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Finite Element Analysis for Excavations and Slopes
Phase2 7.0 is a powerful 2D elasto-plastic finite element stress analysis program for underground or surface excavations in rock or soil. It can be used for a wide range of engineering projects and includes support design, finite element slope stability and groundwater seepage analysis.
Complex, multi-stage models can be easily created and quickly analyzed, for example: tunnels in weak or jointed rock, underground powerhouse caverns, open pit mines and slopes, embankments, MSE stabilized earth structures, and much more. Progressive failure, support interaction and a variety of other problems can be addressed.
Phase2 offers a wide range of support modeling options. Liner elements can be applied in the modeling of shotcrete, concrete, steel set systems, retaining walls, piles, multi-layer composite liners, geotextiles and more. New liner design tools include support capacity plots which allow you to determine the safety factor of reinforced liners. Bolt types include end anchored, fully bonded, cable bolts, split sets and grouted tiebacks.
One of the major features of Phase2
is finite element slope stability analysis using the shear strength reduction method. This option is fully automated and can be used with either Mohr-Coulomb or Hoek-Brown strength parameters. Slope models can be imported / exported between Slide
allowing easy comparison of limit equilibrium and finite element results.
Phase2 includes steady state, finite element groundwater seepage analysis built right into the program. There is no need to use a separate groundwater program. Pore pressure is determined as well as flow and gradient, based on user defined hydraulic boundary conditions and material conductivity. Pore pressure results are automatically incorporated into the stress analysis.
Material models for rock and soil include Mohr-Coulomb, Generalized Hoek-Brown and Cam-Clay. Powerful new analysis features for modeling jointed rock allow you to automatically generate discrete joint or fracture networks according to a variety of statistical models.