasmania to provide more information on the processes controlling aerosol formation and growth. The deployment of the University of York LIF-SO2 instrument (Temple et al. 2025) in the ARM mobile facility container was part of this chemistry-focused deployment. Increased observational efforts are critical for understanding sources and sinks of Southern Ocean aerosols, in particular the role of marine micro-organisms (phytoplankton, algae) on aerosols formation, their properties and growth, cloud droplet formation, and the conversion of cloud droplets to ice crystals and precipitation. The observational focus of the ARC-funded project is aerosol chemical composition and their gaseous precursors. The remote nature of the Southern Ocean poses a significant analytical challenge when studying gaseous precursors, as low concentrations are often below the limits of detection of commercial instrumentation. Historically this has meant that observations have had to be time-averaged over days to weeks to achieve the limits of detection required. Although useful when considering overall average levels of aerosol precursors, this time-averaging obscures temporal variability that can provide insight into the controlling processes. Over recent years advances in analytical techniques have made high-time-resolution measurements of key gas-phase aerosol precursors achievable with sufficiently low limits of detection.
Active galactic nuclei (AGN) are prime candidate sources of the high-energy, astrophysical neutrinos detected by IceCube. This is demonstrated by the real-time multimessenger detection of the blazar TXS 0506+056 and the recent evidence of neutrino emission from NGC 1068 from a separate time-averaged study. However, the production mechanism of the astrophysical neutrinos in AGN is not well established, which can be resolved via correlation studies with photon observations. For neutrinos produced due to photohadronic interactions in AGN, in addition to a correlation of neutrinos with high-energy photons, there would also be a correlation of neutrinos with photons emitted at radio wavelengths. In this work, we perform an in-depth stacking study of the correlation between 15 GHz radio observations of AGN reported in the MOJAVE XV catalog, and 10 yr of neutrino data from IceCube. We also use a time-dependent approach, which improves the statistical power of the stacking analysis. No significant correlation was found for both analyses, and upper limits are reported. When compared to the IceCube diffuse flux, at 100 TeV and for a spectral index of 2.5, the upper limits derived are ~3% and ~9% for the time-averaged and time-dependent cases, respectively.
TiSe 2 is a narrow-gap insulator with a rich array of unique properties. In addition to being a superconductor under certain modifications, it is commonly thought to be a rare realisation of an excitonic insulator. Below 200 K, TiSe 2 undergoes a transition from a high-symmetry ($P\bar{3}m1$) phase to a low-symmetry ($P\bar{3}c1$) charge density wave (CDW). Here we establish that it is indeed an insulator in both $P\bar{3}m1$ and $P\bar{3}c1$ phases. However, the insulating state is driven not by excitonic effects but by symmetry-breaking. In the CDW phase it is static. At high temperature, thermally driven instantaneous deviations from $P\bar{3}m1$ break the symmetry on the characteristic time scale of a phonon. Even though the time-averaged lattice structure assumes $P\bar{3}m1$ symmetry, the time-averaged energy band structure is closer to the CDW phase - a rare instance of a metal-insulator transition induced by dynamical symmetry breaking. We establish these conclusions from quasiparticle self-consistent GW (QSGW) and many-body calculations (QS$G\widehat{W}$), in combination with molecular dynamics simulations to capture the effects of thermal disorder. The many-body theory includes explicitly ladder diagrams in the polarizability, which incorporates excitonic effects in an ab initio manner. We find that the excitonic modification to the potential is weak, ruling out the possibility that TiSe 2 is an excitonic insulator.
Parametric large eddy simulations (LES) of a supersonic lifted hydrogen flame are reported. The emphases are on two aspects: impacts of (1) Lewis number (Lei of the ith species) and (2) turbulent Schmidt and Prandtl numbers (Sc t and Pr t ) on supersonic turbulent flame and flow structures. Five cases are considered: species-specific Le i , Sc t = Sr t = 1.0 (C 0 ); unity Le i , Sc t = Pr t = 1.0 (C 1 ); species-specific Sc t = 0.5, Pr t = 1.0 (C 2 ); species-specific Le i , Sc t = 1.0, Pr t = 0.5 (C 3 ); and species-specific Le i , Sc t = Pr t = 0.5 (C 4 ). Numerical results of instantaneous and/or time-averaged species mole fractions, mixture fraction, heat release rate, flame base location, and mixed modes of premixed and diffusion combustion are compared between cases C 0 and C 1 . Differences in auto-ignition locations and strengths and flame structures and stabilization specify the impacts of Lewis number. They are triggered by different predictions of species mass and thermal diffusions at fuel-coflow and/or coflow-ambient air mixing layers. These differences are rationalized by a scale analysis of mass/thermal diffusion and convection for case C 0 , which suggests the relatively low but non-negligible former against the latter. Cases C 0 and C 2 –C 4 barely see differences in terms of instantaneous and/or time-averaged temperature, velocity, and mixed combustion modes except for further downstream areas where combustion occurs. Both Sc t and Pr t impose less significant influences than Lewis number, as sub-grid scale mass/thermal diffusion is subordinate to its resolved counterpart according to their scale analysis for case C 4 .
The Contractor will build a liquid hydrogen (LH2) fueling station model that is capable of simulating the amount of hydrogen transferred from the liquid storage tank to the vehicle, depending on the station’s design and control scheme. This modeling work will allow the Parties to seek the design and control scheme of an LH2 station that can fill a targeted number of vehicles while meeting a time-average flow rate of 10 kg/min for each fill. While evaluating a high dispensing performance station design and control scheme, the Contractor will analyze the design and control scheme are economically viable.
We analyze particle number fluctuations in the crossover region near the critical endpoint of a first-order phase transition by utilizing molecular dynamics simulations of the classical Lennard-Jones fluid. We extend our previous study [V. A. Kuznietsov , ] by incorporating longitudinal collective flow. The scaled variance of particle number distribution inside different coordinate and momentum space acceptances is computed through ensemble averaging and found to agree with earlier results obtained using time averaging, validating the ergodic hypothesis for fluctuation observables. Presence of a sizable collective flow is found to be essential for observing large fluctuations from the critical point in momentum space acceptances. We discuss our findings in the context of heavy-ion collisions. Published by the American Physical Society 2024
Per- and polyfluoroalkyl substances (PFAS) are a group of industrial and commercial chemicals widely used throughout the world due to their beneficial chemical properties. Because of their widespread use, their chemical stability, and their ability to be transported over long distances through atmospheric deposition and movement through waterways, PFAS are found throughout most aquatic ecosystems; yet large sampling gaps exist among reservoir and river ecosystems in the desert southwest of the United States. In this study, we examine PFAS concentrations in the tissue of fish (catfish [channel and blue], common carp, smallmouth bass, northern pike, walleye, white crappie and white sucker) collected in northern New Mexico, including examining PFAS composition and concentration relative to trophic level distribution. We collected fish from two man-made reservoirs and from the Rio Grande. We then collected muscle and liver tissues from fish specimens, which were screened for 39 PFAS compounds. We detected PFAS compounds in most fish tissue sampled, including the biomagnification of PFAS compounds within liver samples, with PFOS concentrations ranged from 1.13 to 350.1 (64.4 average) times higher in the liver samples compared to muscle samples. Most PFAS concentrations within muscle samples were within the range of atmospheric transportation previously reported and average tissue concentrations of PFAS were calculated to be 2.02 ± 1.81 ng g -1 . Using stable isotopes as a predictor of trophic-foraging exposure and PFAS concentrations, we noted a correlation between enriched δ 15 N values, which had higher perfluorodecanoic acid concentrations.
A privacy-preserving average consensus algorithm is designed based on the Beaver triple technique against passive adversaries. The Beaver triple technique is integrated into a restructure of the discrete-time average consensus algorithm to preserve the privacy of initial values of agents in a multiagent system. The performance of the algorithm is theoretically analyzed.
X-ray reverberation, which exploits the time delays between variability in different energy bands as a function of Fourier frequency, probes the structure of the inner accretion disks and X-ray coronae of active galactic nuclei. We present a systematic X-ray spectroscopic and reverberation study of the high-Eddington-ratio narrow-line Seyfert 1 galaxy Ark 564, using over 900 ks of XMM-Newton and NuSTAR observations spanning 13 yr. The time-averaged spectra can be well described by a model consisting of a coronal continuum, relativistic disk reflection, warm Comptonization, and three warm absorbers. Leveraging the high X-ray brightness of Ark 564, we are able to resolve the time evolution of the spectra and contemporaneous reverberation lags. The soft-band lag relative to the continuum increases with the X-ray flux, while Fe Kα lags are detected in only a subset of epochs and do not correlate with soft lags. Models based on a lamppost corona and reflection from a standard thin disk can broadly reproduce the observed lag-energy spectra of low-flux epochs; however, additional reverberation from the warm Comptonized atmosphere is required to explain the soft lags observed in high-flux epochs. A vertically puffed-up inner disk and a variable, vertically extended corona can better explain the observed evolution of the lags and covariance spectra. Our study underscores the importance of multiepoch, multiband analyses for a comprehensive understanding the inner accretion disk and corona.