INVISCID BLADE-TO-BLADE PREDICTION OF A WAKE-GENERATED UNSTEADY FLOW.

A description is presented of a time-marking calculation of the unsteady flow generated by the interaction of upstream wakes with a moving blade row. The inviscid equations of motion are solved using a finite volume technique. Wake dissipation is modeled using an artificial viscosity. Predictions are presented for the rotor mid-span section of an axial turbine. Reasonable agreement is found between the predicted and measured unsteady blade surface static pressures and velocities. These and other results confirm that simple theories can be used to explain the phenomena of rotor-stator wake interactions.

Variance prediction in sea

A method is presented for predicting the variance of the energy levels in a built-up system to accompany the mean values predicted by SEA. Closed form expressions for the variance are obtained in terms of the standard SEA parameters and an additional set of parameters αk that describe the nature of the power input to each subsystem k, and αks that describe the nature of the coupling between subsystems k and s.

The prediction of hot streak migration in a high-pressure turbine

Accurate predictions of combustor hot streak migration enable the turbine designer to identify high-temperature regions that can limit component life. It is therefore important that these predictions are achieved within the short time scales of a design process. This article compares temperature measurements of a circular hot streak through a turning duct and a research turbine with predictions using a three-dimensional Reynolds-averaged Navier-Stokes solver. It was found that the mixing length turbulence model did not predict the hot streak dissipation accurately. However, implementation of a very simple model of the free stream turbulence (FST) significantly improved the exit temperature predictions on both the duct and research turbine. One advantage of the simple FST model described over more complex alternatives is that no additional equations are solved. This makes the method attractive for design purposes, as it is not associated with any increase in computational time.

Extraction of fibre network architecture by X-ray tomography and prediction of elastic properties using an affine analytical model

This paper proposes a method for extracting reliable architectural characteristics from complex porous structures using micro-computed tomography (μCT) images. The work focuses on a highly porous material composed of a network of fibres bonded together. The segmentation process, allowing separation of the fibres from the remainder of the image, is the most critical step in constructing an accurate representation of the network architecture. Segmentation methods, based on local and global thresholding, were investigated and evaluated by a quantitative comparison of the architectural parameters they yielded, such as the fibre orientation and segment length (sections between joints) distributions and the number of inter-fibre crossings. To improve segmentation accuracy, a deconvolution algorithm was proposed to restore the original images. The efficacy of the proposed method was verified by comparing μCT network architectural characteristics with those obtained using high resolution CT scans (nanoCT). The results indicate that this approach resolves the architecture of these complex networks and produces results approaching the quality of nanoCT scans. The extracted architectural parameters were used in conjunction with an affine analytical model to predict the axial and transverse stiffnesses of the fibre network. Transverse stiffness predictions were compared with experimentally measured values obtained by vibration testing. © 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.