Influence of the state of the inlet endwall boundary layer on the interaction between pressure surface separation and endwall flows

This paper describes the effect of the state of the inlet boundary layer (laminar or turbulent) on the structure of the endwall flow on two different profiles of low-pressure (LP) turbine blades (solid thin and hollow thick). At present the state of the endwall boundary layer at the inlet of a real LP turbine is not known. The intention of this paper is to show that, for different designs of LP turbine, the state of the inlet boundary layer affects the performance of the blade in very different ways. The testing was completed at low speed in a linear cascade using area traversing, flow visualization and static pressure measurements. The paper shows that, for a laminar inlet boundary layer, the two profiles have a similar loss distribution and structure of endwall flow. However, for a turbulent inlet boundary layer the two profiles are shown to differ significantly in both the total loss and endwall flow structure. The pressure side separation bubble on the solid thin profile is shown to interact with the passage vortex, causing a higher endwall loss than that measured on the hollow thick profile.

On the relationship between hidden Markov Models and convex functional transforms for simulating scanning probe Microscopy

Models for simulating Scanning Probe Microscopy (SPM) may serve as a reference point for validating experimental data and practice. Generally, simulations use a microscopic model of the sample-probe interaction based on a first-principles approach, or a geometric model of macroscopic distortions due to the probe geometry. Examples of the latter include use of neural networks, the Legendre Transform, and dilation/erosion transforms from mathematical morphology. Dilation and the Legendre Transform fall within a general family of functional transforms, which distort a function by imposing a convex solution.In earlier work, the authors proposed a generalized approach to modeling SPM using a hidden Markov model, wherein both the sample-probe interaction and probe geometry may be taken into account. We present a discussion of the hidden Markov model and its relationship to these convex functional transforms for simulating and restoring SPM images.©2009 SPIE.