Application of Dual-Tree Complex Wavelet Packet Transform for Generating Synthetic Multivariate Nonstationary Non-Gaussian Thunderstorm Wind Records
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 9, Issue 4
Abstract
The available thunderstorm wind records with subsecond sampling intervals is scarce for a given site; stochastic models that can be used to sample multivariate nonstationary non-Gaussian thunderstorm winds at multiple points or tricomponent thunderstorm winds at a point are lacking. We propose the use of the dual-tree complex wavelet packet transform (DT-) within the framework of the iterative power and amplitude correction (IPAC) algorithm to generate multivariate nonstationary non-Gaussian thunderstorm wind records. This is a data-driven or seed-record-based approach, and the use of the IPAC algorithm ensures the matching of the marginal cumulative probability distribution function. The DT- is used to gain computational efficiency because it is a redundant transform with a low redundancy factor, and it provides phase information. The statistics of the time-frequency power spectral density of the sampled records and the seed record were compared to show the adequacy and effectiveness of the proposed approach. The results also show that the use of the DT- instead of the (discretized) continuous wavelet transform and S-transform significantly reduces the computational time.
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Data Availability Statement
Data will be made available on request from the corresponding author.
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Information
Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 9 • Issue 4 • December 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Mar 5, 2023
Accepted: Jun 20, 2023
Published online: Sep 29, 2023
Published in print: Dec 1, 2023
Discussion open until: Feb 29, 2024
ASCE Technical Topics:
- Algorithms
- Analysis (by type)
- Climates
- Energy engineering
- Energy sources (by type)
- Engineering fundamentals
- Environmental engineering
- Gaussian process
- Mathematical functions
- Mathematics
- Meteorology
- Power spectral density
- Precipitation
- Probability
- Renewable energy
- Statistical analysis (by type)
- Stochastic processes
- Storms
- Structural engineering
- Wavelets
- Wind engineering
- Wind power
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