journal article·2025Open access

Calibration of Elastic-Plastic Degradation Model for 40Cr Steel Applied in Finite Element Simulation of Shear Pins of Friction Pendulum Bearings

Mianyue Yang, Huasheng Sun, Weigao Sheng

Computers, Materials & Continua· Volume 85· Issue 2

Abstract

The shear pin of the friction pendulum bearing (FPB) can be made of 40Cr steel. In conceptual design, the optimal cut-off point of the shear pin is predetermined, guiding the design of bridges isolated by FPBs to maximize their isolation performance. Current researches on the shear pins are mainly based on linear elastic models, neglecting their plasticity, damage, and fracture mechanical properties. To accurately predict its cutoff behavior, the elastic-plastic degradation model of 40Cr steel is indeed calibrated. For this purpose, the Ramberg-Osgood model, the Bao-Wierzbicki damage initiation criterion, and the linear damage evolution criterion were selected to develop the elastic-plastic degradation model of 40Cr. Subsequently, parameter calibration of this model was performed through uniaxial tensile tests on two sets of six smooth, round bars with different diameters. Following this, finite element simulations were conducted for the pure shear test of grade 10.9 high-strength bolts made of 40Cr steel, aiming to verify the elastic-plastic degradation model. The results showed that the failure modes and force-displacement curves simulated by the finite element method were in good agreement with the test results. Moreover, the error between the primary characteristic parameters (initial stiffness, peak load, fracture displacement, and absorbed energy) obtained by finite element calculation and the test values was within 15%. These results demonstrated that the calibration elastic-plastic degradation model of 40Cr steel can predict the cutoff of the shear pin.
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Research context

OpenAlex topics: Metal Alloys Wear and Properties · Gear and Bearing Dynamics Analysis · Tribology and Lubrication Engineering

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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