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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Characterization of Build Parameters and Microstructure in Low Heat Input WAAM of Ni-Based Superalloy Haynes 282

Ni-based superalloy Haynes® 282® is being targeted for various applications in advanced power generation systems for its superior fabricability, weldability, and excellent high temperature creep and corrosion performance. This process optimization study aims to use a low heat-input, high deposition rate, controlled Gas Metal Arc Welding (GMAW) process, Cold Metal Transfer (CMT) by Fronius, attempting to achieve fully dense fabrication and possibly avoid the need for HIP. Twenty-one multilayer blocks (~25x100x40 mm3) were deposited to explore a large set of build parameters variations that focused on varying the travel speed from 14 to 42 inches per minute (ipm) and wire feed speed from 150 to 450 ipm. A strong correlation has been observed between arc energy – controlled primarily by travel and wire feed speed. Initial visual inspection, internal microstructural examination, and computed tomography (CT) have been used to determine the effects of built parameters on evolution of internal porosity and defects. Scanning electron microscopy techniques enabled structural and compositional imaging of heterogeneity and changes in microstructural properties.

additive manufacturing↗
DOE OSTI2025

2025 Status Report - Fiberboard Properties and Degradation Rates for Storage of 9975 Shipping Package in KAC

Fiberboard assemblies in the 9975 package were identified as susceptible to aging and degradation under long-term storage conditions. Thermal, mechanical, and physical properties have been measured on fiberboard samples aging for up to 20 years at accelerated conditions. The aging environments include elevated temperature up to 250 ºF (the maximum allowed service temperature for fiberboard in 9975 packages) and elevated humidity. Accelerated aging results have been analyzed and used to build aging models. Correlations relating several properties (thermal conductivity, energy absorption, weight, dimensions, and density) to their rate of change in potential storage environments have been developed. Combined with an estimate of the actual conditions the fiberboard experiences in K-Area Complex (KAC), these models allow development of service life predictions. KAC completed calculations that supported extending the service life of 9975 packages with 3013 containers in storage from 20 years to 40 years. These calculations addressed the potential for degraded fiberboard properties following 40 years in storage using degradation models. The 40 year storage evaluations assumed the degradation rates from initial values for density, dimensional, and thermal properties were 0.5% per year (i.e., after 40 years, the density, dimensional, and thermal properties of fiberboard were 80% of its initial values). The updated degradation models developed in this report were compared to the assumptions in those calculations, and the current results for fiberboard dimensions, density, axial and radial thermal conductivities, and energy absorption remain consistent with those calculations. Additional data will continue to be collected to permit future refinements to the models and assumptions. Some of the predicted degradation rates presented in this report are purposely high to accelerate aging. These rates relate to environments that do not exist within KAC or are postulated to only occur as upset conditions that are unlikely to persist for an extended period. For a typical package stored in KAC with approximately 10-12 watts internal heat load or less, and ambient temperatures below 90 ºF, the fiberboard assemblies experience storage conditions less severe than any of the aging environments (i.e., under 125 °F) used in this study. Fiberboard in conforming packages with lower internal heat loads should experience little or no degradation and is expected to provide a service life beyond the currently approved 40 year storage period. Packages with higher internal heat loads may not continue to perform their required safety functions beyond 40 years. Ultimately, service life will be determined by the cumulative effect of degradation from all the conditions these packages might encounter. The results and model predictions presented in this report are applicable to 9975 packages with cane or softwood fiberboard overpack assemblies. These degradation models do not address the effects of nonconforming conditions such as the presence of excess moisture and mold or beetle infestations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Surface Energy Balance System (SEBS) Instrument Handbook

A surface energy balance system (SEBS) has been installed collocated with each deployed eddy correlation flux measurement system (ECOR) after 2010 at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility Southern Great Plains (SGP) observatory, North Slope of Alaska (NSA) observatory, Eastern North Atlantic (ENA) observatory, and the first, second, and third ARM Mobile Facilities (AMF1, AMF2, AMF3). A SEBS was also deployed at the Tropical Western Pacific (TWP) site, before it was decommissioned. Data from these sites, including the retired TWP, are available in the ARM Data Center. The SEBS consists of upwelling and downwelling solar and infrared radiometers within one net radiometer, a wetness sensor, and soil temperature, soil moisture, and soil heat flow measurements. The SEBS measurements allow the comparison of ECOR sensible and latent heat fluxes with the energy balance determined from the SEBS and provide information on wetting of the sensors for data quality purposes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Grid Value Propositions for Tidal Generation Resources - a Temporal Analysis

As the energy sector experiences a paradigm shift towards cleaner and greener generation sources, the need for evaluating the applicability of marine energy for grid-based applications has intensified. This is because marine energy (ocean, wave and tidal) may be utilized to provide unique benefits to electric grid operations, especially in conjunction with other established renewable technologies (such as wind and solar) or technologies like energy storage. In this work, we focus our attention on some specific characteristics of two types of marine energy resources i.e. tidal and ocean current based resources. Specifically, we perform a comprehensive temporal analysis using a suite of metrics on resource data to characterize the inherent predictability of the resource across various time scales of interest. We also investigate the correlation of tidal power generation profiles with energy demand and comment on the effectiveness of having such resources in the overall generation portfolio.

Bhattacharya, Saptarshi↗
DOE OSTI2023

Constraining High-energy Neutrino Emission from Supernovae with IceCube

Core-collapse supernovae are a promising potential high-energy neutrino source class. We test for correlation between seven years of IceCube neutrino data and a catalog containing more than 1000 core-collapse supernovae of types IIn and IIP and a sample of stripped-envelope supernovae. We search both for neutrino emission from individual supernovae as well as for combined emission from the whole supernova sample, through a stacking analysis. No significant spatial or temporal correlation of neutrinos with the cataloged supernovae was found. All scenarios were tested against the background expectation and together yield an overall p-value of 93%; therefore, they show consistency with the background only. The derived upper limits on the total energy emitted in neutrinos are 1.7 × 10 48 erg for stripped-envelope supernovae, 2.8 × 10 48 erg for type IIP, and 1.3 × 10 49 erg for type IIn SNe, the latter disfavoring models with optimistic assumptions for neutrino production in interacting supernovae. We conclude that stripped-envelope supernovae and supernovae of type IIn do not contribute more than 14.6% and 33.9%, respectively, to the diffuse neutrino flux in the energy range of about [ 10 3 –10 5 ] GeV, assuming that the neutrino energy spectrum follows a power-law with an index of –2.5. Under the same assumption, we can only constrain the contribution of type IIP SNe to no more than 59.9%. Thus, core-collapse supernovae of types IIn and stripped-envelope supernovae can both be ruled out as the dominant source of the diffuse neutrino flux under the given assumptions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

A Framework for Characterizing the Initial Thermal Conditions of Light-Duty Vehicles in Response to Representative Utilization Patterns, Ambient Conditions, and Vehicle Technologies

It is widely understood that the thermal state of a light-duty vehicle at the beginning of a trip influences the vehicle performance throughout the drive cycle. Cold starts, or initial states with component temperatures near ambient conditions, are strongly correlated with reduced vehicle performance and energy efficiency and with increased emissions. Despite this understanding, there is little literature available that characterizes initial thermal states beyond empirical studies and simplified analyses of dwell times. We introduce a framework that considers vehicle activity patterns, including the previous drive event, duration of the previous dwell event, and relevant ambient conditions occurring during these events. Moreover, the framework allows for technologies to influence the prominence of cold starts and warm starts. An example application of the methodology using a powertrain model approach revealed the significance of all constituent factors: controlling for ambient conditions, the shortest dwell lengths corresponded to an average initial oil temperature of 70°C versus 23°C for the long dwell length simulations, and aggressive conditioning cycles corresponded to an average initial oil temperature of 51°C versus only 35°C for a short conditioning cycle. The coldest ambient conditions evaluated (-30°C to -10°C) produced a weighted initial oil temperature of 19°C versus 57°C for the warmest ambient conditions evaluated (30°C to 50°C). Finally, we introduce weighting factors that account for the real-world frequency of conditioning cycle and dwell length combinations. The procedure outlined may be useful for discovering real-world performance improvements associated with vehicle technologies, a topic of interest to both vehicle manufacturers and regulators.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Techno-Economic Analysis of Biofuel Production via Catalytic Upgrading of Carbohydrates in Paper Sludge

A full-plant model was developed using correlations from a rigorous mass and energy balance and based on experimental results to determine the MFSP and its Sensitivity Analysis in the production of a hydrocarbon product from Paper Sludge. In this base case a preliminary MFSP of $5.97/GGE has been determined. This value is higher than the results reported in recent NREL reports. The difference is explained since much larger capacity plants are considered in those reports, and because we are not considering the production of co-products that bring the fuel costs down. The obtained model is being used to guide the next steps in our laboratory work since the team is now aware of which are the more sensitive process parameters "impacting" the MFSP of the final product.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Water reflection analysis of encapsulated photovoltaic modules

A method for moisture testing of a fully assembled photovoltaic (PV) module. An assembled PV module is probed with short wave IR probe energy in the range of 1700-2000 nm. Energy reflected from the assembled PV module is collected and directed to a sensor. Noise is removed from a signal of the sensor with reference to the probe energy. Absorption is of the probe energy is determined. The absorption is correlated to moisture in the PV module. A preferred system that carries out the method provides a signal-to-noise ratio (as defined by standard deviation/mean of measured reflectance) of at least 3800.

Fenning, David↗
DOE OSTI2020

Exploring Hilbert space on a budget: Novel benchmark set and performance metric for testing electronic structure methods in the regime of strong correlation

This work explores the ability of classical electronic structure methods to efficiently represent (compress) the information content of full configuration interaction (FCI) wave functions. We introduce a benchmark set of four hydrogen model systems of different dimensionalities and distinctive electronic structures: a 1D chain, a 1D ring, a 2D triangular lattice, and a 3D close-packed pyramid. To assess the ability of a computational method to produce accurate and compact wave functions, we introduce the accuracy volume, a metric that measures the number of variational parameters necessary to achieve a target energy error. Using this metric and the hydrogen models, we examine the performance of three classical deterministic methods: (i) selected configuration interaction (sCI) realized both via an a posteriori (ap-sCI) and variational selection of the most important determinants, (ii) an a posteriori singular value decomposition (SVD) of the FCI tensor (SVD-FCI), and (iii) the matrix product state representation obtained via the density matrix renormalization group (DMRG). We find that the DMRG generally gives the most efficient wave function representation for all systems, particularly in the 1D chain with a localized basis. For the 2D and 3D systems, all methods (except DMRG) perform best with a delocalized basis, and the efficiency of sCI and SVD-FCI is closer to that of DMRG. For larger analogs of the models, the DMRG consistently requires the fewest parameters but still scales exponentially in 2D and 3D systems, and the performance of SVD-FCI is essentially equivalent to that of ap-sCI.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

On the minimum number of radiation field parameters to specify gas cooling and heating functions

Fast and accurate approximations of gas cooling and heating functions are needed for hydrodynamic galaxy simulations. We use machine learning to analyze atomic gas cooling and heating functions in the presence of a generalized incident local radiation field computed by Cloudy. We characterize the radiation field through binned radiation field intensities instead of the photoionization rates used in our previous work. We find a set of 6 energy bins whose intensities exhibit relatively low correlation. We use these bins as features to train machine learning models to predict Cloudy cooling and heating functions at fixed metallicity. We compare the relative SHapley Additive exPlanation (SHAP) value importance of the features. From the SHAP analysis, we identify a feature subset of 3 energy bins (0.5-1, 1-4, and 13-16Ry) with the largest importance and train additional models on this subset. We compare the mean squared errors and distribution of errors on both the entire training data table and a randomly selected 20% test set withheld from model training. The machine learning models trained with 3 and 6 bins, as well as 3 and 4 photoionization rates, have comparable accuracy everywhere, with errors ≳10 times smaller than for the interpolation table of Gnedin and Hollon (2012). We conclude that 3 energy bins (or 3 analogous photoionization rates: molecular hydrogen photodissociation, neutral hydrogen HI, and fully ionized carbon CVI) are sufficient to characterize the dependence of the gas cooling and heating functions on our assumed incident radiation field model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

On the minimum number of radiation field parameters to specify gas cooling and heating functions

Fast and accurate approximations of gas cooling and heating functions are needed for hydrodynamic galaxy simulations. We use machine learning to analyze atomic gas cooling and heating functions computed by Cloudy in the presence of a generalized incident local radiation field. We characterize the radiation field through binned radiation field intensities instead of the photoionization rates used in our previous work. We find a set of 6 energy bins whose intensities exhibit relatively low correlation. We use these bins as features to train machine learning models to predict Cloudy cooling and heating functions at fixed metallicity. We compare the relative SHapley Additive exPlanation (SHAP) value importance of the features. From the SHAP analysis, we identify a feature subset of 3 energy bins ($0.5-1, 1-4$, and $13-16 \, \mathrm{Ry}$) with the largest importance and train additional models on this subset. We compare the mean squared errors and distribution of errors on both the entire training data table and a randomly selected 20% test set withheld from model training. The machine learning models trained with 3 and 6 bins, as well as 3 and 4 photoionization rates, have comparable accuracy everywhere, with errors $\gtrsim 10$ times smaller than for the interpolation table of Gnedin and Hollon (2012). We conclude that 3 energy bins (or 3 analogous photoionization rates: molecular hydrogen photodissociation, neutral hydrogen HI, and fully ionized carbon CVI) are sufficient to characterize the dependence of the gas cooling and heating functions on our assumed incident radiation field model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Density functional study of atomic arrangements in CrMnFeCoNi high-entropy alloy and their impact on vacancy formation energy and segregation

Here, using the density functional theory-coupled Monte Carlo approach, we explored the chemical short-range order (SRO) and element segregation in equimolar CrMnFeCoNi alloy. We found that state-of-the-art approximation of random element distribution is only applicable at > 1100 K close to the melting temperature, while the Cr-Cr repulsion driving the system stabilization and accompanying the formation of cubic Cr sublattice, and mild Ni-Ni attraction are the most prominent pair interactions at lower temperatures. Chemical potential and vacancy formation energy calculations indicate that Cr is most sensitive to the local chemical environment, making Cr atoms most stabilized when the preferred SRO is introduced. While the vacancy formation is predicted equally probable among five constituting elements in the random solid solution, Cr and Ni atoms show the lowest vacancy formation energies in the structure with SRO. Furthermore, distinct element segregation was predicted in the vicinity of planar defects, including symmetric tilt grain boundary and stacking fault, which we correlated to the site- and chemistry-dependent atomic volume and bond lengths. It suggests that the local mechanical strain and bond energy induce the SRO development and element segregation: Namely, the system takes advantage of segregation of Ni atoms having large atomic volume or Cr-Cr pairs having elongated bond lengths to fill in the excess volume at defects that relaxes the mechanical strain field and optimizes bond energy distribution. The correlation between the SRO and properties of CrMnFeCoNi alloy needs further investigations, which is expected to greatly help understand and control the properties of high-entropy alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Precision Kinematic Sunyaev--Zel'dovich Measurements Across Halo Mass and Redshift with DESI DR2 and ACT DR6: Part I. Luminous Red Galaxies

We present the most precise measurements of the kinetic Sunyaev-Zel'dovich (kSZ) effect around luminous red galaxies to date, detecting the signal at $18σ$ significance in both harmonic and configuration space. Our analysis cross-correlates 2.4 million spectroscopic LRGs from the Dark Energy Spectroscopic Instrument (DESI) DR2 sample with Data Release 6 (DR6) of the Atacama Cosmology Telescope (ACT). We develop a novel harmonic-space cross-correlation approach using momentum-weighted kSZ templates, yielding nearly uncorrelated bandpowers within a framework consistent with other large-scale structure analyses. By incorporating the LRG halo occupation distribution (HOD) and its uncertainty, we convert measured galaxy gas profiles into halo gas profiles and provide generalized Navarro-Frenk-White (GNFW) fitting profiles, providing empirical targets for tuning feedback efficiency in hydrodynamical simulations and for baryonic modeling in large-scale structure analyses. We find strong evidence that gas profiles do not trace dark matter, providing direct evidence for gas redistribution beyond gravitational collapse. Comparing to hydrodynamical simulations, our measurements favor feedback efficiencies exceeding those in the Battaglia profile, suggesting more efficient gas ejection in group-scale halos than previously predicted. Splitting by redshift, we detect the kSZ signal at SNR $\approx 5$--$10$ in each of four bins and find amplitude evolution consistent with the expected decline in mean halo mass at fixed comoving number density. Splitting by stellar mass, we study the scaling of kSZ amplitude with galaxy properties. Together with BGS and ELG measurements in Paper II, these results span $0.1 \lesssim z \lesssim 1.6$ across three galaxy populations, demonstrating the potential of spectroscopic kSZ to map circumgalactic gas and constrain baryonic feedback.

Qu, F. J. [KIPAC, Menlo Park; Stanford U., HEPL; S↗
DOE OSTI2022

Tracer-field cross-correlations with k -nearest neighbour distributions

ABSTRACT In astronomy and cosmology significant effort is devoted to characterizing and understanding spatial cross-correlations between points – e.g galaxy positions, high energy neutrino arrival directions, X-ray and AGN sources, and continuous fields – e.g. weak lensing meiand Cosmic Microwave Background maps. Recently, we introduced the k-nearest neighbour (kNN) formalism to better characterize the clustering of discrete (point) data sets. Here, we extend it to the point – field cross-correlations analysis. It combines kNN measurements of the point data set with measurements of the field smoothed at many scales. The resulting statistics are sensitive to all orders in the joint clustering of the points and the field. We demonstrate that this approach, unlike the 2-pt cross-correlation, can measure the statistical dependence of two data sets even when there are no linear (Gaussian) correlations between them. We further demonstrate that this framework is far more effective than the two point function in detecting cross-correlations when the continuous field is contaminated by high levels of noise. For a particularly high level of noise, the cross-correlation between haloes and the underlying matter field in a cosmological simulation, between 10 h−1 Mpc and 30 h−1 Mpc, is detected at >5σ significance using the technique presented here, when the two-point cross-correlation significance is ∼1σ. Finally, we show that kNN cross-correlations of haloes and the matter field can be well modelled on quasi-linear scales using the Hybrid Effective Field Theory (HEFT) framework, with the same set of bias parameters as are used for 2-pt cross-correlations. The substantial improvement in the statistical power of detecting cross-correlations using this method makes it a promising tool for various cosmological applications.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

On Alfvénic turbulence of solar wind streams observed by Solar Orbiter during March 2022 perihelion and their source regions

It has been recently accepted that the standard classification of the solar wind solely according to flow speed is outdated, and particular interest has been devoted to the study of the origin and evolution of so-called Alfvénic slow solar wind streams and to what extent such streams resemble or differ from fast wind. In March 2022, Solar Orbiter completed its first nominal phase perihelion passage. During this interval, it observed several Alfvénic streams, allowing for characterization of fluctuations in three slow wind intervals (AS1-AS3) and comparison with a fast wind stream (F) at almost the same heliocentric distance. This work makes use of Solar Orbiter plasma parameters from the Solar Wind Analyzer (SWA) and magnetic field measurements from the magnetometer (MAG). The magnetic connectivity to the solar sources of selected solar wind intervals was reconstructed using a ballistic extrapolation based on measured solar wind speed down to the (spherical) source surface at 2.5 R s below which a potential field extrapolation was used to map back to the Sun. The source regions were identified using SDO/AIA observations. A spectral analysis of in situ measured magnetic field and velocity fluctuations was performed to characterize correlations, Alfvénicity, normalized cross-helicity, and residual energy in the frequency domain as well as intermittency of the fluctuations and spectral energy transfer rate estimated via mixed third-order moments. A machine learning technique was used to separate proton core, proton beam, and alpha particles and to study v − b correlations for the different ion populations in order to evaluate the role played by each population in determining the Alfvénic content of solar wind fluctuations. The comparison between fast wind and Alfvénic slow wind intervals highlights the differences between the two solar wind regimes: The fast wind is characterized by larger amplitude fluctuations, and magnetic and velocity fluctuations are closer to equipartition of energy. In fact the Alfvénic slow wind streams appear to be on a spectrum of wind types, with AS1, originating from open field lines neighboring active regions and displaying similarities with the fast wind in terms of fluctuation amplitude and turbulence characteristics, but not with respect to the alpha particles and proton beams. The other two slow streams differed both in their sources as well as plasma characteristics, with AS2 coming from the expansion of a narrow coronal hole corridor and AS3 from a region straddling a pseudostreamer. The latter displayed the coldest and highest density but the slowest stream with the smallest fluctuation amplitude and greatest magnetic energy excess. It also showed the largest scatter in proton beam speeds and the greatest difference in speed between proton beam and alpha particles. This study shows how the old fast–slow solar wind dichotomy, already called into question by the observations of slower Alfvénic solar wind streams, should further be refined, as the Alfvénic slow wind, originating in different solar wind regions, show significant differences in density, temperature, and proton and alpha-particle properties in the inner heliosphere. The observations presented here provide the starting point for a better understanding of the origin and evolution of different solar wind streams as well as the evolving turbulence contained within.

magnetohydrodynamics (MHD)↗
DOE OSTI2021

Correlated $\ n-γ$ angular distributions from the $\ Q$ = 4.4398 MeV 12 C ($\ n, n' γ$) reaction for incident neutron energies from 6.5 MeV to 16.5 MeV

Neutron scattering cross sections and angular distributions represent one of the most glaring sources of uncertainty in calculations of nuclear systems. Even simple nuclei like 12 C show indications of errors in nuclear databases for scattering reactions. Measurements of inelastic neutron scattering have historically measured either the scattered neutrons or the nuclear deexcitation $\ γ$ emission. Only a very small number of experiments attempted correlated measurements of both the neutron and $\ γ$ data simultaneously, even though these $\ n-γ$ correlations could be essential for understanding particle transport in nuclear systems. In this work we describe a measurement of the $\ n, γ$, and correlated $\ n-γ$ angular distributions from the $\ Q$ = 4.4398 MeV 12 C ($\ n, n'γ$) reaction in a single experiment using an EJ-309 liquid scintillator detector array with wide angular coverage, and with a continuous incident neutron energy range from 6.5 to 16.5 MeV. We also provide a thorough covariance description of these results, including normalization of the probability distribution. While the measured n distributions agree well with the relatively large number of available literature measurements, there are comparatively very few measurements of the γ distributions from this reaction. However, our data support the presence of a nonzero α 4 Legendre polynomial component of the γ angular distribution suggested in past measurements, which is currently not incorporated in the ENDF/B-VIII.0 library despite the use of these same literature data for evaluation of the 12 C ($\ n, n'γ$) cross section. The correlated $\ n-γ$ distribution measurements are limited to three measurements at incident neutron energies near 14 MeV. Our results do not generally agree with any of these literature measurements. We observe clear indications of significant changes in the $\ n$ distribution for specific $\ γ$-detection angles and vice versa especially near thresholds for other reaction channels, which shows the potential for significant bias in experiments that, for example, tag on inelastic scattering using a single or small number of $\ γ$ -detection angles and could impact particle transport calculations.

6 ≤ A ≤ 19↗
DOE OSTI2024

On the statistical theory of self-gravitating collisionless dark matter flow: High order kinematic and dynamic relations

Dark matter, if it exists, accounts for five times as much as ordinary baryonic matter. To better understand the self-gravitating collisionless dark matter flow on different scales, a statistical theory involving kinematic and dynamic relations must be developed for different types of flow, e.g., incompressible, constant divergence, and irrotational flow. This is mathematically challenging because of the intrinsic complexity of dark matter flow and the lack of a self-closed description of flow velocity. Here, this paper extends our previous work on second-order statistics Xu to kinematic relations of any order for any type of flow. Dynamic relations were also developed to relate statistical measures of different orders. The results were validated by N-body simulations. On large scales, we found that (i) third-order velocity correlations can be related to density correlation or pairwise velocity; (ii) the pth-order velocity correlations follow ∝ a (p+2)/2 for odd p and ∝ a p/2 for even p, where a is the scale factor; (iii) the overdensity δ is proportional to density correlation on the same scale, $\langle$δ$\rangle$∝$\langle$δδ'$\rangle$; (iv) velocity dispersion on a given scale r is proportional to the overdensity on the same scale. On small scales, (i) a self-closed velocity evolution is developed by decomposing the velocity into motion in haloes and motion of haloes; (ii) the evolution of vorticity and enstrophy are derived from the evolution of velocity; (iii) dynamic relations are derived to relate second- and third-order correlations; (iv) while the first moment of pairwise velocity follows $\langle$Δu L $\rangle$=-Har (H is the Hubble parameter), the third moment follows $\langle$(Δu L ) 3 $\rangle$ ∝ ε u ar that can be directly compared with simulations and observations, where ε u ≈ 10 -7 m 2 /s 3 is the constant rate for energy cascade; (v) the pth order velocity correlations follow ∝ a (3p-5)/4 for odd p and ∝ a 3p/4 for even p. Finally, the combined kinematic and dynamic relations lead to exponential and one-fourth power-law velocity correlations on large and small scales, respectively.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

The static energy in 2+1+1-flavor QCD

We report on the status of the analysis of the static energy in $2+1+1$-flavor QCD. The static energy is obtained by measuring Wilson line correlators in Coulomb gauge using the HISQ action, yielding the scales $r_{0}/a$, $r_{1}/a$, $r_{2}/a$, their ratios, and the string tension $\sigma r_{i}^{2}$. We put emphasis on the possible effects due to the dynamical charm-quark by comparing the lattice results to continuum results of the static energy with and without a massive flavor at two-loop accuracy. We employ gauge-field ensembles from the HotQCD and MILC Collaborations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗