Sea-ice thickness on the northern Canadian polar shelf: A second look after 40 years

This paper presents a systematic record of multi-year sea-ice thickness on the northern Canadian polar shelf, acquired during the winter of 2009–10. The data were acquired by submerged sonar positioned within Penny Strait where they measured floes drifting south from the notional “last ice area”. Ice was moving over the site until 10 December and fast thereafter. Old ice comprised about half of the 1669-km long survey. The average old-ice thickness within 25-km segments of the survey track was 3–4 m; maximum keels were 12–16 m deep. Floes with high average draft were of two types, one with interspersed low draft intervals and one without. The presence or absence of thin patches apparently distinguished aggregate floes comprised of sub-units of various ages and deformation states from units of more homogeneous age and deformation state. The former were larger and of somewhat lower mean thickness (1–5 km; 3.5–4.5 m) than the latter (400–600 m; 6.5–14 m). Calculated ice accretion onto the multi-year ice measured in autumn 2009 was used to seasonally adjust the observations to a date in late winter, when prior data are available. The adjusted mean thickness for all 25-km segments with 4 tenths or more old ice was 3.6 m (sample deviation of 0.4 m), a value indistinguishable within sampling error from values measured in the same area during the 1970s. The recently measured ice-draft distributions were also very similar to those from the 1970s.

On a reduced-order model-based optimization of rotor electro-thermal anti-icing systems

Purpose Responsible for lift generation, the helicopter rotor is an essential component to protect against ice accretion. As rotorcraft present a smaller wing cross-section and a lower available onboard power compared to aircraft, electro-thermal heating pads are favored as they conform to the blades’ slender profile and limited volume. Their optimization is carried out here taking into account, for the first time, the highly three-dimensional (3D) nature of the flow and ice accretion, in contrast to the current state-of-the-art that is limited to two-dimensional (2D) airfoils. Design/methodology/approach Conjugate heat transfer simulation results are provided by the truly 3D finite element Navier–Stokes analysis package-ICE code, embedded in a proprietary rotorcraft simulation toolkit, with reduced-order modeling providing a time-efficient evaluation of the objective and constraint functions at every iteration. The proposed methodology optimizes heating pads extent and power usage and is versatile enough to address in a computationally efficient manner a wide variety of optimization formulations. Findings Low-error reduced-order modeling strategies are introduced to make the tackling of complex 3D geometries feasible in todays’ computers, with the developed framework applied to four problem formulations, demonstrating marked reductions to power consumption along with improved aerodynamics. Originality/value The present paper proposes a 3D framework for the optimization of electro-thermal rotorcraft ice protection systems, in hover and forward flight. The current state-of-the-art is limited to 2D airfoils.

Aircraft Icing Severity Evaluation

Aircraft icing refers to the ice buildup on the surface of an aircraft flying in icing conditions. The ice accretion on the aircraft alters the original aerodynamic configuration and degrades the aerodynamic performances and may lead to unsafe flight conditions. Evaluating the flow structure, icing mechanism and consequences is of great importance to the development of an anti/deicing technique. Studies have shown computational fluid dynamics (CFD) and machine learning (ML) to be effective in predicting the ice shape and icing severity under different flight conditions. CFD solves a set of partial differential equations to obtain the air flow fields, water droplets trajectories and ice shape. ML is a branch of artificial intelligence and, based on the data, the self-improved computer algorithms can be effective in finding the nonlinear mapping relationship between the input flight conditions and the output aircraft icing severity features.