Paper Info

Title | ||
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Simulation of Transient Non-stationary Winds |

Abstract | ||
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Following the theory of evolutionary power spectral density (EPSD) for non-stationary stochastic processes, it is anticipated that the non-stationary fluctuating wind velocity can be generated by resorting to a deterministic modulating function used to modulate the stationary fluctuating wind velocity. In order to carry out the digital simulation of non-stationary stochastic process with resorting to the spectral representation (SR) method, there is a need for remarkably reducing the increasing number of Cholesky decomposition of the time-varying spectral density matrix with the duration of simulation. In order to cope with this issue, the introduction of spline interpolation algorithm (SIA) is advanced herein so as to enhance the computational speed. Results obtained from the present procedure corroborate its feasibility of simulating the non-stationary stochastic processes. Results also show that the present approach can not only fully capture the nonstationarity but also leads to a surprising speedup of computation in the simulation of non-stationary stochastic processes. |

Year | DOI | Venue |
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2009 | 10.1109/NCM.2009.63 | NCM |

Keywords | Field | DocType |

present procedure,stochastic processes,non-stationary stochastic processes,nonstationary stochastic process,deterministic modulating function,interpolation,cholesky decomposition,simulations,evolutionary power spectral density,transient nonstationary winds simulation,spectral representation (sr),wind,transient non-stationary winds,spline interpolation algorithm,spectral representation method,non-stationary fluctuating wind velocity,non-stationary stochastic process,spline interpolation algorithm (sia),digital simulation,time-varying spectral density matrix,spectral representation,stationary fluctuating wind velocity,fluctuating wind velocity,splines (mathematics),velocity,present approach,time-varying power spectrum,spectral density,spline interpolation,strontium,matrix decomposition,spline,power spectral density,computational modeling,power spectrum,wind velocity,wind speed,stochastic process | Spline (mathematics),Applied mathematics,Mathematical optimization,Spline interpolation,Computer science,Interpolation,Matrix decomposition,Stochastic process,Spectral density,Distributed computing,Cholesky decomposition,Speedup | Conference |

ISBN | Citations | PageRank |

978-0-7695-3769-6 | 0 | 0.34 |

References | Authors | |

1 | 3 |

Authors (3 rows)

Cited by (0 rows)

References (1 rows)

Name | Order | Citations | PageRank |
---|---|---|---|

Chun-xiang Li | 1 | 0 | 1.35 |

Jinhua Li | 2 | 0 | 1.01 |

Jianhong Shen | 3 | 376 | 34.18 |