Browsing by Subject "Turbulence modeling"
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Item A Dynamical Systems Approach Towards Modeling the Rapid Pressure Strain Correlation(2011-08-08) Mishra, Aashwin A.In this study, the behavior of pressure in the Rapid Distortion Limit, along with its concomitant modeling, are addressed. In the first part of the work, the role of pressure in the initiation, propagation and suppression of flow instabilities for quadratic flows is analyzed. The paradigm of analysis considers the Reynolds stress transport equations to govern the evolution of a dynamical system, in a state space composed of the Reynolds stress tensor components. This dynamical system is scrutinized via the identification of the invariant sets and the bifurcation analysis. The changing role of pressure in quadratic flows, viz. hyperbolic, shear and elliptic, is established mathematically and the underlying physics is explained. Along the maxim of "understanding before prediction", this allows for a deeper insight into the behavior of pressure, thus aiding in its modeling. The second part of this work deals with Rapid Pressure Strain Correlation modeling in earnest. Based on the comprehension developed in the preceding section, the classical pressure strain correlation modeling approaches are revisited. Their shortcomings, along with their successes, are articulated and explained, mathematically and from the viewpoint of the governing physics. Some of the salient issues addressed include, but are not limited to, the requisite nature of the model, viz. a linear or a nonlinear structure, the success of the extant models for hyperbolic flows, their inability to capture elliptic flows and the use of RDT simulations to validate models. Through this analysis, the schism between mathematical and physical guidelines and the engineering approach, at present, is substantiated. Subsequently, a model is developed that adheres to the classical modeling framework and shows excellent agreement with the RDT simulations. The performance of this model is compared to that of other nominations prevalent in engineering simulations. The work concludes with a summary, pertinent observations and recommendations for future research in the germane field.Item The influence of thunderstorm downbursts on wind turbine design(2012-08) Nguyen, Hieu Huy, 1980-; Manuel, LanceThe International Electrotechnical Commission (IEC) standard 61400-1 for the design of wind turbines does not explicitly address site-specific conditions associated with anomalous atmospheric events or conditions. Examples of such off-standard atmospheric conditions include thunderstorm downbursts, hurricanes, tornadoes, low-level jets, etc. This study is focused on the simulation of thunderstorm downbursts using a deterministic-stochastic hybrid model and the prediction of wind turbine loads resulting from these simulated downburst wind fields. The wind velocity field model for thunderstorm downburst simulation is first discussed; in this model, downburst winds are generated separately from non-turbulent and turbulent parts. The non-turbulent part is based on an available analytical model (with some modifications), while the turbulent part is simulated as a stochastic process using standard turbulence power spectral density functions and coherence functions. Tower and rotor loads are generated using simulation of the aeroelastic response for models of utility-scale wind turbines. The main objective is to improve our understanding from the point of view of design so that we may begin to address transient events such as thunderstorm downbursts based on the simulations carried out in this research study. The study discusses as well the role of control systems (for blade pitch and turbine yaw), of models for representing transient turbulence characteristics, and of correlated demand and loads on multiple units in turbine arrays during thunderstorm downbursts.Item Large eddy simulation analysis of non-reacting sprays inside a high-g combustor(2012-08) Martinez, Jaime, master of science in engineering; Raman, Venkat; Clemens, Noel TInter-turbine burners are useful devices for increasing engine power. To reduce the size of these combustion devices, ultra-compact combustor (UCC) concepts are necessary. One such UCC concept is the centrifugal-force based high-g combustor design. Here, a model ultra-compact combustor (UCC) with fuel spray injection is simulated using large eddy simulation (LES) and Reynolds-Averaged Navier-Stokes (RANS) methodologies to understand mixing and spray dispersion inside centrifugal-based combustion systems. Both non-evaporating and evaporating droplet simulations were carried, as well as the tracking of a passive scalar, to explore this multiphase system. Simulation results show that mixing of fuel and oxidizer is based on a jet-in-crossflow system, with the fuel jet issuing into a circulating oxidizer flow stream. It is seen that a a high velocity vortex-like ring develops in the inner core of the combustor, which has enough momentum to obstruct the path of combustion products. There is minimal fuel droplet and vapor segregation inside the combustor and enhanced turbulent mixing is seen at mid-radius.Item Modeling turbulence using optimal large eddy simulation(2012-05) Chang, Henry, 1976-; Moser, Robert deLancey; Engquist, Bjorn; Ghattas, Omar; Hughes, Thomas J.; Raman, VenkatMost flows in nature and engineering are turbulent, and many are wall-bounded. Further, in turbulent flows, the turbulence generally has a large impact on the behavior of the flow. It is therefore important to be able to predict the effects of turbulence in such flows. The Navier-Stokes equations are known to be an excellent model of the turbulence phenomenon. In simple geometries and low Reynolds numbers, very accurate numerical solutions of the Navier-Stokes equations (direct numerical simulation, or DNS) have been used to study the details of turbulent flows. However, DNS of high Reynolds number turbulent flows in complex geometries is impractical because of the escalation of computational cost with Reynolds number, due to the increasing range of spatial and temporal scales. In Large Eddy Simulation (LES), only the large-scale turbulence is simulated, while the effects of the small scales are modeled (subgrid models). LES therefore reduces computational expense, allowing flows of higher Reynolds number and more complexity to be simulated. However, this is at the cost of the subgrid modeling problem. The goal of the current research is then to develop new subgrid models consistent with the statistical properties of turbulence. The modeling approach pursued here is that of "Optimal LES". Optimal LES is a framework for constructing models with minimum error relative to an ideal LES model. The multi-point statistics used as input to the optimal LES procedure can be gathered from DNS of the same flow. However, for an optimal LES to be truly predictive, we must free ourselves from dependence on existing DNS data. We have done this by obtaining the required statistics from theoretical models which we have developed. We derived a theoretical model for the three-point third-order velocity correlation for homogeneous, isotropic turbulence in the inertial range. This model is shown be a good representation of DNS data, and it is used to construct optimal quadratic subgrid models for LES of forced isotropic turbulence with results which agree well with theory and DNS. The model can also be filtered to determine the filtered two-point third-order correlation, which describes energy transfer among filtered (large) scales in LES. LES of wall-bounded flows with unresolved wall layers commonly exhibit good prediction of mean velocities and significant over-prediction of streamwise component energies in the near-wall region. We developed improved models for the nonlinear term in the filtered Navier-Stokes equation which result in better predicted streamwise component energies. These models involve (1) Reynolds decomposition of the nonlinear term and (2) evaluation of the pressure term, which removes the divergent part of the nonlinear models. These considerations significantly improved the performance of our optimal models, and we expect them to apply to other subgrid models as well.