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Simulation of shear localization in granular bodies within gradient-enhanced hypoplasticity

100%

Tejchman J.

Archives of Hydro-Engineering and Environmental Mechanics

2004

tom Vol. 51, nr 3

243-265

The paper presents a FE-analysis of a spontaneous shear localization inside non-cohesive sand during plane strain compression. The calculations were carried out with a gradient-enhanced hypoplastic constitutive law. The hypoplastic law can reproduce essential features of granular bodies depending on the void ratio, pressure level and deformation direction. To model the thickness of shear zones, a characteristic length of the microstructure was incorporated via the second gradient of the modulus of the deformation rate. To determine the effect of micro-structure, the analysis was performed with different characteristic lengths for the same specimen size.

Modele zewnętrzne i wewnętrzne w interaktywnej optymalizacji wizualnej w trybie bezpośrednim

72%

Makles K.

Metody Informatyki Stosowanej

2010

tom nr 4 (24)

81-91

The article describes the external and internal models used in on-line interactive optimization. This type of optimization, in fact of increasing computing power of modem computers, allows to solve incompletely determined optimization problems. The application of interactive optimization for linem' and nonlinear tasks is shown. Describes the internal model proposed for use in interactive optimization, along with examples of its construction. Indicated a general scheme of searching for the optimal solutlon for interactive optimization in on-line mode.

Stabilność i zbieżność modelu gradientowego w interaktywnej optymalizacji wizualnej w trybie bezpośrednim

58%

Makles K.

Metody Informatyki Stosowanej

2011

tom nr 4

135-146

The article describes the stability and convergence criterion of linear gradient internal model used in on-line interactive optimization. This type of optimization, in fact of increasing computing power of modern computers, allows to solve incompletely determined optimization problems. Stability and convergence of the linear gradient model was discused for three cases: when searching point moving from the forbidden into the allowed area, when searching point moving in the allowed area, and whensearching point moving from the allowed into the forbidden area.