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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Evaluation of the Quasi-Biweekly Oscillation over the South China Sea in Early and Late Summer in CAM5

Low-frequency intraseasonal oscillations in the tropical atmosphere in general circulation models (GCMs) were studied extensively in many previous studies. However, the simulation of the quasi-biweekly oscillation (QBWO), which is an important component of the intraseasonal oscillations, in GCMs has not received much attention. This paper evaluates the QBWO features over the South China Sea in early [May–June (MJ)] and late [August–September (AS)] summer in the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, version 5.3 (CAM5), using observations and reanalysis data. Results show that the major features of the spatial distribution of the QBWO in both MJ and AS are simulated reasonably well by the model, although the amplitude of the variation is overestimated. CAM5 captures the local oscillation in MJ and the westward propagation in AS of the QBWO. Although there are important biases in geographical location and intensity in MJ, the model represents the QBWO horizontal and vertical structure qualitatively well in AS. The diagnosis of the eddy vorticity budget is conducted to better understand the QBWO activities in the model. Both horizontal advection of relative vorticity and that of planetary vorticity (Coriolis parameter) are important for the local evolution of the QBWO in MJ in observations as well as model simulation, whereas advection of planetary vorticity contributes to the westward propagation of QBWO vorticity anomalies in AS. Since the Coriolis parameter f only changes with latitude, this suggests that the correct simulation of anomalous meridional wind is a key factor in the realistic simulation of the QBWO in the model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

NDA Tech: Multimodal Data Fusion with 3D Gamma-Ray Imaging for Safeguards

The ultimate project goal is to improve quantitative results obtained by the IAEA with the H420 gamma ray imager. Distribution to the IAEA will be through incorporation of project results into the software provided with the device by our commercial partner, H3D, Inc. Toward achieving that goal, we have started discussions with H3D to identify the requisite software components and how they will mesh with their own internally developed contextual data systems and other extant software components. We have identified the coded-aperture response data cube as a key structure. Discussions on contextual imaging were informative but somewhat inconclusive as the project lead on contextual data (LBNL) has not been available.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

The S-PLUS Fifth Data Release: Over 4500 Square Degrees of the Southern Sky and a Multicolor View of the Hydra and Antlia Galaxy Clusters

Abstract We present the fifth data release (DR5) of the Southern Photometric Local Universe Survey (S-PLUS), covering 4592 deg 2 across 2491 fields. Observations were conducted with the T80-South, a Brazilian robotic telescope equipped with the Javalambre 12-filter system, containing five broadband and seven narrowband filters. Data products feature FITS images and extensive catalogs containing fluxes, magnitudes, and shape parameters for over 113 million detections. In addition, several value-added catalogs are provided, offering photometric redshifts (photo- zs ), object classifications, masks, and extinction coefficients. For the first time, this release includes coverage of 110 deg 2 along the Galactic disk, facilitating new research into Galactic structure and stellar populations. The release also provides full coverage of the Hydra Supercluster and numerous other nearby clusters with improved data reduction and calibration, enhancing photo- z accuracy, which is vital for large-scale structure studies. A preliminary analysis of the Hydra and Antlia galaxy clusters up to 5 × R 200 yields an updated catalog of 1706 cluster members based on both spectroscopic and high-quality photo- zs . Our photometric data shows that both clusters have a similar proportion of galaxies with an H α excess relative to their clustercentric distance, though Hydra has a higher fraction near its center. Additionally, the spatial distribution of all objects in our sample highlights a bridge connecting both clusters. We verify that S-PLUS DR5 provides a solid foundation for future scientific investigations, ranging from solar system studies to cosmology.

Vinicius Rodrigues de Lima, Erik [Universidade de ↗
DOE OSTI2023

Neural Networks-Based Inverter Control: Modeling and Adaptive Optimization for Smart Distribution Networks

The optimal voltage control of inverter-based resources, especially under the high penetration of solar photovoltaics, is critical to the stability of the distribution power system. However, the computational complexity as well as the coordinated operation performance of the voltage control optimization in the distribution power system limits the real-time applications. To mitigate this issue, a model-free based adaptive optimal control scheme for the smart inverter is proposed to maximize the active power generation, minimize the power loss, and maintain the bus voltages in smart distribution networks. An inverter-based optimization model for coordinated operation is first established, considering the uncertainties of renewable power generation. Subsequently, by collecting the data and control strategies, the neural networks (NNs) based algorithm is proposed to efficiently predict the best possible control strategy. The main objective of this scheme is to accurately predict candidate optimal solutions with near-negligible feasibility and optimization gaps, with the advantage of avoiding complicated iteration-based numerical algorithms. Thereafter, the co-simulation among OpenDSS, MATLAB, and Python is set up to fully take advantage of the three individual software. Experiments are conducted based on different control parameter characteristics and structures of NNs. Finally, the results reveal that an average mean squared error of 0.013 and 1 ms response time are achieved, which is lower than some state-of-the-art methods.

42 ENGINEERING↗
DOE OSTI2023

Machine learning-based jet and event classification at the Electron-Ion Collider with applications to hadron structure and spin physics

We explore machine learning-based jet and event identification at the future Electron-Ion Collider (EIC). We study the effectiveness of machine learning-based classifiers at relatively low EIC energies, focusing on (i) identifying the flavor of the jet and (ii) identifying the underlying hard process of the event. We propose applications of our machine learning-based jet identification in the key research areas at the future EIC and current Relativistic Heavy Ion Collider program, including enhancing constraints on (transverse momentum dependent) parton distribution functions, improving experimental access to transverse spin asymmetries, studying photon structure, and quantifying the modification of hadrons and jets in the cold nuclear matter environment in electron-nucleus collisions. We establish first benchmarks and contrast the estimated performance of flavor tagging at the EIC with that at the Large Hadron Collider. We perform studies relevant to aspects of detector design including particle identification, charge information, and minimum transverse momentum capabilities. Additionally, we study the impact of using full event information instead of using only information associated with the identified jet. These methods can be deployed either on suitably accurate Monte Carlo event generators, or, for several applications, directly on experimental data. We provide an outlook for ultimately connecting these machine learning-based methods with first principles calculations in quantum chromodynamics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Bayesian Structural Time Series for Behind-the-Meter Photovoltaic Disaggregation

Distributed photovoltaic (PV) generation often occurs ``behind the meter": a grid operator can only observe the net load, which is the sum of the gross load and distributed PV generation. This lack of observability poses a challenge to system operation at both bulk level and distribution level. The lack of real-time or near-future disaggregated estimates of gross load and PV generation will lead to over scheduling of energy production and regulation reserves, reliability constraints violations, wear and tear of controller devices, and potentially cascading failures of a system. In this paper we propose the use of a Bayesian Structural Time Series (BSTS) model with local solar irradiance measurements to disaggregate the summed PV generation and gross load signals at a downstream measurement site. BSTSs are a highly expressive model class that blends classic time series models with the powerful Bayesian state space estimation framework. Disaggregation is done probabilistically, which automatically quantifies the uncertainties of the estimated PV generation and gross load consumption. Depending on the data availability in real-time, it can be used to disaggragate PV and gross load at customer site, or can be used at the feeder level. In this paper, we focus on solving the problem at feeder level. We compare the performance of a BSTS model as well as a handful of state-of-the-art methods on a Pecan Street AMI dataset, using the National Solar Radiation Database (NSRDB) to estimate local irradiance.

bayesian structural time series↗
DOE OSTI2025

Search for medium effects using jet axis decorrelation in inclusive jets from PbPb collisions at $\sqrt{{s}_{\text{NN}}}$ = 5.02 TeV

The jet axis decorrelation in inclusive jets is studied using lead-lead (PbPb) collisions at a center-of-mass energy per nucleon pair of 5.02 TeV. The jet axis decorrelation is defined as the angular difference between two definitions of the jet axis. It is obtained by applying two recombination schemes on all the constituents of a given jet reconstructed by the anti-kT sequential algorithm with a distance parameter of R = 0.4. The data set, corresponding to an integrated luminosity of 0.66 nb −1 , was collected in 2018 with the CMS detector at the CERN LHC. The jet axis decorrelations are examined across collision centrality selections and intervals of jet transverse momentum. A centrality dependent evolution of the measured distributions is observed, with a progressive narrowing seen in more central events. This narrowing could result from medium-induced modification of the internal jet structure or reflect color charge effects in energy loss. This new measurement probes jet substructure in previously unexplored kinematic domains and show great promise for providing new insights on the color charge dependence of energy loss to jet-quenching models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Synthesis and characterization of silica doped alumina catalyst support with superior thermal stability and unique pore properties

A facile, solvent-deficient, one-pot synthesis of a thermally stable silica-doped alumina, having high surface area, large pore volume and uniquely large pores, has been developed. Silica-doped alumina (SDA) was synthesized by adding 5 wt% silica from tetraethyl orthosilicate (TEOS) to aluminum isoproxide (AIP), a 1:5 mol ratio AIP to water, and a 1:2 mol ratio TEOS to water in the absence of a template. The structure of silica-doped alumina was studied by in situ high-temperature powder XRD, nitrogen adsorption, thermogravimetric analysis, solid-state NMR, and TEM. The addition of silica significantly increases the stability of γ-Al 2 O 3 phase to 1200 °C while maintaining a high surface area, a large pore volume and a large pore diameter. After calcination at 1100 °C for 2 h, a surface area of 160 m 2 /g, pore volume of 0.99 cm 3 /g, and a bimodal pore size distribution of 23 and 52 nm are observed. Compared to a commercial silica-doped alumina, after calcination for 24 h at 1100 °C, the surface area, pore volume, and pore diameter SDA are higher by 46, 155, and 94 %, respectively. Results reveal that Si stabilizes the porous structure of γ-Al 2 O 3 up to 1200 °C, while unstabilized alumina is stable to only 900 °C. From our data, we infer that Si enters tetrahedral vacancies in the defect spinel structure of alumina without moving Al from tetrahedral positions and forms a silica–alumina interface.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Comparative analysis of thermal management systems in electric vehicles at extreme weather conditions: Case study on Nissan Leaf 2019 Plus, Chevrolet Bolt 2020 and Tesla Model 3 2020

With the surge in electric vehicle (EV) adoption and the need for extended driving ranges, optimizing energy efficiency, particularly through thermal management, is critical, especially in extreme weather. Managing the substantial energy needed for cabin climate control and battery temperature regulation can increase energy demands by over 50 %, severely limiting range. This study conducts a comparative analysis of thermal management systems (TMS) in three popular EV vehicles, 2020 Chevrolet Bolt, 2019 Nissan Leaf Plus, and 2020 Tesla Model 3, evaluating their distinct TMS configurations and performance under varied weather conditions. Using both numerical simulations and experimental data collected on a controlled test bench at Argonne National Laboratory, we assess how TMS architecture and operational modes influence energy consumption and range. A comprehensive TMS model was developed, integrating cabin and battery thermal sub-models in the Autonomie software platform, to simulate temperature fluctuations and range impacts. Cabin climate was modeled using a mono-zonal approach, while battery cell temperature distribution was estimated through a 2D nodal structure. Each vehicle's distinct TMS setup was evaluated: the Chevrolet Bolt and Tesla Model 3 use a dual evaporator vapor compression cycle with a PTC heater for the cabin and a coolant loop for battery thermal management; the Nissan Leaf Plus employs a heat pump with a PTC heater for the cabin and air-cooling for the battery. Tests conducted at ambient temperatures of 35°C, 22°C, -7°C, and -18°C reveal significant differences in energy use and range reduction across both configurations and conditions. At 35°C, the Tesla Model 3, Chevrolet Bolt, and Nissan Leaf Plus have a range reduction of 8%, 9%, and 13%, respectively, due to air conditioning. In winter, heating technology is paramount; at -7°C, the Nissan Leaf's heat pump configuration achieves a lower range reduction (19.3%) compared to the Tesla and Chevrolet Bolt PTC heaters, which reduce range by 28.3% and 31%, respectively. Further, this study provides valuable insights for automotive engineers, EV technology researchers, and thermal management system designers aiming to enhance electric vehicle performance by understanding how different weather conditions and TMS architectures impact energy consumption and driving range.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Phase field modeling of discontinuous dynamic recrystallization in hot deformation of magnesium alloys

We have developed a quantitative phase field model of discontinuous dynamic recrystallization (PF-DDRX) for investigating grain structure evolution and its impact on mechanical response in magnesium alloy during hot deformation. A set of isothermal compression tests were conducted by Gleeble thermo-mechanical simulator and used to determine PF-DDRX model parameters such as critical stresses of recrystallization, activation energies of dislocation, grain boundaries and recrystallization grain nucleation. In the simulations, the experimentally measured average grain size and distribution were used to generate initial microstructures. The results show that the typical ‘necklace’ microstructures observed in DDRX forms at the earlier stage of recrystallization. The inhomogeneity of microstructures first increases rapidly and then decreases gradually and reaches a constant with the increase of dynamic recrystallization volume fraction. Both predicted grain structure and mechanical response are in good agreement with experimental results. This demonstrates that the model parameters determined by experimental data are reliable for the developed PF-DDRX model to predict the grain structure evolution and flow behavior of AZ80 magnesium alloy under hot deformation. This work presents a path to combine experiments and modeling to give quantitative prediction and minimize experimental cost.

magnesium alloy, Phase field method, dynamic recry↗
DOE OSTI2020

Development of interatomic potential for Al–Tb alloys using a deep neural network learning method

An interatomic potential for the Al–Tb alloy around the composition of Al 90 Tb 10 is developed using the deep neural network (DNN) learning method. The atomic configurations and the corresponding total potential energies and forces on each atom obtained from ab initio molecular dynamics (AIMD) simulations are collected to train a DNN model to construct the interatomic potential for the Al–Tb alloy. Here we show that the obtained DNN model can well reproduce the energies and forces calculated by AIMD simulations. Molecular dynamics (MD) simulations using the DNN interatomic potential also accurately describe the structural properties of the Al 90 Tb 10 liquid, such as partial pair correlation functions (PPCFs) and bond angle distributions, in comparison with the results from AIMD simulations. Furthermore, the developed DNN interatomic potential predicts the formation energies of the crystalline phases of the Al–Tb system with an accuracy comparable to ab initio calculations. The structure factors of the Al 90 Tb 10 metallic liquid and glass obtained by MD simulations using the developed DNN interatomic potential are also in good agreement with the experimental X-ray diffraction data. The development of short-range order (SRO) in the Al 90 Tb 10 liquid and the undercooled liquid is also analyzed and three dominant SROs, i.e., Al-centered distorted icosahedron (DISICO) and Tb-centered ‘3661’ and ‘15551’ clusters, respectively, are identified.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Constructing angular distributions of neutrinos in core-collapse supernovae from zeroth and first moments calibrated by full Boltzmann neutrino transport

Two-moment neutrino transport methods have been widely used for developing theoretical models of core-collapse supernovae (CCSN), since they substantially reduce the computational burden inherent in the multidimensional neutrino-radiation hydrodynamical simulations. The approximation, however, comes at a price; the detailed structure of angular distribution of neutrinos is sacrificed, that is the main drawback of this approach. In this paper, we develop a novel method by which to construct angular distributions of neutrinos from the zeroth and first angular moments. In our method, the angular distribution is expressed with two quadratic functions of the neutrino angle in a piecewise fashion. We determine the best parameters in the fitting function by comparing to the neutrino data in a spherically symmetric CCSN model with full Boltzmann neutrino transport. We demonstrate the capability of our method by using our recent 2D CCSN model. In this work, we find that the essential features of the angular distributions can be well reconstructed, whereas the angular distributions of incoming neutrinos tend to have large errors that increase with flux factor ($\textit{κ}$). This issue originates from the insensitiveness of incoming neutrinos to $\textit{κ}$, that is an intrinsic limitation in moment methods. Based on the results of the demonstration, we assess the reliability of electron- neutrinos lepton number (ELN)-crossing searches with the two-moment neutrino transport. This analysis is complementary to our [L. Johns and H. Nagakura arXiv:2104.04106] that scrutinizes the limitation of crossing searches with a few moments. We find that the systematic errors of angular distributions for incoming neutrinos lead to misjudgements of the crossing at $\textit{κ}$ ≳ 0.5. This casts doubt on the results of ELN-crossing searches based on two-moment methods in some previous studies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

rmc-discord : reverse Monte Carlo refinement of diffuse scattering and correlated disorder from single crystals

A user-friendly program has been developed to analyze diffuse scattering from single crystals with the reverse Monte Carlo method. The approach allows for refinement of correlated disorder from atomistic supercells with magnetic or structural (occupational and/or displacive) disorder. The program is written in Python and optimized for performance and efficiency. Refinements of two user cases obtained with legacy neutron-scattering data demonstrate the effectiveness of the approach and the developed program. It is shown with bixbyite, a naturally occurring magnetic mineral, that the calculated three-dimensional spin-pair correlations are resolved with finer real-space resolution compared with the pair distribution function calculated directly from the reciprocal-space pattern. With the triangular lattice Ba 3 Co 2 O 6 (CO 3 ) 0.7 , refinements of occupational and displacive disorder are combined to extract the one-dimensional intra-chain correlations of carbonate molecules that move toward neighboring vacant sites to accommodate strain induced by electrostatic interactions. The program is packaged with a graphical user interface and extensible to serve the needs of single-crystal diffractometer instruments that collect diffuse-scattering data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Mycorrhizal nutrient acquisition strategies shape tree competition and coexistence dynamics

Mycorrhizal fungi with different nutrient acquisition strategies influence plant species performance and physiology, thereby defining their trophic niche. This might drive resource competition dynamics that cumulatively impact tree species coexistence, but few manipulative experiments have directly tested this. Combining surveys and experiments in a modern coexistence theory framework, we tested how variation in mycorrhizal strategies and nutrient conditions affects plant competitive outcomes. We focused on two genera of co-occurring tree species with different mycorrhizal states: Acer (arbuscular mycorrhizal, AM) and Populus (dual mycorrhizal, but often considered predominantly ectomycorrhizal, EM). The EM and AM fungal responsiveness in Populus species varied with latitude and nitrogen (N) limitation. Host-specific soil microbiome conditioning and inorganic N fertilization combined to qualitatively affect coexistence outcomes. Lower N conditions favoured Populus over Acer trees, and N fertilization reversed this outcome for southern species, aligning with regional-scale forest mycorrhizal transitions. Results from the coexistence experiment also predict competitive exclusion between the tree species pairs, which could arise, in part, from their mycorrhizal differences and is consistent with alternative stable states in dominant forest mycorrhizal strategies. Such bistability appears in natural systems as a bimodal distribution of Populus vs. Acer tree species dominance using long-term forest inventory data. Synthesis: The magnitude and outcome of microbially mediated competition between Populus and Acer depends on soil nutrient availability, which likely relates to their mycorrhizal differentiation. These findings support the importance of mycorrhizal symbioses for contributing to large-scale biogeographical patterns of tree species trophic niche separation across soil resource gradients and bistability in forest mycorrhizal structure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Study of the internal structure, instabilities, and magnetic fields in the dense Z-pinch

Z-pinches are sources of hot dense plasma which generates powerful x-ray bursts and can been applied to various areas of high-energy-density physics (HEDP). The 26-MA Z machine is at the forefront of many of these applications, but important aspects of HEDP have been studied on generators at the 1 MA current level. Recent development of laser diagnostics and upgrade of the Leopard laser at Nevada Terawatt Facility (NTF) give new opportunities for the dense Z-pinch study. The goal of this project is the investigation of the internal structure of the stagnated Z pinch including sub-mm and micron-scale instabilities, plasma dynamics, magnetic fields, and hot spots formation and initiation. New plasma diagnostics will be developed for this project. A 3D structure and instabilities of the pinch will be compared with 3D MHD and spectroscopic modeling and theoretical analysis. The structure and dynamics of stagnated Z pinches has been studied with x-ray self-radiation diagnostics which derive a temperature map of the pinch with a spatial resolution of 70-150 µm. The regular laser diagnostics at 532 nm does not penetrate in the dense pinch due to strong absorption and refraction in trailing plasma. Recent experiments at NTF showed that shadowgraphy at the UV wavelength of 266 nm unfolds a fine structure of the stagnated Z-pinch with unprecedented detail. We propose to develop laser UV diagnostics for Z pinches with a spatial resolution <5 μm to study the small-scale plasma structures, implement two-frame shadowgraphy/interferometry, and develop methods for investigation of strong magnetic fields. New diagnostics will help to understand better basic physical processes in Z pinches. A 3D internal structure of the pinch and characteristic instabilities will be studied in wire arrays with different configurations and compared with 3D MHD simulations and analytical models. Mechanisms of “enhanced heating” of Z-pinch plasma will be studied. Fast dynamics of stagnated plasma will be studied to estimate its contribution to the Doppler broadening of x-ray lines. Development of “necks” and “hot spots” will be studied with high-resolution UV diagnostics, an x-ray streak camera, and x-ray spectroscopy. Laser initiation of hot spots in Z pinches will be tested. A Faraday rotation diagnostic at 266 nm will be applied to 1-10 MG magnetic fields. For magnetic fields B>20 MG, suggested in micropinches, Cotton-Mouton and cutoff diagnostics will be applied. A picosecond optical Kerr shutter will be tested to increase a sensitivity of UV methods for application at multi-MA Z pinches. The proposal is based on the experimental capability of NTF. The Zebra generator produces 1-1.7 MA Z-pinches with electron plasma density of 10 20 -10 21 cm -3 , electron temperature of 0.5-1 keV, and magnetic fields >10 MG. The Leopard laser was upgraded to energy of 90-J at 0.8 ns. This regime will be used for laser initiation of hot spots. A further upgrade to energy of 250-J is suggested for laser-Z-pinch interaction. A picosecond regime will be used for optical gating. A 10-TW Tomcat laser at NTF is available for the high energy UV laser probing of the Z-pinch. Two graduate students will develop new optical and x-ray diagnostics, carry out experiments, and process experimental data. Other students will be involved in the design and fabrication of loads, supporting regular optical and x-ray diagnostics, and data processing. The new plasma diagnostics may be applied to HEDP experiments at NTF and other multi-MA generators. The feasibility of the research plan is based on the experience of the scientific team in Z-pinch plasma physics, laser physics, development of new plasma diagnostics, and the experimental capability of NTF. The experimental group of Dr. V. V. Ivanov (UNR) collaborates with a group for Z pinch MHD modeling of Dr. J. P. Chittenden (Imperial College, London), and theoretical group of Dr. D. D. Ryutov (LLNL). The suggested research ideas are supported by preliminary experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Association of Plages with Sunspots: A Multi-Wavelength Study Using Kodaikanal Ca ii K and Greenwich Sunspot Area Data

Plages are the magnetically active chromospheric structures prominently visible in the Ca ii K line (3933.67 Å). A plage may or may not be associated with a sunspot, which is a magnetic structure visible in the solar photosphere. In this study we explore this aspect of association of plages with sunspots using the newly digitized Kodaikanal Ca ii K plage data and the Greenwich sunspot area data. Instead of using the plage index or fractional plage area and its comparison with the sunspot number, we use, to our knowledge for the first time, the individual plage areas and compare them with the sunspot area time series. Our analysis shows that these two structures, formed in two different layers, are highly correlated with each other on a timescale comparable to the solar cycle. The area and the latitudinal distributions of plages are also similar to those of sunspots. Different area thresholdings on the “butterfly diagram” reveal that plages of area ≥4 arcmin{sup 2} are mostly associated with a sunspot in the photosphere. Apart from this, we found that the cyclic properties change when plages of different sizes are considered separately. These results may help us to better understand the generation and evolution of the magnetic structures in different layers of the solar atmosphere.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

New CTEQ-Jefferson Lab (CJ15) Analysis of Parton Distributions

We present the results of a new global QCD analysis of PDFs from the CTEQ-Jefferson Lab collaboration (dubbed "CJ15"), which includes several new data sets and recent theoretical developments. In particular, we study the constraints from new D0 data on W boson asymmetries on the d/u PDF ratio at large x, and, indirectly, on the models of nuclear corrections in the deuteron. The analysis also considers for the first time the impact of Jefferson Lab data on the free neutron/deuteron structure function ratio at large x, and reanalyzes the light antiquark asymmetry in the proton from Drell-Yan data using more flexible parametrizations and nuclear corrections to deuterium cross sections. The results provide a new set of baseline PDFs which can be used to more reliably calibrate the effects of future data from the LHC.

Melnitchouk, W.↗