Investigating the microstructural effect on elastic and fracture behavior of polycrystals using a nonlocal lattice particle model

2015 ◽  
Vol 631 ◽  
pp. 173-180 ◽  
Author(s):  
Hailong Chen ◽  
Yang Jiao ◽  
Yongming Liu
2013 ◽  
Vol 372 ◽  
pp. 646-649 ◽  
Author(s):  
Yong Ye ◽  
Liang Kang

The bonded particle model (BPM) of granite for pre-stressed machining is build by using the discrete element method (DEM). This model can not only descript the intergranular fracture behavior but also the transgranular fracture behavior of the granite. The processes of crack propagation under different pre-stressed machining conditions are studied by means of DEM simulation. Damages and cracks of surface/subsurface are also observed. The simulation results show that, while the magnitude of pre-stress is controlled in a certatin range, the number of radial cracks reduce as the increasing of pre-stress magnitude, contray to the transverse cracks. It could be seen that maching damage is decreased and surface quality is improved by applying the pre-stressed machining method, and the discrete element method is an effective way to simulate the machining process of granite.


2020 ◽  
Vol 121 (24) ◽  
pp. 5469-5489
Author(s):  
Haoyang Wei ◽  
Hailong Chen ◽  
Yongming Liu

2014 ◽  
Vol 627 ◽  
pp. 457-460
Author(s):  
Jana Kaděrová ◽  
Jan Eliáš

The paper describes results of numerical simulations of experiments on concrete beams loaded in three-point bending. Stochastic lattice-particle model has been applied in which the material was represented by discrete particles of random size and location. Additional spatial variability of material properties was introduced by stationary autocorrelated random field. Three different types of geometrically similar beams were modeled: half-notched, fifth-notched and unnotched, each in four different sizes. The deterministic and stochastic model parameters were identified via automatic procedure based on comparison to a subset of experimental data, so that the adequacy of the model response could be validated by comparison with the remaining experimental data.


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