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*GAP FLOW
Define constitutive parameters for tangential flow in pore pressure cohesive elements.

This option is used to define tangential flow constitutive parameters for pore pressure cohesive elements. It is usually used in a model with hydraulically driven fracture.

Products: Abaqus/Standard  Abaqus/CAE  

Type: Model data

Level: Model  

Abaqus/CAE: Property module

Reference:

Optional parameters:

DEPENDENCIES

Set this parameter equal to the number of field variables included in the definition of the constitutive parameters, in addition to temperature. If this parameter is omitted, it is assumed that the constitutive parameters are constant or depend only on temperature. See “Specifying field variable dependence” in “Material data definition,” Section 21.1.2 of the Abaqus Analysis User's Guide, for more information.

TYPE

Set TYPE=NEWTONIAN (default) to define the viscosity for a Newtonian fluid.

Set TYPE=POWER LAW to define the consistency and exponent for a power law fluid.

KMAX

Set this parameter equal to the maximum permeability value that should be used. This parameter is meaningful only when TYPE=NEWTONIAN. If this parameter is omitted, Abaqus assumes that the permeability is not bounded.

Data lines to define the pore fluid viscosity (TYPE=NEWTONIAN): 

First line:

  1. .

  2. Temperature, .

  3. First field variable.

  4. Second field variable.

  5. Etc., up to five field variables.

Subsequent lines (only needed if the DEPENDENCIES parameter has a value greater than five):

  1. Sixth field variable.

  2. Etc., up to eight field variables per line.

Repeat this set of data lines as often as necessary to define the variation.

Data lines to define the consistency, K, and exponent, (TYPE=POWER LAW): 

First line:

  1. K.

  2. .

  3. Temperature, .

  4. First field variable.

  5. Second field variable.

  6. Third field variable.

Subsequent lines (only needed if the DEPENDENCIES parameter has a value greater than three):

  1. Fourth field variable.

  2. Etc., up to eight field variables per line.

Repeat this set of data lines as often as necessary to define the variation.