Multirow Adjoint-Based Optimization of NICFD Turbomachinery Using a Computer-Aided Design-Based Parametrization

Abstract

The aerodynamic design of turbomachinery components is increasingly carried out by means of automated workflows that integrate high-fidelity physical models with numerical optimization techniques. Currently, most of the adjoint-based design systems documented in the open literature assume that the fluid behaves as an ideal gas, are restricted to the optimization of a single row of blades, or are not suited to impose geometric constraints. In response to these limitations, this paper presents a gradient-based shape optimization framework for the aerodynamic design of turbomachinery blades operating under non-ideal thermodynamic conditions. The proposed design system supports the optimization of multiple blade rows and it integrates a CAD-based parametrization with a RANS flow solver and its discrete adjoint counterpart. The capabilities of the method were demonstrated by performing the design optimization of a single-stage axial turbine that employs isobutane (R600a) as working fluid. Notably, the aerodynamic optimization respected the minimum thickness constraint at the trailing edge of the stator and rotor blades and reduced the entropy generation within the turbine by 36\%, relative to the baseline, which corresponds to a total-to-total isentropic efficiency increase of about 4 percentage points. The analysis of the flow field revealed that the performance improvement was achieved due to the reduction of the wake intensity downstream of the blades and the elimination of a shock-induced separation bubble at the suction side of the stator cascade.

A review on aerodynamic optimization of turbomachinery using adjoint method

“…In addition to the blade thickness and structural constraints (maximum von Mises stress value), new constraints to the adjoint FFD optimization should be added. A discrete adjoint-based optimization framework could be extended for multi-stage turbomachinery and NICFD application 237 to handle 3D problems. The coupled pressure-based adjoint solver 179 should be improved to reduce runtime and memory consumption.…”

“…A discrete adjoint-based optimization framework could be extended for multi-stage turbomachinery and NICFD application 237 to handle 3D problems.…”

“…Apart from the benefits of Vitale et al's 188 extended discrete adjoint solver for NICFD, it is difficult to impose constraints due to the use of FFD boxes for parameterization. To overcome this limitation, Agromayor et al 237 improved a discrete adjoint-based optimization framework for multi-stage turbomachinery by incorporating a new CAD-based parametrization for NICFD application. 234 FFD methods have recently been employed in turbomachinery optimization using the adjoint method.…”