Search NASA⌕ Search

SEARCH · Search NASA

Results for “INFRARED INSPECTION”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

269 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Smart Methane Emission Detection System Development (Final Report)

Working with the Department of Energy's National Energy Technology Laboratory, Southwest Research Institute® (SwRI®) developed a system to identify methane leaks reliably, accurately, and autonomously at critical midstream sections of the natural gas distribution network in real-time for the purpose of mitigating methane emissions using Optical Gas Imaging (OGI) cameras. SwRI's Smart Leak Detection – Methane (SLED/M) adds a high degree of automation to the process of methane leak detection to minimize sources of human error, minimize response time to a leak event, and maximize midstream visibility. Furthermore, SwRI has been working towards integrating Quantitative OGI (QOGI) capabilities into this existing technology. By leveraging Deep Learning, SwRI now has the capability to estimate fugitive emission leak rates quickly and reliably, which allows operators to detect emissions, quantify leak rate, prioritize repairs, and validate the repairs in a single instrument. The next generation QOGI technology leverages the same cameras used in Leak Detection and Repair (LDAR) programs, with improvements in safety and speed for traditional quantification-based repairs, ultimately leading to less overhead cost for the operators. The goals for this research were to develop two types of models with the following goals: Run in real-time on the edge (≥ 12 Hz), Classification: Achieve less than 5% false positive detection, Classification: Achieve ≥ 95% methane plume detection rate, Regression: achieve ≤ 10 standard cubic feet per hour (scfh) prediction > 70% of the time. In order to achieve these results, multiple infrared (IR) and other sensors were investigated in tandem with the midwave IR (MWIR) OGI to provide additional information to train the underlying models. Information on atmospheric conditions including humidity, temperature, pressure, and solar radiation was provided by a weather station. Several machine learning and deep learning architectures and methods, including looking at quantized classification networks and regressions networks, were explored. As further data was collected, curated, and labeled, it allowed for more refined regressive networks to be adequately trained, leading to better insight into the true flow rates being observed. An important valuable deliverable of this research effort was the development of an advanced network which underwent multiple iterations capable of giving a continuous output. The current network has a predicted mean average percentage error (MAPE) of 12.3% just outside our target goal of 10.00%, but an accuracy of 97.78% at ±50 scfh, well within the overall goal for the Department of Energy (DOE) program. Upon closer inspection, it was observed that more than 10% of datapoints contributing to the MAPE predictions were the result of low flow rate predictions and are beyond the sensitivity of instrument measurement as a result of normal operational variation and noise.

03 NATURAL GAS↗
DOE OSTI2021

Smart Methane Emission Detection System Development (Final Report)

Working with the Department of Energy’s National Energy Technology Laboratory, Southwest Research Institute® (SwRI®) developed a system to identify methane leaks reliably, accurately, and autonomously at critical midstream sections of the natural gas distribution network in real- time for the purpose of mitigating methane emissions using Optical Gas Imaging (OGI) cameras. SwRI’s Smart Leak Detection – Methane (SLED/M) adds a high degree of automation to the process of methane leak detection to minimize sources of human error, minimize response time to a leak event, and maximize midstream visibility. Furthermore, SwRI has been working towards integrating Quantitative OGI (QOGI) capabilities into this existing technology. By leveraging Deep Learning, SwRI now has the capability to estimate fugitive emission leak rates quickly and reliably, which allows operators to detect emissions, quantify leak rate, prioritize repairs, and validate the repairs in a single instrument. The next generation QOGI technology leverages the same cameras used in Leak Detection and Repair (LDAR) programs, with improvements in safety and speed for traditional quantification-based repairs, ultimately leading to less overhead cost for the operators. The goals for this research were to develop two types of models with the following goals: 1. Run in real-time on the edge (≥ 12 Hz) 2. Classification: Achieve less than 5% false positive detection 3. Classification: Achieve ≥ 95% methane plume detection rate 4. Regression: achieve ≤ 10 standard cubic feet per hour (scfh) prediction > 70% of the time In order to achieve these results, multiple infrared (IR) and other sensors were investigated in tandem with the midwave IR (MWIR) OGI to provide additional information to train the underlying models. Information on atmospheric conditions including humidity, temperature, pressure, and solar radiation was provided by a weather station. Several machine learning and deep learning architectures and methods, including looking at quantized classification networks and regressions networks, were explored. As further data was collected, curated, and labeled, it allowed for more refined regressive networks to be adequately trained, leading to better insight into the true flow rates being observed. An important valuable deliverable of this research effort was the development of an advanced network which underwent multiple iterations capable of giving a continuous output. The current network has a predicted mean average percentage error (MAPE) of 12.3% just outside our target goal of 10.00%, but an accuracy of 97.78% at ±50 scfh, well within the overall goal for the Department of Energy (DOE) program. Upon closer inspection, it was observed that more than 10% of datapoints contributing to the MAPE predictions were the result of low flow rate predictions and are beyond the sensitivity of instrument measurement as a result of normal operational variation and noise.

03 NATURAL GAS↗
NASA NTRS2024

SOFIA/HAWC+ Far-Infrared Polarimetric Large-area CMZ Exploration Survey. III. Full Survey Data Set

We present the second data release (DR2) of the Far-InfraREd Polarimetric Large-Area CMZ Exploration (FIREPLACE) survey. This survey utilized the Stratospheric Observatory for Infrared Astronomy High-resolution Airborne Wideband Camera plus instrument at 214 μm (E band) at a resolution of 19"6 to observe thermal polarized dust emission throughout the Central Molecular Zone (CMZ). DR2 consists of observations obtained in 2022 covering the region of the CMZ extending from the Brick to the Sgr C molecular clouds (corresponding to a 1° × 0°.75 region of the sky). We combine DR2 with the first FIREPLACE data release (DR1) to obtain full coverage of the CMZ (a 1°.5 × 0°.75 region of the sky). After applying total and polarized intensity significance cuts on the full FIREPLACE data set, we obtain ∼64,000 Nyquist-sampled polarization pseudovectors. The distribution of polarization pseudovectors confirms a bimodal distribution in the CMZ magnetic field orientations, recovering field components that are oriented predominantly parallel or perpendicular to the Galactic plane. This distribution of orientations is similar to what was observed in DR1 and other studies. We also inspect the magnetic fields toward a set of prominent CMZ molecular clouds (the Brick, Three Little Pigs, 50 and 20 km s −1 clouds, circumnuclear disk, CO 0.02-0.02, and Sgr C), revealing spatially varying magnetic fields having orientations that generally trace the total intensity morphologies of the clouds. We find evidence that compression from stellar winds and shear from tidal forces are prominent mechanisms influencing the structure of the magnetic fields.

Molecular clouds↗
NASA NTRS2003

NASA Tech Briefs, June 2003

Topics covered include: Nulling Infrared Radiometer for Measuring Temperature; The Ames Power Monitoring System; Hot Films on Ceramic Substrates for Measuring Skin Friction; Probe Without Moving Parts Measures Flow Angle; Detecting Conductive Liquid Leaking from Nonconductive Pipe; Adaptive Suppression of Noise in Voice Communications; High-Performance Solid-State W-Band Power Amplifiers; Microbatteries for Combinatorial Studies of Conventional Lithium-Ion Batteries; Correcting for Beam Aberrations in a Beam-Waveguide Antenna; Advanced Rainbow Solar Photovoltaic Arrays; Metal Side Reflectors for Trapping Light in QWIPs; Software for Collaborative Engineering of Launch Rockets; Software Assists in Extensive Environmental Auditing; Software Supports Distributed Operations via the Internet; Software Estimates Costs of Testing Rocket Engines; yourSky: Custom Sky-Image Mosaics via the Internet; Software for Managing Inventory of Flight Hardware; Lower-Conductivity Thermal-Barrier Coatings; Process for Smoothing an Si Substrate after Etching of SiO2; Flexible Composite-Material Pressure Vessel; Treatment to Destroy Chlorohydrocarbon Liquids in the Ground; Noncircular Cross Sections Could Enhance Mixing in Sprays; Small, Untethered, Mobile Roots for Inspecting Gas Pipes; Paint-Overspray Catcher; Preparation of Regular Specimens for Atom Probes; Inverse Tomo-Lithography for Making Microscopic 3D Parts; Predicting and Preventing Incipient Flameout in Combustors; MEMS-Based Piezoelectric/Electrostatic Inchworm Actuator; Metallized Capillaries as Probes for Raman Spectroscopy; Adaptation of Mesoscale Weather Models to Local Forecasting; Aerodynamic Design using Neural Networks; Combining Multiple Gyroscope Outputs for Increased Accuracy; and Improved Collision-Detection Method for Robotic Manipulator.

Source record↗
NASA NTRS2013

NASA Tech Briefs, April 2013

Topics covered include: Fully Integrated, Miniature, High-Frequency Flow Probe Utilizing MEMS Leadless SOI Technology; Nanoscale Surface Plasmonics Sensor With Nanofluidic Control; Advanced Dispersed Fringe Sensing Algorithm for Coarse Phasing Segmented Mirror Telescopes; Neural Network Back-Propagation Algorithm for Sensing Hypergols; Bulk Moisture and Salinity Sensor; Change-Based Satellite Monitoring Using Broad Coverage and Targetable Sensing; Circularly Polarized Microwave Antenna Element with Very Low Off-Axis Cross-Polarization; Ultra-Low Heat-Leak, High-Temperature Superconducting Current Leads for Space Applications; Flash Cracking Reactor for Waste Plastic Processing; An Automated Safe-to-Mate (ASTM) Tester; Wireless Chalcogenide Nanoionic-Based Radio-Frequency Switch; Compute Element and Interface Box for the Hazard Detection System; DOT Transmit Module; Composite Aerogel Multifoil Protective Shielding; Li-Ion Electrolytes with Improved Safety and Tolerance to High-Voltage Systems; Polymer-Reinforced, Non-Brittle, Lightweight Cryogenic Insulation; Controlled, Site-Specific Functionalization of Carbon Nanotubes with Diazonium Salts; Regenerable Sorbent for CO2 Removal; Sprayable Aerogel Bead Compositions With High Shear Flow Resistance and High Thermal Insulation Value; Lexan Linear Shaped Charge Holder with Magnets and Backing Plate; Robotic Ankle for Omnidirectional Rock Anchors; Wind, Wave, and Tidal Energy Without Power Conditioning; An Active Heater Control Concept to Meet IXO Type Mirror Module Thermal-Structural Distortion Requirement; Waterless Clothes-Cleaning Machine; Integrated Electrical Wire Insulation Repair System; LVGEMS Time-of-Flight Mass Spectrometry on Satellites; Surface Inspection Tool for Optical Detection of Surface Defects; Per-Pixel, Dual-Counter Scheme for Optical Communications; Certification-Based Process Analysis; Surface Navigation Using Optimized Waypoints and Particle Swarm Optimization; Smart-Divert Powered Descent Guidance to Avoid the Backshell Landing Dispersion Ellipse; Estimating Foreign-Object-Debris Density from Photogrammetry Data; Adaptive Sampling of Spatiotemporal Phenomena with Optimization Criteria; Building a 2.5D Digital Elevation Model From 2D Imagery; Eyes on the Earth 3D; Target Trailing With Safe Navigation for Maritime Autonomous Surface Vehicles; Adams-Based Rover Terramechanics and Mobility Simulator - ARTEMIS; ISTP CDF Skeleton Editor; Uplink Summary Generator (ULSGEN) Version 1.0; Robotics On-Board Trainer (ROBoT); Software Engineering Tools for Scientific Models; Automatic Data Filter Customization Using a Genetic Algorithm; Tracker Toolkit; Towards Efficient Scientific Data Management Using Cloud Storage; On a Formal Tool for Reasoning About Flight Software Cost Analysis; A Nanostructured Composites Thermal Switch Controls Internal and External Short Circuit in Lithium Ion Batteries; Spacecraft Crew Cabin Condensation Control; and Functional Near-Infrared Spectroscopy Signals Measure Neuronal Activity in the Cortex.

Source record↗
NASA NTRS2022

An Overview of Contamination Control for the James Webb Space Telescope Launch Campaign

The James Webb Space Telescope (JWST) is a large, infrared space telescope operating at Lagrange point 2. JWST is a joint effort between NASA, ESA, and CSA and was launched from the Centre Spatial Guyanais (CSG) on an Ariane 5 rocket in December 2021. The three-month launch campaign utilized enhanced contamination controls to meet JWST’s strict cleanliness requirements. Prior to launch, JWST was permitted to only be exposed to ISO Class 7 cleanrooms, whereas the processing facilities at CSG are ISO Class 8. NASA, ESA, Arianespace, and CNES implemented temporary upgrades to the nominal contamination control operations for the launch campaign unique to JWST, including the use of vetted, portable High Efficiency Particulate Air (HEPA) filter walls, pre-entrance cleanliness acceptance surveys of each facility and the intra-plant transporter, tightened cleanroom protocols, upgraded garmenting and laundering techniques, cleaning of Self-Contained Atmospheric Protection Ensemble (SCAPE) suits, increased maintenance, staffed pre-cleaning stations, adaptation of the house purge network, and a contamination control enclosure atop the Ariane 5 launcher prior to fairing encapsulation. The Ariane 5 fairing interior and Vehicle Equipment Bay membrane also received multiple cleanings, detailed inspections, and verification sampling to achieve necessary cleanliness levels. The fairing itself was specially sealed to protect the inner environment with just a small, door porthole accessible via diving board for final closeout of the purge interface. All of these enhancements together allowed JWST to meet its contamination requirements for launch, ensuring successful post-separation deployments and mission science.

Contamination Control↗
NASA NTRSDate not supplied

Overview of Contamination Control for the James Webb Space Telescope Launch Campaign

The James Webb Space Telescope (JWST) is a large, infrared space telescope operating at Lagrange point 2. JWST is a joint effort between NASA, ESA, and CSA and was launched from the Centre Spatial Guyanais (CSG) on an Ariane 5 rocket in December 2021. The three-month launch campaign utilized enhanced contamination controls to meet JWST’s strict cleanliness requirements. Prior to launch, JWST was permitted to only be exposed to ISO Class 7 cleanrooms, whereas the processing facilities at CSG are ISO Class 8. NASA, ESA, Arianespace, and CNES implemented temporary upgrades to the nominal contamination control operations for the launch campaign unique to JWST, including the use of vetted, portable High Efficiency Particulate Air (HEPA) filter walls, pre-entrance cleanliness acceptance surveys of each facility and the intra-plant transporter, tightened cleanroom protocols, upgraded garmenting and laundering techniques, cleaning of Self-Contained Atmospheric Protection Ensemble (SCAPE) suits, increased maintenance, staffed pre-cleaning stations, adaptation of the house purge network, and a contamination control enclosure atop the Ariane 5 launcher prior to fairing encapsulation. The Ariane 5 fairing interior and Vehicle Equipment Bay membrane also received multiple cleanings, detailed inspections, and verification sampling to achieve necessary cleanliness levels. The fairing itself was specially sealed to protect the inner environment with just a small, doored porthole accessible via diving board for final closeout of the purge interface. All these enhancements together allowed JWST to meet its contamination requirements for launch, ensuring successful post-separation deployments and mission science.

James Webb Space Telescope↗
NASA NTRS2022

Overview of Contamination Control for the James Webb Space Telescope Launch Campaign

The James Webb Space Telescope (JWST) is a large, infrared space telescope operating at Lagrange point 2. JWST is a joint effort between NASA, ESA, and CSA and was launched from the Centre Spatial Guyanais (CSG) on an Ariane 5 rocket in December 2021. The three-month launch campaign utilized enhanced contamination controls to meet JWST’s strict cleanliness requirements. Prior to launch, JWST was permitted to only be exposed to ISO Class 7 cleanrooms, whereas the processing facilities at CSG are ISO Class 8. NASA, ESA, Arianespace, and CNES implemented temporary upgrades to the nominal contamination control operations for the launch campaign unique to JWST, including the use of vetted, portable High Efficiency Particulate Air (HEPA) filter walls, pre-entrance cleanliness acceptance surveys of each facility and the intra-plant transporter, tightened cleanroom protocols, upgraded garmenting and laundering techniques, cleaning of Self-Contained Atmospheric Protection Ensemble (SCAPE) suits, increased maintenance, staffed pre-cleaning stations, adaptation of the house purge network, and a contamination control enclosure atop the Ariane 5 launcher prior to fairing encapsulation. The Ariane 5 fairing interior and Vehicle Equipment Bay membrane also received multiple cleanings, detailed inspections, and verification sampling to achieve necessary cleanliness levels. The fairing itself was specially sealed to protect the inner environment with just a small, doored porthole accessible via diving board for final closeout of the purge interface. All these enhancements together allowed JWST to meet its contamination requirements for launch, ensuring successful post-separation deployments and mission science.

James Webb Space Telescope, launch, contamination,↗
NASA NTRS2010

Handheld White Light Interferometer for Measuring Defect Depth in Windows

Accurate quantification of defects (scratches and impacts) is vital to the certification of flight hardware and other critical components. The amount of damage to a particular component contributes to the performance, reliability, and safety of a system, which ultimately affects the success or failure of a mission or test. The launch-commit criteria on a Space Shuttle Orbiter window are governed by the depth of the defects that are identified by a visual inspection. This measurement of a defect is not easy to obtain given the environment, size of the defect, and location of the window(s). The determination of depth has typically been performed by taking a mold impression and measuring the impression with an optical profiling instrument. Another method of obtaining an estimate of the depth is by using a refocus microscope. To use a refocus microscope, the surface of the glass and bottom of the defect are, in turn, brought into focus by the operator. The amount of movement between the two points corresponds to the depth of the defect. The refocus microscope requires a skilled operator and has been proven to be unreliable when used on Orbiter windows. White light interferometry was chosen as a candidate to replace the refocus microscope. The White Light Interferometer (WLI) was developed to replace the refocus microscope as the instrument used for measuring the depth of defects in Orbiter windows. The WLI consists of a broadband illumination source, interferometer, detector, motion control, displacement sensor, mechanical housing, and support electronics. The illumination source for the WLI is typically a visible light emitting diode (LED) or a near-infrared superluminescent diode (SLD) with power levels of less than a milliwatt. The interferometer is a Michelson configuration consisting of a 1-in. (2.5-cm) cube beam splitter, a 0.5-in. (1.3-cm) optical window as a movable leg (used to closely match the return intensity of the fixed leg from the window), and a mirrored prism to fold the optics into the mechanical housing. The detector may be one of many C-mount CCD (charge-coupled device) cameras. Motion is provided by a commercial nanostepping motor with a serial interface. The displacement sensor is a custom device specifically designed for this application. The mechanical housing and support electronics were designed to integrate the various components into an instrument that could be physically handled by a technician and easily transported.

Youngquist, Robert↗
NASA NTRS1996

Second International Airborne Remote Sensing Conference and Exhibition

The conference provided four days of displays and scientific presentations on applications, technology, a science of sub-orbital data gathering and analysis. The twelve displayed aircraft equipped with sophisticated instrumentation represented a wide range of environmental and reconnaissance missions,including marine pollution control, fire detection, Open Skies Treaty verification, thermal mapping, hydrographical measurements, military research, ecological and agricultural observations, geophysical research, atmospheric and meterological observations, and aerial photography. The U.S. Air Force and the On-Site Inspection Agency displayed the new Open Skies Treaty verification Boeing OC 135B that promotes international monitoring of military forces and activities. SRl's Jetstream uses foliage and ground penetrating SAR for forest inventories, toxic waste delineation, and concealed target and buried unexploded ordnance detection. Earth Search Sciences's Gulfstream 1 with prototype miniaturized airborne hyperspectral imaging equipment specializes in accurate mineral differentiation, low-cost hydrocarbon exploration, and nonproliferation applications. John E. Chance and the U.S. Army Corps of Engineers displayed the Bell 2 helicopter with SHOALS that performs hydrographic surveying of navigation projects, coastal environment assessment, and nautical charting surveys. Bechtel Nevada and U.S. DOE displayed both the Beech King AIR B-200 platform equipped to provide first response to nuclear accidents and routine environmental surveillance, and the MBB BO-105 helicopter used in spectral analysis for environmental assessment and military appraisal. NASA Ames Research Center's high-altitude Lockheed ER-2 assists in earth resources monitoring research in atmospheric chemistry, oceanography, and electronic sensors; ozone and greenhouse studies and satellite calibration and data validation. Ames also showcased the Learjet 24 Airborne Observatory that completed missions in Venus cloud cover analysis, Quadantid meteor shower studies, extra-solar far infrared ionic structure lines measurement, Cape Kennedy launch support, and studies in air pollution, The Products and Services Exhibit showcased new sensor and image processing technologies, aircraft data collection services, unmanned vehicle technology, platform equipment, turn-key services, software a workstations, GPS services, publications, and processing and integration systems by 58 exhibitors. The participation of aircraft users and crews provided unique dialogue between those who plan data collection a operate the remote sensing technology, and those who supply the data processing and integration equipment. Research results using hyperspectral imagery, radar and optical sensors, lidar, digital aerial photography, a integrated systems were presented. Major research and development programs and campaigns we reviewed, including CNR's LARA Project and European Space Agency's 1991-1995 Airborne Campaign. The pre-conference short courses addressed airborne video, photogrammetry, hyperspectral data analysis, digital orthophotography, imagery and GIS integration, IFSAR, GPS, and spectrometer calibration.

Source record↗
DOE OSTI2026

Strong Lens Discoveries in DESI Legacy Imaging Surveys DR10 with Two Deep Learning Architectures

Abstract We have conducted a search for strong gravitational lensing systems in the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 10 (DR10). This paper is the fourth in a series of searches. This is the first catalog of lens candidates covering nearly the entirety of the extragalactic sky south of declination δ ≈ +32 ∘ , all observed by DECam, covering ∼14,000 deg 2 . We impose a z -band magnitude cut of <20 in AB magnitude. We deploy a residual neural network and EfficientNet as an ensemble trained on a compilation of known lensing systems and high-grade candidates as well as nonlenses in the same footprint. The predictions from these two base models are aggregated using a meta-learner. After applying our ensemble to the survey data, we exclude known candidates and systems, and use our own visual inspection portal to rank images in the top 0.01 percentile of all neural network recommendations. We have found 811 lens candidates, five of which are confirmed through Euclid Quick Data Release (Q1). These include 484 new candidates in the Legacy Surveys DR9 footprint, all parts of which have been searched for strong lenses at least once before, either by our group or others. Combining the discoveries from this work with those from the first three papers in this series (335, 1210, and 1512), we have discovered a total of 3868 new candidates in the DESI Legacy Surveys.

Inchausti, Jose Carlos [University of San Francisc↗
DOE OSTI2025

Unsupervised Image-Based Classification of Corrosion Severity in Automobile Engine Connecting Rods

Corrosion in engine connecting rods is a critical issue in the automotive industry, potentially leading to catastrophic engine failure, monetary losses, and safety hazards. The labor shortage in the industry further emphasizes the need for fast, accurate, and automated corrosion detection methods to ensure appropriate surface treatments can be applied to restore component integrity. We present an unsupervised image-based framework for classifying corrosion severity in automobile engine connecting rods using short-wave infrared (SWIR) and telecentric grayscale imaging. We employ the structural similarity index measure (SSIM) as a dissimilarity metric and the k-medians clustering algorithm for classification. Our algorithm achieves an overall accuracy of 80.64% for SWIR images, with 100% accuracy in classifying highly corroded samples. For grayscale images, the method attains an overall accuracy of 77.42%, with 90.91% accuracy for highly corroded samples. The method’s ability to work with different imaging modalities and its high accuracy in identifying severe corrosion cases make it a promising tool for automated corrosion assessment in the automotive industry, potentially improving efficiency and safety in engine component maintenance.

42 ENGINEERING↗
NASA NTRS2012

NASA Tech Briefs, May 2012

Topics covered include: An "Inefficient Fin" Non-Dimensional Parameter to Measure Gas Temperatures Efficiently; On-Wafer Measurement of a Multi-Stage MMIC Amplifier with 10 dB of Gain at 475 GHz; Software to Control and Monitor Gas Streams; Miniaturized Laser Heterodyne Radiometer (LHR) for Measurements of Greenhouse Gases in the Atmospheric Column; Anomaly Detection in Test Equipment via Sliding Mode Observers; Absolute Position of Targets Measured Through a Chamber Window Using Lidar Metrology Systems; Goldstone Solar System Radar Waveform Generator; Fast and Adaptive Lossless Onboard Hyperspectral Data Compression System; Iridium Interfacial Stack - IrIS; Downsampling Photodetector Array with Windowing; Optical Phase Recovery and Locking in a PPM Laser Communication Link; High-Speed Edge-Detecting Line Scan Smart Camera; Optical Communications Channel Combiner; Development of Thermal Infrared Sensor to Supplement Operational Land Imager; Amplitude-Stabilized Oscillator for a Capacitance-Probe Electrometer; Automated Performance Characterization of DSN System Frequency Stability Using Spacecraft Tracking Data; Histogrammatic Method for Determining Relative Abundance of Input Gas Pulse; Predictive Sea State Estimation for Automated Ride Control and Handling - PSSEARCH; LEGION: Lightweight Expandable Group of Independently Operating Nodes; Real-Time Projection to Verify Plan Success During Execution; Automated Performance Characterization of DSN System Frequency Stability Using Spacecraft Tracking Data; Web-Based Customizable Viewer for Mars Network Overflight Opportunities; Fabrication of a Cryogenic Terahertz Emitter for Bolometer Focal Plane Calibrations; Fabrication of an Absorber-Coupled MKID Detector; Graphene Transparent Conductive Electrodes for Next- Generation Microshutter Arrays; Method of Bonding Optical Elements with Near-Zero Displacement; Free-Mass and Interface Configurations of Hammering Mechanisms; Wavefront Compensation Segmented Mirror Sensing and Control; Long-Life, Lightweight, Multi-Roller Traction Drives for Planetary Vehicle Surface Exploration; Reliable Optical Pump Architecture for Highly Coherent Lasers Used in Space Metrology Applications; Electrochemical Ultracapacitors Using Graphitic Nanostacks; Improved Whole-Blood-Staining Device; Monitoring Location and Angular Orientation of a Pill; Molecular Technique to Reduce PCR Bias for Deeper Understanding of Microbial Diversity; Laser Ablation Electrodynamic Ion Funnel for In Situ Mass Spectrometry on Mars; High-Altitude MMIC Sounding Radiometer for the Global Hawk Unmanned Aerial Vehicle; PRTs and Their Bonding for Long-Duration, Extreme-Temperature Environments; Mid- and Long-IR Broadband Quantum Well Photodetector; 3D Display Using Conjugated Multiband Bandpass Filters; Real-Time, Non-Intrusive Detection of Liquid Nitrogen in Liquid Oxygen at High Pressure and High Flow; Method to Enhance the Operation of an Optical Inspection Instrument Using Spatial Light Modulators; Dual-Compartment Inflatable Suitlock; Large-Strain Transparent Magnetoactive Polymer Nanocomposites; Thermodynamic Vent System for an On-Orbit Cryogenic Reaction Control Engine; Time Distribution Using SpaceWire in the SCaN Testbed on ISS; and Techniques for Solution- Assisted Optical Contacting.

Source record↗
DOE OSTI2019

Structural and optical properties of Sm{sup 3+}-doped borate glasses for luminescent applications

In this work, most interesting optical investigations are carried out with the glass composition (20 − x) CdCO{sub 3} + 15 Li{sub 2}CO{sub 3} + 15 Na{sub 2}CO{sub 3} + 50 H{sub 3}BO{sub 3} + xSm{sub 2}O{sub 3} (where x = 0.1, 0.5, 1.0, 3.0, 4.0 and 5.0 mol%) prepared with conservative melt-quenching technique. DSC verifies the annealing temperature and thermal stability of the prepared glass. X-ray diffraction technique is employed to inspect the amorphous structure of the glasses. FTIR technique helps to view the vibrational band positions of the host material. For optical studies, optical absorption and emission measurements are used. From the absorption spectra, Judd–Ofelt (JO) parameters (Ω{sub 2}, Ω{sub 4}, Ω{sub 6}), rms value of oscillator strength (δ{sub rms}), nephelauxetic parameter ( β-bar ), bonding parameter (δ) and optical band gaps are evaluated. Radiative properties such as radiative transition probabilities (A{sub T}), branching ratios (β{sub cal}, β{sub exp}) and stimulated emission cross section (σ{sub emi}) are calculated using JO theory. The higher stimulated emission cross section (14.39 × 10{sup −22} cm{sup 2}), optical gain (36.69 × 10{sup −25} cm{sup 2} s) indicate that 1.0 mol% of Sm{sup 3+}-doped borate glass would be a potential gain medium for solid state laser application at 603 nm. Color coordinates of the glasses located in the reddish-orange region could be useful for white light-emitting application.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Relating Aerial Infrared Thermography Defects to Photovoltaic Performance: Preprint

In this research, we examine the relationship between aerial IR defect analysis and photovoltaic (PV) performance data for twelve utility- and commercial-scale solar sites in the United States. To do this, we fuse the site diagram geoJSON's, aerial infrared thermography (aIRT) defect analyses, and associated inverter time series, allowing for a direct comparison between site defects and time series data. Defect analyses were provided by Zeitview, under its Solar Insights platform. Following the data fusion process, we look at the relationship between system performance and aIRT defects. We investigate the relationship between degradation and hotspot defects, as well as the relationship between AC power data and offline strings and misaligned modules. In general, system degradation was not affected by long-term or balance-of-system (BoS) defects as they occurred infrequently in the data set. However, for one system, a near statistically significant relationship (p-value=0.057) was found when comparing the degradation of inverter blocks with several multi-hotspot defects to all other inverter blocks without this particular defect. There was strong alignment when comparing short-term recoverable module defects such as stuck trackers and offline strings to time series data. In general, we found that when an inverter block has more than 80% of modules flagged for one of these defects, its AC power time data is flat-lined and the inverter block is not producing.

aerial inspection↗
DOE OSTI2021

Predicting Nugget Size of Resistance Spot Welds Using Infrared Thermal Videos With Image Segmentation and Convolutional Neural Network

Resistance spot welding (RSW) is a widely adopted joining technique in automotive industry. Recent advancement in sensing technology makes it possible to collect thermal videos of the weld nugget during RSW using an infrared (IR) camera. The effective and timely analysis of such thermal videos has the potential of enabling in situ nondestructive evaluation (NDE) of the weld nugget by predicting nugget thickness and diameter. Deep learning (DL) has demonstrated to be effective in analyzing imaging data in many applications. However, the thermal videos in RSW present unique data-level challenges that compromise the effectiveness of most pre-trained DL models. We propose a novel image segmentation method for handling the RSW thermal videos to improve the prediction performance of DL models in RSW. The proposed method transforms raw thermal videos into spatial-temporal instances in four steps: video-wise normalization, removal of uninformative images, watershed segmentation, and spatial-temporal instance construction. The extracted spatial-temporal instances serve as the input data for training a DL-based NDE model. The proposed method is able to extract high-quality data with spatial-temporal correlations in the thermal videos, while being robust to the impact of unknown surface emissivity. Overall, our case studies demonstrate that the proposed method achieves better prediction of nugget thickness and diameter than predicting without the transformation.

42 ENGINEERING↗
DOE OSTI2025

The R -Process Alliance: Exploring the cosmic scatter among ten r -process sites with stellar abundances

Context. The astrophysical origin of the rapid neutron-capture process (r-process), responsible for producing roughly half of the elements heavier than iron, remains uncertain. Detailed chemical signatures from the oldest, most metal-poor stars, which act as fossil records of the earliest nucleosynthesis events, can be used to identify the dominant r-process sites. Aims. We present a homogeneous chemical abundance analysis of ten r-process element-enhanced stars. These old and metal-poor stars are strongly enriched in r-process elements with minimal contamination from other nucleosynthetic sources. By focusing on this chemically pure sample, we aim to investigate intrinsic variations in the r-process abundance patterns and explore their implications for the nature and potential diversity of r-process sites. Methods. We performed a detailed chemical abundance analysis of high-resolution, high-signal-to-noise spectra. For each star, we inspected over 1400 individual absorption lines using a combination of equivalent width measurements and spectral synthesis. The analysis was conducted under the assumption of 1D local thermodynamic equilibrium and employing the MOOG radiative transfer code. Results. We derived abundances for 54 chemical species, including 29 neutron-capture (n-capture) elements, covering the full mass range of the r-process abundance pattern. A kinematic analysis reveals that stars likely originated from ten kinematically distinct systems. Based on this assumption, we used the sample to probe the maximum variation expected from ten independent r-process nucleosynthesis events and computed the intrinsic dispersion of each element relative to Zr and Eu for the light and heavy r-process elements, respectively. This exercise resulted in a remarkably low cosmic scatter across the ten r-process sites enriching these stars; for the rare earth and third peak elements, for example, we find σ [La/Eu] = 0.08 and σ [Os/Eu] = 0.11 dex, while the scatter between light and heavy elements, σ [Zr/Eu] , is slightly higher at 0.18 dex. Conclusions. The elemental abundance patterns across the ten independent r-process sites show remarkably small cosmic dispersions. This minimal dispersion suggests a high degree of uniformity in r-process yields across diverse astrophysical environments.

Astronomy and AstroPhysics↗