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| Content Provider | The American Society of Mechanical Engineers (ASME) Digital Collection |
|---|---|
| Author | Cassinelli, Andrea Montomoli, Francesco Adami, Paolo Spencer, J. Sherwin |
| Copyright Year | 2018 |
| Abstract | The high order spectral/hp element methods implemented in the software framework Nektar++ are investigated for scale-resolving simulations of LPT profiles. There is a growing demand for high fidelity methods for turbomachinery to move towards numerical “experiments”. The study contributes at building best practices for the use of emerging high fidelity spectral element methods in turbomachinery predictions, with focus on the numerical details that are specific of these classes of methods. For this reason, the T106A cascade is used as a base reference application because of availability of data from previous investigations. The effects of polynomial order (p-refinement), spanwise domain extent and spanwise Fourier planes are considered, looking at flow statistics, convergence and sensitivity of the results. The performance of the high order spectral/hp element method is also assessed through validation against experimental data at moderately high Reynolds number. Thanks to the reduced computational cost, the proposed methods will have a strong impact in turbomachinery, paving the way to its use for design purposes and also allowing for a deeper understanding of the flow physics. |
| Sponsorship | International Gas Turbine Institute |
| File Format | |
| ISBN | 9780791851012 |
| DOI | 10.1115/GT2018-75733 |
| Volume Number | Volume 2C: Turbomachinery |
| Conference Proceedings | ASME Turbo Expo 2018: Turbomachinery Technical Conference and Exposition |
| Language | English |
| Publisher Date | 2018-06-11 |
| Publisher Place | Oslo, Norway |
| Access Restriction | Subscribed |
| Subject Keyword | Design Simulation Cascades (fluid dynamics) Computer software Reynolds number Turbomachinery Statistics as topic Polynomials Engineering simulation Flow (dynamics) Physics |
| Content Type | Text |
| Resource Type | Article |
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