Through the test analysis carried out for the reactivity,strength after reaction of Meishan coke and quality index of coal blend,the results show that coke ash content,volatile matter and maximum thickness value Y of colloidal matter layer of coal blend are the important factors influencing the thermal property of coke,while the cold strengths M40 and M10 of coke have no obvious relationship with the thermal property of coke.
The blending and coking test is carried out with 5% of petroleum coke in different sizes added into coal blend, comparing optimum coal blending proposal with the coke quality produced from coal blend in production of WISCO, coke ash is lowered by 0.57% , sulfur increased by 0.02% , the crushing strength is basically unchanged, the reactivity is reduced by 3.12% , the strength after reaction is increased by 6.59% .
On basis of experimental analysis and theoretical research on coal blend, we receive a conclusion that the relationship between the coal blend properties and compose coals is nonlinear, which is initially regarded as linearity.
The result also indicates that ignition temperature of coal blend is mainly decided by the properties of easily ignited coal when coals blended with great different ignition properties.
The authors have studied the fire point,explosion properties and combustion characteristics of coal blend which contains anthracite with 20%~50% semi-bituminous coal.
in coal blend the blending proportion of coking coal is controlled, after 14SM, 1/2ZN or 26FM are properly blended, its result in coke thermal reactivity is better than coking of single coking coal.
Based on the coal blend of Tianjin Tiantie Coking Plant and individual actual data for producing coke, under the MATLAB environment, the study of prediction method for coke quality based on neural network was conducted.
Coal blending coking test for many proposals have been made on 40kg test oven and analysis on coke reactivity from single kind of coal and coal blend has been made. The results show that when single kind of coking coal is used for coking, after reaction strength of 26JM is better;
Very conclusive document for the influence of coal blend characteristics and coke mass temperature on coke quality are available,however,the influence of carbonization time has not been addressed adequately.
According to coal blending and coke-making principle, coke formation characteristic of coal and nature of binder and in combination with coal source situation of Xuanhua Iron & Steel Company, the coking experimental study and semi-commercial production test study with binder blended into single coal and coal blend is conducted, the study result is applied in industrial production.
The CFD modeling effort was performed utilizing a current typical coal blend of 60% sub-bituminous PRB coal and 40% eastern bituminous coal.
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The volatile mix for the coal blend is as for the cost optimisation at its lowest bound.
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Additionally, a correlation between power plant operating conditions or coal blend and one or more unburned carbon forms present in fly ash may exist.
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This paper introduces a new modern efficient method for remoying PAH from coke oven waterwaster, the PAH removal—efficiencies above 95% can be achieved. The polluted wood flour and organic material is recycled directly to the coal blend so no extra waste is produced. This method development at Hoogovens is started in 1984 and is achieved on industrial application in 1991 in the Netherlands.
The deashing effect of five different rank coals used for preparing the metallurgic coke is studied by treating with NaOH, NH 3·H 2O and C 2Cl 4 under morderate operating conditions. The coking indexes ( G ) under the optimum operating condition are evaluated. The main results are as follows: The deashing ratio of the sample treated with NaOH is the highest, the coking index generally has a little decrease cleaned with NH 3·H 2O. The deashing effect of C 2Cl 4 is very nice. However, the part...
Based on the mathematical model for predicting the coke qualities the optimum coking-coal mixture can be easily achieved by using the linear regression method on computer. This paper gives the computing programs for coal blend optimization which have found successful practical applications.