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At least 559 records · Page 31

Sensor fusion techniques for predicting thunderstorm evolution using lightning and radar networks

A pattern recognition scheme that is used to generate initial seeds or 'first guess' fields for clustering the discrete lightning discharges into storm cells is presented. The clustering process is critically dependent on the prior accuracy of the lightning location estimates. The generation of subsequent storm life-cycle time series (for extrapolation forecasting) also relies on the cluster analysis procedure assigning the correct number of lightning discharges (objects) to the proper storms (groups). The advantages and limitations of different clustering strategies for storm identification and tracking are examined. Storm identification with lightning data alone is compared to storm identification with radar alone, and some synergies for sensor fusion are explored.

Goodman, Steven J.↗

The construction and operation of a water tunnel in application to flow visualization studies of an oscillating airfoil

The water tunnel which was constructed at the NASA Ames Research Center is described along with the flow field adjacent to an oscillating airfoil. The design and operational procedures of the tunnel are described in detail. Hydrogen bubble and thymol blue techniques are used to visualize the flow field. Results of the flow visualizations are presented in a series of still pictures and a high speed movie. These results show that time stall is more complicated than simple shedding from the leading edge or the trailing edge, particularly at relatively low frequency oscillations comparable to those of a helicopter blade. Therefore, any successful theory for predicting the stall loads on the helicopter blades must treat an irregular separated region rather than a discrete vortex passing over each blade surface.

Olsen, J. H.↗

Dust Trails of SP/Tuttle and the Unusual Outbursts of the Ursid Shower

Halley-type comets tend to have a series of dust trails that remain spatially correlated for extended periods of time, each dating from a specific return of the comet. Encounters with 1 - 9 revolution old individual dust trails of 55P/Tempel-Tuttle have led to well recognized Leonid shower maxim, the peak time of which was well predicted by recent models. Now. we used the same model to calculate the position of dust trails of comet Shuttle, a Halley-type comet in an (approximately) 13.6 year orbit passing just outside of Earth's orbit. We discovered that the meteoroids tend to be trapped in the 14:12 mean motion resonance with Jupiter, while the comet librates in a slightly shorter period orbit around the 13:15 resonance. It takes six centuries to change the orbit enough to intersect Earth's orbit. During that time, the meteoroids and comet separate in mean anomaly by six years. thus explaining the unusual aphelion occurrences of Ursid outbursts. The resonances also prevent dispersion, so that the dust trail encounters (specifically, from dust trails of AD 1378 - 1405) occur only in one year in each orbit. We predicted enhanced activity on December 22, 2000, at around 7:29 and 8:35 UT (universal time) from dust trails dating to the 1405 and 1392 return, respectively. This event was observed from California using video and photographic techniques. At the same time, five Global-MS-Net stations in Finland, Japan and Belgium counted meteors using forward meteor scatter. The outburst peaked at 8:06:07 UT, December 22, at Zenith Hourly Rate (approx.) 90 per hour. The Ursid rates were above half peak intensity during 4.2 hours. This is only the second Halley type comet for which a meteor outburst can be dated to a specific return of the parent comet, and traces their presence back form 9 to at least 45 revolutions of the comet. New orbital elements of Ursid meteoroids are presented. We find that most orbits do scatter around the anticipated positions, confirming the link with comet Shuttle and the epoch of ejection. The 1405 and.1392 dust trails appear to have contributed similar amounts to the activity profile. Some orbits provide a hint of much older debris being present as well. Some of the dispersion in the radiant position may reflect a true variation in inclinations, with two groupings at low and high values, which is not understood at present.

Jenniskens, Peter↗

Observations of Land Surface Variability Using Passive Microwave Sensing

Understanding the global variability of land surface wetness (soil moisture), skin temperature, and related surface fluxes of heat and moisture is key to assessing the importance of the land surface in influencing climate. The feasibility of producing model estimates of these quantities is being studied as part of the International Satellite Land Surface Climatology Project (ISLSCP) Global Soil Wetness Project (GSWP). In the GSWP approach, meteorological observations and analyses are used to drive global circulation models. Satellite measurements can provide independent estimates of key land surface parameters that are needed for initializing and validating the climate models and for monitoring long-term change. Satellite observations of the land surface can also be assimilated into soil models to estimate moisture in the root zone. In our research, passive microwave satellite data recorded during 1978-1987 from the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) are being used to examine spatial and temporal trends in surface soil moisture, vegetation, and temperature. These data include observations at C and X bands (6.6 and 10.7 GHz), which are not available on the current Special Sensor Microwave/Imager (SSM/I) and are precursors to data that will become available from the Advanced Microwave Scanning Radiometer (AMSR) on Advanced Earth Observing Satellite (ADEOS-II) and Earth Observing System (EOS) PM1 in the year 2000. A chart shows a time-series of SMMR-derived surface temperature, T-e and surface soil moisture M, retrieved on a 0.5 deg x 0.5 deg grid and further averaged over a 4 deg x 10 deg study region in the African Sahel. Also shown are National Center for Environmental Prediction (NCEP) model outputs of surface temperature, T-sfc, and soil wetness, Soil-w. The variables have been scaled to have similar dynamic ranges on the plots. The NCEP data from the NCEP Reanalysis Project are monthly averages on a 2.5 deg x 2.5 deg grid averaged over the 4 deg x 10 deg study area. Comparisons of SMMR retrievals with forecast model output show the potential of the satellite data for validating model output and monitoring long-term trends. Continuing work will extend these results to other regions to validate the retrievals more quantitatively. In preparation for the launch of AMSR, field experiments are planned in collaboration with the Global Energy and Water Cycle Experiment (GEWEX) Coordinated Enhanced Observing Period (CEOP) experiments to evaluate the satellite-derived soil moisture measurements and to demonstrate their usefulness for land surface hydrology and climate. Additional information is contained in the original.

Njoku, Eni G.↗

Experimental Demonstration of the Dependence of the First Hyperpolarizability of Donor-Acceptor Substituted Polyenes on the Ground-State Polarization and Bond Length Alternation

The dependence of the product of the first hyperpolarizability, beta, and the ground-state dipole moment, mu, for a series of donor-acceptor polyenes with a large range of ground-state polarization, was measured in a variety of solvents by electric field induced second harmonic generation. The observed behavior of mu times beta as a function of ground-state polarization agrees well with theoretical predictions. In particular, as a function of increasing polarization, mu times beta was found to first increase, peak in a positive sense, decrease, pass through zero, become large and negative, and eventually peak in a negative sense.

hyperpolarizability donor-acceptor substituted pol↗

Power Electronics Materials and Bonded Interfaces - Reliability and Lifetime

High temperature operation of wide bandgap devices continue to be a challenge for the power electronics packages. Thermal performance and reliability are important factors that determine the viability of a bonded interface for operation at high temperatures. In this presentation, we present the technical approach and key results from the research on sintered silver, transient liquid phase alloy, and polymeric materials. A lifetime prediction model that incorporates the thermomechanical behavior of sintered silver at 200C was developed. The copper-aluminum transient alloy completed 350 thermal cycles from -40C to 200C and little increase in the defect level was observed. In addition to material research, we initiated a time-series analysis on the scanning acoustic microscope images of eutectic solder to explore statistical forecasting methods and machine learning techniques. Initial results that report the accuracy of a few different statistical models are presented.

ADVANCED PROPULSION SYSTEMS↗

Comparison of Exploration Portable Life Support Subsystem (xPLSS) Thermal Modeling to Thermal Vacuum Testing

To support NASA’s goal to return to the Moon through the Artemis mission, the development of an exploration portable life support system (xPLSS) has been conducted at Johnson Space Center (JSC). As part of this development process, a large system level thermal/fluid model of the xPLSS was developed using Thermal Desktop and an in-house human model (METMAN). The xPLSS model was used throughout the design process to predict the performance and temperature of nearly all components within the xPLSS. In the fall of 2023, the design, verification, and testing (DVT) unit of the xPLSS was tested in a thermal vacuum (TVAC) chamber at JSC. This testing consisted of combining the xPLSS with an upper torso of the exploration pressure garment system (xPGS) and simulating five extravehicular activities (EVAs) in extreme thermal conditions (two cold EVAs and three hot EVAs). The data generated in this test series provided system level data of the xPLSS operating in vacuum and at flight-like environmental temperatures for the first time. This data was compared to results output by the xPLSS system model to assess the accuracy of previous analyses and improve the fidelity and accuracy of the xPLSS system model. The comparison between model and test hardware provides valuable insight that will help improve the design and fidelity of next generation space suits. In general, comparison between test data and model data generally showed slightly un-conservative values (model predicting colder temperatures than test in hot environments, and hotter temperatures than test in cold environments). Model assumptions and test assumptions were assessed to understand potential causes of some of these sources in error. Recommendations to improve the fidelity of the xPLSS model were also made based on the results presented in this paper.

xPLSS↗

Comparison of Exploration Portable Life Support Subsystem (xPLSS) Thermal Modeling to Thermal Vacuum Testing

To support NASA’s goal to return to the Moon through the Artemis Mission, the development of an Exploration Portable Life Support Subsystem (xPLSS) has been conducted at Johnson Space Center (JSC). As part of this development process, a large system level thermal/fluid model of the xPLSS was developed using Thermal Desktop and an in-house human model (METMAN). The xPLSS model was used throughout the design process to predict the performance and temperature of nearly all components within the xPLSS. In the fall of 2023, the Design, Verification, and Testing (DVT) unit of the xPLSS was tested in a thermal vacuum (TVAC) chamber at JSC. This testing consisted of combining the xPLSS with an upper torso of the Exploration Pressure Garment System (xPGS) and simulating five Extravehicular Activities (EVAs) in extreme thermal conditions (two cold EVAs and three hot EVAs). The data generated in this test series provided system level data of the xPLSS operating in vacuum and at flight-like environmental temperatures for the first time. These data were compared to results output by the xPLSS system model to assess the accuracy of previous analyses and improve the fidelity and accuracy of the xPLSS system model. The comparison between model and test hardware provides valuable insight that will help improve the design and fidelity of next generation space suits. In general, comparison between test data and model data generally showed slightly un-conservative values (model predicting colder temperatures than test in hot environments, and hotter temperatures than test in cold environments). Model assumptions and test assumptions were assessed to understand potential causes of some of these sources in error. Recommendations to improve the fidelity of the xPLSS model were also made based on the results presented in this paper.

xPLSS↗

AI-Based Analytics and Energy Modeling Framework for Characterizing Urban Energy Systems

Developing location-specific district energy models is essential for understanding energy patterns and supporting efficient management and planning decisions. However, accurately characterizing these models remains challenging due to gaps in building characteristics and labor-intensive traditional modeling workflows. To address these challenges, we develop an AI-based framework that integrates top-down and bottom-up building energy data to automate urban energy model characterization. The framework trains multimodal deep learning models using heterogeneous ResStockTM datasets to infer missing building characteristics from varying levels of known information and generate simulation-ready inputs for district-scale energy modeling. It also employs a conditioning-based injection approach to generate ”what-if” scenarios, enabling users to explore retrofit, efficiency, and technology-upgrade pathways. Integrated within URBANoptTM, a bottom-up district energy modeling platform for simulating co-located buildings, the framework infers detailed building-level inputs required for bottom-up simulations. Both localized and generalized AI models are developed to learn relationships across categorical, numerical, and time-series data, enabling reconstruction of missing attributes and generation of targeted upgrade scenarios. We demonstrate this methodology on a residential neighborhood in Baltimore, MD, assessing internal consistency against ResStock reference data and URBANopt simulation, and comparing selected attributes against real-world building characteristics. Results show strong overall predictive accuracy in data completion and scenario generation, with localized and generalized models offering complementary trade-offs between precision and scalability. Overall, our automated framework streamlines energy modeling and provides a reliable framework for urban building energy characterization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Machine Learning for Real-time Fusion Plasma Behavior Prediction and Manipulation

This project set out with an ambitious goal: to develop and apply machine learning-based methods of discovering new controllers and operating regimes for achieving better performing plasmas in tokamaks. As summarized in the dozens of papers below, the project was a huge success. It developed several machine learning components and integrated them into a single ML system that was added to the DIII-D PCS. That functionality was demonstrated over a series of experiments on DIII-D. A summary of these results is given here with the details in the published papers below.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Global Geodetic Signatures of the Antarctic Ice Sheet

Four scenarios of present day Antarctic ice sheet mass change are developed from comprehensive reviews of the available glaciological and oceanographic evidence. The gridded scenarios predict widely varying contributions to secular sea level change xi ranging from -1.1 to 0.45 mm/yr, and predict polar motion m and time-varying low-degree gravitational coefficients J(sub l) that differ significantly from earlier estimates. A reasonably linear relationship between the rate of sea level change from Antarctica xi(sub A) and the predicted Antarctic J(sub l) is found for the four scenarios. This linearity permits a series of forward models to be constructed that incorporate the effects of ice mass changes in Antarctica, Greenland, and distributed smaller glaciers, as well as postglacial rebound (assuming the ICE-3G deglaciation history), with the goal of obtaining optimum reconciliation between observed constraints on J(sub l) and sea level rise xi. Numerous viable combinations of lower mantle viscosity and hydrologic sources are found that safely "observed" in the range of 1 to 2-2.5 mm/yr and observed J(sub l) for degrees 2, 3, and 4. In contrast, rates of global sea level rise above 2.5 mm/yr are inconsistent with available J(sub l) observations. The successful composite models feature a pair of lower mantle viscosity solutions arising from the sensitivity of J(sub l) to glacial rebound. The paired values are well separated at xi = 1 mm/yr, but move closer together as xi is increased, and, in fact, merge around xi = 2 - 2.5 mm/yr, revealing an intimate relation between xi and preferred lower mantle viscosity. This general pattern is quite robust and persists for different J(sub l) solutions, for variations in source assumptions, and for different styles of lower mantle viscosity stratification. Tighter J(sub l) constraints for l greater than 2 may allow some viscosity stratification schemes and source assumptions to be excluded in the future. For a given total observed xi the sea level rise from Antarctica xi(sub A) is tightly constrained and ranges from 0 to + 1 mr/yr (corresponding to an ablating ice sheet) as estimates of xi are raised from 1 to 2.5 mm/yr. However, when the degree 3 zonal harmonic constraint is removed, the solutions show little sensitivity to Antarctic mass balance, emphasizing the need for a well determined odd-degree secular zonal harmonic for determining polar ice mass balance.

James, Thomas S.↗

A Search for Planetary Transits of the Star HD 187123 by Spot Filter CCD Differential Photometry

A novel method for performing high precision, time series CCD differential photometry of bright stars using a spot filter, is demonstrated. Results for several nights of observing of the 51 Pegasi b-type planet bearing star HD 187123 are presented. Photometric precision of 0.0015 - 0.0023 magnitudes is achieved. No transits are observed at the epochs predicted from the radial velocity observation. If the planet orbiting HD 187123 at 0.0415 AU is an inflated Jupiter similar in radius to HD 209458b it would have been detected at the greater than 6(sigma), level if the orbital inclination is near 90 degrees and at the greater than 3(sigma), level if the orbital inclination is as small as 82.7 degrees.

Castellano, T.↗

DOE Final Report Machine Learning for Real-time Fusion Plasma Behavior Prediction and Manipulation

This project set out with an ambitious goal: to develop and apply machine learning-based methods of discovering new controllers and operating regimes for achieving better performing plasmas in tokamaks. As summarized in the dozens of papers below, the project was a huge success. It developed several machine learning components and integrated them into a single ML system that was added to the DIII-D PCS. That functionality was demonstrated over a series of experiments on DIII-D. A brief summary of these results is given here with the details in the published papers below.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Observations of vertical velocities in the tropical upper troposphere and lower stratosphere using the Arecibo 430-MHz radar

The first clear-air observations of vertical velocities in the tropical upper troposphere and lower stratosphere (8-22 km) using the Arecibo 430-MHz radar are presented. Oscillations in the vertical velocity near the Brunt-Vaisala period are observed in the lower stratosphere during the 12-hour observation period. Frequency power spectra from the vertical velocity time series show a slope between -0.5 and -1.0. Vertical wave number spectra computed from the height profiles of vertical velocities have slopes between -1.0 and -1.5. These observed slopes do not agree well with the slopes of +1/3 and -2.5 for frequency and vertical wave number spectra, respectively, predicted by a universal gravity-wave spectrum model. The spectral power of wave number spectra of a radial beam directed 15 deg off-zenith is enhanced by an order of magnitude over the spectral power levels of the vertical beam. This enhancement suggests that other geophysical processes besides gravity waves are present in the horizontal flow. The steepening of the wave number spectrum of the off-vertical beam in the lower stratosphere to near -2.0 is attributed to a quasi-inertial period wave, which was present in the horizontal flow during the observation period.

Cornish, C. R.↗

An Integrated Use of Experimental, Modeling and Remote Sensing Techniques to Investigate Carbon and Phosphorus Dynamics in the Humid Tropics

Moist tropical forests comprise one of the world's largest and most diverse biomes, and exchange more carbon, water, and energy with the atmosphere than any other ecosystem. In recent decades, tropical forests have also become one of the globe's most threatened biomes, subjected to exceptionally high rates of deforestation and land degradation. Thus, the importance of and threats to tropical forests are undeniable, yet our understanding of basic ecosystem processes in both intact and disturbed portions of the moist tropics remains poorer than for almost any other major biome. Our approach in this project was to take a multi-scale, multi-tool approach to address two different problems. First, we wanted to test if land-use driven changes in the cycles of probable limiting nutrients in forest systems were a key driver in the frequently observed pattern of declining pasture productivity and carbon stocks. Given the enormous complexity of land use change in the tropics, in which one finds a myriad of different land use types and intensities overlain on varying climates and soil types, we also wanted to see if new remote sensing techniques would allow some novel links between parameters which could be sensed remotely, and key biogeochemical variables which cannot. Second, we addressed to general questions about the role of tropical forests in the global carbon cycle. First, we used a new approach for quantifying and minimizing non-biological artifacts in the NOAA/NASA AVHRR Pathfinder time series of surface reflectance data so that we could address potential links between Amazonian forest dynamics and ENSO cycles. Second, we showed that the disequilibrium in C-13 exchanged between land and atmosphere following tropical deforestation probably has a significant impact on the use of 13-CO2 data to predict regional fluxes in the global carbon cycle.

Townsend, Alan R.↗

Asymmetry in the Rate of Warming and the Phenology of Seasonal Blooms in the Northeast US Shelf Ecosystem

Predicting the impact of marine ecosystem warming on the timing and magnitude of phytoplankton production is challenging. For example, warming can advance the progression of stratification thereby changing the availability of nutrients to surface phytoplankton, or influence the surface mixed layer depth, thus affecting light availability. Here, we use a time series of sea surface temperature (SST) and chlorophyll remote sensing products to characterize the response of the phytoplankton community to increased temperature in the Northeast US Shelf Ecosystem. The rate of change in SST was higher in the summer than in winter in all ecoregions resulting in little change in the timing and magnitude of the spring thermal transition compared to a significant change in the autumn transition. Along with little phenological shift in spring thermal conditions, there was also no evidence of a change in spring bloom timing and duration. However, we observed a change in autumn bloom timing in the Georges Bank ecoregion, where bloom initiation has shifted from late September to late October between 1998 and 2020—on average 33 d later. Bloom duration in this ecoregion also shortened from ∼7.5 to 5 weeks. The shortened autumn bloom may be caused by later overturn in stratification known to initiate autumn blooms in the region, whereas the timing of light limitation at the end of the bloom remains unchanged. These changes in bloom timing and duration appear to be related to the change in autumn thermal conditions and the significant shift in autumn thermal transition. These results suggest that the spring bloom phenology in this temperate continental shelf ecosystem may be more resilient to thermal climate change effects than blooms occurring in other times of the year.

climate change↗

Can Machine Learning Reveal Precursors of Reversals of the Geomagnetic Axial Dipole Field?

It is well known that the axial dipole part of Earth’s magnetic field reverses polarity, so that the magnetic North Pole becomes the South Pole and vice versa. The timing of reversals is well documented for the past 160 Myr, but the conditions that lead to a reversal are still not well understood. It is not known if there are reliable ‘precursors’ of reversals (events that indicate that a reversal is upcoming) or what they might be. We investigate if machine learning (ML) techniques can reliably identify precursors of reversals based on time-series of the axial magnetic dipole field. The basic idea is to train a classifier using segments of time-series of the axial magnetic dipole. This training step requires modification of standard ML techniques to account for the fact that we are interested in rare events—a reversal is unusual, while a non-reversing field is the norm. Without our tweak, the ML classifiers lead to useless predictions. Perhaps even more importantly, the usable observational record is limited to 0–2 Ma and contains only five reversals, necessitating that we determine if the data are even sufficient to reliably train and validate an ML algorithm. To answer these questions we use several ML classifiers (linear/non-linear support vector machines and long short-term memory networks), invoke a hierarchy of numerical models (from simplified models to 3-D geodynamo simulations), and two palaeomagnetic reconstructions (PADM2M and Sint-2000). The performance of the ML classifiers varies across the models and the observational record and we provide evidence that this is not an artefact of the numerics, but rather reflects how ‘predictable’ a model or observational record is. Studying models of Earth’s magnetic field via ML classifiers thus can help with identifying shortcomings or advantages of the various models. For Earth’s magnetic field, we conclude that the ability of ML to identify precursors of reversals is limited, largely due to the small amount and low frequency resolution of data, which makes training and subsequent validation nearly impossible. Put simply: the ML techniques we tried are not currently capable of reliably identifying an axial dipole moment (ADM) precursor for geomagnetic reversals. This does not necessarily imply that such a precursor does not exist, and improvements in temporal resolution and length of ADM records may well offer better prospects in the future.

Kyle Gwirtz↗

Experimental Investigations of Non-Stationary Properties In Radiometer Receivers Using Measurements of Multiple Calibration References

Radiometers must be periodically calibrated because the receiver response fluctuates. Many techniques exist to correct for the time varying response of a radiometer receiver. An analytical technique has been developed that uses generalized least squares regression (LSR) to predict the performance of a wide variety of calibration algorithms. The total measurement uncertainty including the uncertainty of the calibration can be computed using LSR. The uncertainties of the calibration samples used in the regression are based upon treating the receiver fluctuations as non-stationary processes. Signals originating from the different sources of emission are treated as simultaneously existing random processes. Thus, the radiometer output is a series of samples obtained from these random processes. The samples are treated as random variables but because the underlying processes are non-stationary the statistics of the samples are treated as non-stationary. The statistics of the calibration samples depend upon the time for which the samples are to be applied. The statistics of the random variables are equated to the mean statistics of the non-stationary processes over the interval defined by the time of calibration sample and when it is applied. This analysis opens the opportunity for experimental investigation into the underlying properties of receiver non stationarity through the use of multiple calibration references. In this presentation we will discuss the application of LSR to the analysis of various calibration algorithms, requirements for experimental verification of the theory, and preliminary results from analyzing experiment measurements.

Racette, Paul↗