**1. Introduction**

[18] Seydel P. Experimental and Mathematical Modeling of Solid Formation at Spray

[19] Perdana J, Fox M, Schutyser M, Boom R. Single-Droplet Experimentation on Spray Drying: Evaporation of a Sessile Droplet. Chemical Engineering & Technology 2011;

[20] Cheong H, Jeffreys G, Mumford C. A Receding Interface Model For The Drying of

[21] Farid M. A New Approach to Modeling of Single Droplet Drying. Chemical Engi‐

[22] Almubarak A, Mumford C. Characteristics of the receding evaporation front in con‐ vective drying. In: Mujumdar AS. (editor) Proceedings of the 9th International Dry‐

[23] Kays W. M, Crawford M.E. Convective Heat and Mass Transfer, 2nd. ed., McGraw-

[24] Thomas L. C. Heat Transfer professional Version. 2nd ed.: Capston Publishing Cor‐

[25] Kreith F, Bohn M. Principles of Heat Transfer. 6th ed.: Brook/Cole Publishers, Pacific

[26] Almubarak A, Al-Saeedi J, Shoukry M. Effect of Boundary Layer on Mechanisms of Beach and Desert sand. European Journal of Soil Science 2008; 59, 807-816.

[27] Waananen K, Litchfield J, Okos M. Classification of Drying Models for Porous Solids,

[29] Nesic S, Vodnik J. Kinetics of Droplet Evaporation. Chemical Engineering Science

[30] Chen X, Peng F. Modified Biot Number in The Context of Air Drying of Small Moist

[31] Hayder M, Mumford C. 1993. Mechanisms of Drying of Skin Forming Materials.

Drying. Chemical Engineering Technology 2004; 27 (5): 505-510.

Slurry Droplets. AIChE Journal 1986; 32, 1334-1346.

Hill Book Company, New York, NY, USA.1980.

ing Symposium, IDS'94, Marcel Dekker Inc., NY, USA; 1994.

[28] Holman J.P. Heat Transfer: McGraw-Hill Book Co., NY, USA 2002.

Porous Objects. Drying Technology 2005; 23, 83-103.

Drying Technology 1993; 11, 1713-1750.

neering Science 2003; 58, 2985-2993.

196 Wind Tunnel Designs and Their Diverse Engineering Applications

poration, OK. USA. 1999.

Grove, CA, USA 2001.

1991; 46, 527-537.

Drying Technology 1993; 11, 1-40.

34 (7): 1151–1158.

Many studies on wind engineering require the use of different types of statistical analysis associated to the phenomenology of boundary layer flows. Reduced Scale Models (RSM) ob‐ tained in laboratory, for example, attempt to reproduce real atmosphere phenomena like wind loads on buildings and bridges and the transportation of gases and airborne particu‐ lates by the mean flow and turbulent mixing. Therefore, the quality of the RSM depends on the proper selection of statistical parameters and in the similarity between the laboratory generated flow and the atmospheric flow.

The turbulence spectrum is the main physical parameter used to compare the velocity fluc‐ tuation characteristics of atmospheric and laboratory flows in Wind Load Modeling (WLM). This is accomplished by fitting experimental spectra to some functional form, *e.g.*, von Kár‐ mán, Harris or Batchelor-Kaimal formula, and then creating dimensionless turbulence spec‐ tra in accordance with a similarity theory [1, 2, 3]. The objective behind the use of a similarity theory is that the dimensionless spectra of atmospheric and laboratory flows col‐ lapse, if the dimensionless spectra were constructed by appropriate parameters [4].

This classical spectral comparison is commonly used in WLM [5]. However, some difficulties, related to the determination of the inertial range extent, choice of characteristic velocity and length scale parameters and possible effects due to the finiteness of the Reynolds number arise in wind tunnel studies, specially, when simulations are performed at low velocities [6].

Considering this scenario, a complementary study taking into account the use of local scale based Reynolds number, inertial and dissipation range characteristic scales, control of sam‐ pling frequency and post-processing filtering is proposed. Selected data sets obtained under

© 2013 Wittwer et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 Wittwer et al.; licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

distinct configurations of three wind tunnels, a smooth pipe and atmospheric boundary lay‐ er are used. In addition, a different class of spectral representation proposed by Gagne et al. [7], which is based on local similarities and compatible with the multifractal formalism, is compared to traditional approaches.
