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At least 1,135 records · Page 63

A Simulated Fire Edge Vis-IR Detection and Tracking Approach for Autonomous sUAS in STEReO

This study presents a fire edge detection and tracking methodology for an autonomous small UAS (sUAS). The sUAS, onboard sensors, and wildfire are simulated to evaluate the methodology. A visible light (Vis) camera and an infrared (IR) camera are simulated onboard the sUAS to identify burnt, burning, and unburnt areas on a static wildfire bitmap. After differentiating between these areas, a form of nonlinear guidance law (NLGL) is used to generate virtual target points (VTP) that guide the sUAS so that the fire edge is kept within the camera FOV. The VTP are passed to the sUAS flight management system (FMS) in the form of waypoints. The approach was tested in simulation and demonstrated tracking curved, sharp, and linear fire edge shapes at different altitudes. Higher altitude tracking proved to demand the least control effort without sacrificing continuous tracking.

Autonomous UAV↗

Origins Survey Spectrometer: revealing the hearts of distant galaxies and forming planetary systems with far-IR spectroscopy

The Origins Survey Spectrometer (OSS) is a multi-purpose far-IR spectrograph for Origins. Operating at the photon background limit, OSS covers the 25- to 588-μm wavelength range instantaneously at a resolving power (R) of 300 using six logarithmically spaced grating modules. Each module couples at least 30 and up to 100 spatial beams simultaneously, enabling true [three-dimensional (3D)] spectral mapping. In addition, OSS provides two high-resolution modes. The first inserts a long-path Fourier-transform spectrometer (FTS) into a portion of the incoming light in advance of the grating backends, enabling R up to 43,000 × [λ/112 μm] , while preserving the grating-based sensitivity for line detection. The second incorporates a scanning etalon in series with the FTS to provide R up to 300,000 for the 100-to 200-μm range.

Charles M. Bradford↗

Delta Method Application for the Correlation of IR Detector Thermal Parasitic Loads with Statistically Accurate Results

The Linear Etalon Imaging Spectral Array (LEISA) is a cryogenic IR detector that is passively cooled below 110K. LEISA is part of the L’Ralph instrument, which is going on the Lucy mission, with planned flyby’s of the Trojan asteroids around 5.5 AU. One of the primary thermal challenges is to successfully quantify each significant parasitic heat flow value with statistical certainty.Simulation of flight-like thermal environments and correlation of thermal models is an important part of this challenge, which can be critical for thermally sensitive systems such as cryogenic detectors that are passively cooled. It is common practice during TVAC to achieve several thermal balance points and then to correlate several design variables in order to achieve the closest match to all balance points tested. This approach lends itself to high levels of uncertainty in the correlated values due to the cumulative effect of absolute temperature uncertainty and differences between the sensors used for the measurement. Accuracy can be improved with the use of more accurate sensors, by calibrating all sensors with respect to each other, and by using Zero-Q methodologies, all of which add cost and complexity to the test.The Delta Method uses the difference in temperature caused by the changes in the boundary conditions to calculate heat flows and/or thermal resistances across temperature differentials. This eliminates the problem of high uncertainties with absolute temperature measurements, and yields statistically accurate results down to the sensor resolution of 1mK at < 100K, by taking the sensor’s calibration errors out of the equation. During testing, this method relies on parametric variations around an initial balance point, by varying the boundary conditions of the different parasitic heat sources. The Delta Method, as well as its application on the LEISA thermal test, will be discussed in detail.

Daniel G. Bae↗

On the Nature of AGN and Star Formation Enhancement in thez=3.1 SSA22Protocluster: The HST WFC3 IR View

We examine possible environmental sources of the enhanced star formation and active galactic nucleus (AGN) activity in the z=3.09 SSA22 protocluster using Hubble WFC3 F160W (∼1.6μm) observations of the SSA22 field, including new observations centered on eight X-ray selected protocluster AGN. To investigate the role of mergers in the observed AGN and star formation enhancement, we apply both quantitative (Sérsic-fit and Gini–M20)and visual morphological classifications to F160W images of protocluster Lyman-break galaxies (LBGs) in the fields of the X-ray AGN and z∼3field LBGs in SSA22 and GOODS-N. We find no statistically significant differences between the morphologies and merger fractions of protocluster and field LBGs, though we are limited by small number statistics in the protocluster. We also fit the UV-to-near-IR spectral energy distributions of F160W-detected protocluster and field LBGs to characterize their stellar masses and star formation histories. We find that the mean protocluster LBG is a factor of∼2 times more massive and more attenuated than the mean z∼3field LBG. We take our results to suggest that ongoing mergers are not more common among protocluster LBGs than field LBGs, though protocluster LBGs appear to be more massive. We speculate that the larger mass of the protocluster LBGs contributes to the enhancement of SMBH mass and accretion rate in the protocluster, which in turn drives the observed protocluster AGN enhancement

Erik B. Monson↗

Correlating the Seasonal Behavior of Polar Warming and O2 IR Nightglow

Mars’ meridional circulation impacts the climate through the transport of heat, water, dust, and trace gases. The meridional circulation in the middle atmosphere is instrumental in the exchange of water between hemispheres and the expansion phase of large regional- and global-scale dust storms. The overall nature and structure of the mean meridional circulation (i.e., the Hadley cell) in the Martian atmosphere has been widely studied but the detailed behavior is still being investigated. To provide a more detailed examination of the meridional circulation, two features driven by the mean circulation will be analyzed as proxies. The first feature is polar warming (PW), which is dynamically induced due to the compressional heating of air in the descending branch of the Hadley cell. The second feature is O2 IR nightglow emission in the 1.27 micron band, which is the result of a three-body recombination (O+O+CO2-> O2*+CO2) and is largely dependent on the transport of dayside produced chemistry. By characterizing their seasonal sensitivities due to known lower atmosphere circulation drivers and correlating them, we will advance our knowledge of the meridional circulation.

A. S. Brecht↗

All-sky Retrieval of Atmospheric Temperature, Water Vapor, Clouds, Trace Gases, and Surface Properties from Operational Hyperspectral IR Sounders

Operational IR sounders such AIRS, CrIS, and IASI provide high quality hyperspectral measurements for weather and climate applications. We will describe a new all-sky Single Field-of-view Sounder Atmospheric Product (SiFSAP). The uniqueness of this product is that it uses all available channels from hyperspectral sounders and the optimal estimation retrieval is done at a single FOV spatial resolution. The SiFSAP includes atmospheric temperature, water vapor, clouds, trace gases, surface skin, and surface emissivity and will be produced operationally at NASA GES DISC. We will describe the core component of the SiFSAP algorithm, which is the Principal Component-based Radiative Transfer Model (PCRTM), and will show example applications of the SiFSAP product for various atmospheric weather and dynamics studies. We also describe a new Climate Fingerprinting Sounder Product (ClimFiSP), which is derived from spatiotemporally averaged level-1 hyperspectral radiances directly. The ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides fast and accurate data fusion products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. The ClimFiSP are being transitioned to NASA data centers for routine generations level-3 products.

pcrtm↗

NuSTAR Observations of Four Mid-IR-Selected Dual AGN Candidates in Galaxy Mergers

Mergers of galaxies are a ubiquitous phenomenon in the universe and represent a natural consequence of the “bottom-up” mass accumulation and galaxy evolution cosmological paradigm. It is generally accepted that the peak of active galactic nucleus (AGN) accretion activity occurs at nuclear separations of ≲10 kpc for major mergers. Here we present new NuSTAR and XMM-Newton observations for a subsample of mid-IR preselected dual AGN candidates in an effort to better constrain the column densities along the line of sight (LOS) for each system. Only one dual AGN candidate, J0841+0101, is detected as a single, unresolved source in the XMMNewton and NuSTAR imaging, while the remaining three dual AGN candidates, J0122+0100, J1221+1137, and J1306+0735, are not detected with NuSTAR; if these nondetections are due to obscuration alone, these systems are consistent with being absorbed by column densities of log ( N H /cm −2 ) ≽ 24.9, 24.6, and 24.3, which are roughly consistent with previously inferred column densities in these merging systems. In the case of J0841+0101, the analysis of the 0.3–30 keV spectra reveal an LOS column density of N H ≳ 10 24 cm −2 , significantly larger than the column densities previously reported for this system and demonstrating the importance of the higher signal-to-noise ratio XMM-Newton spectra and access to the >10 keV energies via NuSTAR. Though it is unclear if J0841+0101 truly hosts a dual AGN, these results are in agreement with the high obscuring columns expected in AGNs in late-stage mergers.

AGN host galaxies↗

Creating IR-verified Gridded Fire Burn Maps using Public NASA and Satellite Data

Even though fire can be devastating, wildland fire is a natural and integral force on our landscapes, providing value by decreasing fuels at the Wildland Urban Interface (WUI) to promote safe communities. However, uncontained wildfires can devastate communities, threaten our health, and result in substantial economic losses. There has been greater than a $50B increase in wildfire insurance claims from 2017-2021, which has been exacerbated by climate change. Our partners at Kettle reinsurance are focused on building a smarter reinsurance model for protecting today’s globalized world from the catastrophic effects of climate change. Our objective is to develop a high-confidence grid-based wildfire burn product using multiple sources of satellite data to determine whether a ‘conflagration' (fire larger than 999+ acres) has ‘breached’ a grid cell. This product will substantially decrease the time it takes for homeowners to receive payouts, from over a year to a couple months. Working with our partners at Kettle reinsurance, we use VIIRS (Visible Infrared Imaging Radiometer Suite) 375 m fire detections and Sentinel-2 10 m satellite imagery to create a 20-m gridded fire burn product. Our process is based on the level of confidence in the data source and takes into account vegetation change throughout the life of the fire. For example, Sentinel-2 vegetation-change indices have a higher level of confidence when congruent with VIIRS active-fire detection data, rather than VIIRS detections alone. We have also verified our fire burn product against MODIS/ASTER Airborne Simulator (MASTER) Infrared (IR) data from the Fire Influence on Regional to Global Environments Experiment - Air Quality (FIREX-AQ) 2019 campaign, with 88% overall agreement. The first iteration has been developed for responding to wildfires in California, with the possibility to expand nationwide and globally.

Emily Gargulinski↗

Status and Progress of All-Sky Hyperspectral IR Radiance Assimilation in GEOS

The majority of hyperspectral infrared radiance observations that peak in the lower and mid-troposphere have been excluded from the assimilation in the operational GEOS by the cloud detection scheme. The significance and challenges of assimilating these cloud-affected observations have attracted the attention of the research community, encouraged by the progress in utilizing all-sky microwave radiances affected by clouds and precipitation in many data assimilation systems, including GEOS. While the Global Modeling and Assimilation Office (GMAO) has made significant progress on the assimilation of cloud-cleared infrared radiances, this parallel study marks the first effort to directly assimilate cloud-affected hyperspectral infrared radiances in the GEOS. This initial study is focused on CrIS-FSR wa:wqter-vapor channels. The capability of the GEOS model and CRTM in simulating infrared radiances affected by clouds has been evaluated, and the all-sky brightness temperature Jacobians with respect to temperature, specific humidity, and hydrometeors are examined closely in varying cloud conditions. With hydrometeor control variables in the GEOS, several important aspects of all-sky IR radiance assimilation are investigated. The symmetric cloud effects are assessed for their robustness when used as the cloud proxy in observation error modeling that incorporates the inter-channel correlations with error situation dependency on the amount of cloud. The effective radius, bias correction and quality control processes will also be adapted to accommodate modifications necessary for all-sky infrared assimilation before comprehensive four-dimensional ensemble-variational(4dEnVar) experiments are conducted to assess their impacts on the analysis and forecast performance of GEOS.

Wei Gu↗

UVO to Far-IR Mirror Technology Development: Year 2 Status

UVO to Far-IR (UVO-FIR) mirror technology development project is a multiyear effort initiated in Fiscal Year (FY) 2022 to mature the Technology Readiness Level (TRL) of critical technologies required to enable ultra-stable telescope of the Habitable Worlds Observatory (HWO) mission. 2023/24 accomplishments include: continued investigations into gravity sag by comparing rotation test vs flip test, quantifying gravity sag as a function of temperature and designing mount for mirror whose G-sag with elevation angle is only coma. Significant progress in developing a methodology for specify optical surface microstructure, contamination cleanliness level and allowable micrometeoroid impacts. Support of HWO. And, a parametric cost model for x-ray telescopes and a parametric volume cost model for normal incidence telescopes.

H. Philip Stahl↗

A Spectral Fingerprinting Method for Deriving Consistent Climate Data Records from Multiple Satellite IR Sounders

Deriving Climate Data Records (CDRs) from multiple IR sounders such AIRS on Aqua, CrIS on S-NPP, NOAA20 and JPSS-2, IASI on Metop A, B, and C requires from current operational products are challenging due to different radiative transfer models and retireavl algorithms used for processing level 2 data. We developed a Climate Fingerprinting Sounder Product (ClimFiSP) algorithm, which uses a single set of radiative kernels a robust spectral fingerprinting method to performs retrievals using spatiotemporally averaged L1 hyperspectral radiances directly. The ClimFiSP algorithm provides accurate data fusion CDR products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. We plan to add IASI to the CDR data set in the future. The ClimFiSP is being transitioned to NASA GES DISC data center for public access.

Xu Liu↗

Retrieve Methane from IR sounder measurements Using Machine Learning-Enhanced Physical Inversion

The sensitivity of IR sounder measurements to atmospheric CH 4 is often limited due to interferences from signals of other trace gases, insufficient thermal contrast, and cloud blockage. In order to resolve the geographical and vertical distribution of atmospheric CH 4 profiles, accurate scene-dependent a priori information is critically needed to support an optimal estimation method-based physical inversion scheme. Following the principles of indexing, representation, and retrieval, a spectral fingerprinting methodology is developed to address the needs for both accuracy and computational efficiency in sounder-based CH 4 retrieval. Within this framework, a clustering method based on machine learning is first employed to stratify and identify the a priori state within the pre-constructed database, using optimized spectral radiances as predictors. The corresponding radiative kernel is then used to establish the physical inversion scheme for finding the solution. High-quality data from CH 4 data assimilation systems like the Carbon-Tracker and the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis, as well as the state-of-art sounder products are used to build the training database, including radiative kernels. We will demonstrate the results retrieved from CrIS observations and the associated validation work.

Wan Wu↗

Complementary Roles of LEO and GEO IR Sounders in NWP Evaluated using an OSSE Framework

The United States is currently preparing for the next-generation weather satellite program. Building off the multi-decadal successes of the Low-Earth Orbit (LEO) infrared (IR) sounder program, NOAA and NASA are planning for the Geostationary eXtended Observations (GeoXO) Sounder (GXS) that will join international counterparts to form a global ring from geosynchronous orbit (GEO). To address questions about the complementarities and roles of these two platform types in the context of numerical weather prediction (NWP) and forecast accuracy, NASA’s Global Modeling and Assimilation Office (GMAO) Observing System Simulation Experiment (OSSE) framework was used to test their impact individually and in concert. Analyses, forecasts, and forecast sensitivity-based observations impact (FSOI) are examined. Overall, each has a role in forecast error reduction with the most beneficial impacts occurring when both LEO and GEO sounders are used together to address the needs of global skill and targeted regional weather phenomena.

Erica Mcgrath-Spangler↗

Carbon nanotube IR detectors (SV)

Sandia National Laboratories (Sandia) and Lockheed Martin Corporation (LMC) collaborated to (1) evaluate the potential of carbon nanotubes as channels in infrared (IR) photodetectors; (2) assemble and characterize carbon nanotube electronic devices and measure the photocurrent generated when exposed to infrared light;(3) compare the performance of the carbon nanotube devices with that of traditional devices; and (4) develop and numerically implement models of electronic transport and opto-electronic behavior of carbon nanotube infrared detectors. This work established a new paradigm for photodetectors.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Effect of Field Errors in Muon Collider IR Magnets on Beam Dynamics

In order to achieve peak luminosity of a Muon Collider (MC) in the 10{sup 35} cm{sup -2}s{sup -1} range very small values of beta-function at the interaction point (IP) are necessary ({beta}* {le} 1 cm) while the distance from IP to the first quadrupole can not be made shorter than {approx}6 m as dictated by the necessity of detector protection from backgrounds. In the result the beta-function at the final focus quadrupoles can reach 100 km making beam dynamics very sensitive to all kind of errors. In the present report we consider the effects on momentum acceptance and dynamic aperture of multipole field errors in the body of IR dipoles as well as of fringe-fields in both dipoles and quadrupoles in the ase of 1.5 TeV (c.o.m.) MC. Analysis shows these effects to be strong but correctable with dedicated multipole correctors.

43 PARTICLE ACCELERATORS↗

Phase-matched generation of coherent soft and hard X-rays using IR lasers

Phase-matched high-order harmonic generation of soft and hard X-rays is accomplished using infrared driving lasers in a high-pressure non-linear medium. The pressure of the non-linear medium is increased to multi-atmospheres and a mid-IR (or higher) laser device provides the driving pulse. Based on this scaling, also a general method for global optimization of the flux of phase-matched high-order harmonic generation at a desired wavelength is designed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Fuel Cell Manufacturing Diagnostic Techniques: IR Thermography with Reactive Flow through Excitation

While design and material considerations for PEMFCs have a large impact on cost, it is also necessary to consider a transition to high volume production of fuel cell systems, including MEA components, to enable economies of scale and reduce per unit cost. One of the critical manufacturing tasks is developing and deploying techniques to provide in‐process measurement of fuel cell components for quality control. This effort requires a subsidiary task: The study of the effect of manufacturing defects on performance and durability with the objective to establish validated manufacturing tolerances for fuel cell components. This work focuses on the development of a potential quality control method for gas diffusion electrodes (GDEs). The method consists of infrared (IR) thermography combined with reactive flow through (RFT) excitation. Detection of catalyst loading reduction defects in GDE catalyst layers will be presented.

30 DIRECT ENERGY CONVERSION↗

IR Spot Weld Inspect

In automotive industry, destructive inspection of spot welds is still the mandatory quality assurance method due to the lack of efficient non-destructive evaluation (NDE) tools. However, it is costly and time-consuming. Recently at ORNL, a new NDE prototype system for spot weld inspection using infrared (IR) thermography has been developed to address this problem. This software contains all the key functions that ensure the NDE system to work properly: system input/output control, image acquisition, data analysis, weld quality database generation and weld quality prediction, etc.

Chen, Jian↗