Volume 7C: Structures and Dynamics 2018
DOI: 10.1115/gt2018-75502
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The Validation of Flutter Prediction in a Linear Cascade of Non-Rigid Turbine Blades

Abstract: In low-pressure steam turbines, aerodynamic and structural design of the last stage blades is critical in determining the power plant efficiency. The development of longer last stage blades which are recently over 1 meter in length is an important task for steam turbine manufactures. The design process involves a flutter analysis of last stage blade tip sections where increased unsteady aerodynamic forces and moments might endanger the blade aerodynamic stability. However, numerical design tools must be valida… Show more

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Cited by 6 publications
(9 citation statements)
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“…Each moving coil has its feedback control system in order to set a precise blade motion. Further details about the experimental setup are described in [7].…”
Section: Test Rig Description and Measured Data Acquisitionmentioning
confidence: 99%
See 3 more Smart Citations
“…Each moving coil has its feedback control system in order to set a precise blade motion. Further details about the experimental setup are described in [7].…”
Section: Test Rig Description and Measured Data Acquisitionmentioning
confidence: 99%
“…The total time duration of unsteady simulations was specified using the total number of periods per run. It was investigated that 6 periods per run were sufficient enough to calculate the required aerodynamic work [7,12]. To quantify convergence criteria of steadystate simulations, the residual values were used where the RMS (root mean square) residual type was chosen and 1 • 10 −5 residual target value was defined.…”
Section: Ansys Cfx Numerical Analysismentioning
confidence: 99%
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“…As a result, such models exhibit deficits in predicting the production and dissipation rates of turbulent kinetic energy under cyclic strain [2]. Likewise, the prediction of more turbomachinery-specific flows, i.e., in vibrating cascades, as well as the resulting prediction of aero-elastic quantities, using unsteady RANS (URANS) or time-linearised RANS exhibits non-negligible discrepancies from experimental validation data, e.g., Refs [3][4][5].…”
Section: Introductionmentioning
confidence: 99%