Improved vortex lattice method for drag prediction of supersonic wings using shock cone modelling

Drag prediction in supersonic wing design is a computationally demanding task due to complex flow physics and the high volume of data required for accurate modelling. High-fidelity CFD methods, while precise, are often too resource intensive for iterative early-stage design. This study presents a reduced-order approach that enhances the conventional Vortex Lattice Method (VLM) by incorporating the Taylor-Maccoll hypervelocity method (TMHM) to model shock cones and estimate wave and pressure drag due to compressibility effects, but does not model viscous skin friction drag explicitly. The resulting solver offers a balance between computational efficiency and predictive accuracy, enabling rapid analysis across a wide range of supersonic configurations. Validation against experimental and SST RANS data for Mach numbers from 1.0 to 2.7 shows an improvement of up to 20% in drag prediction over standard VLM, with an accuracy ranging from 90% to 95% for various wing geometries including delta, dihedral, and highly swept designs. This method supports the development of data-efficient, fast turnaround tools for the design of next-generation supersonic aircraft.