Methodologies of stochastic simulation for helicopter accidents and nonparametric evaluation of the stochastic responses

Abstract

ABSTRACTThe paper aims to develop stochastic simulation and nonparametric analysis methods for investigation into and harm minimisation of helicopter accidents resulting from a total engine failure. An innovative, stochastic simulation scheme is established for investigating the variability in a full crash event by incorporating the methodologies of hierarchical stochastic simulation and nonparametric analysis. By employing Monte Carlo algorithms in flight emergency and structure crash simulations, a stochastic simulation method is developed for establishing robust correlations between the critical parameters prior to helicopter accidents and possible occupant injury metrics. Based on the nonparametric analysis performed on the stochastic injury responses, a solution is proposed to predict and evaluate the potential severity of occupant's injuries resulting from this class of helicopter accidents. A comparison of using the nonparametric strategy into three different thicknesses of subfloor tubes develops the potential for evaluating the stochastic injury results of the helicopter accidents.