EXPERIMENTAL AND ANALYTICAL STUDY ON ULTIMATE PROPERTY OF RUBBER BEARINGS (PART 5): PREDICTION OF BUCKLING PROPERTY OF NATURAL RUBBER BEARINGS WITH FLARE-LIKE STRUCTURE BASED ON SURROGATE MODEL USING MACHINE LEARNING

In the previous study, the author proposed a new flare-like structure with the aim of improving buckling property, and evaluated the ultimate properties of a high-damping rubber bearing with the proposed structure. In the case of a flare-like structure, the structure is more complex than conventional structures, resulting in more design parameters. In recent years, machine learning has drawn attention as a method for predicting the characteristics of products with many parameters. In this study, a method for predicting the buckling property of natural rubber bearings using machine learning is proposed.