Turbulence characterization of downbursts using LES Haitham Aboshosha, Girma Bitsuamlak n , Ashraf El Damatty WindEEE Research Institute/Civil and Environmental Engineering Department, Western University, London, ON, Canada article info Article history: Received 31 March 2014 Received in revised form 29 October 2014 Accepted 30 October 2014 Available online 17 November 2014 Keywords: Large eddy simulation (LES) Downburst High intensity wind (HIW) Turbulence Length scales Correlation Coherence Peak factor Gust factor abstract Loads associated with downbursts represent a significant vulnerability on various structures. Designing the structures to withstand such loads requires the knowledge about the turbulent characteristics of downbursts, which are the focus of the current study. To this effect, large eddy simulations (LES) of downbursts impinging over four different exposures namely open, countryside, suburban and urban, are performed. Ground surface roughness is simulated using fractal surfaces generated by random Fourier modes (RFM) and scaled to match a targeted aerodynamic roughness z 0 . Simulated wind velocities are averaged spatially and temporally to extract the mean and turbulent components. Properties of both the mean and the turbulent components are discussed. Turbulence length scales, which govern the wide band correlations of the turbulence, are determined in the circumferential, the vertical and the longitudinal directions. It is found that the length scales in the circumferential direction are larger than those in the vertical direction by at least an order of magnitude, indicating that downburst turbulence is more correlated in the circumferential direction. This has a particular importance for long horizontal structures such as transmission lines and long span bridges. Narrow band correlations and the turbulent spectra, which have a particular importance for flexible structures, are also discussed. Applicability of using the resulting turbulent characteristics to estimate the peak forces on structures, e.g. transmission lines, is deduced by employing the gust factor approach. & 2014 Elsevier Ltd. All rights reserved. 1. Introduction Downburst is a strong downdraft that induces an outburst of damaging wind near the ground as defined by Fujita (1985). Hazards associated with downburst winds on different structures are extensively discussed in the literature (Whittingham, 1964; Fujita, 1990; Vicroy, 1992; Holmes, 1999; Li, 2000). Previous field studies such as the Joint Airport Weather Studies (JAWS), the Northern Illinois Meteorological Research on Downbursts (NIM- ROD), and the Federal Aviation Administration Lincoln Laboratory Operational Weather Studies (FLOWS; Fujita, 1985), showed that the maximum downburst wind speeds happen at the 50 m above the ground as indicated by Fujita and Wakimoto (1981), Wilson et al. (1984), and Hjelmfelt (1988). Although field studies can provide the actual velocities, they represent a challenging task due to the unpredictability of the event occurrence in time and in space. That motivated researchers in the past to study downbursts either experimentally (Osegura and Bowles, 1988; Lundgren et al., 1992; Alahyari and Longmire, 1994; Yao and Lundgren, 1996; Wood et al., 2001; Chay and Letchford, 2002) or computationally (Selvam and Holmes, 1992; Hadžiabdić, 2005; Chay et al., 2006; Kim and Hangan, 2007; Sengupta and Sarkar, 2008; Gant, 2009; Mason et al., 2009, 2010a). In terms of the computational studies of downbursts, the following methods are currently used: Imping- ing Jet (IJ) method proposed by Fujita (1985), Cooling Source (CS) method suggested by Anderson et al. (1992) and the method of simulating the downburst-producing thunderstorm indicated by Orf et al. (2012). Both IJ and CS methods are computationally less costly compared with the simulation of the downburst-producing thunderstorm. The latter requires significant computational resources which makes it unaffordable for the current study. There are several attempts over the last decades to simulate downburst either using the IJ or the CS methods. For example, Kim and Hangan (2007) used the IJ method to obtain the running mean downburst wind velocities employing an axis-symmetric two- dimensional domain. Sengupta and Sarkar (2008) simulated down- bursts using the IJ method employing k-epsilon, k-omega, shear stress transport (SST) and LES turbulence models and compared the resulting profiles with those from an experiment. Their results showed a reasonable agreement between the profiles obtained from the LES and from the experiment. The applicability of using LES to simulate downbursts is also indicated from the results of Hadžiabdić (2005), Chay et al. (2006) and Gant (2009). Mason et al. (2009, 2010a) used the CS method to simulate downbursts on a two and three dimensional domains, respectively. Mason et al. (2009, 2010a) used the Shear Adaptive Simulation (SAS) by Menter and Egorov (2005). Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/jweia Journal of Wind Engineering and Industrial Aerodynamics http://dx.doi.org/10.1016/j.jweia.2014.10.020 0167-6105/& 2014 Elsevier Ltd. All rights reserved. n Corresponding author. E-mail address: gbitsuam@uwo.ca (G. Bitsuamlak). J. Wind Eng. Ind. Aerodyn. 136 (2015) 44–61