Steel and Composite Structures

  • 제42권5호
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  • Pages.657-669
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  • 2022
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  • 1229-9367(pISSN)
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  • 1598-6233(eISSN)
테크노프레스 (Techno-Press)
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DOI QR코드

DOI QR Code

Efficient determination of combined hardening parameters for structural steel materials

  • Han, Sang Whan (Department of Architectural Engineering, Hanyang University) ;
  • Hyun, Jungho (Department of Architectural Engineering, Hanyang University) ;
  • Cho, EunSeon (Department of Architectural Engineering, Hanyang University) ;
  • Lee, Kihak (Department of Architectural Engineering, Sejong University)
  • 투고 : 2020.10.20
  • 심사 : 2022.01.02
  • 발행 : 2022.03.10
⟨ 이전 논문 다음 논문 ⟩

초록

Structural materials can experience large plastic deformation under extreme cyclic loading that is caused by events like earthquakes. To evaluate the seismic safety of a structure, accurate numerical material models should be used. For a steel structure, the cyclic strain hardening behavior of structural steel should be correctly modeled. In this study, a combined hardening model, consisting of one isotropic hardening model and three nonlinear kinematic hardening models, was used. To determine the values of the combined hardening model parameters efficiently and accurately, the improved opposition-based particle swarm optimization (iOPSO) model was adopted. Low-cycle fatigue tests were conducted for three steel grades commonly used in Korea and their modeling parameters were determined using iOPSO, which was first developed in Korea. To avoid expensive and complex low cycle fatigue (LCF) tests for determining the combined hardening model parameter values for structural steel, empirical equations were proposed for each of the combined hardening model parameters based on the LCF test data of 21 steel grades collected from this study. In these equations, only the properties obtained from the monotonic tensile tests are required as input variables.

키워드

과제정보

It is acknowledged that this research was financially supported by the National Research Foundation of Korea (2020R1A2C2010548).

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