Abstract
The statistical characterization of sprays is an essential way of organizing data on drop size and velocity to provide reliable information on the spray dynamics. A clear presentation of data using statistical tools provides evidence of a clear research question underlying the spray characterization. In this article, a review of the best practices to build histograms is presented, as well as three relevant details on spray characterization: (i) the application of information theory to assess if we have enough information (not data); (ii) the link between mathematical probability distributions and the physical interpretation of spray data; (iii) and introducing, for the first time, the concept of drop size diversity, with the quantification of the polydispersion and heterogeneity degrees. Finally, the view presented is applied to the characterization of nanofluid sprays for thermal management.
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
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