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Title: Detection of branching points in noisy processes
Authors: Beer, M. 
Liebscher, M.
Keywords: Bifurcation
Branching points
Cluster analysis
Data analysis
Process classification
Time series
Issue Date: Mar-2010
Citation: Beer, M., Liebscher, M. (2010-03). Detection of branching points in noisy processes. Computational Mechanics 45 (4) : 363-374. ScholarBank@NUS Repository.
Abstract: Processes in engineeringmechanics often contain branching points at which the system can follow different physical paths. In this paper a method for the detection of these branching points is proposed for processes that are affected by noise. It is assumed that a bundle of process records are available from numerical simulations or from experiments, and branching points are concealed by the noise of the process. The bundle of process records is then evaluated at a series of discrete values of the independent process coordinates. At each discrete point of the process, the associated point set of process values is investigated with the aid of cluster analysis. The detected branching points are verified with a recursive algorithm. The revealed information about the branching points can be used to identify the physical and mechanical background for the branching. This helps to better understand a mechanical system and to design it optimal for a specific purpose. The proposed method is demonstrated by means of both a numerical example and a practical example of a crashworthiness investigation. © Springer-Verlag 2009.
Source Title: Computational Mechanics
ISSN: 01787675
DOI: 10.1007/s00466-009-0455-7
Appears in Collections:Staff Publications

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