An Animated Visualization Method for Large-Scale Unstructured Unsteady Flow

Abstract

Animation visualization is one of the primary methods for analyzing unsteady flow fields. In this paper, we addressed the issue of data visualization for large-scale unsteady flow fields using animation. Loading and rendering individual time steps sequentially can result in substantial frame delay, whereas loading and rendering all time steps simultaneously can result in excessive memory usage. To address these issues, the proposed method analyzes the variable description information in the data files to bypass redundant variables and read the flow field data as required. Second, a hash table is constructed to derive the two-dimensional surface mesh of the flow field and complex mesh cells are simplified into simple linear cells to reduce the mesh’s complexity. This paper presents a method for reducing the memory usage of complex data sets by more than 90%, compared with the ParaView data reading method. The proposed method is tested on four sets of unstructured unsteady flow field data with different data structures. The animation visualization method based on simplified data can achieve an average frame rate of less than 100ms and supports real-time user interaction on personal computers. It extends the ability of personal computers to analyze large-scale unstructured unsteady flow fields.