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Since, ice accretion can significantly degrade the performance and the stability of an airborne vehicle, it is imperative to be able to model it accurately. While ice accretion studies have been performed on airplane wings and helicopter blades in abundance, there are few that attempt to model the process on more complex geometries such as fuselages. This paper proposes a methodology that extends an existing in-house Extended Messinger solver to complex geometries by introducing the capability to work with unstructured grids and carry out spatial surface streamwise marching. For the work presented here commercial solvers such as STAR-CCM+ and ANSYS Fluent are used for the flow field and droplet dispersed phase computations. The ice accretion is carried out using an in-house icing solver called GT-ICE. The predictions by GT-ICE are compared to available experimental data, or to predictions by other solvers such as LEWICE and STAR-CCM+.

Ice buildup in the compressor section of a commercial aircraft gas turbine engine can cause a number of engine failures. One of these failure modes is known as engine rollback: an uncommanded decrease in thrust accompanied by a decrease in fan speed and an increase in turbine temperature. This paper describes the development of a model which simulates the system level impact of engine icing using the Commercial Modular Aero-Propulsion System Simulation 40k (C-MAPSS40k). When an ice blockage is added to C-MAPSS40k, the control system responds in a manner similar to that of an actual engine, and, in cases with severe blockage, an engine rollback is observed. Using this capability to simulate engine rollback, a proof-of-concept detection scheme is developed and tested using only typical engine sensors.

In this work, a newly developed iced-aircraft modeling tool is applied to wings, engine inlets, and helicopter rotors. The tool is based on a multiscale-physics, unstructured finite-volume CFD approach and is applicable to general purpose aircraft icing applications. The present approach combines an Eulerian-based droplet-trajectory solver that is loosely coupled, in a time-accurate manner, to a surface-film and ice-evolution model. The goal of the model is to improve the fidelity of ice accretion modeling on dynamic geometries and for three-dimensional ice shapes typical of helicopter rotors. The numerical formulation is discussed and presented alongside 2D and 3D static validation cases, and dynamic helicopter rotors. The present results display good validation for predicting ice shape on a variety of geometries, and a strong initial capability of modeling ice forming on helicopters in forward flight.

The paper will present experimental results from two recent icing tests in the NASA Glenn Icing Research Tunnel (IRT). The first test, conducted in February 2009, was to evaluate the current recommended scaling methods for fixed wing on representative rotor airfoils at fixed angle of attack. For this test, scaling was based on the modified Ruff method with scale velocity determined by constant Weber number and water film Weber number. Models were un-swept NACA 0012 wing sections. The reference model had a chord of 91.4 cm and scale model had a chord of 35.6 cm. Reference tests were conducted with velocity of 100 kt (52 m/s), droplet medium volume diameter (MVD) 195 μm, and stagnation-point freezing fractions of 0.3 and 0.5 at angle of attack of 5° and 7°. It was shown that good ice shape scaling was achieved with constant Weber number for NACA 0012 airfoils with angle of attack up to 7°.

Aircraft icing remains a significant threat to aviation safety. Software that predicts the impingement and ice accretion on full aircraft geometries and aircraft components are in demand and NASA Glenn is committed to produce software that meets this need. One of the key parameters affecting an accurate prediction of iced geometry is the effect of ice roughness on the heat transfer coefficient. While many efforts have been made to implement the roughness in the flow solver, this report takes a correlation for roughness height distribution that is based on experimental measurements and demonstrates how to relate those measurements to an augmentation to the heat transfer coefficient provided by the flow solution. The outcome of this effort was the callibration of defaults for user supplied parameters to this correlation through comparison with 95 large glaze conditions from experiment by adjusting user-supplied parameters in the roughness augmentation equation.

In early 2015, a field campaign was conducted at the NASA Glenn Research Center in Cleveland, Ohio, USA. The purpose of the campaign is to test several prototype algorithms meant to detect the location and severity of in-flight icing (or icing aloft, as opposed to ground icing) within the terminal airspace. Terminal airspace for this project is currently defined as within 25 kilometers horizontal distance of the terminal, which in this instance is Hopkins International Airport in Cleveland. Two new and improved algorithms that utilize ground-based remote sensing instrumentation have been developed and were operated during the field campaign. The first is the ‘NASA Icing Remote Sensing System’, or NIRSS. The second algorithm is the ‘Radar Icing Algorithm’, or RadIA.

The formation of ice over lifting surfaces can affect aerodynamic performance. In the case of helicopters, this loss in lift and the increase in sectional drag forces will have a dramatic effect on vehicle performance. The ability to predict ice accumulation and the resulting degradation in rotor performance is essential to determine the limitations of rotorcraft in icing encounters. The consequences of underestimating performance degradation can be serious and so it is important to produce accurate predictions, particularly for severe icing conditions. The simulation of rotorcraft ice accretion is a challenging multidisciplinary problem that until recently has lagged in development over its counterparts in the fixed wing community. But now, several approaches for the robust coupling of a computational fluid dynamics code, a rotorcraft structural dynamics code and an ice accretion code have been demonstrated.

Hybrid electric aircraft propulsion is an emerging technology that presents a variety of potential benefits along with technical integration challenges. Developing these new propulsion architectures with their complex control systems, and ultimately proving their benefit, is a multistep process. This process includes concept development and analysis, dynamic simulation, hardware-in-the-loop testing, full-scale testing, and so on. This effort is being revolutionized and indeed enabled by new digital tools that support increasing the technology readiness level throughout the maturation process. As part of this Digital Transformation, NASA has developed a suite of publicly available digital tools that facilitate the path from concept to implementation. This paper describes the NASA-developed tools and puts them in the context of control system development for hybrid electric aircraft propulsion.