**6. Sample study of building aerodynamics at the LSU WISE lab**

The LSU research team aspires to match the spectral content of real wind using large-scale open-jet testing and CFD simulations in their quest of accurate estimation of peak pressures on building surfaces under wind. The goal is precise estimation of peak pressures on buildings through the generation of large- and small-scale turbulence via open-jet testing as well as advanced CFD simulations. Extreme negative pressures near ridges, corners, and leading edges of roofs are governed dominantly by wind turbulence and Reynolds number, among other factors. Both small- and large-scale turbulence vortices are responsible for peak pressures and can influence separation in the shear layer. This demands for precise replication of wind speed profile, turbulence intensity profiles, and spectral characteristics. Replication of the true physics requires higher Reynolds number which is difficult to achieve in wind tunnels. In traditional wind testing, it is challenging to create large-scale turbulence. An increase in large-scale turbulence content in incident flow allows vortices to attain maturity, and as a result higher peak pressures can be reproduced. A fundamental research objective, however, is to address the challenge of replicating real wind turbulence experimentally and computationally. Resolving the scaling issue by investigating larger test models at higher Reynolds number is another highlight of our research at the LSU WISE lab.

The velocity was measured at different heights in the open-jet facility with cobra probes to obtain the mean velocity and turbulence intensity profiles. **Figure 11(i)** shows the comparison of experimental mean velocity profiles from LSU open jet and TPU wind tunnel with theoretical wind profiles measured for open terrain condition (*z*<sup>0</sup> ¼ 0*:*01 *m*). It was observed that the measured mean velocity profile at LSU open jet was consistent with different theoretical profiles and also velocity profile measured at TPU. It should be noted that the *Uref* corresponding to 10 m in full scale was 22 m/s [66]. For normalizing the experimental data, velocity information corresponding to *Href* ¼ 0*:*75 m was considered. Mean velocity corresponding to 0.75 m was considered to be *Uref* in the open jet. **Figure 11(ii)** shows along wind turbulence intensity profiles from experimental data and theoretical formulations. The velocity data were processed to obtain turbulence intensity, and the profile was compared with theoretical profile corresponding to the following equation.

$$I\_u(z) = \frac{1}{\ln\left(\frac{z}{x\_0}\right)}\tag{10}$$

The vertical profile plot for turbulence intensities shows that the LSU open-jet facility has approximately 20% turbulence intensity at reference height. Both mean velocity and turbulence intensity profiles in **Figure 11** shows that LSU open-jet facility is capable of replicating open terrain near-ground ABL flow.

A scaled (1:13) cubic building model was tested at the LSU WISE large open-jet facility. The primary objective of this task was to compare surface pressure coefficients those obtained by wind tunnel testing on a smaller scale (1:100) model. Wind tunnel measurements are obtained from the published dataset of Tokyo Polytechnic University (TPU). The building model was instrumented with several pressure taps to capture surface pressures. A total of 64 taps were distributed on roof, same as the

to maintain correct physics, and at the same time large-scale testing (not full-scale) will lead to improved Reynolds number. Large-scale wind testing went through several phases before reaching the present stage [63]. A multidisciplinary LSU research team from Civil and Environmental Engineering, Mechanical Engineering, Coast and Environment, Louisiana Sea Grant, Geography and Anthropology, Construction Management, and Sociology collaborated on a project titled "Hurricane Flow Generation at High Reynolds Number for Testing Energy and Coastal Infrastructure" that was awarded by the Louisiana Board of Regents to build Phase 1 of a large wind and rain testing facility (**Figure 10**). Phase 1 permits generating wind flows at a relatively high Reynolds number over a test section of 4 m 4 m. These capabilities enable executing wind engineering experiments at relatively large scales. Moreover, the large open-jet facility has a potential for conducting destructive testing on models built from true construction materials. Blockage is minim, as per the concept of open-jet testing [65]. This state-of-the-art facility can generate realistic hurricane wind turbulence by replicating the entire frequency range of the

The large LSU WISE open-jet facility enables researchers to test their research ideas; to expand knowledge leading to innovations and discovery in science, hurricane engineering, and materials and structure disciplines; and to build the more resilient and sustainable infrastructure. The facility will enable scientists and researchers to test potential mitigation and restoration solutions, both natural (e.g., vegetation) and artificial. Potential applications include, but are not limited to, wind turbines, solar panels, residential homes, large roofs, high-rise buildings, transportation infrastructure, power transmission lines, etc. Testing at this facility can provide knowledge useful for homeowners and insurance companies to deal more effectively with windstorms, for example, to fine tune design codes and give coastal residents options for making their dwellings more storm-resistant. The goal is to build new structures and retrofit existing ones in innovative ways to balance resilience with sustainability, to better protect people, to enhance safety, and to reduce the huge cost of rebuilding after windstorms. In addition, the facility offers tremendous education value to k-12, undergraduate, and graduate students at a flagship state university, designated as a land-grant, sea-grant, and space-grant institution. This will broadly impact the wind/structural engineering research and

velocity spectrum.

*Aerodynamics*

**Figure 10.**

**42**

*LSU WISE large testing facility (with a test section of 4 m 4 m).*

**Figure 11.** *Flow characteristics: (i) mean velocity and (ii) turbulence intensity.*

TPU wind tunnel model. Pressure taps were connected to Scanivalve pressure scanners through appropriate tubing. Two cobra probes were used to monitor upstream velocity at roof height [58]. The following equation was used to compute the pressure coefficient.

$$C\_p(t) = \frac{p(t) - p\_s}{\binom{1}{2} \rho U^2} \tag{11}$$

On the computational side, the k- SST turbulence model was employed for improved mean pressure prediction near the flow separated region. An advanced approach is ongoing that employs large eddy simulation (LES) to generate accurate mean and peak pressures. **Figure 13** shows a sample of high-quality mesh and CFD

*Minimum pressure coefficients on roof: (a) LSU open-jet (b) TPU wind tunnel (wind from bottom left corner).*

*Aerodynamics of Low-Rise Buildings: Challenges and Recent Advances in Experimental…*

*DOI: http://dx.doi.org/10.5772/intechopen.92794*

In order to alleviate the challenges and shortcomings involved within the experimental tests in boundary-layer wind tunnels, in recent years, CFD was considered as an effective tool for the simulation of wind effects on civil engineering structures. However, it is necessary that the numerical CFD model would be capable of generating turbulence in a flow with certain spectral contents and eventually to reproduce peak pressures on building surfaces. The objective of this research is therefore to provide a basis for the development of recommendations and guidelines on using a CFD LES model that enables appropriate simulation of turbulence spectra of ABL inflow and reproducing the peak wind pressures on the roof of low-rise buildings. **Figure 14** represents a schematic of the tools used by Aly and Gol Zaroudi [49] to simulate peak wind loads on a benchmark full-scale building from the Texas Tech University (TTU) in an open-terrain field. The details, advantages, and disadvan-

Considering the current rapid improvements in developing high-speed processors that can run in parallel on high-performance computing (HPC) clusters and devising new digital storage devices with huge capacities, CFD is becoming a promising tool in wind engineering applications. However, it is still a challenge for proper simulation of turbulence according to ABL wind characteristics and accurately reproducing peak pressures on low-rise buildings, even with supercomputers [40]. Aly and Gol Zaroudi [49], therefore, attempt to address some of the challenges in experimental and numerical simulations for aerodynamic testing of lowrise buildings, to reproduce realistic peak pressures. The study focused on wind flow processes in CFD with an objective to mimic full-scale pressures on low-rise building. The study implemented CFD with LES on a scale of 1:1 building. After a proximity experiment was executed in CFD-LES, a location of the test building from the inflow boundary was recommended, different from existing guidelines (RANS-based, e.g., COST and AIJ). The inflow boundary proximity showed significant influence on pressure correlation and the reproduction of peak pressures.

tages of each tool are discussed in Aly and Gol Zaroudi [49].

simulations in OpenFOAM.

**Figure 12.**

**45**

The time history of pressure coefficients, *Cp*(*t*), was obtained from the pressure time history, *p*(*t*), recorded using pressure scanners. The static pressure *ps* was considered reference for the pressure transducers. In addition, base line pressures were collected before and after each experiment. Once the time history of pressure coefficients was obtained, statistical analysis was done to obtain mean, minimum, and root mean square (rms) values. Measurements from LSU open-jet and TPU wind tunnel were processed the same way. The maximum and minimum values were obtained using MATLAB functions with a probabilistic approach described in Ref. [67]. This approach was considered, to account for the highly fluctuating wind flow, to yield a more stable estimator of peak values.

Sample of the findings of the experiment and comparison with TPU results is shown in **Figure 12**. The distribution of pressure coefficients obtained by open jet testing is symmetric like what is observed in the TPU wind tunnel testing. Since the model in open jet was tested at a higher Reynolds number, higher values of peak pressure coefficients are realized. Higher suction was observed near the zone of flow separation on the roof. Stronger suction for open-jet testing was found due to higher Reynolds number in open-jet and the presence of larger-scale turbulence compared to the wind tunnel. This difference in Reynolds number leads to difference in formation of flow separation zone, stagnation point on windward face, and the reattachment length. The difference between full-scale and reduced-scale wind tunnel tests is owed to similar reasons.

*Aerodynamics of Low-Rise Buildings: Challenges and Recent Advances in Experimental… DOI: http://dx.doi.org/10.5772/intechopen.92794*

**Figure 12.** *Minimum pressure coefficients on roof: (a) LSU open-jet (b) TPU wind tunnel (wind from bottom left corner).*

On the computational side, the k- SST turbulence model was employed for improved mean pressure prediction near the flow separated region. An advanced approach is ongoing that employs large eddy simulation (LES) to generate accurate mean and peak pressures. **Figure 13** shows a sample of high-quality mesh and CFD simulations in OpenFOAM.

In order to alleviate the challenges and shortcomings involved within the experimental tests in boundary-layer wind tunnels, in recent years, CFD was considered as an effective tool for the simulation of wind effects on civil engineering structures. However, it is necessary that the numerical CFD model would be capable of generating turbulence in a flow with certain spectral contents and eventually to reproduce peak pressures on building surfaces. The objective of this research is therefore to provide a basis for the development of recommendations and guidelines on using a CFD LES model that enables appropriate simulation of turbulence spectra of ABL inflow and reproducing the peak wind pressures on the roof of low-rise buildings. **Figure 14** represents a schematic of the tools used by Aly and Gol Zaroudi [49] to simulate peak wind loads on a benchmark full-scale building from the Texas Tech University (TTU) in an open-terrain field. The details, advantages, and disadvantages of each tool are discussed in Aly and Gol Zaroudi [49].

Considering the current rapid improvements in developing high-speed processors that can run in parallel on high-performance computing (HPC) clusters and devising new digital storage devices with huge capacities, CFD is becoming a promising tool in wind engineering applications. However, it is still a challenge for proper simulation of turbulence according to ABL wind characteristics and accurately reproducing peak pressures on low-rise buildings, even with supercomputers [40]. Aly and Gol Zaroudi [49], therefore, attempt to address some of the challenges in experimental and numerical simulations for aerodynamic testing of lowrise buildings, to reproduce realistic peak pressures. The study focused on wind flow processes in CFD with an objective to mimic full-scale pressures on low-rise building. The study implemented CFD with LES on a scale of 1:1 building. After a proximity experiment was executed in CFD-LES, a location of the test building from the inflow boundary was recommended, different from existing guidelines (RANS-based, e.g., COST and AIJ). The inflow boundary proximity showed significant influence on pressure correlation and the reproduction of peak pressures.

TPU wind tunnel model. Pressure taps were connected to Scanivalve pressure scanners through appropriate tubing. Two cobra probes were used to monitor upstream velocity at roof height [58]. The following equation was used to compute

> *Cp*ðÞ¼ *<sup>t</sup> p t*ðÞ� *ps* 1 2

time history, *p*(*t*), recorded using pressure scanners. The static pressure *ps* was considered reference for the pressure transducers. In addition, base line pressures were collected before and after each experiment. Once the time history of pressure coefficients was obtained, statistical analysis was done to obtain mean, minimum, and root mean square (rms) values. Measurements from LSU open-jet and TPU wind tunnel were processed the same way. The maximum and minimum values were obtained using MATLAB functions with a probabilistic approach described in Ref. [67]. This approach was considered, to account for the highly fluctuating wind

flow, to yield a more stable estimator of peak values.

*Flow characteristics: (i) mean velocity and (ii) turbulence intensity.*

tunnel tests is owed to similar reasons.

**44**

The time history of pressure coefficients, *Cp*(*t*), was obtained from the pressure

Sample of the findings of the experiment and comparison with TPU results is shown in **Figure 12**. The distribution of pressure coefficients obtained by open jet testing is symmetric like what is observed in the TPU wind tunnel testing. Since the model in open jet was tested at a higher Reynolds number, higher values of peak pressure coefficients are realized. Higher suction was observed near the zone of flow separation on the roof. Stronger suction for open-jet testing was found due to higher Reynolds number in open-jet and the presence of larger-scale turbulence compared to the wind tunnel. This difference in Reynolds number leads to difference in formation of flow separation zone, stagnation point on windward face, and the reattachment length. The difference between full-scale and reduced-scale wind

<sup>ρ</sup>*U*<sup>2</sup> (11)

the pressure coefficient.

**Figure 11.**

*Aerodynamics*

extreme negative pressures near ridges, corners, and leading edges of roofs in wind events. Turbulence (small- and large-scale) is responsible for large peak negative pressures and separation in the shear layer. This demands for precise replication of wind speed profile, turbulence intensity profiles, and spectral characteristics. Replication of true physics requires equality of Reynolds number which is not possible in wind tunnels. In traditional wind tunnels, only small-scale turbulence can be generated. An increase in large-scale turbulence content in incident flow allows vortices to attain maturity, and as a result higher peak pressures are obtained. The challenge of properly simulating wind effects on low-rise buildings is related to the lack of capability in turbulence modeling at a reasonably large scale and its limitation in reproducing the low-frequency part of the ABL turbulence spectrum. As a result, advances in aerodynamic testing employing modern tools such as open-jet testing for large- and full-scale testing were devised in recent years. Resolving the scaling issue by studying larger models at higher Reynolds number is another highlight of recent advances in aerodynamic testing. A large-scale cubic building model was tested in LSU open-jet facility at higher Reynolds number, and pressure coefficients were compared with those from wind tunnel testing. The results reveal the importance of large-scale testing at higher Reynolds numbers to obtain realistic peak pressures. Furthermore, CFD with appropriate turbulence closure was widely implemented recently for full-scale studies of wind effects on civil engineering structures. However, adopting proper inlet transient velocity is very crucial to

*Aerodynamics of Low-Rise Buildings: Challenges and Recent Advances in Experimental…*

correctly simulate ABL wind characteristics.

*DOI: http://dx.doi.org/10.5772/intechopen.92794*

Aly Mousaad Aly\*, Faiaz Khaled and Hamzeh Gol-Zaroudi

University, Baton Rouge, LA, United States

provided the original work is properly cited.

\*Address all correspondence to: aly@LSU.edu

Windstorm Impact, Science and Engineering (WISE) Laboratory, Louisiana State

© 2020 The Author(s). Licensee IntechOpen. This chapter is 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,

**Author details**

**47**

**Figure 13.**

*With high-quality mesh and potential turbulence closure, CFD can provide continuous flow information: (a) 3D view of the computational grid, (b) meshing arrangement along the longitudinal section over a cube, and (c) velocity contour, after simulations in OpenFOAM.*

**Figure 14.**

*The research tools employed to reproduce peak wind pressures on the roof of a benchmark low-rise building from the Texas Tech University (TTU) in an open-terrain field.*

The CFD LES turbulence closure showed its capabilities to reproduce peak loads that can mimic field data owing to the ability of creating inflow with enhanced spectral contents at 1:1 scale [49].
