Experimental and Numerical Study of Laminar-Turbulent Transition on a Low-Pressure Turbine Outlet Guide Vane

This work presents an experimental and numerical investigation on the laminar-turbulent transition and secondary flow structures in a Turbine Rear Structure (TRS). The study was executed at engine representative Reynolds number and inlet conditions at three different turbine load cases. Experiments were performed in an annular rotating rig with a shrouded low-pressure turbine upstream of a TRS test section. The numerical results were obtained using the SST k–ω turbulence model and the Langtry- Menter γ–θ transition model. The boundary layer transition location at the entire vane suction side is investigated. The location of the onset and the transition length are measured using IR thermography along the entire vane span. The IR-thermography approach was validated using hot-wire boundary layer measurements. Both experiments and CFD show large variations of transition location along the vane span with strong influences from endwalls and turbine outlet conditions. Both correlate well with traditional transition onset correlations near midspan and show that the transition onset Reynolds number is independent of the acceleration parameter. However, CFD tends to predict an early transition onset in the midspan vane region and a late transition in the hub region. Furthermore, in the hub region, CFD is shown to overpredict the transverse flow and related losses.

Low-order modeling for transition prediction applicable to wind-turbine rotors

This work aims at developing a low-order framework to predict the onset of transition over wind-turbine blades without requiring three-dimensional simulations. The effects of three-dimensionality and rotation on the transition location are also analyzed. The framework consists of a model to approximate the base-flow and another to predict the transition location. The former is based on the quasi-three-dimensional Euler and boundary-layer equations and only requires the pressure distribution over an airfoil to provide an approximation for the base-flow over the blade. The latter is based on the envelope of N factors method, where this quantity is computed using the parabolized stability equations (PSE) considering rotational effects. It is shown that rotation accelerates the flow towards the tip of the blade in the fully developed flow region and towards the opposite direction close to the stagnation point. The database method embedded in the EllipSys3D RANS code indicates overly premature transition locations, matching those obtained with a PSE analysis of a two-dimensional base-flow. The consideration of the spanwise velocity, as carried out in the developed model, has a stabilizing effect, delaying transition. Conversely, rotation plays a destabilizing role, hastening the transition onset. Moreover, airfoils with lower pressure gradients are more susceptible to its effects. The increase in the rotation speed makes transition occur through increasingly oblique disturbances from the middle to the tip of the blade, whereas the opposite happens for lower radial positions. Tollmien-Schlichting (TS) waves seem to trigger transition. However, highly oblique critical modes that may be intermediates between TS and crossflow ones occur for low radii. The developed framework allows transition prediction with reasonable accuracy using chordwise cp distributions as input, such as those provided by XFOIL.

Experimental and Numerical Study of Laminar-Turbulent Transition on a Low-Pressure Turbine Outlet Guide Vane

This work presents an experimental and numerical investigation on the laminar-turbulent transition and secondary flow structures in a Turbine Rear Structure (TRS). The study was executed at engine representative Reynolds number and inlet conditions at three different turbine load cases. Experiments were performed in an annular rotating rig with a shrouded low-pressure turbine upstream of a TRS test section. The numerical results were obtained using the SST k–ω turbulence model and the Langtry-Menter γ–θ transition model. The boundary layer transition location at the entire vane suction side is investigated. The location of the onset and the transition length are measured using IR-thermography along the entire vane span. The IR-thermography approach was validated using hot-wire boundary layer measurements. Both experiments and CFD show large variations of transition location along the vane span with strong influences from endwalls and turbine outlet conditions. Both correlate well with traditional transition onset correlations near midspan and show that the transition onset Reynolds number is independent of the acceleration parameter. However, CFD tends to predict an early transition onset in the midspan vane region and a late transition in the hub region. Furthermore, in the hub region, CFD is shown to overpredict the transverse flow and related losses.

A penetration model for semi-infinite ultra-high molecular weight polyethylene composite

Ultra-high molecular weight polyethylene (UHMW-PE) composite has been shown to be an effective material for ballistic protection against blunt penetrators [1]. The material exhibits multiple stages of penetration, typically characterised by an initial local penetration phase followed by large bulge deformation of the back face [2]. The location at which transition occurs between the localised penetration stage and non-localised bulging stage is an important property of UHMW-PE composite armour. However, the conditions required to induce transition are poorly understood with a range of different mechanisms proposed to explain the behaviour [2,3], none of which can be used to predict the transition location within the target.

The Hard Problems Are Almost Everywhere For Random CNF-XOR Formulas

Recent universal-hashing based approaches to sampling and counting crucially depend on the runtime performance of SAT solvers on formulas expressed as the conjunction of both CNF constraints and variable-width XOR constraints (known as CNF-XOR formulas). In this paper, we present the first study of the runtime behavior of SAT solvers equipped with XOR-reasoning techniques on random CNF-XOR formulas. We empirically demonstrate that a state-of-the-art SAT solver scales exponentially on random CNF-XOR formulas across a wide range of XOR-clause densities, peaking around the empirical phase-transition location. On the theoretical front, we prove that the solution space of a random CNF-XOR formula 'shatters' at all nonzero XOR-clause densities into well-separated components, similar to the behavior seen in random CNF formulas known to be difficult for many SAT algorithms.

Implementation of a Surface Roughness-Based Transition Onset Correction in the γ-Rθt~ Transition Model

This paper presents an extension of the γ-Rθt~ transition model of Menter et al. (2006) that aims to take into account the effect of a specific type of surface roughness on the transition location. This was done by implementing the roughness transition onset correction of Stripf et al. (2009) inside the γ-Rθt~ model. Stripf et al. have developed a correlation that takes into account the height and spacing of distributed roughness elements to correct the transition Reynolds number predicted over a smooth surface. As the transition Reynolds number takes multiple forms in the γ-Rθt~ model, different implementations of the Stripf et al. correction were tested and are discussed here. We find that it is best to correct the value of the critical Reynolds number Rθc. Computation results on a rough, low-pressure turbine vane are presented and compared to experimental results of the Karlsruhe Institute of Technology. We find that there is a good agreement on the transition location between the computations and experiments. In particular, the model displays accurate sensitivity to the roughness height, though the influence of the roughness spacing, which is of second order in these experiments, is not as well captured. We therefore conclude that the roughness transition onset correction of Stripf et al. is well suited for use in the γ-Rθt~ model.