モンテカルロ評価における危険不確定パラメータの検出法

抄録

In aerospace projects preflight evaluation is crucial for mission success, because flight testing in a real environment is often difficult or impossible. Monte Carlo simulation is a powerful tool for the preflight evaluation because a nonlinear system incorporating various uncertain parameters can be evaluated directly. Monte Carlo simulation has been used in various aerospace projects throughout the world as the computer power increases. After the system evaluation, it is important to detect influential uncertain parameters which cause significant performance degradation so that measures for the system improvement can be studied. However, detecting those parameters is often uneasy because various uncertain parameters are incorporated simultaneously and their magnitudes are randomly generated in Monte Carlo simulation. An interaction of more than two uncertain parameters might be affected. This paper presents a simple approach to detect influential uncertain parameters applying a statistical test to the Monte Carlo results.