JEC COMPOSITES MAGAZINE - Issue #58 - June - July 2010 - 31

Simulation
components, its sampling capability and the ease with which it can interface with inhouse software. Isight allowed the team to conduct trade-off studies with their Abaqus models and achieve rapid design optimization. The team constructed their geometry model in CATIA v5 from Dassault Systèmes using the following: S4R planar elements for the skin and stiffeners; the C3D8R element for the adhesive; shell composite with a single ply for delamination analysis; and a homogeneous solid in which mechanical properties were reduced six orders of magnitude for disbonding analysis. The model included approximately 49,500 elements, 45,400 nodes, and 272,600 variables. The analysis was run on a Windows server with four Intel Xeon processors, each with 64 bits and 8GB of RAM. The team conducted multiple Monte Carlo simulations, with each full cycle analysis – including nominal, delamination, and disbonding analysis – taking 30 minutes. The results of all the FEA analyses – both for intact and damaged components – provided the baseline data used to optimize the design and build of the composite panel using Isight.

Fig. 2: Composite panel with shear loads applied (left) and with axial, or aerodynamic loads applied (right)

To carry out their finiteelement analysis (FEA) of the intact panel, the team started with nominal values typical of the aeronautics industry for all Fig. 3: Composite panel with loads applied shows shear variables. They buckling (left), pressure buckling (right) and considered composite strain (below) three load cases – two with a uniform aerodynamic pressure on the panel (one directed towards the inside of the structure, the other directed out) and one with a shear load directed axially across the face of the panel (see Figures 2 and 3). The team then performed two additional analyses of damaged panels – one with delamination in the middle of the panel, the other with two disbondings under the panel stiffeners.

Isight helps optimize composite performance
As with many materials and structures, there are numerous variables to consider when designing a composite panel for an airplane, and it is difficult to determine which variables might be key to improving structural strength and performance. In such instances, a stochastic approach is useful for managing the enormous amount of data inherent in composite analysis. Isight streamlines this iterative solution process by using an interactive graphical interface and aeronautics features built into the software to enable tools like Monte Carlo, Design of Experiments, and/or Six Sigma for optimization. In this case, the Grupo TAM team chose the Monte Carlo method, which is particularly useful when there is significant uncertainty on the variables and

Fig. 4: Isight’s Monte Carlo simulation process flow as mapped out using the software’s visual tools.

No58 June - July 2010 / jec composites magazine

JEC COMPOSITES MAGAZINE - Issue #58 - June - July 2010

Table of Contents for the Digital Edition of JEC COMPOSITES MAGAZINE - Issue #58 - June - July 2010