Abstract
In aircraft structural integrity analysis, the damage tolerance and fatigue life is investigated against a cyclic loading spectrum. The particular spectrum includes the stress/loading levels counted during a flight of certain duration. The occurrences of load factors may include higher gravitational acceleration 'g' levels. While maintaining a certain g level occurrence at higher angle of attack, wing structure vibrates with the amplitudes of its natural frequencies. The cyclic stress amplitudes of vibration depend upon the natural frequencies of vibrating structure, i.e. lower frequency gives higher amplitudes and vice versa.
To improve the dynamic stability, modal parameters of simple carbon fibre sandwich panels have been adjusted by tailoring the fibre orientation angles and stacking sequence. In this way, the effect of change in structural dynamic characteristics on fatigue life of this simplified structure has been demonstrated. The research methodology followed in this work consists of two phases. In the first phase, aero-elastically tailored design was finalized using FEM based modal analysis and unsteady aerodynamic analysis simulations followed by experimental modal analysis. In the second phase, fatigue and damage tolerance behaviour of material was investigated using different fracture mechanics based techniques. ASTM's standard practices were adopted to determine material allowable and fracture properties. Simulation work was performed after proper calibration and correlation of finite element model with experimentally determined static and dynamic behaviour of panels.
It has been observed that the applicable cyclic loading spectra, as major input parameter of fatigue analysis, largely depend upon the natural frequencies, damping and the stiffness of the structure. The results and discussions of the whole exercise may be beneficial while carrying out aero-elastic tailoring of composite aircraft wing. This research work has also a positive contribution towards multidisciplinary structural design optimization of aerospace vehicles. (C) 2017 Elsevier Masson SAS. All rights reserved.