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NASA NTRS2018

An Algorithm for Trajectory Generation in Redundant Manipulators with Joint Transmission Accommodation

Trajectory generation for manipulators involves generating incremental updates of joint variables to achieve a desired end–eﬀector motion. The Jacobian matrix maps incremental joint motion to incremental end–eﬀector motion in a linear fashion and is typically used in manipulator trajectory generation algorithms. In the case of a redundant manipulator, the Jacobian matrix is not square or invertible and therefore algorithms based on pseudoinverses and their variations are commonly used for trajectory generation. These methods either are computationally not eﬃcient or do not utilize all the joints in motion generation and therefore do not completely exploit the redundancy of the manipulator. The method presented in this paper is a simple method that maximizes transmission of all joint variables onto a desired end–eﬀector motion trajectory. The method is based on aligning the null–space of an augmented Jacobian matrix with the path of the desired end–eﬀector motion, from which a linear combination of joints that projects fully onto the desired end–eﬀector trajectory is obtained. In this manner, all joints of the redundant manipulator are used to generate the end–eﬀector trajectory accommodating the ability of each joint in terms of its motion transmission.

Ravani, Bahram↗

NASA NTRS1994

Radio and X-ray observations of the gamma-ray bright quasar PKS 0528+134

We present a study of the z = 2.07 quasar PKS 0528+134, which has been detected as an extraordinarily luminous gamma-ray source. Its radio properties are highly variable in both total and polarized flux density. Milliarcsecond-scale maps from global very long base interferometry (VLBI) experiments, an X-ray spectrum from ROSAT Position Sensitive Proportional Counter (PSPC) observations, and light curves in total flux density and polarization are used to investigate the geometry, radiation mechanism, and physical environment of the emission region in the source. The VLBI images reveal a bent jet extending toward the northeast on parsec scales, with less intense knots of emission appearing on the opposite side of the brightest spot. The position of the core usually found in such sources is unclear. The polarization angle is stable despite strong variability in polarized flux density and indicates that the magnetic field is aligned with the jet axis as defined by our 8.4 GHz image. The ROSAT X-ray flux density of PKS 0528+134 in 1991 March is measured to be 1.6 micro Jy at 1 keV, with a very steep spectral (`energy') index sigma(sub x) approximately equal to 2.2. The X-ray observations reveal the presence of cold gas along the line of sight significantly in excess of that present in the Galaxy. A strong radio flare began within two months of the first observation of a high flux of gamma-rays from PKS 0528+134 by Hunter et al. Using the geometry and spectral chacateristics determined by our VLBI observations, a synchrotron self-Compton calculation indicates that relativistic bulk motion is required in PKS 0528+134, with an estimated Doppler beaming factor delta approximately greater than 4.3, similar to the value delta approximately greater than 7 required to explain the low optical depth of the gamma-rays to photon-photon pair production. We suggest that the core activity of PKS 0528+134 is sporadic in nature, with the nonthermal outburst starting in 1991 representing a violent period involving ejection of relativistic plasma along a compact jet pointed almost directly toward us.

Zhang, Yun Fei↗

NASA NTRS1989

A multi-sensor remote sensing approach for measuring primary production from space

It is proposed to develop a multi-sensor remote sensing method for computing marine primary productivity from space, based on the capability to measure the primary ocean variables which regulate photosynthesis. The three variables and the sensors which measure them are: (1) downwelling photosynthetically available irradiance, measured by the VISSR sensor on the GOES satellite, (2) sea-surface temperature from AVHRR on NOAA series satellites, and (3) chlorophyll-like pigment concentration from the Nimbus-7/CZCS sensor. These and other measured variables would be combined within empirical or analytical models to compute primary productivity. With this proposed capability of mapping primary productivity on a regional scale, we could begin realizing a more precise and accurate global assessment of its magnitude and variability. Applications would include supplementation and expansion on the horizontal scale of ship-acquired biological data, which is more accurate and which supplies the vertical components of the field, monitoring oceanic response to increased atmospheric carbon dioxide levels, correlation with observed sedimentation patterns and processes, and fisheries management.

Gautier, Catherine↗

NASA NTRS2015

An Assessment of Actual and Potential Building Climate Zone Change and Variability From the Last 30 Years Through 2100 Using NASA's MERRA and CMIP5 Simulations

Background: In the US, residential and commercial building infrastructure combined consumes about 40% of total energy usage and emits about 39% of total CO2 emission (DOE/EIA "Annual Energy Outlook 2013"). Building codes, as used by local and state enforcement entities are typically tied to the dominant climate within an enforcement jurisdiction classified according to various climate zones. These climate zones are based upon a 30-year average of local surface observations and are developed by DOE and ASHRAE. Establishing the current variability and potential changes to future building climate zones is very important for increasing the energy efficiency of buildings and reducing energy costs and emissions in the future. Objectives: This paper demonstrates the usefulness of using NASA's Modern Era Retrospective-analysis for Research and Applications (MERRA) atmospheric data assimilation to derive the DOE/ASHRAE building climate zone maps and then using MERRA to define the last 30 years of variability in climate zones for the Continental US. An atmospheric assimilation is a global atmospheric model optimized to satellite, atmospheric and surface in situ measurements. Using MERRA as a baseline, we then evaluate the latest Climate Model Inter-comparison Project (CMIP) climate model Version 5 runs to assess potential variability in future climate zones under various assumptions. Methods: We derive DOE/ASHRAE building climate zones using surface and temperature data products from MERRA. We assess these zones using the uncertainties derived by comparison to surface measurements. Using statistical tests, we evaluate variability of the climate zones in time and assess areas in the continental US for statistically significant trends by region. CMIP 5 produced a data base of over two dozen detailed climate model runs under various greenhouse gas forcing assumptions. We evaluate the variation in building climate zones for 3 different decades using an ensemble and quartile statistics to provide an assessment of potential building climate zone changes relative to the uncertainties demonstrated using MERRA. Findings and Conclusions: These results show that there is a statistically significant increase in the area covered by warmer climate zones and a tendency for a reduction of area in colder climate zones in some limited regions. The CMIP analysis shows that models vary from relatively little building climate zone change for the least sensitive and conservation assumptions to a warming of at most 3 zones for certain areas, particularly the north central US by the end of the 21st century.

Stackhouse, Paul W., Jr.↗

DOE OSTI2023

Characterizing post-fire delayed tree mortality with remote sensing: sizing up the elephant in the room

Abstract Background Despite recent advances in understanding the drivers of tree-level delayed mortality, we lack a method for mapping delayed mortality at landscape and regional scales. Consequently, the extent, magnitude, and effects of delayed mortality on post-fire landscape patterns of burn severity are unknown. We introduce a remote sensing approach for mapping delayed mortality based on post-fire decline in the normalized burn ratio (NBR). NBR decline is defined as the change in NBR between the first post-fire measurement and the minimum NBR value up to 5 years post-fire for each pixel. We validate the method with high-resolution aerial photography from six wildfires in California, Oregon, and Washington, USA, and then compare the extent, magnitude, and effects of delayed mortality on landscape patterns of burn severity among fires and forest types. Results NBR decline was significantly correlated with post-fire canopy mortality (r 2 = 0.50) and predicted the presence of delayed mortality with 83% accuracy based on a threshold of 105 NBR decline. Plots with NBR decline greater than 105 were 23 times more likely to experience delayed mortality than those below the threshold (p < 0.001). Delayed mortality occurred across 6–38% of fire perimeters not affected by stand-replacing fire, generally affecting more areas in cold (22–41%) and wet (30%) forest types than in dry (1.7–19%) types. The total area initially mapped as unburned/very low-severity declined an average of 38.1% and generally persisted in smaller, more fragmented patches when considering delayed mortality. The total area initially mapped as high-severity increased an average of 16.2% and shifted towards larger, more contiguous patches. Conclusions Differences between 1- and 5-year post-fire burn severity maps depict dynamic post-fire mosaics resulting from delayed mortality, with variability among fires reflecting a range of potential drivers. We demonstrate that tree-level delayed mortality scales up to alter higher-level landscape patterns of burn severity with important implications for forest resilience and a range of fire-driven ecological outcomes. Our method can complement existing tree-level studies on drivers of delayed mortality, refine mapping of fire refugia, inform estimates of habitat and carbon losses, and provide a more comprehensive assessment of landscape and regional scale fire effects and trends.

Environmental Sciences & Ecology↗

DOE OSTI2020

Primal interface debonding formulation for finite strain isotropic plasticity

In this work, a framework is developed for modeling ductile damage of nonlinear materials whose plastic deformation is characterized using rate independent classical plasticity. This method relies on the assumption that the free energy can be decomposed into elastic, plastic and damage parts. A thermodynamically consistent method is derived which satisfies the second law of thermodynamics in the Clausius–Duhem inequality form. The dissipation associated with plasticity takes place in the domain only, while damage dissipation is localized to the interface. The method is developed using Variational Multiscale ideas to obtain definitions of the interface fluxes within a primal formulation analogous to the Discontinuous Galerkin method, which ensures weakly vanishing interface gap prior to reaching a damage initiation criterion. The local nonlinear problem to calculate both plastic deformation gradient and damage variable follows an incremental approach similar to classical plasticity return mapping algorithm. This elastoplastic damage formulation is developed for material undergoing finite strain, and it naturally accommodates a trapezoidal traction separation law (TSL) whose shape can be varied to model either ductile interface behavior or brittle interface behavior. The formulation's performance is assessed through modeling a patch test and a compact tension specimen.

42 ENGINEERING↗

NASA NTRS1982

GRAVSAT error analysis by means of global spectral analyses of the marine geoid from SEASAT altimeter data

The geographical variability of short wavelength geoid power spectra (geoid roughness), was mapped for the world's oceans between latitudes 72 deg N and 72 deg S. A spectral analysis of SEASAT altimeter data, reduced to sea surface heights, was performed at 2 minute intervals for 15 consecutive days of the 3-day repeat orbit. The geoid roughness represented by these spectra for wavelengths shorter than about 220 km is separated from the total sea height variance and is displayed in the form of a global contour map. The global average geoid roughness is 32 cm RMS, varying from a high in excess of 2 m RMS near deep ocean trenches to a low of 2 cm RMS in the southeast Pacific near the East Pacific Rise. This average value agrees well with previous estimates based on gravimetry and GEOS-3 altimetry. In general, the smoothest areas in the marine geoid overlie relatively young seafloor adjacent mid-ocean spreading centers, where even short-wavelength topographic variations tend to be isostatically compensated.

Source record↗

NASA NTRS1987

Comets

Observations of comets obtained with the IUE satellite since its launch in 1978 are reviewed. The status of UV observation of comets prior to IUE is discussed, and particular attention is given to low-resolution UV spectroscopy of cometary comae, the detection of new species in the UV emission, high-dispersion spectroscopy, spatial mapping of the emissions, abundance determinations, and short-term variability. Diagrams, graphs, sample spectra, and tables of numerical data are provided.

Festou, M. C.↗

NASA NTRS1994

Global QBO in circulation and ozone. Part 2: A simple mechanistic model

Although the phenomenon of equatorial quasi-biennial oscillation is relatively well understood, the problem of how the equatorially confined quasi-biennial oscillation (QBO) wave forcing can induce a signal in the extratropics of comparable or larger magnitude remains unsolved. A simple mechanistic model is constructed to provide a quantitative test of the hypothesis that the phenomenon of extratropical QBO is mainly caused by an anomalous seasonal circulation induced by an anomalous Eliassen-Palm (E-P) flux divergence. The anomaly in E-P flux divergence may be caused in turn by the relative poleward and downward shift of the region of irreversible mixing (breaking) of the extratropical planetary waves during the easterly phase of the equatorial QBO as compared to its westerly phase. The hemispheric nature of the anomaly wave forcing in solstice seasons (viz., no wave breaking in the summer hemisphere) induces a global circulation anomaly that projects predominantly into the first few zonal Hough modes of Plumb. Such a global QBO circulation pattern, although difficult to measure directly, is reflected in the distribution of stratospheric tracers transported by it. Our model produces a global pattern of QBO anomaly in column ozone that appears to account for much of the unfiltered interannual variability in the column ozone observed by the total ozone mapping spectrometer (TOMS) instrument aboard the Nimbus satellite. Furthermore, the model produces the characteristic spectrum of the observation with peaks at periods of 20 and 30 months.

Tung, K. K.↗

NASA NTRS1997

Satellite Sensed Skin Sea Surface Temperature

Quantitative predictions of spatial and temporal changes the global climate rely heavily on the use of computer models. Unfortunately, such models cannot provide the basis for climate prediction because key physical processes are inadequately treated. Consequently, fine tuning procedures are often used to optimize the fit between model output and observational data and the validation of climate models using observations is essential if model based predictions of climate change are to be treated with any degree of confidence. Satellite Sea Surface Temperature (SST) observations provide high spatial and temporal resolution data which is extremely well suited to the initialization, definition of boundary conditions and, validation of climate models. In the case of coupled ocean-atmosphere models, the SST (or more correctly the 'Skin' SST (SSST)) is a fundamental diagnostic variable to consider in the validation process. Daily global SST maps derived from satellite sensors also provide adequate data for the detection of global patterns of change which, unlike any other SST data set, repeatedly extend into the southern hemisphere extra-tropical regions. Such data are essential to the success of the spatial 'fingerprint' technique, which seeks to establish a north-south asymmetry where warming is suppressed in the high latitude Southern Ocean. Some estimates suggest that there is a greater than 80% chance of directly detecting significant change (97.5 % confidence level) after 10-12 years of consistent global observations of mean sea surface temperature. However, these latter statements should be qualified with the assumption that a negligible drift in the observing system exists and that biases between individual instruments required to derive a long term data set are small. Given that current estimates for the magnitude of global warming of 0.015 K yr(sup -1) - 0.025 K yr(sup -1), satellite SST data sets need to be both accurate and stable if such a warming trend is to be confidently detected. Some of these activities are focussed to develop and deploy instrumentation suitable for the collection of precise in situ measurements of the SSST which can be used to improve the accuracy of satellite measurements, while others develop techniques to generate improved global analyses of sea surface temperature using historical data.

Donlon, Craig↗

NASA NTRS1999

Precision Interval Estimation of the Response Surface by Means of an Integrated Algorithm of Neural Network and Linear Regression

The integration of Radial Basis Function Networks and Back Propagation Neural Networks with the Multiple Linear Regression has been accomplished to map nonlinear response surfaces over a wide range of independent variables in the process of the Modem Design of Experiments. The integrated method is capable to estimate the precision intervals including confidence and predicted intervals. The power of the innovative method has been demonstrated by applying to a set of wind tunnel test data in construction of response surface and estimation of precision interval.

Lo, Ching F.↗

NASA NTRS2000

Object Based Numerical Zooming Between the NPSS Version 1 and a 1-Dimensional Meanline High Pressure Compressor Design Analysis Code

Within NASA's High Performance Computing and Communication (HPCC) program, NASA Glenn Research Center is developing an environment for the analysis/design of propulsion systems for aircraft and space vehicles called the Numerical Propulsion System Simulation (NPSS). The NPSS focuses on the integration of multiple disciplines such as aerodynamics, structures, and heat transfer, along with the concept of numerical zooming between 0- Dimensional to 1-, 2-, and 3-dimensional component engine codes. The vision for NPSS is to create a "numerical test cell" enabling full engine simulations overnight on cost-effective computing platforms. Current "state-of-the-art" engine simulations are 0-dimensional in that there is there is no axial, radial or circumferential resolution within a given component (e.g. a compressor or turbine has no internal station designations). In these 0-dimensional cycle simulations the individual component performance characteristics typically come from a table look-up (map) with adjustments for off-design effects such as variable geometry, Reynolds effects, and clearances. Zooming one or more of the engine components to a higher order, physics-based analysis means a higher order code is executed and the results from this analysis are used to adjust the 0-dimensional component performance characteristics within the system simulation. By drawing on the results from more predictive, physics based higher order analysis codes, "cycle" simulations are refined to closely model and predict the complex physical processes inherent to engines. As part of the overall development of the NPSS, NASA and industry began the process of defining and implementing an object class structure that enables Numerical Zooming between the NPSS Version I (0-dimension) and higher order 1-, 2- and 3-dimensional analysis codes. The NPSS Version I preserves the historical cycle engineering practices but also extends these classical practices into the area of numerical zooming for use within a companies' design system. What follows here is a description of successfully zooming I-dimensional (row-by-row) high pressure compressor results back to a NPSS engine 0-dimension simulation and a discussion of the results illustrated using an advanced data visualization tool. This type of high fidelity system-level analysis, made possible by the zooming capability of the NPSS, will greatly improve the fidelity of the engine system simulation and enable the engine system to be "pre-validated" prior to commitment to engine hardware.

Follen, G.↗

NASA NTRS2013

The Hyperspectral Infrared Imager (HyspIRI) Public Health and Air Quality Applications

The neglected tropical diseases (NTDs), a group of chronic, debilitating, and poverty-promoting parasitic, bacterial, and some viral and fungal infections, are among the most common causes of illness of the poorest people living in developing countries. Abiotic environmental factors are important in determining the distribution of disease-causing vectors and their life-cycles. HyspIRI observations can be merged through a Land Data Assimilation System (LDAS) be used to drive spatially-explicit ecological models of NTD vectors distribution & life cycles. Assimilations will be driven by observational data LDAS and satellite-derived meteorological forcing data, parameter datasets, and assimilation observations. HyspIRI hyperspectral measurements would provide global measurements of surface mineralogy and biotic crusts important in accessing the impact of dust in human health. HyspIRI surface thermal measurements would also help identify the variability of dust sources due to surface moisture conditions and map mineralogy.

Luvall, Jeffrey C.↗

NASA NTRS2013

The Hyperspectral Infrared Imager (HyspIRI) Public Health and Air Quality Applications

Luvall, Jeffrey C.↗

NASA NTRS2013

The Hyperspectral Infrared Imager (HyspIRI) Public Health & Air Quality Applications

Luvall, Jeffrey C.↗

NASA NTRS2013

Laboratory Instruments Available to Support Space Station Researchers at Marshall Space Flight Center

A number of research instruments are available at NASA's Marshall Space Flight Center (MSFC) to support ISS researchers and their investigations. These modern analytical tools yield valuable and sometimes new informative resulting from sample characterization. Instruments include modern scanning electron microscopes equipped with field emission guns providing analytical capabilities that include angstron-level image resolution of dry, wet and biological samples. These microscopes are also equipped with silicon drift X-ray detectors (SDD) for fast yet precise analytical mapping of phases, as well as electron back-scattered diffraction (EBSD) units to map grain orientations in crystalline alloys. Sample chambers admit large samples, provide variable pressures for wet samples, and quantitative analysis software to determine phase relations. Advances in solid-state electronics have also facilitated improvements for surface chemical analysis that are successfully employed to analyze metallic materials and alloys, ceramics, slags, and organic polymers. Another analytical capability at MSFC is a mganetic sector Secondary Ion Mass Spectroscopy (SIMS) that quantitatively determines and maps light elements such as hydrogen, lithium, and boron along with their isotopes, identifies and quantifies very low level impurities even at parts per billion (ppb) levels. Still other methods available at MSFC include X-ray photo-electron spectroscopy (XPS) that can determine oxidation states of elements as well as identify polymers and measure film thicknesses on coated materials, Scanning Auger electron spectroscopy (SAM) which combines surface sensitivity, spatial lateral resolution (approximately 20 nm), and depth profiling capabilities to describe elemental compositions in near surface regions and even the chemical state of analyzed atoms. Conventional Transmission Electron Microscope (TEM) for observing internal microstructures at very high magnifications and the Electron Probe Micro-analyzer (EPMA) for very precise microanalysis are available as needed by the researcher. Space Station researchers are invited to work with MSFC in analyzing their samples using these techniques.

Panda, Binayak↗

NASA NTRS2014

The Hyperspectral Infrared Imager (HyspIRI) Public Health and Air Quality Applications

The neglected tropical diseases (NTDs), a group of chronic, debilitating, and poverty-promoting parasitic, bacterial, and some viral and fungal infections, are among the most common causes of illness of the poorest people living in developing countries. Abiotic environmental factors are important in determining the distribution of disease-causing vectors and their life-cycles. HyspIRI observations can be merged through a Land Data Assimilation System (LDAS) be used to drive spatially-explicit ecological models of NTD vectors distribution and life cycles. Assimilations will be driven by observational data LDAS and satellite-derived meteorological forcing data, parameter datasets, and assimilation observations. HyspIRI hyperspectral measurements would provide global measurements of surface mineralogy and biotic crusts important in accessing the impact of dust in human health. HyspIRI surface thermal measurements would also help identify the variability of dust sources due to surface moisture conditions and map mineralogy.

Luvall, Jeffrey C.↗

NASA NTRS2022

Northeast US Ecological Forecasting: Modeling Invasive Plant Habitat Suitability to Support Management Efforts in the American Northeast

Invasive plant species threaten environmental and economic interests when they spread into new areas, outcompete native species, and disrupt ecosystem services. If the spread is not controlled early, species can become well-established and increasingly difficult to manage. The National Park Service (NPS) Invasive Plant Management Teams (IPMTs) strive for an “early detection, rapid response” approach to reducing invasive species spread. Management teams can better prioritize their work with the help of species distribution models (SDMs), which map habitat suitability by combining species occurrences with environmental predictor variables. Scarce invaded range data for newly arrived invasive species presents a particular challenge for producing accurate models. To improve future modeling efforts, this project compared SDM methods using different spatial scales to model two plant species invasive to the Northeast US: the well-established Japanese stiltgrass (Microstegium vimineum) and newer invasive species wavyleaf basketgrass (Oplismenus undulatifolius). The team used NASA Earth observations and climate datasets to model occurrence data and predictor layers at a US-specific extent (90m2 spatial resolution) and global extent (1 km2 spatial resolution). Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Operational Land Imager (OLI) provided data for US Normalized Difference Moisture Indices (NDMI), while global NDMI and topographic predictor layers were derived from Shuttle Radar Topography Mission (SRTM) and Terra Moderate Resolution Imaging Spectroradiometer (MODIS). The resulting models indicated important predictor variables for each species and explored the benefits and tradeoffs of using global data to model habitat suitability for new-arrival invasive species.

Rebecca Ohman↗