Many school buildings are vulnerable to earthquakes because they were built before mandatory seismic design was applied. This study uses machine learning to develop an algorithm that rapidly constructs an optimal reinforcement scheme with simple information for non-ductile reinforced concrete school buildings built according to standard design drawings in the 1980s. We utilize a decision tree (DT) model that can conservatively predict the failure type of reinforced concrete columns through machine learning that rapidly determines the failure type of reinforced concrete columns with simple information, and through this, a methodology is developed to construct an optimal reinforcement scheme for the confinement ratio (CR) for ductility enhancement and the stiffness ratio (SR) for stiffness enhancement. By examining the failure types of columns according to changes in confinement ratio and stiffness ratio, we propose a retrofit scheme for school buildings with masonry walls and present the maximum applicable stiffness ratio and the allowable range of stiffness ratio increase for the minimum and maximum values of confinement ratio. This retrofit scheme construction methodology allows for faster construction than existing analysis methods.

Existing reinforced concrete buildings with seismically deficient details have premature failure under earthquake loads. The fiber-reinforced polymer column jacket enhances the lateral resisting capacities with additional confining pressures. This paper aims to quantify the retrofit effect varying the confinement and stiffness-related parameters under three earthquake scenarios and establish the retrofit strategy. The retrofit effects were estimated by comparing energy demands between non-retrofitted and retrofitted conditions. The retrofit design parameters are determined considering seismic hazard levels to maximize the retrofit effects. The critical parameters of the retrofit system were determined by the confinement-related parameters at moderate and high seismic levels and the stiffness-related parameters at low seismic levels.