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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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This study examines the effect of snowfall on high frequency microwave radiances measured from above the atmosphere by airborne radiometers. Attention is given to the analysis of a maritime snow storm so that snow accumulation on the surface would not introduce ambiguities into the analysis of the upwelling radiances.
To realize accurate two-color differential measurements, an image digitizing system with variable spatial resolution was designed, built, and integrated to a photon-counting picosecond streak camera, yielding a temporal scan resolution better than 300 femtosecond/pixel. The streak camera is configured to operate with 3 spatial channels; two of these support green (532 nm) and uv (355 nm) while the third accommodates reference pulses (764 nm) for real-time calibration. Critical parameters affecting differential timing accuracy such as pulse width and shape, number of received photons, streak camera/imaging system nonlinearities, dynamic range, and noise characteristics were investigated to optimize the system for accurate differential delay measurements. The streak camera output image consists of three image fields, each field is 1024 pixels along the time axis and 16 pixels across the spatial axis. Each of the image fields may be independently positioned across the spatial axis. Two of the image fields are used for the two wavelengths used in the experiment; the third window measures the temporal separation of a pair of diode laser pulses which verify the streak camera sweep speed for each data frame. The sum of the 16 pixel intensities across each of the 1024 temporal positions for the three data windows is used to extract the three waveforms. The waveform data is processed using an iterative three-point running average filter (10 to 30 iterations are used) to remove high-frequency structure. The pulse pair separations are determined using the half-max and centroid type analysis. Rigorous experimental verification has demonstrated that this simplified process provides the best measurement accuracy. To calibrate the receiver system sweep, two laser pulses with precisely known temporal separation are scanned along the full length of the sweep axis. The experimental measurements are then modeled using polynomial regression to obtain a best fit to the data. Data aggregation using normal point approach has provided accurate data fitting techniques and is found to be much more convenient than using the full rate single shot data. The systematic errors from this model have been found to be less than 3 ps for normal points.
System-identification methods compose a mathematical model, or series of models, from measurements of inputs and outputs of dynamic systems. The extracted models allow the characterization of the response of the overall aircraft or component subsystem behavior, such as actuators and on-board signal processing algorithms. This paper discusses the use of frequency-domain system-identification methods for the development and integration of aircraft flight-control systems. The extraction and analysis of models of varying complexity from nonparametric frequency-responses to transfer-functions and high-order state-space representations is illustrated using the Comprehensive Identification from FrEquency Responses (CIFER) system-identification facility. Results are presented for test data of numerous flight and simulation programs at the Ames Research Center including rotorcraft, fixed-wing aircraft, advanced short takeoff and vertical landing (ASTOVL), vertical/short takeoff and landing (V/STOL), tiltrotor aircraft, and rotor experiments in the wind tunnel. Excellent system characterization and dynamic response prediction is achieved for this wide class of systems. Examples illustrate the role of system-identification technology in providing an integrated flow of dynamic response data around the entire life-cycle of aircraft development from initial specifications, through simulation and bench testing, and into flight-test optimization.
Density irregularities play a vital role in determining how radio frequency (RF) waves travel through plasmas. In the Earth’s ionosphere, these density irregularities also impact radio communication. In this study, we conduct a detailed numerical analysis of RF wave propagation in small-scale ionospheric density irregularities using the advanced Petra-M code. We focus specifically on high-frequency (HF) waves, ranging from 3 to 30 MHz, which are essential for military, amateur radio operators, and emergency communications. By introducing density structures, such as equatorial plasma bubbles derived from fluid simulations, we demonstrate that HF waves can scatter in multiple directions when they encounter these irregularities. Additionally, we observe significant mode conversion, where incoming electromagnetic waves transform into electrostatic modes within the density gradient layer. This shows that smaller density irregularities can greatly weaken signals or cause complete signal loss for receivers, emphasizing the need for increased awareness and innovative solutions in radio communication transmission.
Effects of both nonlinear damping and large-deflection are included in the analysis in an attempt to explain the experimental phenomena of aircraft panels excited at high sound pressure levels; that is the broadening and flattening out of the strain response peaks and the increasing of the response frequency. A nonlinear damping model is considered in the analysis using a single-mode approach. Root-mean-square (RMS) maximum deflection, RMS strains, spectral density functions of strain, and equivalent linear frequency are obtained for clamped and simply supported rectangular symmetric laminated composite plates. It is demonstrated that nonlinear damping is the one which causes the broadening of the response peaks, and it has great influence on RMS panel deflection, RMS strains, and frequency.
We report a high-speed laser diagnostics technique based on point-wise linear Raman spectroscopy for measuring the frequency content of a CH4-air premixed flame stabilized behind a circular bluff body. The technique, which primarily employs a Nd:YLF pulsed laser and a fast image-intensified CCD camera, successfully measures the time evolution of scalar parameters (N2, O2, CH4, and H2O) in the vortex-induced flame instability at a data rate of 1 kHz. Oscillation of the V-shaped flame front is quantified through frequency analysis of the combustion species data and their correlations. This technique promises to be a useful diagnostics tool for combustion instability studies.
The high time resolution observations obtained by the WAVES experiment of the STEREO spacecraft in solar type III radio bursts show that Langmuir waves often occur as intense localized wave packets. These wave packets are characterized by short durations of only a few ms and peak intensities, which well exceed the supersonic modulational instability (MI) thresholds. These timescales and peak intensities satisfy the criterion of the solitons collapsed to spatial scales of a few hundred Debye lengths. The spectra of these wave packets consist of primary spectral peaks corresponding to beam-resonant Langmuir waves, two or more sidebands corresponding to down-shifted and up-shifted daughter Langmuir waves, and low frequency enhancements below a few hundred Hz corresponding to daughter ion sound waves. The frequencies and wave numbers of these spectral components satisfy the resonance conditions of the modulational instability (MI). Moreover, the tricoherences, computed using trispectral analysis techniques show that these spectral components are coupled to each other with a high degree of coherency as expected of the MI type of four wave interactions. The high intensities, short scale lengths, sideband spectral structures and low frequency spectral enhancements and, high levels of tricoherences amongst the spectral components of these wave packets provide unambiguous evidence for the supersonic MI and related strong turbulence processes in type III radio bursts. The implication of these observations include: (1) the MI and related strong turbulence processes often occur in type III source regions, (2) the strong turbulence processes probably play very important roles in beam stabilization as well as conversion of Langmuir waves into escaping radiation at the fundamental and second harmonic of the electron plasma frequency, fpe, and (3) the Langmuir collapse probably follows the route of MI in type III radio bursts.
Surface acoustic wave devices are key components for processing radio frequency signals in wireless communication because these devices offer simultaneously high performance, compact size and low cost. The optimization of the device structure requires a quantitative understanding of energy conversion and loss mechanisms. Here we use stroboscopic full-field diffraction x-ray microscopy to reveal an unanticipated acoustic loss in a prototypical one-port resonator device. A non-uniform acoustic excitation in the active area was responsible for the substantial end and side leakages observed at the design frequency. Quantitative analysis of the strain amplitude using a wave decomposition method allowed the determination of several key device parameters. This high-resolution high-throughput spatiotemporal strain imaging technique is more generally applicable to the study of dynamic strain modulation in nanoscale acoustic, electronic, optical and quantum devices. The high sensitivity allows precise measurement of the strain modulation with picometer-scale amplitude.
BACKGROUND: Chronic orthostatic intolerance (COI) is a debilitating autonomic condition in young adults. Its neurohumoral and hemodynamic profiles suggest possible alterations of postural sympathetic function and of baroreflex control of heart rate (HR). METHODS AND RESULTS: In 16 COI patients and 16 healthy volunteers, intra-arterial blood pressure (BP), ECG, central venous pressure (CVP), and muscle sympathetic nerve activity (MSNA) were recorded at rest and during 75 degrees tilt. Spectral analysis of RR interval and systolic arterial pressure (SAP) variabilities provided indices of sympathovagal modulation of the sinoatrial node (ratio of low-frequency to high-frequency components, LF/HF) and of sympathetic vasomotor control (LFSAP). Baroreflex mechanisms were assessed (1) by the slope of the regression line obtained from changes of RR interval and MSNA evoked by pharmacologically induced alterations in BP and (2) by the index alpha, obtained from cross-spectral analysis of RR and SAP variabilities. At rest, HR, MSNA, LF/HF, and LFSAP were higher in COI patients, whereas BP and CVP were similar in the two groups. During tilt, BP did not change and CVP fell by the same extent in the 2 groups; the increase of HR and LF/HF was more pronounced in COI patients. Conversely, the increase of MSNA was lower in COI than in control subjects. Baroreflex sensitivity was similar in COI and control subjects at rest; tilt reduced alpha similarly in both groups. CONCLUSIONS: COI is characterized by an overall enhancement of noradrenergic tone at rest and by a blunted postganglionic sympathetic response to standing, with a compensatory cardiac sympathetic overactivity. Baroreflex mechanisms maintain their functional responsiveness. These data suggest that in COI, the functional distribution of central sympathetic tone to the heart and vasculature is abnormal.
An outstanding puzzle in the structure of very heavy nuclei lies in the rotation response of deformed transuranic isotopes. While the rotation alignment of pairs of 𝑖 13/2 protons is ubiquitous and well understood, observing the analogous alignment of the 𝑗 15/2 neutrons has been elusive. In this work we present a new quantitative analysis approach: from their moments of inertia as a function of frequency, we compare the alignments of rotational bands with both “low” and high-𝑗 intrinsic structures in the 𝑁 = 151 isotones of Pu, Cm, Cf, and No, thereby distinguishing between the alignments of neutron versus proton pairs through “blocking” effects. In this way, the alignment of 𝑗 15/2 neutrons can be clearly identified for the first time. The protons and neutrons begin aligning at a very similar frequency. The contribution of 𝑗 15/2 neutrons to the total alignment is found to grow with increasing 𝑍 compared to 𝑖 13/2 protons. To explain these observations, it is necessary to adopt a self-consistent set of single-particle energies corresponding to the nuclear shape that minimizes the mass. The shape description needs to include high-order deformations up to at least 𝛽 6 .
The convergence characteristics of various approximate factorizations for the 3D Euler and Navier-Stokes equations are examined using the von-Neumann stability analysis method. Three upwind-difference based factorizations and several central-difference based factorizations are considered for the Euler equations. In the upwind factorizations both the flux-vector splitting methods of Steger and Warming and van Leer are considered. Analysis of the Navier-Stokes equations is performed only on the Beam and Warming central-difference scheme. The range of CFL numbers over which each factorization is stable is presented for one-, two-, and three-dimensional flow. Also presented for each factorization is the CFL number at which the maximum eigenvalue is minimized, for all Fourier components, as well as for the high frequency range only. The latter is useful for predicting the effectiveness of multigrid procedures with these schemes as smoothers. Further, local mode analysis is performed to test the suitability of using a uniform flow field in the stability analysis. Some inconsistencies in the results from previous analyses are resolved.
A determination is presented of the ionospheric refraction correction requirements for the Goddard range and range rate (GRARR) S-band, modified S-band, very high frequency (VHF), and modified VHF systems. The relation ships within these four systems are analyzed to show that the refraction corrections are the same for all four systems and to clarify the group and phase nature of these corrections. The analysis is simplified by recognizing that the range rate is equivalent to a carrier phase range change measurement. The equation for the range errors are given.
The thermocatalytic reduction of CO2 by H2 often proceeds via two competing reaction mechanisms—the reverse water gas shift reaction (rWGSR, CO2 + H2 ⇌ CO + H2O) and methanation (CO2 + 4H2 ⇌ CH4 + 2H2O). Atomically dispersed Rh1 catalysts on TiO2 show high selectivity toward the rWGSR compared with larger Rh nanoclusters, but the origin of this size-dependent selectivity has not been fully explained. Here we report density functional theory (DFT) calculations and microkinetic simulations that clarify the Rh1 active sites and rWGSR pathway on anatase TiO2(101), as well as the high rWGSR selectivity of Rh1 compared with supported Rhx (x = 2–8 atoms) nanoclusters. DFT-computed formation energies, vibrational frequency analysis, and microkinetic modeling suggest three plausible active sites: Rh1 on titania (Rh1/TiO2(101)), Rh1 with a nearby hydroxyl group (Rh1OH/TiO2(101)), and Rh1 near an oxygen vacancy at a three-fold coordinated site (Rh1 near O3cvac). Predicted turnover frequencies and apparent activation barriers for Rh1 indicate a faster reaction involving CO2 dissociation assisted by a support oxygen vacancy via Rh1 near O3cvac, as well as slower reactions involving Rh1OH/TiO2(101) or Rh1/TiO2(101) through a COOH intermediate. Furthermore, these Rh1 sites are selective toward CO rather than CH4 because of the weak adsorption of CO, large barrier for C-O bond dissociation, and the lack of nearby metal sites for H2 dissociation, in contrast to Rhx nanoclusters, including Rh2 dimers.
Cables are initially qualified for nuclear power plant use for 40 years. As plants extend their operating license to 60 and 80 years, continued use of these cables must shift to a performance-based approach since it is cost prohibitive to completely replace cables that are likely still capable of performing their design function. A variety of cable tests are available and are commonly applied during outages when the cables can be taken out of service. Frequency domain reflectometry (FDR) is one of these test methods that is being more broadly accepted and used because it not only detects anomalies along the cable with a low-voltage signal that does not stress the cable insulation, but the technique also locates the anomalies. This supports follow-up local inspection and local repair or partial replacement of a damaged cable segment. Currently, FDR testing is only applied to cables that are taken out of service since the test instrument would be damaged by operational voltages. A related technology that has found some acceptance in the aircraft and rail industry is spread spectrum time domain reflectometry (SSTDR). This technology has been implemented with a custom commercial instrument by LiveWire Innovation Inc. that is designed to operate on live cables up to 1000 volts. One of the main conclusions of a previous effort was that cable reflectometry plots can be difficult for humans to analyze due to baseline noise, low or noisy anomaly response peaks, or large responses from cable ends. Detection of cable anomalies for many of these frequencies and test conditions was challenging for manual analysis. This presented an ideal opportunity for ML analysis to distinguish undamaged cable indications from anomalous cable indications. This research discusses application of machine learning (ML) to reflectometry cable test methods. The goal was to assess feasibility to distinguish undamaged cable reflectometry responses from damaged or anomalous cable reflectometry responses. The assessment considered the 3 instruments, multiple frequency bandwidths from each instrument, multiple cable anomalies and test conditions, and both supervised and unsupervised ML approaches. Although approaches and analysis methods were not identical or directly comparable, both outputs were encouraging. The unsupervised prediction weighted accuracy was assessed by instrument and by frequency. It performed better at high frequencies with the highest prediction accuracy of 0.84 for the higher frequency FDR, 0.79 for the 48-MHz LiveWire SSTDR, and 0.77 for 300-MHz PNNL SSTDR. The initial weighted accuracy average across all frequencies for using supervised ML was 0.56 to 0.68. The supervised analysis was repeated with noisier training data removed resulting in weighted accuracies of 0.69 to 0.87. These weighted accuracies are not directly comparable due to differences in the supervised and unsupervised analysis details but do indicate an encouraging trend. Even with limited and unbalanced data, strong prediction accuracies seem encouraging for further work including more data under a wider range of conditions.
This paper reports on a surface impedance measurement of a bulk metal niobium–titanium superconducting radio frequency (SRF) cavity in a magnetic field (up to 10 T). Here, a novel method is employed to decompose the surface resistance contributions of the cylindrical cavity end caps and walls using measurements from multiple TM cavity modes. The results confirm that quality factor degradation of a NbTi SRF cavity in a high magnetic field is primarily from surfaces perpendicular to the field (the cavity end caps), while parallel surface resistances (the walls) remain relatively constant. This result is encouraging for applications needing high Q cavities in strong magnetic fields, such as the Axion Dark Matter eXperiment because it opens the possibility of hybrid SRF cavity construction to replace conventional copper cavities.
The Cyclotron Radiation Emission Spectroscopy (CRES) technique pioneered by Project 8 measures cyclotron radiation from individual electrons in a background magnetic field to construct a highly precise energy spectrum for beta decay studies and other applications. The detector, magnetic trap geometry, and electron dynamics give rise to a multitude of complex electron signal structures which carry information about distinguishing physical traits. Here, we develop machine learning models to classify CRES signals with high accuracy based on these traits, improve the resultant frequency spectrum, and offer the potential for a sophisticated analysis which will help Project 8 achieve tritium endpoint measurement in the future.
Effective real-time monitoring and analysis of distributed grids necessitate the use of synchro-waveform measurements, which capture almost all high-frequency disturbances and transient phenomena. However, due to limitations in high-speed measurements and network bandwidth, it is challenging to transfer all high-fidelity synchro-waveforms losslessly and successfully. To cope with these challenges, a hybrid-based online multi-stage compression algorithm is proposed to significantly improve the compression efficiency for synchro-waveform measurements. Initially, the multiple discrete Wavelet transformation is deployed to deconstruct the waveform components. The delta encoding is further developed to decrease the magnitude. In conjunction with the Lempel-Ziv-Markov chain, the hybrid compression algorithm is implemented to achieve real-time compression for the synchro-waveform measurements. Moreover, an innovative error index that synergizes the time and frequency domain error and correlation is formulated to evaluate the waveform distortion. By integrating compression ratio, suitable parameters can be optimally selected. Finally, the simulation, laboratory experiments, as well as field tests across a spectrum of sampling frequencies and time intervals are conducted to substantiate the efficacy of the proposed method. Here, the outcomes demonstrated that a compression ratio of approximately 15.5 and 17.83 can be reached for 0.5 s and 1 s data under both offline and online scenarios, which equates to a substantial 93.5% to 94.39% reduction in data storage requirements.
This letter presents the discovery of a new type oscillations associated with inverter-based resources (IBRs) in weak grids. While typical weak grid oscillations become worse when the grid strength decreases and the power exporting level increases, this new type of oscillations appear when the grid becomes weaker and the power exporting level decreases. Electromagnetic transient (EMT) simulation results are presented, along with eigenvalue loci for a varying power. The notable signatures of such oscillations are also remarked. In further analysis, a feedback system consisting of two blocks is derived with one block associated with the phase-locked-loop (PLL) and the other associated with the rest of the system. Here, this feedback system quantitatively demonstrates why insufficient damping in the PLL may be an issue for stability. Open-loop analysis shows that a larger phase lag in angle tracking in the low-frequency range due to high power exporting level at the weak grid condition is beneficial to the open-loop poles introduced by the PLL. And this is the reason why such oscillations may appear when power is ramping down.