Computational fluid dynamics methods have seen an increasing role in aerodynamic analysis since their first implementation. However, there are several major limitations is these methods of analysis, especially in the area of modeling separated flow. There exists a large demand for high-fidelity experimental data for turbulence modeling validation. Virginia Tech has joined NASA in a cooperative project to design and perform an experiment in the Virginia Tech Stability Wind Tunnel with the purpose of providing a benchmark set of data for the turbulence modeling community for the flow over a three-dimensional bump. This process requires thorough risk mitigation and analysis of potential flow sensitivities. The current study investigates several aspects of the experimental design through the use of several computational fluid dynamics codes. An emphasis is given to boundary condition matching and uncertainty quantification, as well as sensitivities of the flow features to Reynolds number and inflow conditions. Solutions are computed for two different RANS turbulence models, using two different finite-volume CFD codes. Boundary layer inflow parameters are studied as well as pressure and skin friction distribution on the bump surface. The shape and extent of separation are compared for the various solutions. Pressure distributions are compared to available experimental data for two different Reynolds numbers. / Master of Science / Computational fluid dynamics (CFD) methods have seen an increasing role in engineering analysis since their first implementation. However, there are several major limitations is these methods of analysis, especially in the area of modeling of several common aerodynamic phenomena such as flow separation. This motivates the need for high fidelity experimental data to be used for validating computational models. This study is meant to support the design of an experiment being cooperatively developed by NASA and Virginia Tech to provide validation data for turbulence modeling. Computational tools can be used in the experimental design process to mitigate potential experimental risks, investigate flow sensitivities, and inform decisions about instrumentation. Here, we will use CFD solutions to identify risks associated with the current experimental design and investigate their sensitivity to incoming flow conditions and Reynolds number. Numerical error estimation and uncertainty quantification is performed. A method for matching experimental inflow conditions is proposed, validated, and implemented. CFD data is also compared to experimental data. Comparisons are also made between different models and solvers.

Computational fluid dynamics (CFD) methods and schemes have been evolving at a rate that significantly outpaces the equipment needed to readily utilize them at scale. This lack of computational resources has resulted in an increased reliance on turbulence models and the need to know where turbulence models do well, where they do poorly, and where/how they can be improved upon. The BeVERLI Hill experiments aim to address this issue by providing experimental data that achieves a completeness level of three, which has never been done for this type of project. The experimental data collected is studied along side computational results from CFD solvers in order to help address and answer these questions. This paper provides an overview of the current computational status of the BeVERLI Hill project at Virginia Tech. The computational grids used for the analyses are presented such that the reader can gain an appreciation for the modeling techniques and methods being implemented. An analysis of the numerical error associated with the computational results is presented to provide confidence in the results obtained. An in-depth analysis will be presented that shows the results for the various grid levels that are being utilized to determine any grid based effects that are occurring within the solutions. Then, an analysis of the influence of the Reynolds numbers being run is shown. An investigation into the differences between the two different solvers being utilized, SENSEI and Fluent, is shown. An analysis of the effects on the solutions due to numerical limiters is presented to assist in increasing the computational efficiency of the workflow while not adversely affecting the results. Finally, an analysis of the differences between the two turbulence models being utilized is presented. Computational results are compared to available experimentally obtained data to further motivate and identify flow features. / Master of Science / An analysis has been done with high-fidelity computational fluid dynamic solvers that are utilized in order to solve for the flow over a three-dimensional bump called BeVERLI. An analysis is provided that discusses the use of different computational meshes, solvers, turbulence models, and numerical limiters within the computational tools to characterize the flow over the bump. An analysis of the estimated amount of numerical error within the solutions is provided along with a comparison to experimentally obtained data.

Viscous drag reduction plays a vital role in increasing the performance of vehicles. However, there are only so many measurement techniques that can quickly and accurately measure this when compared to pressure drag measurement techniques. The current study makes use of one of the direct and robust measurement techniques that exist, called the Oil Film Interferometry (OFI) to estimate skin friction on the NASA/Virginia Tech BeVERLI (Benchmark Validation Experiment for RANS and LES Investigations) hill. This project aims to develop a detailed database of non-equilibrium, separated turbulent boundary layer flows obtained through wind tunnel experiments for CFD validation. Skin friction measurements are obtained at specific critical locations on the hill and in its close proximity. The challenges involved in obtaining skin friction data from these locations are discussed in detail. Detailed discussions on the experimental setup and data processing methodology are presented. Qualitative and quantitative results from each measurement location are discussed along with uncertainties to explain certain key flow physics. Additionally, skin friction coefficients from selected overlapping measurement locations from another experimental flow measurement technique called Laser Doppler Velocimetry (LDV) are compared with OFI, and a cross-instrument study is performed. Finally, results from well-refined RANS CFD simulations are assessed with the experimental results, and critical improvement areas are identified. / Master of Science / Drag force is a parameter that significantly contributes to the performance efficiency of any vehicle moving in a fluid. This force is categorised into two types - pressure and viscous drag- both of which need to be minimised as much as possible to contribute towards higher vehicle performance. While there are numerous measurement techniques and documentation currently available to measure pressure drag, this is not the case with the measurement of viscous drag. Skin friction measurement directly relates to the estimation of viscous drag, but accurate and quick measurement of this quantity highly challenging with countable measurement techniques currently available. Through this project, BeVERLI (Benchmark Validation Experiment for RANS and LES Investigations), a detailed documentation is developed for accurate measurement of skin friction through Oil Film Interferometry (OFI). The results obtained through this measurement is explained with a detailed experimental procedure as well as using a data processing code. The accuracy of these results are then discussed with the results from another flow measurement technique called Laser Doppler Velocimetry (LDV) and from Computational Fluid Dynamics (CFD).