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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

An Invariant-Preserving ALE Method for Solids under Extreme Conditions

We are proposing a fundamentally new approach to ALE methods for solids undergoing large deformation due to extreme loading conditions. Our approach is based on a physically-motivated and mathematically rigorous construction of the underlying Lagrangian method, vector/tensor reconstruction, remapping, and interface reconstruction. It is transformational because it deviates dramatically from traditionally accepted ALE methods and provides the following set of unique attributes: (1) a three-dimensional, finite volume, cell-centered ALE framework with advanced hypo-/hyper-elasto-plastic constitutive theories for solids; (2) a new physically and mathematically consistent reconstruction method for vector/tensor fields; (3) advanced invariant-preserving remapping algorithm for vector/tensor quantities; (4) moment-of-fluid (MoF) interface reconstruction technique for multi-material problems with solids undergoing large deformations. This work brings together many new concepts, that in combination with emergent cell-centered Lagrangian hydrodynamics methods will produce a cutting-edge ALE capability and define a new state-of-the-art. Many ideas in this work are new, completely unexplored, and hence high risk. The proposed research and the resulting algorithms will be of immediate use in Eulerian, Lagrangian and ALE codes under the ASC program at the lab. In addition, the research on invariant preserving reconstruction/remap of tensor quantities is of direct interest to ongoing CASL and climate modeling efforts at LANL. The application space impacted by this work includes Inertial Confinement Fusion (ICF), Z-pinch, munition-target interactions, geological impact dynamics, shock processing of powders and shaped charges. The ALE framework will also provide a suitable test-bed for rapid development and assessment of hypo-/hyper-elasto-plastic constitutive theories. Today, there are no invariant-preserving ALE algorithms for treating solids with large deformations. Therefore, this is a high-impact effort that will significantly advance the state of ALE methods and position LANL as world leaders in advanced ALE methods.

42 ENGINEERING↗
DOE OSTI2023

Covariance Testing and Update on 239 Pu and 235 U PFNS Covariances [Slides]

This presentation discusses in detail how covariances were obtained and tested. Along with a look into some of the mathematical checks that were performed. Possible "physics issues" in covariances were highlighted and addressed. Covariances for Dysprosium and Erbium-169 were touched on along with various uncertainties and issues. An update on Uranium-235 and Plutonium-239 Pu PFNS covariances was given.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Diffeomorphism Group Representations in Relativistic Quantum Field Theory

We explore the role played by the di eomorphism group and its unitary representations in relativistic quantum eld theory. From the quantum kinematics of particles described by representations of the di eomorphism group of a space-like surface in an inertial reference frame, we reconstruct the local relativistic neutral scalar eld in the Fock representation. An explicit expression for the free Hamiltonian is obtained in terms of the Lie algebra generators (mass and momentum densities). We suggest that this approach can be generalized to elds whose quanta are spatially extended objects.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS1987

On determining important aspects of mathematical models: Application to problems in physics and chemistry

The use of parametric and functional gradient sensitivity analysis techniques is considered for models described by partial differential equations. By interchanging appropriate dependent and independent variables, questions of inverse sensitivity may be addressed to gain insight into the inversion of observational data for parameter and function identification in mathematical models. It may be argued that the presence of a subset of dominantly strong coupled dependent variables will result in the overall system sensitivity behavior collapsing into a simple set of scaling and self similarity relations amongst elements of the entire matrix of sensitivity coefficients. These general tools are generic in nature, but herein their application to problems arising in selected areas of physics and chemistry is presented.

Rabitz, Herschel↗
DOE OSTI2025

Measurement of the branching ratio of 16 N , 15 C , 12 B , and 13 B isotopes through the nuclear muon capture reaction in the Super-Kamiokande detector

The Super-Kamiokande detector has measured solar neutrinos for more than 25 years. The sensitivity for solar neutrino measurement is limited by the uncertainties of energy scale and background modeling. Decays of unstable isotopes with relatively long half-lives through nuclear muon capture, such as 16 N, 15 C, 12 B, and 13 B, are detected as background events for solar neutrino observations. Here, in this study, we developed a method to form a pair of stopping muon and decay candidate events and evaluated the production rates of such unstable isotopes. We then measured their branching ratios considering both their production rates and the estimated number of nuclear muon capture processes as Br⁡( 16 N) = (9.0 ± 0.1)%, Br⁡( 15 C) = (0.6 ± 0.1)%, Br⁡( 12 B) = (0.98 ± 0.18)%, Br⁡( 13 B) = (0.14 ± 0.12)%, respectively. The result for 16 N has world-leading precision at present and the results for 15 C, 12 B, and 13 B are the first branching ratio measurements for those isotopes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Uncertainty quantification in scientific machine learning: Methods, metrics, and comparisons

Neural networks (NNs) are currently changing the computational paradigm on how to combine data with mathematical laws in physics and engineering in a profound way, tackling challenging inverse and ill-posed problems not solvable with traditional methods. However, quantifying errors and uncertainties in NN-based inference is more complicated than in traditional methods. This is because in addition to aleatoric uncertainty associated with noisy data, there is also uncertainty due to limited data, but also due to NN hyperparameters, overparametrization, optimization and sampling errors as well as model misspecification. Although there are some recent works on uncertainty quantification (UQ) in NNs, there is no systematic investigation of suitable methods towards quantifying the total uncertainty effectively and efficiently even for function approximation, and there is even less work on solving partial differential equations and learning operator mappings between infinite-dimensional function spaces using NNs. In this work, we present a comprehensive framework that includes uncertainty modeling, new and existing solution methods, as well as evaluation metrics and post-hoc improvement approaches. Further, to demonstrate the applicability and reliability of our framework, we present an extensive comparative study in which various methods are tested on prototype problems, including problems with mixed input-output data, and stochastic problems in high dimensions. In the Appendix, we include a comprehensive description of all the UQ methods employed. Further, to help facilitate the deployment of UQ in Scientific Machine Learning research and practice, we present and develop in [1] an open-source Python library (github.com/Crunch-UQ4MI/neuraluq), termed NeuralUQ, that is accompanied by an educational tutorial and additional computational experiments.

11 physics-informed neural networks↗
NASA NTRS1986

Physics through the 1990s: Nuclear physics

The volume begins with a non-mathematical introduction to nuclear physics. A description of the major advances in the field follows, with chapters on nuclear structure and dynamics, fundamental forces in the nucleus, and nuclei under extreme conditions of temperature, density, and spin. Impacts of nuclear physics on astrophysics and the scientific and societal benefits of nuclear physics are then discussed. Another section deals with scientific frontiers, describing research into the realm of the quark-gluon plasma; the changing description of nuclear matter, specifically the use of the quark model; and the implications of the standard model and grand unified theories of elementary-particle physics; and finishes with recommendations and priorities for nuclear physics research facilities, instrumentation, accelerators, theory, education, and data bases. Appended are a list of national accelerator facilities, a list of reviewers, a bibliography, and a glossary.

Source record↗
NASA NTRS1984

Kristian Birkeland - The man and the scientist

A review is presented of Birkeland's outstanding contributions to auroral theory and, in particular, to the foundation of modern magnetospheric physics. Birkeland's first years in research, after a study of mathematics and theoretical physics at the university, were concerned with Maxwell's theory, the investigation of electromagnetic waves in conductors, wave propagation in space, an energy transfer by means of electromagnetic waves, and a general expression for the Poynting vector. Experiments with cathode rays near a magnet in 1895, led Birkeland to the development of an auroral theory. This theory represented the first detailed, realistic explanation of the creation of an aurora. Attention is given to experiments conducted to verify the theory, the discovery of the polar elementary storm, and the deduction of auroral electric currents. Birkeland's background and education is also considered along with his personality.

Egeland, A.↗
NASA NTRS1990

Simulations of cloudy, gaseous galactic disks

Aspects of the simulation of cloudy, gaseous galactic disks are discussed. The motivation for conducting such studies is addressed, and the formulation of the fundamental physical problem in mathematical terms is considered. The computational solution study of the formulated physical problem is examined, and the results and interpretation of computational studies are discussed.

Roberts, William W., Jr.↗
DOE OSTI2015

Historical Building Stability Monitoring by Means of a Cosmic Ray Tracking System

Cosmic ray radiation is mostly composed, at sea level, by high energy muons, which are highly penetrating particles capable of crossing kilometers of rock. The ubiquitous and steady presence at the Earth's surface and the high penetration capability have motivated the use of cosmic ray radiation also in fields beyond particle physics, from geology, archaeology, speleology to industrial applications and homeland security. In particular, in recent years, the novel technique of muon tomography has been proposed, with the aim of performing non invasive inspection of large non accessible volumes, material atomic number Z and density discrimination, and three dimension image reconstruction of the inspected volume. In the present paper, after a short recall of the physical principles and mathematical formalism on which muon tomography is based, a number of examples of application of the novel technique in industry and homeland security issues is given. Moreover, a new application of cosmic rays detection techniques in the field of civil engineering is proposed. The aim is the monitoring of the stability of large structures, in particular the static monitoring of historical buildings, where conservation constraints are more severe and the time evolution of the deformation phenomena under study may be of the order of months or years. The new technique may be seen, in some way, as the reverse problem of muon tomography. As a significant case study, the monitoring of the wooden vaulted roof of the Palazzo della Loggia in the town of Brescia, in Italy, has been considered. The feasibility as well as the performances and limitations of a monitoring system based on cosmic ray tracking have been studied by Monte Carlo simulation and discussed in comparison with more traditional monitoring systems. (authors)

42 ENGINEERING↗
DOE OSTI2016

Alternatives to accuracy and bias metrics based on percentage errors for radiation belt modeling applications

This report reviews existing literature describing forecast accuracy metrics, concentrating on those based on relative errors and percentage errors. We then review how the most common of these metrics, the mean absolute percentage error (MAPE), has been applied in recent radiation belt modeling literature. Finally, we describe metrics based on the ratios of predicted to observed values (the accuracy ratio) that address the drawbacks inherent in using MAPE. Specifically, we define and recommend the median log accuracy ratio as a measure of bias and the median symmetric accuracy as a measure of accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Chiral limit of 2d QCD revisited with lightcone conformal truncation

We study the chiral limit of 2d QCD with a single quark flavor at finite Nc using LCT. By modifying the LCT basis according to the quark mass in a manner motivated by ’t Hooft’s analysis, we are able to restore convergence for quark masses much smaller than the QCD strong coupling scale. For such small quark masses, the IR of the theory is expected to be well described by the Sine-Gordon model. We verify that LCT numerics are able to capture in detail the spectrum and correlation functions of the Sine-Gordon model. This opens up the possibility for studying deformations of various integrable CFTs using LCT by considering the chiral limit of QCD like theories.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Mirror symmetry and elliptic Calabi-Yau manifolds

We find that for many Calabi-Yau threefolds with elliptic or genus one fibrations mirror symmetry factorizes between the fiber and the base of the fibration. In the simplest examples, the generic CY elliptic fibration over any toric base surface B that supports an elliptic Calabi-Yau threefold has a mirror that is an elliptic fibration over a dual toric base surface $\tilde{B}$ that is related through toric geometry to the line bundle -6 K B . The Kreuzer-Skarke database includes all these examples and gives a wide range of other more complicated constructions where mirror symmetry also factorizes. Since recent evidence suggests that most Calabi-Yau threefolds are elliptic or genus one fibered, this points to a new way of understanding mirror symmetry that may apply to a large fraction of smooth Calabi-Yau threefolds. The factorization structure identified here can also apply for CalabiYau manifolds of higher dimension.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Quantum algorithms for conformal bootstrap

With the help of recent developments in quantum algorithms for semidefinite programming, we discuss the possibility for quantum speedup for the numerical conformal bootstrap in conformal field theory. We show that quantum algorithms may have significant improvement in the computational performance for several numerical bootstrap problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Understanding Peelle’s Pertinent Puzzle bias in generalized least squares regression through eigenspectrum analysis

Certain correlation structures in the data covariance matrix (DCM) used for generalized least squares (GLS) regression can result in biased estimates, commonly known in the field of nuclear data evaluation as Peele’s Pertinent Puzzle (PPP). This article introduces a generative, forward modeling framework within which the PPP bias is characterized through an eigenspectrum analysis of the DCM. This analysis highlights the root cause of the bias, generalizes the problem beyond the nuclear data field, and provides insight to the problem regimes where it can occur. What follows is an understanding that the bias can show up for any experimental neutron time-of-flight data for which systematic uncertainties have been quantified. Lastly, a discussion of the adaptation of cross validation approaches that require pre-whitening to incorporate the known ‘fix’ to the PPP bias in the GLS estimator.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Increasing the hardness of posiform planting using random QUBOs for programmable quantum annealer benchmarking

Posiform planting is a method for constructing QUBO instances with a unique planted solution that can be tailored to arbitrary connectivity graphs. In this study we investigate making posiform planted QUBOs computationally harder by fusing many smaller random Ising models, whose global minimum is computed classically, with posiform planted QUBOs. The unique ground state of the resulting QUBO is the concatenation of (exactly one of) the ground states of each smaller problem. Our method generates QUBO instances that have a unique solution, are native to the hardware graph, and have tunable computational hardness. We use our QUBOs to benchmark three D-Wave quantum annealing processors (with 563–5627 qubits), and compare them against simulated annealing and Gurobi. Surprisingly, we find that the D-Wave ground state sampling success rate is not dependent on the glued random QUBO size, and that some QUBO classes are solved at high success rates at short annealing times on the Zephyr processors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Quantum neuromorphic computing

Quantum neuromorphic computing physically implements neural networks in brain-inspired quantum hardware to speed up their computation. In this perspective article, we show that this emerging paradigm could make the best use of the existing and near future intermediate size quantum computers. Some approaches are based on parametrized quantum circuits and use neural network-inspired algorithms to train them. Other approaches, closer to classical neuromorphic computing, take advantage of the physical properties of quantum oscillator assemblies to mimic neurons and synapses to compute. In this work, we discuss the different implementations of quantum neuromorphic networks with digital and analog circuits, highlight their respective advantages, and review exciting recent experimental results.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Resonant amplification of enzymatic chemical oscillations by oscillating flow

Using theory and simulation, we analyzed the resonant amplification of chemical oscillations that occur due to externally imposed oscillatory fluid flows. The chemical reactions are promoted by two enzyme-coated patches located sequentially on the inner surface of a pipe that transports the enclosed chemical solution. In the case of diffusion-limited systems, the period of oscillations in chemical reaction networks is determined by the rate of the chemical transport, which is diffusive in nature and, therefore, can be effectively accelerated by the imposed fluid flows. In this work, we first identify the natural frequencies of the chemical oscillations in the unperturbed reaction–diffusion system and, then, use the frequencies as a forcing input to drive the system to resonance. We demonstrate that flow-induced resonance can be used to amplify the amplitude of the chemical oscillations and to synchronize their frequency to the external forcing. In particular, we show that even 10% perturbations in the flow velocities can double the amplitude of the resulting chemical oscillations. Particularly, effective control can be achieved for the two-step chemical reactions where during the first half-period, the fluid flow accelerates the chemical flux toward the second catalytic patch, while during the second half-period, the flow amplifies the flux to the first patch. The results can provide design rules for regulating the dynamics of coupled reaction–diffusion processes and can facilitate the development of chemical reaction networks that act as chemical clocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗