本研究以 OpenFOAM 建立大渦模擬架構，探討時變入流條件下之風力機尾流特性，並比較不同致動器型風力機模型與網格解析度對尾流預測之影響。研究中採用 WALE 次網格尺度模型與 pimpleFoam 求解非穩態不可壓縮流場，並以體積力源項表示風力機氣動效應，包含 ADM-NR、ADM-R 與 ALM。所有案例皆採用相同時變入流條件，並以風洞實驗資料作為比較基準。分析物理量包含時間平均流向速度、流向紊流強度、垂直紊流動量通量，以及 resolved TKE budget terms。
結果顯示，ADM-R1 與最細網格 ADM-R0 具有相近之尾流預測結果，並可在計算成本與預測能力間取得較佳平衡。相較於 ADM-NR，ADM-R1 因考慮非均勻徑向載重與轉子誘導旋轉，可改善近尾流預測。ALM 結果顯示，nacelle 與 tower 源項主要影響 hub 附近與尾流下方之近尾流區域，而降低網格解析度會使紊流相關分布更為平滑。Resolved TKE budget 分析顯示，尾流紊流能量主要由剪切層中的 shear production 產生，並透過 advection 與 turbulent transport 重新分布。整體而言，ADM-R1 可提供合理且成本較低之尾流預測，而 ALM-1 則能提供較細緻之近尾流結構。

This study establishes an OpenFOAM-based large-eddy simulation framework to investigate wind turbine wake characteristics under time-varying inflow conditions and to compare the effects of actuator-type wind turbine models and grid resolution on wake prediction. The WALE subgrid-scale model and pimpleFoam solver are adopted for the unsteady incompressible flow simulation. The turbine-induced aerodynamic effects are introduced into the momentum equation through body-force source terms, including ADM-NR, ADM-R, and ALM. All cases use the same time-varying inflow condition and are compared with wind-tunnel experimental data. The wake characteristics are evaluated using the time-averaged streamwise velocity, streamwise turbulence intensity, vertical turbulent momentum flux, and resolved TKE budget terms.
The results show that ADM-R1 provides wake predictions close to the finest ADM-R0 case while achieving a better balance between computational cost and predictive capability. Compared with ADM-NR, ADM-R1 improves the near-wake prediction by considering non-uniform radial loading and rotor-induced rotation. The ALM results indicate that the nacelle and tower source terms mainly affect the near-wake region around the hub and lower wake, while reducing grid resolution smooths the turbulence-related distributions. The resolved TKE budget analysis shows that wake turbulence is mainly generated by shear production in the wake shear layer and redistributed by advection and turbulent transport. Overall, ADM-R1 provides reasonable wake predictions with lower computational cost, whereas ALM-1 gives a more detailed near-wake structure.

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