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All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Regional Application of an Ecosystem Production Model for Studies of Biogeochemistry in the...

The degree to which primary production, soil carbon, and trace gas fluxes in tropical forests of the Amazon are limited by moisture availability and other environmental factors was examined using an ecosystem modeling application for the country of Brazil. A regional geographic information system (GIS) serves as the data source of climate drivers, satellite images, land cover, and soil properties for input to the NASA Ames-CASA (Carnegie-Ames-Stanford Approach) model over a 8-km grid resolution. Simulation results supports the hypothesis that net primary production (NPP) is limited by cloud interception of solar radiation over the humid northwestern portion of the region. Peak annual rates for NPP of nearly 1.4 kg C m-2yr -1are localized in the seasonally dry eastern Amazon in areas that we assume are primarily deep-rooted evergreen forest cover. Regional effects of forest conversion on NPP and soil carbon content are indicated in the model results, especially in seasonally dry areas. Comparison of model flux predictions along selected eco-climatic transects reveal moisture, soil, and land use controls on gradients of ecosystem production and soil trace gas emissions (CO2, N2O, and NO). These results are used to formulate a series of research hypotheses for testing in the next phase of regional modeling, which includes recalibration of the light-use efficiency term in CASA using field measurements of NPP, and refinements of vegetation index and soil property (texture and potential rooting depth) maps for the region.

Potter, C. S.↗
NASA NTRS2012

Current-State Constrained Filter Bank for Wald Testing of Spacecraft Conjunctions

We propose a filter bank consisting of an ordinary current-state extended Kalman filter, and two similar but constrained filters: one is constrained by a null hypothesis that the miss distance between two conjuncting spacecraft is inside their combined hard body radius at the predicted time of closest approach, and one is constrained by an alternative complementary hypothesis. The unconstrained filter is the basis of an initial screening for close approaches of interest. Once the initial screening detects a possibly risky conjunction, the unconstrained filter also governs measurement editing for all three filters, and predicts the time of closest approach. The constrained filters operate only when conjunctions of interest occur. The computed likelihoods of the innovations of the two constrained filters form a ratio for a Wald sequential probability ratio test. The Wald test guides risk mitigation maneuver decisions based on explicit false alarm and missed detection criteria. Since only current-state Kalman filtering is required to compute the innovations for the likelihood ratio, the present approach does not require the mapping of probability density forward to the time of closest approach. Instead, the hard-body constraint manifold is mapped to the filter update time by applying a sigma-point transformation to a projection function. Although many projectors are available, we choose one based on Lambert-style differential correction of the current-state velocity. We have tested our method using a scenario based on the Magnetospheric Multi-Scale mission, scheduled for launch in late 2014. This mission involves formation flight in highly elliptical orbits of four spinning spacecraft equipped with antennas extending 120 meters tip-to-tip. Eccentricities range from 0.82 to 0.91, and close approaches generally occur in the vicinity of perigee, where rapid changes in geometry may occur. Testing the method using two 12,000-case Monte Carlo simulations, we found the method achieved a missed detection rate of 0.1%, and a false alarm rate of 2%.

Carpenter, J. Russell↗
NASA NTRS2015

A Maneuvering Flight Noise Model for Helicopter Mission Planning

A new model for estimating the noise radiation during maneuvering flight is developed in this paper. The model applies the Quasi-Static Acoustic Mapping (Q-SAM) method to a database of acoustic spheres generated using the Fundamental Rotorcraft Acoustics Modeling from Experiments (FRAME) technique. A method is developed to generate a realistic flight trajectory from a limited set of waypoints and is used to calculate the quasi-static operating condition and corresponding acoustic sphere for the vehicle throughout the maneuver. By using a previously computed database of acoustic spheres, the acoustic impact of proposed helicopter operations can be rapidly predicted for use in mission-planning. The resulting FRAME-QS model is applied to near-horizon noise measurements collected for the Bell 430 helicopter undergoing transient pitch up and roll maneuvers, with good agreement between the measured data and the FRAME-QS model.

Greenwood, Eric↗
NASA NTRS1987

An evaluation of observations from satellites for the study and prediction of mesoscale events and cyclone events

Quantitative observational guidelines have been developed for the study and forecasting of mesoscale events and cyclone events; many of these guidelines have resulted from major meteorological field programs. Increasingly sophisticated satellite-borne instruments in low and geosynchronous orbits have provided valuable measurements of these events. The major deficiencies in the measurements taken from geosynchronous orbit today, relative to guidelines, are (1) the lack of temperature profiles and moisture profiles below clouds, and the poor vertical resolution of these profiles; (2) the insufficient combination of spatial resolution and temporal resolution and spectral intervals available in generating images (imaging); and (3) the lack of accurate precipitation mapping. Considerably more-powerful instrumentation is possible on geosynchronous satellites that can substantially reduce these deficiencies. The capability of advanced geosynchronous observations and those expected with future instrumentation in low-orbit are evaluated with respect to tropical cyclone and severe local-storm observational guidelines. A high percentage of the guidelines are expected to be fulfilled with geosynchronous measurements: (1) using microwave instruments for imaging and for obtaining temperature profiles and moisture profiles, (2) very high spectral-resolution infrared profiling, (3) very high spatial-resolution and very high temporal-resolution imaging, and (4) ozone mapping.

Shenk, William E.↗
NASA NTRS1985

Examination of returned solar-max surfaces for impacting orbital debris and meteoroids

Previous theoretical studies predicted that in certain regions of earth orbit, the man-made earth orbiting debris environment will soon exceed the interplanetary meteoroid environment for sizes smaller than 1 cm. The surfaces returned from the repaired Solar Max Mission (SMM) by STS 41-C on April 12, 1984, offered an excellent opportunity to examine both the debris and meteoroid environments. To date, approximately 0.7 sq. met. of the thermal insulation and 0.05 sq. met of the aluminum louvers have been mapped by optical microscope for crater diameters larger than 40 microns. Craters larger in diameter than about 100 microns found on the initial 75 micron thick Kapton first sheet on the MEB (Main Electronics Box) blanket are actually holes and constitute perforations through that blanket. The following populations have been found to date in impact sites on these blankets: (1) meteoritic material; (2) thermal paint particles; (3) aluminum droplets; and (4) waste particles.

Kessler, D. J.↗
NASA NTRS1990

A model of FTE footprints in the polar cap

The present investigation of the mapping of flux-transfer events (FTEs) onto the polar cap using the Toffoletto and Hill (1989) open version of Voigt's (1981) closed magnetic field model assumes that the magnetic flux associated with FTEs crosses the magnetopause through small regions of large normal components, whence these small flux tubes proceed to map to the polar cap ionosphere. It is found that while the footprint of a circular hole in the magnetopause of an otherwise closed magnetosphere becomes progressively distorted as the hole moves from the day to the night side, a similar region of enhanced open flux in an otherwise open magnetosphere retains an approximately circular footprint. Such regions, moving through the magnetosphere at a slower rate than the background, would generate the dipolar-electric field and current structures predicted by Southwood (1987).

Toffoletto, F. R.↗
NASA NTRS2017

GC13I-0857: Designing a Frost Forecasting Service for Small Scale Tea Farmers in East Africa

Kenya is the third largest tea exporter in the world, producing 10% of the world's black tea. Sixty percent of this production occurs largely by small scale tea holders, with an average farm size of 1.04 acres, and an annual net income of $1,075. According to a recent evaluation, a typical frost event in the tea growing region causes about $200 dollars in losses which can be catastrophic for a small holder farm. A 72-hour frost forecast would provide these small-scale tea farmers with enough notice to reduce losses by approximately 80 USD annually. With this knowledge, SERVIR, a joint NASA-USAID initiative that brings Earth observations for improved decision making in developing countries, sought to design a frost monitoring and forecasting service that would provide farmers with enough lead time to react to and protect against a forecasted frost occurrence on their farm. SERVIR Eastern and Southern Africa, through its implementing partner, the Regional Centre for Mapping of Resources for Development (RCMRD), designed a service that included multiple stakeholder engagement events whereby stakeholders from the tea industry value chain were invited to share their experiences so that the exact needs and flow of information could be identified. This unique event allowed enabled the design of a service that fit the specifications of the stakeholders. The monitoring service component uses the MODIS Land Surface Temperature product to identify frost occurrences in near-real time. The prediction component, currently under testing, uses the 2-m air temperature, relative humidity, and 10-m wind speed from a series of high-resolution Weather Research and Forecasting (WRF) numerical weather prediction model runs over eastern Kenya as inputs into a frost prediction algorithm. Accuracy and sensitivity of the algorithm is being assessed with observations collected from the farmers using a smart phone app developed specifically to report frost occurrences, and from data shared through our partner network developed at the stakeholder engagement meeting. This presentation will illustrate the efficacy of our frost forecasting algorithm, and a way forward for incorporating these forecasts in a meaningful way to the key decision makers - the small-scale farmers of East Africa.

frost↗
NASA NTRS2019

2 mm GISMO Observations of the Galactic Center. I. Dust Emission

The central molecular zone, covering the inner 1° of the Galactic plane has been mapped at 2mm using the Goddard-IRAM Superconducting 2-Millimeter Observer (GISMO) bolometric camera on the 30 m IRAM telescope. The 21 resolution maps show abundant emission from cold molecular clouds, from star-forming regions, and from one of the Galactic center nonthermal filaments. In this work we use the Herschel Hi-GAL data to model the dust emission across the Galactic center. We find that a single-temperature fit can describe the 160-500 um emission for most lines of sight, if the long-wavelength dust emissivity scales as with 2.25. This dust model is extrapolated to predict the 2 mm dust emission. Subtraction of the model from the GISMO data provides a clearer look at the 2 mm emission of star-forming regions and the brightest nonthermal filament.

Arendt, Richard G.↗
NASA NTRSDate not supplied

An Integrated Software Architecture for Solar Cruiser Mission Design and Navigation

Solar Cruiser is a solar sailing mission, riding as a secondary payload to the Interstellar Mapping and Acceleration Probe (IMAP) mission, slated to launch in February of 2025. The Solar Cruiser vehicle will generate thrust via a complex, low-thrust solar sail. The extreme low-thrust nature of the solar sail will leave Solar Cruiser highly sensitive to external environmental effects (such as solar radiation pressure and high-order gravitational perturbations) throughout the entirety of flight. Because of this, preliminary operational optimization routines must be intricately tied to high-order predictive propagation models to ensure the greatest possible confidence in mission success. The Solar Cruiser Mission Design and Navigation (MDNav) team has designed a software tool suite, employing the latest in software containerization technology, to accomplish this task; allowing for seamless development across several users and operating systems. Combining JPL’s Monte toolkit with high-performance optimizers written by the University of Alabama, the proposed architecture allows for instant verification of optimized trajectories within the same development environment that the optimization takes place, removing the need for mission designers and navigators to switch between tools. The MDNav suite image deployment process is separated from the development and operational scripts to be used in flight, which allows for maintaining a low-footprint version control profile without unnecessary file bloating. This paper discusses the historical differences between previous iterations of the Solar Cruiser MDNav tool suite and the current iteration, planned operational interfaces of the tool with other software and subsystems, and the planned path forward in maintaining containerization services for the software throughout the lifetime of Solar Cruiser.

optimization↗
NASA NTRSDate not supplied

An Integrated Software Architecture for Solar Cruiser Mission Design and Navigation

Solar Cruiser is a solar sailing mission, riding as a secondary payload to the Interstellar Mapping and Acceleration Probe (IMAP) mission, expected to launch in February of 2025. The Solar Cruiser vehicle will generate thrust via a complex, low-thrust solar sail. The extreme low-thrust nature of the solar sail will leave Solar Cruiser highly sensitive to external environmental effects (such as solar radiation pressure and high-order gravitational perturbations) throughout the entirety of flight. Because of this, preliminary & operational optimization routines must be intricately tied to high-order predictive propagation models to ensure the greatest possible confidence in mission success. The Solar Cruiser Mission Design and Navigation (MDNav) team has designed a software tool suite, employing the latest in software containerization technology, to accomplish this task, allowing for seamless development across several users and operating systems. Combining JPL’s Monte toolkit with high-performance optimizers written by researchers at the University of Alabama, the proposed architecture allows for instant verification of optimized trajectories within the same development environment that the optimization takes place, removing the need for mission designers and navigators to switch between tools. The MDNav software suite itself is separated from the development and operational scripts to be used in flight, which allows for maintaining a low-footprint version control profile – thus avoiding unnecessary file bloating. This paper discusses the historical differences between previous iterations of the Solar Cruiser MDNav tool suite and the current iteration, planned operational interfaces of the tool with other software and subsystems, and the planned path forward in maintaining containerization services for the software throughout the lifetime of Solar Cruiser.

Containerization↗
NASA NTRSDate not supplied

An Integrated Software Architecture for Solar Cruiser Mission Design and Navigation

Solar Cruiser is a solar sailing mission, riding as a secondary payload to the Interstellar Mapping and Acceleration Probe (IMAP) mission, expected to launch in February of 2025. The Solar Cruiser vehicle will generate thrust via a complex, low-thrust solar sail. The extreme low-thrust nature of the solar sail will leave Solar Cruiser highly sensitive to external environmental effects (such as solar radiation pressure and high-order gravitational perturbations) throughout the entirety of flight. Because of this, preliminary & operational optimization routines must be intricately tied to high-order predictive propagation models to ensure the greatest possible confidence in mission success. The Solar Cruiser Mission Design and Navigation (MDNav) team has designed a software tool suite, employing the latest in software containerization technology, to accomplish this task, allowing for seamless development across several users and operating systems. Combining JPL’s Monte toolkit with University of Alabama’s high-performance optimizer, ASSET, the proposed architecture allows for instant verification of optimized trajectories within the same development environment that the optimization takes place, removing the need for mission designers and navigators to switch between tools. The MDNav software suite itself is separated from the development and operational scripts to be used in flight, which allows for maintaining a low-footprint version control profile – thus avoiding unnecessary file bloating. This paper discusses the historical differences between previous iterations of the Solar Cruiser MDNav tool suite and the current iteration, planned operational interfaces of the tool with other software and subsystems, and the planned path forward in maintaining containerization services for the software throughout the lifetime of Solar Cruiser.

solar cruiser↗
NASA NTRS2022

Neurosymbolic Hybrid Approach to Driver Collision Warning

There are two main algorithmic approaches to autonomous driving systems: (1) An end-to-end system in which a single deep neural network learns to map sensory input directly into appropriate warning and driving responses. (2) A mediated hybrid recognition system in which a system is created by combining independent modules that detect each semantic feature. While some researchers believe that deep learning can solve any problem, others believe that a more engineered and symbolic approach is needed to cope with complex environments with less data. Deep learning alone has achieved state-of-the-art results in many areas, from complex gameplay to predicting protein structures. In particular, in image classification and recognition, deep learning models have achieved accuracies as high as humans. But sometimes it can be very difficult to debug if the deep learning model doesn't work. Deep learning models can be vulnerable and are very sensitive to changes in data distribution. Generalization can be problematic. It's usually hard to prove why it works or doesn't. Deep learning models can also be vulnerable to adversarial attacks. Here, we combine deep learning-based object recognition and tracking with an adaptive neurosymbolic network agent, called the Non-Axiomatic Reasoning System (NARS), that can adapt to its environment by building concepts based on perceptual sequences. We achieved an improved intersection-over-union (IOU) object recognition performance of 0.65 in the adaptive retraining model compared to IOU 0.31 in the COCO data pre-trained model. We improved the object detection limits using RADAR sensors in a simulated environment, and demonstrated the weaving car detection capability by combining deep learning-based object detection and tracking with a neurosymbolic model.

Wang, Pei↗
NASA NTRS1997

Analysis, Repair, and Management of the Total Ozone Mapping Spectrometer Database

In the ensuing period we were able to demonstrate that the origin of these filamentous patterns resulted from the action of synoptic-scale vortical velocity field on the global-scale background gradient of ozone concentration in the meridional direction. Hyperbolic flow patterns between long-lived atmospheric vortices bring together air parcels from different latitudes, thus creating large gradients along the separatrices leaving the hyperbolic (stagnation) point. This result is further confirmed by the KL analysis of the ozone field in the equatorial region, where the background concentration gradient vanishes. The spectral slope in this region has been found to lie close to -1, in agreement with Batchelor's prediction. Another outcome of this result is that it at least provides indirect evidence about the kinetic energy spectrum of the atmospheric turbulence in the range of scales approximately 200 to 2000 km. Namely, Batchelor's analysis is based on the assumption that the velocity field is large-scale, that is the kinetic energy spectrum decays as O(k(sup -3)) or steeper. Since the scalar spectrum is confirmed, this also supports this form of the kinetic energy spectrum. The study of equatorial regions of TOMS data revealed the efficiency of the KL method is in detecting and separating a wave-like measurement artifact inherently present in the dataset due to the non-perfect correction for cross-track bias. Just two to three eigenfunctions represent the error, which makes it possible to enhance the data by reconstituting it from the data by eliminating the subspace of artifactual eigenfunctions. This represents a highly efficient means for achieving an improved rendering of the data. This has been implemented on the database. A wide range of techniques and algorithms have been developed for the repair and extension of the TOMS database.

Sirovich, Lawrence↗
NASA NTRS1986

Preliminary geological investigation of AIS data at Mary Kathleen, Queensland, Australia

The Airborne Imaging Spectrometer (AIS) was flown over granitic, volcanic, and calc-silicate terrain around the Mary Kathleen Uranium Mine in Queensland, in a test of its mineralocial mapping capabilities. An analysis strategy and restoration and enhancement techniques were developed to process the 128 band AIS data. A preliminary analysis of one of three AIS flight lines shows that the data contains considerable spectral variation but that it is also contaminated by second-order leakage of radiation from the near-infrared region. This makes the recognition of expected spectral absorption shapes very difficult. The effect appears worst in terrains containing considerable vegetation. Techniques that try to predict this supplementary radiation coupled with the log residual analytical technique show that expected mineral absorption spectra can be derived. The techniques suggest that with additional refinement correction procedures, the Australian AIS data may be revised. Application of the log residual analysis method has proved very successful on the cuprite, Nevada data set, and for highlighting the alunite, linite, and SiOH mineralogy.

Huntington, J. F.↗
NASA NTRS2005

Computational Model Tracking Primary Electrons, Secondary Electrons, and Ions in the Discharge Chamber of an Ion Engine

Computational modeling of the plasma located in the discharge chamber of an ion engine is an important activity so that the development and design of the next generation of ion engines may be enhanced. In this work a computational tool called XOOPIC is used to model the primary electrons, secondary electrons, and ions inside the discharge chamber. The details of this computational tool are discussed in this paper. Preliminary results from XOOPIC are presented. The results presented include particle number density distributions for the primary electrons, the secondary electrons, and the ions. In addition the total number of a particular particle in the discharge chamber as a function of time, electric potential maps and magnetic field maps are presented. A primary electron number density plot from PRIMA is given in this paper so that the results of XOOPIC can be compared to it. PRIMA is a computer code that the present investigators have used in much of their previous work that provides results that compare well to experimental results. PRIMA only models the primary electrons in the discharge chamber. Modeling ions and secondary electrons, as well as the primary electrons, will greatly increase our ability to predict different characteristics of the plasma discharge used in an ion engine.

Mahalingam, Sudhakar↗
NASA NTRS2013

Integrated Systems Health Management (ISHM) Toolkit

A framework of software components has been implemented to facilitate the development of ISHM systems according to a methodology based on Reliability Centered Maintenance (RCM). This framework is collectively referred to as the Toolkit and was developed using General Atomics' Health MAP (TM) technology. The toolkit is intended to provide assistance to software developers of mission-critical system health monitoring applications in the specification, implementation, configuration, and deployment of such applications. In addition to software tools designed to facilitate these objectives, the toolkit also provides direction to software developers in accordance with an ISHM specification and development methodology. The development tools are based on an RCM approach for the development of ISHM systems. This approach focuses on defining, detecting, and predicting the likelihood of system functional failures and their undesirable consequences.

Venkatesh, Meera↗
NASA NTRSDate not supplied

Fast Machine Learning Lidar Surrogate Simulator: Pristine Clear Sky

The simulations of lidar signals and retrievals rely on a range of optic-physical models, such as radiative transfer models, particle scattering and absorption models, along with the output data from atmospheric physical models. Integrating these different models to represent signals of a lidar system is computationally expensive, and performing backward retrievals can be complex and ambiguous. However, with the advantages of Machine Learning, there is a new potential for building effective lidar signal database linked to corresponding atmospheric profiles. For this project, we are developing a fast pre-trained neural network as the lidar surrogate simulator using simulated data for a CALIPSO-like lidar (355 nm, 532nm, and 1064nm), and a CO2 differential absorption lidar (DIAL) near 1571nm. Specifically, we utilize a long short-term memory (LSTM) model to map the relationships between atmospheric profiles (pressure, temperature, air density and CO2 mixing ratio) and lidar signals. This approach allows us to build machine learning based simulators that can reconstruct lidar signals at specific bands from MERRA reanalysis data, and perform retrievals of atmospheric profiles using lidar signals at various wavelengths. As a first step, the results show the potential of this method to establish a foundational model for sensor signals. This model offers the promise of enabling both accurate predictions and rapid retrievals, providing a more efficient approach to signal processing and analysis.

Shan Zeng↗
NASA NTRS2020

Intensive disc-reverberation mapping of Fairall 9: first year of Swift and LCO monitoring

We present results of time-series analysis of the first year of the Fairall 9 intensive disc-reverberation campaign. We used Swift and the Las Cumbres Observatory global telescope network to continuously monitor Fairall 9 from X-rays to near-infrared at a daily to subdaily cadence. The cross-correlation function between bands provides evidence for a lag spectrum consistent with the τ ∝ λ^(4/3) scaling expected for an optically thick, geometrically thin blackbody accretion disc. Decomposing the flux into constant and variable components, the variable component’s spectral energy distribution is slightly steeper than the standard accretion disc prediction. We find evidence at the Balmer edge in both the lag and flux spectra for an additional bound-free continuum contribution that may arise from reprocessing in the broad-line region. The inferred driving light curve suggests two distinct components, a rapidly variable (<4 d) component arising from X-ray reprocessing, and a more slowly varying (>100 d) component with an opposite lag to the reverberation signal.

J V Hernández Santisteban↗