This study assesses different turbulence modeling approaches for simulation of two-phase coaxial annular swirling jet flows. The problem selected from literature for comparison involves an analytical inlet profile for an annular liquid sheet sandwiched between two coaxial annular gaseous jets. The liquid-gas interface is resolved using the volume-of-fluid model with continuum surface force approximation. Reynolds averaged Navier-Stokes simulations and detached eddy simulations (DES) are conducted to obtain transient multiphase numerical solutions. Different turbulence models explored include the k-ε RNG with swirl modification, the Reynolds stress model (RSM), RSM with scale adaptive simulations (RSM-SAS), and DES. Comparisons with the direct numerical results from literature suggest that the k-ε RNG and RSM approaches simulate only the streamwise shear of the liquid jet and are inadequate in capturing the swirling aspect of the jet flow and expected instabilities. DES can predict several expected features such as radial asymmetry, surrounding gas vortices causing jet instabilities, and eventual jet breakup with reasonable accuracy. While RSM-SAS predicts radial asymmetry, some jet instability, and is much more accurate than k-ε RNG and RSM, it fails to predict instabilities as good as DES and does not predict a complete jet breakup. RSM models are found to be computationally very expensive compared to the k-ε RNG models, suggesting DES as the better alternative than RSM-based methods for such applications if resources are available.

中文翻译：

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同轴旋转液气射流中初级雾化的 DES 和 RANS 建模

本研究评估了用于模拟两相同轴环形旋转射流的不同湍流建模方法。从文献中选择用于比较的问题涉及夹在两个同轴环形气体射流之间的环形液体层的分析入口剖面。使用具有连续表面力近似的流体体积模型解析液-气界面。进行雷诺平均纳维-斯托克斯模拟和分离涡模拟 (DES) 以获得瞬态多相数值解。探索的不同湍流模型包括带有涡流修改的 k-ε RNG、雷诺应力模型 (RSM)、带有尺度自适应模拟的 RSM (RSM-SAS) 和 DES。与文献中直接数值结果的比较表明，k-ε RNG 和 RSM 方法仅模拟液体射流的流向剪切，不足以捕捉射流的涡流方面和预期的不稳定性。DES 可以合理准确地预测几个预期的特征，例如径向不对称、导致射流不稳定的周围气体涡流以及最终的射流破裂。虽然 RSM-SAS 预测径向不对称、一些射流不稳定性，并且比 k-ε RNG 和 RSM 准确得多，但它无法像 DES 那样准确地预测不稳定性，也不能预测射流完全破裂。与 k-ε RNG 模型相比，RSM 模型被发现在计算上非常昂贵，这表明如果资源可用，对于此类应用程序，DES 是比基于 RSM 的方法更好的替代方案。