基于图像处理思想的激波捕捉自适应网格方法

Adaptive grid method for shock capturing based on image processing technique

为了平衡激波的捕捉精度和流场计算效率之间的关系,提出基于图像处理思想的激波捕捉自适应网格方法.将流场计算网格与图像像素类比,以较粗的网格覆盖流场全域,在需要较高分辨率的激波区域将网格进行细分;将算法嵌入到流场求解器中,根据流场求解结果自适应地增加网格密度,反复迭代该过程,直至达到所需的网格分辨率.以某型飞机超音速流动为例,对算法进行验证.结果表明,采用该方法能够有效地捕捉到激波附近的流场信息并在激波区域进行加密,提高了激波的辨识度;在加密区和稀疏区之间的过渡区域,该方法生成的网格更光滑,过渡更平缓,能够有效避免畸形区域的产生.

A new grid adaptive method for shock capturing based on the idea of image processing was proposed in order to balance the relationship between the capturing precision and the computational efficiency of the flow field.An analogy was made between the grid of flow field and the image pixels.The whole flow field was covered by coarse grid and the area where shock occurs will be further subdivided.The division process was embedded into the flow solver,whose computational results helped to adaptively increase the grid density.The above process was repeated until a desired resolution was reached.The proposed method was verified by an example of a certain aircraft.The experimental results show that the proposed method can effectively capture the information of the flow field near the shock and increase its grid density,thus improve the recognition degree of the shock.The grid generated by the proposed method turns out to be smoother in the transition region between the density region and the sparse region,so that the deformed region can be effectively avoided.