@ARTICLE{Blonski_S._The_2019,
 author={Blonski, S. and Pregowska, A. and Michalek, T. and Szczepanski, J.},
 volume={No. 5},
 journal={Bulletin of the Polish Academy of Sciences Technical Sciences},
 pages={957-962},
 howpublished={online},
 year={2019},
 abstract={One of the mathematical tools to measure the generation rate of new patterns along a sequence of symbols is the Lempel-Ziv complexity (LZ). Under additional assumptions, LZ is an estimator of entropy in the Shannon sense. Since entropy is considered as a measure of randomness, this means that LZ can be treated also as a randomness indicator. In this paper, we used LZ concept to the analysis of different flow regimes in cold flow combustor models. Experimental data for two combustor’s configurations motivated by efficient mixing need were considered. Extensive computer analysis was applied to develop a complexity approach to the analysis of velocity fluctuations recorded with hot-wire anemometry and PIV technique. A natural encoding method to address these velocity fluctuations was proposed. It turned out, that with this encoding the complexity values of the sequences are well correlated with the values obtained by means of RMS method (larger/smaller complexity larger/smaller RMS). However, our calculations pointed out the interesting result that most complex, this means most random, behavior does not overlap with the “most turbulent” point determined by the RMS method, but it is located in the point with maximal average velocity. It seems that complexity method can be particularly useful to analyze turbulent and unsteady flow regimes. Moreover, the complexity can also be used to establish other flow characteristics like its ergodicity or mixing.},
 type={Artykuły / Articles},
 title={The use of Lempel-Ziv complexity to analyze turbulence and flow randomness based on velocity fluctuations},
 URL={http://www.journals.pan.pl/Content/114301/PDF/11_957-962_01211_Bpast.No.67-5_03.02.20.pdf},
 doi={10.24425/bpasts.2019.130876},
 keywords={turbulence, complexity, entropy, randomness},
}