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基于全局响应面算法的Q235B钢的Johnson-Cook模型参数最优
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作者 苏绍娟 武玉杰 +4 位作者 王国回 苗哲 熊野萍 郭方昕 刘海波 《哈尔滨工程大学学报(英文版)》 CSCD 2024年第2期470-478,共9页
This study investigates the mechanical properties of Q235B steel through quasi-static tests at both room temperature and elevated temperature.The initial values of the Johnson-Cook model parameters are determined usin... This study investigates the mechanical properties of Q235B steel through quasi-static tests at both room temperature and elevated temperature.The initial values of the Johnson-Cook model parameters are determined using a fitting method.The global response surface algorithm is employed to optimize and calibrate the Johnson-Cook model parameters for Q235B steel under both room temperature and elevated temperature conditions.A simulation model is established at room temperature,and the simulated mechanical performance curves for displacement and stress are monitored.Multiple optimization algorithms are applied to optimize and calibrate the model parameters at room temperature.The global response surface algorithm is identified as the most suitable algorithm for this optimization problem.Sensitivity analysis is conducted to explore the impact of model parameters on the objective function.The analysis indicates that the optimized material model better fits the experimental values,aligning more closely with the actual test results of material strain mechanisms over a wide temperature range. 展开更多
关键词 Q235B mechanical property test Numerical simulation Johnson cook model Global response surface algorithm
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Fast determination of meso-level mechanical parameters of PFC models 被引量:4
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作者 Guo Jianwei Xu Guoan +1 位作者 Jing Hongwen Kuang Tiejun 《International Journal of Mining Science and Technology》 SCIE EI 2013年第1期157-162,共6页
To solve the problems of blindness and inefficiency existing in the determination of meso-level mechanical parameters of particle flow code (PFC) models, we firstly designed and numerically carried out orthogonal test... To solve the problems of blindness and inefficiency existing in the determination of meso-level mechanical parameters of particle flow code (PFC) models, we firstly designed and numerically carried out orthogonal tests on rock samples to investigate the correlations between macro-and meso-level mechanical parameters of rock-like bonded granular materials. Then based on the artificial intelligent technology, the intelligent prediction systems for nine meso-level mechanical parameters of PFC models were obtained by creating, training and testing the prediction models with the set of data got from the orthogonal tests. Lastly the prediction systems were used to predict the meso-level mechanical parameters of one kind of sandy mudstone, and according to the predicted results the macroscopic properties of the rock were obtained by numerical tests. The maximum relative error between the numerical test results and real rock properties is 3.28% which satisfies the precision requirement in engineering. It shows that this paper provides a fast and accurate method for the determination of meso-level mechanical parameters of PFC models. 展开更多
关键词 Particle flow code Meso-level mechanical parameter Macroscopic property Orthogonal test Intelligent prediction
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Combination form analysis and experimental study of mechanical properties on steel sheet glass fiber reinforced polymer composite bar 被引量:1
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作者 Chao WU Xiongjun HE +2 位作者 Li HE Jing ZHANG Jiang WANG 《Frontiers of Structural and Civil Engineering》 SCIE EI CSCD 2021年第4期834-850,共17页
The concept of steel sheet glass fiber reinforced polymer(GFRP)composite bar(SSGCB)was put forward.An optimization plan was proposed in the combined form of SSGCB.The composite principle,material selection,and SSGCB p... The concept of steel sheet glass fiber reinforced polymer(GFRP)composite bar(SSGCB)was put forward.An optimization plan was proposed in the combined form of SSGCB.The composite principle,material selection,and SSGCB preparation technology have been described in detail.Three-dimensional finite element analysis was adopted to perform the combination form optimization of different steel core structures and different steel core contents based on the mechanical properties.Mechanical tests such as uniaxial tensile,shear,and compressive tests were carried out on SSGCB.Parametric analysis was conducted to investigate the influence of steel content on the mechanical properties of SSGCB.The results revealed that the elastic modulus of SSGCB had improvements and increased with the rise of steel content.Shear strength was also increased with the addition of steel content.Furthermore,the yield state of SSGCB was similar to the steel bar,both of which indicated a multi-stage yield phenomenon.The compressive strength of SSGCB was lower than that of GFRP bars and increased with the increase of the steel core content.Stress-strain curves of SSGCB demonstrated that the nonlinear-stage characteristics of SSGCB-8 were much more obvious than other bars. 展开更多
关键词 steel sheet GFRP composite bar combination form numerical modeling mechanical properties test strength
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