Technical Papers
Apr 4, 2024

Ductile Fracture Prediction Framework of Low Yield Point Steel LYP225 under Monotonic Loading: Experiment and Simulation

Publication: Journal of Structural Engineering
Volume 150, Issue 6

Abstract

Low yield point (LYP) structural steels had been developed and used for the seismic energy dissipating, however, the fracture of various LYP steel energy dissipation components may lead to progressive collapse of structures. To address this issue, the fracture behavior of LYP steels under various stress states were comprehensively investigated using experiments, theoretical analysis, and numerical simulations in this work. There are three meaningful contribution points. First, an improved weighted average (WA) method and dichotomy-based optimization are proposed to calibrate true stress–strain relation after necking onset. The maximum deviation for the prediction of full-range tensile load-displacement behavior based on the proposed WA method is less than 3%, which is better than the existing WA methods. Second, a modified ductile fracture model is developed to identify the fracture of LYP steels under various stress states. Comparison results among existing fracture models, the proposed fracture model and tests indicate that the fracture plastic strain can be more reasonably predicted by the proposed ductile fracture model than the existing models. Thirdly, an advanced ductile fracture prediction framework is proposed to simulate the complete tensile behavior of structural steels. Based on the proposed framework and object-oriented programming technique, the complete tensile behavior can be accurately and conveniently predicted by employing the proposed WA model, proposed ductile fracture model and developed user defined material subroutine. The verified WA method and ductile fracture model would contribute to predicting the failure of structural steel members, connections, welds and structures. It is meaningful to prevent casualties and property losses resulting from the subsequent structural progressive collapse.

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Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

The authors express their gratitude for financial support from National Natural Science Foundation of China (52122803 & U23A20662), National Key Research and Development Program of China (2022YFC3005302), Guangxi Science and Technology Major Program (AA23023034 & AA23073017), and Guangxi Science and Technology Base and Talent Project (AA23026011).

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Go to Journal of Structural Engineering
Journal of Structural Engineering
Volume 150Issue 6June 2024

History

Received: Aug 14, 2023
Accepted: Jan 22, 2024
Published online: Apr 4, 2024
Published in print: Jun 1, 2024
Discussion open until: Sep 4, 2024

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Professor, Dept. of Civil Engineering, State Key Laboratory of Coastal and Offshore Engineering and State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian Univ. of Technology, Dalian 116023, China (corresponding author). ORCID: https://orcid.org/0000-0001-7407-8706. Email: [email protected]
Ph.D. Candidate, Dept. of Civil Engineering, State Key Laboratory of Coastal and Offshore Engineering, Dalian Univ. of Technology, Dalian 116023, China. ORCID: https://orcid.org/0000-0001-8663-0879. Email: [email protected]
Ranting Cui [email protected]
Assistant Professor, College of Civil Engineering and Architecture, Guangxi Univ., Nanning 530004, China. Email: [email protected]
Huihui Li, A.M.ASCE [email protected]
Postdoctoral Researcher, College of Civil and Transportation Engineering, Shenzhen Univ., Shenzhen 518060, China. Email: [email protected]
Professor and Member of the Chinese Academy of Engineering, Dept. of Civil Engineering, State Key Laboratory of Coastal and Offshore Engineering, Dalian Univ. of Technology, Dalian 116023, China. Email: [email protected]

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