Improved Verification for Aerospace Systems
Aerospace systems are subject to many stringent performance requirements to be verified with low risk. This report investigates verification planning using conditional approaches vice the standard classical statistical methods, and usage of historical surrogate data for requirement validation and in verification planning. The example used in this report to illustrate the results of these investigations is a proposed mission assurance requirement with the concomitant maximum acceptable verification risk for the NASA Constellation Program Orion Launch Abort System (LAS). This report demonstrates the following improvements: 1) verification planning using conditional approaches vice classical statistical methods results in plans that are more achievable and feasible; 2) historical surrogate data can be used to bound validation of performance requirements; and, 3) incorporation of historical surrogate data in verification planning using conditional approaches produces even less costly and more reasonable verification plans. The procedures presented in this report may produce similar improvements and cost savings in verification for any stringent performance requirement for an aerospace system.