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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

MODIS Reflective Solar Band Calibration Improvements using Pseudo-Invariant Desert Targets

To provide the best science data quality, an accurate characterization of the response versus scan angle (RVS) function is critical for the MODIS reflective solar bands (RSB) on-orbit calibration. In every MODIS operational scan, the Earth’s surface, referred to here as Earth view (EV), the space view (SV) port, and the onboard calibrators are viewed via a two-sided scan mirror. The RVS is defined as the sensor’s relative response as a function the angle of incidence (AOI) to the scan mirror. Many different approaches have been developed to derive the time-dependent RVS and its look-up table (LUT) applied to MODIS Level 1B (L1B) products since calibration Collection 4. For most MODIS RSB, the on-board calibrators can reasonably track the RVS change with time. In practice, their RVS is derived using data from on-board calibrators and the EV mirror side ratio (for mirror side 2). For Terra bands 1-4, 8-10 and Aqua bands 1-4, 8-9, an enhancement has been employed in Collections 6 and 6.1 (C6/C6.1) by using Earth scene response trending from pseudo-invariant desert sites in addition to the onboard calibrators. The current C6/C6/1 RVS algorithm is focused on fitting the EV data at each AOI over time and then deriving the relative change at different AOI. The EV response trending is currently fitted with multiple segments over time. Alternatively, the EV responses can be fit first as a function of AOI before fitting temporally in order to reduce the dependence on the stability of the desert site. These pre-treatment methods on the EV data provide improvement in the derived calibration coefficients. However, evidence of insufficient calibration is still observed in the MODIS L1B reflectance data, especially in the form of differences between the mirror sides. In this paper, we review the current methodologies that utilize the EV response trends from the pseudo-invariant Libyan desert targets to supplement the gain derived from the onboard calibrators. An improvement is then proposed and investigated such that a sliding window average (SWA) is used to pre-process the raw EV data. The SWA parameters are carefully selected using trade-off studies to accurately track the Earth scene response trending in multiple cases to overcome the reflectance differences between two mirror sides. Calibration results show improvements for both Aqua and Terra MODIS RSB L1B data products. This new adjustment has been included in the recently delivered Collection 7 LUT that will be evident in the L1B products expected to be released in late 2021.

MODIS↗
NASA NTRS2021

Additional Characterization of Dome-C to Improve its Use as an Invariant Visible Calibration Target

Dome-C is a recommended CEOS invariant target that has been utilized by the calibration community for several decades for monitoring onboard sensor calibration systems as well radiometric inter-comparisons. Dome-C is a high-altitude Earth target located on the East Antarctic interior plateau, which has a permanent bright, flat, and homogeneous snow-covered surface with little aerosol, cloud cover, snowfall, and water vapor burden. This paper describes angular directional models for characterizing the Dome-C top-of-atmosphere (TOA)radiances as a function of cosine solar zenith angle for pre-solstice and post-solstice conditions. The 0.86-μm channel Dome-C reflectance decreases over the summer due to snow metamorphosisis not observed by the visible channels. Coinciding Terra and AquaMODIS Dome-C reflectance showed occasional inter-annual anomalies when compared against the deep convective cloud and Libya-4 invariant targets observations. Further characterization of the Dome-C reflectances with the Dome-C surface broadband albedo, Antarctic Oscillation(AAO) index, and ozone concentration values were evaluated. A strong correlation with ozone was found for the 0.55-μm and 0.65-μm MODIS channels. The monthly Dome-C reflectances were linearly regressed with ozone to derive the ozone correction coefficients. The uncertainty in the Aqua-and Terra-MODIS Dome-C trends was reduced by half after applying ozone corrections to both the 0.55-μm and 0.65-μm channelTOA observations.

David R Doelling↗
NASA NTRS2023

Implementation and Assessment of Menter’s Galilean-Invariant γ Transition Model in OVERFLOW

With an increased emphasis on greener air transports and sustainable aviation, the modeling of laminar-to-turbulent boundary layer transition is anticipated to have an added significance, particularly in the applications related to laminar flow technology. However, unmanned aerial vehicles, crewed reentry vehicles, and ground-to-flight extrapolation all benefit from transition models. Because no single transition model is ideal for the complete spectrum of applications, it is useful to incorporate a variety of models in general-purpose CFD solvers, such as the NASA OVERFLOW Overset CFD code. While the Langtry-Menter 𝛄 − 𝑹𝒆 𝛉𝒕 model, currently available in OVERFLOW, has been widely used for CFD predictions of flows with laminar, transitional, and turbulent boundary layers, it does not possess the Galilean invariance property, a desirable attribute for rotorcraft applications. To help overcome that limitation, we have recently implemented Menter's baseline version of the SST-based γ transition model, along with a Galilean invariant stationary crossflow extension within OVERFLOW (version 2.3e). An initial assessment of the newly implemented model has been carried out using 2D benchmark cases including flat plates and the NLF-0416 airfoil, addressing several transition scenarios ranging from bypass transition due to freestream turbulence, natural transition via Tollmien-Schlichting instabilities, and transition due to a laminar separation bubble. The crossflow extension has been applied to the infinite swept NLF(2)-0415 wing and the 6:1 prolate spheroid. Wherever possible, the results were obtained on a sequence of meshes to ascertain the grid convergence behavior, which has been evaluated through global metrics such as force coefficients as well as local values of the skin-friction coefficient at selected points near and within the transition region. Overall, the model appears to be correctly implemented and the results show promise for further development using the framework of the γ transition model.

CFD modeling↗
NASA NTRSDate not supplied

A Numerical Method for Computing the State Transition Matrix Using Poincare Integral Invariants

The Poincare integral invariants describe the volumes of sets in Hamiltonian phase space. We use these invariants to derive a new numerical procedure for obtaining the state transition matrix (STM), which can be applied to both conservative and nonconservative systems. The method is analogous to a finite difference approximation of the STM, where perturbed states are numerically propagated along with the reference trajectory. We discuss the mathematical similarities between this new STM and existing methods, show numerical results for orbital motion and uncertainty propagation, and discuss new insights afforded by the Hamiltonian properties of phase flow.

state transition matrix↗
DOE OSTI2025

RINO: Renormalization Group Invariance with No Labels

A common challenge with supervised machine learning (ML) in high energy physics (HEP) is the reliance on simulations for labeled data, which can often mismodel the underlying collision or detector response. To help mitigate this problem of domain shift, we propose RINO (Renormalization Group Invariance with No Labels), a self-supervised learning approach that can instead pretrain models directly on collision data, learning embeddings invariant to renormalization group flow scales. In this work, we pretrain a transformer-based model on jets originating from quantum chromodynamic (QCD) interactions from the JetClass dataset, emulating real QCD-dominated experimental data, and then finetune on the JetNet dataset -- emulating simulations -- for the task of identifying jets originating from top quark decays. RINO demonstrates improved generalization from the JetNet training data to JetClass data compared to supervised training on JetNet from scratch, demonstrating the potential for RINO pretraining on real collision data followed by fine-tuning on small, high-quality MC datasets, to improve the robustness of ML models in HEP.

Hao, Zichun [Caltech] (ORCID:0000000256244907)↗
DOE OSTI2021

Second-order invariant domain preserving approximation of the compressible Navier–Stokes equations

Here, we present a fully discrete approximation technique for the compressible Navier–Stokes equations that is second-order accurate in time and space, semi-implicit, and guaranteed to be invariant domain preserving. The restriction on the time step is the standard hyperbolic CFL condition, i.e. τ ≲ O ( h ) / V where V is some reference velocity scale and h the typical meshsize.

42 ENGINEERING↗
DOE OSTI2021

A compute-bound formulation of Galerkin model reduction for linear time-invariant dynamical systems

This work aims to advance computational methods for projection-based reduced-order models (ROMs) of linear time-invariant (LTI) dynamical systems. For such systems, current practice relies on ROM formulations expressing the state as a rank-1 tensor (i.e., a vector), leading to computational kernels that are memory bandwidth bound and, therefore, ill-suited for scalable performance on modern architectures. This weakness can be particularly limiting when tackling many-query studies, where one needs to run a large number of simulations. This work introduces a reformulation, called rank-2 Galerkin, of the Galerkin ROM for LTI dynamical systems which converts the nature of the ROM problem from memory bandwidth to compute bound. We present the details of the formulation and its implementation, and demonstrate its utility through numerical experiments using, as a test case, the simulation of elastic seismic shear waves in an axisymmetric domain. We quantify and analyze performance and scaling results for varying numbers of threads and problem sizes. In conclusion, we present an end-to-end demonstration of using the rank-2 Galerkin ROM for a Monte Carlo sampling study. We show that the rank-2 Galerkin ROM is one order of magnitude more efficient than the rank-1 Galerkin ROM (the current practice) and about 970 times more efficient than the full-order model, while maintaining accuracy in both the mean and statistics of the field.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Discrete scale invariance of the quasi-bound states at atomic vacancies in a topological material

Recently, log-periodic quantum oscillations have been detected in the topological materials zirconium pentatelluride (ZrTe 5 ) and hafnium pentatelluride (HfTe 5 ), displaying an intriguing discrete scale invariance (DSI) characteristic. In condensed materials, the DSI is considered to be related to the quasi-bound states formed by massless Dirac fermions with strong Coulomb attraction, offering a feasible platform to study the long-pursued atomic-collapse phenomenon. Here, we demonstrate that a variety of atomic vacancies in the topological material HfTe 5 can host the geometric quasi-bound states with a DSI feature, resembling an artificial supercritical atom collapse. The density of states of these quasi-bound states is enhanced, and the quasi-bound states are spatially distributed in the “orbitals” surrounding the vacancy sites, which are detected and visualized by low-temperature scanning tunneling microscope/spectroscopy. By applying the perpendicular magnetic fields, the quasi-bound states at lower energies become wider and eventually invisible; meanwhile, the energies of quasi-bound states move gradually toward the Fermi energy (E F ). These features are consistent with the theoretical prediction of a magnetic field–induced transition from supercritical to subcritical states. The direct observation of geometric quasi-bound states sheds light on the deep understanding of the DSI in quantum materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Decoding the shift-invariant data: applications for band-excitation scanning probe microscopy *

A shift-invariant variational autoencoder (shift-VAE) is developed as an unsupervised method for the analysis of spectral data in the presence of shifts along the parameter axis, disentangling the physically-relevant shifts from other latent variables. Using synthetic data sets, we show that the shift-VAE latent variables closely match the ground truth parameters. The shift VAE is extended towards the analysis of band-excitation piezoresponse force microscopy data, disentangling the resonance frequency shifts from the peak shape parameters in a model-free unsupervised manner. The extensions of this approach towards denoising of data and model-free dimensionality reduction in imaging and spectroscopic data are further demonstrated. This approach is universal and can also be extended to analysis of x-ray diffraction, photoluminescence, Raman spectra, and other data sets.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Translation-Invariant Quantum Algorithms for Ordered Search are Optimal

Ordered search is the task of finding an item in an ordered list using comparison queries. The best exact classical algorithm for this fundamental problem uses [log 2 n] queries for a list of length n. Quantum computers can achieve a constant-factor speedup, but the best possible coefficient of log 2 n for exact quantum algorithms is only known to lie between (ln2)/π ≈ 0.221 and 4/log 2 605 ≈ 0.4333. We consider a special class of translation-invariant algorithms with no workspace, introduced by Farhi, Goldstone, Gutmann, and Sipser, that has been used to find the best known upper bounds. First, we show that any bounded-error, k-query quantum algorithm for ordered search can be implemented by a k-query algorithm in this special class. Second, we use linear programming to show that the best exact 5-query quantum algorithm can search a list of length 7265, giving an ordered search algorithm that asymptotically uses 5 log 7265 n ≈ 0.390 log 2 n quantum queries.

Translation-invariant quantum algorithms↗
DOE OSTI2020

Nonadiabatic Energy Fluctuations of Scale-Invariant Quantum Systems in a Time-Dependent Trap

We consider the nonadiabatic energy fluctuations of a many-body system in a time-dependent harmonic trap. In the presence of scale-invariance, the dynamics becomes self-similar and the nondiabatic energy fluctuations can be found in terms of the initial expectation values of the second moments of the Hamiltonian, square position, and squeezing operators. Nonadiabatic features are expressed in terms of the scaling factor governing the size of the atomic cloud, which can be extracted from time-of-flight images. We apply this exact relation to a number of examples: the single-particle harmonic oscillator, the one-dimensional Calogero-Sutherland model, describing bosons with inverse-square interactions that includes the non-interacting Bose gas and the Tonks-Girdardeau gas as limiting cases, and the unitary Fermi gas. We illustrate these results for various expansion protocols involving sudden quenches of the trap frequency, linear ramps and shortcuts to adiabaticity. Our results pave the way to the experimental study of nonadiabatic energy fluctuations in driven quantum fluids.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗