Automated Parametric Finite-Element-Model Generation and Optimization of a Composite Aircraft Wing ^†

An automated framework for the parametric FE model generation and sizing of composite aircraft wings suitable for early-stage studies is presented. Implemented in Python and HyperMesh TCL, the tool controls both outer-geometry parameters, such as span, taper ratio, and twist, and internal-structural layout parameters, such as spar locations, rib spacing, and stringer layouts, and generates analysis-ready 2D composite GFEM models with material assignment and layups for size optimization. To demonstrate the workflow, a Design of Experiments (DoE) is performed on a representative transport wing internal structural layout, while keeping the outer geometry fixed. For each DoE point, OptiStruct performs gradient-based composite-size optimization to minimize structural mass, subject to composite strength (max strain), buckling, and metallic no-yielding constraints. A staged multi-run strategy is implemented to mitigate the effects of local minima. DoE results show a strong correlation and a non-monotonic effect of stringer number, an increase in mass as the front spar moves aft, and a comparatively weaker effect of the number of aluminum ribs. As a preliminary baseline, a Random Forest surrogate trained on the DoE predicts the wing structural mass with reasonable accuracy (RMSE $=0.081$), motivating the future implementation of Gaussian process models with uncertainty modeling. The framework accelerates early-stage structural design exploration and is amenable to surrogate-based optimization.