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.

Stress Inversion Using LiDAR Tunnel Deformation Measurements

Far-field stresses are those present in a volume of rock prior to excavations being created. Estimates of the orientation and magnitude of far-field stresses, often used in mine design, are generally obtained by single-point measurements of stress, or large-scale, regional trends. Point measurements can be a poor representation of far-field stresses as a result of excavation-induced stresses and geological structures. For these reasons, far-field stress estimates can be associated with high levels of uncertainty. The purpose of this thesis is to investigate the practical feasibility, applications, and limitations of calibrating far-field stress estimates through tunnel deformation measurements captured using LiDAR imaging. A method that estimates the orientation and magnitude of excavation-induced principal stress changes through back-analysis of deformation measurements from LiDAR imaged tunnels was developed and tested using synthetic data. If excavation-induced stress change orientations and magnitudes can be accurately estimated, they can be used in the calibration of far-field stress input to numerical models. LiDAR point clouds have been proven to have a number of underground applications, thus it is desired to explore their use in numerical model calibration. The back-analysis method is founded on the superposition of stresses and requires a two-dimensional numerical model of the deforming tunnel. Principal stress changes of known orientation and magnitude are applied to the model to create calibration curves. Estimation can then be performed by minimizing squared differences between the measured tunnel and sets of calibration curve deformations. In addition to the back-analysis estimation method, a procedure consisting of previously existing techniques to measure tunnel deformation using LiDAR imaging was documented. Under ideal conditions, the back-analysis method estimated principal stress change orientations within ±5° and magnitudes within ±2 MPa. Results were comparable for four different tunnel profile shapes. Preliminary testing using plastic deformation, a rough tunnel profile, and profile occlusions suggests that the method can work under more realistic conditions. The results from this thesis set the groundwork for the continued development of a new, inexpensive, and efficient far-field stress estimate calibration method.