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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 883 records · Page 49

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NASA NTRS2011

Enhanced Spectral Anisotropies Near the Proton-Cyclotron Scale: Possible Two-Component Structure in Hall-FLR MHD Turbulence Simulations

Recent analysis of the magnetic correlation function of solar wind fluctuations at 1 AU suggests the existence of two-component structure near the proton-cyclotron scale. Here we use two-and-one-half dimensional and three-dimensional compressible MHD models to look for two-component structure adjacent the proton-cyclotron scale. Our MHD system incorporates both Hall and Finite Larmor Radius (FLR) terms. We find that strong spectral anisotropies appear adjacent the proton-cyclotron scales depending on selections of initial condition and plasma beta. These anisotropies are enhancements on top of related anisotropies that appear in standard MHD turbulence in the presence of a mean magnetic field and are suggestive of one turbulence component along the inertial scales and another component adjacent the dissipative scales. We compute the relative strengths of linear and nonlinear accelerations on the velocity and magnetic fields to gauge the relative influence of terms that drive the system with wave-like (linear) versus turbulent (nonlinear) dynamics.

Ghosh, Sanjoy↗

DOE OSTI2020

Nanoscale-femtosecond dielectric response of Mott insulators captured by two-color near-field ultrafast electron microscopy

Characterizing and controlling the out-of-equilibrium state of nanostructured Mott insulators hold great promises for emerging quantum technologies while providing an exciting playground for investigating fundamental physics of strongly-correlated systems. Here, we use two-color near-field ultrafast electron microscopy to photo-induce the insulator-to-metal transition in a single VO 2 nanowire and probe the ensuing electronic dynamics with combined nanometer-femtosecond resolution (10 –21 m • s). We take advantage of a femtosecond temporal gating of the electron pulse mediated by an infrared laser pulse, and exploit the sensitivity of inelastic electron-light scattering to changes in the material dielectric function. By spatially mapping the near-field dynamics of an individual nanowire of VO 2 , we observe that ultrafast photo-doping drives the system into a metallic state on a timescale of ~150 fs without yet perturbing the crystalline lattice. Due to the high versatility and sensitivity of the electron probe, our method would allow capturing the electronic dynamics of a wide range of nanoscale materials with ultimate spatiotemporal resolution.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2014

Direct Lorentz force compensation flowmeter for electrolytes

A simplified method of contactless Lorentz force (LF) measurements for flow meters on electrolytes is described and realized. Modification and comparative representation are discussed against recently well-developed methods. Based on the catapult effect, that current carrying conductor experiences a repulsive force in a magnetic field, we demonstrate force measurement method of LF velocimetry applications by commonly known “electromagnetic force” compensation principle. Measurement approach through zero point stability is considered to minimize mechanical influences and avoid gravimetric uncertainties. Here, the current carrying wires are static fixed in the vicinity of magnet system at zero point stable position, while occurring deflection of magnets by electrolyte flow is compensated by external applied current within wires. Measurements performed by developed servo-system which drives control loop by means of optical position sensor for simplified (i) single wire and (ii) coil-like extended compensation schemes. Guided by experiments on electrolyte flow, we demonstrate the applicability of adopted principle for conductivities ranging from 2 to 20 S/m. Further improvements are discussed in agreement with the parameters of demonstration setup, straightforward theory, and experimental results. We argue that this method is potentially suitable for: (a) applications with higher conductivity like molten metal (order of 10{sup 6 }S/m) assuming spatial configuration of setup and (b) for lower range of conductivity (below 1 S/m) while this is strongly subject to stiffness of system and noise mainly mechanical and thermal radiations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Exact solution of the topological symplectic Kondo problem

The Kondo effect is an archetypical phenomenon in the physics of strongly correlated electron systems. Recent attention has focused on the application of Kondo physics to quantum information science by exploiting overscreened Kondo impurities with residual anyon-like impurity entropy. While this physics was proposed in the fine-tuned multi-channel Kondo setup or in the Majorana-based topological Kondo effect, we here study the Kondo effect with symplectic symmetry Sp(2k) and present details about the implementation which importantly only involves conventional s-wave superconductivity coupled to an array of resonant levels and neither requires perfect channel symmetry nor Majorana fermions. Here we carefully discuss the role of perturbations and show that a global Zeeman drives the system to a 2-channel SU(k) fixed point. Exact results for the residual entropy, specific heat and magnetization are derived using the thermodynamic Bethe Ansatz for Sp(2k). This solution not only proves the existence of a quantum critical ground state with anyon-like Hilbert space dimension, but also a particularly weak non-Fermi liquid behavior at criticality. We interpret the weakness of non-analyticities as a manifestation of suppressed density of states at the impurity causing only a very weak connection of putative anyons and conduction electrons. Given this weak connection, the simplicity of the design and the stability of the effect, we conjecture that the symplectic Kondo effect may be particularly suitable for quantum information applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1981

The 15th Aerospace Mechanisms Symposium

The purpose of the symposium was to provide a forum for the interchange of information among those active in the field of mechanism technology. To that end, 27 papers were presented on aeronautics and space flight, with special emphasis on actuators and aerospace applications for pointing systems, latches, connectors, and other mechanisms for large space structures. The papers were authored by engineers from a broad aerospace spectrum including the U. S. aerospace industry, NASA, and several European participants. Technological areas covered include: aerospace propulsion; aerodynamic devices; crew safety; space vehicle control; spacecraft deployment, positioning, and pointing; deployable antennas/reflectors; and large space structures. Devices for payload deployment, payload retention, and crew extravehicular activities on the space shuttle orbiter are also described.

Actuators↗

DOE OSTI2019

Energy Research at Idaho National Laboratory

Energy-related research at Idaho National Laboratory (INL) takes many forms. In this presentation, Liam Boire will step through a specific, on-going research project at INL which seeks to understand transmission grid resilience, and the components which can be improved to increase the resilience of our electrical infrastructure. While utilities and researchers similarly strive to improve power grid reliability, the frequency of large power outages are increasing. Thus, the importance for developing efficient methodologies that enable utilities and researchers alike to identify the most effective areas for improvement within the electric grid is more critical than ever. The method developed during this project recognized that a variety of factors were important to consider when identifying areas for improvement in the electric grid. Physics-based simulators are able to calculate voltage stability, load draws and generation capacities, and enumerate the combinations of component failures which result in system-wide failures (blackout scenarios). Probabilistic Risk Assessment (PRA) is able to assign probabilities to these failure scenarios based on typical component data (or more specific data if a specific system is being analyzed), and thus prioritize the list of failure scenarios based on likelihood and the components based on importance. Finally, adaptive capacity models can simulate the candidate grid and evaluate real and reactive power generation versus demand over time, calculating the total adaptive capacity available in various regions of the grid. The less adaptive capacity a region has, the less “buffer” that region has from failure. Not only are the individual results of these analyses valuable in understanding grid resilience, but the results of these analyses can be cross-correlated for deeper insight. When a grid is analyzed with this approach, failure scenarios can be enumerated and ranked by likelihood, components can be ranked by likelihood to drive system-wide failure, regions can be evaluated for adaptive capacity, and sensitive regions can be identified by recognizing the locations of important components within sensitive regions. Following this detailed discussion, a brief overview of some of the other energy research and areas of interest for the lab will be presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1979

Measurements of reactive gaseous rocket injector admittances

The paper describes the results of an experimental study of the quantitative determination of the capabilities of the combustion processes associated with coaxial gaseous propellant rocket injectors to drive combustor pressure oscillations. The data, obtained by employing the modified impedance tube technique with compressed air as the oxidizer and acetylene gas as the fuel, describe the frequency dependence of the admittance of the combined injector-combustion process. The measured data are compared with the predictions of the Feiler and Heidmann analytical model utilizing different values for the characteristic combustion time tau sub b. The values of tau sub b which result in a best fit between the measured and predicted data are indicated for different equivalence ratios. It is shown that for the coaxial injector investigated in this study the tau sub b varies between 0.7 and 1.2 msec for equivalence ratios in the range of 0.57 to 1.31. In addition, the experimental data indicate that the tested injector system could drive combustion instabilities over a frequency range that is in qualitative agreement with the predictions of the Feiler and Heidmann model.

Janardan, B. A.↗

NASA NTRS2014

Cultivating an Emergent Earth Observation Analytics Ecosystem in the Cloud

A diverse set of data analytics systems for Earth Observations are sprouting up in the Earth Science community, with a wealth of processing algorithms and analysis methods. There is a similar wealth of data resources available via myriad data providers and clearinghouses, including large institutional systems like the Earth Observing System Data and Information System, Comprehensive Large Scale Array-data Stewardship System, and Federated Earth Observation Missions gateway. With Earth system science driving a need to work with more datasets together, and the community developing more analysis tools (some of them dataset-specific), how can we develop analysis workflows that incorporate far-flung datasets and leverage analysis resources from multiple organizations? Cloud computing points the way toward a solution in two different respects. Firstly, the access to and abstraction of virtually unlimited storage and computing power provides an environment that enables more straightforward means of pulling datasets and analysis resources together. Just as importantly, however, cloud computing serves as an example of an "ecosystem" of interoperating services, since the essence of cloud computing is the presentation of all resources as a service, from hardware to infrastructure to platform to software. This enables the combination of off-the-shelf, diverse services to construct entire systems that emerge out of an equally diverse community of architects and developers. This approach can be similarly applied to the data and analysis resources in the Earth Observation community. By exposing these resources via well understood services, and consuming resources in the same way, different organizations can construct bespoke analysis workflows and systems for their own purposes. The key leap the community needs to make is to develop analysis systems in components that interact with other components via services. The result would be a rich ecosystem of analytics components that can be combined to analyze datasets at scale and in conjunction with other datasets from other sources.

chaos↗

DOE OSTI2019

Synthesis and structure of Sr 14 Zn 1+ x As 11 and Eu 14 Zn 1+ x As 11 (x ≤ 0.5). New members of the family of pnictides isotypic with Ca 14 AlSb 11 , exhibiting a new type of structural disorder

Systematic investigation of the ternary systems A–Zn–As (A = Sr, Eu) led to the discovery of two new ternary phases, Sr 14 Zn 1+x As 11 and Eu 14 Zn 1+x As 11 (x ≤ 0.5). Both title compounds were structurally characterized by single-crystal X-ray diffraction. The basic structure of these new arsenides is akin to that of the numerous other pnictides adopting the tetragonal Ca 14 AlSb 11 structure type (space group I4 1 / acd (No. 142); Z = 8). The main difference is the presence of an interstitial Zn atom, located in a nearly trigonal-planar coordination environment of three As atoms. Four such fragments share common edges with the regular ZnAs 4 tetrahedron, to form an unusual new structural unit with the formula [Zn 1+x Sb 8] . The small uptake of additional zinc is needed to augment the overall valence electron count, thereby driving the system to an electronically charge-balanced state. Upon partial substitution of the nominally divalent Sr with a trivalent La, the equivalent of electron doping, the structure rids itself of the interstitial zinc, as demonstrated on the example of Sr 13.30(2) La 0.70 ZnAs 11 , which was also structurally characterized by single-crystal X-ray diffraction as part of this study. In conclusion, electronic structure calculations for the idealized composition Sr 14 ZnAs 11 confirm the speculated electron-deficient assignment, and suggest intrinsic semiconducting behavior for the one-electron richer Sr 14 Zn 1+x As 11 (x = 0.5) and Sr 13 LaZnAs 11 , respectively.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Hybrid Model Based Approaches for Systems Health Management and Prognostics

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision making. In principle, data driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for an effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Hybrid Modeling↗

NASA NTRSDate not supplied

Hybrid Approaches to Systems Health Management and Prognostics

Systems Health Management↗

NASA NTRS2022

Hybrid Model Based Approaches for Systems Health Management and Prognostics

This is a previously approved and published presentation. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Present achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision-making. In principle, data-driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data-driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety-critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Prognostics↗

DOE OSTI2025

Unitary Thermal Energy Management for Propulsion Range Augmentation (UTEMPRA) (CRADA Final Report)

NREL will work with Delphi to develop technology that integrates the thermal management of electric drive vehicle sub-systems into a unified thermal system that reduces auxiliary loads and increases vehicle range. The ultimate goal is to create a cost-effective system which improves climate control efficiency through heat pump operation and waste heat recovery, while maintaining occupant thermal comfort and meeting powertrain thermal requirements. The technology will also aim to reduce the number of independent cooling systems required in electric drive vehicles.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2019

Interlayer correlated fractional quantum Hall state in the ν = 4 / 5 bilayer system

We perform exact diagonalization studies for fractional quantum Hall states at filling factor 4/5 in a bilayer system, on a torus with various aspect ratios and angles. In this work we find that in the absence of tunneling, two weakly coupled 2/5 layers undergo a phase transition into an interlayer-correlated regime, which is also Abelian with the fivefold degeneracy on the torus. In the limit of zero layer separation, this phase becomes a singlet in the pseudospin variable describing the layer degree of freedom. By studying the Chern-number matrix, we show that the K matrix describing the interlayer-correlated regime requires a matrix dimension larger than two and this regime is in particular not described by a Halperin state. A detailed analysis of possible 4 × 4 K matrices having the requisite symmetries and quantum numbers shows that there is only one equivalence class of such matrices. A model wave function representing this universality class is constructed. The role of separate particle number conservation in both layers is discussed, and it is argued that this additional symmetry allows for the further distinction of two different symmetry-protected Abelian phases in the interlayer correlated regime. Interlayer tunneling breaks this symmetry and can drive the system into a single-layer regime when strong enough. A qualitative phase diagram in the tunneling-layer separation parameter space is proposed based on our numerical results.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Electron/hole selectivity in organic semiconductor contacts for solar energy conversion (Final Report)

Four major and accomplishments for the project "Electron/hole selectivity in organic semiconductor contacts for solar energy conversion.'' are reported. The first is a development of a model describing the contact-determined behavior of a solar cell. The most basic solar cell consists of an intrinsic (pure) semiconductor that acts as an absorber to which contacts are made that provide the asymmetry needed to create a driving force (voltage) for the directional flow of electrons (current), in other words, to convert sunlight into electrical energy. The asymmetry at the contacts comes from the different rate at which electrons and holes, the charge carriers generated by illumination, are collected. We developed a model that describes the ideal current-voltage, and hence energy converting properties, of an ideal photovoltaic that is entirely determined by the kinetics for these charge collection processes. Second, we measured how organic semiconductor interfacial layers impact contact electron and hole transfer rates at semiconductor interfaces and described how these concepts do or do not determine the open-circuit voltage of a solar cell. The work clearly controverts common general misconceptions about the action of contact interfacial layers, such as the idea that improved selectivity for one carrier over the other results from decreased recombination, and quantitatively demonstrates how specific interfacial layer materials act to improve the efficiency of a solar cell. Third, we measured the sub-band gap external quantum efficiency (EQE) of a series of organometal halide perovskite (“perovskite”) solar cells. These measurements quantified band-tailing and revealed defect states, which can cause recombination, that correlate with composition, performance, and hysteresis. Finally, we developed a semiconductor bipolar membrane that uses light to pump ions. This structure is unique among systems that drive ion gradients using light in that it is designed to pump salt rather than one sign of ion; it is a photochemical salt pump.

14 SOLAR ENERGY↗

DOE OSTI2014

Hydraulic Hybrid and Conventional Parcel Delivery Vehicles' Measured Laboratory Fuel Economy on Targeted Drive Cycles

This research project compares laboratory-measured fuel economy of a medium-duty diesel powered hydraulic hybrid vehicle drivetrain to both a conventional diesel drivetrain and a conventional gasoline drivetrain in a typical commercial parcel delivery application. Vehicles in this study included a model year 2012 Freightliner P100H hybrid compared to a 2012 conventional gasoline P100 and a 2012 conventional diesel parcel delivery van of similar specifications. Drive cycle analysis of 484 days of hybrid parcel delivery van commercial operation from multiple vehicles was used to select three standard laboratory drive cycles as well as to create a custom representative cycle. These four cycles encompass and bracket the range of real world in-use data observed in Baltimore United Parcel Service operations. The NY Composite cycle, the City Suburban Heavy Vehicle Cycle cycle, and the California Air Resources Board Heavy Heavy-Duty Diesel Truck (HHDDT) cycle as well as a custom Baltimore parcel delivery cycle were tested at the National Renewable Energy Laboratory's Renewable Fuels and Lubricants Laboratory. Fuel consumption was measured and analyzed for all three vehicles. Vehicle laboratory results are compared on the basis of fuel economy. The hydraulic hybrid parcel delivery van demonstrated 19%-52% better fuel economy than the conventional diesel parcel delivery van and 30%-56% better fuel economy than the conventional gasoline parcel delivery van on cycles other than the highway-oriented HHDDT cycle.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2018

Economy and Emissions Impacts from Solazyme Fuel in UPS Delivery Vehicles

To improve understanding of the potential fuel economy and emissions impacts from switching a fleet of vehicles from conventional petroleum diesel to synthetic renewable diesel, the National Renewable Energy Laboratory (NREL) conducted fuel economy and emissions analyses at NREL's Renewable Fuels and Lubricants (ReFUEL) Laboratory. Representative test cycles were developed based on real-world data from six package delivery vehicles and six class 8 day-cab tractors operated by UPS in the Dallas, Texas, area. A three-week in-field data collection period yielded 170 days of real-world vehicle operations data that NREL used to select representative standard drive cycles for testing. Fuel economy and emissions tests at the ReFUEL Laboratory showed that, in general, when switching from conventional diesel to renewable diesel observed changes in tailpipe carbon dioxide (CO2), fuel consumption, and fuel economy are primarily driven by changes in fuel properties such as the hydrogen-to-carbon ratio, density, and lower heating value (LHV). The vehicles tested with the renewable diesel showed a consistent 4.2% reduction in tailpipe CO2 emissions, but a 3.5%-4.8% reduction in fuel economy compared with local pump diesel. This is consistent with the 4.2% lower volumetric LHV of the sourced renewable diesel compared to the pump diesel. The UPS package car tested on renewable diesel also demonstrated a 4.1% oxides of nitrogen (NOx) reduction. NOx emissions from the UPS selective-catalyst-reduction-equipped tractor were an order of magnitude lower than the package car but showed relatively higher variability in results from cycle to cycle.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2014

Advances in long pulse operation at high radio frequency power in Tore Supra

The lower hybrid current drive (LHCD) system of Tore Supra has been upgraded for long pulse operation at higher power (7–8 MW). The two launchers have coupled on plasma 3.8 MW and 2.7 MW separately. This new power capability allows extending the operational domain of Tore Supra for long pulses at higher current and density. 38 long (20 s –155 s) discharges with very low loop voltage (V{sub L} = 30-60 mV) were performed with combined LHCD (5-5.7 MW) and ICRH (1–3 MW) powers, with up to 1 GJ of injected energy. Higher LHCD efficiency, with respect to the previous long discharges, is reported. MHD stability of these discharges is very sensitive to the LHCD power and parallel wave index, in particular in the preforming phase. For theses evanescent loop voltage plasmas, the ICRH power, in excess of 1 MW, is found to have a beneficial effect on the MHD stability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗