Guiyong Zhang
Dalian University of Technology
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Publication
Featured researches published by Guiyong Zhang.
International Journal of Computational Methods | 2015
Guiyong Zhang; Y. Li; X. X. Gao; Da Hui; S. Q. Wang; Zhi Zong
This work formulates the node-based smoothed radial point interpolation method (NS-RPIM), a typical model of smoothed point interpolation method, for the elastoplastic analysis of two-dimensional solids with gradient-dependent plasticity. The NS-RPIM uses radial point interpolation shape functions for field approximation and node-based gradient smoothing for strain field construction. The formulation is based on the parametric variational principle (PVP) in the form of complementarity with the gradient-dependent plasticity being represented by means of the linearization of the yield criterion and the flow rule. Numerical study results have demonstrated the accuracy and stability of the proposed approach for elastoplastic analysis.
Numerical Heat Transfer Part B-fundamentals | 2018
Da Hui; Guiyong Zhang; D. P. Yu; Zhe Sun; Zhi Zong
Abstract Based on the newly developed gradient smoothing method (GSM), three interface-capturing schemes have been implementing using unstructured mesh. The volume of fluid (VOF) model is solved without explicitly interface reconstructing in the framework of GSM. The variables on upwind points are successfully approximated using centroid GSM (cGSM) scheme, which generally cannot be clearly defined on unstructured mesh. Compressive interface-capturing scheme for arbitrary meshes (CICSAM), flux-blending interface-capturing scheme (FBICS), and cubic upwind interpolation-based blending scheme (CUIBS) have been employed through three benchmark cases. The results indicate that FBICS and CUIBS can produce more accurate predictions using unstructured meshes.
International Journal of Computational Methods | 2018
Guiyong Zhang; Yaomei Wang; Yong Jiang; Yichen Jiang; Zhi Zong
The singular cell-based smoothed radial point interpolation method (CS-RPIM) has been previously proposed and shown good performance in solving fracture problems. Motivated from the fact that CS-RPIM performs over softly by providing an upper bound solution and the finite element method (FEM) is overly stiff by providing a lower bound solution, this work proposes a combination of singular CS-RPIM and FEM with a correlation coefficient α, and α = 0.97 has been recommended through intensive numerical studies. Several numerical examples have been studied and the proposed method has been found perform quite well from both stress intensity factors and strain energy.
International Journal of Numerical Methods for Heat & Fluid Flow | 2017
Yijun Liu; Guiyong Zhang; Huan Lu; Zhi Zong
Purpose n n n n nDue to the strong reliance on element quality, there exist some inherent shortcomings of the traditional finite element method (FEM). The model of FEM behaves overly stiff, and the solutions of automated generated linear elements are generally of poor accuracy about especially gradient results. The proposed cell-based smoothed point interpolation method (CS-PIM) aims to improve the results accuracy of the thermoelastic problems via properly softening the overly-stiff stiffness. n n n n nDesign/methodology/approach n n n n nThis novel approach is based on the newly developed G space and weakened weak (w2) formulation, and of which shape functions are created using the point interpolation method and the cell-based gradient smoothing operation is conducted based on the linear triangular background cells. n n n n nFindings n n n n nOwing to the property of softened stiffness, the present method can generally achieve better accuracy and higher convergence results (especially for the temperature gradient and thermal stress solutions) than the FEM does by using the simplest linear triangular background cells, which has been examined by extensive numerical studies. n n n n nPractical implications n n n n nThe CS-PIM is capable of producing more accurate results of temperature gradients as well as thermal stresses with the automated generated and unstructured background cells, which make it a better candidate for solving practical thermoelastic problems. n n n n nOriginality/value n n n n nIt is the first time that the novel CS-PIM was further developed for solving thermoelastic problems, which shows its tremendous potential for practical implications.
ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering | 2017
Yaomei Wang; Biye Yang; Guiyong Zhang; Yichen Jiang; Zhi Zong
The process of ice-structure interaction is a complex problem which is influenced by the properties of both ice and the structure. In this paper, the material point method (MPM) is introduced to simulate the interaction between an ice sheet and a cylinder structure. MPM is efficient in solving history dependent and large deformation problems and has shown advantage in hyper-velocity impact and landslide issues, etc..The constitutive relation of ice is based on elasto-viscous-plastic model with the Drucker-Pragers yield criterion. Ice follows the Maxwell elasto-viscous model before the yield criterion is reached and fails when the plastic strain surpasses the failure strain. Meanwhile, the constitutive model used in this work considers the effect of the Young’s modulus, Poisson’s ratio, density, temperature, cohesive force and internal friction angle of ice.A series of simulations are conducted and the results are in accord with existing theories. According to the comparison, the influences of ice temperature and penetration speed of the structure on the global ice load are testified. The numerical tests have proven the feasibility of MPM in simulating the interaction between an ice sheet and a cylinder structure. Future work in ice-structure interaction problems with MPM is also discussed.Copyright
Engineering Analysis With Boundary Elements | 2018
Guiyong Zhang; Huan Lu; Dapeng Yu; Zhenming Bao; Haiying Wang
Ocean Engineering | 2018
Guiyong Zhang; Shuangqiang Wang; Huan Lu; Zhiqian Zhang; Zhi Zong
International Journal of Computational Methods | 2018
Guiyong Zhang; Da Hui; Da Li; Li Zou; Shengchao Jiang; Zhi Zong
International Journal of Computational Methods | 2018
Biye Yang; Guiyong Zhang; Zhigang Huang; Zhe Sun; Zhi Zong
International Journal of Computational Methods | 2018
Tiezhi Sun; Zhi Zong; Ying-jie Wei; Guiyong Zhang