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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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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Differential flow correlations in relativistic heavy-ion collisions

A systematic analysis of correlations between different orders of p T -differential flow is presented here, including mode coupling effects in flow vectors, correlations between flow angles (a.k.a. event-plane correlations), and correlations between ow magnitudes, all of which were previously studied with integrated flows. Furthermore, we find that the mode coupling effects among differential flows largely mirror those among the corresponding integrated flows, except at small transverse momenta where mode coupling contributions are small. For the fourth- and fifth-order flow vectors V 4 and V 5 we argue that the event plane correlations can be understood as the ratio between the mode coupling contributions to these flows and the flow magnitudes. We also find that for V 4 and V 5 the linear response contribution scales linearly with the corresponding cumulant-defined eccentricities but not with the standard eccentricities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Measurements of normalized differential cross sections for t t ¯ production in p p collisions at ( s ) = 7 TeV using the ATLAS detector

We present measurements of normalized differential cross sections for top-quark pair production as a function of the top-quark transverse momentum, and of the mass, transverse momentum, and rapidity of the $t\bar{t}$ system, in proton–proton collisions at a center-of-mass energy of √ s=7 TeV. The data set corresponds to an integrated luminosity of 4.6 fb ₋1 , recorded in 2011 with the ATLAS detector at the CERN Large Hadron Collider. Events are selected in the lepton + jets channel, requiring exactly one lepton and at least four jets with at least one of the jets tagged as originating from a b-quark. The measured spectra are corrected for detector efficiency and resolution effects and are compared to several Monte Carlo simulations and theory calculations. The results are in fair agreement with the predictions in a wide kinematic range. Nevertheless, data distributions are softer than predicted for higher values of the mass of the $t\bar{t}$ system and of the top-quark transverse momentum. Lastly, the measurements can also discriminate among different sets of parton distribution functions.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Interpretable Models for Workflow Differentiation in High-Performance Scientific Networks

Scientific workflows in high-performance networks spawn hundreds of interdependent flows that must be managed collectively—yet existing network classifiers treat each flow in isolation, leading to fragmented QoS decisions and missed interflow patterns. We present a novel traffic classification solution that operates at the workflow level, distinguishing entire filetransfer operations from streaming analytics by capturing how concurrent flows interact and burst together. We introduce a workflow identification window (WIW) that ingests raw packet headers from parallel flows into unified tensors, preserving the spatial-temporal patterns that differentiate scientific workflows. This approach achieves 98.7% accuracy using CNN, LSTM, and hybrid architectures, while maintaining 84% accuracy on production traffic collected a week later—demonstrating robustness to temporal drift. By integrating SHAP and GradCAM explainability, we reveal that early-packet timing patterns and cross-flow correlations drive classification decisions, providing operators with interpretable insights. Our system enables coherent workflow-level QoS enforcement and dynamic bandwidth allocation in scientific networks, eliminating manual per-flow configuration while maintaining classification latency at millisecond level.

Giannakou, Anna [LBL, Berkeley]↗
DOE OSTI2020

Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations

We developed a new class of physics-informed generative adversarial networks (PI-GANs) to solve forward, inverse, and mixed stochastic problems in a unified manner based on a limited number of scattered measurements. Unlike standard GANs relying solely on data for training, here we encoded into the architecture of GANs the governing physical laws in the form of stochastic differential equations (SDEs) using automatic differentiation. In particular, we applied Wasserstein GANs with gradient penalty (WGAN-GP) for its enhanced stability compared to vanilla GANs. We first tested WGAN-GP in approximating Gaussian processes of different correlation lengths based on data realizations collected from simultaneous reads at sparsely placed sensors. We obtained good approximation of the generated stochastic processes to the target ones even if there is a mismatch between the input noise dimensionality and the effective dimensionality of the target stochastic processes. We also studied the overfitting issue for both the discriminator and the generator, and we found that overfitting occurs also in the generator in addition to the discriminator as previously reported. Subsequently, we considered the solution of elliptic SDEs requiring approximations of three stochastic processes, namely the solution, the forcing, and the diffusion coefficient. Here again, we assumed data collected from simultaneous reads at a limited number of sensors for the multiple stochastic processes. Furthermore, three generators were used for the PI-GANs: two of them were feed forward deep neural networks (DNNs), while the other one was the neural network induced by the SDE. For the case where we have one group of data, we employed one feed forward DNN as the discriminator, while for the case of multiple groups of data we employed multiple discriminators in PI-GANs. We solved forward, inverse, and mixed problems without changing the framework of PI-GANs, obtaining both the means and the standard deviations of the stochastic solution and the diffusion coefficient in good agreement with benchmarks. In this work, we have demonstrated the effectiveness of PI-GANs in solving SDEs for about 120 dimensions. In principle, PI-GANs could tackle very high dimensional problems given more sensor data with low-polynomial growth in computational cost.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Measurements of inclusive and differential fiducial cross-sections of $t\bar{t}\gamma $ production in leptonic final states at $\sqrt{s}=13~\text {TeV}$ TeV in ATLAS

Inclusive and differential cross-sections for the production of a top-quark pair in association with a photon are measured with proton-proton collision data corresponding to an integrated luminosity of 36.1 fb –1 , collected by the ATLAS detector at the LHC in 2015 and 2016 at a centre-of-mass energy of 13 TeV. The measurements are performed in single-lepton and dilepton final states in a fiducial volume. Events with exactly one photon, one or two leptons, a channel-dependent minimum number of jets, and at least one b-jet are selected. Neural network algorithms are used to separate the signal from the backgrounds. The fiducial cross-sections are measured to be 521 ± 9(stat.) ± 41(sys.) fb and 69 ± 3(stat.) ± 4(sys.) fb for the single-lepton and dilepton channels, respectively. The differential cross-sections are measured as a function of photon transverse momentum, photon absolute pseudorapidity, and angular distance between the photon and its closest lepton in both channels, as well as azimuthal opening angle and absolute pseudorapidity difference between the two leptons in the dilepton channel. All measurements are in agreement with the theoretical predictions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Rythmos: Solution and Analysis Package for Differential-Algebraic and Ordinary-Differential Equations

Time integration is a central component for most transient simulations. It coordinates many of the major parts of a simulation together, e.g., a residual calculation with a transient solver, solution with the output, various operator-split physics, and forward and adjoint solutions for inversion. Even though there is this variety in these transient simulations, there is still a common set of algorithms and procedures to progress transient solutions for ordinary-differential equations (ODEs) and differential-alegbraic equations (DAEs). Rythmos is a collection of these algorithms that can be used for the solution of transient simulations. It provides common time-integration methods, such as Backward and Forward Euler, Explicit and Implicit Runge-Kutta, and Backward-Difference Formulas. It can also provide sensitivities, and adjoint components for transient simulations. Rythmos is a package within Trilinos, and requires some other packages (e.g., Teuchos and Thrya) to provide basic time-integration capabilities. It also can be coupled with several other Trilinos packages to provide additional capabilities (e.g., AztecOO and Belos for linear solutions, and NOX for non-linear solutions). The documentation is broken down into three parts: Theory Manual, User's Manual, and Developer's Guide. The Theory Manual contains the basic theory of the time integrators, the nomenclature and mathematical structure utilized within Rythmos, and verification results demonstrating that the designed order of accuracy is achieved. The User's Manual provides information on how to use the Rythmos, description of input parameters through Teuchos Parameter Lists, and description of convergence test examples. The Developer's Guide is a high-level discussion of the design and structure of Rythmos to provide information to developers for the continued development of capabilities. Details of individual components can be found in the Doxygen webpages.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

X-ray diffraction, differential scanning calorimetry and evolved gas analysis of aged plutonium tetrafluoride (PuF4)

A 30 year-old PuF4 sample consisting of brown powder (PuF4-b) and pink granules (PuF4-p) was analyzed. X-ray difraction shows the bulk is comprised of three compounds: PuF4, PuO2, and PuF4·1.6H2O. Broadening of PuF4 XRD peaks suggests possible a-damage. After annealing at 650 °C, crystalline PuF4 and PuO2 remain. Thermogravimetric analysis and diferential scanning calorimetry—with simultaneous evolved gas analysis—of the separated PuF4-p and PuF4-b components reveal a distinct sequence of reactions. Dehydration occurs between~90 and 300 °C. Exothermic annealing of the a-damage occurs in two stages: at 350–355 °C and at 555–558 °C. Hydrofuoric acid, fuorine and helium desorb during the frst exotherm. Above 700 °C, PuF4 reacts with PuO2, resulting in oxygen release and mass loss.

PuF4, dsc, differential scanning calorimetry, plut↗
DOE OSTI2017

Surface Pb nanoparticle aggregation, coalescence and differential capacitance in a deep eutectic solvent using a simultaneous sample-rotated small angle x-ray scattering and electrochemical methods approach [Surface Pb nanoparticle aggregation, coalescence and differential capacitance in a deep eutectic solvent using a simultaneous grazing transmission small angle x-ray scattering and electrochemical methods approach]

Nanoparticle electrodeposition is a simple and scalable approach to synthesizing supported nanoparticles. Used with a deep eutectic solvent (DES), surface nanoparticles can be assembled and exhibit unique surface charge separation when the DES is adsorbed on the nanoparticle surface. Key to understanding and controlling the assembly and the capacitance is a thorough understanding of surface particle mobility and charge screening, which requires an in-situ approach. In this study, Pb particle formation, size, shape and capacitance are resolved in a 1:2 choline Cl – : urea deep eutectic solvent whilst sweeping the cell potential in the range: 0.2 V to –1.2 V (vs. Ag/AgCl). These system parameters were resolved using a complementary suite of sample-rotated small angle X-ray scattering (SR-SAXS) and electrochemical impedance spectroscopy (EIS), which are presented and discussed in detail. This approach is able to show that both particle and ion transport are impeded in the DES, as aggregation occurs over the course of 6 minutes, and dissolved Pb ions accumulate and remain near the surface after a nucleation pulse is applied. The DES-Pb interactions strongly depend on the cell potential as evidenced by the specific differential capacitance of the Pb deposit, which has a maximum value of 2.5 +/– 0.5 F g –1 at –1.0 V vs. Ag/AgCl. Together, the SR-SAXS-EIS approach is able to characterize the unique nanoparticle capacitance, mobility and ion mobility in a DES and can be used to study a wide range of nanoparticle deposition systems in-situ .

36 MATERIALS SCIENCE↗
DOE OSTI2014

Measurement of differential production cross-sections for a Z boson in association with b-jets in 7 TeV proton-proton collisions with the ATLAS detector

We report measurements of differential production cross-sections of a Z boson in association with b-jets in pp collisions at √ s = 7 TeV. The data analysed correspond to an integrated luminosity of 4.6 fb -1 recorded with the ATLAS detector at the Large Hadron Collider. Particle-level cross-sections are determined for events with a Z boson decaying into an electron or muon pair, and containing b-jets. For events with at least one b-jet, the cross-section is presented as a function of the Z boson transverse momentum and rapidity, together with the inclusive b-jet cross-section as a function of b-jet transverse momentum, rapidity and angular separations between the b-jet and the Z boson. For events with at least two b-jets, the cross-section is determined as a function of the invariant mass and angular separation of the two highest transverse momentum b-jets, and as a function of the Z boson transverse momentum and rapidity. Lastly, results are compared to leading-order and next-to-leading-order perturbative QCD calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Statistical detection of differentially abundant ions in mass spectrometry-based imaging experiments with complex designs

Mass Spectrometry Imaging (MSI) characterizes changes in chemical composition between regions of biological samples such as tissues. This translates into a statistical goal of class comparison, i.e. determining analytes that change in abundance between conditions more systematically than as expected by random variation. To reach accurate and reproducible conclusions, statistical analysis must appropriately reflect the initial research question, the design of the MSI experiment, and all the associated sources of variation. This manuscript highlights the importance of following these general statistical principles. Using the example of two case studies with complex experimental designs, and with dierent strategies of data acquisition, we demonstrate the extent to which choices made at key points of this workflow impact the results, and provide suggestions for appropriate design and analysis of MSI experiments that aim at detecting dierentially abundant analytes.

NanoDESI, mass spectrometry, MSIQuickView↗
DOE OSTI2020

Insights into negative differential resistance in MoS 2 Esaki diodes: A first-principles perspective

MoS 2 is a two-dimensional material with a band gap depending on the number of layers and tunable by an external electric field. The experimentally observed intralayer band-to-band tunneling and interlayer band-to-band tunneling in this material present an opportunity for new electronic applications in tunnel field-effect transistors. However, such a widely accepted concept has yet to be been supported by theoretical investigations based on first principles. In this paper, using density functional theory, in conjunction with nonequilibrium Green's function techniques and our electric field gating method, enabled by a large-scale computational approach, we study the relation between band alignment and transmission in planar and side-stack MoS 2 p–i–n junction configurations. Here, we demonstrate the presence of negative differential resistance for both in-plane and interlayer current, a staple characteristic of tunnel diode junctions, and analyze the physical origin of such an effect. Electrostatic potentials, the van der Waals barrier, and a complex band analysis are also examined for a thorough understanding of Esaki diodes.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2016

Measurement of the differential cross-section of highly boosted top quarks as a function of their transverse momentum in s = 8 TeV proton-proton collisions using the ATLAS detector

The differential cross-section for pair production of top quarks with high transverse momentum is measured in 20.3 fb -1 of proton-proton collisions at a center-of-mass energy of 8 TeV. The measurement is performed for t$\bar{t}$t events in the lepton + jets channel. The cross-section is reported as a function of the hadronically decaying top quark transverse momentum for values above 300 GeV. The hadronically decaying top quark is reconstructed as an anti- k t jet with radius parameter R = 1.0 and identified with jet substructure techniques. The observed yield is corrected for detector effects to obtain a cross-section at particle level in a fiducial region close to the event selection. A parton-level cross-section extrapolated to the full phase space is also reported for top quarks with transverse momentum above 300 GeV. The predictions of a majority of next-to-leading-order and leading-order matrix-element Monte Carlo generators are found to agree with the measured cross-sections.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

A Preconditioned Low-Rank Projection Method with a Rank-Reduction Scheme for Stochastic Partial Differential Equations

Herein, we consider the numerical solution of large systems of linear equations obtained from the stochastic Galerkin formulation of stochastic partial differential equations. We propose an iterative algorithm that exploits the Kronecker product structure of the linear systems. The proposed algorithm efficiently approximates the solutions in low-rank tensor format. Using standard Krylov subspace methods for the data in tensor format is computationally prohibitive due to the rapid growth of tensor ranks during the iterations. To keep tensor ranks low over the entire iteration process, we devise a rank-reduction scheme that can be combined with the iterative algorithm. The proposed rank-reduction scheme identifies an important subspace in the stochastic domain and compresses tensors of high rank on-the-fly during the iterations. The proposed reduction scheme is a coarse-grid method in that the important subspace can be identified inexpensively in a coarse spatial grid setting. The efficiency of the present method is displayed by numerical experiments on benchmark problems.

97 MATHEMATICS AND COMPUTING↗