A Monte Carlo statistical uncertainty analysis method for nosetip recession predictions

A Monte Carlo statistical technique has been developed for obtaining quantitative estimates of the uncertainties associated with nosetip recession predictions in clear air and in erosive weather environments. Several key parameters in the analytical ablation and erosion models are identified and uncertainty bands are assigned to each parameter based on a review of the supporting data bases. The Monte Carlo technique was incorporated in a nosetip ablation/erosion computer program and sample calculations were performed to illustrate the use of the method. The technique is shown to provide a rapid, accurate method for defining rational design safety factors and for evaluating the relative importance of individual parameters in the nosetip recession models.