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Joint Networks
Joint network modeling is a powerful new feature introduced in Phase2 version 7, which allows you to easily generate 2-dimensional networks of joint boundaries to simulate patterns of natural or induced jointing in rock masses.
Joint networks can be generated according to a variety of statistical or deterministic models, including:
Phase2 model illustrating several different types of joint network
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Joint Networks: Add Network
A joint network is created with the Add Joint Network option. You can generate a joint network in any selected region(s) of the model, using any of the joint network models shown in the dialog below. Multiple joint networks can be defined, and different networks can be applied to different regions.
Add Joint Network dialog
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Joint Networks: Parallel Deterministic
The Parallel Deterministic joint network model allows you to define a network of parallel joints with a fixed spacing, length and persistence.
Parallel Deterministic joint network, uniform joint spacing, length and persistence
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Joint Networks: Parallel Statistical
The Parallel Statistical joint network model allows you to define a network of parallel joints with user-defined statistical distributions for the joint spacing, length and persistence.
Parallel Statistical joint network, random joint spacing, length and persistence
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Joint Networks: Cross Jointed
The Cross Jointed joint network model allows you to define a network which consists of two sets of parallel joints (e.g. bedding planes with cross joints) which intersect to form rectangular or trapezoidal blocks. The spacing of the joint planes can be defined as random variables.
Cross joint network, 35 degree bedding plane inclination
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Joint Networks: Baecher
The Baecher joint network model is a flexible algorithm that can generate intricate joint networks. Joints are assumed to have finite trace lengths, which follow some statistical distribution. The centers of the joints are located in space according to a Poisson point process. The number of joints is controlled by a joint intensity measure.
Baecher joint network, random joint length and orientation
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Joint Networks: Veneziano
The Veneziano joint network model first generates infinite lines at random locations. The infinite lines are then divided into joint segments of random length, with user-defined statistical distributions
Veneziano joint network, random joint length, orientation and persistence
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Joint Networks: Voronoi
Two-dimensional Voronoi tessellation is a process that randomly subdivides a plane into non-overlapping convex polygons. A Voronoi joint network consists of joints that are defined by the bounding segments of these polygons.
Voronoi joint network, irregular polygons
A Voronoi network is recommended for broken rock masses in which there are no preferred jointing directions. The regularity of the Voronoi network can be controlled by the user, as shown below.
Voronoi joint network, almost regular polygons
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