Advances of Turbomachinery Design Optimization

The aviation industry is under significant commercial and environmental pressure to produce a revolution in design. However, despite the significant advances in automatic design optimization made over the last 30 years, the industry is still largely conducting design by evolution. The complexity of a modern aeroengine encourages the separation of its conceptual from its detailed design: this limits the utility of powerful design optimization tools solving the “classical” optimization problem (of design space search for the global optimum) to the detailed designer who is more usually tasked with reaching a specification. One of the principal difficulties of modifying the design to reach a particular specified goal is that, though the desired improvement might be achieved, it often comes at unacceptable detriment to other performance indicators. We present results of our orthogonal design technique (that assists the designer in producing improvements in specific attributes of the design without penalty in other aspects) applied to the redesign of a generic core engine compressor for two “real-world” design problems: reducing the part count without aerodynamic penalty and increasing the efficiency without reduction in surge margin, pressure rise or mass flow. The two resulting designs, while meeting their constraints, exhibit a reduction in blading equivalent to two rotor rows and an increase in adiabatic efficiency of 1.0 percentage point respectively. The design changes which produce these improvements, together with how these compare with design rationale, are discussed.

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Turbomachinery Design Optimization Using Automatic Differentiated Adjoint Code

Volume 6: Turbo Expo 2007, Parts A and B ◽

10.1115/gt2007-28329 ◽

2007 ◽

Cited By ~ 8

Author(s):

Mihai C. Duta ◽

Shahrokh Shahpar ◽

Michael B. Giles

Keyword(s):

Design Optimization ◽

Adjoint Method ◽

Automatic Differentiation ◽

Nonlinear Flow ◽

Flow Solver ◽

Current State ◽

Discrete Adjoint ◽

Gradient Based ◽

Turbomachinery Design ◽

Objective Functional

The last decade has established the adjoint method as an effective way in Computational Fluid Dynamics of calculating the gradients of an objective functional in a large dimensional design space. This paper addresses the concerns that code developers face when creating a discrete adjoint computer program for design optimization, starting from a nonlinear flow solver and using Automatic Differentiation. Adjoint code development benefits greatly from using Automatic Differentiation but at its current state of maturity, this technology is best applied selectively rather than on entire codes. The paper discusses the practical aspects of using Automatic Differentiation on a large industrial turbomachinery flow solver with the objective of deriving efficient adjoint code. The use of the adjoint gradients is illustrated in an optimization exercise using gradient based methods on the NASA Rotor 37 public testcase.

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On Noise Control in Turbomachinery Using an Automated Multidisciplinary Design Optimization System

Noise Control and Acoustics ◽

10.1115/imece2005-81789 ◽

2005 ◽

Cited By ~ 1

Author(s):

Uyigue Idahosa ◽

Vladimir Golubev

Keyword(s):

Design Optimization ◽

High Speed ◽

High Efficiency ◽

Optimization Procedure ◽

General Aviation ◽

Response Analysis ◽

Efficiency Performance ◽

Gradient Based ◽

Geometry Parameterization ◽

Turbomachinery Design

In this work, we review our recent efforts to develop and apply an expanding database of aerodynamic and aeroacoustic prediction technologies for exploring new conceptual designs of propulsion system turbomachinery components optimized for high-efficiency performance with minimum noise radiation. In this context, we first discuss construction of our automated, distributed, industry-like multi-disciplinary design optimization (MDO) environment used in all the studies. The system was developed on the basis of commercially available optimization modules, and involves a user-friendly interface that provides an easy link to user-supplied response analysis modules. We address various issues in the automated optimization procedure with focus on turbomachinery design, including proper geometry parameterization, algorithms selection, and transparent interconnections between different elements of the optimization process. In a benchmark study testing the performance of the system in application to aero/acoustic optimization, we consider a problem of optimal blade design to minimize fan noise, a dominant source of sound radiation both in high-speed fan applications (such as high-bypass-ratio turbofans, propellers of turboprop and IC engines in general aviation, and helicopter rotors) and low-speed ones (including applications in automotive, computer, air-conditioning and other industries). Two approaches are investigated, with the first relying on commercial CFD software coupled with an unstructured mesh generator, and the second employing a panel-based aerodynamic code integrated with an integral acoustic solver. Success of various optimization algorithms (including gradient-based and evolutionary) in finding global minima of the objective function for a noise metric in both unconstrained and constrained optimization processes is examined.

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