565 resultados para Aerodynamics, Transonic


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© 2014 by ASME. This paper, the second of two parts, presents a new setup for the two-stage two-spool facility located at the Institute for Thermal Turbomachinery and Machine Dynamics (ITTM) of Graz University of Technology. The rig was designed to reproduce the flow behavior of a transonic turbine followed by a counter-rotating low pressure stage such as those in high bypass aero-engines. The meridional flow path of the machine is characterized by a diffusing S-shaped duct between the two rotors. The role of wide chord vanes placed into the mid turbine frame is to lead the flow towards the low pressure (LP) rotor with appropriate swirl. Experimental and numerical investigations performed on this setup showed that the wide chord struts induce large wakes and extended secondary flows at the LP inlet flow. Moreover, large deterministic fluctuations of pressure, which may cause noise and blade vibrations, were observed downstream of the LP rotor. In order to minimize secondary vortices and to damp the unsteady interactions, the mid turbine frame was redesigned to locate two zero-lift splitters into each vane passage. While in the first part of the paper the design process of the splitters and the time-averaged flow field were presented, in this second part the measurements performed by means of a fast response probe will support the explanation of the time-resolved field. The discussion will focus on the comparison between the baseline case (without splitters) and the embedded design.

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© 2014 by ASME. The paper presents a new setup for the two-stage two-spool facility located at the Institute for Thermal Turbomachinery and Machine Dynamics (ITTM) of Graz University of Technology. The rig was designed in order to simulate the flow behavior of a transonic turbine followed by a counter-rotating low pressure (LP) stage like the spools of a modern high bypass aeroengine. The meridional flow path of the machine is characterized by a diffusing S-shaped duct between the two rotors. The role of turning struts placed into the mid turbine frame is to lead the flow towards the LP rotor with appropriate swirl. Experimental and numerical investigations performed on the setup over the last years, which were used as baseline for this paper, showed that wide chord vanes induce large wakes and extended secondary flows at the LP rotor inlet flow. Moreover, unsteady interactions between the two turbines were observed downstream of the LP rotor. In order to increase the uniformity and to decrease the unsteady content of the flow at the inlet of the LP rotor, the mid turbine frame was redesigned with two zero-lifting splitters embedded into the strut passage. In this first part of the paper the design process of the splitters and its critical points are presented, while the time-averaged field is discussed by means of five-hole probe measurements and oil flow visualizations. The comparison between the baseline case and the embedded design configuration shows that the new design is able to reduce the flow gradients downstream of the turning struts, providing a more suitable inlet condition for the low pressure rotor. The improvement in the flow field uniformity is also observed downstream of the turbine and it is, consequently, reflected in an enhancement of the LP turbine performance. In the second part of this paper the influence of the embedded design on the time-resolved field is investigated.

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The classical Purcell's vector method, for the construction of solutions to dense systems of linear equations is extended to a flexible orthogonalisation procedure. Some properties are revealed of the orthogonalisation procedure in relation to the classical Gauss-Jordan elimination with or without pivoting. Additional properties that are not shared by the classical Gauss-Jordan elimination are exploited. Further properties related to distributed computing are discussed with applications to panel element equations in subsonic compressible aerodynamics. Using an orthogonalisation procedure within panel methods enables a functional decomposition of the sequential panel methods and leads to a two-level parallelism.

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Computational modelling of dynamic fluid–structure interaction (DFSI) is a considerable challenge. Our approach to this class of problems involves the use of a single software framework for all the phenomena involved, employing finite volume methods on unstructured meshes in three dimensions. This method enables time and space accurate calculations in a consistent manner. One key application of DFSI simulation is the analysis of the onset of flutter in aircraft wings, where the work of Yates et al. [Measured and Calculated Subsonic and Transonic Flutter Characteristics of a 45° degree Sweptback Wing Planform in Air and Freon-12 in the Langley Transonic Dynamic Tunnel. NASA Technical Note D-1616, 1963] on the AGARD 445.6 wing planform still provides the most comprehensive benchmark data available. This paper presents the results of a significant effort to model the onset of flutter for the AGARD 445.6 wing planform geometry. A series of key issues needs to be addressed for this computational approach. • The advantage of using a single mesh, in order to eliminate numerical problems when applying boundary conditions at the fluid-structure interface, is counteracted by the challenge of generating a suitably high quality mesh in both the fluid and structural domains. • The computational effort for this DFSI procedure, in terms of run time and memory requirements, is very significant. Practical simulations require even finer meshes and shorter time steps, requiring parallel implementation for operation on large, high performance parallel systems. • The consistency and completeness of the AGARD data in the public domain is inadequate for use in the validation of DFSI codes when predicting the onset of flutter.

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A two dimensional staggered unstructured discretisation scheme for the solution of fluid flow problems has been developed. This scheme stores and solves the velocity vector resolutes normal and parallel to each cell face and other scalar variables (pressure, temperature) are stored at cell centres. The coupled momentum; continuity and energy equations are solved, using the well known pressure correction algorithm SIMPLE. The method is tested for accuracy and convergence behaviour against standard cell-centre solutions in a number of benchmark problems: The Lid-Driven Cavity, Natural Convection in a Cavity and the Melting of Gallium in a rectangular domain.