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Glass Formation of n-Butanol: Coarse-grained Molecular Dynamics Simulations Using Gay-Berne Potential Model
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作者 Gui-long Xie Yong-hong Zhang shi-ping huang 《Chinese Journal of Chemical Physics》 SCIE CAS CSCD 2012年第2期177-185,I0003,共10页
Using coarse-grained molecular dynamics simulations based on Gay-Berne potential model, we have simulated the cooling process of liquid n-butanol. A new set of GB parameters are obtained by fitting the results of dens... Using coarse-grained molecular dynamics simulations based on Gay-Berne potential model, we have simulated the cooling process of liquid n-butanol. A new set of GB parameters are obtained by fitting the results of density functional theory calculations. The simulations are carried out in the range of 290-50 K with temperature decrements of 10 K. The cooling characteristics are determined on the basis of the variations of the density, the potential energy and orientational order parameter with temperature, whose slopes all show discontinuity. Both the radial distribution function curves and the second-rank orientational correlation function curves exhibit splitting in the second peak. Using the discontinuous change of these thermodynamic and structure properties, we obtain the glass transition at an estimate of temperature Tg=1204.10 K, which is in good agreement with experimental results 1104-1 K. 展开更多
关键词 Gay-Berne potential Coarse-grainedmolecular dynamics simulations Glass formation
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Identification of ductile fracture model parameters for three ASTM structural steels using particle swarm optimization
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作者 Ya-zhi ZHU shi-ping huang Hao HONG 《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》 SCIE EI CAS CSCD 2022年第6期421-442,共22页
Accurate prediction of ductile fracture requires determining the material properties,including the parameters of the constitutive and ductile fracture model,which represent the true material response.Conventional cali... Accurate prediction of ductile fracture requires determining the material properties,including the parameters of the constitutive and ductile fracture model,which represent the true material response.Conventional calibration of material parameters often relies on a trial-and-error approach,in which the parameters are manually adjusted until the corresponding finite element model results in a response matching the experimental global response.The parameter estimates are often subjective.To address this issue,in this paper we treat the identification of material parameters as an optimization problem and introduce the particle swarm optimization(PSO)algorithm as the optimization approach.We provide material parameters of two uncoupled ductile fracture models—the Rice and Tracey void growth model(RT-VGM)and the micro-mechanical void growth model(MM-VGM),and a coupled model—the gurson-Tvergaard-Needleman(GTN)model for ASTM A36,A572 Gr.50,and A992 structural steels using an automated PSO method.By minimizing the difference between the experimental results and finite element simulations of the load-displacement curves for a set of tests of circumferentially notched tensile(CNT)bars,the calibration procedure automatically determines the parameters of the strain hardening law as well as the uncoupled models and the coupled GTN constitutive model.Validation studies show accurate prediction of the load-displacement response and ductile fracture initiation in V-notch specimens,and confirm the PSO algorithm as an effective and robust algorithm for seeking ductile fracture model parameters.PSO has excellent potential for identifying other fracture models(e.g.,shear modified GTN)with many parameters that can give rise to more accurate predictions of ductile fracture.Limitations of the PSO algorithm and the current calibrated ductile fracture models are also discussed in this paper. 展开更多
关键词 Parameter calibration Void growth model(VGM) Gurson-Tvergaard-Needleman(GTN)model A36 steel A572 Gr.50 steel A992 steel Particle swarm optimization(PSO)
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