2018
DOI: 10.1007/s40789-018-0216-3
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Design of experiments to optimize the extraction parameters of a power grade Indian coal

Abstract: Low grade high ash coals with difficult physical washability characteristics require chemical cleaning techniques such as solvent extraction to obtain super clean coal with lower ash contents. Kedla, an Indian low grade coal has ash content around 44%-50% and there is a need to maximize its solvent extraction yield so as to make this power grade coal industrially useful. This paper highlights the use of definitive screening design and response surface methodology to extract the maximum organic matter from Kedl… Show more

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Cited by 8 publications
(5 citation statements)
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“…The BBD constitutes a rotating spherical response surface that features a center point, as well as midpoints between the corners, all of which are circumscribed on a sphere. This design, determined by the process requirements, can optimize multiple chemical and physical processes with a suitable number of experiments [ [17] , [18] , [19] , [20] ].…”
Section: Methodsmentioning
confidence: 99%
“…The BBD constitutes a rotating spherical response surface that features a center point, as well as midpoints between the corners, all of which are circumscribed on a sphere. This design, determined by the process requirements, can optimize multiple chemical and physical processes with a suitable number of experiments [ [17] , [18] , [19] , [20] ].…”
Section: Methodsmentioning
confidence: 99%
“…To solve the relevant parameters of the creep equation, combined with the creep test data, the mathematical optimization software 1stOpt is used; based on the quasi-Newton method and general global optimization method 36,37 , the solution method of equation ( 7) is given under different conditions, as shown in Table 4: The shear creep model under fatigue loading can be obtained by introducing the relevant parameters in Table 4 into equation (7). To verify the accuracy of the model, comparison diagrams between the test data and the theoretical curves are drawn, as shown in Fig.…”
Section: Model Validationmentioning
confidence: 99%
“…RSM is useful during method development and optimization of processes to establish the relationship between a set of quantitative experimental variables and one or more response variables. With the help of the optimizer function in the tool, optimum parameter are predicted [34] …”
Section: Introductionmentioning
confidence: 99%