David Marquez-Monje

Hybrid Laminar Flow Control (HLFC) is a promising technology for reducing aircraft drag and, therefore, emissions and fuel consumption. The integration of HLFC systems within the small space of the wing leading edge, together with de-icing and high lift systems, is one of the main challenges of this technology. This challenge can be tackled by using microholes along the outer skin panels to control suction without the need for an internal chamber. However, microperforations modify the mechanical properties of titanium sheets, which bring new challenges in terms of wing manufacturability. These modified properties create uncertainty that must be investigated. The present paper studies the mechanical properties of micro-drilled titanium grade 2 sheets and their modeling using the Finite Element Method (FEM). First, an experimental campaign consisting of tensile and Nakajima tests is conducted. Then, an FEM model is developed to understand the role of the anisotropy in sheet formability. The anisotropy ratios are found by combination of Design of Experiments (DoE) and the Response Surface Method (RSM); these ratios are as follows: 1.050, 1.320, and 0.975 in the directions Y, Z, and XY, respectively. Some mechanical properties are affected by the presence of microholes, especially the elongation and formability that are significantly reduced. The reduction in elongation depends on the orientation: 20% in longitudinal, 17% in diagonal, and 31% in transversal.

This paper focuses on the calibration of heat source parameters to reproduce temperatures and distortions in welded joints. Specifically, the proposed methodology, which combines the Finite Element Method and Design of Experiments, is applied to calibrate a T-joint dissimilar titanium laser welding process. The thermal problem is addressed using a 3D transient model with a Conical Gaussian heat flux, and the mechanical problem is tackled using a 3D elastic-plastic model. A Fractional-Factorial Design is performed to define a set of thermo-mechanical uncoupled models. Finally, optimal parameter combinations that replicate experimental data are identified. This methodology allows automation that replaces the traditional trial and error process, which frequently does not provide good results, is an exhausting task and requires a dubious amount of time.