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This paper aims to present a numerical method based on computational fluid dynamics that allows investigating the buffet envelope of reference equivalent wings at the equivalent cost of several two-dimensional, unsteady, turbulent flow analyses. The method bridges the gap between semi-empirical relations, generally dominant in the early phases of aircraft design, and three-dimensional turbulent flow analyses, characterised by high costs in analysis setups and prohibitive computing times.

Accuracy in the predictions and efficiency in the solution are two key aspects. Accuracy is maintained by solving a specialised form of the Reynolds-averaged Navier–Stokes equations valid for infinite-swept wing flows. Efficiency of the solution is reached by a novel implementation of the flow solver, as well as by combining solutions of different fidelity spatially.

Discovering the buffet envelope of a set of reference equivalent wings is accompanied with an estimate of the uncertainties in the numerical predictions. Just over 2,000 processor hours are needed if it is admissible to deal with an uncertainty of ±1.0° in the angle of attack at which buffet onset/offset occurs. Halving the uncertainty requires significantly more computing resources, close to a factor 200 compared with the larger uncertainty case.

To permit the use of the proposed method as a practical design tool in the conceptual/preliminary aircraft design phases, the method offers the designer with the ability to gauge the sensitivity of buffet on primary design variables, such as wing sweep angle and chord to thickness ratio.

The infinite-swept wing, unsteady Reynolds-averaged Navier–Stokes equations have been successfully applied, for the first time, to identify buffeting conditions. This demonstrates the adequateness of the proposed method in the conceptual/preliminary aircraft design phases.

The purpose of this paper is to document an efficient and accurate approach to generate aerodynamic tables using computational fluid dynamics. This is demonstrated in the context of a concept transport aircraft model.

Two designs of experiment algorithms in combination with surrogate modelling are investigated. An adaptive algorithm is compared to an industry-standard algorithm used as a benchmark. Numerical experiments are obtained solving the Reynolds-averaged Navier–Stokes equations on a large computational grid.

This study demonstrates that a surrogate model built upon an adaptive design of experiments strategy achieves a higher prediction capability than that built upon a traditional strategy. This is quantified in terms of the sum of the squared error between the surrogate model predictions and the computational fluid dynamics results. The error metric is reduced by about one order of magnitude compared to the traditional approach.

This work lays the ground to obtain more realistic aerodynamic predictions earlier in the aircraft design process at manageable costs, improving the design solution and reducing risks. This may be equally applied in the analysis of other complex and non-linear engineering phenomena.

This work explores the potential benefits of an adaptive design of experiment algorithm within a prototype working environment, whereby the maximum number of experiments is limited and a large parameter space is investigated.