## 3 Reference Case  
The GMGW (Geometry and Mesh Generation Workshops) aimed to identify suitable improvements and best practices for generating more accurate and reliable meshes. For the second GMGW [47], a parametric aircraft model inspired by the Boeing 787-800 Dreamliner, a twin-engine civilian aircraft for medium- to long-haul routes, was provided [48]. The simplified model (see Figure 1, left) is based on 53 parameters and scaled approximately 1:300 relative to the B787. The entire aircraft body is composed of spheres, cylinders, cones, and ruled surfaces. Cross-sections for the ruled surfaces are either NACA 4-series airfoils or super-ellipses. Full details on the generation of wings, fuselage, and other parts of the aircraft can be found in [48]. As a CAD editor, ESP (Engineering Sketch Pad), an open-source editor developed by the Massachusetts Institute of Technology, was used [49]. The workshop challenge involved starting with a parametric CAD model and developing an automatic meshing procedure that maintains mesh quality for each DP. In this study, a different perspective was taken to address the challenge. Instead of generating a new mesh for each DP, the CAD modifications were transferred to the existing mesh, deforming the baseline mesh accordingly. This innovative and creative approach offers several computational advantages. Notably, it makes the workflow well-suited for generating ROMs, where it is crucial to keep the mesh topology unchanged, and provides a significant step forward compared to the mesh-morphing-based approach presented at GMGW [50], adding the full automation of the process according to the CAD parametrization. The focus of the OPAM-1 challenge was automatic mesh creation. In fact, the ESP tool is fully scriptable, so once the parametric model is defined, each CAD variant can be generated with a Python script. Having also a procedure for automatic mesh creation makes the workflow very attractive, greatly reducing the time to prepare the CFD analysis. Several studies [17; 18; 19; 51; 52] have been conducted in this regard, demonstrating the possibility of automating the mesh creation process. However, some critical issues remain. The processes used are often not fully automated and always require a preliminary step in which the parts that form the aircraft are described and grouped and the reference dimensions for the problem are set. In addition, the mesh creation phase remains a fairly computationally expensive phase. Finally, even after automating the mesh creation process, it remains very difficult to ensure that the mesh is iso-topological (a key aspect of creating ROMs). Another approach is mesh-morphing, which involves using the same mesh while defining parameters at the mesh level; it was used for the OPAM-1 testcase [50], emphasizing its flexibility by showing its effectiveness in large geometric variations. The mesh used for this testcase and the variations considered are shown in Figures 1b and 2. The main advantages of this approach are related to the fact that the same computational grid is always used, so there is no re-meshing noise, the mesh topology does not change (crucial for ROM generation), the convergence of the CFD analysis is faster, and in general, the CFD model update takes less time. In particular, comparing the time required for the two studies [50; 51], even considering the different facility used, mesh morphing is very advantageous. Conversely, the main limitation is related to the setup. In fact, to obtain these shape variations, complex setups are required, there is often a limit on the maximum amplifications to ensure a good mesh quality, and the shape variations must be iso-topological. In addition, in some cases, it is difficult to define the displacements of source points when there is a more complex shape change and the fundamental operations (rigid displacements, scaling, offsets, etc.) are not captured with sufficient accuracy (specifically in [50], post-morphing STL surface projections are required to preserve the geometry).