Applying Monte Carlo Simulation to Launch Vehicle Design and Requirements Verification

摘要

This paper is focused on applying a Monte Carlo simulation to probabilistic launch vehicle design and requirements verification. The approaches developed in this paper can be applied to other complex design efforts as well. Typically, the verification must show that requirement "x" is met for at least "y%" of cases, with, say, 10% consumer risk or 90% confidence. Two aspects of making these runs will be explored in this paper. First, there are several types of uncertainties that should be handled in different ways, depending on when they become known (or not). The paper describes how to handle different types of uncertainties and how to develop vehicle models that can be used to examine their characteristics. This includes items that are not known exactly during the design phase, but will be known for each assembled vehicle; other items that become known before or on flight day; and items that remain unknown on flight day. Second, this paper explains a method (order statistics) for determining whether certain probabilistic requirements are met and enables the user to determine how many Monte Carlo samples are required. The methods also apply to determining the design values of parameters of interest in driving the vehicle design.