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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Phase Inversion: Inferring Solar Subphotospheric Flow and Other Asphericity from the Distortion of Acoustic Waves

A method is proposed for analyzing an almost monochromatic train of waves propagating in a single direction in an inhomogeneous medium that is not otherwise changing in time. An effective phase is defined in terms of the Hilbert transform of the wave function, which is related, via the JWKB approximation, to the spatial variation of the background state against which the wave is propagating. The contaminating effect of interference between the truly monochromatic components of the train is eliminated using its propagation properties. Measurement errors, provided they are uncorrelated, are manifest as rapidly varying noise; although that noise can dominate the raw phase-processed signal, it can largely be removed by low-pass filtering. The intended purpose of the analysis is to determine the distortion of solar oscillations induced by horizontal structural variation and material flow. It should be possible to apply the method directly to sectoral modes. The horizontal phase distortion provides a measure of longitudinally averaged properties of the Sun in the vicinity of the equator, averaged also in radius down to the depth to which the modes penetrate. By combining such averages from different modes, the two-dimensional variation can be inferred by standard inversion techniques. After taking due account of horizontal refraction, it should be possible to apply the technique also to locally sectoral modes that propagate obliquely to the equator and thereby build a network of lateral averages at each radius, from which the full three-dimensional structure of the Sun can, in principle, be determined as an inverse Radon transform.

Gough, Douglas↗
NASA NTRS2013

Mixed Linear/Square-Root Encoded Single-Slope Ramp Provides Low-Noise ADC with High Linearity for Focal Plane Arrays

Single-slope analog-to-digital converters (ADCs) are particularly useful for onchip digitization in focal plane arrays (FPAs) because of their inherent monotonicity, relative simplicity, and efficiency for column-parallel applications, but they are comparatively slow. Squareroot encoding can allow the number of code values to be reduced without loss of signal-to-noise ratio (SNR) by keeping the quantization noise just below the signal shot noise. This encoding can be implemented directly by using a quadratic ramp. The reduction in the number of code values can substantially increase the quantization speed. However, in an FPA, the fixed pattern noise (FPN) limits the use of small quantization steps at low signal levels. If the zero-point is adjusted so that the lowest column is onscale, the other columns, including those at the center of the distribution, will be pushed up the ramp where the quantization noise is higher. Additionally, the finite frequency response of the ramp buffer amplifier and the comparator distort the shape of the ramp, so that the effective ramp value at the time the comparator trips differs from the intended value, resulting in errors. Allowing increased settling time decreases the quantization speed, while increasing the bandwidth increases the noise. The FPN problem is solved by breaking the ramp into two portions, with some fraction of the available code values allocated to a linear ramp and the remainder to a quadratic ramp. To avoid large transients, both the value and the slope of the linear and quadratic portions should be equal where they join. The span of the linear portion must cover the minimum offset, but not necessarily the maximum, since the fraction of the pixels above the upper limit will still be correctly quantized, albeit with increased quantization noise. The required linear span, maximum signal and ratio of quantization noise to shot noise at high signal, along with the continuity requirement, determines the number of code values that must be allocated to each portion. The distortion problem is solved by using a lookup table to convert captured code values back to signal levels. The values in this table will be similar to the intended ramp value, but with a correction for the finite bandwidth effects. Continuous-time comparators are used, and their bandwidth is set below the step rate, which smoothes the ramp and reduces the noise. No settling time is needed, as would be the case for clocked comparators, but the low bandwidth enhances the distortion of the non-linear portion. This is corrected by use of a return lookup table, which differs from the one used to generate the ramp. The return lookup table is obtained by calibrating against a stepped precision DC reference. This results in a residual non-linearity well below the quantization noise. This method can also compensate for differential non-linearity (DNL) in the DAC used to generate the ramp. The use of a ramp with a combination of linear and quadratic portions for a single-slope ADC is novel. The number of steps is minimized by keeping the step size just below the photon shot noise. This in turn maximizes the speed of the conversion. High resolution is maintained by keeping small quantization steps at low signals, and noise is minimized by allowing the lowest analog bandwidth, all without increasing the quantization noise. A calibrated return lookup table allows the system to maintain excellent linearity.

Wrigley, Chris J.↗
NASA NTRS1968

Wideband FM generation.

Wideband FM signal generation without frequency deviation or modulation frequency limitations by wave shaping FM triangular wave, discussing transmitter receiver distortion

Clarke, K. K.↗
NASA NTRS1972

Investigation of factors affecting the heater wire method of calibrating fine wire thermocouples

An analytical investigation was made of a transient method of calibrating fine wire thermocouples. The system consisted of a 10 mil diameter standard thermocouple (Pt, Pt-13% Rh) and an 0.8 mil diameter chromel-alumel thermocouple attached to a 20 mil diameter electrically heated platinum wire. The calibration procedure consisted of electrically heating the wire to approximately 2500 F within about a seven-second period in an environment approximating atmospheric conditions at 120,000 feet. Rapid periodic readout of the standard and fine wire thermocouple signals permitted a comparison of the two temperature indications. An analysis was performed which indicated that the temperature distortion at the heater wire produced by the thermocouple junctions appears to be of negligible magnitude. Consequently, the calibration technique appears to be basically sound, although several practical changes which appear desirable are presented and discussed. Additional investigation is warranted to evaluate radiation effects and transient response characteristics.

Keshock, E. G.↗
NASA NTRS1995

Coherent Effects in Microwave Backscattering Models for Forest Canopies

In modeling forest canopies, several scattering mechanisms are taken into account: 1) volume scattering, 2) surface-volume interaction, and 3) surface scattering from forest floor. Depending on the structural and dielectric characteristics of forest canopies, the relative contribution of each mechanism in the total backscatter signal of an imaging radar can vary. In this paper, two commonly used first order discrete scattering models, Distorted Born Approximation (DBA) and Radiative Transfer (RT) are used to simulate the backscattered power received by polarimetric radars at P-, L-, and C-bands over coniferous and deciduous forests. The difference between the two models resides on the coherent effect in the surface-volume interaction terms.

Microwave Backscattering Models↗
NASA NTRS2017

NeMO-Net: The Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 percent error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets. We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

NeMO-Net↗
NASA NTRS2017

NeMO-Net The Neural Multi-Modal Observation Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets.We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

Remote Sensin↗
NASA NTRS2018

NeMO-Net - The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. By combining spatial and spectral information from varying resolutions, we seek to augment and improve the classification accuracy of previously low-resolution datasets at large temporal scales.NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive learning and training software, currently being developed at NASA Ames, is aimed at assessing the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. The latest iteration uses fully convolutional networks to segment and identify coral imagery taken by UAVs and satellites, including WorldView-2 and Sentinel. We present results taken from the Indian Ocean where classification accuracy has exceeded 91% for 24 geomorphological classes given ample training data. In addition, we utilize deep Laplacian Pyramid Super-Resolution Networks (LapSRN) to reconstruct high resolution information from low resolution imagery, trained from various UAV and satellite datasets. Finally, in the case of insufficient training data, we have developed an interactive online platform that allows users to easily segment and submit their classifications, which has been integrated with the current NeMO-Net workflow. Specifically, we present results from the Fiji islands in which preliminary user data has allowed for the accurate identification of 9 separate classes, despite issues such as cloud shadowing and spectral variation. The project is being supported by NASA's Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

Neural↗
DOE OSTI2026

Pressure-Induced Chemical Bonding Effects on Lattice and Magnetic Instabilities in Antiferromagnetic Insulating CaMn 2 Sb 2

Exotic quantum phenomena often emerge near an electronic delocalization transition (EDT) from an antiferromagnetic insulating phase to a strongly correlated metallic state under pressure. We report the pressure-induced structural and magnetic evolution of the antiferromagnetic insulator CaMn 2 Sb 2 . Single-crystal X-ray diffraction reveals a first-order phase transition near 5.4 GPa from a trigonal P-3m1 structure to a monoclinic P2 1 /m phase accompanied by a ∼7% volume collapse. Residual electron density analysis at intermediate pressures reveals charge localization along Mn–Sb chains, signaling electronic instability preceding the structural transition. Bonding analysis indicates anisotropic Mn–Sb orbital reconfiguration under pressure, driving a distorted square-pyramidal geometry. Neutron scattering confirms the transition and identifies a pressure-induced incommensurate magnetic order, distinct from the ambient antiferromagnetic state. In the monoclinic phase, zigzag Mn chains exhibit antiferromagnetic coupling along the ac-plane, enabled by enhanced orbital overlap. These results establish CaMn 2 Sb 2 as a model system for studying the coupling of structural distortion, charge redistribution, and magnetic order in layered Mn pnictides under pressure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1997

Coherent Effects in Microwave Backscattering Models for Forrest Canopies

In modeling forest canopies, several scattering mechanisms are taken into account: (1) volume scattering; (2) surface-volume interaction; and (3) surface scattering from forest floor. Depending on the structural and dielectric characteristics of forest canopies, the relative contribution of each mechanism in the total backscatter signal of an imaging radar can vary. In this paper, two commonly used first-order discrete scattering models, distorted born approximation (DBA) and radiative transfer (RT) are used to simulate the backscattered power received by polarimetric radars at P-, L-, and C-bands over coniferous and deciduous forests. The difference between the two models resides on the coherent effect in the surface-volume interaction terms. To demonstrate this point, the models are first compared based on their underlying theoretical assumptions and then according to simulation results over coniferous and deciduous forests. It is shown that by using the same scattering functions for various components of trees (i.e., leaf, branch, stem), the radiative transfer and distorted Born models are equivalent, except in low frequencies, where surface-volume interaction terms may become important, and the coherent contribution may be significant. In this case, the difference between the two models can reach up to 3 dB in both co-polarized and cross-polarized channels, which can influence the performance of retrieval algorithms.

Saatchi, Sasan S.↗
NASA NTRS2004

The Direct Digital Modulation of Traveling Wave Tubes

Traveling wave tube (TWT) technology, first described by Rudolf Kompfner in the early 1940s, has been a key component of space missions from the earliest communication satellites in the 1960s to the Cassini probe today. TWTs are essentially signal amplifiers that have the special capability of operating at microwave frequencies. The microwave frequency range, which spans from approximately 500 MHz to 300 GHz, is shared by many technologies including cellular phones, satellite television, space communication, and radar. TWT devices are superior in reliability, weight, and efficiency to solid-state amplifiers at the high power and frequency levels required for most space missions. TWTs have three main components -an electron gun, slow wave structure, and collector. The electron gun generates an electron beam that moves along the length of the tube axis, inside of the slow wave circuit. At the same time, the inputted signal is slowed by its travel through the coils of the helical slow wave circuit. The interaction of the electron beam and this slowed signal produces a transfer of kinetic energy to the signal, and in turn, amplification. At the end of its travel, the spent electron beam moves into the collector where its remaining energy is dissipated as heat or harnessed for reuse. TWTs can easily produce gains in the tens of decibels, numbers that are suitable for space missions. To date, however, TWTs have typically operated at fixed levels of gain. This gain is determined by various, unchanging, physical factors of the tube. Traditionally, to achieve varying gain, an input signal s amplitude has had to first be modulated by a separate device before being fed into the TWT. This is not always desirable, as significant distortion can occur in certain situations. My mentor, Mr. Dale Force, has proposed an innovative solution to this problem called direct digital modulation . The testing and implementation of this solution is the focus of my summer internship. The direct digital modulation of a TWT removes the need for a separate amplitude modulation device. Instead, different levels of gain are achieved by varying the electron beam current. The lower the current, the less kinetic energy is available to be transferred to the signal. To vary the current, a grid is placed in-between the electron gun and the slow wave circuit. By changing the voltage across the grid, the electron beam current can be controlled. Grid technology has mostly been used in pulse applications such as radar, where only two voltage states are necessary. For direct digital modulation, however, a continuous range of voltages is required.

Radhamohan, Ranjan S.↗
NASA NTRS1986

Measuring Acoustic-Radiation Stresses in Materials

System measures nonlinearity parameters of materials. Uses static strain generated by acoustic wave propagating in material. Since static strain is effectively "dc" component of waveform distortion, problems associated with phase-cancellation artifacts disappear. Further, sign of nonlinearity parameter obtained by simple inspection of measured signal polarity. These features make this system very amenable to use in field. System expected to become standard for acoustic-radiation-stress measurements for solids and liquids and for characterization of material properties related to strength and residual or applied stresses. Also expected to become standard for transducer calibration.

Cantrell, John H.↗
NASA NTRS1981

Data enhancement and analysis through mathematical deconvolution of signals from scientific measuring instruments

Mathematical deconvolution of digitized analog signals from scientific measuring instruments is shown to be a means of extracting important information which is otherwise hidden due to time-constant and other broadening or distortion effects caused by the experiment. Three different approaches to deconvolution and their subsequent application to recorded data from three analytical instruments are considered. To demonstrate the efficacy of deconvolution, the use of these approaches to solve the convolution integral for the gas chromatograph, magnetic mass spectrometer, and the time-of-flight mass spectrometer are described. Other possible applications of these types of numerical treatment of data to yield superior results from analog signals of the physical parameters normally measured in aerospace simulation facilities are suggested and briefly discussed.

Wood, G. M.↗
DOE OSTI2025

Quantitative approaches for multiscale structural analysis with atomic resolution electron microscopy

Atomic-resolution imaging with scanning transmission electron microscopy is a powerful tool for characterizing the nanoscale structure of materials, in particular features such as defects, local strains, and symmetry-breaking distortions. In addition to advanced instrumentation, the effectiveness of the technique depends on computational image analysis to extract meaningful features from complex datasets recorded in experiments, which can be complicated by the presence of noise and artifacts, small or overlapping features, and the need to scale analysis over large representative areas. Here, we present image analysis approaches which synergize real and reciprocal space information to efficiently and reliably obtain meaningful structural information with picometer scale precision across hundreds of nanometers of material from atomic-resolution electron microscope images. Damping superstructure peaks in reciprocal space allows symmetry-breaking structural distortions to be disentangled from other sources of inhomogeneity and measured with high precision. Real-space fitting of the wavelike signals resulting from Fourier filtering enables absolute quantification of lattice parameter variations and strain, as well as the uncertainty associated with these measurements. Implementations of these algorithms are made available as an open source python package.

36 MATERIALS SCIENCE↗
NASA NTRS1979

Low-distortion resistive anodes for two-dimensional position-sensitive MCP systems

Microchannel plates (MCPs) are frequently used with resistive anodes to detect charged particles or photons and yield analog signals from which event positions can be decoded. The paper discusses a four-corner concave circular arc terminated resistive anode that permits theoretically distortionless encoding of Cartesian event positions into pulse charge ratios. The theory of the circular arc terminated anode is discussed along with anode design and performance. Electron beam images obtained by using such an anode are presented to confirm the usefulness of the approach.

Lampton, M.↗
NASA NTRS1974

The effects of notch filters on the correlation properties of a PN signal

With wideband pseudo-noise (PN) communications systems, it is sometimes desirable to supplement the inherent interference rejection capabilities by adding notch filters to attenuate relatively narrowband interference. This correspondence presents an investigation of the effects of notch filters on the performance of PN correlation receivers. A theoretical analysis of the correlation drop due to filter distortion has been conducted and confirmed by experimentation. Additional measurements and analysis have established the trade-off between correlation drop and interference suppression as a function of interference bandwidth. A typical result is that by incurring a penalty of a 1-dB drop in correlation peak, interfering signals having bandwidths of 2 to 3% of the PN chip rate can be attenuated by 25 dB.

Sussman, S. M.↗
DOE OSTI2026

Adaptively coupled phase retrieval in multi-peak Bragg coherent diffraction imaging

Recent advances in Bragg coherent diffraction imaging (BCDI) experimental techniques permit routine measurement of multiple Bragg peaks from a single crystalline grain. The resulting images contain the full lattice distortion vector field which can be differentiated to provide lattice strain and rotation. With the advent of fourth-generation synchrotron light sources, such multi-peak datasets are produced at high rates, facilitating the need for rapid phase retrieval of the multiple peaks and subsequent image analysis. Here we describe and demonstrate a new implementation of a coupled phase retrieval technique for multi-peak BCDI which simultaneously treats each Bragg peak of the dataset and produces a three-dimensional image of the crystal's morphology and lattice distortion field. In addition, this method uses the redundant information contained in the various Bragg diffraction patterns to detect and suppress spurious signal appearing on the detector in a subset of the measurements. Compared with manual data editing, adaptive coupling produces a more consistent phase profile in reciprocal space and sharper surfaces in direct space, with no significant difference in computational cost. These improvements reduce the need for manual preprocessing and enable robust high-throughput analysis of multi-peak BCDI data, supporting near-real-time strain microscopy at modern synchrotron facilities.

36 MATERIALS SCIENCE↗