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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Simulations and models for the Richtmyer– Meshkov instability with broadband perturbations

The Richtmyer–Meshkov instability (RMI) is shock driven and affects many phenomena from inertial fusion to supernova explosions. The behavior of single-modes in the RMI has been studied extensively but less is known with the broadband perturbations that occur in applications. Here, we describe extensive numerical simulations and modeling of the RMI with broadband perturbations with an initial power spectrum of the form P∝ k m , where k is the wavenumber. The hydrodynamic condition is the same as in the $\theta$-Group Collaboration [Thornber et al., “Late-time growth rate, mixing, and anisotropy in the multimode narrowband Richtmyer–Meshkov instability: The $\theta$-group collaboration,” Phys. Fluids 29, 105107 (2017)] with a Mach ~1.86 shock and gamma-law = 5/3 fluids with Atwood number A = 0.5. The bubble amplitude h B is found to grow in two stages. Initially, h B undergoes a phase-inversion and grows linearly in time (t) at a rate consistent with a linear theory. Asymptotically, h B grows as a power law $~t^{\theta}$ when $\langle{k}\rangle{|h_B|}$ > O(1), where $\langle{k}\rangle$ is the average wavenumber for the initial spectrum. The RMI behavior in simulations and modeling agree over a wide range of exponent m, spectral width, initial amplitude, and time. The agreement is quantified objectively using statistical analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Trust-Enhancing Probabilistic Transfer Learning for Sparse and Noisy Data Environments

There is an increasing aspiration to utilize machine learning (ML) for various tasks of relevance to national security. ML models have thus far been mostly applied to tasks and domains that, while impactful, have sufficient volume of data. For predictive tasks of national security relevance, ML models of great capacity (ability to approximate nonlinear trends in input-output maps) are often needed to capture the complex underlying physics. However, scientific problems of relevance to national security are often accompanied by various sources of sparse and/or incomplete data, including experiments and simulations, across different regimes of operation, of varying degrees of fidelity, and include noise with different characteristics and/or intensity. State-of-the-art ML models, despite exhibiting superior performance on the task and domain they were trained on, may suffer detrimental loss in performance in such sparse data environments. This report summarizes the results of the Laboratory Directed Research and Development project entitled Trust-Enhancing Probabilistic Transfer Learning for Sparse and Noisy Data Environments. The objective of the project was to develop a new transfer learning (TL) framework that aims to adaptively blend the data across different sources in tackling one task of interest, resulting in enhanced trustworthiness of ML models for mission- and safety-critical systems. The proposed framework determines when it is worth applying TL and how much knowledge is to be transferred, despite uncontrollable uncertainties. The framework accomplishes this by leveraging concepts and techniques from the fields of Bayesian inverse modeling and uncertainty quantification, relying on strong mathematical foundations of probability and measure theories to devise new uncertainty-aware TL workflows.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2004

Assembly of Colloidal Aggregates by Electrohydrodynamic Flow: Kinetic Experiments and Scaling Analysis

Electric fields generate transverse flows near electrodes that sweep colloidal particles into densely packed assemblies. We interpret this behavior in terms of electrohydrodynamic motion stemming from distortions of the field by the particles that alter the body force distribution in the electrode charge polarization layer. A scaling analysis shows how the action of the applied electric field generates fluid motion that carries particles toward one another. The resulting fluid velocity is proportional to the square of the applied field and decreases inversely with frequency. Experimental measurements of the particle aggregation rate accord with the electrohydrodynamic theory over a wide range of voltages and frequencies.

Ristenpart, W. D.↗
DOE OSTI2020

Navigating collinear superspace

We introduce a new set of effective field theory rules for constructing Lagrangians with \( \mathcal{N} \) = 1 supersymmetry in collinear superspace. In the standard superspace treatment, superfields are functions of the coordinates \( \left({x}^{\mu },{\theta}^{\alpha },{\theta}^{\dagger \overset{\cdot }{\alpha }}\right) \) , and supersymmetry preservation is manifest at the Lagrangian level in part due to the inclusion of auxiliary F - and D -term components. By contrast, collinear superspace depends on a smaller set of coordinates ( x μ , η , η † ), where η is a complex Grassmann number without a spinor index. This provides a formulation of supersymmetric theories that depends exclusively on propagating degrees of freedom, at the expense of obscuring Lorentz invariance and introducing inverse momentum scales. After establishing the general framework, we construct collinear superspace Lagrangians for free chiral matter and non-Abelian gauge fields. For the latter construction, an important ingredient is a superfield representation that is simultaneously chiral, anti-chiral, and real; this novel object encodes residual gauge transformations on the light cone. Additionally, we discuss a fundamental obstruction to constructing inter- acting theories with chiral matter; overcoming these issues is the subject of our companion paper, where we introduce a larger set of superfields to realize the full range of interactions compatible with \( \mathcal{N} \) = 1. Along the way, we provide a novel framing of reparametrization invariance using a spinor decomposition, which provides insight into this important light-cone symmetry.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2002

Retrievals of Profiles of Fine And Coarse Aerosols Using Lidar And Radiometric Space Measurements

In couple of years we expect the launch of the CALIPSO lidar spaceborne mission designed to observe aerosols and clouds. CALIPSO will collect profiles of the lidar attenuated backscattering coefficients in two spectral wavelengths (0.53 and 1.06 microns). Observations are provided along the track of the satellite around the globe from pole to pole. The attenuated backscattering coefficients are sensitive to the vertical distribution of aerosol particles, their shape and size. However the information is insufficient to be mapped into unique aerosol physical properties and vertical distribution. Infinite number of physical solutions can reconstruct the same two wavelength backscattered profile measured from space. CALIPSO will fly in formation with the Aqua satellite and the MODIS spectro-radiometer on board. Spectral radiances measured by MODIS in six channels between 0.55 and 2.13 microns simultaneously with the CALIPSO observations can constrain the solutions and resolve this ambiguity, albeit under some assumptions. In this paper we describe the inversion method and apply it to aircraft lidar and MODIS data collected over a dust storm off the coast of West Africa during the SHADE experiment. It is shown that the product of the single scattering albedo, omega, and the phase function, P, for backscattering can be retrieved from the synergism between measurements avoiding a priori hypotheses required for inverting lidar measurements alone. The resultant value of (omega)P(180 deg.) = 0.016/sr are significantly different from what is expected using Mie theory, but are in good agreement with recent results obtained from lidar observations of dust episodes. The inversion is robust in the presence of noise of 10% and 20% in the lidar signal in the 0.53 and 1.06 pm channels respectively. Calibration errors of the lidar of 5 to 10% can cause an error in optical thickness of 20 to 40% respectively in the tested cases. The lidar calibration errors cause degradation in the ability to fit the MODIS data. Therefore the MODIS measurements can be used to identify the calibration problem and correct for it. The CALIPSO-MODIS measurements of the profiles of fine and coarse aerosols, together with CALIPSO measurements of clouds vertical distribution, is expected to be critically important in understanding aerosol transport across continents and political boundaries, and to study aerosol-cloud interaction and its effect on precipitation and global forcing of climate.

Kaufman, Yoram↗
DOE OSTI2023

Microsecond Isomer at the N = 20 Island of Shape Inversion Observed at FRIB

Excited-state spectroscopy from the first experiment at the Facility for Rare Isotope Beams (FRIB) is reported. A 24(2)-μs isomer was observed with the FRIB Decay Station initiator (FDSi) through a cascade of 224- and 401-keV γ rays in coincidence with 32 Na nuclei. This is the only known microsecond isomer (1 μs ≤T 1/2 <1 ms) in the region. This nucleus is at the heart of the N=20 island of shape inversion and is at the crossroads of the spherical shell-model, deformed shell-model, and ab initio theories. It can be represented as the coupling of a proton hole and neutron particle to 32 Mg, 32 Mg+π -1 +ν +1 . This odd-odd coupling and isomer formation provides a sensitive measure of the underlying shape degrees of freedom of 32 Mg, where the onset of spherical-to-deformed shape inversion begins with a low-lying deformed 2 + state at 885 keV and a low-lying shape-coexisting 0$^+_2$ state at 1058 keV. Here, we suggest two possible explanations for the 625-keV isomer in 32 Na: a 6 - spherical shape isomer that decays by E2 or a 0 + deformed spin isomer that decays by M2. The present results and calculations are most consistent with the latter, indicating that the low-lying states are dominated by deformation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

High-throughput investigation of the formation of double spinels

Spinel compounds, with the general chemical formula AB 2 O 4 , are a wide class of materials, where A and B can be a variety of cations, providing this structure with a great deal of functional flexibility and giving rise to its considerable scientific interest. Recently, a spinel with the general formula ABB'O 4 has been predicted, increasing the possible usability of the spinels due to the higher cation diversity in the so-called double spinel structure. In this study, we use density functional theory calculations to predict if double spinels can be formed between experimentally synthesized normal and inverse single spinels. Our computations reveal that 49 double spinels have negative mixing enthalpies and are thus thermodynamically stable, with most of the stable compounds being formed from one of two distinct cation orderings. We show that the 17 different cations that form the different double spinels have a preferred site, tetrahedral or octahedral, except for Mn, Fe and Co which can occupy both sites interchangeably. We also study the relation between mixing enthalpies and cation-specific properties, as well as ways to classify the double spinels into distinct types and spinel groups depending on the cation ordering and cation oxidation states, respectively. Furthermore, by applying the Sure Independence Screening and Sparsifying Operator (SISSO) approach on the coordination-dependent ionic radii of the elemental constituents, we show that an interplay of local strain and electrostatic dominated terms can be used to separate the double spinels into distinct structural types depending on the cation order and their oxidation states.

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

Automated reaction kinetics and network exploration (Arkane): A statistical mechanics, thermodynamics, transition state theory, and master equation software

The open-source statistical mechanics software described here, Arkane–Automated Reaction Kinetics and Network Exploration–facilitates computations of thermodynamic properties of chemical species, high-pressure limit reaction rate coefficients, and pressure-dependent rate coefficient over multi-well molecular potential energy surfaces (PES) including the effects of collisional energy transfer on phenomenological kinetics. Arkane can use estimates to fill in information for molecules or reactions where quantum chemistry information is missing. The software solves the internal energy master equation for complex unimolecular reaction systems. Inputs to the software include converged electronic structure computations performed by the user using a variety of supported software packages (Gaussian, Molpro, Orca, TeraChem, Q-Chem, Psi4). The software outputs high-pressure limit rate coefficients and pressure-dependent phenomenological rate coefficients, as well as computed thermodynamic properties (enthalpy, entropy, and constant pressure heat capacity) with added energy corrections. Some of the key features of Arkane include treatment of 1D, 2D or ND hindered internal rotation modes, treatment of free internal rotation modes, quantum tunneling effect consideration, transition state theory (TST) and Rice-Ramsperger-Kassel-Marcus (RRKM) rate coefficient computations, master equation solution with four implemented methods, inverse-Laplace transform of high-pressure limit rate coefficients into the energy domain, energy corrections based on bond-additivity or isodesmic reactions, automated and efficient PES exploration, and PES sensitivity analysis. The present work describes the design of Arkane, how it should be used, and refers to the theory that it employs. Arkane is distributed via the RMG-Py software suite (https://github.com/ReactionMechanismGenerator/RMG-Py).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

The inversion formula and 6j symbol for 3d fermions

In this work we study the 6 j symbol of the 3 d conformal group for fermionic operators. In particular, we study 4-point functions containing two fermions and two scalars and also those with four fermions. By using weight-shifting operators and harmonic analysis for the Euclidean conformal group, we relate these spinning 6 j symbols to the simpler 6 j symbol for four scalar operators. As one application we use these techniques to compute 3 d mean field theory (MFT) OPE coefficients for fermionic operators. We then compute corrections to the MFT spectrum and couplings due to the inversion of a single operator, such as the stress tensor or a low-dimension scalar. These results are valid at finite spin and extend the perturbative large spin analysis to include non-perturbative effects in spin.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1989

Spin-lattice relaxation and the calculation of gain, pump power, and noise temperature in ruby

The use of a quantitative analysis of the dominant source of relaxation in ruby spin systems to make predictions of key maser amplifier parameters is described. The spin-lattice Hamiltonian which describes the interaction of the electron spins with the thermal vibrations of the surrounding lattice is obtained from the literature. Taking into account the vibrational anisotropy of ruby, Fermi's rule is used to calculate the spin transition rates between the maser energy levels. The spin population rate equations are solved for the spin transition relaxation times, and a comparison with previous calculations is made. Predictions of ruby gain, inversion ratio, and noise temperature as a function of physical temperature are made for 8.4-GHz and 32-GHz maser pumping schemes. The theory predicts that ruby oriented at 90 deg will have approximately 50 percent higher gain in dB and slightly lower noise temperature than a 54.7-deg ruby at 32 GHz (assuming pump saturation). A specific calculation relating pump power to inversion ratio is given for a single channel of the 32-GHz reflected wave maser.

Lyons, J. R.↗
NASA NTRS1973

A geometric theory for the QR, LU and power iterations.

Consideration of the task of computing the invariant subspaces of a given matrix. For this purpose the LU, QR, treppen and bi-iterations have been presented, used, and studied more or less independently of the old-fashioned power method. Each of these methods generates implicitly a sequence of subspaces which determines the convergence properties of the method. The iterations differ in the way in which a basis is constructed to represent each subspace. This aspect largely determines the usefulness of the method. It is shown that the first four iterations produce exactly the same sequence of subspaces as do direct and inverse iteration started from appropriate subspaces. Their convergence properties are therefore the same, and a complete geometric convergence theory is presented in terms of the power method. It is shown that Hessenberg matrices are associated with ideal starting spaces.

Parlett, B. N.↗
NASA NTRS1976

Correlation between nonequilibrium thermodynamic theory and V-I curves of a thermionic converter

The methods of irreversible thermodynamics are used as a basis for developing a transport theory applicable to thermionic cesium diodes. This theory is applied in describing certain aspects of experimental voltage-current (V-I) characteristic curves of a thermionic diode. Emphasis is placed on the open-circuit voltage and short-circuit current of the V-I curves. Experimental results show that the open-circuit voltage is essentially independent of the interelectrode spacing, whereas the short-circuit current varies inversely with the interelectrode separation. The inverse dependence is in agreement with the results of the present analysis and also with results expected from diffusion theory, which has been used in other analyses. In fact, the theory used in this investigation reduces to diffusion theory under special assumptions. Deviations from diffusion theory, which were found in experimental results, can be accounted for using the theory developed in this paper.

Robinson, L. B.↗
NASA NTRS1977

Does electromagnetic radiation accelerate galactic cosmic rays

The 'reactor' theories of Tsytovich and collaborators (1973) of cosmic-ray acceleration by electromagnetic radiation are examined in the context of galactic cosmic rays. It is shown that any isotropic synchrotron or Compton reactors with reasonable astrophysical parameters can yield particles with a maximum relativistic factor of only about 10,000. If they are to produce particles with higher relativistic factors, the losses due to inverse Compton scattering of the electromagnetic radiation in them outweigh the acceleration, and this violates the assumptions of the theory. This is a critical restriction in the context of galactic cosmic rays, which have a power-law spectrum extending up to a relativistic factor of 1 million.

Eichler, D.↗
NASA NTRS2003

Simplified Formulae System for Resonant Inverse Compton Scattering of a Fast Electron in an Intense Magnetic Field

We present simple analytical formulae for the emission spectrum and total power of a special kind of resonant inverse Compton scattering (RICS) of a relativistic electron in an intense magnetic field. In contrast with the available formulae system, we obtain a markedly simplified one based on the semiclassical quantum theory, which is more understandable for people who are unfamiliar with quantum electrodynamics. We show that the RICS process, under an appropriate 'accommodation condition' derived in this paper, is predominantly much more efficient than the coexistent ordinary inverse Compton scattering, and produces highly beamed high-frequency radiation with moderately good monochromaticity. Our formulae are simple to use - thus offering a lucid physical intuition for the theory - and may find wide applications in hard X-ray and gamma-ray astrophysics.

You, J. H.↗
DOE OSTI2023

Visualization and efficient generation of constrained high-dimensional theoretical parameter spaces

We describe a set of novel methods for efficiently sampling high-dimensional parameter spaces of physical theories defined at high energies, but constrained by experimental measurements made at lower energies. Often, theoretical models such as supersymmetry are defined by many parameters, $\mathcal{O}$(10 – 100), expressed at high energies, while relevant experimental constraints are often defined at much lower energies, preventing them from directly ruling out portions of the space. Instead, the low-energy constraints define a complex, potentially non-contiguous subspace of the theory parameters. Naive scanning of the theory space for points which satisfy the low-energy constraints is hopelessly inefficient due to the high dimensionality, and the inverse problem is considered intractable. As a result, many theoretical spaces remain under-explored. We introduce a class of modified generative autoencoders, which attack this problem by mapping the high-dimensional parameter space to a structured low-dimensional latent space, allowing for easy visualization and efficient generation of theory points which satisfy experimental constraints. An extension without dimensional compression, which focuses on limiting potential information loss, is also introduced.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Solving Stochastic Inverse Problems for Property–Structure Linkages Using Data-Consistent Inversion and Machine Learning

Determining process–structure–property linkages is one of the key objectives in material science, and uncertainty quantification plays a critical role in understanding both process–structure and structure–property linkages. In this work, we seek to learn a distribution of microstructure parameters that are consistent in the sense that the forward propagation of this distribution through a crystal plasticity finite element model matches a target distribution on materials properties. This stochastic inversion formulation infers a distribution of acceptable/consistent microstructures, as opposed to a deterministic solution, which expands the range of feasible designs in a probabilistic manner. Furthermore, to solve this stochastic inverse problem, we employ a recently developed uncertainty quantification framework based on push-forward probability measures, which combines techniques from measure theory and Bayes’ rule to define a unique and numerically stable solution. This approach requires making an initial prediction using an initial guess for the distribution on model inputs and solving a stochastic forward problem. To reduce the computational burden in solving both stochastic forward and stochastic inverse problems, we combine this approach with a machine learning Bayesian regression model based on Gaussian processes and demonstrate the proposed methodology on two representative case studies in structure–property linkages.

36 MATERIALS SCIENCE↗
DOE OSTI2023

All-order celestial OPE from on-shell recursion

We determine tree level, all-order celestial operator product expansions (OPEs) of gluons and gravitons in the maximally helicity violating (MHV) sector. We start by obtaining the all-order collinear expansions of MHV amplitudes using the inverse soft recursion relations that they satisfy. These collinear expansions are recast as celestial OPE expansions in bases of momentum as well as boost eigenstates. This shows that inverse soft recursion for MHV amplitudes is dual to OPE recursion in celestial conformal field theory.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Nature of Zirconia on a Copper Inverse Catalyst Under CO 2 Hydrogenation Conditions

The growing concern over the escalating levels of anthropogenic CO 2 emissions necessitates effective strategies for its conversion to valuable chemicals and fuels. In this research, we embark on a comprehensive investigation of the nature of zirconia on a copper inverse catalyst under the conditions of CO 2 hydrogenation to methanol. We employ density functional theory calculations in combination with the Grand Canonical Basin Hopping method, enabling an exploration of the free energy surface including a variable amount of adsorbates within the relevant reaction conditions. Our focus centers on a model three-atom Zr cluster on a Cu(111) surface decorated with various OH, O, and formate ligands, noted Zr 3 O x (OH) y (HCOO) z /Cu(111), revealing major changes in the active site induced by various reaction parameters such as the gas pressure, temperature, conversion levels, and CO 2 /H 2 feed ratios. Further, through our analysis, we have unveiled insights into the dynamic behavior of the catalyst. Specifically, under reaction conditions, we observe a large number of composition and structures with similar free energy for the catalyst, with respect to changing the type, number, and binding sites of adsorbates, suggesting that the active site should be regarded as a statistical ensemble of diverse structures that interconvert.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗