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Frequency‐dependent principal component analysis of multicomponent earthquake ground motions
Author(s) -
Das Sandip,
Hazra Budhaditya
Publication year - 2017
Publication title -
earthquake engineering and structural dynamics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.218
H-Index - 127
eISSN - 1096-9845
pISSN - 0098-8847
DOI - 10.1002/eqe.3008
Subject(s) - principal component analysis , ground motion , computation , process (computing) , dependency (uml) , computer science , stochastic process , motion (physics) , component (thermodynamics) , principal (computer security) , statistical physics , engineering , mathematics , structural engineering , algorithm , artificial intelligence , physics , statistics , thermodynamics , operating system
Summary Stochastic ground motion simulation techniques are becoming increasingly popular because of enhanced computation power enabling direct simulation of complex response quantities. Priestley process assumption is the most general approach for stochastic modeling of earthquake ground motion. However, a framework for multicomponent ground motion simulation using the general Priestley process assumption is not available. Multicomponent motions are useful especially when the correlation structure between them significantly influences the response. The present study proposes a framework for frequency‐dependent principal component analysis (PCA), which facilitates Priestley process–based simulation of multicomponent ground motions. The study focuses only on the frequency‐dependent PCA part, and the results show high dependency of the principal components/directions on the frequency bands of the signals. The present work also advocates that the frequency‐dependent PCA should be preferred to the conventional PCA as the former can address the issues related to the frequency‐independent uniform modulation associated with the latter.