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All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Further Constraints and Uncertainties on the Deep Seismic Structure of the Moon

The Apollo Passive Seismic Experiment (APSE) consisted of four 3-component seismometers deployed between 1969 and 1972, that continuously recorded lunar ground motion until late 1977. The APSE data provide a unique opportunity for investigating the interior of a planet other than Earth, generating the most direct constraints on the elastic structure, and hence the thermal and compositional evolution of the Moon. Owing to the lack of far side moonquakes, past seismic models of the lunar interior were unable to constrain the lowermost 500 km of the interior. Recently, array methodologies aimed at detecting deep lunar seismic reflections found evidence for a lunar core, providing an elastic model of the deepest lunar interior consistent with geodetic parameters. Here we study the uncertainties in these models associated with the double array stacking of deep moonquakes for imaging deep reflectors in the Moon. We investigate the dependency of the array stacking results on a suite of parameters, including amplitude normalization assumptions, polarization filters, assumed velocity structure, and seismic phases that interfere with our desired target phases. These efforts are facilitated by the generation of synthetic seismograms at high frequencies (approx. 1Hz), allowing us to directly study the trade-offs between different parameters. We also investigate expected amplitudes of deep reflections relative to direct P and S arrivals, including predictions from arbitrarily oriented focal mechanisms in our synthetics. Results from separate versus combined station stacking help to establish the robustness of stacks. Synthetics for every path geometry of data were processed identically to that done with data. Different experiments were aimed at examining various processing assumptions, such as adding random noise to synthetics and mixing 3 components to some degree. The principal stacked energy peaks put forth in recent work persist, but their amplitude (which maps into reflector impedance contrast) and timing (which maps into reflector depth) depend on factors that are not well constrained -- most notably, the velocity structure of the overlying lunar interior. Thus, while evidence for the lunar core remains strong, the depths of imaged reflectors have associated uncertainties that will require new seismic data and observations to constrain. These results strongly advocate further investigations on the Moon to better resolve the interior (e.g., Selene missions), for the Moon apparently has a rich history of construction and evolution that is inextricably tied to that of Earth.

Lin, Pei-Ying Patty↗
NASA NTRS2011

Background Studies for Acoustic Neutrino Detection at the South Pole

The detection of acoustic signals from ultra-high energy neutrino interactions is a promising method to measure the flux of cosmogenic neutrinos expected on Earth. The energy threshold for this process depends strongly on the absolute noise level in the target material. The South Pole Acoustic Test Setup (SPATS), deployed in the upper part of four boreholes of the IceCube Neutrino Observatory, has monitored the noise in Antarctic ice at the geographic South Pole for more than two years down to 500m depth. The noise is very stable and Gaussian distributed. Lacking an in-situ calibration up to now, laboratory measurements have been used to estimate the absolute noise level in the 10 to 50 kHz frequency range to be smaller than 20mPa. Using a threshold trigger, sensors of the South Pole Acoustic Test Setup registered acoustic events in the IceCube detector volume and its vicinity. Acoustic signals from refreezing IceCube holes and from anthropogenic sources have been used to test the localization of acoustic events. An upper limit on the neutrino flux at energies E > 10(exp 11) GeV is derived from acoustic data taken over eight months.

Abbasi, R.↗
NASA NTRS2012

Background Studies for Acoustic Neutrino Detection at the South Pole

The detection of acoustic signals from ultra-high energy neutrino interactions is a promising method. to measure the flux of cosmogenic neutrinos expected on Earth. The energy threshold for this process depends strongly on the absolute noise level in the target material. The South Pole Acoustic Test Setup (SPATS). deployed in the upper part of four boreholes of the IceCube Neutrino Observatory, has monitored the noise in Antarctic ice at the geographic South Pole for more than two years down to 500 m depth. The noise is very stable and Gaussian distributed, Lacking an in situ calibration up to now, laboratory measurements have been used to estimate the absolute noise level in the 10-50 kHz frequency range to be smaller than 20 mPa. Using a threshold trigger. sensors of the South Pole Acoustic Test Setup registered acoustic events in the IceCube detector volume and its vicinity. Acoustic signals from refreezing IceCube holes and from anthropogenic sources have been used to test the localization of acoustic events. An upper limit on the neutrino flux at energies E(sub v) > 10(exp 11) GeV is derived from acoustic data taken over eight months.

Abbasi, R.↗
NASA NTRS2017

Distributed Timing and Localization (DiGiTaL)

The Distributed Timing and Localization (DiGiTaL) system provides nano satellite formations with unprecedented,centimeter-level navigation accuracy in real time and nanosecond-level time synchronization. This is achieved through the integration of a multi-constellation Global Navigation Satellite System (GNSS) receiver, a Chip-Scale Atomic Clock (CSAC), and a dedicated Inter-Satellite Link (ISL). In comparison, traditional single spacecraft GNSS navigation solutions are accurate only to the meter-level due to the sole usage of coarse pseudo-range measurements. To meet the strict requirements of future miniaturized distributed space systems, DiGiTaL uses powerful error-cancelling combinations of raw carrier-phase measurements which are exchanged between the swarming nano satellites through a decentralized network. A reduced-dynamics estimation architecture on board each individual nano satellite processes the resulting millimeter-level noise measurements to reconstruct the fullformation state with high accuracy.

Small Spacecraft↗
NASA NTRS2011

Filtering Methods for Error Reduction in Spacecraft Attitude Estimation Using Quaternion Star Trackers

Precision attitude determination for recent and planned space missions typically includes quaternion star trackers (ST) and a three-axis inertial reference unit (IRU). Sensor selection is based on estimates of knowledge accuracy attainable from a Kalman filter (KF), which provides the optimal solution for the case of linear dynamics with measurement and process errors characterized by random Gaussian noise with white spectrum. Non-Gaussian systematic errors in quaternion STs are often quite large and have an unpredictable time-varying nature, particularly when used in non-inertial pointing applications. Two filtering methods are proposed to reduce the attitude estimation error resulting from ST systematic errors, 1) extended Kalman filter (EKF) augmented with Markov states, 2) Unscented Kalman filter (UKF) with a periodic measurement model. Realistic assessments of the attitude estimation performance gains are demonstrated with both simulation and flight telemetry data from the Lunar Reconnaissance Orbiter.

Calhoun, Philip C.↗
NASA NTRS2019

OGLE-2017-BLG-1186: First Application of Asteroseismology and Gaussian Processes to microlensing

We present the analysis of the event OGLE-2017-BLG-1186 from the 2017 Spitzer microlensing campaign. This is a remarkable microlensing event because its source is photometrically bright and variable, which makes it possible to perform an asteroseismic analysis using ground-based data. We find that the source star is an oscillating red giant with average timescale of ∼9 d. The asteroseismic analysis also provides us source properties including the source angular size (∼27 μas) and distance (∼11.5 kpc), which are essential for inferring the properties of the lens. When fitting the light curve, we test the feasibility of Gaussian processes (GPs) in handling the correlated noise caused by the variable source. We find that the parameters from the GP model are generally more loosely constrained than those from the traditional χ(exp 2) minimization method. We note that this event is the first microlensing system for which asteroseismology and GPs have been used to account for the variable source. With both finite-source effect and microlens parallax measured, we find that the lens is likely a ∼0.045 Mʘ brown dwarf at distance ∼9.0 kpc, or a ∼0.073 Mʘ ultracool dwarf at distance ∼9.8 kpc. Combining the estimated lens properties with a Bayesian analysis using a Galactic model, we find a ∼ 35 per cent probability for the lens to be a bulge object and ∼ 65 per cent to be a background disc object.

S.-S. Li↗
NASA NTRSDate not supplied

Conceptual Design Trade Studies for Acoustic Predictions of the NASA UAM Tiltrotor Reference Vehicle

A toolchain of low-and mid-fidelity tools is applied to NASA’s Urban Air Mobility tiltrotor reference vehicle to quantify trades in sizing, performance, and noise at the conceptual design level. The process includes conceptual sizing, comprehensive analysis, and acoustic analysis to design and analyze versions of the concept tiltrotor with differing design variables. Rotor tip speed is the primary design variable studied, with blade twist, blade taper, and blade number also considered. The noise metrics used are the FAA/EASA certification Effective Perceived Noise Levels for takeoff, flyover, and approach. Certification condition noise is calculated for all conditions in both conversion and airplane flight modes, with airplane mode flight resulting in noise 10-25EPNdB quieter than conversion mode and tip speed variation providing noise reduction up to 9EPNdB.

Acoustic↗
DOE OSTI2023

Non-Markovian Hole Excess Noise in Avalanche Amorphous Selenium Thin Films

Enhancing the signal-to-noise ratio in avalanche photodiodes by utilizing impact ionization gain requires materials exhibiting low excess noise factors. Amorphous selenium (a-Se) as a wide bandgap at ~2.1 eV, a solid-state avalanche layer, demonstrates single-carrier hole impact ionization gain and manifests ultralow thermal generation rates. A comprehensive study of the history dependent and non-Markovian nature of hot hole transport in a-Se was modeled using a Monte Carlo (MC) random walk of single hole free flights, interrupted by instantaneous phonon, disorder, hole–dipole, and impact-ionization scattering interactions. The hole excess noise factors were simulated for 0.1–15 μm a-Se thin-films as a function of mean avalanche gain. The hole excess noise factors in a-Se decreases with an increase in electric field, impact ionization gain, and device thickness. The history dependent nature of branching of holes is explained using a Gaussian avalanche threshold distance distribution and the dead space distance, which increases determinism in the stochastic impact ionization process. An ultralow non-Markovian excess noise factor of ~1 was simulated for 100 nm a-Se thin films corresponding to avalanche gains of 1000. Future detector designs can utilize the nonlocal/non-Markovian nature of the hole avalanche in a-Se, to enable a true solid-state photomultiplier with noiseless gain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Image processing pipeline for AI-driven nanoparticle megalibrary characterization

Recent innovations have made it possible to produce megalibraries, millions of structurally and compositionally distinct nanoparticles on a chip. These megalibraries yield vast volumes of data that are impossible to analyze manually, necessitating the development of automated tools. In previous work, we created a binary classification machine learning model to select quality nanoparticle images for downstream analysis. In this work, we show that adding a custom image processing step before training can produce significantly higher-performing models in a fraction of the time and make them more robust to different image noise levels and microscope acquisition settings. The image processing pipeline proposed here effectively cleans raw nanoparticle images, enhances key features, and allows us to use much lower resolution images and simpler neural network model architectures. These features result in higher performance and significant cost savings. Experiments demonstrate superior performance relative to baseline, including an 18.2% improvement in recall and a 13.1% increase in accuracy. Given the high cost of downstream analysis, it is critical to minimize false positives, and our best-performing model reaches a precision of 95.9% and a weighted F-score of 95.1% on an unseen test set. Additionally, model training time is reduced from hours to less than a minute. We also show that, using this custom image processing pipeline, model performance is significantly improved at lower pixel resolutions compared to downsizing alone. We expect that adopting this pipeline for AI-driven automated nanoparticle characterization will allow researchers to rapidly and accurately analyze much greater volumes of data, thereby accelerating materials discovery.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRS2004

NASA's Vision for Jet Noise Engineering

Until recently, the design of jet engines for quiet operation was limited by engineers' ability to predict the jet noise generated by a nozzle exhaust system. More importantly, the 'intermediate steps' between nozzle design and noise had not been understood, limiting the design process to small variations around existing solutions. In recent years NASA's Quiet Aircraft Technology (QAT) Program has advanced the understanding and modeling of jet noise to give engineers the tools they need to design quiet nozzle systems for subsonic exhaust systems. The presentation discusses the approach followed for QAT and argues that a similar effort aimed at supersonic jet exhaust systems will be needed to allow designs of quiet military aircraft in the future.

Kinzie, Kevin W.↗
DOE OSTI2022

Fiber Bundle Morphisms as a Framework for Modeling Many-to-Many Maps

While it is not generally reflected in the `nice' datasets used for benchmarking machine learning algorithms, the real-world is full of processes that would be best described as many-to-many. That is, a single input can potentially yield many different outputs (whether due to noise, imperfect measurement, or intrinsic stochasticity in the process) and many different inputs can yield the same output (that is, the map is not injective). For example, imagine a sentiment analysis task where, due to linguistic ambiguity, a single statement can have a range of different sentiment interpretations while at the same time many distinct statements can represent the same sentiment. When modeling such a multivalued function $f: X \rightarrow Y$, it is frequently useful to be able to model the distribution on $f(x)$ for specific input $x$ as well as the distribution on fiber $f^{-1}(y)$ for specific output $y$. Such an analysis helps the user (i) better understand the variance intrinsic to the process they are studying and (ii) understand the range of specific input $x$ that can be used to achieve output $y$. Following existing work which used a fiber bundle framework to better model many-to-one processes we describe how morphisms of fiber bundles provide a template for building models which naturally capture the structure of many-to-many processes.

Coda, Elizabeth D.↗
NASA NTRS1986

A densely spaced array of sea level monitors for the detection of vertical crustal deformation in the Shumagin seismic gap, Alaska

A network of sea level gauges has been installed with about 40 km spacing in the Shumagin Islands in order to detect relative vertical motion, in particular, possible crustal motion precursory to an expected major earthquake. This required the development and deployment of a pressure sensor sea level gauge suitable for installation on remote and harsh coastlines. Data are collected in near-real-time via satellite, both in order to exploit fully any precursors that may be observed and to provide continuous information on the status of the instruments. Using Wiener filtering techniques, it has been determined conservatively that no relative vertical crustal motion greater than 0.1 m between stations has occurred during 1981-1985. This is consistent with independent geodetic leveling and trilateration data, though evidence exists for more rapid deformation during 1978-1980. The sea level data collected so far have an rms noise level of about 0.04 m after processing; this is limited in part by the pressure sensor and associated electronics. Improved prressure gauges with better long-term stability have recently been installed. A short-baseline tiltmeter operating in a tunnel has demonstrated that suitably designed and located land-based tiltmeters have a lower noise level, and hence better precursor detection characteristics than the sea level gauges, at monthly and shorter periods.

Beavan, John↗
NASA NTRS1999

First Look at Landsat-7 Mission Performance: Technical and Operational Results to Date

A primary goal of the current Landsat-7 mission, launched on April 15, 1999, is to acquire and refresh on a seasonal basis, calibrated ata sets of multispectral digital imagery of the landmass of the Earth The Enhanced Thematic Mapper Plus (ETM+) imager flown on Landsat-7 provides ground spatial resolutions in the panchromatic, reflective and emissive bands of 15, 30 and 60 meters, respectively, for a nominal scene 183 km wide by 170 km long. This mission not only builds on the invaluable 27-year continuous archive of thematic images of the Earth provided by previous Landsat satellites, it also inaugurates a new era of robust data acquisition with an emphasis on global change science. The newly developed Long Term Acquisition Plan (LTAP) is being used to optimize the systematic collection of data from all parts of the globe, populating the U.S.-held archive at the USGS EROS Data Center (EDC) with over 90,000 Landsat scene per year . An additional 73,000 Images are expected to be acquired each year by several international ground stations, for a total downlink of Landsat7 data in excess of 100 terabytes per year. Nearly 20,000 scan of Landsat-7 ETM+ data have already been acquired in the first 100 days of the mission. Early results derived from assessments of the ETM+ instrument, the spacecraft, and the ground processing systems indicate that the image quality is outstanding, clearly the best ever provided by any Landsat mission. Sensor radiometric background stability after the first 100 days in orbit is approximately 0.1 percent. Stability of the Full Aperture Solar Calibrator is approximately 0.3 percent, and mid-scale per pixel noise is approximately 0.6 percent. A ground processing system has been implemented at EDC which is capable of capturing, processing and archiving 250 Landsat scenes 9 per day, and delivering 100 scene products to seems each day. The cost of a systematically-processed Level 1 product has been dropped dramatically to $600, end there is no longer any copyright protection an the data. The net result is that the use of Landsat ETM+ data is expected to grow dramatically, and this growth is expected to benefit all facets of the land remote sensing community.

Williams, Darrel L.↗
NASA NTRS2012

Remote Sensing of Tropical Ecosystems: Atmospheric Correction and Cloud Masking Matter

Tropical rainforests are significant contributors to the global cycles of energy, water and carbon. As a result, monitoring of the vegetation status over regions such as Amazonia has been a long standing interest of Earth scientists trying to determine the effect of climate change and anthropogenic disturbance on the tropical ecosystems and its feedback on the Earth's climate. Satellite-based remote sensing is the only practical approach for observing the vegetation dynamics of regions like the Amazon over useful spatial and temporal scales, but recent years have seen much controversy over satellite-derived vegetation states in Amazônia, with studies predicting opposite feedbacks depending on data processing technique and interpretation. Recent results suggest that some of this uncertainty could stem from a lack of quality in atmospheric correction and cloud screening. In this paper, we assess these uncertainties by comparing the current standard surface reflectance products (MYD09, MYD09GA) and derived composites (MYD09A1, MCD43A4 and MYD13A2 - Vegetation Index) from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to results obtained from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. MAIAC uses a new cloud screening technique, and novel aerosol retrieval and atmospheric correction procedures which are based on time-series and spatial analyses. Our results show considerable improvements of MAIAC processed surface reflectance compared to MYD09/MYD13 with noise levels reduced by a factor of up to 10. Uncertainties in the current MODIS surface reflectance product were mainly due to residual cloud and aerosol contamination which affected the Normalized Difference Vegetation Index (NDVI): During the wet season, with cloud cover ranging between 90 percent and 99 percent, conventionally processed NDVI was significantly depressed due to undetected clouds. A smaller reduction in NDVI due to increased aerosol levels was observed during the dry season, with an inverse dependence of NDVI on aerosol optical thickness (AOT). NDVI observations processed with MAIAC showed highly reproducible and stable inter-annual patterns with little or no dependence on cloud cover, and no significant dependence on AOT (p less than 0.05). In addition to a better detection of cloudy pixels, MAIAC obtained about 20-80 percent more cloud free pixels, depending on season, a considerable amount for land analysis given the very high cloud cover (75-99 percent) observed at any given time in the area. We conclude that a new generation of atmospheric correction algorithms, such as MAIAC, can help to dramatically improve vegetation estimates over tropical rain forest, ultimately leading to reduced uncertainties in satellite-derived vegetation products globally.

tropical ecosystems↗
DOE OSTI2022

Tracking Volumetric Units in Modular Factories for Automated Progress Monitoring Using Computer Vision

The construction industry is increasingly adopting off-site and prefabricated methods due to advantages offered in safety, quality, and lead time. Applying industrialized methods for plant management in offsite construction factories requires the collection of large volumes of production process data, which is a tedious task when performed manually. Recent attempts to automate this process have relied on sensor-based data collection methods which are susceptible to noise, expensive, and difficult to validate. Computer vision methods, however, enable process data collection from videos without the limitations of the other sensor-based methods. This technology has not been applied for offsite construction except in very few instances and therefore, this study proposes a novel method to reliably collect the production process data using computer vision method in near real-time from widely used surveillance cameras in offsite construction. The proposed method allows the user to annotate the workstations of interest on the video as ground truths and process these areas throughout the entire video to track the units entering and leaving stations, while continuously updating a near real-time schedule of the production line. This framework was validated by implementing on the surveillance videos of the production process of modular home manufacturing in a factory. The results consistently provided 100% accuracy, after denoising, for all the videos processed including 60 h of work for a station. The developed method enables real-time tracking of station performance, which can enable continuous improvement methods for factory management and resource allocation.

computer vision↗
NASA NTRSDate not supplied

Quality Assurance of ISS LIS lightning Data

Optical lighting detection from space has been ongoing since 1995 from the Optical Transient detector (1995-2000), then later by the Lightning Imaging Sensors (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite (1997-2015) and the International Space Station (ISS) (ISS 2017-present). A rapid readout (2 ms) 128x128 pixel CCD (Charge-coupled Device) array detects optical transients from lightning (events) and transmits the observations to ground. Ground processing determines whether individual events are likely due to lightning or noise. Likely lightning events are then grouped into groups, flashes, and areas and their location on the earth are determined. The lightning data are saved in orbit files; each file containing the time, location, and intensity of the lightning events, groups, flashes, and areas detected during one orbit. Even after this processing anomalies may exist in some of the orbits. A manual quality assurance (QA) procedure is performed monthly to assess the data and omit orbits with obvious anomalies from the dataset. These files are not included in the final dataset that has undergone QA. The manual QA was developed during the OTD mission to identify artifacts that made it through ground processing algorithms. The manual QA process was continued for the TRMM and ISS LIS missions. Many anomalies have been identified and software updates now address many of them. However, some anomalies still occur in the processed datasets. The manual QA process examines the data for obvious issues in the lightning files that passed through the processing algorithms. These files are considered anomalous and are not included in the final QA dataset. Some issues that may cause an orbit to be considered anomalous include: obvious noise (excess events that make it through the processing), suspect geolocation, and excessive missing data packets. As an example, one way noise manifests is as “streaks” in lightning climatology plots. These streaks are especially apparent in low lightning rate regions (eg., over oceans). Since there is no method at present to extract these anomalies during processing, orbit files with significant anomalies are identified and removed from the final QA ISS LIS dataset. The final QA dataset can be obtained files from the Global Hydrometeorological Resource Center (GHRC). This presentation will provide examples of the various anomalies and examine how often the various anomalies occur and how much data is lost due to the omission of the anomalous orbits. Comparisons with OTD and TRMM LIS will also be examined.

ISS↗
NASA NTRS2020

Validation of a Digital Noise Power Integration Technique for Radiometric Clear Sky Attenuation Estimation at Q-band

This paper presents the validation of a digital signal processing technique that can be used to estimate radiometric sky noise, and hence, atmospheric absorption, within existing digital receivers at little/no additional cost. To demonstrate this, a receiver was constructed that simultaneously records the beacon signal power from the ALPHASAT Aldo Paraboni technology demonstration payload, as well as the integrated noise power in the adjacent band. Calibration from the digital radiometer is performed using tip-curve calibration procedures. Atmospheric fading is then obtained by observing the beacon as well as the radiometric signals. This enables the comparison of fading obtained by the two techniques and provides a means to calibrate the received beacon power level to obtain total atmospheric attenuation. It is shown that for low levels of fading, up to a few dB, the two techniques provide good agreement. This approach can therefore provide a low-cost option for geostationary mmwave satellite channel measurements in the low fading regime, which can be useful in the design and operation of the feeder links in emerging satcom systems.

radiometer↗