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2篇 您的检索式：作者名="Musango Lungu"

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		题名	作者	年代	出处	被引量
	1	Assessment of the TFM in predicting the onset of turbulent fluidization显示文摘Accurate prediction of the onset of turbulent fluidization still remains elusive owing to the dependence of the transition velocity on several factors including measurement methods and interpretation of results. In this work, numerical simulations using the two fluid model (TFM) are performed in an attempt to predict the regime change reported by Gopalan etal.(2016) in a small scale pseudo-2D gas-solid fluidized bed containing Geldart D particles. Various time and frequency domain analyses were applied on predicted absolute and differential pressure time series data to reveal the bed dynamics. Numerical predictions of the transition velocity, Uc are in reasonably good agreement with experimental results from the small scale challenge problem. The literature correlations completely fail to predict the transition velocity for the system considered in this work. This work thus provides a different approach for validating the CFD model against experimental measurements.	Musango Lungu Haotong Wang Jingdai Wang Ronald Ngulube Yongrong Yang Fengqiu Chen John Siame	2019	Chinese Journal of Chemical Engineering2019，27，5：	1
	2	CFD-DEM simulation of Small-Scale Challenge Problem 1 with EMMS bubble-based structure-dependent drag coefficient显示文摘In this study,the energy minimization multi-scale(EMMS)/Bubbling model is coupled with the computational fluid dynamics/discrete element method(CFD-DEM)model via a structure-dependent drag coefficient to simulate the National Energy Technology Laboratory(NETL)small-scale challenge problem using the open-source multiphase flow code MFIX.The numerical predictions are compared against particle velocity measurements obtained from high-speed particle image velocimetry(HSPIV)and differential pressure measurements.The drag-reduction effect of the EMMS bubble-based drag coefficient is observed to significantly improve predictions of the horizontal particle velocity and granular temperature when compared to several other drag coefficients tested;however,the vertical particle velocity and pressure fluctuation characteristic predictions are degraded.The drag-reduction effect is characterized by a reduction in the sizes of slugs or voids,as identified through spectral decomposition of the pressure fluctuations.Overall,this study shows great promise in employing drag coefficients,developed via multi-scale approaches(such as the EMMS paradigm),in CFD-DEM models.	Musango Lungu John Siame Lloyd Mukosha	2021	Particuology2021，19，2：	0

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