Abstract
Grid remapping is an important mechanism for data transfer between different grids in the Earth modeling system, and searching for relevant points is one of the most complex and time-consuming operations. At present, there are few efficient and robust searching algorithms for unstructured grids. However, with the rise of unstructured grid based model and the improvement of model resolution, providing an efficient search algorithm for unstructured grid is in urgent need in engineering practice. In order to improve the performance of searching process between unstructured grid and other grids when remapping, this paper implements two search algorithms based on KD (K-dimension) tree (the nearest neighbor search and range search). Compared with the performance of brute force search, it is found that the efficiency of search algorithms based on KD tree are much higher than that of brute force search, including the nearest neighbor search and range search. The experimental results provide practical experience for the development of remapping software in the future.
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