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The present study focuses on the development, application, and comparison ofthree computational frameworks of varying fidelities for assessing the effectsof fuel sloshing in internal fuel tanks on the aeroelastic characteristics of awing section. The first approach uses the coupling of compressible flow solverfor external aerodynamics integrated with structural solver and incompressiblemultiphase flow solver for fuel sloshing in the embedded fuel tank Astime-domain flutter solution of these coupled solvers is computationallyexpensive, two approximate surrogate models to emulate sloshing flows areconsidered. One surrogate model utilizes a linearised approach for sloshingload computations by creating an Equivalent Mechanical System (EMS) with itsparameters derived from potential flow theory. The other surrogate model aimsto efficiently describe the dominant dynamic characteristics of the underlyingsystem by employing the Radial Basis Function Neural Networks (RBF-NN) usinglimited CFD-based data to calibrate this model. The flutter boundaries of awing section with and without the effects of fuel sloshing are compared. Thelimitation of the EMS surrogate to represent nonlinearities are reflected inthis study. The RBF-NN surrogate shows remarkable agreement with thehigh-fidelity solution for sloshing with significantly low computational cost,thereby motivating extension to three-dimensional problems.

Models for Predicting Transonic Flutter of a Wing-Section with Sloshing in an Embedded Fuel Tank