Handbook of Turbomachinery Second Edition Revised - Ventech!

elevant optimization techniques for turbomachinery design applications is
given. The main focus of discussion is the use of MDO procedures for
component design applications associated with gas turbine engines. The
design of turbine blade geometry for improved heat-transfer performance is
used to demonstrate one particular multidisciplinary, multiobjective
optimization technique. Particular emphasis has been placed on the bladecooling
(internal and external) aspect of the design.
Development of formal optimization techniques for engineering design
applications has reached a high level today [6, 7]. Most of the optimization
techniques developed for engineering applications are typically capable of
addressing only a single design objective at a time subject to several
constraints, which restricts the applicability of the procedure [8] since such
problems usually involve multiple design objectives. A common practice in
addressing multiobjective optimization problems has been to combine
individual objective functions in a linear fashion using weight factors [9] that
are user-specified, thus requiring input based on user intuition and/or prior
experience. Another common method, called the modified global criterion
approach [8], combines the individual objective functions into a single
composite function using separately determined target values for the
objective functions. Optimization of the composite function corresponds
to optimizing the individual objective functions. This requires that separate
optimization be performed for each objective function in order to obtain the
target values, which could be computationally prohibitive for complex
designs. Several efforts for developing multidisciplinary, multiobjective
design optimization procedures have been initiated during the past few
years. One such procedure is the Kreisselmeier–Steinhauser (K–S) function
technique [10, 11], which is capable of addressing design problems with
multiple objectives and inequality constraints. The multiobjective optimization
formulation used in the design optimization problem described in the
present chapter is based on the K–S function technique [12–17], and a brief
description of this approach is given later.
A popular design optimization technique used in aerospace applications,
especially in gas turbine design, is the inverse design method in which
the required performance characteristics, such as a pressure distribution or
velocity distribution about the turbine blade, are prescribed and the
geometric parameters are modified iteratively to arrive at a configuration
that satisfies the prescribed criteria. An extensive review of inverse design
methodologies for aerodynamic shape design has been presented by
Dulikravich [18]. Such a procedure for the design of blade coolant passages
with specified temperatures and heat fluxes has been developed by
Dulikravich et al. [19, 20]. An iterative procedure for three-dimensional
blade design using a transpiration model along with a modified Euler solver
Copyright © 2003 Marcel Dekker, Inc.