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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Accessing new physics with an undoped, cryogenic CsI CEvNS detector for COHERENT at the SNS

We consider the potential for a 10 kg undoped cryogenic CsI detector operating at the Spallation Neutron Source to measure coherent elastic neutrino-nucleus scattering and its sensitivity to discover new physics beyond the standard model (BSM). Through a combination of increased event rate, lower threshold, and good timing resolution, such a detector would significantly improve on past measurements. We considered tests of several BSM scenarios such as neutrino nonstandard interactions and accelerator-produced dark matter. This detector’s performance was also studied for relevant questions in nuclear physics and neutrino astronomy, namely the weak charge distribution of Cs and I nuclei and detection of neutrinos from a core-collapse supernova. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Revealing Fundamental Physics from the Daya Bay Neutrino Experiment Using Deep Neural Networks

Experiments in particle physics produce enormous quantities of data that must be analyzed and interpreted by teams of physicists. This analysis is often exploratory, where scientists are unable to enumerate the possible types of signal prior to performing the experiment. Thus, tools for summarizing, clustering, visualizing and classifying high-dimensional data are essential. Here in this work, we show that meaningful physical content can be revealed by transforming the raw data into a learned high-level representation using deep neural networks, with measurements taken at the Daya Bay Neutrino Experiment as a case study. We further show how convolutional deep neural networks can provide an effective classification filter with greater than 97% accuracy across different classes of physics events, significantly better than other machine learning approaches.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

A new approach to physics of nuclei

We employ the QCD sum rules method for description of nucleons in nuclear matter. We show that this approach provides a consistent formalism for solving various problems of nuclear physics. Such nucleon characteristics as the Dirac effective mass m* and the vector self-energy {Sigma}{sub V} are expressed in terms of the in-medium values of QCD condensates. The values of these parameters at saturation density and the dependence on the baryon density and on the neutron-to-proton density ratio is in agreement with the results, obtained by conventional nuclear physics methods. The contributions to m* and {Sigma}{sub V} are related to observables and do not require phenomenological parameters. The scalar interaction is shown to be determined by the pion-nucleon {sigma} term. The nonlinear behavior of the scalar condensate may appear to provide a possible mechanism of the saturation. The approach provided reasonable results for renormalization of the axial coupling constant, for the contribution of the strong interactions to the neutron-proton mass difference and for the behavior of the structure functions of the in-medium nucleon. The approach enables to solve the problems which are difficult or unaccessible for conventional nuclear physics methods. The method provides guidelines for building the nuclear forces. The three-body interactions emerge within the method in a natural way. Their rigorous calculation will be possible in the framework of self-consistent calculation in nuclear matter of the scalar condensate and of the nucleon effective mass m*.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Physics Flash December 2016

This is the December 2016 issue of Physics Flash, the newsletter of the Physics Division of Los Alamos National Laboratory (LANL). In this issue, the following topics are covered: Novel liquid helium technique to aid highly sensitive search for a neutron electrical dipole moment; Silverleaf: Prototype Red Sage experiments performed at Q-site; John L. Kline named 2016 APS Fellow; Physics students in the news; First Entropy Engine quantum random number generator hits the market; and celebrating service.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

High Energy Physics Research: Experimental & Theoretical (Final Report)

The research at the energy frontier was to explore high energy and luminosity collisions at the LHC using the ATLAS and CMS detectors to lead physics analyses in characterization of the Higgs Boson, to search for its potential partners, to lead searches for Dark Matter and to make extensive studies of Electroweak phenomena. The objectives are also to operate and upgrade the ATLAS and CMS detectors and their computing to optimize their physics performance in the present data taking and to enable the full exploitation of planned High Luminosity LHC. The research for the theory frontier was to analyze and interpret the new data from the experimental frontiers: energy, cosmic and intensity (Phenomenology), to investigate new theories of high energy physics extending the standard model by including gravity within consistent frameworks such as string theory, and examine their phenomenological and cosmological implications (String Theory and Theoretical Cosmology.)

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Constraining Physical Models at Gigabar Pressures

High-energy-density (HED) experiments in convergent geometry are able to test physical models at pressures beyond hundreds of millions of atmospheres. The measurements from these experiments are generally highly integrated and require unique analysis techniques to procure quantitative information. This work describes a methodology to constrain the physics in convergent HED experiments by adapting the methods common to many other fields of physics. As an example, a mechanical model of an imploding shell is constrained by data from a thin-shelled direct-drive exploding-pusher experiment on the OMEGA Laser System using Bayesian inference, resulting in the reconstruction of the shell dynamics and energy transfer during the implosion. The model is tested by analyzing synthetic data from a 1-D hydrodynamics code and is sampled using a Markov chain Monte Carlo to generate the posterior distributions of the model parameters. The goal of this work is to demonstrate a general methodology that can be used to draw conclusions from a wide variety of HED experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2011

Applications of AdS/QCD and Light-Front Holography to Baryon Physics

The correspondence between theories in anti-de Sitter space and field theories in physical space-time leads to an analytic, semiclassical model for strongly-coupled QCD which has scale invariance at short distances and color confinement at large distances. These equations, for both mesons and baryons, give a very good representation of the observed hadronic spectrum, including a zero mass pion. Light-front holography allows hadronic amplitudes in the AdS fifth dimension to be mapped to frame-independent light-front wavefunctions of hadrons in physical space-time, thus providing a relativistic description of hadrons at the amplitude level. The meson and baryon wavefunctions derived from light-front holography and AdS/QCD also have remarkable phenomenological features, including predictions for the electromagnetic form factors and decay constants. The approach can be systematically improved using light-front Hamiltonian methods. Some novel features of QCD for baryon physics are also discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Reco level Smin and subsystem Smin: improved global inclusive variables for measuring the new physics mass scale in MET events at hadron colliders

The variable {radical}s{sub min} was originally proposed in [1] as a model-independent, global and fully inclusive measure of the new physics mass scale in missing energy events at hadron colliders. In the original incarnation of {radical}s{sub min}, however, the connection to the new physics mass scale was blurred by the effects of the underlying event, most notably initial state radiation and multiple parton interactions. In this paper we advertize two improved variants of the {radical}s{sub min} variable, which overcome this problem. First we show that by evaluating the {radical}s{sub min} variable at the RECO level, in terms of the reconstructed objects in the event, the effects from the underlying event are significantly diminished and the nice correlation between the peak in the {radical}s{sub min}{sup (reco)} distribution and the new physics mass scale is restored. Secondly, the underlying event problem can be avoided altogether when the {radical}s{sub min} concept is applied to a subsystem of the event which does not involve any QCD jets. We supply an analytic formula for the resulting subsystem {radical}s{sub min}{sup (sub)} variable and show that its peak exhibits the usual correlation with the mass scale of the particles produced in the subsystem. Finally, we contrast {radical}s{sub min} to other popular inclusive variables such as H{sub T}, M{sub Tgen} and M{sub TTgen}. We illustrate our discussion with several examples from supersymmetry, and with dilepton events from top quark pair production.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2012

Physics and Algorithm Enhancements for a Validated MCNP/X Monte Carlo Simulation Tool, Phase VII

Currently the US lacks an end-to-end (i.e., source-to-detector) radiation transport simulation code with predictive capability for the broad range of DHS nuclear material detection applications. For example, gaps in the physics, along with inadequate analysis algorithms, make it difficult for Monte Carlo simulations to provide a comprehensive evaluation, design, and optimization of proposed interrogation systems. With the development and implementation of several key physics and algorithm enhancements, along with needed improvements in evaluated data and benchmark measurements, the MCNP/X Monte Carlo codes will provide designers, operators, and systems analysts with a validated tool for developing state-of-the-art active and passive detection systems. This project is currently in its seventh year (Phase VII). This presentation will review thirty enhancements that have been implemented in MCNPX over the last 3 years and were included in the 2011 release of version 2.7.0. These improvements include 12 physics enhancements, 4 source enhancements, 8 tally enhancements, and 6 other enhancements. Examples and results will be provided for each of these features. The presentation will also discuss the eight enhancements that will be migrated into MCNP6 over the upcoming year.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2013

Neutrino Cross Sections II: Neutrino Boogaloo. UF Task P3, Accelerator-Based Experimental Neutrino Physics. Final Report

We report on progress in a series of different directions within high energy physics research. 1. Neutrino research in hardware and software on the Minerva and MiniBooNE experiments 2. Experimental particle physics at the hadron colliders, with emphasis on research and development and data analysis on the CMS experiment operating at the CERN LHC. This includes research on the discovery and properties on the Higgs Boson. 3. Educational outreach through the Quarknet program, taking physics research into High School classrooms. 4. Theoretical and Phenomenological High Energy research, covering a broad range of activities ranging from fundamental theoretical issues to areas of immediate phenomenological importance. 5. Experiment searches for the Axion, as part of the ADMX experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Improved Few-group Homogenized Cross-section Sensitivity Analysis for Lattice Physics Calculation

In the conventional reactor physics 'two-step' calculation scheme, lattice-physics calculation is followed by core calculation using neutron diffusion theory. The few-group spatially homogenized cross-sections are the outputs of the lattice-physics calculation as well as the inputs of the core calculation. The uncertainties of fundamental nuclear data will be propagated to the core calculation results through few-group spatially homogenized cross-sections. Consequently, assessing the sensitivity and uncertainty of few-group homogenized cross-sections is necessary for the core-calculation sensitivity and uncertainty analysis. Conventional method for sensitivity analysis is usually performed with respect to effective self-shielding cross sections but not continuous-energy cross sections by neglecting resonance self-shielding effects. The purpose of this work is to improve the sensitivity analysis of few-group cross sections and assess the effects introduced by resonance calculation with the subgroup method being used for resonance calculation. This paper is organized as follows: Firstly, theoretical models of this work are described. Secondly, validation and analysis are performed based on a boiling-water reactor (BWR) fuel-pin cell under hot zero power (HZP) condition. Finally, summaries and conclusions are given. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Overview of the MAST Upgrade physics programme: testing novel concepts at low aspect ratio to inform future devices

The research programme performed on the Mega Amp Spherical Tokamak (MAST) Upgrade experiment has made significant advances in developing the physics understanding of low aspect ratio tokamaks in support of the operation of ITER and design of fusion powerplants. High performance plasma scenarios have been developed to facilitate a broad programme of experiments, in which confinement is constrained by the presence of m/n = 2/1 modes that cause substantial losses of fast ions. The onset of these modes coincides with the q = 2 surface residing in a local minimum in the toroidal current density profile. The maximum electron temperature at the pedestal top, T e,ped is limited with gas fuelling to ∼350 eV to maintain regular ELMs; higher T e,ped results in a transition to a non-stationary ELM-free regime. The operational space of spherical tokamaks has been expanded into small and ELM-free regimes. Strong shaping of the last closed flux surface can induce a transition from large to small ELMs, and ELM suppression with resonant magnetic perturbations has been observed for the first time in a low aspect ratio tokamak. Negative triangularity shaping has induced a transition from ELMy H-mode to a high-performance L-mode regime for the first time in a low aspect ratio tokamak. In studies of fast ion confinement, losses of fast particles due to Global Alfvén Eigenmodes have been identified. Interactions between fast ions generated by off-axis neutral beam injection and thermal neutrals can result in significant losses of fast ions. Experiments with on- and off-axis neutral beam injection exhibit a flux pumping mechanism, where the central safety factor is held to ∼1 in the absence of sawteeth. In studies of pedestal physics, it has been found that elevated main chamber neutral pressures result in an increase in the electron density and reduction in the temperature at the pedestal top. Advances in understanding plasma exhaust include the integration of a high-performance plasma core with detached outer divertors in the X-point target configuration. A newly commissioned lower divertor cryopump reduces the lower divertor neutral pressure by up to 50%, with minimal effect on the main chamber or upper divertor. New measurements and SOLPS-ITER simulations emphasise the importance of plasma–neutral interactions on divertor detachment in the conditions accessible in experiments. Real-time control of the ionisation front location in both divertor chambers independently has been demonstrated in double null experiments, enabled by the tightly baffled divertor chambers.

MAST Upgrade↗
DOE OSTI2022

New Insights into Physical Aging‐Induced Structure Evolution in Carbon Molecular Sieve Membranes

Abstract Carbon molecular sieve (CMS) membranes offer the best available combination of scalable economical processability with excellent separation performance. Physical aging of CMS membranes causes pore structure changes over time that affect CMS membrane performance. To provide fundamental insights into the structure evolution in CMS membranes during physical aging, a combined dual‐mode sorption and transport model is used in this study to characterize the diffusion coefficients of gas molecules in fresh and 7‐day vacuum aged CMS membranes. The results show physical aging of CMS membrane is primarily “diffusion related” and such aging behavior simultaneously causes ultramicropore changes in the continuous phase and Langmuir phase of CMS membrane. The new insights offered in this study suggest strategies to control the physical aging of CMS membranes and even use it as a valuable tool to tune the separation performance of CMS membranes for demanding gas separations.

Liu, Zhongyun↗
DOE OSTI2023

A high‐order discontinuous Galerkin approach for physics‐based thermospheric modeling

Abstract The accurate prediction of aerodynamic drag on satellites orbiting in the upper atmosphere is critical to the operational success of modern space technologies, such as satellite‐based communication or navigation systems, which have become increasingly popular in the last few years due to the deployment of constellations of satellites in low‐Earth orbit. As a result, physics‐based models of the ionosphere and thermosphere have emerged as a necessary tool for the prediction of atmospheric outputs under highly variable space weather conditions. This paper proposes a high‐fidelity approach for physics‐based space weather modeling based on the solution of the Navier–Stokes equations using a high‐order discontinuous Galerkin method, combined with a matrix‐free strategy suitable for high‐performance computing on GPU architectures. The approach consists of a thermospheric model that describes a chemically frozen neutral atmosphere in nonhydrostatic equilibrium driven by the external excitation of the Sun. A novel set of variables is considered to treat the low densities present in the upper atmosphere and to accommodate the wide range of scales present in the problem. At the same time, and unlike most existing approaches, radial and angular directions are treated in a nonsegregated approach. The study presents a set of numerical examples that demonstrate the accuracy of the approximation and validate the current approach against observational data along a satellite orbit, including estimates of established empirical and physics‐based models of the ionosphere‐thermosphere system. Finally, a one‐dimensional radial derivation of the physics‐based model is presented and utilized for conducting a parametric study of the main thermal quantities under various solar conditions.

Engineering↗
DOE OSTI2026

NuGraph2 with context-aware inputs: physics-inspired improvements in semantic segmentation

Graph neural networks have recently shown strong promise for event reconstruction tasks in Liquid Argon Time Projection Chambers, yet their performance remains limited for underrepresented classes of particles, such as Michel electrons. In this work, we investigate physics-informed strategies to improve semantic segmentation within the NuGraph2 architecture. We explore three complementary approaches: (i) enriching the input representation with context-aware features derived from detector geometry and track continuity, (ii) introducing auxiliary decoders to capture class-level correlations, and (iii) incorporating energy-based regularization terms motivated by Michel electron energy distributions. Experiments on MicroBooNE public datasets show that physics-inspired feature augmentation yields the largest gains, particularly boosting Michel electron precision and recall by disentangling overlapping latent space regions. In contrast, auxiliary decoders and energy-regularization terms provided limited improvements, partly due to the hit-level nature of NuGraph2, which lacks explicit particle- or event-level representations. Our findings highlight that embedding physics context directly into node-level inputs is more effective than imposing task-specific auxiliary losses, and suggest that future hierarchical architectures such as NuGraph3, with explicit particle- and event-level reasoning, will provide a more natural setting for advanced decoders and physics-based regularization. The code for this work is publicly available on Github at https://github.com/vitorgrizzi/nugraph_phys/tree/main_phys.

Other Experiments↗
DOE OSTI2024

Griffin: A MOOSE-based reactor physics application for multiphysics simulation of advanced nuclear reactors

Griffin is a Multiphysics Object-Oriented Simulation Environment (MOOSE) based reactor physics application for multiphysics simulations of advanced reactor designs jointly developed by Idaho National Laboratory and Argonne National Laboratory. This paper summarizes the motivation, significance, architecture, design, and features of Griffin. Griffin offers flexible and extensible features to address the challenges associated with advanced reactor designs. These features range from fundamental particle transport to specific reactor physics tasks. The features cover a wide range including on-the-fly and traditional two-step cross-section generation methods, steady-state and transient transport solvers suitable for both heterogeneous and homogeneous models, high-fidelity depletion where thousands of isotopes can be tracked and low-fidelity depletion characterized by burnup, etc. The most fundamental aspect that sets Griffin apart from other reactor analysis codes is that it is developed based on the MOOSE framework. A modular development approach is strongly enforced, with multiphysics being an essential element considered since the beginning of Griffin’s development. Griffin links various MOOSE physics modules and couples to other MOOSE-based applications and non-MOOSE-based applications for multiphyiscs simulations. Griffin includes three modules: ISOXML for preparing and managing multigroup cross sections, radiation transport for solving the neutron transport equation, and reactor analysis for user-oriented reactor physics analysis functionalities. Griffin uses various finite element methods for spatial discretization, multigroup approximation for energy discretization and discrete ordinates method, spherical harmonics expansion method, and diffusion approximation for streaming direction discretization to solve the neutron transport equation. Griffin’s flexibility is evidenced through Griffin’s various applications to fast reactor, high-temperature reactor, pebble bed reactor, molten salt reactor, and microreactor designs. Griffin development follows the software quality assurance procedure for MOOSE-based applications and with software requirements consistent with the ASME NQA-1 standard. Griffin has been adopted into the reactor analysis system for the U.S. NRC and is in use at U.S. companies, universities and national laboratories.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

GRIDS-Net: Inverse shape design and identification of scatterers via geometric regularization and physics-embedded deep learning

This study presents a deep learning based methodology for both remote sensing and design of acoustic scatterers. The ability to determine the shape of a scatterer, either in the context of material design or sensing, plays a critical role in many practical engineering problems. This class of inverse problems is extremely challenging due to their high-dimensional, nonlinear, and ill-posed nature. To overcome these technical hurdles, we introduce a geometric regularization approach for deep neural networks (DNN) based on non-uniform rational B-splines (NURBS) and capable of predicting complex 2D scatterer geometries in a parsimonious dimensional representation. Then, this geometric regularization is combined with physics-embedded learning and integrated within a robust convolutional autoencoder (CAE) architecture to accurately predict the shape of 2D scatterers in the context of identification and inverse design problems. Further, an extensive numerical study is presented in order to showcase the remarkable ability of this approach to handle complex scatterer geometries while generating physically-consistent acoustic fields. The study also assesses and contrasts the role played by the (weakly) embedded physics in the convergence of the DNN predictions to a physically consistent inverse design.

42 ENGINEERING↗
DOE OSTI2021

Recurrent neural network-based multiaxial plasticity model with regularization for physics-informed constraints

We report a recurrent neural network (RNN) based model is developed as a surrogate to predict nonlinear plastic response under multiaxial loading. The RNN-based model is trained and tested on stress versus strain curves generated using a numerical solution based on the classical radial return method. Besides simply learning the basic constitutive relationship, a novel approach is taken to enforce certain physical conditions. Specifically, regularization is employed to maintain non-negative plastic power density throughout the loading history thereby ensuring monotonically increasing plastic work and thermodynamic consistency. Enforcing physics in this manner permits coupling of the data-driven RNN approach with physics-based knowledge and laws. This has the effect of reducing the necessary amount of data and ensuring known physical laws are not violated. Since, once trained, the model need not perform the expensive task of solving nonlinear equations, its efficiency is orders of magnitude greater than its numerical counterpart. The RNN-based model has been trained on varied sets of data and the accuracy on test datasets validated. The developed model is general and robust and has widespread application such as in the simulation of metal forming, large scale plasticity, and part life prediction.

42 ENGINEERING↗