使用高速圖形計算核心的自適應網格精緻化的流體模擬

Abstract

自適應網格精緻化是一個當計算誤差變大時，將網格切得更細密以達到更高精確度的一個模擬方法。本論文發展一個使用高速圖形計算核心的自適應網格精緻化的模擬，提供可達一般自適應網格流體模擬的十倍效能。

Adaptive Mesh Refinement is an idea of saving computing resources. In many cases the most important flow features occupy only a small region in the computation domain. AMR will recursively refine grids when errors grow and remove the fine grids where the coarser grids still give an enough accuracy. In my thesis, I present a fluid simulation program using the graphic processing units which are much powerful than the central processing unit in common personal computers. The program offers ten times computing efficiency than general fluid simulations before.