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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Scientific applications of frequency-stabilized laser technology in space

A synoptic investigation of the uses of frequency-stabilized lasers for scientific applications in space is presented. It begins by summarizing properties of lasers, characterizing their frequency stability, and describing limitations and techniques to achieve certain levels of frequency stability. Limits to precision set by laser frequency stability for various kinds of measurements are investigated and compared with other sources of error. These other sources include photon-counting statistics, scattered laser light, fluctuations in laser power, and intensity distribution across the beam, propagation effects, mechanical and thermal noise, and radiation pressure. Methods are explored to improve the sensitivity of laser-based interferometric and range-rate measurements. Several specific types of science experiments that rely on highly precise measurements made with lasers are analyzed, and anticipated errors and overall performance are discussed. Qualitative descriptions are given of a number of other possible science applications involving frequency-stabilized lasers and related laser technology in space. These applications will warrant more careful analysis as technology develops.

Schumaker, Bonny L.↗
NASA NTRSDate not supplied

Quasi-Wide-Band Laser

Quasi-Wide-Band (QWB) laser is first-time presented, whose gain-line-shape depends on the frequency-shift and line-broadening caused by temperature gradient and others. The self-mode-locking, ultra-low phase-noise amplification, and coherent beam combination of QWB laser are investigated.

Yingxin Bai↗
NASA NTRS1971

Comparison of laser methods for the remote detection of atmospheric pollutants.

Three methods of remote air pollution detection - Raman backscattering, resonance backscattering, and resonance absorption - are discussed and compared. Theoretical expressions are derived for the minimum detectable pollutant concentration, and in each case the depth resolution and the problems of interference, pump depletion, and background noise are discussed. A brief discussion of possible laser sources is included, numerical examples of the detectabilities based on present technology are given. The atmospheric transparency limits the useful range to a few kilometers for the Raman and resonance backscattering schemes. F or the resonance absorption technique the useful range can be as great as 50 kilometers.

Kildal, H.↗
DOE OSTI2020

Coupling laser physics to radiation-hydrodynamics

In order to accurately model implosion hydrodynamics in a radiation-hydrodynamics code, it is essential to include accurate accounting for energy deposition physics. In inertial confinement fusion (ICF), where capsules are driven by lasers or laser-driven x-rays, energy deposition profiles and energy transport have a strong impact on the development and evolution of capsule dynamics and hydrodynamic instabilities. Nevertheless, accurately modeling laser beam propagation in radiation-hydrodynamics codes presents unique challenges associated with disparate resolution requirements, the potential to seed spurious noise in highly unstable systems, and computational expense. We discuss a new method for coupling laser ray-tracing physics to a radiation hydrodynamics code, developed in the process of implementing the Mazinisin laser ray-trace into the xRAGE radiation hydrodynamics code. In contrast to previous approaches, in which laser ray-tracing is performed on the radiation-hydrodynamics mesh, our method involves a mesh generation and evolution strategy that addresses the unique requirements of the laser ray-trace in a separate mesh, enabling performance enhancements and strategies to reduce noise seeded by the discretization of beams into computational rays. In addition, we have employed several methods to ensure that spurious mesh imprinting is minimized. These involved optimizing the laser and radiation-hydrodynamics meshes as well as interpolation between them and requires the use of an exact initialization method for the radiation-hydrodynamics mesh. Furthermore, these techniques have enabled efficient computation of laser-driven implosions and other experiments with minimal introduction of spurious noise.

47 OTHER INSTRUMENTATION↗
NASA NTRSDate not supplied

High-Speed Self-Aligned Focusing Schlieren and Background-Oriented Schlieren with Pulsed Laser Illumination

Laser light sources are commonly used in schlieren-based flow visualization techniques that are in development at NASA Langley Research Center. Of particular interest are high-intensity, low coherence sources that allow for high signal-to-noise schlieren imagery to be acquired without the laser speckle that typically occurs as a result of interference. Results from a self-aligned focusing schlieren system developed at NASA Langley and a background-oriented schlieren system are presented to highlight the effectiveness of these sources.

Schlieren↗
NASA NTRS2012

Laser Development for Gravitational-Wave Interferometry in Space

We are reporting on our development work on laser (master oscillator) and optical amplifier systems for gravitational-wave interferometry in space. Our system is based on the mature, wave-guided optics technologies, which have advantages over bulk, crystal-based, free-space optics. We are investing in a new type of compact, low-noise master oscillator, called the planar-waveguide external cavity diode laser. We made measurements, including those of noise, and performed space-qualification tests.

Numata, Kenji↗
DOE OSTI2022

Resolution of 100 photons and quantum generation of unbiased random numbers

Macroscopic quantum phenomena, such as observed in superfluids and superconductors, have led to promising technological advancements and some of the most important tests of fundamental physics. At present, quantum detection of light is mostly relegated to the microscale, where avalanche photodiodes are very sensitive to distinguishing single-photon events from vacuum but cannot differentiate between larger photon-number events. Beyond this, the ability to perform measurements to resolve photon numbers is highly desirable for a variety of quantum information applications including computation, sensing, and cryptography. True photon-number resolving detectors do exist, but they are currently limited to the ability to resolve on the order of 10 photons, which is too small for certain proposals. In this work, we extend photon measurement into the mesoscopic regime by implementing a detection scheme based on multiplexing highly quantum-efficient transition-edge sensors to accurately resolve photon numbers between zero and 100. Further, we then demonstrate the use of our system by implementing a quantum random number generator with no inherent bias. This method is based on sampling a coherent state in the photon-number basis and is robust against environmental noise, phase and amplitude fluctuations in the laser, loss and detector inefficiency as well as eavesdropping. Beyond true random number generation, our detection scheme serves as a means to implement quantum measurement and engineering techniques valuable for photonic quantum information processing.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Effectiveness of Deep Learning Trained on SynthCity Data for Urban Point-Cloud Classification

3D object recognition is one of the most popular areas of study in computer vision. Many of the more recent algorithms focus on indoor point clouds, classifying 3D geometric objects, and segmenting outdoor 3D scenes. One of the challenges of the classification pipeline is finding adequate and accurate training data. Hence, this article seeks to evaluate the accuracy of a synthetically generated data set called SynthCity, tested on two mobile laser-scan data sets. Varying levels of noise were applied to the training data to reflect varying levels of noise in different scanners. The chosen deep-learning algorithm was Kernel Point Convolution, a convolutional neural network that uses kernel points in Euclidean space for convolution weights.

Geology↗
DOE OSTI2021

A laser inverse Compton scattering diagnostic to study runaway electron dynamics during tokamak disruptions

Both technical and simulation progress has been made toward implementing a laser inverse Compton scattering diagnostic on the DIII-D tokamak. This is a novel diagnostic which uses a short (sub-ns) pulse laser together with a fast (sub-ns) gated x-ray detector to measure relativistic electrons inside a tokamak plasma. The study of these relativistic electrons is important to make sure they can be removed from any tokamak-based power reactor, as they could damage vessel walls and cooling lines. This diagnostic is completely new for magnetic fusion research and has never been implemented before on a tokamak. It is found that good signals and radial profiles could be obtained with an optimized high-energy (7 Joule) laser. Using a standard off-the-shelf Nd:YAG (0.7 Joule) laser would give some signals above the noise but no ability to measure the relativistic electron radial profile.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Detection of Outliers in LiDAR Data Acquired by Multiple Platforms over Sorghum and Maize

High-resolution point cloud data acquired with a laser scanner from any platform contain random noise and outliers. Therefore, outlier detection in LiDAR data is often necessary prior to analysis. Applications in agriculture are particularly challenging, as there is typically no prior knowledge of the statistical distribution of points, plant complexity, and local point densities, which are crop-dependent. The goals of this study were first to investigate approaches to minimize the impact of outliers on LiDAR acquired over agricultural row crops, and specifically for sorghum and maize breeding experiments, by an unmanned aerial vehicle (UAV) and a wheel-based ground platform; second, to evaluate the impact of existing outliers in the datasets on leaf area index (LAI) prediction using LiDAR data. Two methods were investigated to detect and remove the outliers from the plant datasets. The first was based on surface fitting to noisy point cloud data via normal and curvature estimation in a local neighborhood. The second utilized the PointCleanNet deep learning framework. Both methods were applied to individual plants and field-based datasets. To evaluate the method, an F-score was calculated for synthetic data in the controlled conditions, and LAI, the variable being predicted, was computed both before and after outlier removal for both scenarios. Results indicate that the deep learning method for outlier detection is more robust than the geometric approach to changes in point densities, level of noise, and shapes. The prediction of LAI was also improved for the wheel-based vehicle data based on the coefficient of determination (R2) and the root mean squared error (RMSE) of the residuals before and after the removal of outliers.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Deep Learning with Quantized Neural Networks for Gravitational-wave Forecasting of Eccentric Compact Binary Coalescence

We present the first application of deep learning forecasting for binary neutron stars, neutron star–black hole systems, and binary black hole mergers that span an eccentricity range e ≤ 0.9. In this work, we train neural networks that describe these astrophysical populations, and then test their performance by injecting simulated eccentric signals in advanced Laser Interferometer Gravitational-Wave Observatory (LIGO) noise available at the Gravitational Wave Open Science Center to (1) quantify how fast neural networks identify these signals before the binary components merge; (2) quantify how accurately neural networks estimate the time to merger once gravitational waves are identified; and (3) estimate the time-dependent sky localization of these events from early detection to merger. Our findings show that deep learning can identify eccentric signals from a few seconds (for binary black holes) up to tens of seconds (for binary neutron stars) prior to merger. A quantized version of our neural networks achieves 4× reduction in model size, and up to 2.5× inference speedup. These novel algorithms may be used to facilitate time-sensitive multimessenger astrophysics observations of compact binaries in dense stellar environments.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1978

An electro-optic, high-voltage, transient probe

A newly developed electro-optic voltage transducer is described. It is capable of measuring 30 ns rise time, floating or single-ended, 0 to 20 kV transients in a high noise environment such as a fast discharge laser or energetic switch system. The voltage transient is detected by a specially developed resistor in series with a light emitting diode. The light output (proportional to voltage) is transmitted remotely via a fiber-optic cable to a detector and recorder. Typical signals and comparison with commercial probe system signals are described.

Posta, S. J.↗
NASA NTRS1984

NASA three-laser airborne differential absorption lidar system electronics

The system control and signal conditioning electronics of the NASA three laser airborne differential absorption lidar (DIAL) system are described. The multipurpose DIAL system was developed for the remote measurement of gas and aerosol profiles in the troposphere and lower stratosphere. A brief description and photographs of the majority of electronics units developed under this contract are presented. The precision control system; which includes a master control unit, three combined NASA laser control interface/quantel control units, and three noise pulse discriminator/pockels cell pulser units; is described in detail. The need and design considerations for precision timing and control are discussed. Calibration procedures are included.

Allen, R. J.↗
NASA NTRS1987

Development of a P-I-N HgCdTe photomixer for laser heterodyne spectrometry

An improved HgCdTe photomixer technology was demonstrated employing a p-i-n photodiode structure. The i-region was near intrinsic n-type HgCdTe; the n-region was formed by B+ ion implantation; and the p-region was formed either by a shallow Au diffusion or by a Pt Schottky barrier. Experimental devices in a back-side illuminated mesa diode configuration were fabricated, tested, and delivered. The best photomixer was packaged in a 24-hour LN2 dewar along with a cooled GaAs FET preamplifier. Testing was performed by mixing black-body radiation with a CO2 laser beam and measuring the IF signal, noise, and signal-to-noise ratio in the GHz frequency range. Signal bandwidth for this photomixer was 1.3 GHz. The heterodyne NEP was 4.4 x 10 to the -20 W/Hz out to 1 GHz increasing to 8.6 x 10 to the -10 W/Hz at 2 GHz. Other photomixers delivered on this program had heterodyne NEPs at 1 GHz ranging from 8 x 10 to the -20 to 4.4 x 10 to the -19 W/Hz and NEP bandwidths from 2 to 4 GHz.

Bratt, Peter R.↗
NASA NTRS1996

CCD Detects Two Images In Quick Succession

Prototype special-purpose charge-coupled device (CCD) designed to detect two 1,024 x 1,024-pixel images in rapid succession. Readout performed slowly to minimize noise. CCD operated in synchronism with pulsed laser, stroboscope, or other pulsed source of light to form pairs of images of rapidly moving objects.

Janesick, James R.↗
NASA NTRS2003

Full-Waveform, Wide-Swath Lidar Imaging of Forested and Urban Areas in Leaf-On Conditions: Development, Results and Future Direction

Full-Waveform lidar measurements provide unprecedented views of the vertical and horizontal structure of vegetation and the topography of the Earth s surface. Utilizing a high signal-to-noise ratio lidar system, larger than typical laser footprints (10-20 m), and the recorded time history of interaction between a short-duration (approx. 10 ns) pulse of laser light and the surface of the Earth, full-waveform lidar is able to simultaneously image sub-canopy topography as well as the vertical structure of any overlying vegetation. These data reveal the true 3-D vegetation structure in leaf-on conditions enabling important biophysical parameters such as above-ground biomass to be estimated with unprecedented accuracy. An airborne lidar mission was conducted July-August 2003 in support of the North America Carbon Program. NASA s Laser Vegetation Imaging Sensor (LVIS) was used to image approximately 2,000 km$^2$ in Maine, New Hampshire, Massachusetts and Maryland. Areas with available ground and other data were included (e.g., experimental forests, FLUXNET sites) in order to facilitate as many bio- and geophysical investigations as possible. Data collected included ground elevation and canopy height measurements for each laser footprint, as well as the vertical distribution of intercepted surfaces. Data will be publicly distributed within 6- 12 months of collection. Further details of the mission, including the lidar system technology, the locations of the mapped areas, and examples of the numerous data products that can be derived from the return waveform data products will be presented. Future applications including detection of ground and vegetation canopy changes and a spaceborne implementation of wide-swath, full-waveform imaging lidar will also be discussed.

Blair, James B.↗