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At least 127 records · Page 7

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DOE OSTI2020

Drivers for the cracking of multilayer polyamide‐based backsheets in field photovoltaic modules: In‐depth degradation mapping analysis

Abstract There is a lack of understanding on the root cause of cracking of photovoltaic (PV) backsheets due to the challenge of multilayer characterization and the complicated failure modes at the submodule level. In this work, the in‐depth degradation mapping of field‐exposed polyamide‐based (PA‐based) PV module backsheets was studied, with the major focus on the identification of underlying drivers for the through cracking (in between the solar cells). PV modules were retrieved from five different locations, comprising a variety of climates, including humid subtropical, hot‐summer Mediterranean, tropical savanna climate, and hot arid. A suite of microscale cross‐sectional characterizations, including chemical changes, fluorescence intensity, and modulus as a function of distance from the air surface of the backsheet, was performed. Results showed more advanced signs of degradation of the inner layer than the outer layer in the cracking region. Increases in the modulus were identified as the major indicator for the cracking. Moreover, a rudimentary test by immersion in acetic acid, which forms during photodegradation of the ethylene‐vinyl acetate copolymer (EVA) encapsulant, showed the first‐time direct evidence that acetic acid can largely accelerate the chemical degradation and facilitate the cracking of PA inner layer. This study suggests that the field cracking of PA‐based backsheet can be attributed to the combined effects of chemical degradation and physical reorganization (chemi‐crystallization) under cyclic thermomechanical stresses. Therefore, it is important to consider effects of local microclimates and interlayer infection to understand the heterogeneous nature of backsheet failures.

Lyu, Yadong↗

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↗

DOE OSTI2022

Castanha et al. 2018: Hopland Lysimeter 13C-Labeled Root Litter Decomposition Study.

The breakdown and decomposition of plant inputs are critical for nutrient cycling, soil development, and climate-ecosystem feedbacks, but uncertainties persist in how the rates and products of litter decomposition are affected by soil temperature, rhizosphere, and depth of input. To elucidate these questions we measured the effects of soil warming (+ 4 °C), rhizosphere, and depth of litter placement on the decomposition of Avena fatua (wild oat grass) root litter in a Mediterranean grassland ecosystem. Field lysimeters were subjected to three environmental treatments (heating, control, and plant removal) and three 13C-labeled root litter addition treatments (to A horizon, to B horizon, and no-addition disturbance control) for each of two harvest time points. We buried root litter in February 2014 and measured loss of 13C in CO2 from the soil surface and in leachate as dissolved organic carbon (DOC) over two growing seasons. At the end of each of the 2014 and 2015 growing seasons we recovered the 13C remaining in the soil. Loss of root litter C occurred almost entirely via heterotrophic respiration, with an estimated < 2% lost as DOC during the initial decay period. The added roots were broken down and incorporated into bulk soil material very quickly; only ~ 30% of added root was visible after 6 months. In the first growing season, decomposition occurred faster in the B than in the A horizon, the latter having greater moisture limitation. Subsequently, there was almost no further decomposition in the B horizon. After two growing seasons, less than 20% of the added root litter C remained in the A or B horizons of all environmental treatments. Heating did not stimulate decomposition, likely because it exacerbated the moisture limitation. However, while plots without plants dried down more slowly than plots with plants, their decomposition rate was not significantly greater, possibly due to the lack of rhizosphere processes such as priming. We conclude that in this Mediterranean grassland ecosystem, soil moisture, which is affected by season, depth, heating, and rhizosphere, plays a dominant role in mediating the effect of those factors on root litter decomposition, which after two seasons did not differ by depth or by treatment.The files in this dataset comprise (1) 13C-labeled litter additions made to each plot, (2) litter recovery after each of 2 growing seasons, (3) periodical soil flux measurements, (4) leachate measurements, and continuously monitored soil (5) temperature and (6) moisture.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Hydraulic redistribution by deeply rooted grasses and its ecohydrologic implications in the southern Great Plains of North America

Perennial bioenergy crops with deep (>1 m) rooting systems, such as switchgrass (Panicum virgatum L.), are hypothesized to increase carbon storage in deep soil. Deeply rooted plants may also affect soil hydrology by accessing deep soil water for transpiration, which can affect soil water content and infiltration in deep soil layers, thereby affecting groundwater recharge. Using stable H and O isotope (δ 2 H and δ 18 O) and 3 H values, we studied the soil water conditions at 20–30 cm intervals to depths of 2.4–3.6 m in paired fields of switchgrass and shallow rooted crops at three sites in the southern Great Plains of North America. We found that soil under switchgrass had consistently higher soil water content than nearby soil under shallow-rooted annual crops by a margin of 15%–100%. Soil water content and isotopic depth profiles indicated that hydraulic redistribution of deep soil water by switchgrass roots explained these observed soil water differences. To our knowledge, these are the first observations of hydraulic redistribution in deeply rooted grasses, and complement earlier observations of dynamic soil water fluxes under shallow-rooted grasses. Hydraulic redistribution by switchgrass may be a strategy for drought avoidance, wherein the plant may actively prevent water limitation. Furthermore, this raises the possibility that deeply rooted grasses may be used to passively subsidize soil water to more shallow-rooted species in inter-cropping arrangements.

3H↗

DOE OSTI2025

Geospatial modeling of near subsurface temperatures of the contiguous United States for assessment of materials degradation

Abstract Understanding subsurface temperature variations is crucial for assessing material degradation in underground structures. This study maps subsurface temperatures across the contiguous United States for depths from 50 to 3500 m, comparing linear interpolation, gradient boosting (LightGBM), neural networks, and a novel hybrid approach combining linear interpolation with LightGBM. Results reveal heterogeneous temperature patterns both horizontally and vertically. The hybrid model performed best achieving a root mean square error of 2.61 °C at shallow depths (50–350 m). Model performance generally decreased with depth, highlighting challenges in deep temperature prediction. State-level analyses emphasized the importance of considering local geological factors. This study provides valuable insights for designing efficient underground facilities and infrastructure, underscoring the need for depth-specific and region-specific modeling approaches in subsurface temperature assessment.

Science & Technology - Other Topics↗

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.↗

DOE OSTI2021

NGEE Arctic Plant Traits: Fine Roots, Kougarok Road Mile Marker 64, Seward Peninsula, Alaska, 2016

Soil cores were collected from twelve vegetation biomass plots at the Kougarok hillslope in late July of 2016. The sampled plots were located across six ecotypes present at this site (n=2 replicates per ecotype). Soil cores were separated into depth intervals in the field and frozen for transport to Oak Ridge National Laboratory. Data package contains one *.csv and one *.pdf.Laboratory sample processing of these soils generated depth-specific data on soil properties as well as fine root biomass, length, %C, %N, delta13C, and delta15N. Only live fine roots were analyzed. Fine roots were not separated by species or plant functional type.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

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.↗

DOE OSTI2024

Soil microenvironmental variation drives below‐ground trait variation and interacts with macroclimate to structure above‐ground trait variation of arctic shrubs

Abstract Intraspecific trait variation can influence plant performance in different environments and may thereby determine the ability of individual plants to respond to climate change. However, our understanding of its patterns and environmental drivers across different spatial scales is incomplete, especially in understudied regions like the Arctic. To fill this knowledge gap, we examined above‐ground and below‐ground traits from three shrub taxa expanding across the tundra biome and evaluated their relationships with multiple microenvironmental and macroclimatic factors. The traits reflected plant size and structure (plant height, leaf area and root to shoot ratio), leaf economics (specific leaf area, nitrogen content), and root economics and collaboration with mycorrhizal fungi (specific root length, root tissue density, nitrogen content, and ectomycorrhizal colonisation intensity). We also measured leaf and root δ 15 N and leaf δ 13 C to characterise nitrogen source and acquisition pathways and plant water stress. Traits were measured in replicated plots ( N = 135) varying in soil microclimate, thaw depth and organic layer thickness established across five sites spanning a macroclimate gradient in northern Alaska. This hierarchical design allowed us to disentangle the independent and combined effects of fine‐scale and broad‐scale factors on intraspecific trait variation. We found substantial intraspecific variation at fine spatial scales for most traits and less variation along the macroclimate gradient and between shrub taxa. Consistent with these patterns, microenvironmental factors, mainly soil moisture and thaw depth, interacted with macroclimate, mainly climatic water deficit, to structure size‐structural and leaf trait variation. In contrast, most root traits responded additively to thaw depth and macroclimate. Synthesis . Our results demonstrate that above‐ground and below‐ground tundra shrub traits respond differently to microenvironmental and macroclimatic variation. These differing responses contribute to substantial trait variation at fine spatial scales and may decouple above‐ground and below‐ground trait responses to climate change.

Environmental Sciences & Ecology↗

DOE OSTI2024

Study of ablation and shock generation across three orders of magnitude of laser intensity with 100 ps laser pulses

The laser ablation and subsequent shock generation in solid targets plays an important role in a variety of research topics from equation of state models for materials to inertial confinement fusion. One of the long-standing issues is the knowledge of ablation depth in the picosecond time regime. Here, we report on a direct technique for determining the ablation depth in aluminum using x-ray diffraction data from Linac Coherent Light Source at the Stanford Linear Accelerator Center. This technique gives a direct measurement of the shock wave propagation in the bulk target, enabling an ability to discern early timescale physics from late timescale effects not available in postmortem analysis. We find that the ablation depths only vary by 0.2 μm across three orders of magnitude of laser intensity, while the pressure increased by a factor of 10 following a square root dependence on laser pulse energy. We further observe that the ablation depth in this intensity range (10 11 –10 13 W/cm 2 in intensity, corresponding to 0.8–80 J/cm 2 in fluence) cannot be modeled by a universal scaling law, given the complexity of the mechanisms governing laser ablation in this intensity regime.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

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↗

DOE OSTI2020

Collar Properties and Measurement Time Confer Minimal Bias Overall on Annual Soil Respiration Estimates in a Global Database

Abstract Measuring the soil‐to‐atmosphere carbon dioxide (CO 2 ) flux (soil respiration, R S ) is important to understanding terrestrial carbon balance and to forecasting climate change. Such measurements are frequently made using measurement collars permanently inserted into the soil surface. However, differences in measurement duration and frequency, as well as collar properties, may lead to biases in the estimation of annual R S . Using a newly updated global R S database (SRDB‐V5), we investigated the annual R S bias associated with five methodological factors: collar height, collar coverage area, collar insertion depth, measurement duration, and measurement frequency. We found that annual R S was negatively correlated with collar insertion depth, consistent with the idea that collar insertion cuts roots and thus reduces R S . Annual R S was also negatively related with collar height and collar coverage area, perhaps because uniform head‐space mixing is difficult to achieve in larger volume chambers; however, these effects were quantitatively small (bias of ~2% to 10% of mean R S ). We found no correlation of measurement duration or measurement frequency with annual R S . These findings suggest that variation in R S methodology generally introduces minimal bias overall. Therefore, compilations of minimally adjusted annual R S measurements provide a reliable resource for synthesis studies, global annual R S modeling, and investigation of how soil carbon responds to climate change.

Jian, Jinshi↗

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↗