Shape design optimization of dynamic crack propagation using peridynamics

Author(s):  
Myunghoon Oh ◽  
Bonyong Koo ◽  
Jae-Hyun Kim ◽  
Seonho Cho
2012 ◽  
Vol 36 (5) ◽  
pp. 651-657 ◽  
Author(s):  
Jun Lei ◽  
Yue-Sheng Wang ◽  
Yifeng Huang ◽  
Qingsheng Yang ◽  
Chuanzeng Zhang

1998 ◽  
Vol 539 ◽  
Author(s):  
T. Cramer ◽  
A. Wanner ◽  
P. Gumbsch

AbstractTensile tests on notched plates of single-crystalline silicon were carried out at high overloads. Cracks were forced to propagate on {110} planes in a <110> direction. The dynamics of the fracture process was measured using the potential drop technique and correlated with the fracture surface morphology. Crack propagation velocity did not exceed a terminal velocity of v = 3800 m/s, which corresponds to 83%7 of the Rayleigh wave velocity vR. Specimens fractured at low stresses exhibited crystallographic cleavage whereas a transition from mirror-like smooth regions to rougher hackle zones was observed in case of the specimens fractured at high stresses. Inspection of the mirror zone at high magnification revealed a deviation of the {110} plane onto {111} crystallographic facets.


PAMM ◽  
2007 ◽  
Vol 7 (1) ◽  
pp. 1090801-1090802
Author(s):  
A.-M. Sändig ◽  
A. Lalegname ◽  
S. Nicaise

Author(s):  
Myung-Jin Choi ◽  
Min-Geun Kim ◽  
Seonho Cho

We developed a shape-design optimization method for the thermo-elastoplasticity problems that are applicable to the welding or thermal deformation of hull structures. The point is to determine the shape-design parameters such that the deformed shape after welding fits very well to a desired design. The geometric parameters of curved surfaces are selected as the design parameters. The shell finite elements, forward finite difference sensitivity, modified method of feasible direction algorithm and a programming language ANSYS Parametric Design Language in the established code ANSYS are employed in the shape optimization. The objective function is the weighted summation of differences between the deformed and the target geometries. The proposed method is effective even though new design variables are added to the design space during the optimization process since the multiple steps of design optimization are used during the whole optimization process. To obtain the better optimal design, the weights are determined for the next design optimization, based on the previous optimal results. Numerical examples demonstrate that the localized severe deviations from the target design are effectively prevented in the optimal design.


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