Author/Authors :
Haroon Rashid, N. I Department of Aerospace Engineering - Madras Institute of Technology - Anna University, Tamil Nadu, India , Nadaraja Pillai, S School of Mechanical Engineering - SASTRA University, Tamil Nadu, India , Selvi Rajan, S Structural Engineering Research Centre, CSIR, Taramani, Chennai, Tamil Nadu, India , Senthil Kumar, C Department of Aerospace Engineering - Madras Institute of Technology - Anna University, Tamil Nadu, India
Abstract :
Generally, the Gaussian assumption has been considered in analyzing the data pertaining to the wind effects on
the structures or bluff bodies due to the abundance of the statistical information. In this study, Horizontal Axis
Wind Turbine (HAWT) tower system with dimension of 1:330 scale is studied in order to understand their peak
pressure behavior for wind resistant design. Generally, tower systems are constructed of various geometrical
structures such as lattice towers, tubular steel towers, concrete towers, but in this present study tubular
cylindrical tower is only considered. Simultaneous pressure measurements on the surface of the tower were
performed in the low-speed boundary layer wind tunnel with test section dimension of 18 m × 2.5 m × 2.15 m
having Reynolds number ranging from 102 to 104. The peak pressures acting on the tower systems are
calculated for a number of ten-minute samples on various locations of the wind turbine. Peak value calculations
based on Gaussian and Non – Gaussian processes are discussed mathematically and applied to the data collected
from the wind tunnel tests. A mathematical model of Davenport and Kareem – Zhou is used in calculating the
peak factor for Gaussian and non – Gaussian processes, respectively. The results indicate that higher moments
dominate as most of the distribution is skewed and with kurtosis value. Henceforth, a study on extreme value
analysis is deemed necessary in designing wind resistant structures or bluff bodies. Considering Gaussian nature
alone may under-represent the peak value of the HAWT tower.
Keywords :
Non-Gaussian , HAWT , Peak factor , Tower system , Probability distribution