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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Further development of the losipescu shear test method

Recent activities by the present investigators to further develop the losipescu-shear-test method for use with composite materials are summarized. Finite-element analyses used to predict the stress states in the specimen are described, with particular emphasis on how they are influenced by the specific test-fixture configuration used. These same analytical tools were also used to predict the influence of specimen notch depth, notch angle, and notch-root radius. The result was a redesign of the original Wyoming version of the losipescu-shear-test fixture, and the establishment of guidelines for preparing specimens. These are discussed in some detail. Many references to available literature are included. An attempt has been made to put the work performed to date into perspective, to aid the potential user of the losipescu-shear-test method in establishing proper test procedures.

Adams, D. F.↗
NASA NTRS1992

Deformational mass transport and invasive processes in soil evolution

Channels left in soil by decayed roots and burrowing animals allow organic and inorganic precipitates and detritus to move through soil from above, to depths at which the minuteness of pores restricts further passage. Consecutive translocation-and-root-growth phases stir the soil, constituting an invasive, dilatational process which generates cumulative strains. Below the depths thus affected, mineral dissolution by descending organic acids leads to internal collapse; this softened/condensed precursor horizon is then transformed into soil via biological activity that mixes and expands the evolving residuum through root and micropore-network invasion.

Brimhall, George H.↗
NASA NTRS2019

Estimating Alpine Snow Depth by Combining Multi-Frequency Passive Radiance Observations with Ensemble Snowpack Modeling

This paper presents a physically-based snow depth retrieval algorithm adapted for deep mountainous snowpack and airborne multifrequency (10.7, 18.7, 37.0 and 89.0 GHz) passive microwave (PM) radiance observations from a single flight. The algorithm employs a single forecast-analysis cycle of a traditional sequential assimilation scheme. It uses an ensemble of multi-layer snowpack model runs to resolve snow microstructure and melt-refreeze crusts, andmicrowave radiative transfer models to relate snow properties to microwave measurements.Snow depth was retrieved at a 120 m spatial resolution over three 1 km2 Intensive Study Area (ISA) within the Rabbit Ears Meso-Cell Study Area (MSA) from the NASA Cold Land Processes Experiment (CLPX) in Colorado (United States) for one date in February 2003. When evaluated against in situ observations, root mean square error (RMSE) of the snow depth from the assimilation was 13.3 cm for areas with low (<5 %) forest cover, which was a reduction of 48 % in the RMSE compared with the modeled snow depth when the PM observations were not assimilated; indicating a ~5% relative error of the posterior snow depth with respect to the average snow depth (200 cm) measured at these pixels. For pixels with forest cover ranging from 5-15% and 15-30%, results were improved (R2 increased from 0.65 to 0.71 and from 0 to 0.38, respectively) by introducing a forest radiative transfer model during the assimilation.

Airborne Multifrequency↗
NASA NTRS1976

Overall evaluation of LANDSAT (ERTS) follow-on imagery for cartographic application

The author has identified the following significant results. The NASA/Cousteau experiment showed that under suitable conditions and with calibration data, the bottom of clear tropical seas can be mapped with LANDSAT to a depth of 22 meters with a root-mean-square error of about 10 percent. This application required the high gain setting of band 4 of the MSS. The experiment also confirmed that a somewhat lower waveband than band 4 would increase the water penetration capability of future LANDSATS. Other experiments illustrated by the reprinting of upper Chesapeake Bay indicate that the original LANDSAT signals must be modulated and optimized for the photographic and lithographic processes. Work by the Canadian mapping agency indicates significant improvements in the control identification and geometric accuracy of LANDSAT cartographic applications.

Colvocoresses, A. P.↗
NASA NTRS1989

A parameterization of the depth of the entrainment zone

A theory of the parameterization of the entrainment zone depth has been developed based on conservation of energy. This theory suggests that the normalized entrainment zone depth is proportional to the inverse square root of the Richardson number. A comparison of this theory with atmospheric observations indicates excellent agreement. It does not adequately predict the laboratory data, although it improves on parcel theory, which is based on a momentum balance.

Boers, Reinout↗
NASA NTRS1993

An evaluation of the National Meteorological Center weekly hindcast of upper-ocean temperature along the eastern Pacific equator in January 1992

The upper-ocean temperature distribution along the Pacific equator from 139 to 103 deg W was observed in January 1992 with temperature profiles recorded from a ship and inferred from an ocean general circulation model calculation involving data assimilation (i.e., hindcast). An El Nino episode was in progress. The l00-m-thick mixed layer depth, the mixed-layer temperature, and the depth-averaged temperature below the thermocline were similar in both data products. Considerable differences occurred in the representation of the 15-25 C thermocline, such as the depth-averaged temperatures above and below the 20 C isotherm, the east-west slope of the 20 C isotherm, and a 1000-km-wide depression. The longitudinal-averaged root-mean-square difference between the hindcast and observed depths of the center of the thermocline was 17 m. Most of the disparities could be attributed to a high wavenumber transient event that the model-based assimilation system was not intended to resolve.

Halpern, David↗
NASA NTRS2018

The NASA Eulerian Snow on Sea Ice Model (NESOSIM) v1.0: initial model development and analysis

The NASA Eulerian Snow On Sea Ice Model (NESOSIM) is a new, open-source snow budget model that is currentlyconfigured to produce daily estimates of the depth and density of snow on sea ice across the Arctic Ocean throughthe accumulation season. NESOSIM has been developed in a three-dimensional Eulerian framework and includes two(vertical) snow layers and several simple parameterizations (accumulation, wind packing, advection_divergence, blowingsnow lost to leads) to represent key sources and sinks of snow on sea ice. The model is forced with daily inputs of snowfall and near-surface winds (from reanalyses), sea ice concentration (from satellite passive microwave data) and sea ice drift (from satellite feature tracking) during the accumulation season (August through April). In this study, we present the NESOSIM formulation, calibration efforts, sensitivity studies and validation efforts across an Arctic Ocean domain (100 km horizontal resolution). The simulated snow depth and density are calibrated with in situ data collected on drifting ice stations during the 1980s. NESOSIM shows strong agreement with the in situ seasonal cycles of snow depth and density, and shows good (moderate) agreement with the regional snow depth (density) distributions. NESOSIM is run for a contemporary period (2000 to 2015), with the results showing strong sensitivity to the reanalysis derived snowfall forcing data, with the Modern-Era Retrospective analysis for Research and Applications (MERRA) and the Japanese Meteorological Agency 55-year reanalysis (JRA-55) forced snow depths generally higher than ERA-Interim,and the Arctic System Reanalysis (ASR) generally lower. We also generate and force NESOSIM with a consensus "median" daily snowfall dataset from these reanalyses.The results are compared against snow depth estimates derived from NASA's Operation IceBridge (OIB) snow radar data from 2009 to 2015, showing moderate_strong correlations and root mean squared errors of 10 cm depending on the OIB snow depth product analyzed, similar to the comparisons between OIB snow depths and the commonly used modified Warren snow depth climatology. Potential improvements to this initial NESOSIM formulation are discussed in the hopes of improving the accuracy and reliability of these simulated snow depths and densities.

Petty, Alek A.↗
NASA NTRSDate not supplied

Snow Depth from AMSR-2 Using Multispectral Satellite Data in an Artificial Neural Network

By using diffusion theory and Monte Carlo lidar radiative transfer simulations, Hu et al. (2022b) has derived snow depth from the first-, second- and third-order moments of the lidar backscattering pathlength distribution. Lu et al. (2022) calculated the snow depth by applying the methods to the satellite ICESat-2 lidar measurements over the Arctic sea ice, as well as land surfaces of Northern Hemisphere. In this paper, an artificial neural network (ANN) algorithm, employing several channels from Advanced Microwave Scanning Radiometer 2 (AMSR-2) and the humidity vertical profiles from Global Modeling and Assimilation Office (GMAO) Goddard Earth Observing System for Instrument Teams (GEOS-IT) product, is trained to determine snow depth identified by time and geolocation matched 2019 ICESat-2 snow-depth data during winter months over the Arctic sea ice. The trained ANN snow-depth was applied to 2018 AMSR-2 clear pixel data, although the algorithms perform reasonably well in thinner clouds. The validation data (different from the training set) of ANN snow depth from AMSR-2 showed a good agreement with time matched and co-located snow-depth values from ICESat-2. The bias was near zero, with mean absolute error (MAE) 0.05 cm and a root-mean-square-error (RMSE) 0.08 cm. Prior applying the trained ANN snow depth to AMSR-2 data, a cloud screening algorithm was developed with a similar approach. A separate ANN cloud mask was trained to determine an AMSR-2 pixel is clear or cloudy with time and geolocation matched 2015 CALIOP Vertical Feature Mask (VFM) over Arctic sea ice. The ANN cloud mask from AMSR-2 under-estimated cloud fraction by 3-6% compared to CALIOP . The additional research is needed to conclusively evaluate the ANN cloud mask accuracy. Finally, this paper will lay the foundation for a sustained long-term snowfall and snow-storm monitoring system. The future Cloud Aerosol LIdar for Global scale Observations of the ocean-Land Atmosphere system (CALIGOLA) mission will provide a means to calculate snow depth from the lidar backscattering pathlength distribution, benefiting from the UV, visible and infrared pulses. With the calculated snow depth as the truth one could develop a machine learning algorithm, as it was done in this paper, using a passive microwave instrument available at that time to generate a wide range of snow depth data, covering extensive spatial areas in the cross-orbit direction.

Neural Network↗
NASA NTRS1974

Computer extension and analytic continuation of Stokes' expansion for gravity waves

Stokes' infinitesimal-wave expansion for steady progressive free-surface waves has been extended to high order using a computer to perform the coefficient arithmetic. Stokes' expansion has been found to be incapable of yielding the highest wave for any value of the water depth since convergence is limited by a square-root branch-point some distance short of the maximum. By reformulating the problem using a different independent parameter, the highest waves are obtained correctly. Series summation and analytic continuation are facilitated by the use of Pade approximants. The method is valid in principle for any finite value of the wavelength and solutions of high accuracy can be obtained for most values of the wave height and water depth.

Schwartz, L. W.↗
NASA NTRS1990

Comparison of the ultrastructure of conventionally fixed and high pressure frozen/freeze substituted root tips of Nicotiana and Arabidopsis

To circumvent the limitations of chemical fixation (CF) and to gain more reliable structural information about higher plant tissues, we have cryofixed root tips of Nicotiana and Arabidopsis by high pressure freezing (HPF). Whereas other freezing techniques preserve tissue to a relatively shallow depth, HPF in conjunction with freeze substitution (FS) resulted in excellent preservation of entire root tips. Compared to CF, in tissue prepared by HPF/FS: (1) the plasmalemma and all internal membranes were much smoother and often coated on the cytoplasmic side by a thin layer of stained material, (2) the plasmalemma was appressed to the cell wall, (3) organelle profiles were rounder, (4) the cytoplasmic, mitochondrial, and amyloplast matrices were denser, (5) vacuoles contained electron dense material, (6) microtubules appeared to be more numerous and straighter, with crossbridges observed between them, (7) cisternae of endoplasmic reticulum (ER) were wider and filled with material, (8) Golgi intercisternal elements were more clearly resolved and were observed between both Golgi vesicles and cisternae, and (9) larger vesicles were associated with Golgi stacks. This study demonstrates that HPF/FS can be used to successfully preserve the ultrastructure of relatively large plant tissues without the use of intracellular cryoprotectants.

NASA Program Space Biology↗
NASA NTRS1980

A simplified method for the calculation of diurnally averaged photodissociation rates

Expressions are given for the calculation of the diurnally averaged transmission of solar flux from a series summation involving relatively few terms and readily available mathematical functions. It is shown that these expressions can be scaled to remove much of the dependence on latitude and solar declination so that at large optical depth, they become asymptotic to a function which depends only on the optical depth at noon and displays an inverse-square-root variation. From this variation, a simple analytic form containing one adjustable parameter is proposed. The functional dependence of this parameter on latitude and solar declination is determined by numerical fitting procedures. The accuracy of the analytic approximation is better than 4.5% for all altitudes, latitudes and seasons of the year.

Boughner, R. E.↗
NASA NTRS1993

Effect of Long-Term 1093 K Exposure to Air or Vacuum on the Structure of Several Wrought Superalloys

Long-term 1093 K heat treatments of three commercial superalloy sheet materials were undertaken in air -IAI and vacuum. With either exposure, significant precipitation of second phases occurred in the Co-base Haynes(R) Alloy 188 (HA 188) and the Ni-base Haynes(R) Alloy 230 (HA 230); however, much less precipitation was found in the exposed Ni-base alloy Inconel(R) 617 (IN 617). Although some grain growth occurred in HA 198, no changes in the grain size of either HA 230 or IN 617 were observed after 22,500 h at temperature. Oxidation during air heat treatments led to weight gain due to the formation of chromia + spinel scales and surface-connected grain boundary pits/oxides in all three superalloys. Both the weight gain and depth of intergranular attack were dependent on the square root of time, which is indicative of diffusion-controlled phenomena. Because many alloy samples had neighbors in close proximity, most vacuum heat treated specimens did not suffer significant loss of volatile elements. However, some exposed samples were subjected to unrestricted vacuum heat treatments, allowing estimates of volatilization to be made. Based on the data for HA 188, the weight loss during 1093 K vacuum exposure was diffusion controlled once the inhibiting effects of surface films on the as-received alloys were broken down.

J.D. Whittenberger↗
NASA NTRS2018

Global Relationships Among Traditional Reflectance Vegetation Indices (NDVI and NDII), Evapotranspiration (ET), and Soil Moisture Variability on Weekly Time Scales

Monitoring the effects of water availability on vegetation globally using satellites is important for applications such as drought early warning, precision agriculture, and food security as well as for more broadly understanding relationships between water and carbon cycles. In this global study, we examine how quickly several satellite-based indicators, assumed to have relationships with water availability, respond, on timescales of days to weeks, in comparison with variations in root-zone soil moisture (RZM) that extends to about 1 m depth. The satellite indicators considered are the normalized difference vegetation and infrared indices (NDVI and NDII, respectively) derived from reflectances obtained with moderately wide (20–40 nm) spectral bands in the visible and near-infrared (NIR) and evapotranspiration (ET) estimated from thermal infrared observations and normalized by a reference ET. NDVI is primarily sensitive to chlorophyll contributions and vegetation structure while NDII may contain additional information on water content in leaves and canopy. ET includes both the loss of root zone soil water through transpiration (modulated by stomatal conductance) as well as evaporation from bare soil. We find that variations of these satellite-based drought indicators on time scales of days to weeks have significant correlations with those of RZM in the same water-limited geographical locations that are dominated by grasslands, shrublands, and savannas whose root systems are generally contained within the 1 m RZM layer. Normalized ET interannual variations show generally a faster response to water deficits and enhancements as compared with those of NDVI and NDII, particularly in sparsely vegetated regions.

Joanna Joiner↗
NASA NTRS1997

Computer based imaging and analysis of root gravitropism

Two key issues in studies of the nature of the gravitropic response in roots have been the determination of the precise pattern of differential elongation responsible for downward bending and the identification of the cells that show the initial motor response. The main approach for examining patterns of differential growth during root gravitropic curvature has been to apply markers to the root surface and photograph the root at regular intervals during gravitropic curvature. Although these studies have provided valuable information on the characteristics of the gravitropic motor response in roots, their labor intensive nature limits sample size and discourages both high frequency of sampling and depth of analysis of surface expansion data. In this brief review we describe the development of computer-based video analysis systems for automated measurement of root growth and shape change and discuss some key features of the root gravitropic response that have been revealed using this methodology. We summarize the capabilities of several new pieces of software designed to measure growth and shape changes in graviresponding roots and describe recent progress in developing analysis systems for studying the small, but experimentally popular, primary roots of Arabidopsis. A key finding revealed by such studies is that the initial gravitropic response of roots of maize and Arabidopsis occurs in the distal elongation zone (DEZ) near the root apical meristem, not in the main elongation zone. Another finding is that the initiation of rapid elongation in the DEZ following gravistimulation appears to be related to rapid membrane potential changes in this region of the root. These observations have provided the incentive for ongoing studies examining possible links between potential growth modifying factors (auxin, calcium, protons) and gravistimulated changes in membrane potential and growth patterns in the DEZ.

NASA Discipline Plant Biology↗
NASA NTRS1979

The radiation pressure-driven Rayleigh-Taylor instability - Analysis and application to QSO emission line clouds

The growth of perturbations in a photoionized gas slab accelerated by radiation pressure under conditions like those in QSO emission-line regions is analyzed. A linear dispersion relation is derived, and numerical radiation-transfer calculations are performed to evaluate the coefficients and roots of that dispersion relation for L-alpha optical depths between 0.1 and 10,000. The nonlinear growth of the waves is estimated, and it is concluded that complete dispersal of the clouds is likely. On the basis of qualitative arguments it is suggested that clouds of greater optical depth are linearly stable.

Krolik, J. H.↗
NASA NTRS1983

A non-Gaussian statistical model for surface elevation of nonlinear random wave fields

Probability density function of the surface elevation of a nonlinear random wave field is obtained. The wave model is based on the Stokes expansion carried to the third order for both deep water waves and waves in finite depth. The amplitude and phase of the first-order component of the Stokes wave are assumed to be Rayleigh and uniformly distributed and slowly varying, respectively. The probability density function for the deep water case was found to depend on two parameters: the root-mean-square surface elevation and the significant slope. For water of finite depth, an additional parameter, the nondimensional depth, is also required. An important difference between the present result and the Gram-Charlier representation is that the present probability density functions are always nonnegative. It is also found that the 'constant' term in the Stokes expansion, usually neglected in deterministic studies, plays an important role in determining the details of the density function. The results compare well with laboratory and field experiment data.

Huang, N. E.↗
NASA NTRS2023

Towards Soil Moisture Profile Estimation in the Root Zone Using L- and P-Band Radiometer Observations: A Coherent Modelling Approach

Precision irrigation management and crop water stress assessment rely on accurate estimation of root zone soil moisture. However, only the top 5cm soil moisture can be estimated using the two current passive microwave satellite missions, Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP), which operate at L-band (wavelength of ~21cm). Since the contributing depth of the soil to brightness temperature increases with observation wavelength, it is expected that a P-band (wavelength of ~40cm) radiometer could potentially provide soil moisture information from deeper layers of the soil profile. Moreover, by combining both L- and P- bands, it is hypothesized that the soil moisture profile can be estimated even beyond their individual observation depths. The aim of this study was to demonstrate the potential of combined L-band and P-band radiometer observations to estimate the soil moisture profile under flat bare soil using a stratified coherent forward model. Brightness temperature observations at L-band and P-band from a tower based experimental site across a dry (April 2019) and a wet (March 2020) period, covering different soil moisture profile shapes, were used in this study. Results from an initial synthetic study showed that the performance of a combined L-band and P-band approach was better than the performance of using either band individually, with an average depth over which reliable soil moisture profile information could be estimated (i.e. with a target root mean square error (RMSE) of less than 0.04 m3/m3) being 20cm for linear and 15cm for second-order polynomial functions. Other functions were also tested but found to have a poorer performance. Applying the method to the tower-based brightness temperature achieved an average estimation depth of 28cm (20cm) and 5cm (5cm) during the dry and wet periods respectively when using a second-order polynomial (linear) function. These findings highlight the opportunity of a satellite mission with L-band and P-band observations to accurately estimate the soil moisture profile to as deep as 30cm globally.

Foad Brakhasi↗
NASA NTRS1982

Applications of remote sensing to geobotanical prospecting for non-renewable resources

Airborne sensors used in the remote detection of geobotanical anomalies are able to locate mineral deposits. Geobotanical stress is manifested in increased visible spectrum reflectance due to a decrease in chlorophyll content which induces chlorosis. The effectiveness of this method is, however, restricted to soils in which plant root structures are embedded in bedrock-derived soils to a depth sufficient for the production of heavy metal stress. It is noted that Landsat remote sensors are inherently better suited to the detection of overall plant density or biomass changes relating to zones of mineralization.

Birnie, R. W.↗