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Failure characteristics of jointed rock-like material containing multi-joints under a compressive-shear test: Experimental and numerical analyses

Cao R. H., Cao P., Lin H., Ma G. W., Zhang C. Y., Jiang C.

Archives of Civil and Mechanical Engineering

2018

Vol. 18, no. 3

784--798

Extensive efforts have been made to gain a better understanding of the failure behaviour of rocks and rock-like materials, but crack propagation and failure processes under compressive-shear loading have not yet been comprehensively investigated. To address this area of research, the peak shear strengths (τ) and failure processes of specimens with multiple joints are studied by lab testing and particle flow code (PFC2D). Four types of failure modes are observed: (a) shear failure through a plane (Mode-I), (b) intact shear failure (Mode-II), (c) oblique shear crack connection failure (Mode-III), and (d) stepped path failure (Mode-IV). The failure mode gradually transformed to Mode-III as α (joint inclination angle) increases from 0° to 90° in the specimens. In addition, with increasing joint distance (d) in the specimens, the failure mode changes to Mode-II. As the non-overlapping length between joints (c) in the specimens increases, the failure mode changes to Mode-IV. The joint geometry has a major influence on the shear strength of the jointed specimens. The peak shear strength of specimens with different joint inclination angles is obtained when α = 45°. Additionally, the peak shear strength increases as the joint distance (d) and non-overlapping length (c) increase.

Energy Management for Grid-connected Micro Grid with Renewable Energies and Dispatched Loads

Liu Y., Jiang C., Shen J., Zhou X.

Przegląd Elektrotechniczny

2012

R. 88, nr 5b

87-92

This paper focused on energy management program for grid-connected micro grid with renewable generation and electric vehicles. The proposed program, including energy purchase and self-scheduling problems, aimed to minimize energy cost based on forecasting of loads, prices and renewable generations and was solved with genetic algorithm and pattern search methods. Furthermore, it adopts the expectation model and Monte Carlo methods to solve the uncertainty problems. Simulation results proved the effectiveness of the proposed program.

Analizowano zarządzanie energią w sieci typu microgrid. Celem jest minimalizacja kosztów bazująca na przewidywaniu obciążenia. Wykorzystano algorytmy genetyczne oraz metodę Monte Carlo.