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However, this modeling method has two problems: it takes too much time to model all movements, and accuracy depends on the modeling technician.
This modeling method has high computational efficiency and clear physical meanings.
The modeling method has important theoretical and engineering values for the research of combustion technology, large-scale design and operating performances of a circulating fluidized bed.
A comprehensive two-phase compressible gas-solid particle computational fluid dynamics-based modeling method has been developed and applied to study the erosion and fouling along flow path surfaces due to particle impact.
For the first time, a unified data-driven model for the prediction of boiling heat transfer coefficient in a thermosiphon reboiler, using support vector regression (SVR) as the modeling method, has been proposed.
Thus, the modeling method has been shown to be efficient.
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These three methods, i.e. a conventional quenching and image analysis method, calculations using two simplistic solidification models, and a proposed DTA coupled with mathematical modeling method, have been illustrated.
The results from the present modeling method have been obtained considering ten assumed modes compared with those reported by Ozgumus and Kaya (2006) using the differential transform method.
An off-line optimization technique based on soft modeling methods has been used to determine the optimum conditions for the separation of eight carbonyl-2,4-dinitrophenylhydrazones by gas chromatography equipped with a nitrogen phosphorous detector.
Since then, different modeling methods have been applied to tackle this and other modeling problems.
Urban modeling methods have traditionally followed a forward modeling approach.
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