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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 OSTI2023

Oracle-Preserving Latent Flows

A fundamental task in data science is the discovery, description, and identification of any symmetries present in the data. We developed a deep learning methodology for the simultaneous discovery of multiple non-trivial continuous symmetries across an entire labeled dataset. The symmetry transformations and the corresponding generators are modeled with fully connected neural networks trained with a specially constructed loss function, ensuring the desired symmetry properties. The two new elements in this work are the use of a reduced-dimensionality latent space and the generalization to invariant transformations with respect to high-dimensional oracles. The method is demonstrated with several examples on the MNIST digit dataset, where the oracle is provided by the 10-dimensional vector of logits of a trained classifier. We find classes of symmetries that transform each image from the dataset into new synthetic images while conserving the values of the logits. We illustrate these transformations as lines of equal probability (“flows”) in the reduced latent space. These results show that symmetries in the data can be successfully searched for and identified as interpretable non-trivial transformations in the equivalent latent space.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1966

Wave propagation and turbulent media.

Book on electromagnetic wave propagation and turbulent media covering invariant imbedding method, turbulence generation, statistical methods of analysis, etc

INVARIANT IMBEDDING↗
NASA NTRS1998

Massively Parallel Solution of Poisson Equation on Coarse Grain MIMD Architectures

In this paper a new algorithm, designated as Fast Invariant Imbedding algorithm, for solution of Poisson equation on vector and massively parallel MIMD architectures is presented. This algorithm achieves the same optimal computational efficiency as other Fast Poisson solvers while offering a much better structure for vector and parallel implementation. Our implementation on the Intel Delta and Paragon shows that a speedup of over two orders of magnitude can be achieved even for moderate size problems.

parallel algorithms MIMD parallel architectures↗
NASA NTRS2004

Unstable Resonant Orbits near Earth and Their Applications in Planetary Missions

This paper explores the uses of planar, simple-periodic symmetrical families of orbits in mission designs in the Earth-Moon system. This classification is defined as the planar periodic orbits that pierce the x-axis in the rotating frame exactly twice per orbit where each piercing is orthogonal to the x-axis. A continuation method has been used to explore several families of this class of orbit in the Earth-Moon restricted three-body system. The invariant manifolds of the unstable orbits in each of these families are then produced and several mission designs are discussed that take advantage of these manifolds. Focus is given to mission designs that implement resonant orbits that periodically fly by the moon.

invariant manifolds↗
NASA NTRS2014

Limiting Superluminal Electron and Neutrino Velocities Using the 2010 Crab Nebula Flare and the IceCube PeV Neutrino Events

The observation of two PetaelectronVolt (PeV)-scale neutrino events reported by Ice Cube allows one to place constraints on Lorentz invariance violation (LIV) in the neutrino sector. After first arguing that at least one of the PetaelectronVolt IceCube events was of extragalactic origin, I derive an upper limit for the difference between putative superluminal neutrino and electron velocities of less than or equal to approximately 5.6 x 10(exp -19) in units where c = 1, confirming that the observed PetaelectronVolt neutrinos could have reached Earth from extragalactic sources. I further derive a new constraint on the superluminal electron velocity, obtained from the observation of synchrotron radiation from the Crab Nebula flare of September, 2010. The inference that the greater than 1 GigaelectronVolt gamma-rays from synchrotron emission in the flare were produced by electrons of energy up to approx. 5.1 PetaelectronVolt indicates the nonoccurrence of vacuum Cerenkov radiation by these electrons. This implies a new, strong constraint on superluminal electron velocities delta(sub e) less than or equal to approximately 5 x 10(exp -21). It immediately follows that one then obtains an upper limit on the superluminal neutrino velocity alone of delta(sub v) less than or equal to approximately 5.6 x 10(exp -19), many orders of magnitude better than the time-of-flight constraint from the SN1987A neutrino burst. However, if the electrons are subluminal the constraint on the absolute value of delta(sub e) less than or equal to approximately 8 x 10(exp -17), obtained from the Crab Nebula gamma-ray spectrum, places a weaker constraint on superluminal neutrino velocity of delta(sub v) less than or equal to approximately 8 x 10(exp -17).

Lorentz invariance↗
NASA NTRS2023

Development of the Ames Global Hyperspectral Synthetic Data Set: Surface Bidirectional Reflectance Distribution Function

This study introduces the Ames Global Hyperspectral Synthetic Data set (AGHSD), in particular the surface bidirectional reflectance distribution function (BRDF) product, to support the NASA Surface Biology and Geology (SBG) mission development. The data set is generated based on the corresponding multispectral BRDF products from NASA's MODIS satellite sensor. Based on theories of radiative transfer in vegetation canopies, we derive a simple but robust relationship that indicates that the hyperspectral surface BRDF can be accurately approximated as a weighted sum of the soil surface reflectance, the leaf single albedo, and the canopy scattering coefficient, where the weights or coefficients are spectrally invariant and thus readily estimated from the multispectral MODIS products. We validate the algorithm with simulations by a Monte Carlo Ray Tracing model and find the results highly consistent with the theoretic derivation. Using reflectance spectra of soil and vegetation derived from existing spectral libraries, we apply the algorithm to generate the AGHSD BRDF product at 1 km and 8-day resolutions for the year of 2019. The data set is biogeochemically and biogeophysically coherent and consistent, and serves the goal to support the SBG community in developing sciences and applications for the future global imaging spectroscopy mission.

Hyperspectral Remote Sensing↗
DOE OSTI2022

Latent Mechanisms of Polarization Switching from In Situ Electron Microscopy Observations

In situ scanning transmission electron microscopy enables observation of the domain dynamics in ferroelectric materials as a function of externally applied bias and temperature. The resultant data sets contain a wealth of information on polarization switching and phase transition mechanisms. However, identification of these mechanisms from observational data sets has remained a problem due to a large variety of possible configurations, many of which are degenerate. Here, an approach based on a combination of deep learning-based semantic segmentation, rotationally invariant variational autoencoder (VAE), and non-negative matrix factorization to enable learning of a latent space representation of the data with multiple real-space rotationally equivalent variants mapped to the same latent space descriptors is introduced. By varying the size of training sub-images in the VAE, the degree of complexity in the structural descriptors is tuned from simple domain wall detection to the identification of switching pathways. Importantly, this yields a powerful tool for the exploration of the dynamic data in mesoscopic electron, scanning probe, optical, and chemical imaging. Moreover, this work adds to the growing body of knowledge of incorporating physical constraints into the machine and deep-learning methods to improve learned descriptors of physical phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Enhanced Magnetization in CoFe 2 O 4 Through Hydrogen Doping

Magnetic spinel oxides have attracted extensive research interest due to their rich physics and wide range of applications. However, these materials invariably suffer suppressed magnetization, due to structural imperfections (e.g., disorder, anti-site defects, etc.). Herein, a dramatic enhanced magnetization is obtained with an increasement of 5 µ B /u.c in CoFe 2 O 4 (CFO) through ionic liquid gating induced hydrogen doping. Further, the intercalated hydrogen ions lead to both distinct lattice expansion of ≈0.7% and notable Fe valence state reduction through electron doping, in which ≈17% Fe 3+ is reduced into Fe 2+ . These facts collectively trigger a site-specific spin-flip on tetrahedrally coordinated Co 2+ sites that enhances the net ferrimagnetic moment nearly to its theoretical maximum for perfect CFO.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Disentangling Ferroelectric Wall Dynamics and Identification of Pinning Mechanisms via Deep Learning

Field-induced domain-wall dynamics in ferroelectric materials underpins multiple applications ranging from actuators to information technology devices and necessitates a quantitative description of the associated mechanisms including giant electromechanical couplings, controlled nonlinearities, or low coercive voltages. While the advances in dynamic piezoresponse force microscopy measurements over the last two decades have rendered visualization of polarization dynamics relatively straightforward, the associated insights into the local mechanisms have been elusive. This work explores the domain dynamics in model polycrystalline materials using a workflow combining deep-learning-based segmentation of the domain structures with nonlinear dimensionality reduction using multilayer rotationally invariant autoencoders (rVAE). The former allows unambiguous identification and classification of the ferroelectric and ferroelastic domain walls. Here, the rVAE discovers the latent representations of the domain wall geometries and their dynamics, consequently providing insight into the intrinsic mechanisms of polarization switching, that can further be compared to simple physical models. The rVAE disentangles the factors affecting the pinning efficiency of ferroelectric walls, offering insights into the correlation of ferroelastic wall distribution and ferroelectric wall pinning.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Hysteresis-Free Nanoparticle-Reinforced Hydrogels

The elastic storage and release of mechanical energy has been key to many developments throughout the history of mankind. Resilience, absent hysteresis, has been an elusive goal to achieve, particularly at large deformations. Using a low-crosslink-density polyacrylamide hydrogel at 96% water content having hyperbranched silica nanoparticles (HBSPs) as the major junction points, a hysteresis-free material is realized. The fatigue-free characteristic of these composite hydrogels is evidenced by the invariance of the stress–strain curves at strain ratios of 4, even after 5000 cycles. At a strain ratio of 7, only a 1.3% hysteresis is observed. A markedly increased strain-ratio-at-break of 11.5 is observed. Finally, the unique attributes of these resilient hydrogels are manifested in the high-fidelity detection of dynamic deformations under cyclic loading over a broad range of frequencies, difficult to achieve with other materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Asymmetry of the Ferroelectric Phase Transition in BaTiO 3

Symmetry changes during phase transformations fundamentally determine the behavior of thermodynamic systems, governing phenomena as diverse as water evaporation, fermion condensation, and epidemic spreading. Phase transitions are conventionally divided into two classes, and this classification is typically assumed to remain invariant upon reversing the transition. Here, an asymmetric phase transformation is uncovered in the ferroelectric–paraelectric transition of single-crystal BaTiO 3 , a model system for first-order transitions. Under slow temperature variation (≤0.1 °C min −1 ), thermodynamic, dielectric, and domain-structure measurements reveal that the ferroelectric-to-paraelectric transition exhibits latent heat, phase coexistence, and a discontinuous order parameter, while these signatures are absent upon cooling. Complementary phase-field simulations demonstrate similar behavior, attributing it to distinct elastic strain energy accumulation and release during heating and cooling. These findings reveal a first-order character upon heating but a second-order-like behavior upon cooling, challenging the conventional paradigm of symmetric phase-transition classification and suggesting new possibilities for ferroelectric-based energy storage.

Hershkovitz, Asaf [Technion-Israel Institute of Te↗
DOE OSTI2020

Steam‐Induced Coarsening of Single‐Unit‐Cell MFI Zeolite Nanosheets and Its Effect on External Surface Brønsted Acid Catalysis

Abstract Commonly used methods to assess crystallinity, micro‐/mesoporosity, Brønsted acid site density and distribution (in micro‐ vs. mesopores), and catalytic activity suggest nearly invariant structure and function for aluminosilicate zeolite MFI two‐dimensional nanosheets before and after superheated steam treatment. Yet, pronounced reaction rate decrease for benzyl alcohol alkylation with mesitylene, a reaction that cannot take place in the zeolite micropores, is observed. Transmission electron microscopy images reveal pronounced changes in nanosheet thickness, aspect ratio and roughness indicating that nanosheet coarsening and the associated changes in the external (mesoporous) surface structure are responsible for the changes in the external surface catalytic activity. Superheated steam treatment of hierarchical zeolites can be used to alter nanosheet morphology and regulate external surface catalytic activity while preserving micro‐ and mesoporosity, and micropore reaction rates.

Guefrachi, Yasmine↗