developments in computational wind engineering

Journal of Wind & Engineering, Vol. 5, No. 1, Jan 2008, pp. 47-54

DEVELOPMENTS IN COMPUTATIONAL WIND ENGINEERING R. Panneer Selvam James T. Womble Professor of Computational Mechanics and Nanotechnology Modeling, Department of Civil Engineering, BELL 4190 University of Arkansas, Fayetteville, AR, USA, Email: [email protected],Ph: 479-575-5356, Fax: 479-575-7168

ABSTRACT A brief history and survey on computational wind engineering (CWE) is presented. Recent work conducted at the Computational Mechanics Laboratory in the areas of building aerodynamics, bridge aerodynamics and other computer modeling to enhance the performance of wind tunnels are reported. The issues related to computing corner roof pressures using computer modeling, challenges in implementing adaptive finite element for CWE are discussed with examples. Future challenges in computer modeling of hurricanestructure interaction, bridge-vehicle interaction and rain-wind and cable interactions are also addressed. Key Words: Computational Wind Engineering, Fluid-structure interaction, Finite element method INTRODUCTION Computational Wind Engineering (CWE) as a field has been addressed by the wind engineering community from mid 1980s. Paterson and Aplet (1986) computed the flow over three-dimensional buildings using k-ε turbulence model and at the same time, Murakami and Mochida (1987) computed the flow over a surface mounted cube using large eddy simulation, and, McDonald and Selvam (1985) computed the forces on a building due to a tornado using inviscid flow equations. Later full Navier-Stokes equations in the primitive form were used by Selvam (1992 & 1993) to study roof corner pressures, to study the impact of thunderstorm wind on buildings and to initiate the study of bridge aerodynamics. To reduce computer time efficient solution techniques were introduced in CWE by Selvam (1996). After this many researchers started to apply CWE to building and bridge aerodynamics and pollutant transport in and around buildings as surveyed by Murakami (1997), Selvam (1997) and Stathopoulos (1997). CWE for bridge aerodynamics were reviewed by Walther (1998) with special attention to discrete vortex method and Selvam (1998 & 2002) with reference to grid based methods. From then on several researchers started to enter the field and their contributions are available from National and International Wind Engineering and Computational Wind Engineering Conferences. In this paper, recent work performed in the Computational Mechanics Laboratory at the Department of Civil Engineering, University of Arkansas is reviewed and future challenges is addressed. COMPUTING PRESSURES AROUND BUILDINGS The pressures around the building envelope have been computed using large eddy simulation or k-ε model as reported in Selvam (1996, 1997 & 2005). In those works due to limitations in computer memory and time coarse grids of the order of 50,000 nodes to 1.6 Million nodes were used. Selvam and Millett (2005) used five different grids for their tornado-structure interaction as shown in Table 1. In Figure 1, the computed

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Developments in Computational Wind Engineering Table 1: Grid Properties (H is the height of the building) GRID

Computational Grid

Min. Spacing close to bldg.

Total no. of points

A B C D E

45 x 45 x 45 61 x 61 x 37 103 x 103 x 561 31 x 131 x 691 55 x 155 x 69

0.1000 H 0.0720 H 0.0104 H 0.0078 H 0.0055 H

50,625 137,677 594,104 1,184,109 1,657,725

2

1

Cx 0

Cy Cz

-1

Cp -2

FORCE COEFFICIENTS

FORCE COEFFICIENTS

2

1

Cx

0

Cy -1

Cz Cp

-2

-3

-3 A

B

C

GRIDS

(a)

D

E

A

B

C

D

E

GRIDS

(b)

Fig. 1: Convergence of force and pressure coefficients for (a) 0o tornado angle and (b) 45o tornado angle (from Selvam and Millett, 2005).

force coefficients Cx, Cy and Cz and maximum pressure coefficient Cp are plotted against different mesh sizes. It is found that the local pressure coefficient did not converge for the finest grid. This is similar to wind tunnel modeling where high frequency effects are damped due to scale limitations. Through the model the authors explained systematically why the roof of a building lifted up in a tornado. It was explained that when the rotating wind is around the building, the wind can not flow around the building as it happens for straight wind and hence it goes up and lifts the roof as shown in Figure 2. From the study it was found that the pressure coefficients developed on the roof are twice those for straight wind and 50% more on the walls. Later Millett et al. (2005) reported that moment coefficient about the vertical axis is found to be significant compared to straight wind (moment coefficient is zero)

(a)

(b)

Fig. 2: Views of vertical velocity at (a) the xz-plane, and (b) the yz-plane for grid D with the tornado surrounding the building (Selvam and Millett, 2005).


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Further detailed study is needed on grid resolution to capture small vortices. Also it is to be noted that, most of the modeling work is conducted with out inflow turbulence (Selvam, 1997). The influence of turbulence on pressures on the building needs to be investigated. Katakoa and Mizuno (2002) and Izuka et al. (1999) used inflow turbulence to study flow over buildings as an initial study. More systematic study is needed to see the effect of different spectra of turbulence on pressures on the building. ADAPTIVE FEM FOR BRIDGE AERODYNAMICS Bridge aerodynamics studies were initiated by Selvam and Paterson (1993) by developing experimentally verified computer model based on finite difference method. The model is verified by computing the drag and lift coefficients for circular cylinder at Reynolds number 100 and 1000. Later the models were improved for aeroelastic analysis of bridges by using finite elements and moving grids techniques as reported in Selvam et al. (2002 and 2003). The model can be used to calculate the flow around the fixed and moving bridge and also to calculate the critical flutter velocity. Both finite element and finite difference methods are used to solve the Navier-Stokes equations. The critical flutter velocity is calculated using the free motion of the bridge. Presently the model can calculate the critical flutter velocity in about a month using a personal computer. In the wind-tunnel to conduct a similar study it takes about 3 months and costs around $100,000. The major bottleneck of the current model is the use of inadequate grid refinements around bridge deck and to compute critical flutter velocity with reasonable accuracy. It is difficult to formulate proper refinements around the bridge deck using structured grid as shown in Figure 3 for great Belt East Bridge (GBEB) taken from Selvam et al. (2005). Using unstructured grid it is possible to make proper refinements if adaptive techniques are incorporated. Grid refinements around GBEB using unstructured grid are shown in Figure 4 and the corresponding vorticity contour is also reported. It can be seen that due to fine refinements recirculation on the top of the bridge deck is captured in Figure 4 but not in Figure 3. On the other hand the number of grid

Fig. 3: Great Belt East Bridge suspension span close-up view of the grid and vorticity contour (Selvam et al. 2005)

Fig. 4: Unstructured grid for Great Belt East Bridge and the corresponding vorticity contour (Selvam et al. 2005)

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Developments in Computational Wind Engineering

points used in Figure 3 and Figure 4 are 19,080 and 46,932 nodes. Hence much more computer time is used in adopting the grid in figure 4. Preliminary investigation of applying adaptive techniques to flow over circular cylinder (Selvam and Qu, 2002) is encouraging. Selvam et al. (2007) used h-adaptive FEM to study flow over GBEB. The computed results are encouraging. The drawbacks are that the model took extensive computer time and there were difficulties in obtaining the necessary refinement in grid size close to the bridge. The reason is that in using adaptive procedure when triangular grids are refined close to the bridge for a spacing of 0.001B (where B is the bridge width) one needs more than 2000 points around the bridge. In the boundary layer one needs spacing perpendicular to the surface of the order of 0.001B and around the bridge one can use much larger spacing. But using triangular grid generator it is difficult to refine other than equilateral triangles. If one uses higher order elements as reported by Sherwin and Karniadakis (1995), Henderson (1999) and Karniadakis and Sherwin (2004) one can have much larger spacing close to the wall. Further work is underway to implement the higher order finite element techniques. MODELING TO IMPROVE THE PERFORMANCE OF WIND EXPERIMENTS Modeling the Turbulence Generated by Moving Airfoil in the Wind Tunnel The Wall of Wind (WOW) facility developed for building studies (Gan Chowdhury et al. 2007) at the Florida International University is further improved by controlling and enhancing the turbulence generated in the WOW by using NACA4 (1996) airfoil. This is similar to the way turbulence is generated in the wind tunnel by Ozono et al. (2006). To understand the turbulence generated by NACA4 airfoil the programs developed for bridge aerodynamics study (Selvam et al. 2002 & 2003) were modified to consider forced motion of the airfoil. The flow around the model is computed using 161x72 finite difference grid as shown in Figure 5. The airfoil is rotated using the non-dimensional reduced velocity u* = V/wB equal to 1.2 where V is the upstream velocity, B is the width of the airfoil and w is the frequency of the airfoil rotation in radians/second. The u*= 1.2 relates to a period of 0.1 sec for a wind speed of 110 mph and a chord length of 25 inches Using the model, the effect of amplitude and frequency on turbulence generated is investigated. A sample plot of velocity in the x and y directions with respect to time is given in Figure 6. For more details one can refer to Selvam and Mita (2007). Further work is underway to simulate a known spectrum as input and see how much turbulence is generated behind the airfoil. Thus the model is very useful to design the airfoil. Modeling the Flow Features in the Wind Tunnel The WOW facility can further enhance the wind field by pumping the air from different cabinets inclined to one another. When the cabinets are placed in parallel the wind field from one cabinet affects the neighboring cabinets. A computer model is developed to understand the flow features and how the model can help to

Fig. 5: Variation of rms values of pressure at various zones a) upper surface; b) lower surface;


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Fig. 6: Variation of net upward pressure coefficient at various zones a) zone-1; b) zone-2, c) zone-3, d) zone-4

Fig. 7: Variation of net downward pressure coefficient at various location of wall a) zone-1; b) zone-2, c) zone-3, d) zone-4

improve the flow. Every cabinet is 8 foot in width which is equal to 1 unit in computational length scale. The wind is flowing through each cabinet from left to right (along X axis). The cabinet (flow) separating wall thickness is 0.015 (1.44 inches) units. Initial flow studies in and around the WOW cabinets are reported in Figure 8. The model uses the Navier-Stokes equations using finite difference method. The rectangular grids

Fig. 8: Variation of net mean pressure coefficient for different zones at various location of wall

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are used and the non flow regions are flagged for no flow. The grid size in x direction is 0.0217 (2.08 inches) units and in y direction it is 0.0147 (1.41 inches) units. The model is further used to study the effect of different dimensions of the WOW cabinets and the angle of inclination on the flow developed on the leeward side. Further details can be found in the report of Selvam and Mita (2007). FUTURE CHALLENGES IN CWE Hurricane-Building Interaction In hurricanes, in addition to wind moving in a particular direction it also rotates, as in a tornado. Only difference between a tornado and a hurricane is that the translating wind speed of the core is slower and the diameter of the core is in hundreds of miles compared to less than a mile in a tornado. This kind of hurricane - building interaction is very difficult to simulate in a wind tunnel. Selvam and Millett (2005) used computer model to compute tornado impact on a building. See Fig. 2 and related discussion given earlier in the paper. It was reported that it was not possible to get a grid converged solution due to computer storage limitations. The topics to be investigated in the area of building aerodynamics and hurricane structure interaction are: i. ii. iii.

iv.

v.

Develop hurricane model to be used in the flow code to compute pressure coefficients. The range of diameter of the core of a hurricane and rotational and translational wind speed needs to be determined from field observations. Conduct convergence study by decreasing the grid size and get a converged solution for pressure coefficients and pressures. Conduct systematic study by varying the translational and rotational wind speed as well as the diameter of the core of the hurricane. The effect of these hurricane parameters on the pressure and moment coefficients of the building to be analyzed systematically. The difference between straight wind and hurricane type wind to be brought out. In addition the hurricane and tornado wind pressure coefficients change in a short time. Hence this dynamic effect on the enhancement of pressures also needs to be investigated. This has rarely been investigated in the past. The sum of all these effects needs to be considered to get an equivalent static pressure coefficient. The equivalent static pressure coefficient procedure is the one used in the current building codes. From this study the change in pressure coefficients on the roof and sides should be recommended for building codes and industry.

Bridge-Vehicle Interaction The bridge aerodynamics model should study the effect of vehicles on the bridge and their interaction on critical velocity for flutter. Only few researchers have investigated these phenomena from wind tunnel experiments. This is very important during hurricane evacuation time. Because of stability reasons sometime major bridges may need to be closed beyond certain wind speed during hurricane evacuation. The model can help to understand the impact of hurricane on bridge with vehicle. Especially when the bridges are designed aerodynamically the wind speed on the vehicle is severe compared to bridges not having aerodynamic shape. The stability of the vehicle is another issue during hurricane which needs to be investigated. Wind-Rain-Cable Interaction Nowadays several long span bridges are built using cables due to economic construction. These cables are easily excited by wind because of their inherent low structural damping. This vibration causes structural fatigue or human discomfort and hence cable-vibration has to be mitigated. To suppress vibration one should understand clearly the vibration mechanism. The flow-induced vibrations are Von Korman vortex excitation and galloping instability. Galloping instability for isolated cables due to rain and wind induced vibration of inclined cables are of recent interest as reported by Matsumoto (2002). Matsumoto has given the status of


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wind and field study and problems that are not yet resolved. There are many difficulties in the wind tunnel tests for the simulation of prototype inclined cable aerodynamics, because of three dimensionality and the unsteadiness of the flow field around an inclined cable and the simulation of rain as reported by Matsumoto (2002). The major problems identified in the wind tunnel are simulating the support conditions, modeling the water rivulet movement and influence of axial flow on inclined cables. In these situations computer modeling may be a viable tool to assist wind tunnel work as well as serve as an alternate tool. Computer modeling has been successfully applied to calculate a bridge critical velocity for flutter (Selvam et al. 2002). Similar techniques can be applied to study the cable aerodynamics. The computer models are useful to understand the phenomena much better because of the availability of detailed information of velocity and pressure all around the cable. ACKNOWLEDGEMENTS This study has been partially funded by Mr. Harold Bosch, Federal Highway Administration through Lendis Corporation, McLean, Virginia and by Dr. Arindam Gan Chowdhury, Florida International University through International Hurricane Center. The author also acknowledges the help provided by Dr. Paul Millett, Dr. Sanjaya Patro and Ms. Mita Sarkar from the Computational Mechanics Laboratory, University of Arkansas to prepare this paper. REFERENCES 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15.

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