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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1961

Applications of Power Spectral Analysis Methods to Maneuver Loads Obtained on Jet Fighter Airplanes During Service Operations

Power spectral densities of normal load factor have been obtained for two service operational training flights of a Republic F-84G airplane and three service operational training flights of a North American F-86A airplane in order to indicate the load-factor frequency content and possible uses of power spectral methods in analyzing maneuver load data. It was determined that the maneuvering load-factor time histories appeared to be described by a truncated normal distribution. The power spectral densities obtained were relatively level at frequencies below 0.03 cycle per second and varied inversely with approximately the cube of the frequency at the higher frequencies. In general, the frequency content was very low above 0.2 cycle per second. The load-factor peak distributions were estimated fairly well from the spectrum analysis. In addition, peak load data obtained during service operations of fighter-type airplanes with flight time totaling about 24,000 hours were examined and appeared to agree reasonably well with the type of equations obtained from spectrum peak-load distributions.

Mayer, John P.↗
NASA NTRS1986

Spectra of noise and amplified turbulence emanating from shock-turbulence interaction: Two scenarios

This work is a small extension of NACA studies of the early fifties that predicted amplification of turbulence on passing through a shock wave (observed for turbulent boundary layers), as well as the generation of intense noise (observed for supersonic jets). The first solved the basic gasdynamics problem of the interaction of an infinite planar shock with a single three-dimensional spectrum component of turbulence (an oblique sinusoidal shear wave). The second developed the comprehensive 3D spectrum analysis necessary to generalize the scenario to the interaction of a shock wave with convected homogeneous turbulence. Numerical calculations were carried out to yield curves (vs. Mach number) of rms sound pressure, temperature fluctuation, and two components of turbulent velocity downstream of the shock, for two cases of preshock turbulence. The present numerical study reproduces these for one case and provides in addition their one-dimensional power spectra (vs. wavenumber or frequency). Ratios of the several postshock spectra to the longitudinal preshock turbulence spectrum (1D) have been computed for a wide range of Mach numbers; curves vs. wavenumber are presented for two scenarios of preshock turbulence: isotropy and axisymmetry, both based on the von Karman 3D spectrum.

Ribner, H. S.↗
NASA NTRS1987

Spectra of noise and amplified turbulence emanating from shock-turbulence interaction

This work is a small extension of NACA studies of the early fifties that predicted amplification of turbulence on passing through a shock wave (observed for turbulent boundary layers), as well as the generation of intense noise (observed for supersonic jets). The first solved the basic gasdynamics problem of the interaction of an infinite planar shock with a single three-dimensional spectrum component of turbulence (an oblique sinusoidal shear wave). The second developed the comprehensive 3D spectrum analysis necessary to generalize the scenario to the interaction of a shock wave with convected homogeneous turbulence. Numerical calculations were carried out to yield curves (vs. Mach number) of rms sound pressure, temperature fluctuation, and two components of turbulent velocity downstream of the shock, for two cases of preshock turbulence. The present numerical study reproduces these for one case and provides in addition their one-dimensional power spectra (vs. wavenumber of frequency). Ratios of the several postshock spectra to the longitudinal preshock turbulence spectrum (4D) have been computed for a wide range of Mach numbers; curves vs. wavenumber are presented for two scenarios of preshock turbulence: isotropy and axisymmetry, both based on the von Karman 3D spectrum.

Ribner, Herbert S.↗
NASA NTRS1988

Spectrometer technology recommendations

A typical heterodyne remote sensing system contains three major elements: the antenna, the radiometer, and the spectrometer. The radiometer consists of the local oscillator, the mixer, and the intermediate frequency amplifiers. This subsystem performs the function of down converting the high frequency incident thermal emission signal to a lower intermediate frequency. The spectrometer measures the power spectrum of the down-converted signal simultaneously in many contiguous frequency channels. Typical spectrum analysis requirements involve measurement of signal bandwidths of 100 to 1000 MHz with a channel resolution of 0.5 to 10 MHz. Three general approaches are used for spectrometers: (1) filter banks, (2) Acousto-Optic Spectrometers (AOS's), and (3) digital autocorrelators. In contrast to the two frequency domain techniques, an autocorrelator works in the time domain. The autocorrelation function (ACF) of the incoming signal is computed and averaged over the integration time. The averaged ACF is then Fourier transformed to obtain the signal power spectrum. Significant progress was made in the development of sub mm antennas and radiometers. It is now time to begin research in the development of low power spaceborne spectrometers and to reduce their size and weight. The near-term research goal will be to develop a prototype digital autocorrelation spectrometer, using VLSI gate array technology, which will have a small size, low power requirements, and can be used in spacecraft mm and sub mm radiometer systems. The long-range objective of this technology development is to make extremely low power, less than 10 mW/channel, small and stable wideband spectrometers which can be used in future mm and sub mm wavelength space missions such as the Large Deployable Reflector.

Wilson, William J.↗
DOE OSTI2022

Neural network acceleration of large-scale structure theory calculations

Here, we make use of neural networks to accelerate the calculation of power spectra required for the analysis of galaxy clustering and weak gravitational lensing data. For modern perturbation theory codes, evaluation time for a single cosmology and redshift can take on the order of two seconds. In combination with the comparable time required to compute linear predictions using a Boltzmann solver, these calculations are the bottleneck for many contemporary large-scale structure analyses. Here, we construct neural network-based surrogate models for Lagrangian perturbation theory (LPT) predictions of matter power spectra, real and redshift space galaxy power spectra, and galaxy-matter cross power spectra that attain ~ 0.1% (at one sigma) accuracy over a broad range of scales in a ωCDM parameter space. The neural network surrogates can be evaluated in approximately one millisecond, a factor of 1000 times faster than the full Boltzmann code and LPT computations. In a simulated full-shape redshift space galaxy power spectrum analysis, we demonstrate that the posteriors obtained using our surrogates are accurate compared to those obtained using the full LPT model. We make our surrogate models public at https://github.com/sfschen/EmulateLSS, so that others may take advantage of the speed gains they provide to enable rapid iteration on analysis settings, something that is essential in complex contemporary large-scale structure analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Operando XPS in reactive plasmas: The importance of the wall reactions

In this article, advancements in differential pumping and electron optics over the past few decades have enabled x-ray photoelectron spectroscopy (XPS) measurements at (near-)ambient pressures, bridging the pressure gap for characterizing realistic sample chemistries. Recently, we have demonstrated the capabilities of an ambient pressure XPS setup for in situ plasma environment measurements, allowing plasma-surface interactions to be studied in operando rather than using the traditional before-and-after analysis approach. This new “plasma-XPS” technique facilitates the identification of reaction intermediates critical for understanding plasma-assisted surface processes relevant to semiconductor nanomanufacturing, such as physical vapor deposition, etching, atomic layer deposition, and many other plasma applications. In this paper, we apply the plasma-XPS approach to monitor real-time surface chemical changes on a model Ag(111) single crystal exposed to oxidizing and reducing plasmas. We correlate surface-sensitive data with concurrent gas-phase XPS measurements and residual gas mass-spectrum analysis of species generated during plasma exposure, highlighting the significant role of plasma-induced chamber wall reactions. Ultimately, we demonstrate that plasma-XPS provides comprehensive insights into both surface and gas-phase chemistry, establishing it as a versatile and dynamic characterization tool with broad applications in microelectronics research. Finally, we outline potential enhancements and future metrology directions to advance plasma-XPS investigations further.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Remote Radiation Sensing Using Aerial and Ground Platforms

Remote sensing of ionizing radiation has a significant role in waste management, nuclear material management and nonproliferation, and radiation safety. Robotic platforms can surpass the number of tasks that are achieved by humans. With this technique, the operator's radiation exposure can be decreased. Remote sensing allows for the evaluation and monitoring of radiological contamination. Gamma-ray and neutron sensors were integrated onto the robotic platforms. This approach allows for the radiation sensor data to be dynamically tracked and mapped thus enabling further analysis of the radiation flux in temporal and spatial domains. The goal is to complete scheduled tasks while the robot is being irradiated. To achieve this, electronic components must be shielded and radiation hardened. CZT Detector: Cadmium Zinc Telluride (CZT) detector technology has been a promising solution for gamma-ray and x-ray measurements. Detector data is transferred to the Odroid minicomputer that controls and powers the module via the USB. Robot Operating System (ROS) was utilized for data acquisition and data fusion. The Mariscotti method was employed for the spectrum analysis. A function was programmed in ROS for the automatic identification of photopeaks. CLYC Detector: A Cs{sub 2}LiYCl{sub 6}:Ce{sup 3+} (CLYC) detector was used for simultaneous medium-resolution gamma-ray measurements and neutron counting. A 2.54 cm diameter photomultiplier tube (PMT) was equipped with a high voltage supply and a miniature digitizer. Gamma-ray excitation: fast core-to-valence luminescence (CVL) with 1 ns decay constant, and prompt Ce{sup 3+} emission with 50 ns decay constant. Neutron excitation: slow cerium self-trapped excitation (Ce{sup 3+} STE), 1000 ns decay constant. Radiation Source Localization: Maximum Likelihood Estimation (MLE) and gradient-based methods were used to locate the position of a radiation source based on measured radiation intensities. Multi-Particle Transport Code FLUKA: Estimation of radiation damage of the electronic components is important in order to optimize the robot's operational time while it is irradiated. Displacement per atom (DPA) represents the radiation damage in materials exposed to the ionizing radiation. Various shielding layers of different thickness t were analyzed (< 5% statistical error). The model of the controller of the UAS was designed in FLUKA. Conclusion: CZT and CLYC detectors were integrated onto the robotic platforms. Radiation source localization and contour mapping using robotic platforms were studied. Functions for data analysis and fusion were developed in ROS. FLUKA code was utilized to analyze DPA values. Layers of low-density and high-density materials were used to shield the UAS electronics.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Electrically interfaced Brillouin-active waveguide for microwave photonic measurements

New strategies for converting signals between optical and microwave domains could play a pivotal role in advancing both classical and quantum technologies. Traditional approaches to optical-to-microwave transduction typically perturb or destroy the information encoded on intensity of the light field, eliminating the possibility for further processing or distribution of these signals. In this paper, we introduce an optical-to-microwave conversion method that allows for both detection and spectral analysis of microwave photonic signals without degradation of their information content. This functionality is demonstrated using an optomechanical waveguide integrated with a piezoelectric transducer. Efficient electromechanical and optomechanical coupling within this system permits bidirectional optical-to-microwave conversion with a quantum efficiency of up to -54.16 dB. Leveraging the preservation of the optical field envelope in intramodal Brillouin scattering, we demonstrate a multi-channel microwave photonic filter by transmitting an optical signal through a series of electro-optomechanical waveguide segments, each with distinct resonance frequencies. Such electro-optomechanical systems could offer flexible strategies for remote sensing, channelization, and spectrum analysis in microwave photonics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Identification of Distorted Gamma-Ray Signature Patterns Using Digital Filtering and Auto-Associative Memory Implemented with a Hopfield Neural Network

The detection and identification of radioactive sources in search applications involve analyzing passive gamma-ray emissions from high-level radioactive materials. This process uses a mobile detector-spectrometer in a complex field test environment. Recently, the use of artificial intelligence for gamma-ray spectrum analysis has shown promising results. However, challenges persist in identifying isotopic signatures from spectral measurements that may be distorted due to source shielding, random variations in natural radioactive background, or insufficient measurement time to obtain clear spectral lines. Here, this paper presents a novel intelligent signature recognition method that combines digital filtering techniques with an artificial Hopfield Neural Network (HNN). The HNN leverages auto-associative memory to store training sample patterns and match them with incoming gamma spectra from distorted sources. It restores the testing sources’ measurements by finding the closest matching signature patterns in the spectral library. Before HNN recognition, the measured spectrum undergoes preprocessing with a digital image filter to reduce fluctuations. Performance of the proposed method is evaluated using a set of gamma-ray spectra measured with a sodium iodide detector. The data collected include measurements from six pure samples: 241 Am, 60 Co, 137 Cs, 192 Ir, 239 Pu, and 235 U, which are used for training and validation (i.e. six cases). Additionally, the data set contains 24 distorted synthesized sources with various fluctuating backgrounds. Test results demonstrate the potential of the proposed method to accurately recognize the correct isotope with high precision, achieving an accuracy rate exceeding 85%. Furthermore, the proposed method exhibits superior performance compared to the conventional multiple regression fitting and simple feedforward neural network methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1988

Winds aloft statistical analysis in support of day of launch Shuttle systems evaluation

In connection with the development of the Meteorological Interactive Data Display System (MIDDS) for utilization by the Launch Systems Evaluation Advisory Team (LSEAT), requirements have been established to expand the pre-launch analysis of winds aloft for the Space Shuttle. Statistical analyses developed for the system include: comparison of pre-launch wind component profiles to wind component extremes at each altitude calculated from launch site historical data; conditional probability ellipses for wind vectors at a future time given the wind vector at an initial time; comparison of observed extreme wind shear and associated wind speed with launch site historical data utilizing the bivariate extreme value (Gumbel) distribution; estimation of extremes of wind speed or wind shear at a future time given the extremes of either variable at an initial time, utilizing the conditional extreme value distribution; power spectrum analysis for tracking wind perturbation energy in sequential pre-launch Jimsphere wind profiles.

Adelfang, S. I.↗
NASA NTRS1978

Dynamic analysis of flexible rotor-bearing systems using a modal approach

The generalized dynamic equations of motion were obtained by the direct stiffness method for multimass flexible rotor-bearing systems. The direct solution of the equations of motion is illustrated on a simple 3-mass system. For complex rotor-bearing systems, the direct solution of the equations becomes very difficult. The transformation of the equations of motion into modal coordinates can greatly simplify the computation for the solution. The use of undamped and damped system mode shapes in the transformation are discussed. A set of undamped critical speed modes is used to transform the equations of motion into a set of coupled modal equations of motion. A rapid procedure for computing stability, steady state unbalance response, and transient response of the rotor-bearing system is presented. Examples of the application of this modal approach are presented. The dynamics of the system is further investigated with frequency spectrum analysis of the transient response.

Choy, K. C.↗
DOE OSTI2023

Enabling quantitative analysis of complex polymer blends by infrared nanospectroscopy and isotopic deuteration

Atomic-force microscopy coupled with infrared spectroscopy (AFM-IR) deciphers surface morphology of thin-film polymer blends and composites by simultaneously mapping physical topography and chemical composition. However, acquiring quantitative phase and composition information from multi-component blends can be challenging using AFM-IR due to the possible overlapping infrared absorption bands between different species. Isotope labeling one of the blend components introduces a new type of bond (carbon-deuterium vibration) that can be targeted using AFM-IR and responds at wavelengths sufficiently shifted toward unoccupied regions (around 2200 cm –1 ). In this project, AFM-IR was used to probe the surface morphology and chemical composition of three polymer blends containing deuterated polystyrene; each blend is expected to exhibit various degrees of miscibility. AFM-IR results successfully demonstrated that deuterium labeling prevents infrared spectral overlap and enables the visualization of blend phases that could not normally be distinguished by other scanning probe techniques. The nanoscale domain composition was resolved by fast infrared spectrum analysis. Overall, we presented isotope labeling as a robust approach for circumventing obstacles preventing the quantitative analysis of multiphase systems by AFM-IR.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Evaluating the mutagenicity of N-nitrosodimethylamine in 2D and 3D HepaRG cell cultures using error-corrected next generation sequencing

Human liver-derived metabolically competent HepaRG cells have been successfully employed in both two-dimensional (2D) and 3D spheroid formats for performing the comet assay and micronucleus (MN) assay. In the present study, we have investigated expanding the genotoxicity endpoints evaluated in HepaRG cells by detecting mutagenesis using two error-corrected next generation sequencing (ecNGS) technologies, Duplex Sequencing (DS) and High-Fidelity (HiFi) Sequencing. Both HepaRG 2D cells and 3D spheroids were exposed for 72 h to N-nitrosodimethylamine (NDMA), followed by an additional incubation for the fixation of induced mutations. NDMA-induced DNA damage, chromosomal damage, and mutagenesis were determined using the comet assay, MN assay, and ecNGS, respectively. The 72-h treatment with NDMA resulted in concentration-dependent increases in cytotoxicity, DNA damage, MN formation, and mutation frequency in both 2D and 3D cultures, with greater responses observed in the 3D spheroids compared to 2D cells. The mutational spectrum analysis showed that NDMA induced predominantly A:T → G:C transitions, along with a lower frequency of G:C → A:T transitions, and exhibited a different trinucleotide signature relative to the negative control. These results demonstrate that the HepaRG 2D cells and 3D spheroid models can be used for mutagenesis assessment using both DS and HiFi Sequencing, with the caveat that severe cytotoxic concentrations should be avoided when conducting DS. With further validation, the HepaRG 2D/3D system may become a powerful human-based metabolically competent platform for genotoxicity testing.

3D spheroids↗
DOE OSTI2026

Using Filter Methods to Guide Convergence for ADMM, with Applications to Nonnegative Matrix Factorization Problems

Nonconvex, nonlinear optimization problems arise naturally in parameter fitting and machine learning. While augmented Lagrangian methods have demonstrated robust convergence for classes of these problems, their convergence for block updates has been relatively unexplored outside of the context of the alternating direction method of multipliers (ADMM). ADMM has seen extensive use in these applications, but may exhibit uncertain convergence behavior in many practical nonconvex settings, and struggles with general nonlinear constraints. In contrast, filter methods have proved effective in enforcing convergence for sequential quadratic programming methods and interior point methods with feasibility criteria. We develop an ADMM-filter method for highly nonlinear and nonconvex problems. Here, we show convergence under mild assumptions for several types of coordinate descent schemes, and demonstrate our algorithm on nonnegative matrix factorization and completion problems in imaging and chemical spectrum analysis.

Nonconvex optimization↗
DOE OSTI2021

Surface enhanced performance of La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3-δ cathodes by infiltration Pr-Ni-Mn-O progress

Herein the present study reports the enhancement of electrochemical oxygen reduction activity of porous La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3–δ (LSCF) cathodes by coating a thin film of Pr-Ni-Mn oxide (PNM5) using a multi-step infiltration process. XRD examination reveals that PNM5 mainly contains a multiphase mixture of Pr 6 O 11 , PrNiO 3 , MnO and NiO. SEM morphology shows a thin PNM5 film and small particles are formed on the surface of LSCF backbone particles. Impedance spectrum analysis indicates that PNM5 infiltrated LSCF exhibits dramatically reduced polarization resistance (R p ), reaching R p of 0.244 Ω cm 2 at 973 K, which is one-half of the baseline LSCF cathode. The activation energy of LSCF cathodes infiltrated with PNM5 is 1.45 eV, slightly lower than the baseline LSCF cathode (1.77 eV). Distribution of relaxation time (DRT) function analysis shows PNM5 infiltration layer significantly promotes the oxygen reduction reaction (ORR) of cathode surface. With the increase in firing temperature, the total resistance increases and R p changes from ion transport to oxygen reduction reaction. Degradation rate of the PNM5-infiltrated LSCF is also lower, 0.02168% vs 0.07093% for the baseline LSCF over a 200-h period. A single cell testing indicated that the peak power density of the PNM5-infiltrated cell was increased by 140.66%. Overall, PNM5 could be a potential catalyst for boosting the performance of a commercial LSCF cathode for solid oxide fuel cells (SOFC).

36 MATERIALS SCIENCE↗
DOE OSTI2023

Interplanar Ferromagnetism Enhanced Ultrawide Zero Thermal Expansion in Kagome Cubic Intermetallic (Zr,Nb)Fe 2

A cubic metal exhibiting zero thermal expansion (ZTE) over a wide temperature window demonstrates significant applications in a broad range of advanced technologies but is extremely rare in nature. Here, enabled by high-temperature synthesis, we realize tunable thermal expansion via magnetic doping in the class of kagome cubic (Fd-3m) intermetallic (Zr,Nb)Fe 2 . A remarkably isotropic ZTE is achieved with a negligible coefficient of thermal expansion (+0.47 x 10 -6 K -1 ) from 4 to 425 K, almost wider than most ZTE in metals available. A combined in situ magnetization, neutron powder diffraction, and hyperfine Mössbauer spectrum analysis reveals that interplanar ferromagnetic ordering contributes to a large magnetic compensation for normal lattice contraction upon cooling. Trace Fe-doping introduces extra magnetic exchange interactions that distinctly enhance the ferromagnetism and magnetic ordering temperature, thus engendering such an ultrawide ZTE. Finally, this work presents a promising ZTE in kagome metallic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Shivalik Plasma Device-I, a glow discharge device to study the collective dynamics of dusty plasma

Using a uniquely configured glow discharge-based Shivalik Plasma Device-I, we demonstrate a variety of collective phenomena in dusty plasma away from the glow discharge region. The cylindrical glass device produces plasma using parallel disc-shaped electrodes with a smaller anode size than the cathode. The dust microparticles are initially sprinkled over the grounded cathode. These particles acquire a significant negative charge upon plasma formation, resulting in their levitation due to the balance between the Coulomb force and gravity. The new device supports the levitation of a big-sized (10 × 8 × 5 cm 3 ) three-dimensional dust cloud over the glass surface. It contrasts the dusty plasma formations in-between electrodes reported earlier. As the discharge voltage varies from high to low, the dust cloud travels from over the glass surface to between the electrodes. A complex interplay of dust void over the cathode, a sharp density gradient, and gravity lead to self-excitation of collective dust phenomena. It includes dust density waves (phase velocity, v ph ~4 cm/s), dust cloud oscillation (frequency, f = 5 Hz), sheared flow (flow velocity, v f ~ 1 cm/s), and multiple-sized dust vortices. These dust vortices provided an excellent platform for studying turbulent mixing phenomena. The power spectrum analysis agreed with two-dimensional Kolmogorov power-law scaling. This is an ideal dusty plasma apparatus where we can create or move the dust cloud to a location of choice from the glass surface to in-between the electrodes and excite one among many collective dust dynamics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Radioisotope Identification with List-Mode Gamma-Ray Data

This work explores the potential of utilizing temporal data from gamma-ray detectors, known as list-mode data, to enhance radioisotope identification. Traditional identification methods, which rely on full gamma-ray spectrum analysis, often require long dwell times and struggle with spectra containing similarly spaced spectral peaks. We hypothesize that by leveraging the probabilistic nature of nuclear decay and the time-encoded information from decay sequences and interactions with surrounding materials, we can improve classification accuracy over static spectral analysis. This research examines the temporal content of list-mode data through exploratory data analysis via correlation discovery and qualitative distribution analysis. Additionally, we propose a probabilistic classification model that can utilize spectral data, temporal data, or both to determine if the incorporation of temporal information improves radioisotope identification. Our findings suggest that the temporal information present in list-mode gamma-ray data has merit and should be further investigated to develop more robust and optimal methods for utilizing this temporal information in applications requiring radioisotope identification.

List-mode data↗