In a pretensioned concrete member, the effective prestress is not fully developed in a certain length from the end of the member, which is defined as transfer length. Because of its complex mechanism, previous transfer length models are mostly empirical and provide very different results. In this study, the Adaptive Neuro-Fuzzy Inference System(ANFIS) was introduced to estimate the transfer lengths of pretensioned concrete members. A total of 209 experimental data has been used to train ANFIS, and the trained ANFIS algorithm estimated the transfer lengths of test specimens very accurately.

• 김민수(서울시립대학교 건축학부, 석사과정) | Kim, Minsu
• 한선진(서울시립대학교 건축학부, 박사과정) | Han, Sun-Jin
• 이은지(서울시립대학교 건축학부, 석사과정) | Lee, Eun-Ji
• 함경원(한국전력공사 전력연구원, 차장) | Hahm, Kyung Won
• 김강수(서울시립대학교 건축학부, 교수) | Kim, Kang Su