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NASA NTRS2012

NASA's Next Generation Space Geodesy Network

NASA's Space Geodesy Project (SGP) is developing a prototype core site for a next generation Space Geodetic Network (SGN). Each of the sites in this planned network co-locate current state-of-the-art stations from all four space geodetic observing systems, GNSS, SLR, VLBI, and DORIS, with the goal of achieving modern requirements for the International Terrestrial Reference Frame (ITRF). In particular, the driving ITRF requirements for this network are 1.0 mm in accuracy and 0.1 mm/yr in stability, a factor of 10-20 beyond current capabilities. Development of the prototype core site, located at NASA's Geophysical and Astronomical Observatory at the Goddard Space Flight Center, started in 2011 and will be completed by the end of 2013. In January 2012, two operational GNSS stations, GODS and GOON, were established at the prototype site within 100 m of each other. Both stations are being proposed for inclusion into the IGS network. In addition, work is underway for the inclusion of next generation SLR and VLBI stations along with a modern DORIS station. An automated survey system is being developed to measure inter-technique vectorties, and network design studies are being performed to define the appropriate number and distribution of these next generation space geodetic core sites that are required to achieve the driving ITRF requirements. We present the status of this prototype next generation space geodetic core site, results from the analysis of data from the established geodetic stations, and results from the ongoing network design studies.

Desai, S. D.↗

DOE OSTI2024

Learning stochastic dynamics and predicting emergent behavior using transformers

We show that a neural network originally designed for language processing can learn the dynamical rules of a stochastic system by observation of a single dynamical trajectory of the system, and can accurately predict its emergent behavior under conditions not observed during training. We consider a lattice model of active matter undergoing continuous-time Monte Carlo dynamics, simulated at a density at which its steady state comprises small, dispersed clusters. We train a neural network called a transformer on a single trajectory of the model. The transformer, which we show has the capacity to represent dynamical rules that are numerous and nonlocal, learns that the dynamics of this model consists of a small number of processes. Forward-propagated trajectories of the trained transformer, at densities not encountered during training, exhibit motility-induced phase separation and so predict the existence of a nonequilibrium phase transition. Transformers have the flexibility to learn dynamical rules from observation without explicit enumeration of rates or coarse-graining of configuration space, and so the procedure used here can be applied to a wide range of physical systems, including those with large and complex dynamical generators.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2013

The Utility of the Real-Time NASA Land Information System Data for Drought Monitoring Applications

Measurements of soil moisture are a crucial component for the proper monitoring of drought conditions. The large spatial variability of soil moisture complicates the problem. Unfortunately, in situ soil moisture observing networks typically consist of sparse point observations, and conventional numerical model analyses of soil moisture used to diagnose drought are of coarse spatial resolution. Decision support systems such as the U.S. Drought Monitor contain drought impact resolution on sub-county scales, which may not be supported by the existing soil moisture networks or analyses. The NASA Land Information System, which is run with 3 km grid spacing over the eastern United States, has demonstrated utility for monitoring soil moisture. Some of the more useful output fields from the Land Information System are volumetric soil moisture in the 0-10 cm and 40-100 cm layers, column-integrated relative soil moisture, and the real-time green vegetation fraction derived from MODIS (Moderate Resolution Imaging Spectroradiometer) swath data that are run within the Land Information System in place of the monthly climatological vegetation fraction. While these and other variables have primarily been used in local weather models and other operational forecasting applications at National Weather Service offices, the use of the Land Information System for drought monitoring has demonstrated utility for feedback to the Drought Monitor. Output from the Land Information System is currently being used at NWS Huntsville to assess soil moisture, and to provide input to the Drought Monitor. Since feedback to the Drought Monitor takes place on a weekly basis, weekly difference plots of column-integrated relative soil moisture are being produced by the NASA Short-term Prediction Research and Transition Center and analyzed to facilitate the process. In addition to the Drought Monitor, these data are used to assess drought conditions for monthly feedback to the Alabama Drought Monitoring and Impact Group and the Tennessee Drought Task Force, which are comprised of federal, state, and local agencies and other water resources professionals.

White, Kristopher D.↗

NASA NTRS2023

Tracking NO2 Pollution Changes Over Texas: Synthesis of In Situ and Satellite Observations

Nitrogen oxides (NO x ) are major air pollutants that play a crucial role in atmospheric chemistry. We compare Ozone Measuring Instrument's (OMI) NO 2 records with the in situ surface measurements from the Air Quality System of the US Environmental Protection Agency and the Texas Commission on Environmental Quality network in the state of Texas with the goal of understanding the correspondence of satellite and in situ surface observations and identifying the potential synergies between the two observing systems. Our analysis of over 40 in situ daily surface site observations, mostly from urban areas, and OMI daily observed data suggests a correlation ( r ) ranging between 0.2 and 0.8. The correlation improves considerably ( r > 0.5) for monthly average data. Weekly variation of surface NO 2 with a Sunday minimum is well captured by OMI tropospheric NO 2 column observations with similar weekend reductions. NO 2 trend in Texas during 2005–2019 is characterized by significant reductions of 20%–36% in highly populated cities and urban centers. However, a significant (up to 80%) increase was observed in oil and gas producing regions of the Permian and Eagle Ford Basins over the same period. In March–April of 2020, like the other US and global cities, Texas experienced up to 60% reduction in NO 2 levels in major cities due to travel restrictions imposed at local and national levels to contain the spread of COVID-19. Though such reduction is temporary, these reductions were significantly larger than those achieved in the past 16 years of OMI record suggesting that technological advancement can curtail NO x emissions.

Nitrogen dioxide (NO2)↗

DOE OSTI2022

Physics constrained learning for data-driven inverse modeling from sparse observations

Deep neural networks (DNN) have been used to model nonlinear relations between physical quantities. Those DNNs are embedded in physical systems described by partial differential equations (PDE) and trained by minimizing a loss function that measures the discrepancy between predictions and observations in some chosen norm. This loss function often includes the PDE constraints as a penalty term when only sparse observations are available. As a result, the PDE is only satisfied approximately by the solution. However, the penalty term typically slows down the convergence of the optimizer for stiff problems. We present a new approach that trains the embedded DNNs while numerically satisfying the PDE constraints. We develop an algorithm that enables differentiating both explicit and implicit numerical solvers in reverse-mode automatic differentiation. This allows the gradients of the DNNs and the PDE solvers to be computed in a unified framework. We demonstrate that our approach enjoys faster convergence and better stability in relatively stiff problems compared to the penalty method. Furthermore, our approach allows for the potential to solve and accelerate a wide range of data-driven inverse modeling, where the physical constraints are described by PDEs and need to be satisfied accurately.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2019

IDN Update

The objective of this presentation is to provide International Directory Network (IDN) updates on features and activities to the Committee on Earth Observation Satellites (CEOS) Working Group on Information Systems and Services (WGISS) and provider community.

Committee on Earth Observation Satellites (CEOS)↗

NASA NTRS1984

Active Optical Sounding of Ozone and Minor Constituents in the Middle Atmosphere: a Review of Ground-based Lidar Measurements

Due to the rapid development of powerful laser sources in the UV wavelength range which includes nd:yag pumped dye lasers and excimer lasers, ground-based lidar systems are now operational for ozone monitoring in the troposphere and the stratosphere. Such systems will play an important role in the determination of long term ozone trends in the photochemical region. The capacities of active lidar systems in terms of high temporal and spatial resolution and measurements continuity, allow the observation of the ozone variations at various time and space scales which are important in present day areas of interest. The already operational character of the lidar systems will constitute the basis for development of a ground-base network for middle atmospheric observations of ozone and other race gases.

Megie, G.↗

NASA NTRS1993

Applications of CCSDS recommendations to Integrated Ground Data Systems (IGDS)

This paper describes an application of the CCSDS Principle Network (CPH) service model to communications network elements of a postulated Integrated Ground Data System (IGDS). Functions are drawn principally from COSMICS (Cosmic Information and Control System), an integrated space control infrastructure, and the Earth Observing System Data and Information System (EOSDIS) Core System (ECS). From functional requirements, this paper derives a set of five communications network partitions which, taken together, support proposed space control infrastructures and data distribution systems. Our functional analysis indicates that the five network partitions derived in this paper should effectively interconnect the users, centers, processors, and other architectural elements of an IGDS. This paper illustrates a useful application of the CCSDS (Consultive Committee for Space Data Systems) Recommendations to ground data system development.

Mizuta, Hiroshi↗

NASA NTRS1989

Extended observability of linear time-invariant systems under recurrent loss of output data

Recurrent loss of sensor data in integrated control systems of an advanced aircraft may occur under different operating conditions that include detected frame errors and queue saturation in computer networks, and bad data suppression in signal processing. This paper presents an extension of the concept of observability based on a set of randomly selected nonconsecutive outputs in finite-dimensional, linear, time-invariant systems. Conditions for testing extended observability have been established.

Luck, Rogelio↗

NASA NTRS2005

Large decreases in ionospheric total electron content as a result of thermospheric composition changes during geomagnetic storms

The geomagnetic storms of April 17-21,2002 and May 29-30,2003 caused large decreases in the O/N2 column density ratio in the thermosphere. For these storms, ON2 column density decreases of greater than 50% were observed to extend to mid-to-low latitudes with the FUV sensitive Earth Camera of the Visible Imaging System (VIS) on the Polar spacecraft. Simultaneously in these same regions, the ground-based GPS network observed approximately 80% reductions in the Total Electron Content (TEC) of the ionosphere. The reduction in the Om2 column density ratio is due mainly to increases in the molecular species that have welled-up into the thermosphere from the lower levels of the atmosphere due to auroral heating. The geomagnetic-storm driven increase in molecular densities at typical ionospheric heights rapidly charge exchange with the ambient ionized atoms and subsequently dissociatively recombine with the ionospheric electrons leading to a reduction in the total charge density. The transition boundaries between high and low regions of O/N2 as well as TEC can be tracked in the images and the thermospheric winds can be determined from the motion of the boundaries. The motion of these boundaries during the development of the geomagnetic storm will be discussed.

Sigwarth, J. B.↗

NASA NTRS2005

The Dynamics of Thermospheric Composition and Ionospheric Total Electron Content During Geomagnetic Storms

The geomagnetic storms of April 17-21,2002 and May 29-30,2003 caused large decreases in the O/N2 column density ratio in the thermosphere. For these storms, O/N2 column density decreases of greater than 50% were observed to extend to mid-to-low latitudes with the FUV sensitive Earth Camera of the Visible Imaging System (VIS) on the Polar spacecraft. Simultaneously in these same regions, the ground-based GPS network observed approximately 80% reductions in the Total Electron Content (TEC) of the ionosphere. The reduction in the O/N2 column density ratio is due mainly to increases in the molecular species that have welled-up into the thermosphere from the lower levels of the atmosphere due to auroral heating. The geomagnetic-storm driven increase in molecular densities at typical ionospheric heights rapidly charge exchange with the ambient ionized atoms and subsequently dissociatively recombine with the ionospheric electrons leading to a reduction in the total charge density. The transition boundaries between high and low regions of O/N2 as well as TEC can be tracked in the images and the thermospheric winds may be inferred from the motion of the boundaries. The motion of these boundaries during the development of the geomagnetic storm will be discussed.

Sigwarth, John B.↗

NASA NTRS1972

Critical configurations of fundamental range networks.

A range network is defined to consist of ground stations and targets where only distances between the two sets of points are observed. Such a network is said to be fundamental when only those six constraints are used that are needed to define the coordinate system for an adjustment. When ground stations or targets have certain configurations, a unique adjustment in terms of coordinates may be impossible, even when the number of observations is sufficient and the coordinate system is uniquely defined. Such configurations, resulting in the singular solutions, are said to be critical. Attention is therefore focused on singular solutions rather than on numerical problems in some ill-conditioned systems of fundamental range networks. The critical configurations are presented in two separate groups. The first deals with ground stations lying all in a plane and the second deals with ground stations generally distributed. The two kinds of problems require different mathematical treatments and lead to quite different conclusions.

Blaha, G.↗

NASA NTRS1994

Max 1991 and beyond

Max '91, a coordinated, broad based observational program, was designed to help maximize the scientific return of solar activity studies. Max '91 benefited from the support of the NOAA space environment laboratory. An important source that increases solar ground based support observations is the solar observing optical network (SOON) solar patrol on tape (SOONSPOT) solar image archival system which has started operations. The past means and the future plans for ground based coordination and communications of Max '91 are summarized. The current status and the future developments of SOONSPOT are presented.

Kiplinger, Alan L.↗

NASA NTRS2004

VLBI2010: Networks and Observing Strategies

The Observing Strategies Sub-group of IVS's Working Group 3 has been tasked with producing a vision for the following aspects of geodetic VLBI: antenna-network structure and observing strategies; source strength/structure/distribution; frequency bands, RFI; and field system and scheduling. These are high level considerations that have far reaching impact since they significantly influence performance potential and also constrain requirements for a number of other \VG3 sub-groups. The paper will present the status of the sub-group's work on these topics.

Petrachenko, Bill↗

NASA NTRS2011

NASA Tech Briefs, May 2011

Topics covered include: 1) Method to Estimate the Dissolved Air Content in Hydraulic Fluid; 2) Method for Measuring Collimator-Pointing Sensitivity to Temperature Changes; 3) High-Temperature Thermometer Using Cr-Doped GdAlO3 Broadband Luminescence; 4)Metrology Arrangement for Measuring the Positions of Mirrors of a Submillimeter Telescope; 5) On-Wafer S-Parameter Measurements in the 325-508-GHz Band; 6) Reconfigurable Microwave Phase Delay Element for Frequency Reference and Phase-Shifter Applications; 7) High-Speed Isolation Board for Flight Hardware Testing; 8) High-Throughput, Adaptive FFT Architecture for FPGA-Based Spaceborne Data Processors; 9) 3D Orbit Visualization for Earth-Observing Missions; 10) MaROS: Web Visualization of Mars Orbiting and Landed Assets; 11) RAPID: Collaborative Commanding and Monitoring of Lunar Assets; 12) Image Segmentation, Registration, Compression, and Matching; 13) Image Calibration; 14) Rapid ISS Power Availability Simulator; 15) A Method of Strengthening Composite/Metal Joints; 16) Pre-Finishing of SiC for Optical Applications; 17) Optimization of Indium Bump Morphology for Improved Flip Chip Devices; 18) Measuring Moisture Levels in Graphite Epoxy Composite Sandwich Structures; 19) Marshall Convergent Spray Formulation Improvement for High Temperatures; 20) Real-Time Deposition Monitor for Ultrathin Conductive Films; 21) Optimized Li-Ion Electrolytes Containing Triphenyl Phosphate as a Flame-Retardant Additive; 22) Radiation-Resistant Hybrid Lotus Effect for Achieving Photoelectrocatalytic Self-Cleaning Anticontamination Coatings; 23) Improved, Low-Stress Economical Submerged Pipeline; 24) Optical Fiber Array Assemblies for Space Flight on the Lunar Reconnaissance Orbiter; 25) Local Leak Detection and Health Monitoring of Pressurized Tanks; 26) Dielectric Covered Planar Antennas at Submillimeter Wavelengths for Terahertz Imaging; 27) Automated Cryocooler Monitor and Control System; 28) Broadband Achromatic Phase Shifter for a Nulling Interferometer; 29) Super Dwarf Wheat for Growth in Confined Spaces; 30) Fine Guidance Sensing for Coronagraphic Observatories; 31) Single-Antenna Temperature- and Humidity-Sounding Microwave Receiver; 32) Multi-Wavelength, Multi-Beam, and Polarization-Sensitive Laser Transmitter for Surface Mapping; 33) Optical Communications Link to Airborne Transceiver; 34) Ascent Heating Thermal Analysis on Spacecraft Adaptor Fairings; 35) Entanglement in Self-Supervised Dynamics; 36) Prioritized LT Codes; 37) Fast Image Texture Classification Using Decision Trees; 38) Constraint Embedding Technique for Multibody System Dynamics; 39) Improved Systematic Pointing Error Model for the DSN Antennas; 40) Observability and Estimation of Distributed Space Systems via Local Information-Exchange Networks; 41) More-Accurate Model of Flows in Rocket Injectors; 42) In-Orbit Instrument-Pointing Calibration Using the Moon as a Target; 43) Reliability of Ceramic Column Grid Array Interconnect Packages Under Extreme Temperatures; 44) Six Degrees-of-Freedom Ascent Control for Small-Body Touch and Go; and 45) Optical-Path-Difference Linear Mechanism for the Panchromatic Fourier Transform Spectrometer.

Source record↗

DOE OSTI2023

A Novel LCC-CLCC Resonant Tuning Network for Light-Load Conditions in Wireless Power Transfer Systems

In wireless power transfer (WPT) systems, voltage and current distortions are observed at the vehicle side rectifier when power flow is from grid to vehicle (G2V) under light load conditions. These distortions can increase switching losses and decrease the overall efficiency of the WPT system. To address this issue, this paper proposes adding a higher value inductor in series with the original LCC tuning network at the vehicle side. However, increasing the series inductance causes the input impedance and phase angle to move away from the resonant frequency. To solve this problem, a capacitor is added in series to tune out the difference between the original and modified inductor values. This series tuning capacitor also improves the power factor and brings the input impedance and phase angle back to the resonant frequency. The traditional LCC-LCC and proposed LCC-CLCC WPT systems are compared and analyzed analytically, and simulated in a MATLAB/Simulink environment to verify parameters such as efficiency and power transfer capacity. An experimental prototype is implemented and compared with the simulation. The obtained results confirm the validity of the proposed method.

Harave, Sudarshan↗

DOE OSTI2021

Dynamic consensus and extended high gain observers as a tool to achieve practical frequency synchronization in power systems under unknown time-varying power demand

In this paper, we consider the frequency synchronization problem in a network of lossless, connected, and network-reduced power system. Frequency synchronization is an important problem in power systems as frequency deviation can lead to degraded power quality, tripping of generators, etc. We present a load-estimator-based consensus algorithm in a network of fourth-order generator models that achieves practical frequency synchronization in the presence of unknown time-varying power demand. We do not assume that the demand is generated by a known model. We follow a multiple time-scale approach for the stability analysis. It is shown that synchronization is achieved for the case of constant power demand, by showing that the system is exponentially stable. Furthermore, for the case of time-varying power demand, we show the error trajectories are ultimately bounded, and the synchronization error is proportional to an upper bound on the derivative of the time-varying power demand. We simulate the controller performance on a four area network which is equivalent to the IEEE New England 39-Bus system.

42 ENGINEERING↗

DOE OSTI2025

Mesoscale Cellular Convection Detection and Classification Using Convolutional Neural Networks: Insights From Long-Term Observations at ARM Eastern North Atlantic Site

Marine boundary layer clouds are crucial in Earth's climate system. They frequently manifest as closed or open cell mesoscale cellular convection (MCC). MCC clouds are challenging to represent accurately in current climate models, highlighting the need for detailed observational data sets and in-depth analyses. This study utilizes over 8 years of observations from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility Eastern North Atlantic (ENA) site at Graciosa Island, Azores, to investigate these clouds. We first apply a convolutional neural network with a U-Net architecture to classify open and closed cells, marking the first application of such an approach for automatically detecting MCC patterns from ground-based radar measurements. This method addresses some observational gaps in satellite data related to low temporal resolution, nighttime challenges, and limited vertical structure capture. The analysis of the MCC cases shows clear differences between closed and open MCCs: Closed MCC clouds are characterized by lower cloud tops and bases, shallower cloud geometrical depth, weaker horizontal wind speeds, stronger atmospheric stability, and a more homogeneous liquid water path than open MCCs. Finally, we demonstrate two potential applications of our radar-based MCC classifications: (a) facilitating the investigation of aerosol-cloud interactions and (b) exploring meteorological factors along with MCC's evolution by integrating satellite imagery and back-trajectory analysis. The identified MCC cases offer a valuable resource for the scientific community to study MCC processes further and improve climate model accuracy.

54 ENVIRONMENTAL SCIENCES↗