Abstract. In this paper, we investigate the role of flow structures generated in wind farm control through yaw misalignment. A pair of counter-rotating vortices is shown to be important in deforming the shape of the wake and in explaining the asymmetry of wake steering in oppositely signed yaw angles. We also demonstrate that vortices generated by an upstream turbine that is performing wake steering can deflect wakes of downstream turbines, even if they are themselves aligned.We encourage the development of improvements to control-oriented engineering models of wind farm control, to include the effects of these large-scale flow structures. Such a new model would improve the predictability of control-oriented models. Further, we demonstrate that the vortex structures created in wake steering can lead to greater impact on power generation than currently modeled in control-oriented models. We propose that wind farm controllers can be made more effective if designed to take advantage of these effects.

Olfaction begins when an animal draws odorant-laden air into its nasal cavity by sniffing, thus transporting odorant molecules from the external environment to olfactory receptor neurons (ORNs) in the sensory region of the nose. In the dog and other macrosmatic mammals, ORNs are relegated to a recess in the rear of the nasal cavity that is comprised of a labyrinth of scroll-like airways. Evidence from recent studies suggests that nasal airflow patterns enhance olfactory sensitivity by efficiently delivering odorant molecules to the olfactory recess. Here, we simulate odorant transport and deposition during steady inspiration in an anatomically correct reconstructed model of the canine nasal cavity. Our simulations show that highly soluble odorants are deposited in the front of the olfactory recess along the dorsal meatus and nasal septum, whereas moderately soluble and insoluble odorants are more uniformly deposited throughout the entire olfactory recess. These results demonstrate that odorant deposition patterns correspond with the anatomical organization of ORNs in the olfactory recess. Specifically, ORNs that are sensitive to a particular class of odorants are located in regions where that class of odorants is deposited. The correlation of odorant deposition patterns with the anatomical organization of ORNs may partially explain macrosmia in the dog and other keen-scented species.

The canine nasal cavity contains a complex airway labyrinth, dedicated to respiratory air conditioning, filtering of inspired contaminants, and olfaction. The small and contorted anatomical structure of the nasal turbinates has, to date, precluded a proper study of nasal airflow in the dog. This study describes the development of a high-fidelity computational fluid dynamics (CFD) model of the canine nasal airway from a three-dimensional reconstruction of high-resolution magnetic resonance imaging scans of the canine anatomy. Unstructured hexahedral grids are generated, with large grid sizes ((10-100) x 10(6) computational cells) required to capture the details of the nasal airways. High-fidelity CFD solutions of the nasal airflow for steady inspiration and expiration are computed over a range of physiological airflow rates. A rigorous grid refinement study is performed, which also illustrates a methodology for verification of CFD calculations on complex unstructured grids in tortuous airways. In general, the qualitative characteristics of the computed solutions for the different grid resolutions are fairly well preserved. However, quantitative results such as the overall pressure drop and even the regional distribution of airflow in the nasal cavity are moderately grid dependent. These quantities tend to converge monotonically with grid refinement. Lastly, transient computations of canine sniffing were carried out as part of a time-step study, demonstrating that high temporal accuracy is achievable using small time steps consisting of 160 steps per sniff period. Here we demonstrate that acceptable numerical accuracy (between approximately 1% and 15%) is achievable with practical levels of grid resolution (approximately 100 x 10(6) computational cells). Given the popularity of CFD as a tool for studying flow in the upper airways of humans and animals, based on this work we recommend the necessity of a grid dependence study and quantification of numerical error when presenting CFD results in complicated airways.

This paper describes the development of a computational fluid dynamics (CFD) methodology to simulate the hydrodynam ics of horizontal-axis tidal current turbines (HATTs). First, an HATT blade was designed using the blade element momentum method in conjunction with a genetic optimization algorithm. Several unstructured computational grids were generated using this blade geometry and steady CFD simulations were used to perform a grid resolution study. Transient simulations were then performed to determine the effect of time-dependent flow phe nomena and the size of the computational timestep on the numer ical solution. Qualitative measures of the CFD solutions were independent of the grid resolution. Conversely, quantitative com parisons of the results indicated that the use of coarse computa tional grids results in an under prediction of the hydrodynamic forces on the turbine blade in comparison to the forces predicted using more resolved grids. For the turbine operating conditions considered in this study, the effect of the computational timestep on the CFD solution was found to be minimal, and the results from steady and transient simulations were in good agreement. Additionally, the CFD results were compared to corresponding blade element momentum method calculations and reasonable agreement was shown. Nevertheless, we expect that for other turbine operating conditions, where the flow over the blade is separated, transient simulations will be required.

Wave energy converters (WECs) are commonly designed and analyzed using numerical models that combine multibody dynamics with hydrodynamic models based on the Cummins equation and linearized hydrodynamic coefficients. These modeling methods are attractive design tools because they are computationally inexpensive and do not require the use of highperformance computing resources necessitated by high-fidelity methods, such as Navier-Stokes computational fluid dynamics. Modeling hydrodynamics using linear coefficients assumes that the device undergoes small motions and that the wetted surface area of the devices is approximately constant. WEC devices, however, are typically designed to undergo large motions to maximize power extraction, calling into question the validity of assuming that linear hydrodynamic models accurately capture the relevant fluid-structure interactions.In this paper, we study how calculating buoyancy and Froude-Krylov forces from the instantaneous position of a WEC device changes WEC simulation results compared to simulations that use linear hydrodynamic coefficients. First, we describe the WEC-Sim tool used to perform simulations and how the ability to model instantaneous forces was incorporated into WEC-Sim. We then use a simplified one-body WEC device to validate the model and to demonstrate how accounting for these instantaneously calculated forces affects the accuracy of simulation results, such as device motions, hydrodynamic forces, and power generation.Other aspects of WEC-Sim code development and verification are presented in a companion paper [1] that is also being presented at OMAE2014. INTRODUCTIONWave energy is the most abundant source of marine hydrokinetic energy in the United States and is a plentiful resource around the globe [2]. Recent estimates indicate that the U.S. wave energy resource is 2,600 TWh/year [3]. If it is possible to extract even a small fraction of this energy, there is potential to satisfy a significant amount of U.S. electricity demand [4]. This finding has stimulated commercial and governmental interest in developing wave energy converter (WEC) technologies, and indicates that wave energy could play a significant role in the world's renewable energy portfolio for years to come. Nevertheless, WEC devices are at an early stage of development, corresponding to technology readiness levels (TRLs) 3 through 5, and are not yet a commercially viable technology.Over the past several decades, open-source numerical modeling tools have helped the wind turbine industry achieve commercial viability by enabling the rapid development, analysis, and certification of system designs. The recent emergence of the WEC industry has created a need for a similar set of WEC design and analysis tools that enable the advancement of WEC technologies. Several companies have developed WEC modeling tools, such as WaveDyn, OrcaFlex, and AQWA, that meet many of the needs of the WEC research and development community. Previous experience at the National Renewable Energy Laboratory (NR...