Page 64 - ansys
P. 64

w   Regardless of whether Use Advanced Size Function is on or off:
             o  Choosing the Hard option for edges means that the size or number of divisions is fixed on the
         edge  and  cannot  be  changed  by  the  meshing  algorithm  and  the  likelihood  of  a  mesh  failure
         increases.
             o  Choosing the Soft option for edges, faces, and bodies means that the size control will be
         affected by proximity, curvature, and local remeshing during the meshing process.

         w   If Use Advanced Size Function is off:
             o  Choosing Hard on a face/body means that curvature pre-refinement is not performed on the
         edges of the face/body, but the edge can be split by the mesher.
         w   Remember these notes when using the Behavior option:

             o  If Use Advanced Size Function is on and a Soft size is specified on an entity, the specified
         Growth Rate is used.
         w   If Use Advanced Size Function is on and a Hard size is specified on an entity, the Growth Rate is not
         respected; the mesher will try to maintain a uniform size on the entity. If two entities with Hard   sizes
         of different values are adjacent to one another, no growth occurs and there will be an abrupt    s i z e
         change  between  them.  However,  growth  will  occur  on  all  entities  without  hard  size
         constraints that are adjacent to a hard size entity, even if the Hard size applied is smaller than Min
         Size/Proximity Min Size.


















                                             Sizing on Edge
         Bias Type and Bias Factor
         Specify the grading scheme and factor
         Bias Type: grading of elements towards one end, both ends, or the center
         Bias Option:
         Bias Factor: is the ratio of the largest element to the smallest element

         Smooth Transition: defined by Growth Rate which is ratio of size of an element with size of
         previous element. (Growth Rate = Bias Factor (1(n-1))






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