# Performance of Turbulence Models in Simulating Wind Loads on Photovoltaics Modules

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## Abstract

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## 1. Introduction

## 2. Problem Description

#### Grid Independence Analysis

## 3. Results & Discussion

#### 3.1. Steady RANS Models

#### 3.2. Unsteady RANS Model

## 4. Conclusions

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 1.**Schematics of the computational domain and the spatial grid (not to scale). The darker regions are the result of higher density grid.

**Figure 3.**Streamlines plot of the wake central $xy-$plane from different RANS models at $Re$ = 1200.

**Figure 5.**Comparison of the mean velocity and turbulent kinetic energy along the wake centerline compared to Reference [29].

**Figure 7.**Mean streamwise velocity (left) and streamwise velocity gradient (right) computed by steady and unsteady $k-\epsilon $ and compared to Reference [29].

**Figure 8.**Comparison of mean velocities at $x=5h$, calculated by steady and unsteady $k-\epsilon $ and compared to Reference [29].

**Figure 9.**Comparison of mean velocities at $x=8h$, calculated by steady and unsteady $k-\epsilon $ and compared to Reference [29].

**Figure 10.**Comparison of the turbulent kinetic energy in the wake, computed by steady and unsteady $k-\epsilon $ and compared to Reference [29].

**Figure 11.**Comparison of Reynolds normal stress in the wake, computed by unsteady $k-\epsilon $ and compared to Reference [29].

**Figure 12.**The turbulence kinetic energy production (left) and dissipation (right) along the wake centerline. x is normalized by the mean recirculation length and production results from DNS are scaled by ${10}^{3}$.

**Figure 13.**The profile of mean streamwise velocity gradient along the wake centerline. x is normalized by the mean recirculation length.

**Table 1.**Comparing the mean drag coefficient and recirculation length for different turbulence model, with the Direct Numerical Simulation (DNS) results at similar Reynolds number ($Re=1200$).

Case | Method | $\overline{{\mathit{C}}_{\mathit{d}}}$ | $\overline{{\mathit{L}}_{\mathit{w}}}/\mathit{h}$ |
---|---|---|---|

SIM-1 | Standard k-$\epsilon $ | 1.93 | 5.15 |

SIM-2 | SST k-$\omega $ | 1.73 | 6.98 |

SIM-3 | RNG k-$\epsilon $ | 1.73 | 8.34 |

SIM-4 | BSL RSM | 1.66 | 10.73 |

Hemmati et al. [5] | DNS | 2.13 | 2.65 |

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**MDPI and ACS Style**

Fogaing, M.B.T.; Hemmati, A.; Lange, C.F.; Fleck, B.A.
Performance of Turbulence Models in Simulating Wind Loads on Photovoltaics Modules. *Energies* **2019**, *12*, 3290.
https://doi.org/10.3390/en12173290

**AMA Style**

Fogaing MBT, Hemmati A, Lange CF, Fleck BA.
Performance of Turbulence Models in Simulating Wind Loads on Photovoltaics Modules. *Energies*. 2019; 12(17):3290.
https://doi.org/10.3390/en12173290

**Chicago/Turabian Style**

Fogaing, Mireille B. Tadie, Arman Hemmati, Carlos F. Lange, and Brian A. Fleck.
2019. "Performance of Turbulence Models in Simulating Wind Loads on Photovoltaics Modules" *Energies* 12, no. 17: 3290.
https://doi.org/10.3390/en12173290