Optimization Of The Ls89 Axial Turbine Profile Using A Cad And Adjoint Based Approach
| Autor: | Lasse Mueller, Ismael Sanchez Torreguitart, Tom Verstraete |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Leading edge
Computer science Automatic differentiation lcsh:Mechanical engineering and machinery Energy Engineering and Power Technology Aerospace Engineering 02 engineering and technology Computational fluid dynamics base pressure profile losses algorithmic differentiation adjoint optimization 01 natural sciences 010305 fluids & plasmas Physics::Fluid Dynamics symbols.namesake 020401 chemical engineering Control theory 0103 physical sciences Trailing edge lcsh:TJ1-1570 0101 mathematics 0204 chemical engineering business.industry Turbulence Mechanical Engineering Aerodynamics Solver 010101 applied mathematics Mach number symbols business |
| Zdroj: | International Journal of Turbomachinery, Propulsion and Power Volume 3 Issue 3 International Journal of Turbomachinery, Propulsion and Power, Vol 3, Iss 3, p 20 (2018) |
| ISSN: | 2410-4833 |
| DOI: | 10.29008/etc2017-087 |
| Popis: | The LS89 high pressure axial turbine vane was originally designed and optimized for a downstream isentropic Mach number of 0.9. This profile has been widely used for computational fluid dynamics (CFD) validation in the open literature but very few attempts have been made to improve the already optimized design. This paper presents a sound methodology to design and optimize the LS89 using computer-aided design (CAD) at design conditions. The novelty of the study resides in the parametrization of design space, which is done at the CAD level, and the detailed analysis of the aerodynamic performance of the optimized design. Higher level constraints are imposed on the shape, such as the trailing edge thickness, the axial chord length, and G2 geometric continuity between the suction side and pressure side at the leading edge. The gradients used for the optimization are obtained by applying algorithmic differentiation to the CAD kernel and grid generator and the discrete adjoint method to the CFD solver. A reduction of almost 12% entropy generation is achieved, which is equivalent to a 16% total pressure loss reduction. The entropy generation is reduced while keeping the exit flow angle as a flow constraint, which is enforced via the penalty formulation. The resulting unconstrained optimization problem is solved by the L-BFGS-B algorithm. The flow is governed by the Reynolds-averaged Navier-Stokes equations and the one-equation transport Spalart-Allmaras turbulence model. The optimal profile is compared and benchmarked against the baseline case. |
| Databáze: | OpenAIRE |
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