AbstractHigh fidelity modelling and simulation are prerequisites for ensuring confidence in decision making during aircraft design and development, including performance and handling qualities, control law developments, aircraft dynamic loads analysis, and the creation of a realistic simulation environment. The techniques of system identification provide a systematic framework for ‘enhancing’ a physics–based simulation model derived from first principles and aircraft design data. In this paper we adopt a frequency domain approach for model enhancement and fidelity improvement of a baseline FLIGHTLAB Bell 412 helicopter model developed at the University of Liverpool. Predictability tests are based on responses to multi–step control inputs. The techniques have been used to generate one, three, and six degree-of-freedom linear models, and their derivatives and predictability are compared to evaluate and augment the fidelity of the FLIGHTLAB model. The enhancement process thus involves augmenting the simulation model based on the identified parameters. The results are reported within the context of the rotorcraft simulation fidelity project, Lifting Standards, involving collaboration with the Flight Research Laboratory (NRC, Ottawa), supported with flight testing on the ASRA research helicopter.
Complete-genome analysis of hepatitis B virus from wild-born chimpanzees in central Africa demonstrates a strain-specific geographical cluster
