Fractal characteristics of particle size distribution in dynamic flocculation process

2009 ◽  
Vol 14 (6) ◽  
pp. 511-517 ◽  
Author(s):  
Jun Nan ◽  
Weipeng He ◽  
Zhijun Zhang ◽  
Guibai Li
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Fractal Characteristics ◽  
Flocculation Process

Multi-fractal characteristics of particle size distribution of granular backfilling materials under different loads

2018 ◽  
Vol 60 (2) ◽  
pp. 202-208 ◽  
Author(s):  
Hao Yan ◽  
Jixiong Zhang ◽  
Jiaqi Wang ◽  
Nan Zhou ◽  
Sheng Zhang
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Fractal Characteristics

Water ecology and fractal characteristics of soil particle size distribution of three typical vegetations in Shell Island

2013 ◽  
Vol 33 (21) ◽  
pp. 7013-7022 ◽  
Author(s):  
夏江宝 XIA Jiangbao ◽  
张淑勇 ZHANG Shuyong ◽  
王荣荣 WANG Rongrong ◽  
赵艳云 ZHAO Yanyun ◽  
孙景宽 SUN Jingkuan ◽  
...  
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Soil Particle ◽  
Soil Particle Size ◽  
Soil Particle Size Distribution ◽  
Fractal Characteristics ◽  
Water Ecology

scholarly journals Effect of Grinding Time on the Particle Size Distribution Characteristics of Tuff Powder

2021 ◽  
pp. X
Author(s):  
Shuhua LIU ◽  
Hao WANG ◽  
Hongling WANG
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Milling Time ◽  
Milling Process ◽  
Coarse Grained ◽  
Distribution Model ◽  
Fine Grained ◽  
Fractal Characteristics ◽  
Grinding Time

We study the grinding dynamic behavior and particle size distribution (PSD) characteristics of tuff powder. With the analysis of particle size and data of activity test, the results indicate that tuff powder is easy to be ground for the coarse-grained while is difficult for the fine-grained. It is feasible to quantitatively express the milling process of tuff powder by Divas-Aliavden milling dynamic equation. The milling speed and the milling time are negatively correlated, and the grinding efficiency is minimized after 60 min. Equivalent particle size (EPS) is positively linearly correlated with the logarithm of grinding time, while specific surface area (SSA) is inversely correlated, both of them have a highly linear correlation. The PSD of tuff powder, which complies well with the Rosin-Rammler-Bennet (RRB) distribution model, has typical fractal characteristics, and its fractal dimension is also positively correlated with the milling time.

Derivation and Verification of the Breakage Rate Coefficient during Flocculation Process Based on Shear Strength

2013 ◽  
Vol 779-780 ◽  
pp. 1482-1489 ◽  
Author(s):  
Jian Liu ◽  
Min Zhou ◽  
Jian Hao Zhou ◽  
Qi Chao Hu ◽  
Jun Guo He
Keyword(s):  
Particle Size ◽  
Shear Strength ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Rate Coefficient ◽  
Northwest China ◽  
Rate Coefficients ◽  
Theoretical Derivation ◽  
Breakage Rate ◽  
Flocculation Process

The dynamics of flocculation is always one of the most interesting and difficult points for water treatment. The applicability of existing breakage rate coefficients was restricted due to the limitations of their theoretical derivation. In order to solve this problem, a breakage rate coefficient of flocculation process was derived based on shear strength. It could be described by the equation "s(m)=E0Fr1.2m1/D". Then it was applied to a flocculation model which described the change of particle size distribution during flocculation. Laboratory scale experiments were carried out to verify the feasibility of the new breakage rate coefficient with the typical surface water in northwest China characterized by low temperature and low turbidity. Results indicated that both the change of particle size distribution with time and the effects of operation variables on the stable particle size distribution could be excellently simulated, agreeing well with the experimental results with the relative error ranged from 3% ~ 17%. It was demonstrated that the breakage rate coefficient based on shear strength could be used to describe the breakage rate of flocs during flocculation.

Particle size distribution and removal by a chemical-biological flocculation process

2007 ◽  
Vol 19 (5) ◽  
pp. 559-563 ◽  
Author(s):  
Zhi-bin ZHANG ◽  
Jian-fu ZHAO ◽  
Si-qing XIA ◽  
Chang-qing LIU ◽  
Xing-sheng KANG
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Flocculation Process

scholarly journals Numerical Simulation of Rockfill Materials Based on Fractal Theory

2021 ◽  
Vol 12 (1) ◽  
pp. 289
Author(s):  
Hongxing Han ◽  
Yun Ma ◽  
Wei He ◽  
Weifang Yang ◽  
Xudong Fu
Keyword(s):  
Particle Size ◽  
Fractal Dimension ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Fine Particles ◽  
Mechanical Performance ◽  
Fractal Theory ◽  
Two Dimensions ◽  
Performance Indexes ◽  
Fractal Characteristics

With the use of the particle flow code in two dimensions, a fractal model is established with the number of particles of different particle fractions used as the statistics to study the fractal characteristics of particle size distribution. Numerically simulated specimens obtained by four scale methods are subjected to the relative density test and the biaxial compression test to explore the influences of fractal dimension D on the macroscopic and mesomechanical properties of specimens, as well as to study the relationship between fractal dimension D and different mechanical performance indexes. Results show that the particle size distribution of each of the four groups after scale exhibits fractal characteristics, with the fractal dimension D ranging from 1.27 to 2.03. The number of fine particles in the specimen increases with the fractal dimension D, the particle aggregates become more compact, the macroscopic mechanical properties of the specimens are improved, and a linear relationship exists between the fractal dimension D and different mechanical performance indexes. A large fractal dimension D corresponds to a great mesoparticle coordination number.

scholarly journals Análise da floculação por meio da distribuição do tamanho de partículas

Revista DAE ◽  
2019 ◽  
Vol 221 (68) ◽  
pp. 12-19
Author(s):  
Yuri Cardoso Mendes ◽  
Luan Serafim Mendes Gonçalves ◽  
Ricardo Henrique de Andrade Dutra ◽  
Rodrigo Braga Moruzzi ◽  
André Luiz de Oliveira
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Aluminum Sulfate ◽  
Distribution Functions ◽  
Adjustable Parameter ◽  
Velocity Gradients ◽  
Coagulation And Flocculation ◽  
Flocculation Process ◽  
Polyaluminium Chloride

Neste trabalho foi investigada a evolução da distribuição de tamanho de partículas no processo de floculação por meio de duas funções de distribuição contínuas distintas. A coagulação e a floculação foram estudadas em escala de bancada usando como coagulantes o sulfato de alumínio, cloreto férrico e cloreto de polialu- mínio, sob diferentes gradientes de velocidade médios e tempos de floculação. O acompanhamento do pro- cesso foi feito por meio de aquisição e análise de imagens dos flocos obtidos para cada coagulante em cada gradiente médio de floculação nos tempos de floculação de 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 30, 40, 50 e 60 minutos. Os resultados apresentados permitem concluir que o parâmetro ajustável da função Gama pode ser usado no acompanhamento da evolução da distribuição de tamanho de partícula e, a exemplo do parâmetro β, pode ser empregado em futuros estudos de modelagem do processo de floculação. The evolution of the particle size distribution in flocculation process was performed by two different distribution functions. Coagulation and flocculation studies were develop in bath essays using aluminum sulfate, ferric chloride and polyaluminium chloride under different velocity gradients and flocculation times. Image analysis was applied to monitoring the process in each one of the velocity gradient at the flocculation times of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 30, 40, 50 and 60 minutes. The results presented showed that the adjustable parameter of the Gamma function can be used to follow the evolution of the particle size distribution and, like the parameter β, can be used in future modeling studies of the flocculation process.

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