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Browsing by Subject "Turbulence modeling"

Now showing 1 - 3 of 3
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    Large Eddy simulation of high Reynolds number complex flows
    (2012-09) Verma, Aman
    Marine configurations are subject to a variety of complex hydrodynamic phenomena affecting the overall performance of the vessel. The turbulent flow affects the hydrodynamic drag, propulsor performance and structural integrity, control-surface effectiveness, and acoustic signature of the marine vessel. Due to advances in massively parallel computers and numerical techniques, an unsteady numerical simulation methodology such as Large Eddy Simulation (LES) is well suited to study such complex turbulent flows whose Reynolds numbers (Re) are typically on the order of 10^6. LES also promises increased accuracy over RANS based methods in predicting unsteady phenomena such as cavitation and noise production. This dissertation develops the capability to enable LES of high Re flows in complex geometries (e.g. a marine vessel) on unstructured grids and provide physical insight into the turbulent flow. LES is performed to investigate the geometry induced separated flow past a marine propeller attached to a hull, in an off-design condition called crashback. LES shows good quantitative agreement with experiments and provides a physical mechanism to explain the increase in side-force on the propeller blades below an advance ratio of J=-0.7. Fundamental developments in the dynamic subgrid-scale model for LES are pursued to improve the LES predictions, especially for complex flows on unstructured grids. A dynamic procedure is proposed to estimate a Lagrangian time scale based on a surrogate correlation without any adjustable parameter. The proposed model is applied to turbulent channel, cylinder and marine propeller flows and predicts improved results over other model variants due to a physically consistent Lagrangian time scale. A wall model is proposed for application to LES of high Reynolds number wall-bounded flows. The wall model is formulated as the minimization of a generalized constraint in the dynamic model for LES and applied to LES of turbulent channel flow at various Reynolds numbers upto Re_tau=10000 and coarse grid resolutions to obtain significant improvement.
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    Low-complexity stochastic modeling of wall-bounded shear flows
    (2016-12) Zare, Armin
    Turbulent flows are ubiquitous in nature and they appear in many engineering applications. Transition to turbulence, in general, increases skin-friction drag in air/water vehicles compromising their fuel-efficiency and reduces the efficiency and longevity of wind turbines. While traditional flow control techniques combine physical intuition with costly experiments, their effectiveness can be significantly enhanced by control design based on low-complexity models and optimization. In this dissertation, we develop a theoretical and computational framework for the low-complexity stochastic modeling of wall-bounded shear flows. Part I of the dissertation is devoted to the development of a modeling framework which incorporates data-driven techniques to refine physics-based models. We consider the problem of completing partially known sample statistics in a way that is consistent with underlying stochastically driven linear dynamics. Neither the statistics nor the dynamics are precisely known. Thus, our objective is to reconcile the two in a parsimonious manner. To this end, we formulate optimization problems to identify the dynamics and directionality of input excitation in order to explain and complete available covariance data. For problem sizes that general-purpose solvers cannot handle, we develop customized optimization algorithms based on alternating direction methods. The solution to the optimization problem provides information about critical directions that have maximal effect in bringing model and statistics in agreement. In Part II, we employ our modeling framework to account for statistical signatures of turbulent channel flow using low-complexity stochastic dynamical models. We demonstrate that white-in-time stochastic forcing is not sufficient to explain turbulent flow statistics and develop models for colored-in-time forcing of the linearized Navier-Stokes equations. We also examine the efficacy of stochastically forced linearized NS equations and their parabolized equivalents in the receptivity analysis of velocity fluctuations to external sources of excitation as well as capturing the effect of the slowly-varying base flow on streamwise streaks and Tollmien-Schlichting waves. In Part III, we develop a model-based approach to design surface actuation of turbulent channel flow in the form of streamwise traveling waves. This approach is capable of identifying the drag reducing trends of traveling waves in a simulation-free manner. We also use the stochastically forced linearized NS equations to examine the Reynolds number independent effects of spanwise wall oscillations on drag reduction in turbulent channel flows. This allows us to extend the predictive capability of our simulation-free approach to high Reynolds numbers.
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    A New Realistic Approach To Convective Heat Transfer Modeling And Simulation In The Presence Of Swirling Flows
    (2017-12) Ilamparuthi, Santosh
    The thesis deals with internal fluid flows with heat transfer where swirl is a dominant component. The modeling of these flows is important due to their wide prevalence in industrial processes. The use of appropriate turbulence models for swirling flows and verification is performed in the chapter 2. Chapters 3 and 4 deals with applications with swirling flows. This includes the cooling and thermal management of a PCR machine and studying the thermal and flow behavior of fluid flows in large pipes under directly ducted fan flows. Fluid flow was visualized with both normalized and non-normalized vector plots while temperature contour plots and turbulence ratio contour plots were utilized to delineate the various thermal and fluid flow regimes which were encountered. The simulations were all carried out in ANSYS – CFX predominantly using versions 14 through 16. The results demonstrated the need for further adoption of the SST turbulence model especially in flows where swirl was a significant factor.