STUDY ON IMMEDIATE EVALUATION METHOD OF RESTORING FORCE CHARACTERISTICS BY DEEP LEARNING WHEN BASE-ISOLATED BUILDING COLLIDES WITH RETAINING WALL

Abstract

It has been pointed out that a seismic isolation structure may collide with a retaining wall when a larger earthquake motion than assumed in the design is input. In order to simulate the behavior of the whole seismic isolation system when a seismic isolation structure collides with a retaining wall, it is necessary to model the restoring force characteristics of the retaining wall with the collision. However, for that purpose, nonlinear analysis by full scale experiment and precise three-dimensional FEM is required, and the modeling is not easy at all. Therefore, this paper proposes an evaluation method which can immediately calculate the restoring force characteristics of a retaining wall in a base isolation layer, which is necessary for analysis in the case of a retaining wall collision, from design parameters by using a machine learning prior learning model. In this paper, we first explain the proposed method, and then construct a pre-learning model according to the proposed method. Finally, this paper compares the restoring force characteristics obtained by the prior learning model and the restoring force characteristics made using the result of the three-dimensional FEM model, and shows the applicability of this proposed method.