本文主要在探討二維晶格波茲曼法結合大渦模型應用到三種不同的紊流場並提出了有系統與廣泛的研究評估。此三種數值模擬的範例分別為頂蓋驅動流場、背向階梯流場以及紊流噴流衝擊冷卻。紊流統御方程式使用流函數-渦度法配合大渦模型表示之，並使用晶格波茲曼法將統御方程式做離散，採用D2Q5的晶格波茲曼模型模擬速度場及溫度場。首先在前兩個範例，頂蓋驅動流與背向階梯流場的驗證中，與基準的實驗結果相比較之下，發現使用晶格波茲曼法結合大渦模擬，模擬結果是相當可靠與準確的。
最後，將晶格波茲曼法結合大渦模擬實際應用到噴流衝擊流場進行數值模擬與討論。首先對具有兩種熱邊界的紊流衝擊噴流作驗證，等溫邊界(Re=10200,H/W=2.6)與等熱通量邊界(Re=10000,H/W=2)，對於紊流噴流衝擊流場與熱傳的數值預測值與文獻的數據作驗證。另外，對於暫態噴流衝擊亦進行分析，其研究範圍為300<=Re<=1500，2<=H/W<=4，0.5<=q<=1.5，工作流體為空氣(Pr=0.71)。數值結果顯示紐賽數隨著雷諾數的增加而增加，而改變了衝擊高度(H/W)會使得流場提早轉變為紊流，並且對紐賽數的分布有顯著的影響。在整個模擬的結果可以發現，晶格波茲曼法結合大渦模擬，模擬暫態之紊流流場具有相當的準確性，在未來紊流場的模擬應用上是很有前途的。

In this study, systematic and comprehensive research has been proposed to evaluate a two-dimensional Lattice Boltzmann Method (LBM) coupled with a Large Eddy Simulation (LES) model and has been applied to three different turbulent flow type. Three numerical examples, lid driven cavity, backward facing step flow and turbulent jet impingement cooling are employed. Turbulent governing equations using the stream function-vorticity method combined the Large-Eddy Simulation model is solved and discreted with Lattice Boltzmann model. A numerical scheme to solve the flow and the temperature fields using the D2Q5 is presented. In the first two examples, the LBM coupled with LES for predicting the lid driven cavity, and the backward facing step flow have been evaluated by comparing the numerical results with benchmark experimental data. The good agreement indicates the LBM coupled with LES is reliable and accurate.
Finally, a practical application of LBM coupled with LES for jet impingement is simulated and discussed. The validation of the turbulent impinging jet with two thermal boundary, constant temperature boundary (Re=10200,H/W=2.6) and constant flux (Re=10000,H/W=2) are studied first. The numerical predictions of turbulent jet impingement flow and heat transfer have been evaluated by comparing with the available data in the literature. In addition, the analysis of transient jet impingement is carried out for 300<=Re<=1500,2<=H/W<=4,0.5<=q<=1.5 . The fluid considered here is air (Pr=0.71). The results show that Nu increases with increasing jet Reynolds number, while the increase in parameters H/W to advance the time of flow field from the transition to turbulence and has a significant influence on the Nusselt number distribution. The results demonstrate that the present numerical model is a promising tool to investigate the solution of fluid flow and heat transfer for turbulent flow.

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