TY - GEN
T1 - Data mining for the investigation of unsteady flow field in a hard disk drive
AU - Morizawa, Seiichiro
AU - Jeong, Shinkyu
AU - Shimoyama, Koji
AU - Obayashi, Shigeru
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2010
Y1 - 2010
N2 - This study was performed to examine the mechanism of flow-induced vibration (FIV) in a hard disk drive (HDD). For this purpose, data mining using self-organizing map (SOM) and Bayesian network was applied to unsteady computational fluid dynamics (CFD) simulation data for a hard disk drive. The present data mining started from the extraction of temporal indices from the time series data of fluid properties given at each grid point. Then, a set of grid points was divided into several clusters based on the similarity of the temporal indices by using SOM, and the clustered data were mapped onto a real space of HDD. Through this process, characteristic phenomena latent in the unsteady flow field were classified and identified. Finally, the relations between temporal indices and FIV were constructed by using Bayesian network. The resulting network structure revealed a possible mechanism ofFIV that originates from a temporal sequence of flow energy dissipation and production.
AB - This study was performed to examine the mechanism of flow-induced vibration (FIV) in a hard disk drive (HDD). For this purpose, data mining using self-organizing map (SOM) and Bayesian network was applied to unsteady computational fluid dynamics (CFD) simulation data for a hard disk drive. The present data mining started from the extraction of temporal indices from the time series data of fluid properties given at each grid point. Then, a set of grid points was divided into several clusters based on the similarity of the temporal indices by using SOM, and the clustered data were mapped onto a real space of HDD. Through this process, characteristic phenomena latent in the unsteady flow field were classified and identified. Finally, the relations between temporal indices and FIV were constructed by using Bayesian network. The resulting network structure revealed a possible mechanism ofFIV that originates from a temporal sequence of flow energy dissipation and production.
KW - Bayesian network
KW - Flow-induced vibration
KW - Hard disk drive
KW - Self-organizing map
KW - Unsteady flow field
UR - http://www.scopus.com/inward/record.url?scp=79952758594&partnerID=8YFLogxK
U2 - 10.1109/NABIC.2010.5716324
DO - 10.1109/NABIC.2010.5716324
M3 - Conference contribution
AN - SCOPUS:79952758594
SN - 9781424473762
T3 - Proceedings - 2010 2nd World Congress on Nature and Biologically Inspired Computing, NaBIC 2010
SP - 152
EP - 157
BT - Proceedings - 2010 2nd World Congress on Nature and Biologically Inspired Computing, NaBIC 2010
T2 - 2010 2nd World Congress on Nature and Biologically Inspired Computing, NaBIC 2010
Y2 - 15 December 2010 through 17 December 2010
ER -