The demand for high-strength steel is rising due to its economic efficiency. Low-cycle fatigue (LCF) tests have been conducted to investigate the nonlinear behaviors of high-strength steel. Accurate material models must be used to obtain reliable results on seismic performance evaluation using numerical analyses. This study uses the combined hardening model to simulate the LCF behavior of high-strength steel. However, it is challenging and complex to determine material model parameters for specific high-strength steel because a highly nonlinear equation is used in the model, and several parameters need to be resolved. This study used the particle swarm algorithm (PSO) to determine the model parameters based on the LCF test data of HSA 650 steel. It is shown that the model with parameter values selected from the PSO accurately simulates the measured LCF curves.

1. 서 론
2. 재료실험
    2.1 단순 인장 시험 (Monotonic tensile test)
    2.2 저주기 피로 실험 (Low-cycle fatigue test)
3. 재료모델
    3.1 등방 경화 모델 (Isotropic hardening model)
    3.2 이동 경화 모델 (Kinematic hardening model)
    3.3 복합경화 모델 (Combined hardening model)
4. 재료상수 결정
    4.1 입자 군집 최적화 (Particle Swarm Optimization, PSO)
    4.2 재료상수 결정
5. 결 론
감사의 글

• 조은선(한양대학교 건축공학과 대학원생) | Cho EunSeon (Graduate Student, Department of Architectural Engineering, Hanyang University)
• 조진우(한양대학교 건축공학과 대학원생) | Cho Jin Woo (Graduate Student, Department of Architectural Engineering, Hanyang University)
• 한상환(한양대학교 건축공학과 교수) | Han Sang Whan (Professor, Department of Architectural Engineering, Hanyang University) Corresponding author