scholarly journals On the Impacts of Different Definitions of Maximum Dimension for Nonspherical Particles Recorded by 2D Imaging Probes

2016 ◽  
Vol 33 (5) ◽  
pp. 1057-1072 ◽  
Author(s):  
Wei Wu ◽  
Greg M. McFarquhar
Keyword(s):  
Particle Size ◽  
Strong Dependence ◽  
3D Structure ◽  
Terminal Velocity ◽  
Sample Volume ◽  
Nonspherical Particles ◽  
Particle Dimension ◽  
Imaging Probes ◽  
Definition Of ◽  
Ice Water

AbstractKnowledge of ice crystal particle size distributions (PSDs) is critical for parameterization schemes for atmospheric models and remote sensing retrieval schemes. Two-dimensional in situ images captured by cloud imaging probes are widely used to derive PSDs in term of maximum particle dimension (). In this study, different definitions of for nonspherical particles recorded by 2D probes are compared. It is shown that the derived PSDs can differ by up to a factor of 6 for μm and mm. The large differences for μm are caused by the strong dependence of sample volume on particle size, whereas differences for mm are caused by the small number of particles detected. Derived bulk properties can also vary depending on the definitions of because of discrepancies in the definition of used to characterize the PSDs and that used to describe the properties of individual ice crystals. For example, the mass-weighted mean diameter can vary by 2 times, the ice water content (IWC) by 3 times, and the mass-weighted terminal velocity by 6 times. Therefore, a consistent definition of should be used for all data and single-particle properties. As an invariant measure with respect to the orientation of particles in the imaging plane for 2D probes, the diameter of the smallest circle enclosing the particle () is recommended as the optimal definition of . If the 3D structure of a particle is observed, then the technique can be extended to determine the minimum enclosing sphere.

Refinements to Ice Particle Mass Dimensional and Terminal Velocity Relationships for Ice Clouds. Part I: Temperature Dependence

2007 ◽  
Vol 64 (4) ◽  
pp. 1047-1067 ◽  
Author(s):  
Andrew J. Heymsfield ◽  
Aaron Bansemer ◽  
Cynthia H. Twohy
Keyword(s):  
Weather Forecast ◽  
Terminal Velocity ◽  
Fall Velocity ◽  
Cross Sectional ◽  
Convective Clouds ◽  
Particle Mixing ◽  
Particle Dimension ◽  
Mass Dimension ◽  
Forecast Models ◽  
Ice Water

Abstract This two-part study attempts to find appropriate mass dimension and terminal velocity relationships that, when considered together with particle size distributions (PSD), agree with coincident measurements of ice water content (IWC), and with variables related to higher moments such as the mean mass-weighted fall speed. Reliable relationships are required for improving microphysical parameterizations for weather forecast models and developing methods for evaluating them, subjects addressed in detail in Part II of this study. Here, a range of values from 1.5 to 2.3 is assumed for the exponent b in the mass dimension relationship, m = aDb, where D is the maximum particle dimension, to bound its likely value for sizes above about 100 μm. Measured IWC and size spectra are used to find appropriate values for the coefficient a. It is demonstrated that all values of the exponent b, with appropriate a coefficients, can fit the IWC measurements. Coincident information on particle cross-sectional areas with the m(D) relationships is used to develop general fall velocity relationships of the form Vt = ADB. These assessments use five midlatitude, synoptically generated ice layers, and 10 low-latitude, convectively generated ice cloud layers, spanning the temperature range from −60° to 0°C. The coefficients a and A and exponent B are represented in terms of the exponent b and are shown to be temperature-dependent for the synoptic clouds and relatively independent of it in the convective clouds, a result of particle mixing through the cloud column. Consistency is found with earlier results and with analytic considerations. It is found that the fall velocity is inversely proportional to the air density to approximately the exponent 0.54, close to values assumed in earlier studies.

The Size Distribution and Mass-Weighted Terminal Velocity of Low-Latitude Tropopause Cirrus Crystal Populations

2009 ◽  
Vol 66 (7) ◽  
pp. 2013-2028 ◽  
Author(s):  
C. G. Schmitt ◽  
A. J. Heymsfield
Keyword(s):  
Particle Size ◽  
Size Distribution ◽  
Terminal Velocity ◽  
Range Data ◽  
Regional Study ◽  
Low Latitude ◽  
Particle Properties ◽  
Validation Experiment ◽  
Using Data ◽  
Ice Water

Abstract Ice crystal terminal velocities govern the lifetime of radiatively complex, climatologically important, low-latitude tropopause cirrus clouds. To better understand cloud lifetimes, the terminal velocities of low-latitude tropopause cirrus cloud particles have been estimated using data from aircraft field campaigns. Data used in this study were collected during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers–Florida Area Cirrus Experiment (CRYSTAL-FACE) and the Pre-Aura Validation Experiment (Pre-AVE). Particle properties were measured with the NCAR video ice particle sampler (VIPS) probe, thus providing information about particles in a poorly understood size range. Data used in this study were limited to high-altitude nonconvective thin clouds with temperatures between −56° and −86°C. Realistic particle terminal velocity estimates require accurate values of particle projected area and mass. Exponential functions were used to predict the dimensional properties of ice particles smaller than 200 microns and were found to predict ice water content measurements well when compared to power-law representations. The shapes of the particle size distributions were found to be monomodal and were well represented by exponential or gamma functions. Incorporating these findings into terminal velocity calculations led to lower values of mass-weighted terminal velocities for particle populations than are currently predicted for low-latitude ice clouds. New parameterizations for individual particle properties as well as particle size distribution properties are presented and compared to commonly used parameterizations. Results from this study are appropriate for use in estimating the properties of low-latitude thin and subvisible cirrus at temperatures lower than −56°C.

Limitations of a 3-D Image Analysis-Based Particle Size Measuring System for Wood Particle Dimension Measurement

2018 ◽  
Vol 50 (3) ◽  
pp. 358-362
Author(s):  
Jan T Benthien ◽  
Jan Ludtke ◽  
Rainer Friehmelt ◽  
Michael Schafer
Keyword(s):  
Particle Size ◽  
Image Analysis ◽  
Wood Particle ◽  
Measuring System ◽  
Dimension Measurement ◽  
Particle Dimension

Refinements to Ice Particle Mass Dimensional and Terminal Velocity Relationships for Ice Clouds. Part II: Evaluation and Parameterizations of Ensemble Ice Particle Sedimentation Velocities

2007 ◽  
Vol 64 (4) ◽  
pp. 1068-1088 ◽  
Author(s):  
Andrew J. Heymsfield ◽  
Gerd-Jan van Zadelhoff ◽  
David P. Donovan ◽  
Frederic Fabry ◽  
Robin J. Hogan ◽  
...  
Keyword(s):  
Climate Models ◽  
Doppler Radar ◽  
Terminal Velocity ◽  
Fall Velocity ◽  
Particle Sedimentation ◽  
Cloud Properties ◽  
Wide Range ◽  
Single Moment ◽  
Ice Water Content ◽  
Ice Water

Abstract This two-part study addresses the development of reliable estimates of the mass and fall speed of single ice particles and ensembles. Part I of the study reports temperature-dependent coefficients for the mass-dimensional relationship, m = aDb, where D is particle maximum dimension. The fall velocity relationship, Vt = ADB, is developed from observations in synoptic and low-latitude, convectively generated, ice cloud layers, sampled over a wide range of temperatures using an assumed range for the exponent b. Values for a, A, and B were found that were consistent with the measured particle size distributions (PSD) and the ice water content (IWC). To refine the estimates of coefficients a and b to fit both lower and higher moments of the PSD and the associated values for A and B, Part II uses the PSD from Part I plus coincident, vertically pointing Doppler radar returns. The observations and derived coefficients are used to evaluate earlier, single-moment, bulk ice microphysical parameterization schemes as well as to develop improved, statistically based, microphysical relationships. They may be used in cloud and climate models, and to retrieve cloud properties from ground-based Doppler radar and spaceborne, conventional radar returns.

scholarly journals Characterising optical array particle imaging probes: implications for small-ice-crystal observations

2021 ◽  
Vol 14 (3) ◽  
pp. 1917-1939
Author(s):  
Sebastian O'Shea ◽  
Jonathan Crosier ◽  
James Dorsey ◽  
Louis Gallagher ◽  
Waldemar Schledewitz ◽  
...  
Keyword(s):  
Field Experiments ◽  
Field Measurements ◽  
Sample Volume ◽  
Ice Crystal ◽  
Cloud Particle ◽  
Ice Clouds ◽  
Cloud Properties ◽  
Imaging Probes ◽  
New Methodologies ◽  
Particle Imaging

Abstract. The cloud particle concentration, size, and shape data from optical array probes (OAPs) are routinely used to parameterise cloud properties and constrain remote sensing retrievals. This paper characterises the optical response of OAPs using a combination of modelling, laboratory, and field experiments. Significant uncertainties are found to exist with such probes for ice crystal measurements. We describe and test two independent methods to constrain a probe's sample volume that remove the most severely mis-sized particles: (1) greyscale image analysis and (2) co-location using stereoscopic imaging. These methods are tested using field measurements from three research flights in cirrus. For these cases, the new methodologies significantly improve agreement with a holographic imaging probe compared to conventional data-processing protocols, either removing or significantly reducing the concentration of small ice crystals (< 200 µm) in certain conditions. This work suggests that the observational evidence for a ubiquitous mode of small ice particles in ice clouds is likely due to a systematic instrument bias. Size distribution parameterisations based on OAP measurements need to be revisited using these improved methodologies.

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.  

Prediction of Packing Density of Milled Powder Based on Packing Simulation and Particle Shape Analysis

2007 ◽  
Vol 534-536 ◽  
pp. 1621-1624
Author(s):  
Yuto Amano ◽  
Takashi Itoh ◽  
Hoshiaki Terao ◽  
Naoyuki Kanetake
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Shape Analysis ◽  
Packing Density ◽  
Particle Shape ◽  
Milled Powder ◽  
Spherical Particles ◽  
Nonspherical Particles ◽  
Property Control

For precise property control of sintered products, it is important to know the powder characteristics, especially the packing density of the powder. In a previous work, we developed a packing simulation program that could make a packed bed of spherical particles having particle size distribution. In order to predict the packing density of the actual powder that consisted of nonspherical particles, we combined the packing simulation with a particle shape analysis. We investigated the influence of the particle size distribution of the powder on the packing density by executing the packing simulation based on particle size distributions of the actual milled chromium powders. In addition, the influence of the particle shape of the actual powder on the packing density was quantitatively analyzed. A prediction of the packing density of the milled powder was attempted with an analytical expression between the particle shape of the powder and the packing simulation. The predicted packing densities were in good agreement with the actual data.

What Constitutes a Smart City?

2019 ◽  
pp. 1-29
Author(s):  
Sekhar Kondepudi ◽  
Ramita Kondepudi
Keyword(s):  
Detailed Analysis ◽  
Smart City ◽  
Strong Dependence ◽  
Common Theme ◽  
Standard Definition ◽  
Definition Of ◽  
Holistic Description ◽  
Insight Into

This chapter provides an insight into what is meant by a Smart City and the underlying factors that make a city smart. The authors answer the question of “what constitutes a smart city” by presenting a multi-faceted approach including a detailed analysis of classical smart city definitions, attributes of a smart city, industry viewpoints and efforts by standards developing organizations. Through this approach, a common theme is established which best describes a smart city. The content of this chapter can therefore form the basis of developing a standard definition of a global smart city, and subsequently can be used to develop a framework to measure the performance of a smart city. The authors also propose a definition which in their view provides a reasonably holistic description of a smart city. However, they recognize that a smart city may mean different things to different stakeholders, and therefore has a strong dependence on the “lens” through which a smart city is viewed.

What Constitutes a Smart City?

2018 ◽  
pp. 1-29
Author(s):  
Sekhar Kondepudi ◽  
Ramita Kondepudi
Keyword(s):  
Detailed Analysis ◽  
Smart City ◽  
Strong Dependence ◽  
Common Theme ◽  
Standard Definition ◽  
Definition Of ◽  
Holistic Description ◽  
Insight Into

This chapter provides an insight into what is meant by a Smart City and the underlying factors that make a city smart. The authors answer the question of “what constitutes a smart city” by presenting a multi-faceted approach including a detailed analysis of classical smart city definitions, attributes of a smart city, industry viewpoints and efforts by standards developing organizations. Through this approach, a common theme is established which best describes a smart city. The content of this chapter can therefore form the basis of developing a standard definition of a global smart city, and subsequently can be used to develop a framework to measure the performance of a smart city. The authors also propose a definition which in their view provides a reasonably holistic description of a smart city. However, they recognize that a smart city may mean different things to different stakeholders, and therefore has a strong dependence on the “lens” through which a smart city is viewed.

Petrophysical Rocks: Electrofacies and Lithofacies

2014 ◽  
Author(s):  
John H. Doveton
Keyword(s):  
Particle Size ◽  
Physical Properties ◽  
Sedimentary Rocks ◽  
Well Control ◽  
The Core ◽  
Lateral Extent ◽  
Petrophysical Logs ◽  
Definition Of

Many years ago, the classification of sedimentary rocks was largely descriptive and relied primarily on petrographic methods for composition and granulometry for particle size. The compositional aspect broadly matches the goals of the previous chapter in estimating mineral content from petrophysical logs. With the development of sedimentology, sedimentary rocks were now considered in terms of the depositional environment in which they originated. Uniformitarianism, the doctrine that the present is the key to the past, linked the formation of sediments in the modern day to their ancient lithified equivalents. Classification was now structured in terms of genesis and formalized in the concept of “facies.” A widely quoted definition of facies was given by Reading (1978) who stated, “A facies should ideally be a distinctive rock that forms under certain conditions of sedimentation reflecting a particular process or environment.” This concept identifies facies as process products which, when lithified in the subsurface, form genetic units that can be correlated with well control to establish the geological architecture of a field. The matching of facies with modern depositional analogs means that dimensional measures, such as shape and lateral extent, can be used to condition reasonable geomodels, particularly when well control is sparse or nonuniform. Most wells are logged rather than cored, so that the identification of facies in cores usually provides only a modicum of information to characterize the architecture of an entire field. Consequently, many studies have been made to predict lithofacies from log measurements in order to augment core observations in the development of a satisfactory geomodel that describes the structure of genetic layers across a field. The term “electrofacies” was introduced by Serra and Abbott (1980) as a way to characterize collective associations of log responses that are linked with geological attributes. They defined electrofacies to be “the set of log responses which characterizes a bed and permits it to be distinguished from the others.” Electrofacies are clearly determined by geology, because physical properties of rocks. The intent of electrofacies identification is generally to match them with lithofacies identified in the core or an outcrop.

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