Details
| Original language | English |
|---|---|
| Pages (from-to) | 363-374 |
| Number of pages | 12 |
| Journal | Computational mechanics |
| Volume | 45 |
| Issue number | 4 |
| Early online date | 18 Dec 2009 |
| Publication status | Published - Mar 2010 |
| Externally published | Yes |
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.
Keywords
- Bifurcation, Branching points, Cluster analysis, Data analysis, Noise, Process classification, Processes, Time series
ASJC Scopus subject areas
- Engineering(all)
- Computational Mechanics
- Engineering(all)
- Ocean Engineering
- Engineering(all)
- Mechanical Engineering
- Computer Science(all)
- Computational Theory and Mathematics
- Mathematics(all)
- Computational Mathematics
- Mathematics(all)
- Applied Mathematics
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In: Computational mechanics, Vol. 45, No. 4, 03.2010, p. 363-374.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Detection of branching points in noisy processes
AU - Beer, Michael
AU - Liebscher, Martin
PY - 2010/3
Y1 - 2010/3
N2 - 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.
AB - 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.
KW - Bifurcation
KW - Branching points
KW - Cluster analysis
KW - Data analysis
KW - Noise
KW - Process classification
KW - Processes
KW - Time series
UR - http://www.scopus.com/inward/record.url?scp=84898074739&partnerID=8YFLogxK
U2 - 10.1007/s00466-009-0458-4
DO - 10.1007/s00466-009-0458-4
M3 - Article
AN - SCOPUS:84898074739
VL - 45
SP - 363
EP - 374
JO - Computational mechanics
JF - Computational mechanics
SN - 0178-7675
IS - 4
ER -