Propagation of uncertainty in test-analysis correlation of substructured spacecraft

Abstract

Organizations, such as the Air Force and NASA make critical decisions on spacecraft performance and survivability based on the results of test-analysis correlation metrics. In order to ensure the success of a new paradigm in finite element model validation where there is no system level test, uncertainty in the substructures must be propagated into the system level correlation metrics. The objective of this work is to quantify the level of accuracy required at the substructure level to produce acceptable analytical model accuracy at the system level. In preparation for future synthesized system level uncertainty analysis, a framework is presented for propagating analytical model uncertainty from a fixed interface Craig–Bampton substructure representation into a free–free substructure. Model uncertainty is parameterized in terms of test- or truth-analysis correlation metrics that are dictated by the Air Force. A statistical model is presented for these correlation metrics such that an analyst can specify a covariance matrix for uncertainty in model correlation at the fixed substructure level, and then propagate it into correlation uncertainty at the free substructure level. Development of the forward propagation approach then allows propagation of correlation uncertainty in the reverse direction from the free substructure into the fixed interface based Craig–Bampton representation. The proposed methods are applied to a typical spacecraft representation.