Feature Extraction and Seed Point Selection Algorithms of Ocean Flow Field on Unstructured Grids
In the context of unstructured grid flow field data,existing research faces challenges such as the inability to precisely locate critical points within the flow field,a lack of fine classification for these points,and insufficient methods for seed point placement on unstructured grids.To address these issues,this study introduces innovative improvements in the extraction of critical points and selection of seed points,specifically tailored to unstructured grid flow field data.Initially,an innovative technique for locating and classifying critical points on unstructured grids is proposed.The Poincare index method is employed to identify triangular grids containing critical points.Following this,a center-of-mass iteration method is developed to accurately locate critical points within these grids.Additionally,a method for constructing a Jacobian matrix in triangular grids is designed for the fine classification of critical points.Subsequently,the study introduces a seed point selection algorithm for unstructured grids,based on a"maximum score"principle and grid density.This involves calculating a score for each grid point by comparing the scalar values of adjacent points,thereby creating a"maximum score"scalar field.A threshold value is then set based on grid density,and grid points exceeding this threshold are selected as seed points.These seed points serve as the starting points for generating streamlines,effectively capturing key features and conveying the global information of the flow field.Finally,a comparative analysis of experimental results from flow field data across several seas is presented.This analysis demonstrates that the accuracy of critical point classification can exceed 99%,validating the precision of the proposed critical point extraction method and the effectiveness of the seed point selection algorithm in enhancing the visualization of flow fields.
unstructured triangular gridcritical point extractionseed point selectionmaximum scoreflow field visualization
国家科技期刊平台
NSTL
万方数据
维普
