Search NASA⌕ Search

SEARCH · Search NASA

Results for “INFRARED IMAGES”

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.

At least 55 records · Page 3

Effect of threshold parameters on infrared segmentation methods for porosity detection in electron beam powder bed fusion

In-situ process monitoring has seen significant interest in additive manufacturing to address qualification and certification goals. This is especially prevalent in metal powder bed fusion processes such as electron beam powder bed fusion (PBF-EB), with layer-wise infrared imaging being commonly used to detect defects. Here, this work compares two different segmentation methods (static thresholding and statistical thresholding) used for detecting porosity from in-situ infrared imaging data for PBF-EB. Samples were manufactured at a variety of focus offset values to induce porosity. Then, the segmented infrared images were compared to ex-situ X-ray computed tomography scans, which served as a ground-truth reference for objective evaluation. Through this analysis framework, the influential parameters, static threshold and N-value (number of standard deviations above the mean pixel value), respectively, for both image segmentation methods were analyzed and compared for their effects on porosity detection. With optimal parameter settings, the two methods had similar porosity detection performance, but the statistical method performed better under a larger variety of parameter settings.

Infrared imaging↗

Designing an Observing System to Study the Surface Biology and Geology (SBG) of the Earth in the 2020s

Abstract Observations of planet Earth from space are a critical resource for science and society. Satellite measurements represent very large investments and United States (US) agencies organize their effort to maximize the return on that investment. The US National Research Council conducts a survey of Earth science and applications to prioritize observations for the coming decade. The most recent survey prioritized a visible to shortwave infrared imaging spectrometer and a multispectral thermal infrared imager to meet a range of needs for studying Surface Biology and Geology (SBG). SBG will be the premier integrated observatory for observing the emerging impacts of climate change by characterizing the diversity of plant life and resolving chemical and physiological signatures. It will address wildfire risk, behavior, and recovery as well as responses to hazards such as oil spills, toxic minerals in minelands, harmful algal blooms, landslides, and other geological hazards. The SBG team analyzed needed instrument characteristics (spatial, temporal, and spectral resolutions, measurement uncertainty) and assessed the cost, mass, power, volume, and risk of different architectures. We present an overview of the Research and Applications trade‐study analysis of algorithms, calibration and validation needs, and societal applications with specifics of substudies detailed in other articles in this special collection. We provide a value framework to converge from hundreds down to three candidate architectures recommended for development. The analysis identified valuable opportunities for international collaboration to increase the revisit frequency, adding value for all partners, leading to a clear measurement strategy for an observing system architecture.

54 ENVIRONMENTAL SCIENCES↗

Siena Galaxy Atlas 2020

Abstract We present the 2020 version of the Siena Galaxy Atlas (SGA-2020), a multiwavelength optical and infrared imaging atlas of 383,620 nearby galaxies. The SGA-2020 uses optical grz imaging over ≈20,000 deg 2 from the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 9 and infrared imaging in four bands (spanning 3.4–22 μ m) from the 6 year unWISE coadds; it is more than 95% complete for galaxies larger than R (26) ≈ 25″ and r < 18 measured at the 26 mag arcsec −2 isophote in the r band. The atlas delivers precise coordinates, multiwavelength mosaics, azimuthally averaged optical surface-brightness profiles, model images and photometry, and additional ancillary metadata for the full sample. Coupled with existing and forthcoming optical spectroscopy from the DESI, the SGA-2020 will facilitate new detailed studies of the star formation and mass assembly histories of nearby galaxies; enable precise measurements of the local velocity field via the Tully–Fisher and fundamental plane relations; serve as a reference sample of lasting legacy value for time-domain and multimessenger astronomical events; and more.

79 ASTRONOMY AND ASTROPHYSICS↗

Detection of Foreign Materials on Broiler Breast Meat Using a Fusion of Visible Near-Infrared and Short-Wave Infrared Hyperspectral Imaging

Foreign material (FM) found on a poultry product lowers the quality and safety of the product. We developed a fusion method combining two hyperspectral imaging (HSI) modalities in the visible-near infrared (VNIR) range of 400–1000 nm and the short-wave infrared (SWIR) range of 1000–2500 nm for the detection of FMs on the surface of fresh raw broiler breast fillets. Thirty different types of FMs that could be commonly found in poultry processing plants were used as samples and prepared in two different sizes (5 × 5 mm 2 and 2 × 2 mm 2 ). The accuracies of the developed Fusion model for detecting 2 × 2 mm 2 pieces of polymer, wood, and metal were 95%, 95%, and 81%, respectively, while the detection accuracies of the Fusion model for detecting 5 × 5 mm 2 pieces of polymer, wood, and metal were all 100%. The performance of the Fusion model was higher than the VNIR- and SWIR-based detection models by 18% and 5%, respectively, when F1 scores were compared, and by 38% and 5%, when average detection rates were compared. The study results suggested that the fusion of two HSI modalities could detect FMs more effectively than a single HSI modality.

36 MATERIALS SCIENCE↗

Biomimetic tissue phantoms for neurosurgical near-infrared fluorescence imaging

Neurosurgical fluorescence imaging is a well-established clinical approach with a growing range of indications for use. However, this technology lacks effective phantom-based tools for development, performance testing, and clinician training. Our primary aim was to develop and evaluate 3D-printed phantoms capable of optically and morphologically simulating neurovasculature under fluorescence angiography. Volumetric digital maps of the circle of Willis with basilar and posterior communicator artery aneurysms, along with surrounding cerebral tissue, were generated. Phantoms were fabricated with a stereolithography printer using custom photopolymer composites, then visualized under white light and near-infrared fluorescence imaging. Feature sizes of printed components were found to be within 13% of digital models. Phantoms exhibited realistic optical properties and convincingly recapitulated fluorescence angiography scenes. Methods identified in this study can facilitate the development of realistic phantoms as powerful new tools for fluorescence imaging.

3D modeling↗

Multiscale Characterization of Photovoltaic Modules—Case Studies of Contact and Interconnect Degradation

The current popularity of photovoltaic (PV) systems is due in large part to their exceptional reliability and significantly lower cost than other energy sources. Studying cell and module degradation is key to promote further development in the state of the art. Fielded or accelerated aged modules exhibit different failure modes, of which metallization degradation (contacts and interconnections) is prevalent. In this work, we discuss how multiscale characterization methods can be applied to a variety of module technologies that have been field exposed and have undergone accelerated age testing. These methods include performing characterization on the module level, cell level, and finally the materials level. The observed performance losses from the module- and cell-level characterization can be correlated with materials properties to find out the root cause of degradation. We recommend an initial nondestructive characterization suite, including module- and cell-level current-voltage ( I--V ), Suns-V OC , photoluminescence and electroluminescence imaging, quantum efficiency, ultraviolet fluorescence imaging, and thermal infrared imaging. Samples are then extracted from particularly degraded regions of the module and prepared for materials characterization techniques, such as top-down and cross-sectional scanning electron microscopy, energy-dispersive X-ray spectroscopy, X-ray photoelectron spectroscopy, secondary ion mass spectrometry, Raman spectroscopy, and transmission electron microscopy, allowing a deeper look into the mechanism behind the metallization degradation. This article serves as an instructional review to introduce the different multiscale characterization methods and how they can be effectively applied to perform PV degradation studies. Furthermore, we also share some of our examples and discuss the strengths, limitations, and best practices for each of the characterization techniques.

14 SOLAR ENERGY↗

An experimental and one-dimensional modeling analysis of turbulent gas ejection in pre-chamber engines

In this work, experimental results from a study on the evolution of gas jets ejected through the orifices of a pre-chamber in a heavy-duty optical engine are presented. The work examines conditions without fuel inside the main-chamber, which helps to describe the dynamics of the ejected gas jets without the interference of subsequent combustion in the main-chamber. Experimental diagnostics consist of high-speed visible intensified imaging and low-speed infrared imaging. Additionally a one-dimensional gas jet model is used to characterize the spatial distribution of the ejected flow, including parameters such as tip penetration, which are then validated based on experimental results. Different stages in the ejection of pre-chamber jets are identified, with chemical activity restricted to a maximum distance of 5 to 10 orifice diameters downstream of the orifice as indicated by the recorded visible radiation. Sensitivity of cycle-to-cycle variations in pre-chamber jet development to the air-to-fuel ratio in the pre-chamber observed in the experiments is in most part attributed to the variations in the timing of combustion initiation in the pre-chamber. The influence of the ejection flow on the penetration of the gas jet on a cycle-to-cycle basis is presented using the one-dimensional model. The one-dimensional model also indicates that the local flow exhibits highest sensitivity to operating conditions during the start of ejection until the timing when maximum flow is attained. Differences that exist during the decreasing mass-flow ejection time-period tend to smear out in part due to the transient slowdown of the ejection process.

1-D gas jet model↗

Subaru/HSC deep optical imaging of infrared sources in the AKARI North Ecliptic Pole-Wide field

In this work, we present a five-broad-band (grizy) photometric catalogue of Subaru/Hyper Suprime-Cam (HSC) optical imaging observations at around the North Ecliptic Pole (NEP) where the AKARI infrared (IR) satellite conducted a large survey (NEP-Wide survey). The observations cover almost all the NEP-Wide survey field down to the depth of 28.1, 26.8, 26.3, 25.5, and 25.0 mag (5σ) at grizy, respectively. The five-band HSC catalogue contains about 2.6 million objects, and 70 959 AKARI NEP-Wide counterpart sources are identified in the catalogue. We added existing supplementary catalogues from the u band to the far-IR band, and estimated photo-z for the AKARI-HSC sources. We achieved σΔz/(1 + zs) = 0.06 and an outlier rate of 13.4 per cent at z = 0.2–1.5. Using the spectral energy distribution (SED) template fitting, we classified the AKARI-HSC galaxies into four categories, namely quiescent, star-forming, Type1 active galactic nucleus (AGN), and Type2 AGN, in each redshift bin. Then, at z > 1, the mean SED of star-forming galaxies in mid-IR (3–10 μm) range is significantly different from that of spiral galaxies in the nearby Universe, indicating that many of star-forming galaxies at z > 1 contain a heat source capable of heating dust to temperatures that radiate thermal emission in the mid-IR range. Furthermore, we estimated the number fraction of AGNs (fAGN) in each bin of redshift and IR luminosity (L IR ), and examined the dependence of redshift and L IR . In log(L IR /L ⊙ ) = 11.0–14.0, the fAGN shows a significant increase with increasing redshift, regardless of the LIR bins. In contrast, the fAGN shows a slight increase against L IR at z < 1 and no increase with increasing L IR at z > 1.

79 ASTRONOMY AND ASTROPHYSICS↗

Demonstration of Non-linear Optical Spectroscopy Enhancement utilizing Entangled Photons

Laser-based nonlinear optical spectroscopy approaches have enabled the direct sensing of important chemistry in nearly every fundamental or applied field of science. Yet in many applications, increased detectivity is needed to unravel fundamental mechanisms. One possibility is the use of quantum entanglement to increase detection cross-sections, but it is unproven that enhancement from quantum light extends to practical intensities for chemical sensing. In this report, we investigated the creation and use of entangled photons in nonlinear optical mixing for second harmonic generation and infrared imaging. We observe that the linear scaling of nonlinear mixing from entangled photon sources extends to the mW laser power regime, and enhances direct infrared imaging on Si-based charge coupled device cameras. These results motivate future experimentation on practical uses of entangled photons for nonlinear optical sensing applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Application of reference-free natural background–oriented schlieren photography for visualizing leakage sites in building walls

Air leakage in buildings can cause health and comfort concerns for occupants and can contribute to mold growth on building materials, or in extreme conditions, rot of building materials. Unwanted air leakage through the building envelope also contributes to approximately 4 quadrillion Btu (1172 TWh) of energy consumption per year in the building sector in the United States. Locating and sealing leakage sites can improve the energy efficiency, comfort, air quality, and moisture durability of the building stock. Typical methods of finding leakage sites, such as infrared imaging and smoke tracing, rely on concurrent blower door operation, which can also measure the total leakage rate of the building. Smoke tracing can be disruptive to occupants, and infrared imaging and smoke tracing cannot measure the contribution of individual leaks to prioritize sealing efforts. Here, an optical fluid flow imaging technique, reference-free natural background–oriented schlieren imaging, was adapted to visualize air exfiltration. This is the first step in developing a method to noninvasively locate and measure exfiltration or infiltration sites so that sealing efforts can be prioritized. Experimental results of this technique are presented, demonstrating the method's applicability to visualizing exfiltration through three common building claddings in an outdoor environment. Key variables impacting the performance of this technique when applied to building leakage are also discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Near-field infrared microscopy: A novel analytic mapping technique to nanocharacterize calcium silicate-based cement materials

Infrared imaging via scattering-type scanning near-field optical microscopy (s-SNOM) allows chemical mapping of organic and inorganic materials with nanoscale spatial resolution. However, its potential adaptation to the complex multiphase structure of Portland cement is yet to be explored. Here we demonstrate the successful implementation of s-SNOM to spatially resolve coexisting chemical phases in tricalcium silicate, Portland cement's main compound, with 20-nm resolution. We found that s-SNOM is sensitive to different anhydrous polymorphic phases, revealing nanoscale domains that are ‘invisible’ to other microscopic techniques. Furthermore, s-SNOM's ability to distinguish the unhydrated and hydrated phases signifies its great promise as an analytical tool to study the complex hydration process of cement. The key to s-SNOM's application was nano-modifying the surface roughness of the cement samples, allowing nanoscale infrared imaging without topographical artifacts. Our study opens a window for infrared spectral microscopy in cement and other porous inorganic materials.

36 MATERIALS SCIENCE↗

Diffractive Imaging of Conical Intersections Amplified by Resonant Infrared Fields

The fate of virtually all photochemical reactions is determined by conical intersections. These are energetically degenerate regions of molecular potential energy surfaces that strongly couple electronic states, thereby enabling fast relaxation channels. Their direct spectroscopic detection relies on weak features that are often buried beneath stronger, less interesting contributions. For azobenzene photoisomerization, a textbook photochemical reaction, we demonstrate how a resonant infrared field can be employed during the conical intersection passage to significantly enhance its coherence signatures in time-resolved Xray diffraction while leaving the product yield intact. Furthermore, this transition-state amplification holds promise to bring signals of conical intersections above the detection threshold.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Stellar Content of H72.97-69.39, a Potential Super Star Cluster in the Making

Young massive clusters and super star clusters (SSCs) represent an extreme mode of star formation. Far-infrared imaging of the Magellanic Clouds has identified one potential embedded SSC, HSO BMHERICC J72.971176-69.391112 (H72.97-69.39 in short), in the southwest outskirts of the Large Magellanic Cloud. We present Gemini Flamingos 2 and GSAOI near-infrared imaging of a 3′ × 3′ region around H72.97-69.39 in order to characterize the stellar content of the cluster. The stellar content is probed down to 1.5 M {sub ⊙}. We find substantial dust extinction across the cluster region, extending up to A {sub K} of 3. Deeply embedded stars are associated with ALMA-detected molecular gas suggesting that star formation is ongoing. The high spatial resolution of the GSAOI data allows identification of the central massive object associated with the {sup 13}CO ALMA observations and detection of fainter low-mass stars around the H30α ALMA source. The morphology of the molecular gas and the nebulosity from adjacent star formation suggest they have interacted covering a region of several parsecs. The total stellar content in the cluster is estimated from the intermediate- and high-mass stellar content to be at least 10,000 M {sub ⊙}, less than R136 with up to 100,000 M {sub ⊙} within 4.7 pc radius, but places it in the regime of an SSC. Based on the extinction determination of individual stars we estimate a molecular gas mass in the vicinity of H72.97-69.39 of 6600 M {sub ⊙}, suggesting more star formation can be expected.

74 ATOMIC AND MOLECULAR PHYSICS↗

Maps of growing season gross primary production and net ecosystem exchange for Council Road Mile Marker 71, Seward Peninsula, Alaska, [2017-2023]

This data archive is in support of the Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) publication "Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape", by Murphy et al. (2025a). Murphy et al. (2025a) evaluated whether incorporating observed Arctic vegetation heterogeneity into ELM, the land model of the Department of Energy’s Energy Exascale Earth System Model (E3SM), improved simulations of tundra carbon cycling. The associated model archive can be found at Murphy et al. (2025b). The study focused on the spatial patterns and net landscape-level growing season productivity and carbon uptake. As part of this evaluation, observationally derived maps of average growing season (June–August) net ecosystem exchange (NEE) and gross primary production (GPP) were developed for the same domain. These maps, which form the dataset described here, integrate eddy covariance flux tower, remote sensing, and vegetation community data to provide spatially explicit benchmarks for model evaluation. The maps provide spatially explicit estimates of average growing season NEE and GPP across 13 tundra vegetation communities within the study domain. By combining flux tower observations with Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) hyperspectral imagery and drone-based normalized difference vegetation index (NDVI), these maps capture the heterogeneity of carbon fluxes associated with different Arctic vegetation types. While they represent average seasonal conditions rather than interannual variability, the maps provide a unique dataset for evaluating model performance, comparing vegetation community contributions to landscape-scale carbon cycling, and supporting regional analyses of Arctic carbon dynamics. This data archive contains 5 m resolution maps of vegetation communities, vegetation community average growing season GPP, and vegetation community average growing season NEE (three *.tif files), a User’s Guide (*pdf file), and Table 1 of the User’s Guide displaying vegetation community coverage and average growing season NEE and GPP values (*.csv file).

Murphy, Bailey [ORNL] (ORCID:0000000203995221)↗

Pulsed Infrared Thermography Nondestructive Imaging of SiC-SiC f Composite Cladding Architectures; Understanding the Performance of SiC-SiC f Composite Cladding Architectures with Cr Coating in Normal Operating and Accident Conditions in LWRs and Advanced Reactors

SiC-SiC f composites, consisting of silicon carbide fibers embedded in a silicon carbide matrix, are advanced materials with high thermal conductivity, temperature stability, and resistance to radiation damage. Traditional methods for quality control of fabricated SiC-SiC f composites involve nondestructive evaluation (NDE) with X-ray computed tomography (XCT). However, XCT imaging of typical SiC-SiC f structures for cladding applications can involve several hours. In this project, we investigate an alternative approach to NDE of SiC-SiC f composites that involves rapid (on the order of seconds) imaging with Pulsed infrared thermography (PIT). PIT images of a planar SiC-SiC f specimen show the structure of the surface monolith layer and internal SiC f structures. The capability of PIT imaging in visualizing SiC f structures is qualitatively confirmed by observing similarity in the PIT and X-ray transmission images of the same specimen. Computer vision analysis of defects in the PIT image of the monolith was performed with thresholding followed by topological structural analysis that computed geometric descriptors, including major/minor axes of fitted ellipses, area, perimeter, Feret diameter, circularity, roundness, and solidity.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Euclid I. Overview of the Euclid mission

The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015–2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14 000 deg 2 of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance.

cosmology↗