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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

The effect of variable fuel staging transients on self-excited instabilities in a multiple-nozzle combustor

Combustion instability in gas turbine engines is often mitigated using fuel staging. Fuel staging, sometimes referred to as fuel splitting, is a strategy by which fuel is unevenly distributed between different nozzles of a multiple-nozzle combustor. These fuel splits are conducted in a transient manner in real engines, and the effects of these transients on instability are not well characterized. This work fills this gap by systematically studying the effects of transient fuel staging on self-excited combustion instability by varying the amount of staging fuel (staging amplitude), timescale in which the fuel is added (transient duration), and whether staging fuel is added or subtracted (transient direction). In this work, three staging amplitudes, five transient durations, and both transient directions are considered. The transient timescales are broadly divided into “short” duration transients, which have fuel delivery timescales shorter than the characteristic instability decay or onset timescales, and “long” duration transients, which have fuel delivery timescales longer than the characteristic instability decay or onset timescales. For short duration transients, we find the instability decay timescale depends on staging amplitude but does not depend on transient duration. For long duration transients, we find the instability decay timescale does not strongly depend on staging amplitude. The instability onset timescale is found to be longer and more variable between runs than the instability decay timescale for a given fuel delivery timescale. The onset timescale is also longer in duration and more variable than the decay timescale at a given fuel delivery timescale, implying that the instability rise process is overall more variable and slower than the instability decay process. Analysis of combustor damping rates show a strong dependence of damping rate on staging amplitude but no strong dependence on transient duration or direction. Instantaneous phase difference images between p' and are used to differentiate regions in the combustor that have constructive versus destructive interference between heat release rate oscillations and pressure fluctuations. Furthermore, the phase images show that p' and q . ' become in-phase early in the transient for the onset transients.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2018

Turbulent heating due to magnetic reconnection

Dissipation of plasma turbulent energy is a phenomenon having significant implications for the heating of the solar corona and solar wind. While processes involving linear wave damping, stochastic heating, and reconnection have been postulated as contributors to heating mechanisms, the relative role that they play is not currently understood. In this manuscript, we establish a theoretical framework for applying reconnection heating predictions to turbulent systems. Kinetic particle-in-cell (PIC) simulations are used to study heating due to reconnection, and these results are then adapted to a turbulent medium. First, the factors controlling the heating of plasmas in reconnection exhausts are examined using laminar reconnection simulations; predictions for heating are determined which require only the plasma conditions just upstream of the reconnection diffusion region as input. The laminar predictions are then applied to PIC simulations of turbulence. Key assumptions are: (1) the plasma conditions just upstream of the diffusion region are consistent with Kolmogorov scaling of turbulent fluctuations at the ion inertial scale and (2) the statistics of the numbers of reconnecting x-lines do not vary significantly between the various turbulent simulations. We find that the reconnection theory predicts quite well the scaling of the ratio of ion to electron heating, in which the statistics of the turbulent reconnection sites are expected to roughly cancel. Separate ion and electron heating rates scale differently from the theory, however. This suggests that the statistics of the turbulent reconnection (e.g., number of x-lines, percentage of x-lines reconnecting) is playing an important role in determining the ion and electron heating.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

DIRECT INTEGRATION OF THE COLLISIONLESS BOLTZMANN EQUATION IN SIX-DIMENSIONAL PHASE SPACE: SELF-GRAVITATING SYSTEMS

We present a scheme for numerical simulations of collisionless self-gravitating systems which directly integrates the Vlasov-Poisson equations in six-dimensional phase space. Using the results from a suite of large-scale numerical simulations, we demonstrate that the present scheme can simulate collisionless self-gravitating systems properly. The integration scheme is based on the positive flux conservation method recently developed in plasma physics. We test the accuracy of our code by performing several test calculations, including the stability of King spheres, the gravitational instability, and the Landau damping. We show that the mass and the energy are accurately conserved for all the test cases we study. The results are in good agreement with linear theory predictions and/or analytic solutions. The distribution function keeps the property of positivity and remains non-oscillatory. The largest simulations are run on 64{sup 6} grids. The computation speed scales well with the number of processors, and thus our code performs efficiently on massively parallel supercomputers.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

The ASAS-SN catalogue of variable stars – IV. Periodic variables in the APOGEE survey

ABSTRACT We explore the synergy between photometric and spectroscopic surveys by searching for periodic variable stars among the targets observed by the Apache Point Observatory Galactic Evolution Experiment (APOGEE) using photometry from the All-Sky Automated Survey for Supernovae (ASAS-SN). We identified 1924 periodic variables among more than $258\, 000$ APOGEE targets; 465 are new discoveries. We homogeneously classified 430 eclipsing and ellipsoidal binaries, 139 classical pulsators (Cepheids, RR Lyrae, and δ Scuti), 719 long-period variables (pulsating red giants), and 636 rotational variables. The search was performed using both visual inspection and machine learning techniques. The light curves were also modelled with the damped random walk stochastic process. We find that the median [Fe/H] of variable objects is lower by 0.3 dex than that of the overall APOGEE sample. Eclipsing binaries and ellipsoidal variables are shifted to a lower median [Fe/H] by 0.2 dex. Eclipsing binaries and rotational variables exhibit significantly broader spectral lines than the rest of the sample. We make ASAS-SN light curves for all the APOGEE stars publicly available and provide parameters for the variable objects.

Pawlak, Michał↗
DOE OSTI2011

Decoherence and the nature of system-environment correlations

We investigate system-environment correlations based on the exact dynamics of a qubit and its environment in the framework of pure decoherence (phase damping). We focus on the relation of decoherence and the buildup of system-reservoir entanglement for an arbitrary (possibly mixed) initial qubit state. In the commonly employed regime where the qubit dynamics can be described by a Markov master equation of the Lindblad type, we find that for almost all qubit initial states inside the Bloch sphere, decoherence is complete while the total state is still separable--no entanglement is involved. In general, both ''separable'' and ''entangling'' decoherence occurs, depending on the temperature and initial qubit state. Moreover, we find situations where classical and quantum correlations periodically alternate as a function of time in the regime of low temperatures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Synthesis of monodisperse CeO 2 -ZrO 2 particles exhibiting cyclic superelasticity over hundreds of cycles

Nano- and microscale CeO 2 –ZrO 2 (CZ) shape memory ceramics are promising materials for smart micro-electro-mechanical systems (MEMS), sensing, actuation and energy damping applications, but the processing science for scalable production of such small volume ceramics has not yet been established. Herein, we report a modified sol-gel method to synthesize highly monodisperse spherical CZ particles with diameters in the range of ~0.8-3.0 μm. Synchrotron X-ray micro-diffraction (μSXRD) confirmed that most of the particles are single crystal after annealing at 1450°C. Having a monocrystalline structure and a small specimen length scale, the particles exhibit significantly enhanced shape memory and superelasticity properties with up to ~4.7% compression being completely recoverable. Highly reproducible superelasticity through over five hundred strain cycles, with dissipated energy up to ~40 MJ/m 3 per cycle, is achieved in the CZ particles containing 16 mol% ceria. This cycling capability is enhanced by ten times compared with our first demonstration using micropillars (only 50 cycles in Lai et al, Science, 2013, 341, 1505). Furthermore, the effects of cycling and testing temperature (in 25°C-400°C) on superelasticity have been investigated.

36 MATERIALS SCIENCE↗
NASA NTRS1982

A high speed implementation of the random decrement algorithm

The algorithm is useful for measuring net system damping levels in stochastic processes and for the development of equivalent linearized system response models. The algorithm works by summing together all subrecords which occur after predefined threshold level is crossed. The random decrement signature is normally developed by scanning stored data and adding subrecords together. The high speed implementation of the random decrement algorithm exploits the digital character of sampled data and uses fixed record lengths of 2(n) samples to greatly speed up the process. The contributions to the random decrement signature of each data point was calculated only once and in the same sequence as the data were taken. A hardware implementation of the algorithm using random logic is diagrammed and the process is shown to be limited only by the record size and the threshold crossing frequency of the sampled data. With a hardware cycle time of 200 ns and 1024 point signature, a threshold crossing frequency of 5000 Hertz can be processed and a stably averaged signature presented in real time.

Kiraly, L. J.↗
NASA NTRS1983

A high-speed implementation of the random decrement algorithm

The algorithm is useful for measuring net system damping levels in stochastic processes and for the development of equivalent linearized system response models. The algorithm works by summing together all subrecords which occur after predefined threshold level is crossed. The random decrement signature is normally developed by scanning stored data and adding subrecords together. The high speed implementation of the random decrement algorithm exploits the digital character of sampled data and uses fixed record lengths of 2(n) samples to greatly speed up the process. The contributions to the random decrement signature of each data point was calculated only once and in the same sequence as the data were taken. A hardware implementation of the algorithm using random logic is diagrammed and the process is shown to be limited only by the record size and the threshold crossing frequency of the sampled data. With a hardware cycle time of 200 ns and 1024 point signature, a threshold crossing frequency of 5000 Hertz can be processed and a stably averaged signature presented in real time.

Kiraly, L. J.↗
NASA NTRSDate not supplied

Attitude Reconstruction of Free-Flight CFD Generated Trajectories Using Non-Linear Pitch Damping Coefficient Curves

Attitude history reconstruction of Free-flight CFD generated trajectories with non-linear pitch damping coefficient curves is investigated. Free-flight CFD simulations of the capsule shape used for the Genesis sample return mission and the upcoming Dragonfly mission to Titan are conducted for 1-, 2-, and 3-degree-of-freedom cases. Two different data reduction methodologies are employed to derive a pitch damping curve as a function of instantaneous angle of attack. These curves are then used to reconstruct the attitude history of the body which is compared to the raw simulation results. While both data reduction methods produce pitch damping curves that can generally reconstruct the motion seen in the Free-flight simulations, it is found that optimization of the pitch damping curve using an inverse estimation process yields superior and more generalizable results. Further refinement of this technique could allow pitch damping curves derived using CFD to serve as a capability complementary to existing techniques for dynamic stability characterization.

entry↗
NASA NTRSDate not supplied

Attitude Reconstruction of Free-Flight CFD Generated Trajectories Using Non-Linear Pitch Damping Coefficient Curves

Attitude history reconstruction of Free-flight CFD generated trajectories with non-linear pitch damping coefficient curves is investigated. Free-flight CFD simulations of the capsule shape used for the Genesis sample return mission and the upcoming Dragonfly mission to Titan are conducted for 1-, 2-, and 3-degree-of-freedom cases. Two different data reduction methodologies are employed to derive a pitch damping curve as a function of instantaneous angle of attack. These curves are then used to reconstruct the attitude history of the body which is compared to the raw simulation results. While both data reduction methods produce pitch damping curves that can generally reconstruct the motion seen in the Free-flight simulations, it is found that optimization of the pitch damping curve using an inverse estimation process yields superior and more generalizable results. Further refinement of this technique could allow pitch damping curves derived using CFD to serve as a capability complementary to existing techniques for dynamic stability characterization.

entry↗
DOE OSTI2019

Enhanced piezoresistive sensing of fiber-reinforced composites via embedded nanoparticles

Carbon fiber composites offer outstanding structural performance with high specific strength and are experiencing significant commercial adoption as the fiber price continues to decrease. Composite research efforts now need to focus on creating multifunctional composites, which can offer sensing capabilities in addition to structural attributes. This work focuses on creating multifunctional carbon fiber composites with structural health monitoring capabilities through the integration of piezoresistive nanoparticles on the surface of carbon fiber. Prior research introduced the development of coating silicon carbide nanoparticles on the surface of carbon fiber in a continuous feed-through process to achieve increased SHM sensitivity with enhanced interlaminar strength and tunable mechanical damping properties. One benefit of that coating process is the compatibility with various nanomaterials. This research capitalizes on that benefit by coating different nanoparticles, such as titanium dioxide, on carbon fiber to further enhance the sensing capabilities. A modification to the prior coating process is made in this research to enable significantly higher nanoparticle loading to be achieved. The resulting composites more accurately measure an applied force by responding with a more profound electrical resistance change. This research lays the foundation for efficiently integrating nanoparticles onto fibers leading to homogenously dispersed nanoparticles throughout a fiber reinforced composite for multifunctional performance.

Bowland, Christopher↗
DOE OSTI2022

Superconducting dome in ferroelectric-type materials from soft mode instability

Here we present a minimal theory of superconductivity enhancement in ferroelectric-type materials. Simple expressions for the optical mode responsible for the soft mode transition are assumed. A key role is played by the anharmonic phonon damping which is modulated by an external control parameter (electron doping or mechanical strain) causing the appearance of the soft mode. It is shown that the enhancement in the superconducting critical temperature T c upon approaching the ferroelectric transition from either side is due to the Stokes electron-phonon scattering processes promoted by strong phonon damping effects.

36 MATERIALS SCIENCE↗
NASA NTRS2000

Novel Vibration Damping of Ceramic Matrix Composite Turbine Blades Developed for RLV Applications

The Reusable Launch Vehicle (RLV) represents the next generation of space transportation for the U.S. space program. The goal for this vehicle is to lower launch costs by an order of magnitude from $10,000/lb to $1,000/lb. Such a large cost reduction will require a highly efficient operation, which naturally will require highly efficient engines. The RS-2200 Linear Aerospike Engine is being considered as the main powerplant for the RLV. Strong, lightweight, temperature-resistant ceramic matrix composite (CMC) materials such as C/SiC are critical to the development of the RS-2200. Preliminary engine designs subject turbopump components to extremely high frequency dynamic excitation, and ceramic matrix composite materials are typically lightly damped, making them vulnerable to high-cycle fatigue. The combination of low damping and high-frequency excitation creates the need for enhanced damping. Thus, the goal of this project has been to develop well-damped C/SiC turbine components for use in the RLV. Foster-Miller and Boeing Rocketdyne have been using an innovative, low-cost process to develop light, strong, highly damped turbopump components for the RS-2200 under NASA s Small Business Innovation Research (SBIR) program. The NASA Glenn Research Center at Lewis Field is managing this work. The process combines three-dimensionally braided fiber reinforcement with a pre-ceramic polymer. The three-dimensional reinforcement significantly improves the structure over conventional two-dimensional laminates, including high through-the-thickness strength and stiffness. Phase I of the project successfully applied the Foster-Miller pre-ceramic polymer infiltration and pyrolysis (PIP) process to the manufacture of dynamic specimens representative of engine components. An important aspect of the program has been the development of the manufacturing process. Results show that the three-dimensionally braided carbon-fiber reinforcement provides good processability and good mechanical stiffness and strength in comparison to materials produced with competing processes as shown in the graphs.

Min, James B.↗
DOE OSTI2026

An Atom-Precise Approach to Damp First-Order Phase Transitions and Its Implications for Neuromorphic Signal Processing

Neuromorphic computing inspired by mammalian intelligence aims to emulate the nonlinear dynamics of biological neurons and synapses to achieve fast, low-energy, and highly efficient information processing. Brain-inspired computing relies on the design and discovery of materials exhibiting nonlinear current–voltage profiles, frequently underpinned by electronic state transitions, to achieve spiking neurons and dynamically tunable synapses. A signature challenge in the design of artificial neurons is controlling the steepness of first-order transitions in active elements, as abrupt transitions are at risk of driving unstable voltage and temperature oscillations, which result in catastrophic device failure. A critical knowledge gap is the lack of structure–function correlations mapping the composition and atomistic structure of crystalline solids to nonlinear dynamical response characteristics. Here, we address the key question of how modification of atomistic structure correlates with alteration of neuron-like functionality. Constructing oscillator circuits from millimeter-scale single crystals enables high-resolution atomic structure solutions, which we use to demonstrate that the selective positioning of Pb cations modifies charge ordering along a one-dimensional CuxV2O5 framework even at low insertion stoichiometries, thereby providing an atom-precise design parameter for damping first-order transitions. We use temperature-variant X-ray diffraction and X-ray spectroscopy to elucidate the suppression of Cu-ion shuttling based on the precise positioning of Pb ions in seven-coordinated tunnel interstitial sites as the mechanistic basis for transition broadening, thus bridging a critical gap between statistical mechanics and quantum chemical descriptions of phase transitions. Such mechanistic understanding thus paves the way to site-selective modification strategies for modulating the sharpness of first-order transitions, with an exemplary demonstration here in tuning neuronal signal processing.

Crystal structure↗
NASA NTRS1995

Alpha particle heating at comet-solar wind interaction regions

The satellite observations at comet Halley have shown strong heating of solar wind alpha particles over an extended region dominated by high-intensity, low-frequency turbulence. These waves are excited by the water group pickup ions and can energize the solar wind plasma by different heating processes. The alpha particle heating by the Landau damping of kinetic Alfven waves and the transit time damping of low-frequency hydromagnetic waves in this region of high plasma beta are studied in this paper. The Alfven wave heating was shown to be the dominant mechanism for the observed proton heating, but it is found to be insufficient to account for the observed alpha particle heating. The transit time damping due to the interaction of the ions with the electric fields associated with the magnetic field compressions of magnetohydrodynamic waves is found to heat the alpha particles preferentially over the protons. Comparison of the calculated heating times for the transit time damping with the observations from comet Halley shows good agreement. These processes contribute to the thermalization of the solar wind by the conversion of its directed energy into the thermal energy in the transition region at comet-solar wind interaction.

Sharma, A. S.↗
NASA NTRS2024

Exploring Standing and Reflected Slow-mode Waves in Flaring Coronal Loops: A Parametric Study Using 2.5D MHD Modeling

Abstract Recent observations of reflected propagating and standing slow-mode waves in hot flaring coronal loops have spurred our investigation into their underlying excitation and damping mechanisms. To understand these processes, we conduct 2.5D magnetohydrodynamic (MHD) simulations using an arcade active region model that includes a hot and dense loop. Our simulations allow for in-depth parametric investigations complementing and expanding our previous 3D MHD modeling results. We excite these waves using a large-amplitude, flow pulse applied at one footpoint of the loop in two distinct models as motivated by observations from the Solar Dynamics Observatory/Atmospheric Imaging Assembly (SDO/AIA). The first model (Model 1) incorporates classical compressive viscosity coefficient, while the second model (Model 2) adopts a 10-times enhanced viscosity coefficient. We obtain the following major results: (1) Our 2.5D MHD simulations reinforce previous conclusions derived from 1D and 3D MHD models that significantly enhanced viscosity is crucial for the rapid excitation of standing slow waves with damping times consistent with observations by Wang et al. (2015). (2)We uncover that nonlinearity in Model 1 delays the conversion of a reflected propagating wave into a standing wave. In contrast, Model 2 exhibits a much weak influence of nonlinearity on the excitation time of standing waves, thanks to the suppression of these effects by enhanced viscosity. (3) Our results reveal that the transverse temperature structure holds more influence on wave behavior than the density structure. In Model 1, increased loop temperature contrast significantly enhances wave trapping within the structure, mitigating the impact of temperature-dependent viscous damping. Conversely, in Model 2, the impact of temperature structure on wave behavior weakens in comparison to the effect of viscosity. (4) Model 1 displays evident nonlinear coupling to the fast and kink magnetoacoustic waves and pronounced wave leakage into the corona. Model 2 exhibits significantly weaker effects in this regard. Analyzing three observed wave events by SDO/AIA aligns with Model 2 predictions, providing further support for the substantial viscosity increase. Our 2.5D study unravels the complex interplay of wave-flow phenomena and nonlinear processes in coronal loops, extending our previous 1D modeling results to incorporate more realistic loop geometry. This provides insights into scenarios where 3D effects may be neglected, thereby enhancing our understanding of the intricate dynamics of the solar corona.

Tongjiang Wang↗
NASA NTRS2003

Large-Eddy Simulation of Conductive Flows at Low Magnetic Reynolds Number

In this paper we study the LES method with dynamic procedure in the context of conductive flows subject to an applied external magnetic field at low magnetic Reynolds number R(sub m). These kind of flows are encountered in many industrial applications. For example, in the steel industry, applied magnetic fields can be used to damp turbulence in the casting process. In nuclear fusion devices (Tokamaks), liquid-lithium flows are used as coolant blankets and interact with the surrounding magnetic field that drives and confines the fusion plasma. Also, in experimental facilities investigating the dynamo effect, the flow consists of liquid-sodium for which the Prandtl number and, as a consequence, the magnetic Reynolds number is low. Our attention is focused here on the case of homogeneous (initially isotropic) decaying turbulence. The numerical simulations performed mimic the thought experiment described in Moffatt in which an initially homogeneous isotropic conductive flow is suddenly subjected to an applied magnetic field and freely decays without any forcing. Note that this flow was first studied numerically by Schumann. It is well known that in that case, extra damping of turbulence occurs due to the Joule effect and that the flow tends to become progressively independent of the coordinate along the direction of the magnetic field. Our comparison of filtered direct numerical simulation (DNS) predictions and LES predictions show that the dynamic Smagorinsky model enables one to capture successfully the flow with LES, and that it automatically incorporates the effect of the magnetic field on the turbulence. Our paper is organized as follows. In the next section we summarize the LES approach in the case of MHD turbulence at low R(sub m) and recall the definition of the dynamic Smagorinsky model. In Sec. 3 we describe the parameters of the numerical experiments performed and the code used. Section 4 is devoted to the comparison of filtered DNS results and LES results. Conclusions are presented in Sec. 5.

Knaepen, B.↗
DOE OSTI2024

Latent Stochastic Differential Equations for Modeling Quasar Variability and Inferring Black Hole Properties

Quasars are bright and unobscured active galactic nuclei (AGN) thought to be powered by the accretion of matter around supermassive black holes at the centers of galaxies. The temporal variability of a quasar’s brightness contains valuable information about its physical properties. The UV/optical variability is thought to be a stochastic process, often represented as a damped random walk described by a stochastic differential equation (SDE). Upcoming wide-field telescopes such as the Rubin Observatory Legacy Survey of Space and Time (LSST) are expected to observe tens of millions of AGN in multiple filters over a ten year period, so there is a need for efficient and automated modeling techniques that can handle the large volume of data. Latent SDEs are machine learning models well suited for modeling quasar variability, as they can explicitly capture the underlying stochastic dynamics. In this work, we adapt latent SDEs to jointly reconstruct multivariate quasar light curves and infer their physical properties such as the black hole mass, inclination angle, and temperature slope. Our model is trained on realistic simulations of LSST ten year quasar light curves, and we demonstrate its ability to reconstruct quasar light curves even in the presence of long seasonal gaps and irregular sampling across different bands, outperforming a multioutput Gaussian process regression baseline. Our method has the potential to provide a deeper understanding of the physical properties of quasars and is applicable to a wide range of other multivariate time series with missing data and irregular sampling.

79 ASTRONOMY AND ASTROPHYSICS↗