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At least 325 records · Page 18

Dispersion of surface-modified, aggregated, fumed silica in polymer nanocomposites

Surface modification of model silica to enhance compatibility in nanocomposites has been widely studied. In addition to model spherical silica, several authors have investigated the impact of surface conditions on compatibility in commercial aggregated carbon black and silica. Here, dispersion is investigated for a series of nanocomposites produced from commercially modified fumed silica mixed with styrene butadiene rubber, polystyrene, and polydimethylsiloxane. Surface modification includes variation in surface hydroxyl content, siloxane, and silane treatment. Qualitatively, hydroxyl groups on the silica surface are considered incompatible with non-polar polymers, while methyl groups are compatible with oleophilic polymers. X-ray scattering was used to analyze the filler aggregate structure before and after dispersion, and the second virial coefficient was used to quantify nanodispersion. The content of surface moieties was determined from Fourier-transform infrared spectroscopy. It is observed that modified silica can display mean field or specific interactions as reflected by the presence of a correlation peak in x-ray scattering. For systems with specific interactions, a critical ordering concentration is observed related to the free energy change for structuring. A van der Waals model was used to model the second virial coefficient as a function of accumulated strain, yielding the excluded volume and an energetic term. The excluded volume could be predicted from the structural information, and the bound polymer layer was directly related to the surface methyl content, whereas the energetic term was found to synergistically depend on both the methyl and hydroxyl surface content.

36 MATERIALS SCIENCE↗

Comprehensive Severe Weather Impact Assessment and Monitoring using Synthetic Aperture Radar and Auxiliary Data

Remote sensing datasets, particularly acquired by Synthetic Aperture Radar (SAR) sensors, have become increasingly important in severe weather disaster impact studies given their ability to observe the Earth largely irrespective of weather and sunlight conditions. The reliability of existing SAR change detection products applied on a pair of SAR images is constrained by the limitation of current methods to differentiate and classify disaster specific changes from anthropogenic surface alterations. Moreover, the inherent properties of the sensors, variations in SAR backscatter due to changes in surface conditions, and other factors exacerbate these limitations. We proposed a novel procedure expanding on earlier SAR-based change detection methods to exclude anthropogenic alterations and other sources of ambiguity that might lead to inaccurate mapping of the impacts of severe weather disasters. We applied the proposed procedure that is based on long term interferometric and amplitude-based change detection analyses of Sentinel- 1 SAR imagery to two study sites recently impacted by severe weather disasters (Flooding post severe weather events in urban centers; Hailstorm damage on crops). For the first case study, Sentinel-1 SLC scenes from two flood events in the Houston area (April 2016 flooding event and Hurricane Harvey of August-September 2017) were used to construct a flood map depicting areas repeatedly affected by the flood. Pixels with consistent coherence values in the pre-disaster coherence stack were retained for comparison with the pre- and post-disaster coherence stack and pixels with significant decline (greater than 60%) in coherence values were retained in the final flood map. The findings of the applied technique were calibrated and validated through datasets from NOAA/NWS Service storm reports, aerial imaging (NOAA and Civil Air Patrol), Federal Emergency Management Agency (FEMA) reporting, and targeted collections of NASA’s L-band UAVSAR data. Findings and products derived from the adopted methodology can be useful in disaster response and mitigation activities.

Gebremichael, Esayas↗

A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model: Overview - Part 1

Knowledge of the amount of water in the soil is of great importance to many earth science disciplines. Soil moisture is a key variable in controlling the exchange of water and energy between the land surface and the atmosphere. Thus, soil moisture information is valuable in a wide range of applications including weather and climate, runoff potential and flood control, early warning of droughts, irrigation, crop yield forecasting, soil erosion, reservoir management, geotechnical engineering, and water quality. Despite the importance of soil moisture information, widespread and continuous measurements of soil moisture are not possible today. Although many earth surface conditions can be measured from satellites, we still cannot adequately measure soil moisture from space. Research in soil moisture remote sensing began in the mid 1970s shortly after the surge in satellite development. Recent advances in remote sensing have shown that soil moisture can be measured, at least qualitatively, by several methods. Quantitative measurements of moisture in the soil surface layer have been most successful using both passive and active microwave remote sensing, although complications arise from surface roughness and vegetation type and density. Early attempts to measure soil moisture from space-borne microwave instruments were hindered by what is now considered sub-optimal wavelengths (shorter than 5 cm) and the coarse spatial resolution of the measurements. L-band frequencies between 1 and 3 GHz (10-30 cm) have been deemed optimal for detection of soil moisture in the upper few centimeters of soil. The Electronically Steered Thinned Array Radiometer (ESTAR), an aircraft-based instrument operating a 1,4 GHz, has shown great promise for soil moisture determination. Initiatives are underway to develop a similar instrument for space. Existing space-borne synthetic aperture radars (SARS) operating at C- and L-band have also shown some potential to detect surface wetness. The advantage of radar is its much higher resolution than passive microwave systems, but it is currently hampered by surface roughness effects and the lack of a good algorithm based on a single frequency and single polarization. In addition, its repeat frequency is generally low (about 40 days). In the meantime, two new radiometers offer some hope for remote sensing of soil moisture from space. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), launched in November 1997, possesses a 10.65 GHz channel and the Advanced Microwave Scanning Radiometer (AMSR) on both the ADEOS-11 and Earth Observing System AM-1 platforms to be launched in 1999 possesses a 6.9 GHz channel. Aside from issues about interference from vegetation, the coarse resolution of these data will provide considerable challenges pertaining to their application. The resolution of TMI is about 45 km and that of AMSR is about 70 km. These resolutions are grossly inconsistent with the scale of soil moisture processes and the spatial variability of factors that control soil moisture. Scale disparities such as these are forcing us to rethink how we assimilate data of various scales in hydrologic models. Of particular interest is how to assimilate soil moisture data by reconciling the scale disparity between what we can expect from present and future remote sensing measurements of soil moisture and modeling soil moisture processes. It is because of this disparity between the resolution of space-based sensors and the scale of data needed for capturing the spatial variability of soil moisture and related properties that remote sensing of soil moisture has not met with more widespread success. Within a single footprint of current sensors at the wavelengths optimal for this application, in most cases there is enormous heterogeneity in soil moisture created by differences in landcover, soils and topography, as well as variability in antecedent precipitation. It is difficult to interpret the meaning of 'mean' soil moisture under such conditions and even more difficult to apply such a value. Because of the non-linear relationships between near-surface soil moisture and other variables of interest, such as surface energy fluxes and runoff, mean soil moisture has little applicability at such large scales. It is for these reasons that the use of remote sensing in conjunction with a hydrologic model appears to be of benefit in capturing the complete spatial and temporal structure of soil moisture. This paper is Part I of a four-part series describing a method for intermittently assimilating remotely-sensed soil moisture information to improve performance of a distributed land surface hydrology model. The method, summarized in section II, involves the following components, each of which is detailed in the indicated section of the paper or subsequent papers in this series: Forward radiative transfer model methods (section II and Part IV); Use of a Kalman filter to assimilate remotely-sensed soil moisture estimates with the model profile (section II and Part IV); Application of a soil hydrology model to capture the continuous evolution of the soil moisture profile within and below the root zone (section III); Statistical aggregation techniques (section IV and Part II); Disaggregation techniques using a neural network approach (section IV and Part III); and Maximum likelihood and Bayesian algorithms for inversely solving for the soil moisture profile in the upper few cm (Part IV).

Crosson, William L.↗

Green's Function Applicable to Turbofan Exhaust Noise in Jets with an External Center-Body

The problem of propagation of sound across the shear layer in a turbofan jet exhaust with an external center-body is discussed. The wave equation of interest is compressible Rayleigh equation. Two forms of the equation are considered, and the Green's function solutions subject to appropriate surface conditions on the center-body and flight condition in the ambient are presented. Directivity studied in a heated exhaust at temperature ratio of 2.0 and Mach number 0.90 indicate that a rigid center-body tends to increase the sound propagation at forward angles relative to an exhaust without a center-body, while application of suitable surface liner may significantly reduce this enhancement. A general form of the far-field solution to the propagation equation in a parallel flow under supersonic conditions and in the neighborhood of the shear layer singularity is also discussed.

Noise↗

Early Spring Post-Fire Snow Albedo Dynamics in High Latitude Boreal Forests Using Landsat-8 OLI Data

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (less than 100 m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high-burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500 m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will thus play an important role in characterizing the carbon cycle and ecosystem processes of high latitude systems.

Landsat-8 snow albedo↗

Design of high efficiency HLE solar cells for space and terrestrial applications

A first-order analysis of HLE cells is presented for both beginning-of-life and end-of-life conditions. Based on this analysis and on experimentally observed values for material parameters. Design approaches for both space and terrestrial cells are presented. The approaches result in specification of doping levels, junction depths, and surface conditions. The proposed structures are projected to have both high V sub OC and high J sub SC.

Neugroschel, A.↗

Air-sea heat exchange, an element of the water cycle

The distribution and variation of water vapor, clouds and precipitation are examined. Principal driving forces for these distributions are energy exchange and evaporation at the air-sea interface, which are also important elements of air-sea interaction studies. The overall aim of air-sea interaction studies is to quantitatively determine mass, momentum and energy fluxes, with the goal of understanding the mechanisms controlling them. The results of general circulation simulations indicate that the atmosphere in mid-latitudes responds to changes in the oceanic surface conditions in the tropics. This correlation reflects the strong interaction between tropical and mid-latitude conditions caused by the transport of heat and momentum from the tropics. Studies of air-sea exchanges involve a large number of physica, chemical and dynamical processes including heat flux, radiation, sea-surface temperature, precipitation, winds and ocean currents. The fluxes of latent heat are studied and the potential use of satellite data in determining them evaluated. Alternative ways of inferring heat fluxes will be considered.

Chahine, M. T.↗

Remote sensing of atmospheric and surface parameters from HIRS2/MSU on TIROS-N

At the Goddard Laboratory for Atmospheric Sciences (GLAS) a physically based satellite temperature sounding retrieval system was developed, involving the simultaneous analysis of sounding data, for determining atmospheric and surface conditions that are consistent with the observed radiances. In addition to determining accurate atmospheric temperature profiles even in the presence of clouds, the system provides global estimates of day and night sea or land surface temperatures, snow and ice cover, cloud amounts, cloudtop heights and temperatures, and albedo. The characteristics of the atmospheric and surface parameters derived from the GLAS Physical Retrieval System are reviewed, results for the FGGE year are presented and, whenever possible, compared with other measurements of the same fields. Some of the model-derived diagnostic fields available from the GLAS Analysis/Forecast System are also discussed. These fields may lead to more accurate determination of the source terms of the atmospheric heat and moisture budgets.

Susskind, J.↗

Surface engineering to enhance heat generation and joint strength in dissimilar materials AZ31 and DP590 ultrasonic welding

A multiscale simulation approach was developed and employed to optimize the sheet surface conditions for higher interfacial temperature and joint strength in ultrasonic welding of magnesium alloy AZ31 and dual-phase steel DP590. First, a mesoscale model was used to study the relationship between friction coefficient and surface roughness, which can be modified by various engineering methods. Then a macroscopic process model was employed to study the effects of surface roughness on heat generation, indicating that a temperature increase can be achieved with rougher surfaces on two sides of both DP590 and AZ31 sheets. Samples prepared by sanding and filing, as well as grinding, were first characterized for surface roughness and then welded under ultrasonic vibration. An infrared camera was used to measure temperatures in situ for model validation. Overall, lap shear test results for the welded joint showed that the joint strength can be improved by 10~25% using filing and round grinding methods as a result of the enhanced heat generation and mechanical interlocking on the interface.

42 ENGINEERING↗

The importance of surface recombination and energy-bandgap narrowing in p-n-junction silicon solar cells

Experimental data demonstrating the sensitivity of open-circuit voltage to front-surface conditions are presented for a variety of p-n-junction silicon solar cells. Analytical models accounting for the data are defined and supported by additional experiments. The models and the data imply that a) surface recombination significantly limits the open-circuit voltage (and the short-circuit current) of typical silicon cells, and b) energy-bandgap narrowing is important in the manifestation of these limitations. The models suggest modifications in both the structural design and the fabrication processing of the cells that would result in substantial improvements in cell performance. The benefits of one such modification - the addition of a thin thermal silicon-dioxide layer on the front surface - are indicated experimentally.

Fossum, J. G.↗

Remote sensing of weather and climate parameters from HIRS2/MSU on Tiros-N

At the Goddard Laboratory for Atmospheric Sciences (GLAS) a physically based satellite temperature sounding retrieval system, involving the simultaneous analysis of HIRS2 and MSU sounding data, has been developed for determining atmospheric and surface conditions which are consistent with the observed radiances. In addition to determining accurate atmospheric temperature profiles even in the presence of cloud contamination, the system provides global estimates of day and night sea or land surface temperatures, snow and ice cover, and parameters related to cloud cover. The inverse radiative transfer equation approach to the multi-spectral analysis of the data, and details of its implementation, are described. Ice, snow, and cloud fields derived for January 1979 are consistent with other measures of similar parameters obtained from AVHRR and SMMR. Monthly mean sea-surface temperature fields agree with those derived from ship and buoy measurements to 0.5 C.

Susskind, J.↗

Goddard Laboratory for Atmospheric Sciences physical retrieval system for remote determination of weather and climate parameter from HIRS2 and MSU observations

At the Goddard Laboratory for Atmospheric Sciences (GLAS) a physically based satellite temperature sounding retrieval system, involving the simultaneous analysis of HIRS2 and MSU sounding data, was developed for determining atmospheric and surface conditions which are consistent with the observed radiances. In addition to determining accurate atmospheric temperature profiles even in the presence of cloud contamination, the system provides global estimates of day and night sea or land surface temperatures, snow and ice cover, and parameters related to cloud cover. Details of the system are described elsewhere. A brief overview of the system is presented, as well as recent improvements and previously unpublished results, relating to the sea-surface intercomparison workshop, the diurnal variation of ground temperatures, and forecast impact tests.

Susskind, J.↗

Atmospheric Soundings from AIRS/AMSU in Partial Cloud Cover

Simultaneous use of AIRS/AMSU-A observations allow for the determination of accurate atmospheric soundings under partial cloud cover conditions. The methodology involves the determination of the radiances AIRS would have seen if the AIRS fields of view were clear, called clear column radiances, and use of these radiances to infer the atmospheric and surface conditions giving rise to these clear column radiances. Susskind et al. demonstrate via simulation that accurate temperature soundings and clear column radiances can be derived from AIRS/AMSU-A observations in cases of up to 80% partial cloud cover, with only a small degradation in accuracy compared to that obtained in clear scenes. Susskind and Atlas show that these findings hold for real AIRS/AMSU-A soundings as well. For data assimilation purposes, this small degradation in accuracy is more than offset by a significant increase in spatial coverage (roughly 50% of global cases were accepted, compared to 3.6% of the global cases being diagnosed as clear), and assimilation of AIRS temperature soundings in partially cloudy conditions resulted in a larger improvement in forecast skill than when AIRS soundings were assimilated only under clear conditions. Alternatively, derived AIRS clear column radiances under partial cloud cover could also be used for data assimilation purposes. Further improvements in AIRS sounding methodology have been made since the results shown in Susskind and Atlas . A new version of the AIRS/AMSU-A retrieval algorithm, Version 4.0, was delivered to the Goddard DAAC in February 2005 for production of AIRS derived products, including clear column radiances. The major improvement in the Version 4.0 retrieval algorithm is with regard to a more flexible, parameter dependent, quality control. Results are shown of the accuracy and spatial distribution of temperature-moisture profiles and clear column radiances derived from AIRS/AMSU-A as a function of fractional cloud cover using the Version 4.0 algorithm. Use of the Version 4.0 AIRS temperature profiles increased the positive forecast impact arising from AIRS retrievals relative to what was shown in Susskind and Atlas .

Susskind, Joel↗

Mars Water Well Performance: Experimental Heat Transfer Results Supporting Simulations

Favorable indications of massive quantities of water on Mars have initiated studies of potential changes to human Mars missions. Using a technique known as a Rodriguez Well to melt the ice, store the resulting water in a subsurface ice cavity until needed, and then pump water to the surface for use is one potential means to effect these changes. A computer simulation of the Rodriguez Well in a terrestrial environment is one of the engineering tools being used to characterize the performance of this type of well on Mars. An experiment at the NASA Johnson Space Center gathered data for evaporation rates and convective heat transfer at Mars surface conditions so that this computer simulation could be appropriately modified to predict performance on Mars. Tests have indicated that a pool of water can be maintained at 1°C to 2° C while at Mars surface temperatures and pressures. Preliminary results for evaporation rates and convective heat transfer have been determined and are presented.

Stephen J Hoffman↗

Ocean experiments and remotely sensed images of chemically dispersed oil spills

A series of experiments was performed at sea where the effectiveness of dispersants applied from a helicopter was tested on fresh and weathered crude oils released from a surface research vessel. In conjunction with these experiments, remote sensing measurements using an array of airborne optical and microwave sensors were performed in order to aid in the interpretation of the dispersant effectiveness and to obtain quantitative images of oil on the sea under controlled conditions. Surface oil thickness and volume are inferred from airborne measurements using a dual-channel microwave imaging radiometer, aerial color photography, and an airborne oceanographic lidar. The remotely sensed measurements are compared with point sampled data obtained using a research vessel. The mass balance computations of surface versus subsurface oil volume using remotely sensed and point sampled data are consistent with each other and with the volumes of oil released. Data collected by the several techniques concur in indicating that, for the oils used and under the sea conditions encountered, the dispersant and application method are primarily useful when applied to fresh oil.

Croswell, W. F.↗

Deep Learning and Photogrammetric Reconstruction for Automated Crack Detection and Dimensional Measurement in Mining Operations

Surface crack detection and dimensional measurement at active mining sites present significant safety and operational challenges. Manual inspection methods are labor-intensive, spatially incomplete, and expose personnel to hazardous environments, while existing automated approaches have been developed primarily for concrete civil infrastructure and have not been validated on the complex, variable surfaces characteristic of mining environments. This dissertation presents an automated pipeline that integrates deep learning semantic segmentation with Structure-from-Motion photogrammetry to detect surface cracks and measure their aperture, length, and vertical displacement from standard RGB imagery acquired during routine Uncrewed Aerial Vehicle (UAV) survey operations, without requiring additional sensor hardware or manual measurement. The pipeline combines a U-Net architecture with an EfficientNet-B0 encoder, pretrained on the SDNET2018 concrete crack dataset and fine-tuned on a mining-specific dataset spanning laboratory concrete specimens, coal refuse impoundment embankments, and post-blast limestone quarry benches. Photogrammetric reconstruction is performed using COLMAP Structure-from-Motion and Multi-View Stereo, with crack segmentation masks projected into the reconstructed point cloud to enable three-dimensional vertical displacement measurement through local plane fitting and bimodal surface detection. The pipeline was validated across 36 controlled laboratory specimens at three imaging distances and four vertical displacement levels, achieving aperture measurement RMSE of 0.047 cm and R² of 0.954, and vertical displacement RMSE of 0.140 cm and R² of 0.966, against independent caliper measurements. Field application at a coal refuse impoundment in southwestern Pennsylvania detected 71 crack components across the embankment crest, with a dominant longitudinal crack exhibiting aperture values reaching 28 cm and a 95th percentile vertical displacement of 35.53 cm, consistent in magnitude and spatial distribution with simultaneously acquired LiDAR-derived estimates. Application across four post-blast limestone quarry bench datasets in California successfully characterized blast-induced fracture networks at ground sampling distances ranging from 0.59 to 1.23 cm/pixel, with detected crack geometries physically consistent with observable surface conditions at each site. The results demonstrate that deep learning-based crack detection and photogrammetric measurement can be integrated into routine UAV inspection workflows at mining sites, providing repeatable, scalable, and quantitative crack characterization across surface types, crack scales, and displacement magnitudes not previously addressed in the literature. The pipeline requires no dedicated surveying equipment beyond the UAV platforms already deployed at mine sites for survey and monitoring purposes, supporting practical adoption within existing operational workflows.

Crack detection, Dimensional Measurement↗

Three-dimensional low Reynolds number flows with a free surface

The two-dimensional leveling problem (Degani, Gutfinger, 1976) is extended to three dimensions in the case where the flow Re number is very low and attention is paid to the free surface boundary condition with surface tension effects included. The no-slip boundary condition on the wall is observed. The numerical solution falls back on the Marker and Cell (MAC) method (Harlow and Welch, 1965) with the computation region divided into a finite number of stationary rectangular cells (or boxes in the 3-D case) and fluid flow traverses the cells (or boxes).

Degani, D.↗

Ultrasonic techniques for aircraft ice accretion measurement

Results of tests to measure ice growth in natural (flight) and artificial (icing wind tunnel) icing conditions are presented. Ice thickness is measured using an ultrasonic pulse-echo technique. Two icing regimes, wet and dry ice growth, are identified and the unique ultrasonic signal characteristics associated with these different types of ice growth are described. Ultrasonic measurements of ice growth on cylinders and airfoils exposed to artificial and natural icing conditions are presented. An accuracy of plus or minus 0.5 mm is achieved for ice thickness measurement using the pulse-echo technique. The performance of two-probe type ice detectors is compared to the surface mounted ultrasonic system. The ultrasonically measured ice accretion rates and ice surface condition (wet or dry) are used to compare the heat transfer characteristics for flight and icing wind tunnel environments. In general the heat transfer coefficient is inferred to be higher in the wind tunnel environment, not likely due to higher freestream turbulence levels. Finally, preliminary results of tests to measure ice growth on airfoil using an array of ultrasonic transducers are described. Ice profiles obtained during flight in natural icing conditions are shown and compared with mechanical and stereo image measurements.

Hansman, R. John, Jr.↗