This study proposes a generative design method for tire tread patterns that incorporates latent design intent extracted from patent documents. As various tread patterns satisfy primary performance criteria resulting from different combinations of grooves, generative design is a suitable means for the early design stage. However, designers cannot control the exploration range due to the lack of correlation between geometric characteristics and evaluation criteria. While their correlation is often implicit in practice, certain aspects are described in patent documents to claim their originality. The proposed method aims to extract the correlation between geometric characteristics and evaluation criteria from patent documents and apply them to the generative design of tire tread patterns. Firstly, tread pattern images and their characteristic summaries are constructed from drawings and descriptions in patent documents related to a design problem. Then, the geometric features of the pattern images are extracted using image processing techniques from a reverse engineering perspective. Secondly, categories that share some characteristics are identified through a concept identification approach. Finally, generative design explores promising alternatives under geometric constraints derived from the selected category that satisfies the desired evaluation criteria. This study demonstrates the capability of the proposed method in the design problem of tread patterns for summer passenger car tires.

The stress concentration factor (SCF) of a stepped round bar with fillets is fundamental in machine design and SCF diagrams are included in many textbooks and handbooks on mechanics of materials and machine design. Among them, Peterson's handbook, for example, is continuously used around the world. Noda et al. analyzed such stepped round bar under tension and bending accurately by using the body force method and proposed a calculation formula for the entire range of geometries. However, the above textbooks and handbooks still indicate different stress concentration diagrams throughout. Therefore, in this study, for the entire range of fillet shape dimensions including the range of very small fillet radius, Peterson's results are compared with Noda and Takase's results to clarify the error. As a result, Peterson's stress concentration factor is found to have an error of up to 25% in tension and up to 15% in bending. The errors of stress concentration factors in other books are also discussed.

In order to effectively learn the designer's behavioral style that is summarized and visualized from the previous research about the design process of model Stirling engines and industrial image recording apparatus, an example of a high-power low temperature difference Stirling engine teaching material is presented, showing that the use of a resin multi-hole regenerator manufactured by an FDM 3D printer can produce more than three times the rotational speed and four times the torque compared to the engine without the regenerator. By this example, the design condition of low temperature difference Stirling engine becomes much wider than prior arts and it is possible for students to try their ideas in their designs. The mechanical loss, pressure loss, working fluid temperature during operation, P-V diagram, shaft power, and indicated power are also shown, and they contribute as the basic data to consider improved designs.