  It is shown how the central limit theorem for U-statistics of spatial Poisson
point processes can help to derive the central limit theorem for U-statistics
of a Gibbs facet process from stochastic geometry. A full-dimensional submodel
enables a simpler approach to the investigation. Finally the general situation
is studied and the asymptotics with increasing intensity is described.
