Locally adapted tetrahedral meshes play a crucial role in
the efficient computation of the numerical solution for many
problems. Bisection of individual tetrahedra can be effectively
used to formulate algorithms producing nested sequences of conforming,
locally adapted tetrahedral meshes starting with an arbitrary
coarse conforming mesh. The talk will explore some of the connections
and relations among different "bisection of tetrahedra" algorithms.
In particular, I will concentrate on an algorithm that involves
very simple data-structures and has the property that the repeated
bisection of an arbitrary tetrahedron produces at most thirty-six
similarity classes of tetrahedra.
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