scholarly journals Particle Size Estimation in Ice-Phase Clouds Using Multifrequency Radar Reflectivity Measurements at 95, 33, and 2.8 GHz

1999 ◽  
Vol 38 (1) ◽  
pp. 5-28 ◽  
Author(s):  
Stephen M. Sekelsky ◽  
Warner L. Ecklund ◽  
John M. Firda ◽  
Kenneth S. Gage ◽  
Robert E. McIntosh
Keyword(s):  
Particle Size ◽  
Radar Reflectivity ◽  
Size Estimation ◽  
Multifrequency Radar ◽  
Ice Phase

scholarly journals Particle Size Estimation in Mixed Commercial Waste Images Using Deep Learning

2021 ◽  
Author(s):  
Phongsathorn Kittiworapanya ◽  
Kitsuchart Pasupa ◽  
Peter Auer
Keyword(s):  
Computer Vision ◽  
Particle Size ◽  
Deep Learning ◽  
Waste Management ◽  
State Of The Art ◽  
Learning Algorithms ◽  
Input Image ◽  
Size Estimation ◽  
Waste Particles ◽  
Set Up

<div>We assessed several state-of-the-art deep learning algorithms and computer vision techniques for estimating the particle size of mixed commercial waste from images. In waste management, the first step is often coarse shredding, using the particle size to set up the shredder machine. The difficulty is separating the waste particles in an image, which can not be performed well. This work focused on estimating size by using the texture from the input image, captured at a fixed height from the camera lens to the ground. We found that EfficientNet achieved the best performance of 0.72 on F1-Score and 75.89% on accuracy.<br></div>

scholarly journals Fluid Dynamics Properties of Barium Hexaferrite Particle

2014 ◽  
Vol 17 (49) ◽  
Author(s):  
Perdamean Sebayang ◽  
Muljadi ◽  
Anggito Tetuko ◽  
Priyo Sardjono
Keyword(s):  
Particle Size ◽  
Bulk Density ◽  
Barium Hexaferrite ◽  
Reynolds Numbers ◽  
Terminal Velocity ◽  
Size Estimation ◽  
Floc Size ◽  
Ethanol Medium ◽  
Lower Bulk Density ◽  
Relationship Of

Particle size distribution of Barium Hexaferrite sample has been performed with commonly used methods of mathematical models by Rosin-Rammler (RR model) distribution. By using sieving method from 20-400 mesh, the basis of network analysis distribution function F(d) and density function, f(d) were obtained. Particle size estimation was performed using sedimentation gravitation based on Stokes law to obtained Reynolds numbers and terminal velocity of flocs in medium value has been calculated. The results of Reynolds numbers shows that Barium hexaferrite flocs in ethanol medium in laminar flow, whereas terminal velocity increases as larger particle size and density, however, bulk density reduce due to contained highly porous in the sample which yields lower bulk density. The relationship of turbidity with the floc size has been evaluated. The results show that turbidity and bulk density increases as smaller particle size, meanwhile, terminal velocity reduced. Differences in turbidity for each sample (20-400 mesh) has been determined which shows two region instead, with first region from 150-850 µm yields larger differences compared to the second region: 37-105 µm.  

scholarly journals Stimulating effect of magnesium hydroxide on aqueous characteristics of iron nanocomposites

2019 ◽  
Vol 80 (10) ◽  
pp. 1996-2002 ◽  
Author(s):  
I. Maamoun ◽  
O. Eljamal ◽  
O. Falyouna ◽  
R. Eljamal ◽  
Y. Sugihara
Keyword(s):  
Particle Size ◽  
Magnesium Hydroxide ◽  
Iron Nanoparticles ◽  
Aqueous Suspension ◽  
Average Particle Size ◽  
Degree Of Crystallinity ◽  
Iron Core ◽  
Average Particle ◽  
Size Estimation ◽  
Aqueous Corrosion

Abstract Nanoscale zero-valent iron (nFe0) tends to aggregate, which dramatically affects its aqueous characteristics and thereby its potential in water treatment applications. Hence, the main aim of this study is to overcome such drawback of nFe0 by a new modification approach. Iron nanoparticles were modified by magnesium hydroxide (Mg(OH)2) addition with different mass ratios in order to form a nanocomposite with superior aqueous characteristics. The optimization process of the iron–magnesium nanocomposite (nFe0-Mg) was conducted through different approaches including settlement tests, morphology and crystallinity investigations and particle size estimation. The addition of Mg(OH)2 to nFe0 with a Mg/Fe coating ratio of 100% resulted in stimulated stability of the particles in aqueous suspension with around 95% enhancement in the suspension efficiency compared to that of nFe0. Results showed that the average particle size and degree of crystallinity of nFe0-Mg(Mg/Fe:100%) decreased by 46.7% and increased by 16.8%, respectively, comparing with that of nFe0. Additionally, the iron core of the synthesized nFe0 was adequately protected from aqueous corrosion with lower iron oxides leachates after the optimal modification with Mg(OH)2. Furthermore, Mg(OH)2 coating resulted in a stimulated adsorption reactivity of the composite towards phosphorus (P) with around 3.13% promotion in the removal efficiency comparing to that of nFe0.

scholarly journals Dual-wavelength radar technique development for snow rate estimation: a case study from GCPEx

2019 ◽  
Vol 12 (2) ◽  
pp. 1409-1427 ◽  
Author(s):  
Gwo-Jong Huang ◽  
Viswanathan N. Bringi ◽  
Andrew J. Newman ◽  
Gyuwon Lee ◽  
Dmitri Moisseev ◽  
...  
Keyword(s):  
Particle Size ◽  
Power Law ◽  
Radar Reflectivity ◽  
Dual Wavelength ◽  
Hydrodynamic Theory ◽  
Estimation Methods ◽  
Fall Velocity ◽  
Large Variability ◽  
Ka Band ◽  
Rate Estimation

Abstract. quantitative precipitation estimation (QPE) of snowfall has generally been expressed in power-law form between equivalent radar reflectivity factor (Ze) and liquid equivalent snow rate (SR). It is known that there is large variability in the prefactor of the power law due to changes in particle size distribution (PSD), density, and fall velocity, whereas the variability of the exponent is considerably smaller. The dual-wavelength radar reflectivity ratio (DWR) technique can improve SR accuracy by estimating one of the PSD parameters (characteristic diameter), thus reducing the variability due to the prefactor. The two frequencies commonly used in dual-wavelength techniques are Ku- and Ka-bands. The basic idea of DWR is that the snow particle size-to-wavelength ratio is falls in the Rayleigh region at Ku-band but in the Mie region at Ka-band. We propose a method for snow rate estimation by using NASA D3R radar DWR and Ka-band reflectivity observations collected during a long-duration synoptic snow event on 30–31 January 2012 during the GCPEx (GPM Cold-season Precipitation Experiment). Since the particle mass can be estimated using 2-D video disdrometer (2DVD) fall speed data and hydrodynamic theory, we simulate the DWR and compare it directly with D3R radar measurements. We also use the 2DVD-based mass to compute the 2DVD-based SR. Using three different mass estimation methods, we arrive at three respective sets of Z–SR and SR(Zh, DWR) relationships. We then use these relationships with D3R measurements to compute radar-based SR. Finally, we validate our method by comparing the D3R radar-retrieved SR with accumulated SR directly measured by a well-shielded Pluvio gauge for the entire synoptic event.

scholarly journals A radar reflectivity operator with ice-phase hydrometeors for variational data assimilation (version 1.0) and its evaluation with real radar data

2019 ◽  
Vol 12 (9) ◽  
pp. 4031-4051 ◽  
Author(s):  
Shizhang Wang ◽  
Zhiquan Liu
Keyword(s):  
Data Assimilation ◽  
Three Dimensional ◽  
Wrf Model ◽  
Radar Data ◽  
Poor Quality ◽  
Variational Data Assimilation ◽  
Radar Reflectivity ◽  
Background Error ◽  
Background Fields ◽  
Ice Phase

Abstract. A reflectivity forward operator and its associated tangent linear and adjoint operators (together named RadarVar) were developed for variational data assimilation (DA). RadarVar can analyze both rainwater and ice-phase species (snow and graupel) by directly assimilating radar reflectivity observations. The results of three-dimensional variational (3D-Var) DA experiments with a 3 km grid mesh setting of the Weather Research and Forecasting (WRF) model showed that RadarVar was effective at producing an analysis of reflectivity pattern and intensity similar to the observed data. Two to three outer loops with 50–100 iterations in each loop were needed to obtain a converged 3-D analysis of reflectivity, rainwater, snow, and graupel, including the melting layers with mixed-phase hydrometeors. It is shown that the deficiencies in the analysis using this operator, caused by the poor quality of the background fields and the use of the static background error covariance, can be partially resolved by using radar-retrieved hydrometeors in a preprocessing step and tuning the spatial correlation length scales of the background errors. The direct radar reflectivity assimilation using RadarVar also improved the short-term (2–5 h) precipitation forecasts compared to those of the experiment without DA.

scholarly journals Retrievals of ice microphysics using dual-wavelength polarimetric radar observations during stratiform precipitation events

2021 ◽  
Author(s):  
Eleni Tetoni ◽  
Florian Ewald ◽  
Martin Hagen ◽  
Gregor Köcher ◽  
Tobias Zinner ◽  
...  
Keyword(s):  
Particle Size ◽  
Particle Shape ◽  
Radar Reflectivity ◽  
Dual Wavelength ◽  
Ice Cloud ◽  
Cloud Radar ◽  
Stratiform Precipitation ◽  
Mass Size ◽  
Ice Microphysics ◽  
Precipitation Events

Abstract. Ice growth processes within clouds affect the type as well as the amount of precipitation. Hence, the importance of an accurate representation of ice microphysics in numerical weather and numerical climate models has been confirmed by several studies. To better constrain ice processes in models, we need to study ice cloud regions before and during monitored precipitation events. For this purpose, two radar instruments facing each other were used to collect complementary measurements. The C-band POLDIRAD weather radar from the German Aerospace Center (DLR), Oberpfaffenhofen and the Ka-band MIRA-35 cloud radar from the Ludwig Maximilians University of Munich (LMU) were used to monitor stratiform precipitation in the vertical cross-section area between both instruments. The logarithmic difference of radar reflectivities at two different wavelengths (54.5 and 8.5 mm), known as dual-wavelength ratio, was exploited to provide information about the size of the detected ice hydrometeors, taking advantage of the different scattering behavior in the Rayleigh and Mie regime. Along with the dual-wavelength ratio, differential radar reflectivity measurements from POLDIRAD provided information about the apparent shape of the detected ice hydrometeors. Scattering simulations using the T-matrix method were performed for oblate and horizontally aligned prolate ice spheroids of varying shape and size using a realistic particle size distribution and a well-established mass-size relationship. The combination of dual-wavelength ratio, radar reflectivity and differential radar reflectivity measurements as well as scattering simulations was used for the development of a novel retrieval for ice cloud microphysics. The development of the retrieval scheme also comprised a method to estimate the hydrometeor attenuation in both radar bands. To demonstrate this approach, a feasibility study was conducted on three stratiform snow events which were monitored over Munich in January 2019. The ice retrieval can obtain ice particle shape, size and mass which are in line with differential radar reflectivity, dual-wavelength ratio and radar reflectivity observations when a suitable mass-size relation is used and when ice hydrometeors are assumed to be represented by oblate ice spheroids. A furthermore finding was the importance of the differential radar reflectivity for the particle size retrieval directly above the MIRA-35 cloud radar. Especially for that observation geometry, the simultaneous slantwise observation from the polarimetric weather radar POLDIRAD could reduce ambiguities in retrieval of the ice particle size by constraining the ice particle shape.

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