Aviation has always been at the forefront of technology. In recent years, the technological progress has been pushed even stronger to significantly reduce the environmental impact of air transportation.
The Clean Sky 2 Joint Undertaking (CS2 JU) is a clear example of the effort produced by the European Union and its aerospace industry to increase aircraft performance and reduce the aviation environmental impact.
The performance-improvement objectives sought in the CS2 JU require a departure from conventional empennage configurations and technologies that constitute the current state of the art in aircraft design.
An “Advanced Rear End” component for the forthcoming generation of ultra-efficient aircraft might consist of a very compact rear fuselage and tail surfaces with planforms significantly different from those currently used in terms of aspect ratio, taper ratio and sweep angle.
Unfortunately, there is little knowledge at the moment about the aerodynamic performance of tailplanes with unconventional geometries.
This project aims at filling this lack of knowledge by building a new database made of numerical and experimental results optimally balanced by virtue of Uncertainty Quantification. More importantly, the project aims at developing and validating an innovative, physics-based low-order method to predict the non-linear aerodynamic characteristics of lifting surfaces with controls whose geometry could significantly differ from the usual ones. The low-order model will be used to design and optimise the rear end of next-generation ultra-efficient aircraft. The impact will be a further reduction of CO2 and other pollutants by aircraft of tomorrow.
The present project intends to contribute to the design of a demonstrator of the Advanced Rear End of advanced and ultra-advanced, short/medium/long range civil aircraft. The contribution of the present project to this endeavour
is to develop numerical methods to predict the nonlinear aerodynamic characteristics of lifting surfaces, of the type used in the tails of civil commercial aircraft. In particular, the main objective of the project is to develop a low-order numerical method based as far as possible on physical phenomena to match the results of the wind tunnel tests of the systematic series of geometries of tails of civil commercial aircraft, possibly including small correction factors.
Intermediate objectives, which are functional to achieving the main one are:
1. To develop a systematic series of wind tunnel tests of several models of tails of civil commercial aircraft covering a wide range of planform parameters, with and without simulated ice shapes. The choice of the test parameters will be driven by advanced Uncertainty Quantification techniques coupled to high-fidelity simulation.
2. To integrate the experimental database with a systematic series of numerical simulations of tails of civil commercial aircraft in order to increase the resolution of the database with respect to the control parameters. The proposed approach would permit to detect regions of the parameter space for which experimental measurements of tails of civil commercial aircraft can be substituted by high-fidelity numerical simulations.
3. To develop bayesian-based calibration methods using the full database of the aerodynamic performance of tails of civil commercial aircraft in order to extend the prediction of the maximum lift coefficient and hinge moment of tail surfaces given by the low-order numerical technique to an arbitrary Reynolds number.
4. To use the developed database to build an error function, which will correct the outcome of the low-order numerical method.
The project achieved all the objectives reaching and overall TRL of 5. An extensive database of data describing the nonlinear aerodynamics of swept wings was developd mixing numerical and experimental results under the control of Uncertainty Quantification techniques. The low-order model was successfully developed and calibrated through Bayesian techniques based on the database.
