「力の流れ」に着目した力学的感性の検討

抄録

The capability to make unconscious and intuitive judgments for the mechanics aspect of an object is called Mechanical Kansei, and there are attempts to elucidate how this capability is utilized in the realization of structural rationality within the design process. In this study, we focus on the fact that there are many descriptions of the internal force-flow within the structure in explanations of functional beauty and design education; and assume that the ability to intuitively recall the flows without mechanical analysis is based on Mechanical Kansei. We try to reproduce that intuitive process by training a deep learning network model that can generate mechanical loading patterns, e.g. equivalent stress, principal stress, and signed Tresca stress, inside the structure under various conditions without a mechanical model. The obtained network model implies a mapping from structural conditions to the mechanical loading patterns and could help to understand the Mechanical Kansei.