A highly important aspect of safe sea-based helicopter operation is the establishment of ship-helicopter operational limits for current and future helicopter/ship combinations. The capabilities of Computational Fluid Dynamics for the determination of ship airwakes have been investigated, aiming at complementing existing experimental data acquisition techniques consisting of wind tunnel and on-board full-scale measurements. In this paper, computed airwakes based on the Reynolds-averaged Navier-Stokes (RANS) equations as well as on a hybrid RANS-Large Eddy Simulation (LES) approach are compared with experimental data. The resulting airwakes have been converted for usage in a helicopter flight simulator to enable additional feed-back on the reality level of the computational approaches from experienced pilots. It is shown that, from a practical point of view, a useful first impression of the average flow characteristics in the ship airwake can be obtained from steady RANS flow modeling, although the more computationally intensive hybrid RANS-LES approach has an inherently better potential for capturing all of the physical content of the fluctuating flow fields. Nomenclature C v = ratio of local velocity to free-stream velocity, defined as (u 2 + v 2 + w 2 ) 0.5 h = characteristic mesh cell size k = turbulent kinetic energy L = reference length of the ship t = physical time t * = non-dimensional time, in CTS units u = velocity component in x-direction, scaled with U U = reference velocity of the free-stream flow v = velocity component in y-direction, scaled with U w = velocity component in z-direction, scaled with U x, y, z = orthogonal Cartesian coordinate directions β = sideslip angle of reference flow vector β local = local sideslip angle Δt = time step Δt * = non-dimensional time step = vertical deviation of local flow vector from the horizontal plane χ = horizontal deviation of local flow vector from the oncoming flow direction, β local -β ω = specific turbulent dissipation rate CFD = Computational Fluid Dynamics CFL = Courant-Friedrichs-Lewy number, stability criterion for numerical integration CTS = Convective Time Scale, defined as L/U, average time required for a fluid particle to pass the ship

Real-time simulation of gas turbine engine performance is used in a variety of aerospace applications. For simulation of propulsion system performance in flight-simulators, fidelity requirements become increasingly stringent. Significant improvements in simulation fidelity can be obtained when using thermodynamic models instead of the customary (piece-wise) linear real-time models. However, real-time thermodynamic models require sophisticated methods to efficiently solve the model equations on a real-time basis with sufficient speed. NLR has developed the ‘Turbine Engine Real-Time Simulator’ (TERTS) generic real-time engine simulation environment for full thermodynamic simulation of various gas turbine engine configurations. At NLR’s National Simulator Facility (NSF), research is performed on pilot-in-the-loop simulation of complex aircraft and helicopter configurations such as thrust-vectoring and Integrated Flight Propulsion Control (IFPC) concepts. For this application, high-fidelity real-time gas turbine models are required. TERTS has an efficient method for solving the engine model equations real-time. The system is implemented in Matlab-Simulink®, which offers advantages in terms of control system modeling flexibility. With TERTS, detailed thermodynamic real-time engine models can easily be implemented in NSF providing an excellent means to analyze a variety of engine effects on pilot-in-the-loop aircraft performance. In this paper the TERTS modeling environment will be described including the numerical solutions used to comply with the real-time requirements. A TERTS model of a military afterburning turbofan will be presented including simulation results.

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