Premium
Clustering based on geometry and interactions of turbulence bursting rate processes in a trough region
Author(s) -
Mazumder Rahul
Publication year - 2007
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/env.853
Subject(s) - bursting , cluster analysis , randomness , turbulence , statistical physics , parametric statistics , trough (economics) , entropy (arrow of time) , geometry , computer science , physics , geology , mathematics , artificial intelligence , statistics , mechanics , macroeconomics , quantum mechanics , neuroscience , economics , biology
Abstract This paper aims at understanding turbulence occurring due to fluid flow in the trough region between two artificial adjacent asymmetric waveforms in an open‐channel using velocity data collected by 3‐D Acoustic Doppler Velocimeter (ADV), concentrating on interactions among the turbulence bursting phenomena across different spatial locations. The Statistical Learning stage of the analysis begins with the identification and extraction of statistically informative and physically interpretable features in the geometry of the Bursting Rate Processes (BRP). Statistical measures characterising the differences among the concerned processes have been developed and used for splitting the trough region into different regions based on the geometry, structure and randomness in the BRP, using the principles of statistical clustering involving parametric, non‐parametric techniques and ideas of information theoretic entropy. Experimental observations support the existence of certain BRP which may be considered to be dominant over the others in an almost global sense. The issue of identifying a single bursting phenomenon that changes its orientation strongly relative to others or its closest neighbour across all spatial locations or stretches of vertical heights for every horizontal location and its importance in the entire physical scenario in the light of the spatial clustering problem has been addressed and settled too. Copyright © 2007 John Wiley & Sons, Ltd.