Abstract

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.

Highlights

  • Designing and optimizing a turbine vane is a complex iterative design process that can take significant time and effort

  • This paper presents an single point optimization of the LS89 axial turbine cascade vane profile for the design downstream isentropic Mach number of 0.9

  • The parameterization is done at the computer-aided design (CAD) level, which allows the imposition of higher level constraints on the shape, such as the axial chord length, the trailing edge radius and G2 geometric continuity between the suction side and pressure side at the leading edge

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Summary

Introduction

Designing and optimizing a turbine vane is a complex iterative design process that can take significant time and effort. One of the limitations of using the CAD in a gradient-based optimization framework is the computation of the grid sensitivities i.e., the partial derivative of the grid points with respect to the design parameters. These sensitivities can be approximated by finite differences using the design velocity approach [7], which is robust against the possible changes in boundary topology of the model. The in-house CAD and grid generation tools are automatically differentiated in forward mode to obtain the exact derivatives of the grid coordinates with respect to the CAD-based design parameters This allows for an accurate prediction of the sensitivities and circumvention of the errors introduced by finite differences. A computer aided design and optimization tool for turbomachinery applications (CADO) [13] is used throughout this study

Computer-Aided Design-Based Parametrization
Optimization
Grid Generation
Flow and Adjoint Solvers
Gradient Computation
Results
Zweifel Loading Coefficient
Boundary Layer Parameters
Base Pressure
Profile Losses
Off-Design Performance
Findings
Conclusions
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