This paper proposes a design procedure to determine the optimal configuration of multi-degrees of freedom (MDOF) multiple tuned mass dampers (MTMD) to mitigate the global dynamic aeroelastic response of aerospace structures. The computation of the aerodynamic excitations is performed considering two models of atmospheric disturbances, namely, the Power Spectral Density (PSD) modelled with the Davenport Spectrum (DS) and the Tuned Discrete Gust (TDG) with the one-minus cosine profile. In order to determine the optimum sets of MTMD, a Multi-objective design Optimization considering Genetic Algorithm (MOGA) is implemented, where the selected fitness functions for the analysis are the minimization of the total mass of the resonators as well as the concurrent minimization of the peak displacements of a specified structural node in all translational degrees of freedom. A case study is presented to demonstrate the proposed methodology, where the optimal sets of MTMD are determined for the concurrent minimization of the pointing error of a truss-like antenna structure as well as the mass of the considered MTMD. It is found that the placement of the MTMD in the primary reflector of the antenna structure provided a maximum reduction in the pointing error of 62.0% and 39.2%, considering the PSD and the TDG models, respectively. Finally, this paper presents an advanced framework to estimate optimal parameters of MTMD control devices under convoluted loading cases as an initial step towards the use of such passive systems in applications that commonly employ active or semi-active solutions.

No abstract

No abstract

No abstract

This thesis proposes a framework for the design optimization of geometric nonlinearities developed by active elements embedded in truss-like aerospace structures for the purpose of attenuating their dynamic aeroelastic response under turbulent aerodynamic gust conditions. Dynamic aeroelastic responses are analyzed considering random Power Spectral Density (PSD) and Tuned Discrete Gust (TDG) excitation profiles. MSC NASTRAN® is employed for the development of the dynamic aeroelastic models where the random PSD with a continuous Davenport spectrum (DS) and the TDG with a One-minus cosine (OMC) wind gust excitation profiles are developed. This work presents a multi-objective genetic optimization algorithm (MOGA) utilized to determine optimal prestress values through active element actuations for the purpose of tuning the geometric stiffness and therefore modal response of the structure when exposed to gust excitations. Additionally, this work contributes a new simplified control metric for comparing active member locations. Two case studies are presented to minimize the pointing error of both a simplified and high-fidelity (HF) Earth-based very-long baseline interferometry (VLBI) antenna structure. The pointing error is calculated as the spatial displacement of the secondary reflector using time-consistent displacements (TCD) imparted by time consistent loads (TCL).To increase the computational efficiency of the design optimization process of the HF model, model order reduction is conducted using the Craig-Bampton method which resulted in the computation time decreasing from 39.21 minutes to only 50 seconds while maintaining a 99.9% Modal Assurance Criterion (MAC) correlation in the first 20 mode shapes of interest of the structure. With the reduced model, the framework used multi-objective genetic optimization with iii the dual objectives of decreasing total pointing error while minimizing the total strain energy in the system as a result of both the applied aerodynamic and inertia loads as well as the applied actuations. The yield strength of the elements and their maximum displacements were used as design constraints to ensure integrity of the structure. Pareto fronts are presented containing optimal responses for 16, 32, and 44 active members of the structure. The utopian point method was employed to calculate the best configuration of active members to be considered. A reduction of 82.6% with a total strain energy increase of 292.5% was obtained for the primary operating case under PSD gust excitation. On the other hand, at the increased mean wind speeds of the secondary operating case, the developed design algorithm was able to reduce the total pointing error by 80.9% but with a total strain energy increase of 825.3%. Similarly, for TDG analysis with the OMC excitation profile the optimization algorithm reduced the total pointing error by 51.6% with a TSE increase of 2098.1% and 80.5% with a TSE increase of 48.7% for the primary and secondary operating conditions, respectively, when compared to the uncontrolle...