Reduced order modeling (ROM) is proposed to drastically reduce the time and cost of 3-D viscous turbulent CFD-Icing simulations, with no sacrifice in dimensionality or physics. ROM uses a limited but strategically selected number of snapshots (CFD-Aero or CFD-Icing solutions obtained at various operating conditions) to extract, via proper orthogonal decomposition (POD), a basis of vectors (modes) that represent its most fundamental physical features. A linear combination of these POD modes, with coefficients obtained via multi-dimensional interpolation, can then be used to rapidly obtain solutions for all conditions within the design space other than the snapshots.

    The chapter presents a local POD approach, specifically designed for the icing certification appendices, clustering the snapshots in sharply delimited trace-glaze-rime regions. An error-driven iterative sampling combining a greedy approach and a centroidal Voronoi tessellation (CVT) then positions additional snapshots in regions of high nonlinearity, to achieve a balance between accuracy and number of snapshots. Finally, a Gappy POD approach is presented to combine data from tunnel or flight tests with CFD solutions for comprehensive coverage of the certification requirements.

    The icing applications for which ROM is demonstrated include, singly and in combination, airflow, small and large supercooled droplets impingement, ice accretion, aerodynamic performance penalties, ice protection systems (IPS) optimization, shed-ice tracking, wind and icing tunnel tests, ice shapes testing, natural ice flight tests and flight simulators. The results give additional impetus to the drive for Certification by Analysis, as well as to pilot training programs, leading to increased aviation safety.


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