Toward a refined estimation of typhoon wind hazards: Parametric modeling and upstream terrain effects

2021 ◽  
Vol 209 ◽  
pp. 104460
Author(s):  
Genshen Fang ◽  
Weichiang Pang ◽  
Lin Zhao ◽  
Prashant Rawal ◽  
Shuyang Cao ◽  
...  
Author(s):  
Na Tian ◽  
Huanyong Cui ◽  
Xiuhua Men ◽  
Ruichuan Li ◽  
Wenhui Yang ◽  
...  
Keyword(s):  

Author(s):  
John L. Schroeder

This article reviews the techniques and approaches historically employed to measure non-synoptic wind storms. While most of these efforts have originated from the atmospheric science community, the focus of this article relates to meeting the requirements of the engineering community. While the recognition of the importance of these non-synoptic wind system events is increasing, their engineering-relevant characteristics are still largely unknown. While gaps in knowledge concerning the engineering-relevant aspects of non-synoptic wind systems are plentiful, focused application of high-resolution research instrumentation offers hope to remove many of these unknowns. Future engineering-oriented measurement campaigns will likely make use of both traditional anemometry and remote sensing technologies to document the characteristics of non-synoptic wind systems.


2004 ◽  
Vol 14 (06) ◽  
pp. 1975-1985
Author(s):  
RASTKO ŽIVANOVIĆ

The task of locating an arcing-fault on overhead line using sampled measurements obtained at a single line terminal could be classified as a practical nonlinear system identification problem. The practical reasons impose the requirement that the solution should be with maximum possible precision. Dynamic behavior of an arc in open air is influenced by the environmental conditions that are changing randomly, and therefore the useful practically application of parametric modeling is out of question. The requirement to identify only one parameter is yet another specific of this problem. The parameter we need is the one that linearly correlates the voltage samples with the current derivative samples (inductance). The correlation between the voltage samples and the current samples depends on the unpredictable arc dynamic behavior. Therefore this correlation is reconstructed using nonparametric regression. A partially linear model combines both, parametric and nonparametric parts in one model. The fit of this model is noniterative, and provides an efficient way to identify (pull out) a single linear correlation from the nonlinear time series.


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