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Добірка наукової літератури з теми "Particle size distribution"

Автор: Grafiati

Опубліковано: 4 червня 2021

Оновлено: 14 березня 2023

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Статті в журналах з теми "Particle size distribution"

1

Lin, Hsin-Yi, Der-Jen Hsu, and Jia-Shan Su. "Particle Size Distribution of Aromatic Incense Burning Products." International Journal of Environmental Science and Development 6, no. 11 (2015): 857–60. http://dx.doi.org/10.7763/ijesd.2015.v6.712.

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2

Vítěz, T., and P. Trávníček. "Particle size distribution of sawdust and wood shavings mixtures." Research in Agricultural Engineering 56, No. 4 (December 1, 2010): 154–58. http://dx.doi.org/10.17221/8/2010-rae.

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Particle size distribution of the sample of waste sawdust and wood shavings mixtures were made with two commonly used methods of mathematical models by Rosin-Rammler (RR model) and by Gates-Gaudin-Schuhmann (GGS model).On the basis of network analysis distribution function F (d) (mass fraction) and density function f (d) (number of particles captured between two screens) were obtained. Experimental data were evaluated using the RR model and GGS model, both models were compared. Better results were achieved with GGS model, which leads to a more accurate separation of the different particle sizes in order to obtain a better industrial profit of the material.

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3

Nauman, E. Bruce, and Timothy J. Cavanaugh. "Method of Calculating True Particle Size Distributions from Observed Sizes in a Thin Section." Microscopy and Microanalysis 4, no. 2 (April 1998): 122–27. http://dx.doi.org/10.1017/s1431927698980102.

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Particle size distributions obtained from a thin section are usually a skewed version of the true distribution. A previous method for determining the parent distribution was questionable because negative particle frequencies could be obtained. Here, we describe a method of determining parent distributions of spherical particles using a model with adjustable parameters. Our calculated distributions are somewhat broader than the distributions obtained with previous methods, but the average particle sizes are nearly identical. The newly developed model is applicable to any type of transmission microscopy.

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4

Pfeifer, Sascha, Thomas Müller, Kay Weinhold, Nadezda Zikova, Sebastiao Martins dos Santos, Angela Marinoni, Oliver F. Bischof, et al. "Intercomparison of 15 aerodynamic particle size spectrometers (APS 3321): uncertainties in particle sizing and number size distribution." Atmospheric Measurement Techniques 9, no. 4 (April 7, 2016): 1545–51. http://dx.doi.org/10.5194/amt-9-1545-2016.

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Abstract. Aerodynamic particle size spectrometers are a well-established method to measure number size distributions of coarse mode particles in the atmosphere. Quality assurance is essential for atmospheric observational aerosol networks to obtain comparable results with known uncertainties. In a laboratory study within the framework of ACTRIS (Aerosols, Clouds, and Trace gases Research Infrastructure Network), 15 aerodynamic particle size spectrometers (APS model 3321, TSI Inc., St. Paul, MN, USA) were compared with a focus on flow rates, particle sizing, and the unit-to-unit variability of the particle number size distribution. Flow rate deviations were relatively small (within a few percent), while the sizing accuracy was found to be within 10 % compared to polystyrene latex (PSL) reference particles. The unit-to-unit variability in terms of the particle number size distribution during this study was within 10 % to 20 % for particles in the range of 0.9 up to 3 µm, which is acceptable for atmospheric measurements. For particles smaller than that, the variability increased up to 60 %, probably caused by differences in the counting efficiencies of individual units. Number size distribution data for particles smaller than 0.9 µm in aerodynamic diameter should only be used with caution. For particles larger than 3 µm, the unit-to-unit variability increased as well. A possible reason is an insufficient sizing accuracy in combination with a steeply sloping particle number size distribution and the increasing uncertainty due to decreasing counting. Particularly this uncertainty of the particle number size distribution must be considered if higher moments of the size distribution such as the particle volume or mass are calculated, which require the conversion of the aerodynamic diameter measured to a volume equivalent diameter. In order to perform a quantitative quality assurance, a traceable reference method for the particle number concentration in the size range 0.5–3 µm is needed.

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5

Pfeifer, S., T. Müller, K. Weinhold, N. Zikova, S. Santos, A. Marinoni, O. F. Bischof, et al. "Intercomparison of 15 aerodynamic particle size spectrometers (APS 3321): uncertainties in particle sizing and number size distribution." Atmospheric Measurement Techniques Discussions 8, no. 11 (November 3, 2015): 11513–32. http://dx.doi.org/10.5194/amtd-8-11513-2015.

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Abstract. Aerodynamic particle size spectrometers are a well-established method to measure number size distributions of coarse mode particles in the atmosphere. Quality assurance is essential for atmospheric observational aerosol networks to obtain comparable results with known uncertainties. In a laboratory study within the framework of ACTRIS (Aerosols, Clouds, and Trace gases Research Infrastructure Network), 15 aerodynamic particle size spectrometers (APS model 3321, TSI Inc., St. Paul, MN, USA) were compared with a focus on flow rates accuracy, particle sizing, and unit-to-unit variability of the particle number size distribution. Flow rate deviations were relatively small (within a few percent), while the sizing accuracy was found to be within 10 % compared to polystyrene latex (PSL) reference particles. The unit-to-unit variability in terms of the particle number size distribution during this study was within 10–20 % for particles in the range of 0.9 up to 3 μm, which is acceptable for atmospheric measurements. For particles smaller than that, the variability increased up to 60 %, probably caused by differences in the counting efficiencies of individual units. Number size distribution data for particles smaller than 0.9 μm in aerodynamic diameter should be only used with caution. For particles larger than 3 μm, the unit-to-unit variability increased as well. A possible reason is an insufficient sizing accuracy in combination with a steeply sloping particle number size distribution and the increasing uncertainty due to decreasing counting. This uncertainty of the particle number size distribution has especially to be considered if higher moments of the size distribution such as the particle volume or mass are calculated, which require the conversion of the aerodynamic diameter measured to a volume equivalent diameter. In order to perform a quantitative quality assurance, a traceable reference method for the particle number concentration in the size range 0.5–3 μm is needed.

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6

Ferguson, J. R., and D. E. Stock. "“Heavy” Particle Dispersion Measurements With Mono- and Polydisperse Particle Size Distributions." Journal of Fluids Engineering 115, no. 3 (September 1, 1993): 523–26. http://dx.doi.org/10.1115/1.2910170.

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A method is presented to estimate the effects of a polydisperse particle size distribution on the measured turbulent dispersion of particles. In addition, the analysis provides a means to estimate the standard deviation of the size distribution for which a class of particles may be considered monodisperse. If monodisperse particles are unavailable because of practical considerations (e.g., the required standard deviation of particle size is too small to obtain a sufficient quantity) then the method provides a means to correct the data of near monodisperse size distributions to reflect the dispersion of monodisperse particles.

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7

Kontkanen, Jenni, Chenjuan Deng, Yueyun Fu, Lubna Dada, Ying Zhou, Jing Cai, Kaspar R. Daellenbach, et al. "Size-resolved particle number emissions in Beijing determined from measured particle size distributions." Atmospheric Chemistry and Physics 20, no. 19 (October 5, 2020): 11329–48. http://dx.doi.org/10.5194/acp-20-11329-2020.

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Abstract. The climate and air quality effects of aerosol particles depend on the number and size of the particles. In urban environments, a large fraction of aerosol particles originates from anthropogenic emissions. To evaluate the effects of different pollution sources on air quality, knowledge of size distributions of particle number emissions is needed. Here we introduce a novel method for determining size-resolved particle number emissions, based on measured particle size distributions. We apply our method to data measured in Beijing, China, to determine the number size distribution of emitted particles in a diameter range from 2 to 1000 nm. The observed particle number emissions are dominated by emissions of particles smaller than 30 nm. Our results suggest that traffic is the major source of particle number emissions with the highest emissions observed for particles around 10 nm during rush hours. At sizes below 6 nm, clustering of atmospheric vapors contributes to calculated emissions. The comparison between our calculated emissions and those estimated with an integrated assessment model GAINS (Greenhouse Gas and Air Pollution Interactions and Synergies) shows that our method yields clearly higher particle emissions at sizes below 60 nm, but at sizes above that the two methods agree well. Overall, our method is proven to be a useful tool for gaining new knowledge of the size distributions of particle number emissions in urban environments and for validating emission inventories and models. In the future, the method will be developed by modeling the transport of particles from different sources to obtain more accurate estimates of particle number emissions.

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8

Ensor, David, Robert Donovan, and Bruce Locke. "Particle Size Distributions in Clean Rooms." Journal of the IEST 30, no. 6 (November 1, 1987): 44–49. http://dx.doi.org/10.17764/jiet.1.30.6.m24044316827q326.

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Measurements of particle size distributions smaller than 0.1 μm in Class 100 clean rooms are summarized. The size distributions were measured in operational rooms during periods of time with little activity—the so-called "at rest" conditions. A simple particle number balance model is proposed, illustrating the importance of filter penetration and atmospheric aerosol on the concentration of submicrometer particles. Preliminary calculations are used to explain the absence of < 0.1 μm diameter particles in the clean rooms tested. A ratio of condensation nucleus counter concentration to optical particle counter concentration is suggested as a parameter to provide an indication of changes in clean room particle size distribution.

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9

Rao, S., and C. R. Houska. "X-ray particle-size broadening." Acta Crystallographica Section A Foundations of Crystallography 42, no. 1 (January 1, 1986): 6–13. http://dx.doi.org/10.1107/s0108767386099981.

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X-ray diffraction profiles and Fourier coefficients are given for particles distributed according to experimentally verified size distributions. Calculations are based upon the log normal distribution of sphere diameters and intercept lengths in addition to a normal distribution of column heights. It is found that the diffraction profile is not sensitive to the fine details of the distribution but rather the mean column height and the column-height variation coefficient. Errors in particle-size determinations will result from an improper choice of the variation coefficient. Two simplified models are given that describe the diffraction profiles for a large range of variation coefficients.

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10

Friedman, B., A. Zelenyuk, J. Beránek, G. Kulkarni, M. Pekour, A. G. Hallar, I. B. McCubbin, J. A. Thornton, and D. J. Cziczo. "Aerosol measurements at a high elevation site: composition, size, and cloud condensation nuclei activity." Atmospheric Chemistry and Physics Discussions 13, no. 7 (July 9, 2013): 18277–306. http://dx.doi.org/10.5194/acpd-13-18277-2013.

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Abstract. Measurements of cloud condensation nuclei (CCN) concentrations, single particle composition and size distributions at a high-elevation research site from March 2011 are presented. The temporal evolution of detailed single particle composition is compared with changes in CCN activation on four days, two of which include new particle formation and growth events. Sulfate-containing particles dominated the single particle composition by number; biomass burning particles, sea salt particles, and particles containing organic components also were present. CCN activation largely followed the behavior of the sulfate-containing particle types; biomass burning particle types also likely contained hygroscopic material that impacted CCN activation. Newly formed particles also may contribute to CCN activation at higher supersaturation conditions. Derived aerosol hygroscopicity parameters from the size distribution and CCN concentration measurements are within the range of previous reports of remote continental kappa values.

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Дисертації з теми "Particle size distribution"

1

Patel, Ketan Shantilal. "Vibro-spring particle size distribution analyser." Thesis, University College London (University of London), 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.252097.

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2

Darley, A. D. "Particle size distribution effects in chocolate processing." Thesis, University of Bradford, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.253973.

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3

Ip, Trevor Tsz-Leung. "Influence of particle size distribution on fluidized bed hydrodynamics." Thesis, University of British Columbia, 1988. http://hdl.handle.net/2429/27891.

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Past literature has shown that the production efficiency of a fluidized bed can be affected by changing the particle size distribution. The hydrodynamics of fine particle fluidization were studied with FCC and glass bead powders which have different surface-volume mean particle diameter (40-110 μM) and particle size distributions (narrow cut, wide cut and bimodal) under ambient conditions. Increasing the mean particle size increases the minimum fluidization velocity, minimum bubbling velocity and dense phase velocity (U[sub d]) while decreasing the voidages at minimum fluidization and minimum bubbling and the dense phase voidage (∈[sub d]) as well as the fractional bubble free bed expansion. Increasing the particle size spread increases U[sub d] and decreases ∈[sub d] for FCC, but no clear conclusion can be made for glass bead powders. Increasing the static bed height decreases U[sub d] and ∈[sub d] of FCC powders though it has no effect on minimum fluidization and bubbling properties. The magnitude of pressure fluctuations increases with increasing superficial gas velocity and as the size spread of the FCC powder becomes more narrow. However, the frequency of fluctuations is independent of each of these factors. Therefore, the quality and production efficiency of the fluidization process should improve with the use of a wide and continuous size distribution powder.
Applied Science, Faculty of
Chemical and Biological Engineering, Department of
Graduate

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4

Jahanzad, Fatemeh. "Evolution of particle size distribution in suspension polymerisation reactions." Thesis, Loughborough University, 2004. https://dspace.lboro.ac.uk/2134/10300.

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Suspension polymerisation processes are commercially important for the production of polymer beads having wide applications. Polymers produced by suspension polymerisation can be directly used for particular applications such as chromatographic separations and ion-exchange resins. Particle Size Distribution (PSD) may appreciably influence the performance of the final product. Therefore, the evolution of PSD is a major concern in the design of a suspension polymerisation process. In this research, methyl methacrylate (MMA) has been used as a model monomer. A comparative study of MMA suspension polymerisation and MMNwater dispersion was carried out, for the first time, to elaborate the evolution of mean particle size and distribution. Polyvinyl alcohol (PVA) and Lauroyl Peroxide (LPO) have been used as stabiliser and initiator, respectively. Polymerisation experiments were carried out using a 1-litre jacketed glass reactor equipped with a turbine impeller and a condenser. The stabiliser, initiator and chain transfer concentrations, inhibitor concentration and type, reaction temperature, impeller speed, and monomer hold up were used as variables. A mathematical model was developed to predict the kinetics of polymerisation as well as the evolution of PSD by population balance modelling. The experimental results were compared with the model predictions. From the comprehensive experimental results, the characteristic intervals of a typical suspension polymerisation were realised as: 1) Transition stage during which PSD narrows dramatically and drop size decreases exponentially due to higher rate of drop break up in comparison with drop coalescence . _ until a steady state is reached. The importance, and even the existence, of the transition stage have been totally ignored in the literature. The results indicate that increasing the impeller speed, and PV A concentration will lead to a shorter transition period. Also increasing the rate of reaction, via increasing initiator concentration, and reaction temperature will shorten this period. ABSTRACT 2) Quasi steady-state stage during which the rate of drop break up and drop coalescence are almost balanced leading to a steady-state drop size and distribution. The occurrence of this stage is conditional. Low impeller speed and PV A concentration may remove the quasi steady-state stage completely and drops may start growing considerably after a sharp decrease in size during the transition stage. 3) Growth stage during which the rate of drop break up considerably falls below the rate of drop coalescence due to the viscosity build up in drops leading to drop enlargement and PSD broadening. Results show that the onset of the growth stage may not be fixed and it depends on the balance of the forces acting on drops. The onset of the growth stage in terms of time was advanced with decreasing stirring speed and PV A concentration and increasing monomer hold up. Under a static steady state, which is formed when a high concentration of PV A is used, there is almost no growth. 4) Identification stage during which a solid-liquid suspension is attained and the PSD and mean particle size remain unchanged afterwards. The onset of this stage appears to be fairly constant for different formulations. The developed model could fairly predict the rate of polymerisation. It was also capable of predicting the evolution of particle size average and distribution qualitatively in the course of polymerisation. The results can be used as a guideline for the control of particle size and distribution in suspension polymerisation reactors. A more quantitative exploitation of the model has been left for a future research.

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5

Salimi, Farhad. "Characteristics of spatial variation, size distribution, formation and growth of particles in urban environments." Thesis, Queensland University of Technology, 2014. https://eprints.qut.edu.au/69332/1/Farhad_Salimi_Thesis.pdf.

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This thesis is the first comprehensive study of important parameters relating to aerosols' impact on climate and human health, namely spatial variation, particle size distribution and new particle formation. We determined the importance of spatial variation of particle number concentration in microscale environments, developed a method for particle size parameterisation and provided knowledge about the chemistry of new particle formation. This is a significant contribution to our understanding of processes behind the transformation and dynamics of urban aerosols. This PhD project included extensive measurements of air quality parameters using state of the art instrumentation at each of the 25 sites within the Brisbane metropolitan area and advanced statistical analysis.

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6

Zhang, Shuo. "Relationship between particle size distribution and porosity in dump leaching." Thesis, University of British Columbia, 2017. http://hdl.handle.net/2429/63383.

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Fluid flow is a critical process involved in the valuable metals extraction from low grade ore in heap and dump leaching as well as the release of harmful substances from waste rock piles. The mechanisms by which fluids move through the porous media depend on the fluid properties and the intrinsic properties of the porous media, with permeability being one critical factor. Particle size distribution is a key factor that affects permeability by forming pores of different structure and size. The objective of this research was to assess the particle size distribution in heterogeneous packed ore/rock beds and quantify the effect of particle size distribution on porosity. In the studied mine site, the particle size distribution in the dump leach pad was determined by analyzing aerial images of multiple dump faces taken by a drone. Particles spanned a wide range in size from less than 2 cm in diameter to larger than 2 m in diameter, with a P80 to be 2 m. The spatial segregation of fine particles and coarse particles along the dump faces was observed, which may contribute to the formation of preferential flow. The effect of particle size distribution on porosity was quantified by two methods: the bulk density and CT-imaging techniques. Porosities under three particle sorting conditions were studied: narrow-sized particles, poorly sorted particles and well sorted particles. For narrow-sized particles, the porosity measured by the bulk density method decreased as the particle size was increased up to 0.151 mm after which the porosity remained constant in the range tested. The influence of the particle size on the porosity for the well sorted particles was similar to that of the narrow-sized particles from both of the methods. For poorly sorted particles, in both methods, porosity decreased as the fraction of the fine particles added was increased to a certain value, after which the porosity started to increase as the fraction of fine particles was further increased. The results have important implications for metal extraction from run of mine ores using dump leaching and release of contaminants from waste rock piles by influencing fluid flow properties.
Applied Science, Faculty of
Materials Engineering, Department of
Graduate

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7

Leng, Tianyang. "Cellulose Nanocrystals: Particle Size Distribution and Dispersion in Polymer Composites." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/34073.

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This thesis describes the characterization of the particle size distribution of cellulose nanocrystals (CNC), the synthesis and characterization of fluorescent CNCs, and the development of a fluorescence microscopy method to probe the distribution of fluorescent CNCs in polymer composites. In this thesis, several methods are used to characterize the size of CNC particles. Size distribution measurements by single particle counting methods (Transmission electron microscopy, Atomic force microscopy) are compared to an ensemble method, Dynamic lighting scattering (DLS) and differences between the various methods will be discussed. The effect of sonication on the CNC size distributions measured by AFM and DLS is examined. Furthermore, a reliable and reproducible method for re-dispersing dry CNC powder will be explored in this chapter since CNC is often stored in a dry environment due to its stability. Rhodamine B isothiocyanate (RBITC) and 5-(4,6-dichlorotriazinyl) amino fluorescein (DTAF) were selected for labelling CNCs. These dyes have the advantage of being cheap and readily available and compatible with relatively simple synthetic chemistry. The photophysical properties of all dye labeled CNCs were studied in more detail than in previous studies. The focus is on understanding the most appropriate labeling efficiency to maximize the ability to detect individual CNCs while minimizing the amount of dye used to avoid modifying the CNC properties. The characterization methods include ensemble methods such as UV-Vis absorption and scattering measurements, fluorescence spectroscopy and single molecule methods such as Total internal reflection fluorescence microscopy (TIRFM), Atomic force microscopy (AFM) and correlated TIRFM/AFM measurements. All of these methods have their advantages and disadvantages. After characterization, the most suitable dye labeled CNC sample was selected for development of a fluorescence microscopy method to characterize CNC distribution in CNC/polymer composites. The dye labeled CNC has been incorporated into polyvinyl alcohol (PVA) films and studied by fluorescence microscopy. These experiments demonstrated that the level of CNC agglomeration varies significantly for different film preparation methods, indicating that fluorescence microscopy is a useful and easily accessible method for optimizing film preparation. The self-quenching of the dye in the film was also measured and discussed and is an important consideration for choice of the dye loading and CNC content in the films.

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8

Hildebrand, Erin N. "The effect of particle size distribution on spectral backscattering coefficient." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0015/MQ57296.pdf.

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9

Gursky, Barry Michael. "Particle size distribution optimization of filler content in shingle asphalt." Thesis, Georgia Institute of Technology, 1986. http://hdl.handle.net/1853/20989.

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10

Rekhibi, Soliman Abograra. "Condition monitoring of mining machinery using debris particle size distribution." Thesis, University of Nottingham, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.335821.

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Книги з теми "Particle size distribution"

1

Provder, Theodore, ed. Particle Size Distribution. Washington, DC: American Chemical Society, 1987. http://dx.doi.org/10.1021/bk-1987-0332.

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2

Provder, Theodore, ed. Particle Size Distribution III. Washington, DC: American Chemical Society, 1998. http://dx.doi.org/10.1021/bk-1998-0693.

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3

Provder, Theodore, ed. Particle Size Distribution II. Washington, DC: American Chemical Society, 1991. http://dx.doi.org/10.1021/bk-1991-0472.

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4

1939-, Provder Theodore, American Chemical Society. Division of Polymeric Materials: Science and Engineering., and American Chemical Society Meeting, eds. Particle size distribution III: Assessment and characterization. Washington, DC: American Chemical Society, 1998.

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5

1939-, Provder Theodore, American Chemical Society. Division of Polymeric Materials: Science and Engineering., and American Chemical Society Meeting, eds. Particle size distribution: Assessment and characterization. Washington, D.C: American Chemical Society, 1987.

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6

1939-, Provder Theodore, American Chemical Society. Division of Polymeric Materials: Science and Engineering., and American Chemical Society Meeting, eds. Particle size distribution II: Assessment and characterization. Washington, DC: American Chemical Society, 1991.

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7

Etkin, Bernard. Research on an aerodynamic particle separator (the EPS). Downsview, Ont: Institute for Aerospace Studies, 1986.

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8

Etkin, Bernard. Research on an aerodynamic particle separator (the EPS). [S.l.]: Hemisphere Publishing Corp, 1988.

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9

Rosbury, Keith D. Generalized particle size distribution for use in preparing size specific particulate emission inventories. Research Triangle Park, NC: U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, 1986.

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10

Koskinen, Jukka Tapio. Use of population balances and particle size distribution analysis to study particulate processes affected by simultaneous mass and heat transfer an nonuniform flow conditions. Lappeenranta: Lappeenranta University of Technology, 1993.

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Частини книг з теми "Particle size distribution"

1

Stock, Ruth S., and W. Harmon Ray. "Measuring Particle Size Distribution of Latex Particles Using Dynamic Light Scattering." In Particle Size Distribution, 105–14. Washington, DC: American Chemical Society, 1987. http://dx.doi.org/10.1021/bk-1987-0332.ch007.

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2

Beddow, J. K. "Size, Shape, and Texture Analysis." In Particle Size Distribution, 2–29. Washington, DC: American Chemical Society, 1987. http://dx.doi.org/10.1021/bk-1987-0332.ch001.

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3

Jang, B. Z., and Y. S. Chang. "Assessment of Particle Size Distribution and Spatial Dispersion of Rubbery Phase in a Toughened Plastic." In Particle Size Distribution, 30–45. Washington, DC: American Chemical Society, 1987. http://dx.doi.org/10.1021/bk-1987-0332.ch002.

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4

Weiner, B. B., and W. W. Tscharnuter. "Uses and Abuses of Photon Correlation Spectroscopy in Particle Sizing." In Particle Size Distribution, 48–61. Washington, DC: American Chemical Society, 1987. http://dx.doi.org/10.1021/bk-1987-0332.ch003.

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5

Vaidya, R. A., M. J. Mettille, and R. D. Hester. "A Comparison of Methods for Determining Macromolecular Polydispersity from Dynamic Laser Light Scattering Data." In Particle Size Distribution, 62–73. Washington, DC: American Chemical Society, 1987. http://dx.doi.org/10.1021/bk-1987-0332.ch004.

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Bott, S. E. "Submicrometer Particle Sizing by Photon Correlation Spectroscopy: Use of Multiple-Angle Detection." In Particle Size Distribution, 74–88. Washington, DC: American Chemical Society, 1987. http://dx.doi.org/10.1021/bk-1987-0332.ch005.

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7

Herb, C. A., E. J. Berger, K. Chang, I. D. Morrison, and E. F. Grabowski. "Using Quasi-Elastic Light Scattering To Study Particle Size Distributions in Submicrometer Emulsion Systems." In Particle Size Distribution, 89–104. Washington, DC: American Chemical Society, 1987. http://dx.doi.org/10.1021/bk-1987-0332.ch006.

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8

Xu, Renliang, James R. Ford, and Benjamin Chu. "Photon Correlation Spectroscopy, Transient Electric Birefringence, and Characterization of Particle Size Distributions in Colloidal Suspensions." In Particle Size Distribution, 115–32. Washington, DC: American Chemical Society, 1987. http://dx.doi.org/10.1021/bk-1987-0332.ch008.

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9

Gulari, Erdogan, A. Annapragada, Esin Gulari, and B. Jawad. "Determination of Particle Size Distributions Using Light-Scattering Techniques." In Particle Size Distribution, 133–45. Washington, DC: American Chemical Society, 1987. http://dx.doi.org/10.1021/bk-1987-0332.ch009.

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10

Frock, Harold N. "Particle Size Determination Using Angular Light Scattering." In Particle Size Distribution, 146–60. Washington, DC: American Chemical Society, 1987. http://dx.doi.org/10.1021/bk-1987-0332.ch010.

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Тези доповідей конференцій з теми "Particle size distribution"

1

Andrews, G. E., A. G. Clarke, N. Y. Rojas, T. Sale, and D. Gregory. "Diesel Particle Size Distribution: The Conversion Of Particle Number Size Distribution To Mass Distribution." In International Spring Fuels & Lubricants Meeting. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2001. http://dx.doi.org/10.4271/2001-01-1946.

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2

Ventola, Andrea, and Roman D. Hryciw. "On-Site Particle Size Distribution by FieldSed." In Eighth International Conference on Case Histories in Geotechnical Engineering. Reston, VA: American Society of Civil Engineers, 2019. http://dx.doi.org/10.1061/9780784482131.015.

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3

Ma, Binjian, and Debjyoti Banerjee. "Predicting Particle Size Distribution in Nanofluid Synthesis." In ASME 2017 Heat Transfer Summer Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/ht2017-5048.

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Wet chemistry approaches have been widely used to synthesize nanoparticle suspensions with different size and shape. Controlling particle size is crucial for tailoring the properties of the nanofluid. In this study, we simulated the particle size growth during a thermal-chemical nanofluid synthesis routine. The simulation was based on the population balance model for aggregation kinetics, which is coupled with thermal decomposition, nucleation and crystal growth kinetics. The simulation result revealed a typical burst nucleation mechanism towards self-assembly of supersaturated monomers in the nanoparticle formation process and the shift from monodispersed particles to polydispersed particles by the particle-particle coagulation.

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4

Lee, Hakyeul, Matthew Hudson, and Janz Rondon. "Particle Size Distribution Acid Soluble Cement." In Unconventional Resources Technology Conference. Society of Petroleum Engineers, 2015. http://dx.doi.org/10.2118/178683-ms.

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5

Kuhlman, Michael R., Rachel E. Gooding, Vladimir G. Kogan, and Curtis Bridges. "Particle size distribution of cocaine hydrochloride." In Enabling Technologies for Law Enforcement and Security, edited by Pierre Pilon and Steve Burmeister. SPIE, 1997. http://dx.doi.org/10.1117/12.266779.

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6

A.K.Jha and V. M. Puri. "Percolation Segregation for Broad Particle Size Distribution." In 2005 Tampa, FL July 17-20, 2005. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2005. http://dx.doi.org/10.13031/2013.19517.

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7

Swanepoel, F., D. M. Weber, and G. Metzner. "Particle size distribution determination using acoustic information." In 1999 IEEE Africon. 5th Africon Conference in Africa. IEEE, 1999. http://dx.doi.org/10.1109/afrcon.1999.820840.

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8

Daun, K. J., B. J. Stagg, F. Liu, G. J. Smallwood, and D. R. Snelling. "Determining Aerosol Particle Size Distribution Using Time-Resolved Laser-Induced Incandescence." In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-13595.

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Time-resolved laser-induced incandescence is a powerful tool for determining the physical characteristics of aerosol dispersions of refractory nano-particles. In this procedure, particles within a small aerosol volume are heated with a nano-second laser pulse, and the temporal incandescence of the particles is then measured as they return to the ambient gas temperature. It is possible to infer particle size distribution from the temporal decay of the LII signal since the cooling rate of an individual particle depends on its area-to-volume ratio. This requires solving a mathematically ill-posed inverse problem, however, since the measured LII signal is due to the incandescence contributed by all particle sizes within the aerosol volume. This paper reviews techniques proposed in the literature for recovering particle size distributions from time-resolved LII data. The characteristics of this ill-posed problem are then discussed in detail, particularly the issues of solution stability and uniqueness. Finally, the accuracy and stability of each method is evaluated by performing a perturbation analysis, and the overall performance of the techniques is compared.

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9

Khalek, Imad A. "Characterization of Particle Size, Number, and Mass Emissions From a Diesel Powered Generator." In ASME 2006 Internal Combustion Engine Division Fall Technical Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/icef2006-1533.

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Total (volatile plus solid) and solid particle size, number, and mass emitted from a 3.8 kW diesel powered generator were characterized using a Scanning Mobility Particle Sizer (SMPS) that measures the size distribution of particles, and a catalytic stripper that facilitates the measurement of solid particles. The engine was operated at a constant speed for six steady-state engine operations ranging from idle to rated power. The solid particle size distributions were mainly monomodal lognormal distributions in nature reflecting a typical soot agglomerate size distribution with a number mean diameter in the size range from 98 nm to 37 nm as the load decreases from high to low. At idle, M6, however, the solid particle distribution was bimodal in nature with a high number of solid nanoparticles in the sub-20 nm size range. It is likely that these solid particles nucleated later in the combustion process from metallic ash typically present in the lube oil. The total particle size distributions exhibited a bimodal structure only at light load, M5, engine operation, where a high number of volatile nanoparticles were observed. The rest of the operating conditions exhibited monomodal distributions although the nature of the particles was vastly different. For the medium load modes, M2, M3, and M4, the particles were mainly solid particles. For the rated power, M1, and idle, M6, modes of engine operation, significant number of volatile particles grew to a size nearing that of soot particles making the distribution monomodal, similar to that of a solid particle distribution. This shows that monomodal distributions are not necessarily solid particle but they can be strongly dominated with volatile particles if significant particle growth takes place like the case at M1, and M6. The total number and mass concentration were extremely high at engine rated power. The number concentration exceeded 1.2 billion particles per cubic centimeter and the mass exceeded 750 milligrams per cubic meter. The number concentration is more than five orders of magnitude higher than a typical ambient level concentration, and the mass concentration is more than four orders of magnitude higher. It is important to indicate, however, that if the engine power rating is lowered by 35 percent from its designated level, both particle mass and number emissions will be reduced by two orders of magnitude. By measuring total and solid particle size and number concentration of particles, one can calculate other metrics such as surface area and mass to provide detail information about particle emissions. Such information can serve as an important database where all metrics of particle emissions are captured.

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10

Wang, Tom D., Enson Chang, and Randy J. Patton. "Measurement of ocean-particle size distribution by small-angle light scattering." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1990. http://dx.doi.org/10.1364/oam.1990.mrr6.

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Ocean-particle sizes range from submicrometers to tens of micrometers and roughly follow an inverse-power-law distribution. The abundance of small particles causes most light-scattering techniques for particle-size measurement to suffer from instability or inaccuracy. This paper describes a compact instrument that determines the number density of particles of 1-50μm in size by measuring near-forward scattering (< 3.5°). The intensity data is inverted by a modified Phillips-Twomey method to obtain the size distribution. This technique is stable, accurate, and efficient in the size range of interest. The instrument performs well when applied to samples of simulated sea water. The simple design of the instrument, in conjunction with the robustness of the inversion algorithm, makes it a strong candidate for development into an in situ, expendable instrument.

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Звіти організацій з теми "Particle size distribution"

1

Spriggs, G., and A. Ray-Maitra. Particle-Size-Distribution of Nevada Test Site Soils. Office of Scientific and Technical Information (OSTI), September 2007. http://dx.doi.org/10.2172/922100.

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2

Okhuysen, W., and J. D. Gassaway. Particle size distribution instrument. Topical report 13. Office of Scientific and Technical Information (OSTI), April 1995. http://dx.doi.org/10.2172/39146.

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3

Shah, K. B. Particle size distribution of indoor aerosol sources. Office of Scientific and Technical Information (OSTI), October 1990. http://dx.doi.org/10.2172/6325100.

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4

Bigl, Matthew, Samuel Beal, and Charles Ramsey. Determination of residual low-order detonation particle characteristics from Composition B mortar rounds. Engineer Research and Development Center (U.S.), August 2022. http://dx.doi.org/10.21079/11681/45260.

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Empirical measurements of the spatial distribution, particle-size distribution, mass, morphology, and energetic composition of particles from low-order (LO) detonations are critical to accurately characterizing environ-mental impacts on military training ranges. This study demonstrated a method of generating and characterizing LO-detonation particles, previously applied to insensitive munitions, to 81 mm mortar rounds containing the conventional explosive formulation Composition B. The three sampled rounds had estimated detonation efficiencies ranging from 64% to 82% as measured by sampled residual energetic material. For all sampled rounds, energetic deposition rates were highest closer to the point of detonation; however, the mass per radial meter varied. The majority of particles (>60%), by mass, were <2 mm in size. However, the spatial distribution of the <2 mm particles from the point of detonation varied be-tween the three sampled rounds. In addition to the particle-size-distribution results, several method performance observations were made, including command-detonation configurations, sampling quality control, particle-shape influence on laser-diffraction particle-size analysis (LD-PSA), and energetic purity trends. Overall, this study demonstrated the successful characterization of Composition B LO-detonation particles from command detonation through combined analysis by LD-PSA and sieving.

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5

Patterson, Philip, and William Lum. Laser Scattering Particle Size Distribution Analyses of Pigments. Fort Belvoir, VA: Defense Technical Information Center, September 1998. http://dx.doi.org/10.21236/ada353710.

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6

Kerlin, M., E. Balboni, and K. Knight. Characterization, Chemistry, and Particle Size Distribution of Fallout Particles Isolated from Filter Samples. Office of Scientific and Technical Information (OSTI), March 2022. http://dx.doi.org/10.2172/1864128.

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7

Tresouthick, S. W. Energy conservation potential of Portland Cement particle size distribution control. Office of Scientific and Technical Information (OSTI), January 1985. http://dx.doi.org/10.2172/6299351.

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8

Tresouthick, S. W., and S. J. Weiss. Energy conservation potential of Portland cement particle size distribution control. Office of Scientific and Technical Information (OSTI), January 1986. http://dx.doi.org/10.2172/6047449.

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9

Tresouthick, S. W., and S. J. Weiss. Energy conservation potential of Portland cement particle size distribution control. Office of Scientific and Technical Information (OSTI), January 1986. http://dx.doi.org/10.2172/6047458.

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10

Tresouthick, S. W., and S. J. Weiss. Energy conservation potential of Portland Cement particle size distribution control. Office of Scientific and Technical Information (OSTI), January 1985. http://dx.doi.org/10.2172/6047465.

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