An adaptive ghost fluid finite volume method for compressible gas-water simulations
An adaptive ghost fluid finite volume method for compressible gas-water simulations
复制标题
DOI：
10.1016/j.jcp.2008.03.005
复制
发表时间：
2008-06
期刊：
影响因子：
--
通讯作者：
Chun-Wei Wang;Huazhong Tang;Tiegang Liu
中科院分区：
文献类型：
--
作者：
Chun-Wei Wang;Huazhong Tang;Tiegang Liu
本文发展了一种适用于一、二维可压缩多介质流动的自适应鬼流体有限体积法。它耦合了真实的鬼流体方法（GFM）[C.W. Wang，T.G.刘炳昌，多介质可压缩流场模拟的真实的-虚拟流体方法，上海工业大学学报。Comput. 28（2006）278 - 302]和自适应移动网格方法[H. Z.唐氏T.唐一维和二维双曲守恒律的移动网格方法，SIAM J。Numer。anal. 41（2003）487 - 515; H.Z.唐氏T. Tang，P.W. Zhang，二维和三维非线性Hamilton-Jacobi方程的自适应网格重分布方法，J. Comput. Phys.188（2003）543 - 572]，并因此结合了它们的优点。这项工作表明，在材料界面附近的局部网格聚类可以有效地减少由材料界面周围的GFM和其他不连续性引起的数值和保守误差。自适应GFM不仅提高了流场分辨率，而且大大提高了计算效率。数值实验证明了该方法的有效性和鲁棒性。它们包括几个一维和二维气水流动问题，涉及在材料界面处的大密度梯度和强激波界面相互作用。结果表明，该算法能够准确地捕捉到冲击波和材料界面，并且即使对于大密度和压力梯度的解也是稳定和鲁棒的。
An adaptive ghost fluid finite volume method is developed for one- and two-dimensional compressible multi-medium flows in this work. It couples the real ghost fluid method (GFM) [C.W. Wang, T.G. Liu, B.C. Khoo, A real-ghost fluid method for the simulation of multi-medium compressible flow, SIAM J. Sci. Comput. 28 (2006) 278–302] and the adaptive moving mesh method [H.Z. Tang, T. Tang. Moving mesh methods for one- and two-dimensional hyperbolic conservation laws, SIAM J. Numer. Anal. 41 (2003) 487–515; H.Z. Tang, T. Tang, P.W. Zhang, An adaptive mesh redistribution method for non-linear Hamilton–Jacobi equations in two- and three-dimensions, J. Comput. Phys. 188 (2003) 543–572], and thus combines their advantages. This work shows that the local mesh clustering in the vicinity of the material interface can effectively reduce both numerical and conservative errors caused by the GFM around the material interface and other discontinuities. Besides the improvement of flow field resolution, the adaptive GFM also largely increases the computational efficiency. Several numerical experiments are conducted to demonstrate robustness and efficiency of the current method. They include several 1D and 2D gas–water flow problems, involving a large density gradient at the material interface and strong shock-interface interactions. The results show that our algorithm can capture the shock waves and the material interface accurately, and is stable and robust even for solutions with large density and pressure gradients.