  An important feature in the design of superhydrophobic surfaces is their
robustness against collapse from the Cassie-Baxter configuration to the Wenzel
state. Upon such a transition a surface loses its properties of low adhesion
and friction. We describe how to adapt the Surface Evolver algorithm to predict
the parameters and mechanism of the collapse transition on posts of arbitrary
shape. In particular, contributions to the free energy evaluated over the
solid-liquid surface are reduced to line integrals to give good convergence.
The algorithm is validated for straight, vertical and inclined, posts.
Numerical results for curved posts with a horizontal section at their ends show
that these are more efficient in stabilising the Cassie state than straight
posts, and identify whether the interface first depins from the post sides or
the post tips.
