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Computational evaluation of wind pressures on tall buildings

Agerneh K. Dagnew 1, Girma T. Bitsuamalk2, Ryan Merrick3

1 Research Assistant, Civil and Environmental Engineering department (CEE), InternationalHurricane Research Center (IHRC), Florida International University (FIU), Miami, Florida,

USA, adagn001@fiu.edu

2 Assistant Professor of Wind/Structural Engineering, CEE, IHRC, FIU, Miami, Florida, USAbitsuamg@fiu.edu

3 Senior Technical Coordinator, RWDI USA LLC, Miramar, Florida, USA,Ryan.Merrick@rwdi.com

ABSTRACTAt present, the wind engineering toolbox consists of wind-tunnel testing of scaled models, limitedfull-scale testing, field measurements, and mechanical load/pressure testing. The evolution ofcomputational wind engineering (CWE) based on computational fluid dynamics (CFD)principles are making the numerical evaluation of wind loads a potentially attractiveproposition. This is particularly true in light of the positive development trends in hardware andsoftware technology, as well as numerical modeling. The present study focuses on numericalevaluation of wind pressures on tall buildings by using the Commonwealth AdvisoryAeronautical Council (CAARC) building model (Melbourne, 1980). The CARRC model has beenused extensively to study wind loading on tall buildings in wind tunnel studies and is usuallyadopted for calibration of experimental techniques. Numerically obtained pressure coefficientson the surface of CAARC building under different configurations of adjacent building arecompared with wind tunnel data collected at the RWDI USA LLC laboratory for the presentstudy and from literature. The present numerical simulation uses mostly Reynolds AveragedNavier- Stokes equations (RANS) and Large Eddy Simulation (LES) for selected few cases.

KEY WORDS: Computational fluid dynamics, boundary layer wind tunnel, wind pressure, tallbuilding, RANS, LES

INTRODUCTION

Buildings, bridges, large span roof structures and other civil structures must be able to withstandthe external loads imposed by nature, at least to the extent that the disastrous damage of naturalforce reduced to the acceptable limit (Irwin, 2007). Wind is one of the major forces responsiblefor the catastrophic failure and loss of life. Therefore, accurate evaluation and prediction of windloads and proper mitigations are very important in reducing the adverse effects of wind in thebuilt environment. In addition to the mean and the background (due to turbulent fluctuations)loads on rigid buildings, flexible structures will be subjected to resonant wind loads as well. Theprimary source of the along-wind motion is the pressure fluctuations in the windward andleeward faces due to the fluctuation in the approach flow and its interaction with the building.Building codes and Standards usually provide loads along the wind direction for common shapes

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in open and suburban terrain category perhaps with the exception of the AS-NZ 2002 code whichattempts to provide provisions in for the cross-wind direction as well. The cross-wind motion ismainly caused by fluctuations in the separating shear layers. Torsional motion can be caused dueto imbalance in the instantaneous pressure distribution on each face of the building either due tooblique wind directions, unsteadiness in the approaching flow, partial sheltering and interferencefrom surrounding buildings or due to own shape and dynamic structural properties. Studiesshows that for many high-rise buildings, the crosswind and torsional response may exceeds thealong wind response in terms of both limit state and serviceability requirements (Kareem, 1985).Nevertheless, most existing standards, including ASCE07-05, only provides procedure forevaluation of along-wind effects. For complex cases, the standards refer to physical modeltesting in boundary layer wind tunnel (BLWT) facility.

The success of application of computational fluid dynamics (CFD) in aeronautical engineering isvery encouraging. Acknowledging the difference between streamlined and bluff body flows, theuse of computational fluid dynamics for predicting wind effects in the atmospheric boundarylayer appears very promising. This is particularly so considering the recent advances in hardwareand software technology, development of reliable sub-grid turbulence models and numericalreproduction of inflow turbulence (Tamura 2008). At this stage of CWE application, however, asystematic validation of CWE models through comparison with wind tunnel experiments shallcontinue to enhance the confidence and warrant its use for practical applications.

Significant progress has been made in the application of CWE to evaluate wind loads onbuildings (e.g. Murakami and Mochida 1988; Selvam 1997; Stathopoulos 1997; Wright et al.2003; Camarri et al. 2005; Tamura 2006; Tutar and Celik 2007; El-Okda et al. 2008; Tominagaet al. 2008a; Cóstola et al. 2009 and others). Significant progress has also been made on theevaluation of wind load modifications due to topographic elements (Bitsuamlak et al. 2004,2006; Poggi and Katul 2007). Some countries have already established working groups toinvestigate the practical applicability of CWE and develop recommendations for their use forwind resistant design of actual buildings and for assessing pedestrian level winds, within theframework of the Architectural Institute of Japan (AIJ) (Tamura et al. 2008, Tominaga et al.2008b`) and the European cooperation in the field of scientific and technical (COST) research(Franke et al. 2004). Further, AIJ provides methods for predicting wind loading on buildings bythe Reynolds Averaged Navier Stokes equations (RANS) and LES. Practical applications ofCWE are widespread in areas such as pedestrian level wind evaluation Chang (2006), Lam andTo (2006), Blocken and Carmeliet (2008), Yoshie et al. (2007), and Tablada et al. (2009), whereonly the mean wind speeds are required for evaluating pedestrian comfort (Stathopoulos and Hu2004). CWE applications for wind driven rain are reported by researchers such as Choi (2000),and Blocken and Cameliet (2004). Some CFD wind flow studies for urban neighborhoodinclude Zhang et al. (2006), Huang et al. (2006), and Jiang et al. (2008). While most of studiesmentioned above focus on straight winds, studies by Lin and Savory (2006), and Hangan andKim (2008) focused on simulation of downburst. Other common uses of CWE, includeaugmentation of experimental wind engineering research: Sengupta and Sarkar (2008)augmented their microburst and tornado wind simulator facility with numerical simulation;Merrick and Bitsuamlak (2008) used numerical simulation to facilitate selection of an artificialsurface roughness length to be applied on curved surfaced buildings during wind tunnel testingas a means to compensate for High Reynolds number effects that is usually missing from lowwind speed tunnels.

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The majority of numerical prediction of wind pressure loads on buildings devoted on the basiccube shape, because of its geometrical simplicity yet representing the complex features ofbuilding aerodynamics and availability of experimental data (Stathopoulos 2002; Nozawa andTamura 2002; Lim et al. 2009). These include full-scale low-rise building structures such asSilsoe Cube (Wright and Easom 1999, 2003), Texas Tech University (Senthooran et al. 2004)and Wall of Wind test building (Bitsuamlak et al. 2008). Some of the computational studies forTall Buildings include studies by Nozawa and Tamura (2002), Huang et al., (2007), Tominaga etal., (2008), Tamura (2008) and Braun et al. (2009). Huang et al. (2007) and Braun et al. (2009)focused on the aerodynamics of Commonwealth Advisory Aeronautical Council (CAARC)building model and investigate the flow pattern and mean and rms pressure coefficient. CAARCtall building is considered as one of the most extensively studied building model and popular inwind tunnel researcher community as well (Wardlaw and Moss 1970 as referenced by Braun etal. 2009; Melbourne 1980; Obasaju 1992). As a result, the present study also uses the CAARCbuilding model both for the numerical as well as boundary layer wind tunnel investigation thusallowing a comparative study among different researcher results which is required perhaps at thisstage of CWE application for building aerodynamics. Different from previous CAARC studies inliterature which focuses on isolated building, the present study include experimental andnumerical aerodynamic analysis of CAAR building model under different orientation of adjacentbuilding conditions. While the numerical simulation uses Fluent 6.3 commercial software andemploys mostly RANS and LES (for limited case) turbulence models, the experimental partinclude boundary layer wind tunnel experiments conducted at RWDI USA LLC, Miramar FL forthe present study.

Unlike flow around streamed line object, analysis of flow around sharp edged bluff-bodyinvolves many difficulties as pointed out by Murakami (1998) and Stathopoulos (1997).Intensive studies have been done on the suitability of various turbulence models (Murakami andMochida 1989; Murakami 1998; Castro and Graham 1999; Saha and Ferziger 1996, 1997).RANS has been used in wind engineering application due to their simplicity in modeling andreduced computational cost. Despite the computational cost, LES (large eddy simulation) isbelieved to have reached the stage where analysis can be carried out within a reasonablecomputational time for complicated turbulent flow around actual buildings and should beconsidered as a complementary tool for wind loads evaluation (Tamura, 2008).

NUMERICAL MODEL

Based on a preliminary exploratory study on surface mounted cube, different turbulence modelsfrom literature have been examined for their relative suitability for the present bluff bodyapplication. Figure 1 shows comparison between numerically obtained pressure coefficients onsurface mounted cube by several researches with experimental results. As expected LESprovides superior results that agree well the experimental data obtained from wind tunnel andfull-scale tests. From RANS family of models the RNG k- provides relatively better resultcompared to the standard k- model. In the present study RNG k- has been therefore opted dueto its relatively good agreement with BLWT compared to Standard k- and relatively lowercomputational resource demand compared to LES. Only for comparison purpose LES has beenapplied for Case 1A and Case 1B. Due to the chaotic nature of flow around bluff bodies, theturbulence flows significantly affected by the presence of walls. The near-wall treatment has agreat impact on the result of the numerical simulation. Murakami et al. (1999) discussed thedifficulty in using no-slip boundary condition at solid walls for flows with high Reynolds

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number, such as the present case. For such flow environment, Werner and Wengle (1991) wallfunctions in the viscous sub layer (as provided by Fluent 6.3), which will reduce the use ofexcessive fine meshes around the solid walls can be used. While for Case 1A, very fine meshesare used in the near-wall region in attempt to resolve the low Reynolds number flow up to thewall surface and Werner and Wengle (1991) wall functions are applied for Case 1B. Case 2 and3 uses non-equilibrium wall functions as described in FLUENT user manual (2006).

Figure 1 Comparison of mean pressure coefficients by several researchers using several turbulence models.

NUMERICAL AND WIND TUNNEL MODEL SETUPS

The geometrical modeling for the numerical simulation of CAARC building model mimics the1:400 scale rigid model of the wind tunnel testing. The CAARC model has a rectangularprismatic shape with dimensions 100 ft (x) by 150 ft (y) by 600 ft (z) height. The flow isdescribed in a Cartesian coordinate system (x, y, z), in which the x-axis is aligned with thestream-wise direction, the z-axis is in the perpendicular direction and the y-axis is in the verticaldirection. The computational domain dimensions, boundary conditions and the wind tunnelconfigurations and are given in Fig. 2. The driver (inlet), lateral and downstream boundaries areextended laterally to minimize blockage issue on the aerodynamics of the test building. TheReynolds number based on building height H and inflow velocity UH at Hz is 5108.3 x . Openexposure velocity profile with power low exponent of 0.16 is used during the present BLWT test.

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-1.5

-1

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0

0.5

1

1.5

Cp

Bitsuamlak et al., 2008 (K-e)

Wright and Easom, 2003 (K-e)

Wright and Easom, 2003 (RNG)

Wright and Easom, 2003 (NL)

Lim et al., 2009 (LES)

Wind tunnel (Holscher et al., 1998)

Wind tunnel (Richards et al., 2007)

Full Scale (Richards et al., 2007)

A B DC

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Table 1: Study cases

Case Configuration Velocity profile Scale

Case 1A Isolated BLWT (Huang 2007) 1:250Case 1B Isolated BLWT (present)Case 1C Isolated ASCE (exposure B)Case 1D Isolated ASCE (exposure C)Case 2A full height adj. bldg upwind of CAARC ASCE (exposure B)Case 2B full height adj. bldg upwind of CAARC ASCE (exposure C) 1:400Case 2C full height adj. bldg downwind of CAARC ASCE (exposure B)Case 2D full height adj. bldg downwind of CAARC ASCE (exposure C)Case 3A half height adj. bldg upwind of CAARC ASCE (exposure B)

In the present study, three building configurations under four different flow fields have beeninvestigated. Table 1 describes all cases considered for the numerical simulation of CAARCbuilding model. Case 1 simulates wind effects on the isolated building without considering theinterference action of the surroundings. Case 2 simulates CAARC building with an adjacentsurrounding building having similar height with the test building placed upwind and downwindof the study building. Case 3 simulates similar to Case 2 but the adjacent building has only halfheight of the CAARC model.

The computational domain contains non uniform grid points and the grid stretching ratio for LESsimulation is less than 1.1 to avoid cut-off wave number between neighboring grids, see Fig. 3.High mesh resolution is used in the low Reynolds viscous sub-layer zone. The inlet velocityboundary condition comprising four different mean profiles as shown in Fig. 4 has beensimulated. For transient flow simulation generation of inflow turbulence for LES analysis (Case1A), the velocity fluctuation is generated using spectral synthesizer available in Fluent. Free outflow boundary conditions are imposed as the downstream of the computational domain. Walltreatments as described in Numerical Model section are used at the building wall and the groundsurface. At the top and side boundaries are assumed to have zero velocity gradient andsymmetric boundary conditions are applied.

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(a) Computational domain and boundary conditions: Case 1.

(b) Wind tunnel configurations.

Isolated testbuilding

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(c) Computational domain: Case 3. (d) Computational domain: Case 2.

Figure 2 Computational and wind tunnel set up.

Figure 3 Typical grid used in the present study: Case 1A.

Horizontal section

Vertical section

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Figure 4 Inflow boundary condition (velocity profiles) used in the present study.

RESULT AND DISCUSSIONS

For validation and comparison purposes, both standard and LES simulations have been usedfor Case 1A and Case 1B. Measurements of mean pressure coefficients normalized by thedynamic pressure at the building height are compared with the present BLWT data as well asthose obtained from literature. The mean pressure coefficients, Cp, on the upper windward,sidewall and leeward faces are extracted for the isolated building case at 2/3H of the building asshown in Fig. 5 for various inflow boundary conditions. As shown in Fig. 5, there is a goodagreement between the present LES as well as Braun’s (2009) and Huang’s (2007) numericalsimulation results of the current study with the experimental results on the windward face. Theagreement deteriorates slightly at the sidewalls and improves at the lee-ward wall. The standard method over-predicts the pressure coefficient at the stagnation point and at flow separationpoint.

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8 9 10 11 12 13 14 15 16

U(m/s)

Z(m

) - M

odel

sca

le

BLWT (Huang et aL., 2007)

BLWT (Present study)

ASCE (Exposure - C)

ASCE (Exposure - B)

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Figure 2. Comparison of mean pressure coefficient.

Figure 3. Mean velocity contour at mid-vertical and 2/3 H horizontal section.

Figure 5 Measurements of mean pressure coefficients over the perimeter at Z/H =2/3: Velocity pressurenormalized by UH (12.7m/s)

Windward wall Leeward wall

Figure 6 Contour plot of mean pressure distribution over the building walls (Case 1A)

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Present study (ke - Case 1A)

Present study (LES - Case 1A)

Present study (LES - Case 1B)

Braun et al., (2009)-numerical

Huang et al., (2007)-numerical

Wind tunnel (BLWT- P resent study)

Wind tunnel (Tong Ji University)

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Mea

n C

p

Case 1B (RNG)

Case 1C (Exposure-B )(RNG)Case 1D (Exposure-C)(RNG)

Wind Tunnel (P resent study)

Figure 6 shows mean-pressure contour pots of the windward and leeward face of configurationCase 1A. The horseshoe vortex shape contour generated on the front wall agrees well withHuang et al. (2007) and Braun et al. (2009) flow field investigation. To asses the effects ofinflow boundary conditions, the present work studies four different inflow conditions as outlinedin table 1. Where each of the categories varies in their velocity profile, turbulence intensity andturbulence integral length scale. Figure 7 exhibits the comparison of mean pressure coefficientsobtained by numerical simulation with the wind tunnel data. Among all, there is reasonableagreement between Case 1C and the experiment on the windward face. As expected there issubstantial increase in prediction of mean Cp by the numerical method.

Figure 7 Measurements of mean pressure coefficients over the perimeter at Z/H =2/3 (Case 1): Velocitypressure normalized by UG (14.63 m/s)

Effect of adjacent building plays an important role on the aerodynamic response of buildings.Each building site is unique and needs to be examined case by case. In the present study alimited attempt was made to assess the effect of different adjacent building with different height,Case 2 with same height as with the study building and Case 3 with half height. The numericalas well as the wind tunnel test results, reveals the sheltering effect due to the presence of tallstructures upwind of the study building as shown in Fig. 8. Approximately a 150% reduction inmean pressure coefficient has been observed relative to the isolated case. Figure 9 presents thesame case but when the adjacent building is placed in the leeward direction of the flow. In thiscase the interference has no significant on the front wall pressure distribution but there is

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Figure 8 Comparison of mean pressure coefficients over the perimeter at Z/H =2/3 (Case 2A & 2B): Velocitypressure normalized by UG (14.63 m/s).

Figure 9 Measurements of mean pressure coefficients over the perimeter at Z/H =2/3 (Case 2C & 2D):Velocity pressure normalized by UG (14.63 m/s)

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p

W ind Tu nne l (P re se nt stud y)

C a se 2 A (E xp o sure -B )(R NG)

C a se 2 B (E xp o sure -C )(RN G)

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Mea

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W ind tunne l (P re se nt stud y)

C a se 2 C (Expo sure -B )

C a se 2 D (Expo sure -C )

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reduction in suction pressure coefficient. The presence of the half height adjacent building haveless significant impact on the mean pressure load compared to the effect of full height adjacentbuilding as can be expected.

Figure 10 Comparison of mean pressure coefficients over the perimeter at Z/H =2/3: Surroundinginterference effects

Mean pressure contours on the building surface are shown in Figs 11a and 11b for Cases 2 and 3respectively. Flow modification due to complex fluid structure interactions including theadjacent buildings are also shown in Figs. 11c and 11d for Cases 2 and 3 respectively. Flowseparation points, down washes on windward walls, recirculation behind buildings that aresignature of tall buildings are clearly depicted in these figures. These capabilities of CFDsimulations are very useful in explaining aerodynamics phenomena among wind engineers and tostructural engineers and architects.

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Case 1B (BLWT - Present study)

Case 1B (Exposure - B)(RNG)

Case 2 (BLWT - Present study)

Case 2A (Exposure - B)(RNG)

Case 3 (BLWT - Present study)

Case 3A (Exposure - B)(RNG)

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(a) Case 2 (b) Case 3Mean pressure coefficients

(c) Velocity path lines: Case 2

(d) Velocity path lines: Case 3

Figure 11 Mean pressure coefficient and velocity path lines: Case 2& Case 3

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CONCLUSIONS AND FUTURE WORKS

Several comparisons between CFD and experimental analysis have been discussed in order tobetter understand the current state-of-the-art and assess the potential use of numerical wind loadpredictions approaches for practical use. In the past, consistent efforts have been made to makeCFD a better tool for evaluation of wind loads. The application of CFD techniques to predictwind load, on CAARC model and with different surrounding conditions reveals the suitability ofCFD tools for preliminary assessments and detail explanation of complex building aerodynamiccharacteristics. Consistent to reports in literature, numerical data comparison withmeasurements in boundary wind tunnel carried out in the present study suggests that an accuratetime-dependent analysis, such as LES analysis is very vital. Planned future studies include detailLES analysis of buildings incorporating various orientation of surrounding effects.

ACKNOWLEDGMENT

The support from National Science Foundation (through NSF Career award to the second author)is gratefully acknowledged.

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