scholarly journals Modelling the Nucleation, Growth and Agglomeration of Alumina Inclusions in Molten Steel by Combining Kampmann–Wagner Numerical Model with Particle Size Grouping Method

2021 ◽  
Author(s):  
Qifeng Shu ◽  
Tuomas Alatarvas ◽  
Ville-Valtteri Visuri ◽  
Timo Fabritius
Keyword(s):  
Particle Size ◽  
Diffusion Coefficient ◽  
Numerical Model ◽  
Interfacial Tension ◽  
Size Distribution ◽  
Inclusion Size ◽  
Number Density ◽  
Grouping Method ◽  
Peak Value ◽  
Nucleation Growth

AbstractRecent inclusion models are mainly focused on the compositional evolution of inclusion, steel and slag. Due to the importance of inclusion size distribution to steel properties, the evolution of inclusion size distributions should also be accounted for. As the first step to establish a model to predict the evolution of inclusion size distribution, the nucleation, growth and removal of alumina inclusions in molten steel were modeled by combining Kampmann and Wagner numerical model for nucleation, growth and coarsening with particle size grouping method. The model could simulate the time evolution of the size distribution of alumina inclusions after aluminum de-oxidation. The model was validated by using the experimental size distribution data of alumina inclusions available in the literature. The model calculation results were also compared with previous simulation results. The influences of interfacial tension between steel and inclusion and diffusion coefficient on the calculated inclusion size distribution were investigated. As interfacial tension between steel and alumina increases, the maximum number density decreases and the peak value of radius increases. As diffusion coefficient increases, the maximum number density decreases and the peak-value radius increases. The calculated size distribution curves showed a change from log normal to fractal, which is due to the change of dominating mechanisms for crystal growth and agglomeration.

scholarly journals Monte Carlo simulation for soot dynamics

2012 ◽  
Vol 16 (5) ◽  
pp. 1391-1394 ◽  
Author(s):  
Kun Zhou
Keyword(s):  
Particle Size ◽  
Monte Carlo ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Gas Phase ◽  
Volume Fraction ◽  
Soot Formation ◽  
Bimodal Distribution ◽  
Number Density ◽  
Stochastic Error

A new Monte Carlo method termed Comb-like frame Monte Carlo is developed to simulate the soot dynamics. Detailed stochastic error analysis is provided. Comb-like frame Monte Carlo is coupled with the gas phase solver Chemkin II to simulate soot formation in a 1-D premixed burner stabilized flame. The simulated soot number density, volume fraction, and particle size distribution all agree well with the measurement available in literature. The origin of the bimodal distribution of particle size distribution is revealed with quantitative proof.

scholarly journals Evolution of non-metallic inclusions during heat treatment

2020 ◽  
Vol 117 (4) ◽  
pp. 408
Author(s):  
Chengsong Liu ◽  
Bryan Webler
Keyword(s):  
Heat Treatment ◽  
Size Distribution ◽  
Inclusion Size ◽  
Isothermal Heat Treatment ◽  
Number Density ◽  
Inclusion Composition ◽  
Steel Microstructure ◽  
Metallic Inclusions ◽  
Higher Temperature ◽  
Average Size

Isothermal heat treatment can not only modify steel microstructure, but also non-metallic inclusions. In this work, heat treatment experiments were conducted between 1373 and 1573 K (1100 and 1300 °C) to study the evolution of inclusion composition, morphology, and size distribution. Results showed that during the heat treatment at 1473 and 1573 K (1200 and 1300 °C), two main kinds of inclusions initially in the steel, CaS and MgO–Al2O3–CaO–CaS, gradually transformed to (Ca, Mn)S and MgO–Al2O3–(Ca, Mn)S inclusions, and some MgO–Al2O3–CaO inclusions also transformed to MgO–Al2O3–(Ca, Mn)S. At the lowest temperature studied, 1373 K (1100 °C), little change was observed. No significant changes in number density and area fraction of the measured inclusions were observed, while the average size of inclusions increased after the heat treatment. The extent of transformation of CaS, MgO–Al2O3–CaO–CaS and MgO–Al2O3–CaO inclusions increased with decreasing inclusion size and higher temperature.

scholarly journals Model for Inclusion Precipitation Kinetics During Solidification of Steel Applications in MnS and TiN Inclusions

2020 ◽  
Vol 51 (6) ◽  
pp. 2905-2916 ◽  
Author(s):  
Qifeng Shu ◽  
Ville-Valtteri Visuri ◽  
Tuomas Alatarvas ◽  
Timo Fabritius
Keyword(s):  
Interfacial Tension ◽  
Simulation Model ◽  
Size Distribution ◽  
Inclusion Size ◽  
Bimodal Distribution ◽  
Precipitation Kinetics ◽  
Cooling Rates ◽  
Model Calculations ◽  
Mean Size ◽  
Present Simulation

AbstractA simulation model for inclusion precipitation kinetics during solidification of steel was proposed in this work. With the aim to calculate the inclusion size distribution during solidification of steel, the microsegregation calculation combined with the Kampmann–Wagner numerical (KWN) model for nucleation and growth of inclusion was incorporated into the present simulation model for calculating the evolution of inclusion size distribution during solidification of steel. The inclusion agglomeration due to Brownian collisions was also taken into account. The present simulation model was first applied in simulating precipitation of MnS during steel solidification and validated by the experimental data available in the literature. The effects of cooling rates and sulfur concentrations on the precipitation of MnS were investigated by the model calculations. Then, the present simulation model was applied in simulating the precipitation of TiN inclusions during steel solidification. The calculated mean size was found to be in good agreement with data available in the literature. Finally, the model was employed for studying the effects of interfacial tension between TiN and steel due to sulfur concentration change and cooling rates on the inclusion precipitation kinetics. It was found that interfacial tension between TiN and steel has a crucial influence on the precipitation of TiN. With an increase of the cooling rate, the size distribution of TiN transforms from the lognormal distribution to the bimodal distribution.

Sampling, testing and modeling particle size distribution in urban catch basins

2014 ◽  
Vol 70 (11) ◽  
pp. 1873-1879 ◽  
Author(s):  
G. Garofalo ◽  
M. Carbone ◽  
P. Piro
Keyword(s):  
Particle Size ◽  
Numerical Model ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Particle Diameter ◽  
Experimental Treatment ◽  
Catch Basin ◽  
Traffic Intersection ◽  
Parking Lot ◽  
Catch Basins

The study analyzed the particle size distribution of particulate matter (PM) retained in two catch basins located, respectively, near a parking lot and a traffic intersection with common high levels of traffic activity. Also, the treatment performance of a filter medium was evaluated by laboratory testing. The experimental treatment results and the field data were then used as inputs to a numerical model which described on a qualitative basis the hydrological response of the two catchments draining into each catch basin, respectively, and the quality of treatment provided by the filter during the measured rainfall. The results show that PM concentrations were on average around 300 mg/L (parking lot site) and 400 mg/L (road site) for the 10 rainfall-runoff events observed. PM with a particle diameter of <45 μm represented 40–50% of the total PM mass. The numerical model showed that a catch basin with a filter unit can remove 30 to 40% of the PM load depending on the storm characteristics.

scholarly journals Synergistic Effect of Laccase and Sugar Beet Pectin on the Properties of Concentrated Protein Emulsions and Its Application in Concentrated Coconut Milk

Molecules ◽  
2018 ◽  
Vol 23 (10) ◽  
pp. 2591 ◽  
Author(s):  
Pusen Chen ◽  
Wenxue Chen ◽  
Shan Jiang ◽  
Qiuping Zhong ◽  
Haiming Chen ◽  
...  
Keyword(s):  
Particle Size ◽  
Zeta Potential ◽  
Particle Size Distribution ◽  
Sugar Beet ◽  
Interfacial Tension ◽  
Size Distribution ◽  
Water Interface ◽  
Oil Water ◽  
Coconut Protein ◽  
The Stability

Concentrated coconut milk (CCM), a raw material from coconut products, is extremely unstable because of its high oil content (>30%). In this study, three model emulsions—primary emulsions stabilized by coconut proteins only, secondary emulsions stabilized by the conjugation of sugar beet pectin (SBP) and coconut protein, and laccase-treated secondary emulsions—were prepared to investigate the effects of different factors (coconut proteins, coconut proteins + SBP, laccase-treated emulsions) on the stability of model emulsions and the application of this method to real CCM. The stability of the emulsions was evaluated based on their interfacial tension, zeta potential, particle size distribution, rheological properties, and the assembly formation of SBP and coconut protein at the oil–water interface. Results showed that addition of SBP or laccase can increase the viscosity and reduce the interfacial tension of the emulsion, and the effect was concentration dependent. Zeta potential of the emulsion decreased with the increase of protein (from −16 to −32 mV) and addition of SBP (from −32 to −46 mV), and it was reduced when laccase was added (from −9.5 to −6.0 mV). The secondary emulsion exhibited the narrowest particle size distribution (from 0.1 to 20 μm); however, laccase-catalyzed secondary emulsions showed the best storage stability and no layering when the laccase content reached 10 U/100 g. Confocal laser scanning microscopy (CLSM) revealed that protein was adsorbed on the oil–water interface and SBP distributed in the continuous phase could undergo oxidative crosslinking by laccase. These results show that the stability of the concentrated emulsion can be effectively improved by adding SBP and laccase.

MODELING OF PARTICLE SIZE DISTRIBUTION (PSD) DURING THE AGEING PROCESS: A MODIFIED KWN MODEL

2009 ◽  
Vol 20 (07) ◽  
pp. 1113-1119
Author(s):  
LINDA WU ◽  
W. GEORGE FERGUSON
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Full Range ◽  
Particle Growth ◽  
Diffusion Control ◽  
Isothermal Heat Treatment ◽  
Treatment Conditions ◽  
Diffusion Controlled ◽  
Nucleation Growth

During the process of precipitation hardening, the phase decompositions in supersaturated solid solution (SSS) are often initiated by nucleation, then proceed to particle growth and eventually ended by Ostwald coarsening. To produce a model that is valid over the full range of transformation, the competing processes of nucleation, growth and coarsening cannot be considered in isolation. A powerful method for dealing with concomitant nucleation, growth and coarsening has been developed by Kampmann and Wagner. In the present work, the standard Kampmann and Wagner numerical model (KWN model) has been extended and modified to determine the dynamics of particle size distribution (PSD) as well as the microstructure evolution. In the present model, the newly nucleated particles are added to the corresponding size classes using the Trapezoidal shape assumption in order to eliminate the problem of discontinuity. During the growth and coarsening, since phase separations start as an interface-controlled transformation and gradually shift towards diffusion control, the mixed-mode (or co-controlled) model, therefore, is used in the present work instead of the diffusion controlled rate used in the standard KWN. Finally, the model is applied to aluminium alloys under both isothermal and non-isothermal heat treatment conditions.

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