Wind Tunnels and Experimental Fluid Dynamics Research Part 1 pdf

Chapter 1 Optimal Processing of Wind Tunnel Measurements in View of Stochastic Structural Design of Large Flexible Structures 3 Nicolas Blaise and Vincent Denoël Chapter 2 Wire Robot Su

WIND TUNNELS AND  EXPERIMENTAL FLUID  DYNAMICS RESEARCH 

  Edited by Jorge Colman Lerner  

and Ulfilas Boldes 

Wind Tunnels and Experimental Fluid Dynamics Research

Edited by Jorge Colman Lerner and Ulfilas Boldes

Published by InTech

Janeza Trdine 9, 51000 Rijeka, Croatia

Copyright © 2011 InTech

All chapters are Open Access articles distributed under the Creative Commons

Non Commercial Share Alike Attribution 3.0 license, which permits to copy,

distribute, transmit, and adapt the work in any medium, so long as the original

work is properly cited After this work has been published by InTech, authors

have the right to republish it, in whole or part, in any publication of which they

are the author, and to make other personal use of the work Any republication,

referencing or personal use of the work must explicitly identify the original source

Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher No responsibility is accepted

for the accuracy of information contained in the published articles The publisher

assumes no responsibility for any damage or injury to persons or property arising out

of the use of any materials, instructions, methods or ideas contained in the book

Publishing Process Manager Davor Vidic

Technical Editor Teodora Smiljanic

Cover Designer Jan Hyrat

Image Copyright WIANGYA, 2010 Used under license from Shutterstock.com

First published July, 2011

Printed in Croatia

A free online edition of this book is available at www.intechopen.com

Additional hard copies can be obtained from orders@intechweb.org

Wind Tunnels and Experimental Fluid Dynamics Research, Edited by Jorge Colman Lerner and Ulfilas Boldes

p cm

978-953-307-623-2

free online editions of InTech

Books and Journals can be found at

www.intechopen.com

Chapter 1 Optimal Processing of Wind Tunnel Measurements

in View of Stochastic Structural Design of Large Flexible Structures 3

Nicolas Blaise and Vincent Denoël Chapter 2 Wire Robot Suspension Systems for Wind Tunnels 29

Tobias Bruckmann, Christian Sturm and Wildan Lalo Chapter 3 Wind Tunnels for the Study of Particle Transport 51

Keld Rømer Rasmussen, Jonathan Peter Merrison and Per Nørnberg Chapter 4 Wind Tunnel Flutter Testing of Composite T-Tail Model

of a Transport Aircraft with Fuselage Flexibility 75

Raja Samikkannu and A R Upadhya Chapter 5 Wind Tunnel: A Tool to Test the Flight

Response to Semiochemicals 89

Yooichi Kainoh Chapter 6 Flow Visualization in Wind Tunnels 99

Muzafferuddin Mahmood Chapter 7 Components of a Wind Tunnel Balance:

Design and Calibration 115

Miguel A González, José Miguel Ezquerro, Victoria Lapuerta, Ana Laverĩn and Jacobo Rodríguez Chapter 8 Wind Tunnel ‘Concept of Proof’ Investigations

in the Development of Novel Fluid Mechanical Methodologies and Devices 135

N Findanis and N.A Ahmed

VI Contents

Chapter 9 Air Speed Measurement Standards

Using Wind Tunnels 173

Sejong Chun Chapter 10 Low Speed Turbulent Boundary

Layer Wind Tunnels 197

U Boldes, J Colman, J Marañón Di Leo and J.S Delnero Chapter 11 Wind Tunnels in Engineering Education 235

Josué Njock Libii Chapter 12 The Importance of Turbulence in Assessment

of Wind Tunnel Flow Quality 261

Mojtaba Dehghan Manshadi

and Fluid Mechanics 279

Chapter 13 The Use of Wind Tunnel Measurements in

Building Design 281

Dat Duthinh and Emil Simiu Chapter 14 Tall Buildings Under Multidirectional Winds:

Response Prediction and Reduction 301

Aly Mousaad Aly, Alberto Zasso and Ferruccio Resta Chapter 15 Wind Tunnel Tests on the Horn-Shaped

Membrane Roof 325

Yuki Nagai, Akira Okada, Naoya Miyasato and Masao Saitoh Chapter 16 Sport Aerodynamics: On the Relevance

of Aerodynamic Force Modelling Versus Wind Tunnel Testing 349

Caroline Barelle Chapter 17 Active and Passive Control of Flow Past a Cavity 369

Seiichiro Izawa Chapter 18 Aerodynamic Parameters on a Multisided Cylinder for

Fatigue Design 395

Byungik Chang Chapter 19 A New Methodology to Preliminary Design

Structural Components of Re-Entry and Hypersonic Vehicles 409

Michele Ferraiuolo and Oronzio Manca

Part 3 Aerodynamic Field Measurements

and Real Full Scale Analysis 427

Chapter 20 A Computer-assisted Wind Load Evaluation System

for the Design of Cladding of Buildings: A Case Study

of Spatial Structures 429

Yasushi Uematsu

Chapter 21 Monitoring of Soil Surface under Wind and

Water Erosion by Photogrammetry 447

Shigeoki Moritani, Tahei Yamamoto, Henintsoa Andry,

Mitsuhiro Inoue, Taku Nishimura, Haruyuki Fujimaki,

Reiji Kimura and Hirotaka Saito

Chapter 22 Public Square Design with Snow and Wind

Simulations Using Wind Tunnel 463

Tsuyoshi Setoguchi

Chapter 23 The Study of Details Effects in Cycling Aerodynamics:

Comparison Between Two Different

Experimental Approaches 481

Giuseppe Gibertini, Gabriele Campanardi,

Donato Grassi and Luca Guercilena

Chapter 24 Relationships between Large-Scale Coherent Motions

and Bursting Events in a Turbulent Boundary Layer 493

Yasuhiko Sakai, Kouji Nagata and Hiroki Suzuki

Chapter 25 Wavelet Analysis to Detect Multi-Scale

Coherent Eddy Structures and Intermittency

in Turbulent Boundary Layer 509

Jiang Nan

Chapter 26 Evaluation of Local Effects of Transitional Knudsen

Number on Shock Wave Boundary Layer Interactions 537

R Votta, G Ranuzzi, M Di Clemente, A Schettino and M Marini Chapter 27 Investigation on Oblique Shock Wave Control by Surface

Arc Discharge in a Mach 2.2 Supersonic Wind Tunnel 553

Yinghong Li and Jian Wang

Chapter 28 Investigations of Supersonic Flow

around a Long Axisymmetric Body 569

M.R Heidari, M Farahani, M.R Soltani and M Taeibi-Rahni

VIII Contents

Chapter 29 SCIROCCO Plasma Wind Tunnel: Synergy between

Numerical and Experimental Activities for Tests on Aerospace Structures 585

Rosario Borrelli and Adolfo Martucci Chapter 30 Study of Turbulent Supersonic Flow Based

on the Optical and Acoustic Measurements 607

Viktor Banakh, Dmitri Marakasov, Ruvim Tsvyk and Valeri Zapryagaev Chapter 31 Guidance of a Supersonic Projectile by

Plasma-Actuation Concept 629

Patrick Gnemmi and Christian Rey Chapter 32 Wind Tunnel Experiments for Supersonic

Optical-electrical Seeker’s Dome Design 661

Qun Wei, Hongguang Jia, Ming Xuan and Zhenhai Jiang Chapter 33 Design, Execution and Rebuilding of a Plasma

Wind Tunnel Test Compared with an Advanced Infrared Measurement Technique 685

Marco Di Clemente, Giuseppe Rufolo, Francesco Battista and Adolfo Martucci

Preface

The most important fact related with fluid motion is to understand the fluid patterns, and  the  flow  structure  ‐  vortices,  recirculation  zones,  high  mix  regions,  poor  mix  re‐gions, calm regions, to name a few. Moreover,  most of the flows have turbulent char‐acteristics  and  turbulence  remains  one  of  the  unsolved  problems  in  physics.  No  one knows  how  to  obtain  stochastic  solutions  to  the  well‐posed  set  of  partial  differential equations that govern turbulent flows.  

Averaging  those  non  linear  equations  to  obtain  statistical  quantities  always  leads  to more  unknowns  than  equations,  and  ad‐hoc  modeling  is  then  necessary  to  solve  the problem. So, except for a few rare cases, first‐principle analytical solutions to the tur‐bulence phenomena are not possible. 

During  the  last  years,  the  trend  for  describing  unsteady  turbulent  flow  problems  by means of numerical simulation methodologies, based on basic building blocks like el‐emental  eddies  and  vortices,  has  increased.  The  objective  is  to  achieve  more  realistic representations of key aspects of the dynamic pattern of the oncoming turbulent struc‐tures. These computational models are very dependent upon the quality and amount 

of experimental data obtained in real flow processes or at least in representative wind tunnel experiments.  

Typically,  flows  exhibit  time  dependent  distinctive  flow  structures  which  can  be  de‐scribed by an acceptable amount of pattern related simple relations.  

The experimentally detected flow patterns of these structures can facilitate the identifi‐cation of their geometrical and dynamic behavior. Different pattern recognition proce‐dures  based  on  visualizations  techniques,  PIV  velocimetry,    conditional  sampling, POD  and  diverse  detection  algorithms  are  used  to  recognize  and  describe  the  main flow patterns and their evolution. 

It is known that a direct correlation between the instantaneous aerodynamic behavior 

of wings and bodies interacting with oncoming particular vortex structures cannot be determined  with  commonly  used  statistics  methods  disregarding  pattern  related  as‐pects  of  the  impinging  flow  structures.  Unsteady  aerodynamics  should  focus  on  the diverse changing flow‐pattern aspects of a flow. During real flow experiences within a given time record, numerous turbulent structures may go by. 

XII Preface

In particular aerodynamic problems, the most representative turbulent structures im‐mersed  in  the  oncoming  wind  must  be  previously  identified  in  order  to  reproduce them in wind tunnel experiments. A main objective in unsteady boundary layer wind tunnel aerodynamics is the realistic reproduction of the dynamic response of a body to approaching  individual  turbulent  structures  immersed  in  the  oncoming  wind.  It  is  a complex problem associated with various space and time scales involved in the flow. For a wing in some cases, a particular vortex structure embedded in the approaching wind producing intense turbulent velocity fluctuations may only enhance instantane‐ous Reynolds stresses without significant changes in the lift forces.  

In the range of high velocity flow, i.e. for Mach number equal or greater than 0.5, the complex phenomena associated with compressible subsonic and transonic flows often requires  experimentation.  The  same  holds  true  for  supersonic  and  hypersonic  flows, including  the  interaction  between  shocks  and  compressible  boundary  layer  and boundary layer transition, to mention only a part of the huge compressible phenome‐

na. Researchers developed very good CFD codes in this area of knowledge, but the ne‐cessity to perform experiments to validate the numerical results, particularly those re‐lated with compression waves, shock waves, isentropic waves, compressible boundary layers,  laminar‐turbulent  transition,  hypersonic  phenomena  remains  high  and  the main tool is the compressible flow wind tunnel, either, transonic, supersonic or hyper‐sonic.  

In general, the experimentally detected flow patterns can facilitate the identification of geometrical and dynamic relations. Different pattern recognition procedures based on visualizations  techniques,  PIV  velocimetry,  conditional  sampling,  POD  and  diverse detection algorithms are used to recognize and describe the main flow patterns and its evolution. 

Due to all of the reasons exposed, performing experiments becomes necessary in stud‐ying  fluid  flows.  Such  experiments  can  be  “in  situ”,  that  is,  in  real  situations  of  the flow and in laboratories, using wind tunnels and any other scientific instrument asso‐ciated  with  it,  like  constant  temperature  anemometers,  PIV  equipment  pressure  sys‐tems,  balances,  etc. At  those occasions  when  performing  “in‐situ”  experiments  is  not  possible, researchers must employ the wind tunnels. But in any case, the experimental part of the work is always essential. 

The Editors of this book wish to present the lecturers and researchers worldwide with 

a  set  of  chapters  dealing  with  realistic  and  representative  experiments  in  fluids  and practical criteria applied by the researchers in one of the essential fluid dynamic and aerodynamic tool ‐ the wind tunnel.  

Dr. Jorge Colman Lerner and Dr. Ulfilas Boldes 

Boundary Layer & Environmental Fluid Dynamics Laboratory, Engineering Faculty, 

National University of La Plata,  

Argentina 

1 Introduction

Wind loads are decisive for a wide range of structures and must therefore be modeledadequately in a structural design Some codes and standards provide a general set ofdesign guidelines only for structures with limited dimensions and under the assumption of adynamic response in the fundamental mode (Eurocode, 1991) As a matter of fact, very largeand flexible structures as, bridges and stadiums, do not fall within the context of application

of such simplified procedures One reason is that large flexible structures may evince a serioussensitivity to the random gust loading, although being stiff enough to limit strong aeroelasticphenomena, but flexible enough to allow for a significant dynamic response

The buffeting analysis of civil structures, i.e subjected to random pressures due to thefluctuations of the oncoming flow and to the weak interaction of that flow with the windwardpart of the structure, is typically tackled as a stochastic dynamic analysis In this view, theusual analysis is performed with a probabilistic description of the wind velocities in theatmospheric boundary layer (local statistical properties as well as spatial coherence), as well

as aerodynamic admittances Based on site-specific and structure-specific data, they allow thedetermination of the probabilistic description of the loading, namely power spectral densities

of (and coherence between) forces resulting from the wind loading at various spots of thestructure A traditional stochastic analysis follows (Clough & Penzien, 1993; Preumont, 1994),for which structural engineers are used to cope with The well-known decomposition intomean, background and resonant contributions of the wind-induced responses (Davenport,1961; Holmes, 2007) offers an affordable access to stochastic analysis in the everyday practice

As a ultimate outcome of the structural, extreme values of some structural responses, such asdisplacements, internal forces or stresses, have to be estimated They are actually expressedwith peak factors, for which there exist various analytical expressions, depending on theproperties of the considered random process (Floris & Iseppi, 1998; Rice, 1945)

The wind tunnel testing of large flexible structures is much more realistic than theaforementioned codified procedure since it allows a precise estimation of the time-spacedistribution of the pressures and the modeling of a number of phenomena as the aerodynamicinstabilities and aerodynamic admittance, that are difficult to estimate Design codes thereforerecommend wind tunnel measurements for large structures, with a need to model carefullythe wind flow surrounding the construction site Wind tunnels have been being developedsince the 1960’s with early contributions from Scanlan, Scruton among others, although the

0

Optimal Processing of Wind Tunnel Measurements in View of Stochastic Structural

Design of Large Flexible Structures

Nicolas Blaise and Vincent Denoël

University of Liège, Structural Engineering Division

Belgium

1

2 Wind Tunnel book 2

principles of the similitude and dimensional analysis were awaiting to be applied to windflows for more than fifteen years (Langhaar, 1951) In the context of random fluctuatingpressures, wind tunnels are of course well equipped because they just require the dynamicacquisition of pressures at various locations of the structure under investigation Even aturbulent flow may be generated with a series of well-known methods in case of fluctuatingoncoming flow Then, a statistical processing (Papoulis, 1965) of the measured pressuresshould provide the same probabilistic quantities as those that are necessary for the stochasticanalysis Nevertheless, outputs of wind tunnel testing are basically deterministic nonrepeatable measurements Starting from this raw data, the structural design can followdifferent ways depending on the level at which the statistical processing is performed

In the context of a structural analysis, two extreme data processing may be distinguished.The first option is a deep analysis and understanding of the pressure field as measured inthe wind tunnel, and before any consideration of the dynamic properties of the structureunder investigation Naturally, maps of averages of local pressures as well as their standarddeviations or higher statistical moments are the basic output of that kind Besides, datamining procedures as Karhunen-Loeve decomposition (Loeve, 1977) or the proper orthogonaldecomposition (Jolliffe, 2005) offer an interesting way to better understand the air flow aroundstructures They are also a smart way to compress the data and extract the main informationembedded in the acquired signals In particular, the proper orthogonal decompositionhas been widely applied to wind tunnel measurements (Baker, 2000; Best & Holmes, 1983;Bienkiewicz et al., 1993; 1995; Carassale, 2005; Holmes et al., 1997; Solari et al., 2007);more advanced methods such as the normalized proper orthogonal decomposition (Ruan

et al., 2006) have also proved to be efficient in understanding wind tunnel measurements.Obviously statistical data such as power spectral densities of wind pressures are also avaluable outcome of the post-processing Indeed, together with their spatial coherence, theloading information is recast into a format that matches design procedures offered by designstandards

The second possibility is to postpone the statistical treatment after the structural analysis

A deterministic structural analysis is then performed, based on the single acquired pressurehistories In this case, the structure is analyzed with usual tools as the Newmark integrationscheme (Clough & Penzien, 1993) The statistical treatment is then limited to the estimation

of mean, standard deviation and extreme values of displacements, strains and stresses, moregenerally of the structural response It is thus left to the structural engineer, as a part of thestructural design

As a caricature, in these extreme solutions, the statistical processing is therefore left either towind-tunnel engineers when it concerns the acquired data itself, either to structural engineerswhen it comes to estimating structural design quantities In any case, we may deplore -andthis is also probability a matter of sharing responsibilities and expertise a limited interactionbetween both parties

Furthermore, one may disclose evidences that both the traditional deterministic and stochasticmethods discussed as extreme situations before are not robust against the type of structure,loading and details of the measurement procedure Indeed, the deterministic approach maysuffer from inadequate sampling frequencies and consequences thereof, or from additionalnoise that may hardly be dealt with (Blaise, 2010) On the other hand, a stochasticdescription of the pressure field itself may result in a poor estimation of the coherence field,whenever crossed statistics between all pressure taps are considered, or from an excessive

4 Wind Tunnels and Experimental Fluid Dynamics Research

Optimal Processing of Wind Tunnel Measurements in View of Stochastic Structural Design of Large Flexible Structures 3

data compression, resulting in the inability of representing properly global and local structuralresponses at the same time

A wind tunnel is a convenient tool that may be run successfully only if all protagonists agree

on what to measure, how to measure and more importantly what to do with the measuredsignals In this chapter, we discuss and demonstrate the need to break up the border betweenthem It is obvious that the optimum situation should lie somewhere between both extremesdescribed before As a simple example, just the shape of a structure would be sufficient for

a wind-tunnel engineer to measure the surrounding air flow as well as wall pressures Thetrouble is that if the sampling rate considered for the wind-tunnel testing is not chosen inaccordance with the natural frequencies of the structure (a detail typically pertaining to thestructural engineer), the subsequent structural design may yield unrealistic results

According to the philosophy in which design standards have been developed, it appears thatthe most promising analysis technique, among deterministic or stochastic, is the stochasticone This assertion is supported by the idea that a deterministic analysis remains a singleshot (a sample of a Monte Carlo simulation), while the stochastic approach provides a rationalunique probabilistic description Keeping in mind the objective of finding an optimum level to

fit a probabilistic model to wind-tunnel data, and under the constraints that the fitting should

be simple and reliable, and also the assumption that it is possible to find a solution involvingthe joint expertise of wind-tunnel and structural teams, we demonstrate the optimality ofthe fitting of a probabilistic model to the modal forces In this document, the benefits ofthe proposed method are also illustrated and the reasons for which it provides a superiormodeling are clearly pointed out

Some advantages of the stochastic approach over a deterministic one have already beenidentified, such as the flexibility in pre-processing the measured pressures in order tosmoothen their probabilistic description (Blaise et al., 2011) The main point developed inthis document consists in investigating and comparing other probabilistic pre-processingmethods

2 Post-processing of measured wind pressures

Pressures recorded on a wind-tunnel model represent the time-space distribution of the loads

to be considered for a structural design Owing to the complexity of the air flow around bluffbodies, as encountered in civil engineering applications, a substantial amount of pressure tapshave to be used in order to provide an accurate representation of the wind flow Furthermore,

as a result of some frequency scaling that has to be satisfied, typical sampling frequenciesexpressed in wind-tunnel time scale are such that the true scale 10-min observation window,

as required by many standards translates into a massive amount of data This huge amount

of data has to be analyzed in a statistical manner in order to extract the most significantinformation, to make it therefore understandable, and if possible to suggest the probabilisticproperties of the families to which the recorded signals belong

Indeed, it is commonly agreed that statistics include both the descriptive statistics, preciselyaiming at summarizing the recorded data by means of some numerical descriptors, andthe inferential statistics consisting in drawing inferences about the population to which therecorded data presumably belong (Casella, 2001) In this latter case, descriptors of the

population, referred to as probabilistic models in the following are naturally expected to be more

representative of the global phenomenology In other words, two successive wind-tunnel

5

Optimal Processing of Wind Tunnel

Measurements in View of Stochastic Structural Design of Large Flexible Structures

4 Wind Tunnel book 2

Fig 1 Model of the stadium in the wind tunnel (a) View of the exit of the turbine, (b) Block

to create the wind velocity profile, (c) and (d) Surrounding buildings, (e) Surrounding woods

- also published in: (Blaise et al., 2011)

measurements could provide different descriptive statistics (means, standard deviations,extreme values, etc.), although they belong to the same probabilistic model

A rudimentary structural design from wind-tunnel recorded pressures may be conductedwith only descriptive statistics This section presents typical steps of such a post-processing.There is no doubt that more global statistics, as those resulting from inferential statistics,related to a population rather than a single sample in the statistical sense, would provide

a more robust information about the pressure field over a structure This more robustinformation is of marginal importance for means and standard deviations of pressures (whichare expected to be reproducible from test to test), but is definitely crucial for extreme valueswhich are most likely much more scattered, from test to test This idea is developed inSection 3 where we suggest to fit probabilistic models on various quantities measured in thewind-tunnel

This document is meant to be a treatise on these probabilistic models, rather than thepresentation of a particular case study For convenience, the following sections are howeverillustrated with the wind-tunnel testing and structural analysis of a stadium roof This rooffeatures a retractable part resting on two main longitudinal beams, which owned it to betested for various roof configurations and wind directions Further details of this particularstructural system are given in (Blaise et al., 2011) The simulated wind targets properties of theatmospheric boundary layer, as prescribed in the Eurocodes (Eurocode, 1991) and its Frenchnational appendix Notably, the targeted wind loads correspond to the Service Limit Stateones and a IIIa category terrain is appropriate to represent the surrounding of the stadium

The mean velocity recorded at the top of the stadium v m =28.3 m/s accurately corresponds

to the target value and thus to an expected reference velocity pressure q mean=491.7 Pa Figure

1 shows the 1/200 scaled model in the wind tunnel The velocity and time scales are 1/2.98and 1/67 respectively The model is assumed to be infinitely rigid The surrounding buildingsand trees are also modeled to simulate a realistic environment

The instrumentation of the scaled model required approximately three hundred and fiftysynchronous pressure sensors, sampled at 200 Hz, which corresponds to 2.94 Hz in full scale

6 Wind Tunnels and Experimental Fluid Dynamics Research