Validation of a DEM Modeling of Gas-Solid Fluidized Bed using the S-statistic in the State-Space Domain
DOI:
https://doi.org/10.1260/1750-9548.5.1.79Abstract
A reliable method was developed to validate results of a gas-solid bubble fluidized bed model with discrete element method (DEM) through comparison of corresponding pressure fluctuations experimental data. Attractors of two independent pressure signals, evaluation series of DEM model and reference time series of measured pressure signals, were compared in the state-space domain using the S-statistic. Comparison between two reconstructed attractors of evaluation and reference series was performed based on the null hypothesis. The null hypothesis that the evaluation and reference time series originate from the same dynamic sources is rejected if the two series significantly differ. To prove the power of the method, the S-statistic was estimated for obtained experimental data under the same operating conditions. In addition, experimental and model pressure fluctuations were decomposed into 9 levels using wavelet transform to study the validity of the model in a broad range of frequencies. Results indicated that the model results were consistent with experiments.
References
Van Wachem, B.G.M., Schouten, J.C., Krishna, R., van den Bleek, C.M., Eulerian simulation of bubbling behavior in gas-solid fluidized beds, Comput. Chem. Engng, 1998, 22, 299-307. https://doi.org/10.1016/s0098-1354(98)00068-4
Van Wachem, B.G.M., van der Schaaf, J., Schouten, J.C., Krishna, R., van den Bleek, C.M., Eperimental validation of Lagrangian-Eulerian simulation of fluidized beds, Powder Technology, 2000, 116, 155-165. https://doi.org/10.1016/s0032-5910(00)00389-2
Mansourpour, Z., Karimi. S., Zarghami, R., Mostoufi, N., Sotudeh-Gharebagh, R., Insights in hydrodynamics of bubbling fluidized beds at elevated pressure by DEM-CFD approach, Particulogy, 2010, in press. https://doi.org/10.1016/j.partic.2010.03.017
Grace, J. R., Taghipour, F., Verification and validation of CFD models and hydrodynamic similarity for fluidized beds, Powder Technology, 2004, 139, 99-110. https://doi.org/10.1016/j.powtec.2003.10.006
Diks, C., van Zwet, W. R., Takens, F., DeGoede, J., Detecting differences between delay vector distributions, Phys. Rev. E., 1996, 53, 2169-2174. https://doi.org/10.1103/physreve.53.2169
van Ommen, J. R., Coppens, M. O., van den Bleek, C. M., Schouten, J. C., Early warning of agglomeration in fluidized beds by attractor comparison. AIChE Journal, 2000, 46, 2183-2197. https://doi.org/10.1002/aic.690461111
Wen, C., Yu, Y., A generalized method for predicting the minimum fluidization velocity, AIChE J., 1966, 12, 610. https://doi.org/10.1002/aic.690120343
Zarghami, R., Mostoufi, N., Sotudeh-Gharebagh, R., Nonlinear characterization of pressure fluctuations in fluidized beds. Ind. Eng. Chem, 2008, 47, 9497-9499. https://doi.org/10.1021/ie800460f
Mallat. S, A theory for multi-resolution signal decomposition: the wavelet representation, IEEE Trans, Pattern Anal. Mach. Intell, 1989, 11, 674-693. https://doi.org/10.1109/34.192463
Rioul, O., Duhamel P., Fast algorithm for discrete and continuous wavelet transform, IEEE trans. Inf. Theory, 1992, 38, 569. https://doi.org/10.1109/18.119724
Shannon, C. E., Weaver, W., Mathematical theory of information university of Illinois Press Urbana (1949).
Zhao, G. B., Yang, Y. R., Multiscale resolution of fluidized bed pressure fluctuations. AIChE Journal, 2003, 49, 869-882. https://doi.org/10.1002/aic.690490407
Yang, T. Y., Leu, L. P., Multi-resolution analysis of wavelet transform on pressure fluctuations in L-valve, International Journal of Multiphase Flow, 2008, 34, 567-579. https://doi.org/10.1016/j.ijmultiphaseflow.2007.12.005
Published
How to Cite
Issue
Section
Copyright (c) 2011 M Karimi, N Mostoufi, R Zarghami, R Sotudeh-Gharebagh
This work is licensed under a Creative Commons Attribution 4.0 International License.