  A monotonic, non-kernel density variant of the density-matching technique for
optimization under uncertainty is developed. The approach is suited for
turbomachinery problems which, by and large, tend to exhibit monotonic
variations in the circumferentially and radially mass-averaged quantities--such
as pressure ratio, efficiency and capacity--with common aleatory turbomachinery
uncertainties. The method is successfully applied to de-sensitize the effect of
an uncertainty in rear-seal leakage flows on the fan stage of a modern jet
engine.
