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Title: Unsteady inlet condition generation for Large Eddy Simulation CFD using particle image velocimetry
Author: Robinson, Mark D.
ISNI:       0000 0004 2684 0518
Awarding Body: Loughborough University
Current Institution: Loughborough University
Date of Award: 2009
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In many areas of aerodynamics the technique of Large Eddy Simulation (LES) has proved a practical way of modelling the unsteady phenomena in numerical simulations. Few applications are as dependent on such an approach as the prediction of flow within a gas turbine combustor. Like any form of Computational Fluid Dynamics (CFD), LES requires specification of the velocity field at the inflow boundary, with much evidence suggesting the specification of inlet turbulence can be critical to the resultant accuracy of the prediction. While a database of time-resolved velocity data may be obtained from a precursor LES calculation, this technique is prohibitively expensive for complex geometries. An alternative is to use synthetic inlet conditions obtained from experimental data High-speed Particle Image Velocimetry (PIV) is used here to provide planar velocity data at up to 1kHz temporal resolution in two test cases representative of gas turbine combustor flows (a vortex generator in a duct and an idealised combustor). As the data sampling rate is approaching a typical LES time-step it introduces the possibility of applying instantaneous experimental data directly as an inlet condition. However, as typical solution domain inlet regions for gas turbine combustor geometries cannot be adequately captured in a single field of PIV data, it is necessary to consider a method by which a synchronous velocity field may be obtained from multiple PIV fields that were not captured concurrently. A method is proposed that attempts to achieve this by a combined process of Linear Stochastic Estimation and high-pass filtering. The method developed can be generally applied without a priori assumptions of the flow and is demonstrated to produce a velocity field that matches very closely that of the original PIV, with no discontinuities in the velocity correlations. The fidelity and computational cost of the method compares favourably to several existing inlet condition generation methods. Finally, the proposed and existing methods for synthetic inlet condition generation are applied to LES predictions of the two test cases. There is shown to be significant differences in the resulting flow, with the proposed method showing a marked ii reduction in the adjustment period that is required to establish turbulent equilibrium downstream of the inlet. However, it is noted the presence of downstream turbulence generating features can mask any differences in the inlet condition, to the extent that the flow in the core of the combustor test case is found to be insensitive to the inlet condition applied at the entry to the feed annulus for the test conditions applied here.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Particle image velocimetry ; Large Eddy Simulation ; Gas turbine combustors ; Inlet conditions ; Linear stochastic estimation ; Proper orthogonal decomposition