This thesis focuses on the effects of wave-induced motions on the airwake of a ship and on the operation of a helicopter in the airwake. While the topic is broad, efforts are concentrated on understanding fundamentals of the ship’s airwake structure at varying Reynolds (Re) numbers without motions, using available experimental data for validation of the computational fluid dynamics (CFD) methodology used, and on studying the effects of waves and motions on the airwake of a ship and a helicopter operating above a ship’s flight deck in full-scale. The static ONR Tumblehome (ONRT) ship geometry with a solid boundary representative of the free surface is simulated at three different Re numbers, 3.2x104, 1x106, and 1.3x108. Validation is performed against experimental measurements at model-scale Re=1x106. Full-scale simulations of the ONRT are carried out in head winds and regular waves approximately equivalent to conditions seen at sea states 3 and 6. Effects of waves and motions are isolated for both sea states using simulations with combinations of waves and motions, waves and no motions, no waves with motions, and no motions or waves. A triple velocity decomposition is conducted in order to quantify changes in the airwake due to motions and waves. The operation of rotorcraft in the ONRT airwake is analyzed using one-way and two-way coupling approaches. The one-way coupling approach uses the velocity field data from the full-scale ONRT simulations and disk actuator theory to calculate thrust fluctuations for three different rotor sizes. The results of the one-way coupling approach show that the smallest rotor is much more affected by small scale turbulence, while small scale fluctuations are filtered out by larger rotor diameters. In the two-way coupling approach, a helicopter based on the Sikorsky SH-60 hovering above the flight deck is simulated, including explicitly moving grids to discretize the main rotor, tail rotor, and fuselage. This method captures the effects of the interaction between the rotor downwash and the ONRT airwake. The study shows that for the mild conditions of sea state 3 the motions have little effect on the airwake behavior. At sea state 6 the airwake behavior is significantly altered, which is reflected in the resulting forces on the helicopter body operating in this condition.

Helicopter operations in the vicinity of small naval surface vessels often require excessive pilot workload. Because of the unsteady flow field and large mean velocity gradients, the envelope for flight operations is limited. This experimental investigation uses a 1:144 scale model of the U.S. Navy destroyer DDG-81 to explore the problem. Both active and passive flow control techniques were used to improve the flow field in the helicopter's final decent onto the flight deck. Wind tunnel data was collected at a set of grid points over the ship's flight deck using a single component hotwire. Results show that the use of porous surfaces decreases the unsteadiness of the flow field. Further improvements are found by injecting air through these porous surfaces, causing a reduction in unsteadiness in the landing region of 6.6% at 0 degrees wind-over-deck (WOD) and 8.3% at 20 degrees WOD. Other passive configurations tested include fences placed around the hangar deck edges which move the unsteady shear layer away from the flight deck. Although these devices cause an increase in unsteadiness downstream of the edge of the fence when compared to the baseline, the reticulated foam fence caused an overall decrease in unsteadiness in the landing region of 12.1% at 20 degrees WOD. / Master of Science

This dissertation explores the applicability of RC helicopters as a tool to map wind conditions. This dissertation presents the construction of a robust instrumentation system capable of wireless in-situ measurement and mapping of ship airwake. The presented instrumentation system utilizes an RC helicopter as a carrier platform and uses the helicopter's dynamics for spatial 3D mapping of wind turbulence. The system was tested with a YP676 naval training craft to map ship airwake generated in controlled heading wind conditions. Novel system modeling techniques were developed to estimate the dynamics of an instrumented RC helicopter, in conjunction with onboard sensing, to estimate spatially varying (local) wind conditions. The primary problem addressed in this dissertation is the reliable estimation and separation of pilot induced dynamics from the system measurements, followed by the use of the dynamics residuals/discrepancies to map the wind conditions. This dissertation presents two different modelling approaches to quantify ship airwake using helicopter dynamics. The helicopter systems were characterized using both machine learning and analytical aerodynamic modelling approaches. In the machine learning based approaches, neural networks, along with other models, were trained then assessed in their capability to model dynamics from pilot inputs and other measured helicopter states. The dynamics arising from the wind conditions were fused with the positioning estimates of the helicopter to generate ship airwake maps which were compared against CFD generated airwake patterns. In the analytical modelling based approach, the dynamic response of an RC helicopter to a spatially varying parameterized wind field was modeled using a 30-state nonlinear ordinary differential equation-based dynamic system, while capturing essential elements of the helicopter dynamics. The airwake patterns obtained from both types of approach were compared against anemometrically produced wind maps of turbulent wind conditions artificially generated in a controlled indoor environment. Novel hardware architecture was developed to acquire data critical for the operation and calibration of the proposed system. The mechatronics design of three prototypes of the proposed system were presented and performance evaluated using experimental testing with a modified YP676 naval training vessel in the Chesapeake Bay area. In closing, qualitative analysis of these systems along with potential applications and improvements are discussed to conclude this dissertation. / Ph. D. / Ship airwake is a trail of wind turbulence left behind the superstructure of cruising naval vessels and are considered as a serious safety concern for aviators during onboard operations. Prior knowledge of the airwake distribution around the ship can alert pilots of possible hazards ahead of time and mitigate operational risks during the launch and recovery of the aircraft on the flight deck. This dissertation presents a novel application of Remote Control (RC) helicopters as tools to measure and map ship airwake. This dissertation presents two approaches to extract wind conditions from helicopter dynamics: (1) using machine learning based modeling, and (2) using analytic aerodynamic modeling-based estimation. Machine Learning is a modern engineering tool to model and simulate any system using experimental data alone. Under the machine learning based approach, the helicopter’s response to pilot inputs was modeled using multiple algorithms, with experimental flight data collected the absence of the ship airwake. With an assumption of capturing all the aerodynamic effects with the machine learning algorithms, the deviations in the dynamics estimates during testing environment were used to characterize and map ship airwake. In contrast to the machine learning model, the analytical approach modeled all critical aerodynamic processes of the RC helicopter as functions of pilot inputs and wind conditions using well defined physics laws, thus eliminating any need for training data. This approach predicts wind conditions on the basis of the model’s capability to match the estimates of helicopter dynamics to the actual measurements. Both presented approaches were tested on wind conditions created in indoor and outdoor environments. The performance of the proposed system was evaluated in experimental testing with a modified YP676 naval training vessel in the Chesapeake Bay area. The dissertation also presents the mechatronic design details of the novel hardware prototypes and subsystems used in the various studies and experiments. Finally, qualitative analysis of these systems along with their potential applications and improvements are discussed to conclude this dissertation.