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The high computational cost of 3-D viscous turbulent aero-icing simulations is one of the main limitations to address in order to more extensively use computational fluid dynamics to explore the wide variety of icing conditions to be tested before achieving aircraft airworthiness. In an attempt to overcome the computational burden of these simulations, a Reduced Order Modeling (ROM) approach, based on Proper Orthogonal Decomposition (POD) and Kriging interpolation techniques, is applied to the computation of the impingement pattern of supercooled large droplets (SLD) on aircraft. Relying on a suitable database of high fidelity full-order simulations, the ROM approach provides a lower-order approximation of the system in terms of a linear combination of appropriate functions. The accuracy of the resulting surrogate solution is successfully compared to experimental and CFD results for sample 2-D problems and then extended to a typical 3-D case.

CFD-Icing (CFD-I) is a powerful companion to CFD-Aero (CFD-A) in the design and certification of new aircraft, rotorcraft and jet engines. It can drastically reduce the number of tunnel and flight tests, and their associated costs, by simulating on computers the full Appendix C and beyond such as is proposed in new Appendices D and O. It can also predict performance and moment coefficients in roll, pitch and yaw. These predictions can then be used in original certification or supplemental certifications to the type design, allowing mitigating potential hazards of flight-testing. This work presents an example of the application of FENSAP-ICE to predict 45 minutes of ice accretion on a RC-26B aircraft fuselage retrofitted by the addition of a FLIR sensor and a SATCOM antenna. The predicted aerodynamic penalties are compared with recorded flight test data obtained with simulated ice shapes.