scholarly journals New algorithm to retrieve the effective snow grain size and pollution amount from satellite data

2008 ◽  
Vol 49 ◽  
pp. 139-144 ◽  
Author(s):  
E. Zege ◽  
I. Katsev ◽  
A. Malinka ◽  
A. Prikhach ◽  
I. Polonsky
Keyword(s):  
Grain Size ◽  
Spectral Reflectance ◽  
Analytical Approach ◽  
Optical Model ◽  
A Priori ◽  
Spherical Particles ◽  
Reflection Data ◽  
Ocean Monitoring ◽  
Spectral Channels ◽  
Fast Inversion

AbstractThis paper presents a new simple and efficient algorithm to retrieve the effective snow grain size and soot concentration from spectral reflectance on snow measured by optical instrument on a satellite. This algorithm was recently developed and will be used for integrated ice–atmosphere–ocean monitoring in the framework of the DAMOCLES program. The algorithm is based on an analytical approach to snow optics. In this approach snow is considered as a close-packed medium with irregularly shaped grains rather than with independent spherical particles. Unlike the known conventional algorithms, the developed algorithm uses no a priori snow optical model. The analytical nature of this algorithm provides a very fast inversion of the reflection data. The developed algorithm was realized and validated for the GLI and MODIS instruments. The algorithm can be generalized for other satellite instruments with appropriate spectral channels. Finally, the results of verifications using a computer simulation are discussed.

Effect of Li on Mechanical Properties and Electrical Conductivity of the Al–Zn–Cu–Mg Based Alloys

2021 ◽  
Vol 21 (9) ◽  
pp. 4897-4901
Author(s):  
Hyo-Sang Yoo ◽  
Yong-Ho Kim ◽  
Hyeon-Taek Son
Keyword(s):  
Mechanical Properties ◽  
Electrical Conductivity ◽  
Grain Size ◽  
Tensile Strength ◽  
Spherical Particles ◽  
Al Alloy ◽  
High Angle ◽  
Average Grain Size ◽  
Strength Improvement ◽  
Li Content

In this study, changes in the microstructure, mechanical properties, and electrical conductivity of cast and extruded Al–Zn–Cu–Mg based alloys with the addition of Li (0, 0.5 and 1.0 wt.%) were investigated. The Al–Zn–Cu–Mg–xLi alloys were cast and homogenized at 570 °C for 4 hours. The billets were hot extruded into rod that were 12 mm in diameter with a reduction ratio of 38:1 at 550 °C. As the amount of Li added increased from 0 to 1.0 wt.%, the average grain size of the extruded Al alloy increased from 259.2 to 383.0 µm, and the high-angle grain boundaries (HGBs) fraction decreased from 64.0 to 52.1%. As the Li content increased from 0 to 1.0 wt.%, the elongation was not significantly different from 27.8 to 27.4% and the ultimate tensile strength (UTS) was improved from 146.7 to 160.6 MPa. As Li was added, spherical particles bonded to each other, forming an irregular particles. It is thought that these irregular particles contribute to the strength improvement.

scholarly journals An integral equation formulation of the N-body dielectric spheres problem. Part 1: Numerical analysis

2020 ◽  
Author(s):  
Muhammad Hassan ◽  
Benjamin Stamm
Keyword(s):  
Integral Equation ◽  
Numerical Analysis ◽  
Error Analysis ◽  
Convergence Rates ◽  
A Priori ◽  
Approximation Error ◽  
Spherical Particles ◽  
Integral Equation Formulation ◽  
Dielectric Spheres ◽  
The Stability

In this article, we analyse an integral equation of the second kind that represents the solution of N interacting dielectric spherical particles undergoing mutual polarisation. A traditional analysis can not quantify the scaling of the stability constants- and thus the approximation error- with respect to the number N of involved dielectric spheres. We develop a new a priori error analysis that demonstrates N-independent stability of the continuous and discrete formulations of the integral equation. Consequently, we obtain convergence rates that are independent of N.

Bayesian reverberation inversion incorporating grain-size dependent regression relations as a priori information

2012 ◽  
Author(s):  
Leif Abrahamsson ◽  
Brodd Leif Andersson ◽  
Sven M. Ivansson ◽  
Jörgen Pihl ◽  
Michael A. Ainslie ◽  
...  
Keyword(s):  
Grain Size ◽  
A Priori ◽  
A Priori Information ◽  
Size Dependent ◽  
Regression Relations ◽  
Priori Information

The Mechanical Alloying of Magnetite Concentrate with Biochar

2020 ◽  
Vol 10 (2) ◽  
pp. 116-125
Author(s):  
Elif Aranci Öztürk ◽  
Mustafa Boyrazli ◽  
Mehmet Deniz Turan ◽  
Murat Erdemoğlu
Keyword(s):  
Crystal Structure ◽  
Particle Size ◽  
Grain Size ◽  
Mechanical Alloying ◽  
Milled Powder ◽  
Spherical Particles ◽  
Size Analysis ◽  
Biomass Waste ◽  
Magnetic Separator ◽  
Magnetite Concentrate

Aim: In this work, the effect of milling time on the mechanical alloying of the mixture containing the magnetite concentrate and biomass waste was investigated. Materials and Methods: The ore’s grade consisting of hematite and magnetite minerals was increased from 49.87% Fe to 67.29% Fe using the low intensity wet magnetic separator. Biomass waste which was supplied from ÇAYKUR black tea facilities, used as a carbon source was subjected to carbonization processes at 800°C for 1440 min. After the carbonization process, the carbon and sulphur contents of the biomass were measured as 94.68% and 0.03%, respectively. For the mechanical alloying process, a mixture consisting of magnetite concentrate with a grain size of -45 μm and biomass which was added two times the amount of carbon required for the reduction of magnetite to metallic iron was used. Result: After the mechanical alloying process which was carried out at different times, it was observed in the particle size analysis that the particle size of 90% of the mixture was reduced to about 4 μm. In SEM (Scanning Electron Microscopy) images, cube-like particles along with the spherical particles were observed depending on the mechanical alloying times. After 45 minutes of alloying, it was observed that the carbonized product milled together with magnetite concentrate was partially integrated into the crystal structure. Conclusion: The carbonized tea plant waste milled together with magnetite concentrate was partially integrated into the crystal structure. And the mechanical alloying provide to increase in the specific surface area in parallel with the grain size decrease in the study. Thus, in the later stage of the study, the milled powder acquired more ability to react.

scholarly journals Frequency-dependent attenuation analysis of ground-penetrating radar data

Geophysics ◽  
2007 ◽  
Vol 72 (3) ◽  
pp. J7-J16 ◽  
Author(s):  
John H. Bradford
Keyword(s):  
Attenuation Coefficient ◽  
Ground Penetrating Radar ◽  
A Priori ◽  
Radar Data ◽  
Frequency Dependent ◽  
First Order ◽  
Reflection Data ◽  
Frequency Independent ◽  
Band Limited ◽  
Ground Penetrating

In the early 1990s, it was established empirically that, in many materials, ground-penetrating radar (GPR) attenuation is approximately linear with frequency over the bandwidth of a typical pulse. Further, a frequency-independent [Formula: see text] parameter characterizes the slope of the band-limited attenuation versus frequency curve. Here, I derive the band-limited [Formula: see text] function from a first-order Taylor expansion of the attenuation coefficient. This approach provides a basis for computing [Formula: see text] from any arbitrary dielectric permittivity model. For Cole-Cole relaxation, I find good correlation between the first-order [Formula: see text] approximation and [Formula: see text] computed from linear fits to the attenuation coefficient curve over two-octave bands. The correlation holds over the primary relaxation frequency. For some materials, this relaxation occurs between 10 and [Formula: see text], a typical frequency range for many GPR applications. Frequency-dependent losses caused by scattering and by the commonly overlooked problem of frequency-dependent reflection make it difficult or impossible to measure [Formula: see text] from reflection data without a priori understanding of the materials. Despite these complications, frequency-dependent attenuation analysis of reflection data can provide valuable subsurface information. At two field sites, I find well-defined frequency-dependent attenuation anomalies associated with nonaqueous-phase liquid contaminants.

An analytical approach for predicting as-cast grain size of inoculated aluminum alloys

2015 ◽  
Vol 99 ◽  
pp. 337-346 ◽  
Author(s):  
Xin Bo Qi ◽  
Yun Chen ◽  
Xiu Hong Kang ◽  
Dian Zhong Li ◽  
Qiang Du
Keyword(s):  
Grain Size ◽  
Aluminum Alloys ◽  
Analytical Approach

scholarly journals An analysis of acquisition-related subsampling effects on Marchenko focusing, redatuming, and primary estimation

Geophysics ◽  
2021 ◽  
pp. 1-97
Author(s):  
Haorui Peng ◽  
Ivan Vasconcelos ◽  
Yanadet Sripanich ◽  
Lele Zhang
Keyword(s):  
A Priori ◽  
Synthetic Data ◽  
Velocity Model ◽  
Iterative Solvers ◽  
Sampled Data ◽  
Reflection Data ◽  
Reconstruction Quality ◽  
Essential Components ◽  
Convolution Process ◽  
Set Up

Marchenko methods can retrieve Green’s functions and focusing functions from single-sided reflection data and a smooth velocity model, as essential components of a redatuming process. Recent studies also indicate that a modified Marchenko scheme can reconstruct primary-only reflection responses directly from reflection data without requiring a priori model information. To provide insight into the artifacts that arise when input data are not ideally sampled, we study the effects of subsampling in both types of Marchenko methods in 2D earth and data — by analyzing the behavior of Marchenko-based results on synthetic data subsampled in sources or receivers. With a layered model, we find that for Marchenko redatuming, subsampling effects jointly depend on the choice of integration variable and the subsampling dimension, originated from the integrand gather in the multidimensional convolution process. When reflection data are subsampled in a single dimension, integrating on the other yields spatial gaps together with artifacts, whereas integrating on the subsampled dimension produces aliasing artifacts but without spatial gaps. Our complex subsalt model indicates that the subsampling may lead to very strong artifacts, which can be further complicated by having limited apertures. For Marchenko-based primary estimation (MPE), subsampling below a certain fraction of the fully sampled data can cause MPE iterations to diverge, which can be mitigated to some extent by using more robust iterative solvers, such as least-squares QR. Our results, covering redatuming and primary estimation in a range of subsampling scenarios, provide insights that can inform acquisition sampling choices as well as processing parameterization and quality control, e.g., to set up appropriate data filters and scaling to accommodate the effects of dipole fields, or to help ensuring that the data interpolation achieves the desired levels of reconstruction quality that minimize subsampling artifacts in Marchenko-derived fields and images.

scholarly journals Evaluation of prediction models applied to the soil-water characteristic curve of ideal materials

2020 ◽  
Vol 195 ◽  
pp. 02024
Author(s):  
Roberto Dutra Alves ◽  
Gilson de F. N. Gitirana ◽  
Sai K. Vanapalli
Keyword(s):  
Grain Size ◽  
Size Distribution ◽  
Soil Water ◽  
Grain Size Distribution ◽  
Characteristic Curve ◽  
Empirical Models ◽  
Spherical Particles ◽  
Soil Water Characteristic Curve ◽  
Varying Coefficients ◽  
Semi Empirical

The development of theoretical and semi-empirical models to study capillary mechanisms and predict the soil-water characteristic curve (SWCC) generally requires the idealization of pore space and pore water, considering simplifying hypotheses. The study of ideal materials comprised of particles with controlled shape and size allows the evaluation of such simplifying hypotheses and the subsequent generalization to actual soils. In this paper, four theoretical and semi-empirical models for the prediction of the SWCC are applied to the prediction of artificial materials comprised of spherical particles. Nineteen grain-size distribution curves, with varying coefficients of uniformity are considered. The dataset is comprised of materials previously published and additional tests carried out by the authors, under highly controlled conditions. The analyses allowed the evaluation of the effect of grain-size distribution curve and shape of the particles. The limitations and advantages of each prediction model was investigated, and a detailed comparison is presented, guiding future implementations of improved models.

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