Journal article
Approximate representation of the statistics for extreme responses of single degree-of-freedom system excited by non-stationary processes
Probabilistic engineering mechanics, v 23(2), pp 279-288
2008
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The objective of this study is to estimate the statistics of the maximum response of a structural system excited by a non-stationary process. To provide basic information for the design of structures, the response of a single degree-of-freedom (SDOF) system subjected to a non-stationary Gaussian white noise is considered. For this purpose, we first derive the probabilistic properties of the maximum values of a non-stationary and zero-mean white noise, whose standard deviation varies temporally under some limited conditions. Then, using the obtained properties, we propose a method to estimate the stochastic properties of the maximum response of a given SDOF system excited by a non-stationary white noise whose time-varying standard deviation is known. The validity of the obtained results is confirmed through Monte Carlo simulation.
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Details
- Title
- Approximate representation of the statistics for extreme responses of single degree-of-freedom system excited by non-stationary processes
- Creators
- Hitoshi Morikawa - Department of Built Environment, Tokyo Institute of Technology, 4259-G3-7 Nagatsuta, Midori-ku, Yokohama 226-8502, JapanAspasia Zerva - Department of Civil, Architectural & Environmental Engineering, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104, USA
- Publication Details
- Probabilistic engineering mechanics, v 23(2), pp 279-288
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Civil, Architectural, and Environmental Engineering
- Web of Science ID
- WOS:000255567300020
- Scopus ID
- 2-s2.0-41549133053
- Other Identifier
- 991014878540804721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Engineering, Mechanical
- Mechanics
- Statistics & Probability