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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A comprehensive and fair comparison of two neural operators (with practical extensions) based on $\mathrm{FAIR}$ data

Neural operators can learn nonlinear mappings between function spaces and offer a new simulation paradigm for real-time prediction of complex dynamics for realistic diverse applications as well as for system identification in science and engineering. Herein, we investigate the performance of two neural operators, which have shown promising results so far, and we develop new practical extensions that will make them more accurate and robust and importantly more suitable for industrial-complexity applications. The first neural operator, DeepONet, was published in 2019 (Lu et al., 2019), and its original architecture was based on the universal approximation theorem of Chen & Chen (1995). The second one, named Fourier Neural Operator or FNO, was published in 2020, and it is based on parameterizing the integral kernel in the Fourier space. DeepONet is represented by a summation of products of neural networks (NNs), corresponding to the branch NN for the input function and the trunk NN for the output function; both NNs are general architectures, e.g., the branch NN can be replaced with a CNN or a ResNet. According to Kovachki et al. (2021), FNO in its continuous form can be viewed conceptually as a DeepONet with a specific architecture of the branch NN and a trunk NN represented by a trigonometric basis. In order to compare FNO with DeepONet computationally for realistic setups, we develop several extensions of FNO that can deal with complex geometric domains as well as mappings where the input and output function spaces are of different dimensions. We also develop an extended DeepONet with special features that provide inductive bias and accelerate training, and we present a faster implementation of DeepONet with cost comparable to the computational cost of FNO, which is based on the Fast Fourier Transform. Here we consider 16 different benchmarks to demonstrate the relative performance of the two neural operators, including instability wave analysis in hypersonic boundary layers, prediction of the vorticity field of a flapping airfoil, porous media simulations in complex-geometry domains, etc. We follow the guiding principles of FAIR (Findability, Accessibility, Interoperability, and Reusability) for scientific data management and stewardship. The performance of DeepONet and FNO is comparable for relatively simple settings, but for complex geometries the performance of FNO deteriorates greatly. We also compare theoretically the two neural operators and obtain similar error estimates for DeepONet and FNO under the same regularity assumptions.

42 ENGINEERING↗
DOE OSTI2025

Enabling Multireference Calculations on Multimetallic Systems with Graphic Processing Units

Modeling multimetallic systems efficiently enables faster prediction of desirable chemical properties and the design of new materials. This work describes an initial implementation for performing multireference wave function method localized active-space self-consistent field (LASSCF) calculations through the use of multiple graphics processing units (GPUs) to accelerate time-to-solution. Density fitting is leveraged to reduce memory requirements, and we demonstrate the ability to fully utilize multi-GPU compute nodes. Performance improvements of 5–10x in total application runtime were observed in LASSCF calculations for multimetallic catalyst systems up to 1200 AOs and an active space of (22e,40o) using up to four NVIDIA A100 GPUs. Furthermore, written with performance portability in mind, a comparable performance is also observed in early runs on the Aurora exascale system using Intel Max Series GPUs.

Algorithms↗
DOE OSTI2020

Stringent constraints on neutron-star radii from multimessenger observations and nuclear theory

The properties of neutron stars are determined by the nature of the matter that they contain. These properties can be constrained by measurements of the star’s size. We obtain stringent constraints on neutron-star radii by combining multimessenger observations of the binary neutron-star merger GW170817 with nuclear theory that best accounts for density-dependent uncertainties in the equation of state. We construct equations of state constrained by chiral effective field theory and marginalize over these using the gravitational-wave observations. Combining this with the electromagnetic observations of the merger remnant that imply the presence of a short-lived hypermassive neutron star, we find that the radius of a 1.4 M⊙ neutron star is $R_{1.4M_⊙} = 11.0^{+0.9}_{-0.6} km$ (90% credible interval). Finally, using this constraint, we show that neutron stars are unlikely to be disrupted in neutron star–black hole mergers; subsequently, such events will not produce observable electromagnetic emission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Design of a high energy density experiment to measure the suppression of hydrodynamic instability in an applied magnetic field

A transverse magnetic field can suppress the hydrodynamic instability growth of an unstable plasma interface. This effect, of interest to inertial confinement fusion and astrophysics, has mostly been studied via simulation. Here, we present the design of an experiment at the National Ignition Facility (NIF) to demonstrate this effect in a laboratory. Simulations indicate that the timescale for the diffusion of the magnetic field across the mixing region should be at least comparable to the timescale of the instability growth in order to have a measurable suppression effect. This motivates the use of lower density target materials than usual high energy density (HED) hydrodynamics experiments to permit faster hydrodynamics and higher plasma conductivities (through higher temperature), for a given laser drive and magnetic field. We discuss a target design for creating a Rayleigh–Taylor unstable HED plasma interface that uses 320 mg/cc iodine-doped carbon foam as the heavy material, 20 mg/cc carbon foam as the light material, and a 6 lm amplitude, a 120 lm wavelength ripple machined at the interface, which shows a measurable suppression effect with a nominal NIF drive and a 30 T magnetic field (the present facility limit). Here, models indicate lower density foams that may display even larger suppression effects, as the Hohlraum drive also radiatively preheats the foam to permit even higher temperatures and, hence, higher conductivities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Ion cyclotron heating at high plasma density in Proto-MPEX

The physics of ion cyclotron heating (ICH) relevant to the steady-state linear machine MPEX (Material Plasma Exposure eXperiment) has been explored in its predecessor, short-pulse device: Proto-MPEX. MPEX will utilize fundamental ICH to increase heat flux at the target and produce ion temperatures and velocity distributions with improved fidelity to those found in a tokamak divertor region, in comparison to those produced by substrate biasing. In the experiments on Proto-MPEX described here, bulk ion temperatures up to ~15 eV have been achieved with 20 kW net ICH power at 6.5 MHz, using ICH heating of a deuterium plasma produced by a helicon plasma source. The heat flux at the target has been observed to increase throughout the plasma cross section, including in the core region. Core $T_i$ and target heat flux are observed to scale linearly with injected ICH power. Further, measurements of plasma loading and target heat flux as a function of the magnetic field strength at the antenna, together with modeling of the wave propagation from the antenna to the ion cyclotron resonance using the ANTENA and COMSOL codes with a warm plasma dielectric tensor, indicate that power is coupled to the core plasma via fast wave excitation of a kinetic Alfvén wave.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Staged cooling of a fusion-grade plasma in a tokamak thermal quench

Abstract In tokamak disruptions where the magnetic connection length becomes comparable to or even shorter than the plasma mean-free-path, parallel transport can dominate the energy loss and the thermal quench of the core plasma goes through four phases (stages) that have distinct temperature ranges and durations. The main temperature drop occurs while the core plasma remains nearly collisionless, with the parallel electron temperature T e ∥ dropping in time t as T e ∥ ∝ t − 2 and a cooling time that scales with the ion sound wave transit time over the length of the open magnetic field line. These surprising physics scalings are the result of effective suppression of parallel electron thermal conduction in an otherwise bounded, quasineutral, and collisionless plasma, which is different from what are known to date on electron thermal conduction along the magnetic field in a nearly collisionless and quasineural plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Finding simplicity: unsupervised discovery of features, patterns, and order parameters via shift-invariant variational autoencoders *

Abstract Recent advances in scanning tunneling and transmission electron microscopies (STM and STEM) have allowed routine generation of large volumes of imaging data containing information on the structure and functionality of materials. The experimental data sets contain signatures of long-range phenomena such as physical order parameter fields, polarization, and strain gradients in STEM, or standing electronic waves and carrier-mediated exchange interactions in STM, all superimposed onto scanning system distortions and gradual changes of contrast due to drift and/or mis-tilt effects. Correspondingly, while the human eye can readily identify certain patterns in the images such as lattice periodicities, repeating structural elements, or microstructures, their automatic extraction and classification are highly non-trivial and universal pathways to accomplish such analyses are absent. We pose that the most distinctive elements of the patterns observed in STM and (S)TEM images are similarity and (almost-) periodicity, behaviors stemming directly from the parsimony of elementary atomic structures, superimposed on the gradual changes reflective of order parameter distributions. However, the discovery of these elements via global Fourier methods is non-trivial due to variability and lack of ideal discrete translation symmetry. To address this problem, we explore the shift-invariant variational autoencoders (shift-VAEs) that allow disentangling characteristic repeating features in the images, their variations, and shifts that inevitably occur when randomly sampling the image space. Shift-VAEs balance the uncertainty in the position of the object of interest with the uncertainty in shape reconstruction. This approach is illustrated for model 1D data, and further extended to synthetic and experimental STM and STEM 2D data. We further introduce an approach for training shift-VAEs that allows finding the latent variables that comport to known physical behavior. In this specific case, the condition is that the latent variable maps should be smooth on the length scale of the atomic lattice (as expected for physical order parameters), but other conditions can be imposed. The opportunities and limitations of the shift VAE analysis for pattern discovery are elucidated.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

The Origin Symphony: Probing Baryogenesis with Gravitational Waves

Affleck-Dine (AD) baryogenesis is compelling yet challenging to probe because of the high energy physics involved. We demonstrate that this mechanism can be realized generically with low-energy new physics without supersymmetry while producing detectable gravitational waves (GWs) sourced by parametric resonance of a light scalar field. In viable benchmark models, the scalar has a mass of ${\cal O}(0.1-10)$ GeV, yielding GWs with peak frequencies of ${\cal O}(10-100)$ Hz. This study further reveals a new complementarity between upcoming LIGO-frequency GW detectors and laboratory searches across multiple frontiers of particle physics.

Cosmology and Nongalactic Astrophysics (astro-ph.C↗
DOE OSTI2023

Moiré Kanamori-Hubbard model for transition metal dichalcogenide homobilayers

Ab initio and continuum model studies predicted that the Γ valley transition metal dichalcogenide (TMD) homobilayers could simulate the conventional multiorbital Hubbard model on the moiré honeycomb lattice. Here, in this work, we perform the Wannierization starting from the continuum model and show that a more general moiré Kanamori-Hubbard model emerges, beyond the extensively studied standard multiorbital Hubbard model, which can be used to investigate the many-body physics in the Γ valley TMD homobilayers. Using the unrestricted Hartree-Fock and Lanczos techniques, we study these half-filled multiorbital moiré bands. By constructing the phase diagrams we predict the presence of an antiferromagnetic state and in addition we found unexpected and dominant states, such as a S = 1 ferromagnetic insulator and a charge density wave state. Our theoretical predictions made using this model can be tested in future experiments on the Γ valley TMD homobilayers.

2-dimensional systems↗
DOE OSTI2022

Numerical relativity simulations of prompt collapse mergers: Threshold mass and phenomenological constraints on neutron star properties after GW170817

We determine the threshold mass for prompt (no bounce) black hole formation in equal-mass neutron star (NS) mergers using a new set of 227 numerical relativity simulations. We consider 23 phenomenological and microphysical finite-temperature equations of state (EOS), including models with hyperons and first-order phase transitions to deconfined quarks. We confirm the existence of EOS-insensitive relations between the threshold mass, binary tidal parameter at the threshold (Λth), maximum mass of nonrotating NSs, and radii of reference mass NSs. We combine the EOS-insensitive relations, phenomenological constraints on NS properties, and observational data from GW170817 to derive an improved lower limit on radii of maximum mass and a 1.6 M ⊙ NS of 9.81 and 10.90 km, respectively. We also constrain the radius and quadrupolar tidal deformability (Λ) of a 1.4 M ⊙ NS to be larger than 10.74 km and 172, respectively. We consider uncertainties in all independent parameters—fitting coefficients as well as GW170817 masses while reporting the range of radii constraints. We discuss an approach to constrain the upper as well as lower limit of NS maximum mass using future binary NS detections and their identification as prompt or delayed collapse. With future observations, it will be possible to derive even tighter constraints on the properties of matter at and above nuclear density using the method proposed in this work.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Preparations for quantum simulations of quantum chromodynamics in 1+1 dimensions. I. Axial gauge

Here, tools necessary for quantum simulations of 1+1 dimensional quantum chromodynamics are developed. When formulated in axial gauge and with two flavors of quarks, this system requires 12 qubits per spatial site with the gauge fields included via nonlocal interactions. Classical computations and D-wave’s quantum annealer advantage are used to determine the hadronic spectrum, enabling a decomposition of the masses and a study of quark entanglement. Color “edge” states confined within a screening length of the end of the lattice are found. IBM’s seven-qubit quantum computers, ibmq_jakarta and ibm_perth, are used to compute dynamics from the trivial vacuum in one-flavor QCD with one spatial site. More generally, the Hamiltonian and quantum circuits for time evolution of 1+1 dimensional SU(N c ) gauge theory with Nf flavors of quarks are developed, and the resource requirements for large-scale quantum simulations are estimated.

1+1 dimensions↗
DOE OSTI2024

Geometric and thermodynamic characterization of binary neutron star accretion discs

Accretion disks formed in binary neutron star mergers play a central role in many astrophysical processes of interest, including the launching of relativistic jets or the ejection of neutron-rich matter hosting heavy element nucleosynthesis. In this work we analyze in detail the properties of accretion disks from 44 ab initio binary neutron star merger simulations for a large set of nuclear equations of state, binary mass ratios, and remnant fates, with the aim of furnishing reliable initial conditions for disk simulations and a comprehensive characterization of their properties. We find that the disks have a significant thermal support, with an aspect ratio decreasing with the mass ratio of the binary from ~0.7 to 0.3. Even if the disk sample spans a broad range in mass and angular momentum, their ratio is independent from the equation of state and from the mass ratio. This can be traced back to the rotational profile of the disk, characterized by a constant specific angular momentum (as opposed to a Keplerian one) of 3 – 5×10 16 cm 2 s –1 . The profiles of the entropy per baryon and of the electron fraction depend on the mass ratio of the binary. For more symmetric binaries, they follow a sigmoidal distribution as a function of the rest mass density, for which we provide a detailed description and a fit. Furthermore, the disk properties discussed in this work can be used as a robust set of initial conditions for future long-term simulations of accretion disks from binary neutron star mergers, posing the basis for progress in the quantitative study of the outflow properties.

79 ASTRONOMY AND ASTROPHYSICS↗