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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Universal Spreading of Conditional Mutual Information in Noisy Random Circuits

For this work, we study the evolution of conditional mutual information (CMI) in generic open quantum systems, focusing on one-dimensional random circuits with interspersed local noise. Unlike in noiseless circuits, where CMI spreads linearly while being bounded by the light cone, we find that noisy random circuits with an error rate 𝑝 exhibit superlinear propagation of CMI, which diverges far beyond the light cone at a critical circuit depth 𝑡 𝑐 ∝ 𝑝 −1 . We demonstrate that the underlying mechanism for such rapid spreading is the combined effect of local noise and a scrambling unitary, which selectively removes short-range correlations while preserving long-range correlations. To analytically capture the dynamics of CMI in noisy random circuits, we introduce a coarse-graining method, and we validate our theoretical results through numerical simulations. Furthermore, we identify a universal scaling law governing the spreading of CMI.

decoherence↗
DOE OSTI2022

Rheology and dynamics of a solvent segregation driven gel (SeedGel)

Bicontinuous structures promise applications in a broad range of research fields, such as energy storage, membrane science, and biomaterials. Kinetically arrested spinodal decomposition is found responsible for stabilizing such structures in different types of materials. A recently developed solvent segregation driven gel (SeedGel) is demonstrated to realize bicontinuous channels thermoreversibly with tunable domain sizes by trapping nanoparticles in a particle domain. As the mechanical properties of SeedGel are very important for its future applications, a model system is characterized by temperature-dependent rheology. The storage modulus shows excellent thermo-reproducibility and interesting temperature dependence with the maximum storage modulus observed at an intermediate temperature range (around 28 °C). SANS measurements are conducted at different temperatures to identify the macroscopic solvent phase separation during the gelation transition, and solvent exchange between solvent and particle domains that is responsible for this behavior. Further, the long-time dynamics of the gel is further studied by X-ray Photon Correlation Spectroscopy (XPCS). The results indicate that particles in the particle domain are in a glassy state and their long-time dynamics are strongly correlated with the temperature dependence of the storage modulus.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1987

Dynamic substorm injections - Similar magnetospheric phenomena at earth and Mercury

Correlations between energetic electrons, plasma electrons, and magnetic fields during the Mercury 1 energetic particle events are examined and comparisons are made with several well-documented substorm injections at the earth. The data reveal that the B and B-prime events possess the same characteristics as single-point observations of terrestrial dynamic injections. Several recently discovered correlations between the energetic electrons, plasma electrons, and magnetic fields at Mercury are discussed.

Christon, S. P.↗
NASA NTRS2009

Correlation of Smart Active Flap Rotor Loads

The ability to predict SMART active trailing edge flap rotor loads is explored in this study. Full-scale wind tunnel data recently acquired in the NASA Ames 40- by 80- Foot Wind Tunnel are compared with analytical results from CAMRAD II. For the 5-bladed rotor, two high-speed forward flight cases are considered, namely, a 0 deg flap deflection case and a 5P, 2 deg flap deflection case. Overall, the correlation is reasonable, with the following exceptions: the torsion moment frequency and the chordwise bending moment are under predicted. In general, the effect of the 5P, 2 deg flap motion is captured by the analysis, though there is over prediction in the neighborhood of the 105 deg and 120 deg azimuthal locations. Changes to the flexbeam torsion stiffness are also briefly considered in this study, as this stiffness will be updated in the future. Finally, the indication is that compressibility effects are important, and this suggests that computational fluid dynamics might improve the current correlation.

Kottapalli, Sesi↗
NASA NTRS2002

Prediction of Aerodynamic Coefficient using Genetic Algorithm Optimized Neural Network for Sparse Data

Wind tunnels use scale models to characterize aerodynamic coefficients, Wind tunnel testing can be slow and costly due to high personnel overhead and intensive power utilization. Although manual curve fitting can be done, it is highly efficient to use a neural network to define the complex relationship between variables. Numerical simulation of complex vehicles on the wide range of conditions required for flight simulation requires static and dynamic data. Static data at low Mach numbers and angles of attack may be obtained with simpler Euler codes. Static data of stalled vehicles where zones of flow separation are usually present at higher angles of attack require Navier-Stokes simulations which are costly due to the large processing time required to attain convergence. Preliminary dynamic data may be obtained with simpler methods based on correlations and vortex methods; however, accurate prediction of the dynamic coefficients requires complex and costly numerical simulations. A reliable and fast method of predicting complex aerodynamic coefficients for flight simulation I'S presented using a neural network. The training data for the neural network are derived from numerical simulations and wind-tunnel experiments. The aerodynamic coefficients are modeled as functions of the flow characteristics and the control surfaces of the vehicle. The basic coefficients of lift, drag and pitching moment are expressed as functions of angles of attack and Mach number. The modeled and training aerodynamic coefficients show good agreement. This method shows excellent potential for rapid development of aerodynamic models for flight simulation. Genetic Algorithms (GA) are used to optimize a previously built Artificial Neural Network (ANN) that reliably predicts aerodynamic coefficients. Results indicate that the GA provided an efficient method of optimizing the ANN model to predict aerodynamic coefficients. The reliability of the ANN using the GA includes prediction of aerodynamic coefficients to an accuracy of 110% . In our problem, we would like to get an optimized neural network architecture and minimum data set. This has been accomplished within 500 training cycles of a neural network. After removing training pairs (outliers), the GA has produced much better results. The neural network constructed is a feed forward neural network with a back propagation learning mechanism. The main goal has been to free the network design process from constraints of human biases, and to discover better forms of neural network architectures. The automation of the network architecture search by genetic algorithms seems to have been the best way to achieve this goal.

Rajkumar, T.↗
NASA NTRS1997

Measured Spacecraft Dynamic Effects on Atmospheric Science Instruments

On September 1991, NASA launched the Upper Atmosphere Research Satellite. In addition to its atmospheric science mission, spacecraft dynamic effects on science measurements were analyzed. The investigation included two in-flight experiments to determine how each on-board instrument, subsystem and environmental disturbance contributed to the spacecraft dynamic response and how these disturbances affected science measurements. Three case studies are presented which show the impact of spacecraft dynamic response on science measurements. In the first case, correlation of independent atmospheric meridional wind measurements taken by two instruments with the spacecraft dynamic response demonstrated that excessive vibration (exceeding instrument pointing requirements) resulted in wind measurement disagreement. In the second case, solar array disturbances produced a spacecraft response signature on radiometer measurements. The signature explicitly demonstrated that if an instrument has sufficient spatial and temporal resolution, spacecraft dynamic response could impact measurements. In the final case, correlation of an instrument's fine sun sensor data and CO2 measurements demonstrated the effect of temporal and spatial sampling resolution and active pointing control on science measurements. The sun sensor had a frequency modulated characteristic due to spacecraft vibration and the periodic scanning of another instrument which was not present on the CO2 measurements.

Woodard, Stanley E.↗
NASA NTRS1975

Wind modeling and lateral control for automatic landing

For the purposes of aircraft control system design and analysis, the wind can be characterized by a mean component which varies with height and by turbulent components which are described by the von Karman correlation model. The aircraft aero-dynamic forces and moments depend linearly on uniform and gradient gust components obtained by averaging over the aircraft's length and span. The correlations of the averaged components are then approximated by the outputs of linear shaping filters forced by white noise. The resulting model of the crosswind shear and turbulence effects is used in the design of a lateral control system for the automatic landing of a DC-8 aircraft.

Holley, W. E.↗
DOE OSTI2022

Specific Ion Effects in Lanthanide–Amphiphile Structures at the Air–Water Interface and Their Implications for Selective Separation

The use of surfactants to attract dissolved ions to water surfaces and interfaces is an essential step in both solvent-based and solvent-free separation processes. Here, we have studied the interactions of lanthanide ions in the aqueous subphase with monolayers of dihexadecyl phosphate at air–water interfaces. With heavier lanthanides (atomic number Z ≥ 65) in the subphase, the floating layer can be compressed to an area/molecule of about half the molecular cross section, indicating bilayer formation. X-ray fluorescence and reflectivity data support this conclusion. In the presence of lighter lanthanides (Z < 65), only monolayers are observed. Subphase-concentration-dependent studies using Er 3+ (heavier) and Nd 3+ (lighter) lanthanides show a stepwise progression, with ions attaching to the monolayer only when the solution concentration is >3 × 10 –7 M. Above ~10 –5 M, bilayers form but only in the presence of the heavier lanthanide. Grazing incidence X-ray diffraction shows evidence of lateral ion–ion correlations in the bilayer structure but not in monolayers. Explicit solvent all-atom molecular dynamics simulations confirm the elevated ion–ion correlation in the bilayer system. This bilayer structure isolates heavier lanthanides but not lighter lanthanides from an aqueous solution and is therefore a potential mechanism for the selective separation of heavier lanthanides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Electronic correlations in the semiconducting half-Heusler compound FeVSb

Electronic correlations are crucial to the low-energy physics of metallic systems with localized d and f states; however, their effect on band insulators and semiconductors is typically negligible. Here, we measure the electronic structure of the half-Heusler compound FeVSb, a band insulator with a filled shell configuration of 18 valence electrons per formula unit ( s 2 p 6 d 10 ). Additionally, angle-resolved photoemission spectroscopy reveals a mass renormalization of m * / m bare = 1.4 , where m * is the measured effective mass and m bare is the mass from density functional theory calculations with no added on-site Coulomb repulsion. Our measurements are in quantitative agreement with dynamical mean-field theory calculations, highlighting the many-body origin of the mass renormalization. This mass renormalization lies in dramatic contrast to other filled shell intermetallics, including the thermoelectric materials CoTiSb and NiTiSn, and has a similar origin to that in FeSi, where Hund's coupling induced fluctuations across the gap can explain a dynamical self-energy and correlations. Our work calls for a rethinking of the role of correlations and Hund's coupling in intermetallic band insulators.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2022

Effect of an Interplanetary Coronal Mass Ejection on Saturn’s Radio Emission

The Saturn Kilometric Radiation (SKR) was observed for the first time during the flyby of Saturn by the Voyager spacecraft in 1980. These radio emissions, in the range of a few kHz to 1 MHz, are emitted by electrons travelling around auroral magnetic field lines. Their study is useful to understand the variability of a magnetosphere and its coupling with the solar wind. Previous studies have shown a strong correlation between the solar wind dynamic pressure and the SKR intensity. However, up to now, the effect of an Interplanetary Coronal Mass Ejection (ICME) has never been examined in detail, due to the lack of SKR observations at the time when an ICME can be tracked and its different parts be clearly identified. In this study, we take advantage of a large ICME that reached Saturn mid-November 2014 (Witasse et al., J. Geophys. Res. Space Physics, 2017, 122, 7865–7890). At that time, the Cassini spacecraft was fortunately travelling within the solar wind for a few days, and provided a very accurate timing of the ICME structure. A survey of the Cassini data for the same period indicated a significant increase in the SKR emissions, showing a good correlation after the passage of the ICME shock with a delay of ∼13 h and after the magnetic cloud passage with a delay of 25–42 h.

B. Cecconi↗
DOE OSTI2020

The carboxylation status of osteocalcin has important consequences for its structure and dynamics

The carboxylation status of Osteocalcin (Ocn) not only influences formation and structure in bones but also has important endocrine functions affecting energy metabolism and expenditure. In this study, the role of γ-carboxylation of the glutamate residues in the structure-dynamics-function relationship in Ocn is investigated. Three forms of Ocn, differentially carboxylated at the Glu-17, 21 and 24 residues, along with a mutated form of Ocn carrying Glu/Ala mutations, are modeled and simulated using molecular dynamics (MD) simulation in the presence of calcium ions. Characterization of the global conformational dynamics of Ocn, described in terms of the orientational variations within its 3-helical domain, highlights large structural variations in the non-carboxylated osteocalcin (nOcn). The bi-carboxylated Ocn (bOcn) and tri-carboxylated (tOcn) species, in contrast, display relatively rigid tertiary structures, with the dynamics of most regions strongly correlated. Radial distribution functions calculated for both bOcn and tOcn show long-range ordering of the calcium ion distribution around the carboxylated glutamate (γGlu) residues, likely playing an important role in promoting stability of these Ocns. Additionally, the same calcium ions are observed to coordinate with neighboring γGlu, better shielding their negative charges and in turn stabilizing these systems more than do the singly coordinating calcium ions observed in the case of nOcn. bOcn is also found to exhibit a more helical C-terminal structure, that has been shown to activate its cellular receptor GPRC6A, highlighting the allosteric role of Ocn carboxylation in modulating the stability and binding potential of the active C-terminal. Furthermore, the carboxylation status of Ocn as well and its calcium coordination appear to have a direct influence on Ocn structure and dynamics, possibly leading to the known differences in Ocn biological function.

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

Assessment of software methods for estimating protein-protein relative binding affinities

A growing number of computational tools have been developed to accurately and rapidly predict the impact of amino acid mutations on protein-protein relative binding affinities. Such tools have many applications, for example, designing new drugs and studying evolutionary mechanisms. In the search for accuracy, many of these methods employ expensive yet rigorous molecular dynamics simulations. By contrast, non-rigorous methods use less exhaustive statistical mechanics, allowing for more efficient calculations. However, it is unclear if such methods retain enough accuracy to replace rigorous methods in binding affinity calculations. This trade-off between accuracy and computational expense makes it difficult to determine the best method for a particular system or study. Here, eight non-rigorous computational methods were assessed using eight antibody-antigen and eight non-antibody-antigen complexes for their ability to accurately predict relative binding affinities (ΔΔG) for 654 single mutations. In addition to assessing accuracy, we analyzed the CPU cost and performance for each method using a variety of physico-chemical structural features. This allowed us to posit scenarios in which each method may be best utilized. Most methods performed worse when applied to antibody-antigen complexes compared to non-antibody-antigen complexes. Rosetta-based JayZ and EasyE methods classified mutations as destabilizing (ΔΔG < -0.5 kcal/mol) with high (83–98%) accuracy and a relatively low computational cost for non-antibody-antigen complexes. Some of the most accurate results for antibody-antigen systems came from combining molecular dynamics with FoldX with a correlation coefficient (r) of 0.46, but this was also the most computationally expensive method. Overall, our results suggest these methods can be used to quickly and accurately predict stabilizing versus destabilizing mutations but are less accurate at predicting actual binding affinities. This study highlights the need for continued development of reliable, accessible, and reproducible methods for predicting binding affinities in antibody-antigen proteins and provides a recipe for using current methods.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2014

Deducing Electronic Unit Internal Response During a Vibration Test Using a Lumped Parameter Modeling Approach

During random vibration testing of electronic boxes there is often a desire to know the dynamic response of certain internal printed wiring boards (PWBs) for the purpose of monitoring the response of sensitive hardware or for post-test forensic analysis in support of anomaly investigation. Due to restrictions on internally mounted accelerometers for most flight hardware there is usually no means to empirically observe the internal dynamics of the unit, so one must resort to crude and highly uncertain approximations. One common practice is to apply Miles Equation, which does not account for the coupled response of the board in the chassis, resulting in significant over- or under-prediction. This paper explores the application of simple multiple-degree-of-freedom lumped parameter modeling to predict the coupled random vibration response of the PWBs in their fundamental modes of vibration. A simple tool using this approach could be used during or following a random vibration test to interpret vibration test data from a single external chassis measurement to deduce internal board dynamics by means of a rapid correlation analysis. Such a tool might also be useful in early design stages as a supplemental analysis to a more detailed finite element analysis to quickly prototype and analyze the dynamics of various design iterations. After developing the theoretical basis, a lumped parameter modeling approach is applied to an electronic unit for which both external and internal test vibration response measurements are available for direct comparison. Reasonable correlation of the results demonstrates the potential viability of such an approach. Further development of the preliminary approach presented in this paper will involve correlation with detailed finite element models and additional relevant test data.

random vibration response↗
DOE OSTI2021

Performing In Situ Closed-Cell Gas Reactions in the Transmission Electron Microscope

Gas reactions studied by in situ electron microscopy can be used to capture the real-time morphological and microchemical transformations of materials at length scales down to the atomic level. In situ closed-cell gas reaction (CCGR) studies performed using (scanning) transmission electron microscopy (STEM) can separate and identify localized dynamic reactions, which are extremely challenging to capture using other characterization techniques. For these experiments, we used a CCGR holder that utilizes microelectromechanical systems (MEMS)-based heating microchips (hereafter referred to as "E-chips"). The experimental protocol described here details the method for performing in situ gas reactions in dry and wet gases in an aberration-corrected STEM. This method finds relevance in many different materials systems, such as catalysis and high-temperature oxidation of structural materials at atmospheric pressure and in the presence of various gases with or without water vapor. Here, several sample preparation methods are described for various material form factors. During the reaction, mass spectra obtained with a residual gas analyzer (RGA) system with and without water vapor further validates gas exposure conditions during reactions. Integrating an RGA with an in situ CCGR-STEM system can, therefore, provide critical insight to correlate gas composition with the dynamic surface evolution of materials during reactions. In situ/operando studies using this approach allow for detailed investigation of the fundamental reaction mechanisms and kinetics that occur at specific environmental conditions (time, temperature, gas, pressure), in real-time, and at high spatial resolution.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

From Bulk to Interface: Solvent Exchange Dynamics and Their Role in Ion Transport and the Interfacial Model of Rechargeable Magnesium Batteries

Multivalent battery chemistries have been explored in response to the increasing demand for high-energy rechargeable batteries utilizing sustainable resources. Solvation structures of working cations have been recognized as a key component in the design of electrolytes; however, most structure–property correlations of metal ions in organic electrolytes usually build upon favorable static solvation structures, often overlooking solvent exchange dynamics. We here report the ion solvation structures and solvent exchange rates of magnesium electrolytes in various solvents by using multimodal nuclear magnetic resonance (NMR) analysis and molecular dynamics/density functional theory (MD/DFT) calculations. These magnesium solvation structures and solvent exchange dynamics are correlated to the combined effects of several physicochemical properties of the solvents. Moreover, Mg 2+ transport and interfacial charge transfer efficiency are found to be closely correlated to the solvent exchange rate in the binary electrolytes where the solvent exchange is tunable by the fraction of diluent solvents. Our primary findings are (1) most battery-related solvents undergo ultraslow solvent exchange coordinating to Mg 2+ (with time scales ranging from 0.5 μs to 5 ms), (2) the cation transport mechanism is a mixture of vehicular and structural diffusion even at the ultraslow exchange limit (with faster solvent exchange leading to faster cation transport), and (3) an interfacial model wherein organic-rich regions facilitate desolvation and inorganic regions promote Mg 2+ transport is consistent with our NMR, electrochemistry, and cryogenic X-ray photoelectron spectroscopy (cryo-XPS) results. In conclusion, this observed ultraslow solvent exchange and its importance for ion transport and interfacial properties necessitate the judicious selection of solvents and informed design of electrolyte blends for multivalent electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2021

Electron correlation effects on exchange interactions and spin excitations in 2D van der Waals materials

Despite serious effort, the nature of the magnetic interactions and the role of electron-correlation effects in magnetic two-dimensional (2D) van der Waals materials remains elusive. Using CrI 3 as a model system, we show that the calculated electronic structure including nonlocal electron correlations yields spin excitations consistent with inelastic neutron-scattering measurements. Remarkably, this approach identifies an unreported correlation-enhanced interlayer super-superexchange, which rotates the magnon Dirac lines off, and introduces a gap along the high-symmetry Γ-K-M path. This discovery provides a different perspective on the gap-opening mechanism observed in CrI 3 , which was previously associated with spin–orbit coupling through the Dzyaloshinskii–Moriya interaction or Kitaev interaction. Our observation elucidates the critical role of electron correlations on the spin ordering and spin dynamics in magnetic van der Waals materials and demonstrates the necessity of explicit treatment of electron correlations in the broad family of 2D magnetic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Determining the diffusivity for light quarks from experiment

Charge balance functions reflect the evolution of charged pair correlations throughout the stages of pair production, dynamical diffusion, and hadronization in heavy-ion collisions. In this work, microscopic modeling of these correlations in the full collision volume shows that the balance functions are sensitive to the diffusivity of light quarks when studied as functions of relative azimuthal angle. By restricting our analysis to K + K – and $p\bar{p}$ pairs, we find that the diffusivity of light quarks, a fundamental property not currently well understood, can be constrained by experimental measurement.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗