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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

An Icy Kuiper Belt Around the Young Solar-type Star HD 181327

Context. HD 181327 is a young main sequence F5/F6 V star belonging to the Beta Pictoris moving group (age approx.. 12 Myr). It harbors an optically thin belt of circumstellar material at radius approx.. 90 AU, presumed to result from collisions in a population of unseen planetesimals. Aims. We aim to study the dust properties in the belt in details, and to constrain the gas-to-dust ratio. Methods. We obtained far-infrared photometric observations of HD 181327 with the PACS instrument onboard the Herschel Space Observatory, complemented by new 3.2 mm observations carried with the ATCA array. The geometry of the belt is constrained with newly reduced HST/NICMOS scattered light images that allow the degeneracy between the disk geometry and the dust properties to be broken. We then use the radiative transfer code GRaTeR to compute a large grid of models, and we identify the grain models that best reproduce the spectral energy distribution (SED) through a Bayesian analysis. We attempt to detect the oxygen and ionized carbon fine-structure lines with Herschel/PACS spectroscopy, providing observables to our photochemical code ProDiMo. Results. The HST observations confirm that the dust is confined in a narrow belt. The continuum is detected with Herschel/PACS completing nicely the SED in the far-infrared. The disk is marginally resolved with both PACS and ATCA. A medium integration of the gas spectral lines only provides upper limits on the [OI] and [CII] line fluxes.We show that the HD 181327 dust disk consists of micron-sized grains of porous amorphous silicates and carbonaceous material surrounded by an important layer of ice, for a total dust mass of approx.. 0.05 Solar Mass (in grains up to 1 mm). We discuss evidences that the grains consists of fluffy aggregates. The upper limits on the gas atomic lines do not provide unambiguous constraints: only if the PAH abundance is high, the gas mass must be lower than approx. 17 Solar Mass. Conclusions. Despite the weak constraints on the gas disk, the age of HD 181327 and the properties of the dust disk suggest that it has passed the stage of gaseous planets formation. The dust reveals a population of icy planetesimals, similar to the primitive Edgeworth-Kuiper belt, that may be a source for the future delivery of water and volatiles onto forming terrestrial planets.

HD 181327↗
NASA NTRS2013

Simultaneous Laser Ranging and Communication from an Earth-Based Satellite Laser Ranging Station to the Lunar Reconnaissance Orbiter in Lunar Orbit

We report a free space laser communication experiment from the satellite laser ranging (SLR) station at NASA Goddard Space Flight Center (GSFC) to the Lunar Reconnaissance Orbiter (LRO) in lunar orbit through the on board one-way Laser Ranging (LR) receiver. Pseudo random data and sample image files were transmitted to LRO using a 4096-ary pulse position modulation (PPM) signal format. Reed-Solomon forward error correction codes were used to achieve error free data transmission at a moderate coding overhead rate. The signal fading due to the atmosphere effect was measured and the coding gain could be estimated.

fee-space optical communication↗
NASA NTRS2016

Multi-Sensor Cloud and Aerosol Retrieval Simulator and Remote Sensing from Model Parameters : Aerosols - Part 2

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a simulated radiance product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers. This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled. In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model sub grid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to operational remote-sensing algorithms. Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (MOYD04). TheMOYD04 product is of course normally produced from MOYD021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a MOYD021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source. We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

aerosol retrieval↗
NASA NTRS2020

Watershed Modeling with Remotely Sensed Big Data: MODIS Leaf Area Index Improves Hydrology and Water Quality Predictions

Traditional watershed modeling often overlooks the role of vegetation dynamics. There is also little quantitative evidence to suggest that increased physical realism of vegetation dynamics in process-based models improves hydrology and water quality predictions simultaneously. In this study, we applied a modified Soil and Water Assessment Tool (SWAT) to quantify the extent of improvements that the assimilation of remotely sensed Leaf Area Index (LAI) would convey to streamflow, soil moisture, and nitrate load simulations across a 16,860 km2 agricultural watershedin the midwestern United States. We modified the SWAT source code to automatically override the model’s built-in semiempirical LAI with spatially distributed and temporally continuous estimates from Moderate Resolution Imaging Spectroradiometer (MODIS). Compared to a “basic” traditional model with limited spatial information, our LAI assimilation model (i) significantly improved daily streamflow simulations during medium-to-low flow conditions, (ii) provided realistic spatial distributions of growing season soil moisture, and (iii) substantially reproduced the long-term observed variability of daily nitrate loads. Further analysis revealed that the overestimation or underestimation of LAI imparted a proportional cascading effect on how the model partitions hydrologic fluxes and nutrient pools. As such, assimilation of MODIS LAI data corrected the model’sLAI overestimation tendency, which led to a proportionally increased rootzone soil moisture and decreased plant nitrogen uptake. With these new findings, our study fills the existing knowledge gap regarding vegetation dynamics in watershed modeling and confirms that assimilation of MODIS LAI data in watershed models can effectively improve both hydrology and water quality predictions.

Adnan Rajib↗
DOE OSTI2025

Enhancing Cluster Identification in Atom Probe Tomography Data Using Transfer Learning

Atom Probe Tomography (APT) is a powerful technique for visualizing the atomic-scale distribution of solutes in materials, but quantitative cluster analysis of APT datasets remains a challenge due to the need for subjective parameter selection in clustering algorithms. While distance-based and density-based methods such as HDBSCAN are widely used, their performance is highly sensitive to user-defined parameters, which undermines reproducibility and accuracy. This study proposes an image-based, deep learning-aided workflow for automating parameter selection and cluster detection in APT data analysis. By projecting 3D APT point clouds onto 2D planes, we leverage pretrained convolutional neural networks (ConvNeXt-Tiny and ResNet-50) through transfer learning to predict the number of clusters present in synthetic datasets. The output is used to guide K-means clustering and estimate HDBSCAN parameters, specifically minimum cluster size and minimum sample points. This approach reduces reliance on manual parameter tuning, improving consistency and scalability. The methodology demonstrates the feasibility of using image-based deep learning for interpreting complex spatial patterns in APT data, enabling faster and more objective analysis. The complete workflow and code are made publicly available to support reproducibility and future research.

Density-based clustering↗
NASA NTRS2018

PIV and Rotational Raman-Based Temperature Measurements for CFD Validation in a Single Injector Cooling Flow

Film cooling is used in a wide variety of engineering applications for protection of surfaces from hot or combusting gases. The design of more efficient thin film cooling geometries/configurations could be facilitated by an ability to accurately model and predict the effectiveness of current designs using computational fluid dynamics (CFD) code predictions. Hence, a benchmark set of flow field property data were obtained for use in assessing current CFD capabilities and for development of better turbulence models. Both Particle Image Velocimetry (PIV) and spontaneous rotational Raman scattering (SRS) spectroscopy were used to acquire high quality, spatially-resolved measurements of the mean velocity, turbulence intensity and also the mean temperature and normalized root mean square (rms) temperatures in a single injector cooling flow arrangement. In addition to flowfield measurements, thermocouple measurements on the plate surface enabled estimates of the film effectiveness. Raman spectra in air were obtained across a matrix of radial and axial locations downstream from a 68.07 mm square nozzle blowing heated air over a range of temperatures and Mach numbers, across a 30.48 cm long plate equipped with a single injector cooling hole. In addition, both centerline streamwise 2-component PIV and cross-stream 3-component Stereo PIV data at 15 axial stations were collected in the same flows. The velocity and temperature data were then compared against Wind-US CFD code predictions for the same flow conditions. The results of this and planned follow-on studies will support NASA's development and assessment of turbulence models for heated flows.

Raman Scattering↗
NASA NTRS1977

Some aspects of adaptive transform coding of multispectral data

This paper concerns a data compression study pertaining to multi-spectral scanner (MSS) data. The motivation for this undertaking is the need for securing data compression of images obtained in connection with the Landsat Follow-On Mission, where a compression of at least 6:1 is required. The MSS data used in this study consisted of four scenes: Tristate, consisting of 256 pels per row and a total of 512 rows - i.e., (256x512), (2) Sacramento (256x512), (3) Portland (256x512), and (4) Bald Knob (200x256). All these scenes were on digital tape at 6 bits/pel. The corresponding reconstructed scenes of 1 bit/pel (i.e., a 6:1 compression) are included.

Ahmed, N.↗
DOE OSTI2024

Bulk reconstruction and non-isometry in the backwards-forwards holographic black hole map

The backwards-forwards map, introduced as a generalization of the non-isometric holographic maps of the black hole interior of Akers, Engelhardt, Harlow, Penington, and Vardhan to include non-trivial dynamics in the effective description, has two possible formulations differing in when the post-selection is performed. While these two forms are equivalent on the set of dynamically generated states — states formed from unitary time evolution acting on well-defined initial configurations of infalling matter — they differ on the generic set of states necessary to describe the apparent world of the infalling observer. We show that while both versions successfully reproduce the Page curve, the version involving post-selection as the final step, dubbed the backwards-forwards-post-selection (BFP) map, has the desirable properties of being non-isometric but isometric on average and providing state-dependent reconstruction of bulk operators, while the other version does not. Thus the BFP map is a suitable non-isometric code describing the black hole interior including interior interactions.

3-D Image Reconstruction↗
NASA NTRS2017

A Fast Hybrid (3-D/1-D) Model for Thermal Radiative Transfer in Cirrus via Successive Orders of Scattering

We investigate the impact of cirrus cloud heterogeneity on the direct emission by cloud or surface and on the scattering by ice particles in the thermal infrared (TIR). Realistic 3-D cirri are modeled with the 3DCLOUD code, and top-of-atmosphere radiances are simulated by the 3-D Monte Carlo radiative transfer (RT) algorithm 3DMCPOL for two (8.65 micrometers and 12.05 micrometers) channels of the Imaging Infrared Radiometer on CALIPSO. At nadir, comparisons of 1-D and 3-D RT show that 3-D radiances are larger than their 1-D counterparts for direct emission but smaller for scattered radiation. For our cirrus cases, 99% of the 3-D total radiance is computed by the third scattering order, which corresponds to 90% of the total computational effort, but larger optical thicknesses need more scattering orders. To radically accelerate the 3-D RT computations (using only few percent of 3-D RT time with a Monte Carlo code), even in the presence of large optical depths, we develop a hybrid model based on exact 3-D direct emission, the first scattering order from 1-D in each homogenized column, and an empirical adjustment linearly dependent on the optical thickness to account for higher scattering orders. Good agreement is found between the hybrid model and the exact 3-D radiances for two very different cirrus models without changing the empirical parameters. We anticipate that a future deterministic implementation of the hybrid model will be fast enough to process multiangle thermal imagery in a practical tomographic reconstruction of 3-D cirrus fields.

radiative transfer↗
NASA NTRS1998

Hard X-ray Observation of Cygnus X-1 By the Marshall Imaging X-ray Experiment (MIXE2)

The second generation of the Marshall Imaging X-ray Experiment (MIXE2) was flown from Fort Sumner, New Mexico on May 7-8, 1997. The experiment consists of coded-aperture telescope with a field of view of 1.8 degrees (FWHM) and an angular resolution of 6.9 arcminutes. The detector is a large (7.84x10(exp 4) sq cm) effective area microstrip proportional counter filled with 2.0x10(exp5) Pascals of xenon with 2% isobutylene. We present MIXE2 observation of the 20-80keV spectrum and timing variability of Cygnus X-1 made during balloon flight.

Minamitani, Takahisa↗
NASA NTRS2017

Suppression of Hydrogen Emission in an X-Class White-Light Solar Flare

We present unique NUV observations of a well-observed X-class flare from NOAA 12087 obtained at the Ondrejov Observatory. The flare shows a strong white-light continuum but no detectable emission in the higher Balmer and Lyman lines. Reuven Ramaty High-Energy Solar Spectroscopic Imager and Fermi observations indicate an extremely hard X-ray spectrum and gamma-ray emission. We use the RADYN radiative hydrodynamic code to perform two types of simulations: one where an energy of 3 x 10(exp 11) erg/sq cm/s is deposited by an electron beam with a spectral index of approx. = 3, and a second where the same energy is applied directly to the photosphere. The combination of observations and simulations allows us to conclude that the white-light emission and the suppression or complete lack of hydrogen emission lines is best explained by a model where the dominant energy deposition layer is located in the lower layers of the solar atmosphere, rather than the chromosphere.

Prochazka, Ondrej↗
NASA NTRS2019

Vicarious Calibration of GOCI for the SeaDAS Ocean Color Retrieval

A key on-orbit calibration step for satellite remote sensing of ocean color is the vicarious calibration. This establishes the final gains for each spectral band on the sensor that minimize bias in the retrieved ocean color signal. The vicarious calibration is specific to the instrument and the atmospheric correction algorithm. The vicarious calibration gains for the Geostationary Ocean Color Imager (GOCI) are presented here, which were derived to optimize the performance ofNASA's standard atmospheric correction algorithm as implemented in the l2gen code and distributed through the SeaDAS open-source software package. Following NASA's protocols, the near-infrared(NIR) bands were calibrated first, and the visible bands were then calibrated relative to this fixed NIR calibration. The gain for the 745-nm NIR band was derived using a fixed aerosol model, which waschosen based on the Angstrom Coefficients derived from MODIS onAqua (MODISA). For the vicarious gains of the visible bands, twosources for the target water-leaving radiances were tested: matchupsfrom MODISA and climatological data from SeaWiFS. A validation analysis using AERONET-OC data shows an improvement in sensor performance when compared with results using the current vicarious gains and results using no vicarious calibration. Good agreement was found in vicarious gains derived using both concurrent MODISA and climatological SeaWiFS as vicarious calibration data sources. These results support the use of a concurrent sensor for the vicarious calibration when in situ data are not available and demonstrate that using climatology from a well-calibrated sensor like SeaWiFSfor the vicarious calibration is a valid alternative when it is not possible to use a concurrent sensor or in situ data. We recommend using the gains derived from concurrent GOCI matchups with MODISA for GOCI processing in SeaDAS/l2gen.

Concha, Javier↗
NASA NTRS2024

LED Intensity Decay Particle Tracking Velocimetry

A particle tracking velocimetry (PTV) system is demonstrated that eliminates the need for expensive lasers and cameras, and encodes the particle tracks with a known intensity variation which allows for high-resolution particle velocity and directionality determination. Using a light-emitting diode (LED) as the light source significantly reduces cost and allows for eye-safe operation, in comparison to traditional laser systems. The intensity variation control is passive, being dictated by the capacitance discharge rate in the LED pulsing circuit. The decay rate can be adjusted with the LED circuit capacitors/resistors, while the duration of the decay can be adjusted with the LED trigger pulse width. Because the intensity decay illumination is controlled by the LED, a single long exposure camera image is used to acquire images of the particle streaks, and there is no need for a more complicated and costly double-pulsing camera. With the intensity coding of the light, a single-camera/ single-LED system can identify particles entering of leaving the illumination plane, but cannot discern the direction toward or away from the camera. By using a two-color system, three-dimensionality of the particle tracks can be determined.

Joshua M Weisberger↗
DOE OSTI2024

Beyond Binary: Automated PLC Memory Forensics through RGB Image Analysis and Deep Learning

The introduction of Industry 4.0 and the evolution of industrial control systems (ICS) to adopt Internet-based technologies enhanced productivity, but have inadvertently increased their vulnerability to cyber-based malicious attacks. When an ICS system is compromised, security analysts need to identify the root cause quickly to start the recovery process and develop mitigation strategies to safeguard against future instances. Memory forensics is critical in the analysis process to ascertain what occurred. To date, approaches to analyze the persistent memory in ICS devices are limited, and almost nonexistent for volatile memory. This paper proposes an automated methodology, COMA, for PLC memory dump analysis using computer vision and deep learning techniques. Specifically, COMA converts the sequences of bytes in a PLC memory dump to RGB pixels and creates a deep learning model that learns the underlying patterns and features of pre-labeled forensic artifacts in images and segments them into distinct regions. COMA then uses the trained model to automatically segment new memory images and extract forensic artifacts. We evaluate COMA on a Schneider Electric Modicon M221 PLC involving two cyber-based attack scenarios: (i) code injection and (ii) code modification. The empirical results show that COMA can successfully detect attack artifacts in memory dumps in both scenarios.

Asmar Awad, Rima↗
NASA NTRS1994

Reed-Solomon Codes and the Exploration of the Solar System

The exploration of the solar system by unmanned spacecraft is one of the triumph of the 20th century. The dramatic photographs of Mercury, Venus, Mars, Jupiter, Saturn, Uranus, and Neptune transmitted by spacecraft with romantic names like Mariner, Voyager, Viking, etc. over distances of hundreds of millions, even billions, of miles, have made these planets, which were previously known to us only as fuzzy telescopic images in textbooks, as real to us in the 1990's as, say, the Himalayas, the Sahara Desert, or Antarctica.

Reed-Solomon coding↗
NASA NTRS2012

ORIGIN: Metal Creation and Evolution from the Cosmic Dawn

ORIGIN is a proposal for the M3 mission call of ESA aimed at the study of metal creation from the epoch of cosmic dawn. Using high-spectral resolution in the soft X-ray band, ORIGIN will be able to identify the physical conditions of all abundant elements between C and Ni to red-shifts of z=10, and beyond. The mission will answer questions such as: When were the first metals created? How does the cosmic metal content evolve? Where do most of the metals reside in the Universe? What is the role of metals in structure formation and evolution? To reach out to the early Universe ORIGIN will use Gamma-Ray Bursts (GRBs) to study their local environments in their host galaxies. This requires the capability to slew the satellite in less than a minute to the GRB location. By studying the chemical composition and properties of clusters of galaxies we can extend the range of exploration to lower redshifts (z approx. 0.2). For this task we need a high-resolution spectral imaging instrument with a large field of view. Using the same instrument, we can also study the so far only partially detected baryons in the Warm-Hot Intergalactic Medium (WHIM). The less dense part of the WHIM will be studied using absorption lines at low redshift in the spectra for GRBs. The ORIGIN mission includes a Transient Event Detector (coded mask with a sensitivity of 0.4 photon/sq cm/s in 10 s in the 5-150 keV band) to identify and localize 2000 GRBs over a five year mission, of which approx.65 GRBs have a redshift >7. The Cryogenic Imaging Spectrometer, with a spectral resolution of 2.5 eV, a field of view of 30 arcmin and large effective area below 1 keV has the sensitivity to study clusters up to a significant fraction of the virial radius and to map the denser parts of the WHIM (factor 30 higher than achievable with current instruments). The payload is complemented by a Burst InfraRed Telescope to enable onboard red-shift determination of GRBs (hence securing proper follow up of high-z bursts) and also probes the mildly ionized state of the gas. Fast repointing is achieved by a dedicated Controlled Momentum Gyro and a low background is achieved by the selected low Earth orbit.

Kouveliotou, C.↗
NASA NTRS1976

Data compression for satellite images

An efficient data compression system is presented for satellite pictures and two grey level pictures derived from satellite pictures. The compression techniques take advantages of the correlation between adjacent picture elements. Several source coding methods are investigated. Double delta coding is presented and shown to be the most efficient. Both predictive differential quantizing technique and double delta coding can be significantly improved by applying a background skipping technique. An extension code is constructed. This code requires very little storage space and operates efficiently. Simulation results are presented for various coding schemes and source codes.

Chen, P. H.↗
DOE OSTI2023

Machine Learning Benchmarks for the Classification of Equivalent Circuit Models from Electrochemical Impedance Spectra

Analysis of Electrochemical Impedance Spectroscopy (EIS) data for electrochemical systems often consists of defining an Equivalent Circuit Model (ECM) using expert knowledge and then optimizing the model parameters to deconvolute various resistance, capacitive, inductive, or diffusion responses. For small data sets, this procedure can be conducted manually; however, it is not feasible to manually define a proper ECM for extensive data sets with a wide range of EIS responses. Automatic identification of an ECM would substantially accelerate the analysis of large sets of EIS data. We showcase machine learning methods to classify the ECMs of 9,300 impedance spectra provided by QuantumScape for the BatteryDEV hackathon. The best-performing approach is a gradient-boosted tree model utilizing a library to automatically generate features, followed by a random forest model using the raw spectral data. A convolutional neural network using boolean images of Nyquist representations is presented as an alternative, although it achieves a lower accuracy. We publish the data and open source the associated code. The approaches described in this article can serve as benchmarks for further studies. A key remaining challenge is the identifiability of the labels, underlined by the model performances and the comparison of misclassified spectra.

25 ENERGY STORAGE↗