AWSD: An Aircraft Wing Dataset Created by an Automatic Workflow for Data Mining in Geometric Processing

Abstract

This paper introduces an aircraft wing simulation data set (AWSD) created by an automatic workflow based on creating models, meshing, simulating the wing flight flow field solution, and parameterizing solution results. AWSD is a flexible, independent wing collection of simulations with specific engineering requirements. The data set is applicable to handle computer geometry processing tasks. In contrast to the existing 3D model data set, there are some advantages the scale of this data set is not limited by the collection source, the data files have high quality, no defects, redundancy, and other problems, and the models and simulation are all designed for the specific actual engineering demand. Moreover, AWSD has the characteristics of rich information and a similar model structure, which contributes to the construction of the surrogate model. On the other hand, this data set is suitable for advancing research of data mining in computational geometry graphics. To solve the problem that the CFD flows field results are not intuitive, this paper used the resampling method of surface data to sample the result to the model surface, then segmented the re-sampled 3D mesh surface, and compared with the differences among K-means algorithm, Mini-Batch K-means algorithm, and Spectral Clustering algorithm. AWSD provides 300 sets of models, meshes, CFD simulation results, and parametric results based on ARAP (As-Rigid-As-Possible) and Harmonic mapping for advancing the construction of engineering surrogate models, 3D mesh segmentation, surface resampling, and related geometric processing tasks.