Extraction and Visualization of Human Experts’ Knowledge in Airplane Design via Mapper

―Design Informatics Approach with Topological Data Analysis―

Abstract

  In this paper, we introduce a novel design-informatics approach to extract and visualize human experts’ knowledge about airplane design. Using the dataset of candidate designs for Silent Super-Sonic Technology Demonstrator (S3TD) developed by Japan Aerospace Exploration Agency (JAXA), we try to extract and visualize the expert’s chosen design among 58 candidates in a systematic manner. Using Mapper, which is one of the representative methods in topological data analysis, we visualize a four-dimensional trade-off relationship as a directed graph. Our method found the expert’s choice as a knee point of the Pareto front, which implies that our approach can systematically select candidate designs that human experts may prefer.