Loads-based optimal fuel-usage strategy by using a neural-network-based reduced-order model for vertical sloshing

Abstract

This paper explores methods to reduce aircraft design loads through an optimal fuel usage strategy, which maximises the beneficial effects of wing-tank sloshing-induced damping. A reduced-order neural network models the nonlinear sloshing behaviour in various tank fill level scenarios. Integrated into an aeroelastic framework, this model allows for the assessment of incremental sloshing-induced damping in gust response of wings. The optimised fuel usage strategy enables control of fuel consumption from each individual tank to provide maximisation of load alleviation.