Experimental and RANS-CFD Study of Nacelle Drag

The drag on a nacelle model was investigated experimentally and computationally to provide guidance and insight into the capabilities of RANS-based CFD. The research goal was to determine whether industry constrained CFD could participate in the aerodynamic design of nacelle bodies. Grid refinement level, turbulence model and near wall treatment settings, to predict drag to the highest accuracy, were key deliverables. Cold flow low-speed wind tunnel experiments were conducted at a Reynolds number of 6∙〖10〗^5, 293 K and a Mach number of 0.1. Total drag force was measured by a six-component force balance. Detailed wake analysis, using a seven-hole pressure probe traverse, allowed for drag decomposition via the far-field method. Drag decomposition was performed through a range of angles of attack between 0o and 45o. Both methods agreed on total drag within their respective uncertainties. Reversed flow at the measurement plane and saturation of the load cell caused discrepancies at high angles of attack. A parallel CFD study was conducted using commercial software, ICEM 15.0 and FLUENT 15.0. Simulating a similar nacelle geometry operating under inlet boundary conditions obtained through wind tunnel characterization allowed for direct comparisons with experiment. It was determined that the Realizable k-ϵ was best suited for drag prediction of this geometry. This model predicted the axial momentum loss and secondary flow in the wake, as well as the integrated surface forces, within experimental error up to 20o angle of attack. SST k-ω required additional surface grid resolution on the nacelle suction side, resulting in 15% more elements, due to separation point prediction sensitivity. It was further recommended to apply enhanced wall treatment to more accurately capture the viscous drag and separated flow structures. Overall, total drag was predicted within 5% at 0o angle of attack and 10% at 20o, each within experimental uncertainty. What is more, the form and induced drag predicted by CFD and measured by the wake traverse shared good agreement. Which indicated CFD captured the key flow features accurately despite simplification of the nacelle interior geometry.

Vibrational Feedback Training System for Use with SEMG Controlled Powered Prostheses

Loss of limb results in loss of function and a partial loss of freedom. A powered prosthetic device can partially assist an individual with everyday tasks and therefore return some level of independence. Powered upper limb prostheses are often controlled by the user generating surface electromyographic (SEMG) signals. The goal of this thesis is to develop a virtual environment in which a user can control a virtual hand to safely grasp representations of everyday objects using EMG signals from his/her forearm muscles, and experience visual and vibrotactile feedback relevant to the grasping force in the process. This can then be used to train potential wearers of real EMG controlled prostheses, with or without vibrotactile feedback. To test this system an experiment was designed and executed involving ten subjects, twelve objects, and three feedback conditions. The tested feedback conditions were visual, vibrotactile, and both visual and vibrotactile. In each experimental exercise the subject attempted to grasp a virtual object on the screen using the virtual hand controlled by EMG electrodes placed on his/her forearm. Two metrics were used: score, and time to task completion, where score measured grasp dexterity. It was hypothesized that with the introduction of vibrotactile feedback, dexterity, and therefore score, would improve and time to task completion would decrease. Results showed that time to task completion increased, and score did not improve with vibrotactile feedback. Details on the developed system, the experiment, and the results are presented in this thesis.