Characterizing the Separation and Reattachment of Suction Surface Boundary Layer in Low Pressure Turbine Using Massively Parallel Large Eddy Simulations

The separation and reattachment of the suction surface boundary layer in a low pressure turbine is characterized using large-eddy simulation at Re=68,000 based on freestream velocity and suction surface length. A high pass filtered Smagorinsky model is used for modeling the sub-grid scales. The onset of time mean separation is at s=so = 0:61 and reattachment at s=so = 0:81, extending over 20% of the suction surface. The boundary layer is convectively unstable with a maximum reverse flow velocity of about 13% of freestream. The breakdown to turbulence occurs over a very short distance of suction surface which is followed by reattachment. Detailed investigations into the structure and kinematics of the bubble and turbulence statistics are presented. The vortex shed from the bubble, convects downstream and interacts with the trailing edge vortices increasing the turbulence intensity. On the suction side, dominant hairpin structures near the transitional and turbulent flow regime are observed. These hairpin vortices are carried by the freestream even downstream of the trailing edge of the blade with a possibility of reaching the next stage. Longitudinal streaks that evolve from the breakdown of hairpin vortices formed near the leading edge are observed on the pressure surface

On the Relation between Small-scale Intermittency and Shocks in Turbulent Flows

AbstractHigh Reynolds number turbulence is characterized by extreme fluctuations of velocity gradients which can interact with shock waves in compressible flows. While these processes are traditionally thought to happen at very disparate range of scales, both turbulence gradients as well as shock gradients become stronger as the Reynolds number increases. Our interest here is to in- vestigate their relation in the high-Reynolds number limit. Our conclusion is that for intermittent turbulence with inertial range scaling exponents which grow more slowly than linear at asymptotically high orders, small-scale intermittency produces gradients which are commensurate with shocks. This result is interpreted in the context of shock-turbulence interactions where intermittency appears to be responsible, in part, for the holes observed in shocks from simulations and experiments. This effect is aided by the correlation between strong gradients and flow retardation ahead of the shock which is observed from analysis of our direct numerical simulation database of incompressible and compressible turbulence

Reynolds and Mach Number Scaling in Stationary Compressible Turbulence Using Massively Parallel High Resolution Direct Numerical Simulations

Turbulence is the most common state of fluid motion in both natural and engineering systems. Many real world applications depend on our ability to predict and control turbulent processes. Due to the presence of both hydrodynamic and thermodynamic fluctuations, simulations of compressible flows are more expensive than incompressible flows. A highly scalable code is presented which is used to perform direct numerical simulations (DNS) aimed at understanding fundamental turbulent processes. The code is parallelized using both distributed and shared memory paradigms and is shown to scale well up to 264144 cores. The code is used to generate a large database of stationary compressible turbulence at world-record resolutions and a range of Reynolds and Mach numbers, and different forcing schemes to investigate the effect of compressibility on classical scaling relations, to study the role of thermodynamic fluctuations and energy exchanges between the internal and kinetic modes of energy, and to investigate the plausibility of a universal behavior in compressible flows. We find that pressure has a qualitatively different behavior at low and high levels of compressibility. The observed change in the likelihood of positive or negative fluctuations of pressure impacts the direction of energy transfer between internal and kinetic energy. We generalize scaling relations to different production mechanisms, and discover a plausible universal behavior for compressible flows, which could provide a path to successful modeling of turbulence in compressible flows. Our results, unprecedented in size, accuracy and range of parameters will be helpful in addressing a number of additional open issues in turbulence research