Experiment research on rate-dependent constitutive model of Q420 steel

Chen, Junling; Li, Jinwei; Li, Zhexu

doi:10.1016/j.conbuildmat.2017.07.064

Cited by 52 publications

(24 citation statements)

References 16 publications

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“…The C-S model has been employed to simulate the dynamic response of different steels, as listed in Table 3 [12][13][14]17,30]. There exists significant difference in the characteristic parameters D and p, in particular, a vast gap can be found between the D values of different steels.…”

Section: Factors On Dynamic Deformationmentioning

confidence: 99%

“…Since steel structure is very sensitive to the change of strain rate, diverse models have been established to predict the dynamic deformation behavior of structural steels [11][12][13][14][15]. The Johnson-Cook (J-C) model defines the constitutive relation of the effective yield stress with strain, strain rate and temperature [11].…”

Section: Introductionmentioning

confidence: 99%

“…The Johnson-Cook (J-C) model defines the constitutive relation of the effective yield stress with strain, strain rate and temperature [11]. In order to obtain an accurate rate-prediction model, Chen et al [12,13] studied the mechanical behavior of Q420 and Q345 steels with strain rates from 0.001 s −1 to 288 s −1 and 0.001 s −1 to 330 s −1 , respectively. Compared with the J-C models, a modified Hollomon-Voce model is proposed to predict the ratedependent response.…”

Section: Introductionmentioning

confidence: 99%

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Effect of Material Anisotropy on the Mechanical Response of Automotive Steel under High Strain Rates

et al. 2022

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A constitutive model for automobile steel with high elongation needs to be established to predict the dynamic deformation behavior under hydroforming applications. In order to clarify the confusing discrepancy in the essential parameters of the classical Cowper-Symonds (C-S) model, a series of automobile structural steels have been employed to investigate the strain rate response by conducting tensile dynamic deformation. Metallographic microscopy and orientation distribution functions were used to characterize the microstructure and texture components of the steels. The microstructure observation discloses that the matrix of all steels is mainly of ferrite and the texture constituent provides a framework for steel to withstand external deformation. The C-S model can be applied to simulate the dynamic deformation with satisfied expectations. It is concluded that the essential parameters D and p in the model show a specific relationship with the steel grade, and the parameter D is proportional to the steel grade and related to material anisotropy, while the parameter p is inversely proportional to the steel grade and has close links with the grain boundary characteristics.

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Section: Factors On Dynamic Deformationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Effect of Material Anisotropy on the Mechanical Response of Automotive Steel under High Strain Rates

et al. 2022

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“…11) was obtained by linear fitting, as shownFigure 9.Figure 8shows the comparison between test curves and the modified Mander model with different P. It can be seen that the curves derived from the model with a constant P = 2.67 have acceptable accuracy. Taking P as a constant makes the expression of the Mander model simple, but taking P as a variable expressed as Equation(11)makes the model have a better agreement with the test results.…”

mentioning

confidence: 98%

“…The proposed constitutive model can provide better prediction accuracy for yield stress than the Johnson-Cook model.It has been proved experimentally that steel is significantly sensitive to the strain rate induced by dynamic loads [6][7][8]. Furthermore, it is possible for engineering structures to be exposed to extreme dynamic loads during their service life, such as vehicle or vessel collision, gas or bomb explosion [9], and progressive collapse [10][11][12]. Therefore, understanding the strain rate behavior and obtaining the rate-dependent constitutive model of reinforcing bar are of significance for the design and performance evaluation of RC structures under such extreme dynamic loads.…”

mentioning

confidence: 99%

Dynamic Tensile Behavior of Steel HRB500E Reinforcing Bar at Low, Medium, and High Strain Rates

et al. 2020

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The strain rate effect of engineering materials should be considered in the assessment of the performance of reinforced concrete (RC) structures under extreme dynamic loads such as blast and impact. However, the strain rate behavior of 500 MPa-grade anti-earthquake hot-rolled high-strength ribbed bar (HRB500E), used in critical RC members to improve the anti-earthquake performance, has not been investigated and reported in the open literature. That restricts its application in RC structures subjected to extreme dynamic loads. In this paper, dynamic tensile tests of HRB500E steel were conducted using an electromechanical universal testing machine and a servo-hydraulic high-speed testing machine. The stress–strain curves at strain rates ranging from 0.00025 to 550 s−1 were obtained where HRB500E steel was found significantly sensitive to strain rate. Existing formulations to evaluate the dynamic increase factor for yield stress (DIFy) are found to be not suitable for HRB500E steel, thus the widely used Cowper–Symonds and Malvar models for predicting the DIFy were modified based on the test results. Furthermore, the parameter of the Mander material model for describing engineering stress–strain relationship was also calibrated. Finally, the Johnson-Cook and proposed constitutive models for the true stress–strain relationship were examined. The proposed constitutive model can provide better prediction accuracy for yield stress than the Johnson-Cook model.

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Performance Prediction of Thin-Walled Tube Energy Absorbers Using Machine Learning

Ghasemi

Silani

Yaghoubi

et al. 2022

Lecture Notes in Networks and Systems

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Experiment research on rate-dependent constitutive model of Q420 steel

Cited by 52 publications

References 16 publications

Effect of Material Anisotropy on the Mechanical Response of Automotive Steel under High Strain Rates

Effect of Material Anisotropy on the Mechanical Response of Automotive Steel under High Strain Rates

Dynamic Tensile Behavior of Steel HRB500E Reinforcing Bar at Low, Medium, and High Strain Rates

Performance Prediction of Thin-Walled Tube Energy Absorbers Using Machine Learning

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