Despite their importance in benchmarking numerical simulations, buckling tests still feature compromises between component-level and high-fidelity large-scale tests. For example, compression-induced buckling tests cannot capture the through-thickness or span-wise stress gradients
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Despite their importance in benchmarking numerical simulations, buckling tests still feature compromises between component-level and high-fidelity large-scale tests. For example, compression-induced buckling tests cannot capture the through-thickness or span-wise stress gradients in wing skins. Consequently, the results obtained often require careful interpretation and conservative considerations before applying to a structure. Alternatively, a system-level large-scale test can be used, yet at considerably increased time and expense. There has been little progression towards capturing system-level behaviour in a simplified test. Herein, for buckling behaviour assessment, a three-point bending test is used, which is quick, simple to implement, and cost-effective compared to existing conventional methods. The proposed method relies on subjecting a panel with auxiliary stiffeners to bending to introduce compression-induced buckling in the skin. The three-point bend test is used, because it provides readily controllable loading and boundary conditions. The location of the neutral plane can be tailored via design of the stiffeners, thus allowing for control of the through-thickness stress gradient induced in the skin. This method is applicable to buckling of stiffened structures subject to bending (e.g., aircraft wingboxes). Numerical models are used to explore the limits of the proposed method and comparing it against traditional coupon and full-scale structural level tests. The test method is experimentally demonstrated for capturing the buckling behaviour of a thermoplastic composite panel made via automated fibre placement. The proposed approach is shown to reliably capture the buckling behaviour of a large-scale test using a simpler and more time and cost-efficient setup than conventional methods.
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